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• What Is a Case-Control Study? | Definition & Examples

What Is a Case-Control Study? | Definition & Examples

Published on February 4, 2023 by Tegan George . Revised on June 22, 2023.

A case-control study is an experimental design that compares a group of participants possessing a condition of interest to a very similar group lacking that condition. Here, the participants possessing the attribute of study, such as a disease, are called the “case,” and those without it are the “control.”

It’s important to remember that the case group is chosen because they already possess the attribute of interest. The point of the control group is to facilitate investigation, e.g., studying whether the case group systematically exhibits that attribute more than the control group does.

Table of contents

When to use a case-control study, examples of case-control studies, advantages and disadvantages of case-control studies, other interesting articles, frequently asked questions.

Case-control studies are a type of observational study often used in fields like medical research, environmental health, or epidemiology. While most observational studies are qualitative in nature, case-control studies can also be quantitative , and they often are in healthcare settings. Case-control studies can be used for both exploratory and explanatory research , and they are a good choice for studying research topics like disease exposure and health outcomes.

A case-control study may be a good fit for your research if it meets the following criteria.

• Data on exposure (e.g., to a chemical or a pesticide) are difficult to obtain or expensive.
• The disease associated with the exposure you’re studying has a long incubation period or is rare or under-studied (e.g., AIDS in the early 1980s).
• The population you are studying is difficult to contact for follow-up questions (e.g., asylum seekers).

Retrospective cohort studies use existing secondary research data, such as medical records or databases, to identify a group of people with a common exposure or risk factor and to observe their outcomes over time. Case-control studies conduct primary research , comparing a group of participants possessing a condition of interest to a very similar group lacking that condition in real time.

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Case-control studies are common in fields like epidemiology, healthcare, and psychology.

You would then collect data on your participants’ exposure to contaminated drinking water, focusing on variables such as the source of said water and the duration of exposure, for both groups. You could then compare the two to determine if there is a relationship between drinking water contamination and the risk of developing a gastrointestinal illness. Example: Healthcare case-control study You are interested in the relationship between the dietary intake of a particular vitamin (e.g., vitamin D) and the risk of developing osteoporosis later in life. Here, the case group would be individuals who have been diagnosed with osteoporosis, while the control group would be individuals without osteoporosis.

You would then collect information on dietary intake of vitamin D for both the cases and controls and compare the two groups to determine if there is a relationship between vitamin D intake and the risk of developing osteoporosis. Example: Psychology case-control study You are studying the relationship between early-childhood stress and the likelihood of later developing post-traumatic stress disorder (PTSD). Here, the case group would be individuals who have been diagnosed with PTSD, while the control group would be individuals without PTSD.

Case-control studies are a solid research method choice, but they come with distinct advantages and disadvantages.

Advantages of case-control studies

• Case-control studies are a great choice if you have any ethical considerations about your participants that could preclude you from using a traditional experimental design .
• Case-control studies are time efficient and fairly inexpensive to conduct because they require fewer subjects than other research methods .
• If there were multiple exposures leading to a single outcome, case-control studies can incorporate that. As such, they truly shine when used to study rare outcomes or outbreaks of a particular disease .

Disadvantages of case-control studies

• Case-control studies, similarly to observational studies, run a high risk of research biases . They are particularly susceptible to observer bias , recall bias , and interviewer bias.
• In the case of very rare exposures of the outcome studied, attempting to conduct a case-control study can be very time consuming and inefficient .
• Case-control studies in general have low internal validity  and are not always credible.

Case-control studies by design focus on one singular outcome. This makes them very rigid and not generalizable , as no extrapolation can be made about other outcomes like risk recurrence or future exposure threat. This leads to less satisfying results than other methodological choices.

If you want to know more about statistics , methodology , or research bias , make sure to check out some of our other articles with explanations and examples.

• Student’s  t -distribution
• Normal distribution
• Null and Alternative Hypotheses
• Chi square tests
• Confidence interval
• Quartiles & Quantiles
• Cluster sampling
• Stratified sampling
• Data cleansing
• Reproducibility vs Replicability
• Peer review
• Prospective cohort study

Research bias

• Implicit bias
• Cognitive bias
• Placebo effect
• Hawthorne effect
• Hindsight bias
• Affect heuristic
• Social desirability bias

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A case-control study differs from a cohort study because cohort studies are more longitudinal in nature and do not necessarily require a control group .

While one may be added if the investigator so chooses, members of the cohort are primarily selected because of a shared characteristic among them. In particular, retrospective cohort studies are designed to follow a group of people with a common exposure or risk factor over time and observe their outcomes.

Case-control studies, in contrast, require both a case group and a control group, as suggested by their name, and usually are used to identify risk factors for a disease by comparing cases and controls.

A case-control study differs from a cross-sectional study because case-control studies are naturally retrospective in nature, looking backward in time to identify exposures that may have occurred before the development of the disease.

On the other hand, cross-sectional studies collect data on a population at a single point in time. The goal here is to describe the characteristics of the population, such as their age, gender identity, or health status, and understand the distribution and relationships of these characteristics.

Cases and controls are selected for a case-control study based on their inherent characteristics. Participants already possessing the condition of interest form the “case,” while those without form the “control.”

Keep in mind that by definition the case group is chosen because they already possess the attribute of interest. The point of the control group is to facilitate investigation, e.g., studying whether the case group systematically exhibits that attribute more than the control group does.

The strength of the association between an exposure and a disease in a case-control study can be measured using a few different statistical measures , such as odds ratios (ORs) and relative risk (RR).

No, case-control studies cannot establish causality as a standalone measure.

As observational studies , they can suggest associations between an exposure and a disease, but they cannot prove without a doubt that the exposure causes the disease. In particular, issues arising from timing, research biases like recall bias , and the selection of variables lead to low internal validity and the inability to determine causality.

Sources in this article

We strongly encourage students to use sources in their work. You can cite our article (APA Style) or take a deep dive into the articles below.

George, T. (2023, June 22). What Is a Case-Control Study? | Definition & Examples. Scribbr. Retrieved April 8, 2024, from https://www.scribbr.com/methodology/case-control-study/

Schlesselman, J. J. (1982). Case-Control Studies: Design, Conduct, Analysis (Monographs in Epidemiology and Biostatistics, 2) (Illustrated). Oxford University Press.

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Case-control and Cohort studies: A brief overview

Posted on 6th December 2017 by Saul Crandon

Introduction

Case-control and cohort studies are observational studies that lie near the middle of the hierarchy of evidence . These types of studies, along with randomised controlled trials, constitute analytical studies, whereas case reports and case series define descriptive studies (1). Although these studies are not ranked as highly as randomised controlled trials, they can provide strong evidence if designed appropriately.

Case-control studies

Case-control studies are retrospective. They clearly define two groups at the start: one with the outcome/disease and one without the outcome/disease. They look back to assess whether there is a statistically significant difference in the rates of exposure to a defined risk factor between the groups. See Figure 1 for a pictorial representation of a case-control study design. This can suggest associations between the risk factor and development of the disease in question, although no definitive causality can be drawn. The main outcome measure in case-control studies is odds ratio (OR) .

Figure 1. Case-control study design.

Cases should be selected based on objective inclusion and exclusion criteria from a reliable source such as a disease registry. An inherent issue with selecting cases is that a certain proportion of those with the disease would not have a formal diagnosis, may not present for medical care, may be misdiagnosed or may have died before getting a diagnosis. Regardless of how the cases are selected, they should be representative of the broader disease population that you are investigating to ensure generalisability.

Case-control studies should include two groups that are identical EXCEPT for their outcome / disease status.

As such, controls should also be selected carefully. It is possible to match controls to the cases selected on the basis of various factors (e.g. age, sex) to ensure these do not confound the study results. It may even increase statistical power and study precision by choosing up to three or four controls per case (2).

Case-controls can provide fast results and they are cheaper to perform than most other studies. The fact that the analysis is retrospective, allows rare diseases or diseases with long latency periods to be investigated. Furthermore, you can assess multiple exposures to get a better understanding of possible risk factors for the defined outcome / disease.

Nevertheless, as case-controls are retrospective, they are more prone to bias. One of the main examples is recall bias. Often case-control studies require the participants to self-report their exposure to a certain factor. Recall bias is the systematic difference in how the two groups may recall past events e.g. in a study investigating stillbirth, a mother who experienced this may recall the possible contributing factors a lot more vividly than a mother who had a healthy birth.

A summary of the pros and cons of case-control studies are provided in Table 1.

Table 1. Advantages and disadvantages of case-control studies.

Cohort studies

Cohort studies can be retrospective or prospective. Retrospective cohort studies are NOT the same as case-control studies.

In retrospective cohort studies, the exposure and outcomes have already happened. They are usually conducted on data that already exists (from prospective studies) and the exposures are defined before looking at the existing outcome data to see whether exposure to a risk factor is associated with a statistically significant difference in the outcome development rate.

Prospective cohort studies are more common. People are recruited into cohort studies regardless of their exposure or outcome status. This is one of their important strengths. People are often recruited because of their geographical area or occupation, for example, and researchers can then measure and analyse a range of exposures and outcomes.

The study then follows these participants for a defined period to assess the proportion that develop the outcome/disease of interest. See Figure 2 for a pictorial representation of a cohort study design. Therefore, cohort studies are good for assessing prognosis, risk factors and harm. The outcome measure in cohort studies is usually a risk ratio / relative risk (RR).

Figure 2. Cohort study design.

Cohort studies should include two groups that are identical EXCEPT for their exposure status.

As a result, both exposed and unexposed groups should be recruited from the same source population. Another important consideration is attrition. If a significant number of participants are not followed up (lost, death, dropped out) then this may impact the validity of the study. Not only does it decrease the study’s power, but there may be attrition bias – a significant difference between the groups of those that did not complete the study.

Cohort studies can assess a range of outcomes allowing an exposure to be rigorously assessed for its impact in developing disease. Additionally, they are good for rare exposures, e.g. contact with a chemical radiation blast.

Whilst cohort studies are useful, they can be expensive and time-consuming, especially if a long follow-up period is chosen or the disease itself is rare or has a long latency.

A summary of the pros and cons of cohort studies are provided in Table 2.

The Strengthening of Reporting of Observational Studies in Epidemiology Statement (STROBE)

STROBE provides a checklist of important steps for conducting these types of studies, as well as acting as best-practice reporting guidelines (3). Both case-control and cohort studies are observational, with varying advantages and disadvantages. However, the most important factor to the quality of evidence these studies provide, is their methodological quality.

• Song, J. and Chung, K. Observational Studies: Cohort and Case-Control Studies .  Plastic and Reconstructive Surgery.  2010 Dec;126(6):2234-2242.
• Ury HK. Efficiency of case-control studies with multiple controls per case: Continuous or dichotomous data .  Biometrics . 1975 Sep;31(3):643–649.
• von Elm E, Altman DG, Egger M, Pocock SJ, Gøtzsche PC, Vandenbroucke JP; STROBE Initiative.  The Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) statement: guidelines for reporting observational studies.   Lancet 2007 Oct;370(9596):1453-14577. PMID: 18064739.

Saul Crandon

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No Comments on Case-control and Cohort studies: A brief overview

Very well presented, excellent clarifications. Has put me right back into class, literally!

Very clear and informative! Thank you.

very informative article.

Thank you for the easy to understand blog in cohort studies. I want to follow a group of people with and without a disease to see what health outcomes occurs to them in future such as hospitalisations, diagnoses, procedures etc, as I have many health outcomes to consider, my questions is how to make sure these outcomes has not occurred before the “exposure disease”. As, in cohort studies we are looking at incidence (new) cases, so if an outcome have occurred before the exposure, I can leave them out of the analysis. But because I am not looking at a single outcome which can be checked easily and if happened before exposure can be left out. I have EHR data, so all the exposure and outcome have occurred. my aim is to check the rates of different health outcomes between the exposed)dementia) and unexposed(non-dementia) individuals.

Very helpful information

Thanks for making this subject student friendly and easier to understand. A great help.

Thanks a lot. It really helped me to understand the topic. I am taking epidemiology class this winter, and your paper really saved me.

Happy new year.

Wow its amazing n simple way of briefing ,which i was enjoyed to learn this.its very easy n quick to pick ideas .. Thanks n stay connected

Saul you absolute melt! Really good work man

am a student of public health. This information is simple and well presented to the point. Thank you so much.

very helpful information provided here

really thanks for wonderful information because i doing my bachelor degree research by survival model

Quite informative thank you so much for the info please continue posting. An mph student with Africa university Zimbabwe.

Thank you this was so helpful amazing

Apreciated the information provided above.

So clear and perfect. The language is simple and superb.I am recommending this to all budding epidemiology students. Thanks a lot.

Great to hear, thank you AJ!

I have recently completed an investigational study where evidence of phlebitis was determined in a control cohort by data mining from electronic medical records. We then introduced an intervention in an attempt to reduce incidence of phlebitis in a second cohort. Again, results were determined by data mining. This was an expedited study, so there subjects were enrolled in a specific cohort based on date(s) of the drug infused. How do I define this study? Thanks so much.

thanks for the information and knowledge about observational studies. am a masters student in public health/epidemilogy of the faculty of medicines and pharmaceutical sciences , University of Dschang. this information is very explicit and straight to the point

Very much helpful

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What Is A Case Control Study?

Julia Simkus

Editor at Simply Psychology

BA (Hons) Psychology, Princeton University

Julia Simkus is a graduate of Princeton University with a Bachelor of Arts in Psychology. She is currently studying for a Master's Degree in Counseling for Mental Health and Wellness in September 2023. Julia's research has been published in peer reviewed journals.

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A case-control study is a research method where two groups of people are compared – those with the condition (cases) and those without (controls). By looking at their past, researchers try to identify what factors might have contributed to the condition in the ‘case’ group.

Explanation

A case-control study looks at people who already have a certain condition (cases) and people who don’t (controls). By comparing these two groups, researchers try to figure out what might have caused the condition. They look into the past to find clues, like habits or experiences, that are different between the two groups.

The “cases” are the individuals with the disease or condition under study, and the “controls” are similar individuals without the disease or condition of interest.

The controls should have similar characteristics (i.e., age, sex, demographic, health status) to the cases to mitigate the effects of confounding variables .

Case-control studies identify any associations between an exposure and an outcome and help researchers form hypotheses about a particular population.

Researchers will first identify the two groups, and then look back in time to investigate which subjects in each group were exposed to the condition.

If the exposure is found more commonly in the cases than the controls, the researcher can hypothesize that the exposure may be linked to the outcome of interest.

Figure: Schematic diagram of case-control study design. Kenneth F. Schulz and David A. Grimes (2002) Case-control studies: research in reverse . The Lancet Volume 359, Issue 9304, 431 – 434

Quick, inexpensive, and simple

Because these studies use already existing data and do not require any follow-up with subjects, they tend to be quicker and cheaper than other types of research. Case-control studies also do not require large sample sizes.

Beneficial for studying rare diseases

Researchers in case-control studies start with a population of people known to have the target disease instead of following a population and waiting to see who develops it. This enables researchers to identify current cases and enroll a sufficient number of patients with a particular rare disease.

Useful for preliminary research

Case-control studies are beneficial for an initial investigation of a suspected risk factor for a condition. The information obtained from cross-sectional studies then enables researchers to conduct further data analyses to explore any relationships in more depth.

Limitations

Subject to recall bias.

Participants might be unable to remember when they were exposed or omit other details that are important for the study. In addition, those with the outcome are more likely to recall and report exposures more clearly than those without the outcome.

Difficulty finding a suitable control group

It is important that the case group and the control group have almost the same characteristics, such as age, gender, demographics, and health status.

Forming an accurate control group can be challenging, so sometimes researchers enroll multiple control groups to bolster the strength of the case-control study.

Do not demonstrate causation

Case-control studies may prove an association between exposures and outcomes, but they can not demonstrate causation.

A case-control study is an observational study where researchers analyzed two groups of people (cases and controls) to look at factors associated with particular diseases or outcomes.

Below are some examples of case-control studies:

• Investigating the impact of exposure to daylight on the health of office workers (Boubekri et al., 2014).
• Comparing serum vitamin D levels in individuals who experience migraine headaches with their matched controls (Togha et al., 2018).
• Analyzing correlations between parental smoking and childhood asthma (Strachan and Cook, 1998).
• Studying the relationship between elevated concentrations of homocysteine and an increased risk of vascular diseases (Ford et al., 2002).
• Assessing the magnitude of the association between Helicobacter pylori and the incidence of gastric cancer (Helicobacter and Cancer Collaborative Group, 2001).
• Evaluating the association between breast cancer risk and saturated fat intake in postmenopausal women (Howe et al., 1990).

Frequently asked questions

1. what’s the difference between a case-control study and a cross-sectional study.

Case-control studies are different from cross-sectional studies in that case-control studies compare groups retrospectively while cross-sectional studies analyze information about a population at a specific point in time.

In  cross-sectional studies , researchers are simply examining a group of participants and depicting what already exists in the population.

2. What’s the difference between a case-control study and a longitudinal study?

Case-control studies compare groups retrospectively, while longitudinal studies can compare groups either retrospectively or prospectively.

In a  longitudinal study , researchers monitor a population over an extended period of time, and they can be used to study developmental shifts and understand how certain things change as we age.

In addition, case-control studies look at a single subject or a single case, whereas longitudinal studies can be conducted on a large group of subjects.

3. What’s the difference between a case-control study and a retrospective cohort study?

Case-control studies are retrospective as researchers begin with an outcome and trace backward to investigate exposure; however, they differ from retrospective cohort studies.

In a  retrospective cohort study , researchers examine a group before any of the subjects have developed the disease, then examine any factors that differed between the individuals who developed the condition and those who did not.

Thus, the outcome is measured after exposure in retrospective cohort studies, whereas the outcome is measured before the exposure in case-control studies.

Boubekri, M., Cheung, I., Reid, K., Wang, C., & Zee, P. (2014). Impact of windows and daylight exposure on overall health and sleep quality of office workers: a case-control pilot study. Journal of Clinical Sleep Medicine: JCSM: Official Publication of the American Academy of Sleep Medicine, 10 (6), 603-611.

Ford, E. S., Smith, S. J., Stroup, D. F., Steinberg, K. K., Mueller, P. W., & Thacker, S. B. (2002). Homocyst (e) ine and cardiovascular disease: a systematic review of the evidence with special emphasis on case-control studies and nested case-control studies. International journal of epidemiology, 31 (1), 59-70.

Helicobacter and Cancer Collaborative Group. (2001). Gastric cancer and Helicobacter pylori: a combined analysis of 12 case control studies nested within prospective cohorts. Gut, 49 (3), 347-353.

Howe, G. R., Hirohata, T., Hislop, T. G., Iscovich, J. M., Yuan, J. M., Katsouyanni, K., … & Shunzhang, Y. (1990). Dietary factors and risk of breast cancer: combined analysis of 12 case—control studies. JNCI: Journal of the National Cancer Institute, 82 (7), 561-569.

Lewallen, S., & Courtright, P. (1998). Epidemiology in practice: case-control studies. Community eye health, 11 (28), 57–58.

Strachan, D. P., & Cook, D. G. (1998). Parental smoking and childhood asthma: longitudinal and case-control studies. Thorax, 53 (3), 204-212.

Tenny, S., Kerndt, C. C., & Hoffman, M. R. (2021). Case Control Studies. In StatPearls . StatPearls Publishing.

Togha, M., Razeghi Jahromi, S., Ghorbani, Z., Martami, F., & Seifishahpar, M. (2018). Serum Vitamin D Status in a Group of Migraine Patients Compared With Healthy Controls: A Case-Control Study. Headache, 58 (10), 1530-1540.

Further Information

• Schulz, K. F., & Grimes, D. A. (2002). Case-control studies: research in reverse. The Lancet, 359(9304), 431-434.
• What is a case-control study?

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Quantitative study designs: Case Control

Quantitative study designs.

• Introduction
• Cohort Studies
• Randomised Controlled Trial

Case Control

• Cross-Sectional Studies
• Study Designs Home

In a Case-Control study there are two groups of people: one has a health issue (Case group), and this group is “matched” to a Control group without the health issue based on characteristics like age, gender, occupation. In this study type, we can look back in the patient’s histories to look for exposure to risk factors that are common to the Case group, but not the Control group. It was a case-control study that demonstrated a link between carcinoma of the lung and smoking tobacco . These studies estimate the odds between the exposure and the health outcome, however they cannot prove causality. Case-Control studies might also be referred to as retrospective or case-referent studies. 

Stages of a Case-Control study

This diagram represents taking both the case (disease) and the control (no disease) groups and looking back at their histories to determine their exposure to possible contributing factors.  The researchers then determine the likelihood of those factors contributing to the disease.

(FOR ACCESSIBILITY: A case control study is likely to show that most, but not all exposed people end up with the health issue, and some unexposed people may also develop the health issue)

Which Clinical Questions does Case-Control best answer?

Case-Control studies are best used for Prognosis questions.

For example: Do anticholinergic drugs increase the risk of dementia in later life? (See BMJ Case-Control study Anticholinergic drugs and risk of dementia: case-control study )

What are the advantages and disadvantages to consider when using Case-Control?

* Confounding occurs when the elements of the study design invalidate the result. It is usually unintentional. It is important to avoid confounding, which can happen in a few ways within Case-Control studies. This explains why it is lower in the hierarchy of evidence, superior only to Case Studies.

What does a strong Case-Control study look like?

A strong study will have:

• Well-matched controls, similar background without being so similar that they are likely to end up with the same health issue (this can be easier said than done since the risk factors are unknown). 
• Detailed medical histories are available, reducing the emphasis on a patient’s unreliable recall of their potential exposures. 

What are the pitfalls to look for?

• Poorly matched or over-matched controls.  Poorly matched means that not enough factors are similar between the Case and Control. E.g. age, gender, geography. Over-matched conversely means that so many things match (age, occupation, geography, health habits) that in all likelihood the Control group will also end up with the same health issue! Either of these situations could cause the study to become ineffective. 
• Selection bias: Selection of Controls is biased. E.g. All Controls are in the hospital, so they’re likely already sick, they’re not a true sample of the wider population. 
• Cases include persons showing early symptoms who never ended up having the illness. 

Critical appraisal tools 

To assist with critically appraising case control studies there are some tools / checklists you can use.

CASP - Case Control Checklist

JBI – Critical appraisal checklist for case control studies

CEBMA – Centre for Evidence Based Management  – Critical appraisal questions (focus on leadership and management)

STROBE - Observational Studies checklists includes Case control

SIGN - Case-Control Studies Checklist

NCCEH - Critical Appraisal of a Case Control Study for environmental health

Real World Examples

Smoking and carcinoma of the lung; preliminary report

• Doll, R., & Hill, A. B. (1950). Smoking and carcinoma of the lung; preliminary report.  British Medical Journal ,  2 (4682), 739–748. Retrieved from  https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2038856/
• Key Case-Control study linking tobacco smoking with lung cancer
• Notes a marked increase in incidence of Lung Cancer disproportionate to population growth.
• 20 London Hospitals contributed current Cases of lung, stomach, colon and rectum cancer via admissions, house-physician and radiotherapy diagnosis, non-cancer Controls were selected at each hospital of the same-sex and within 5 year age group of each.
• 1732 Cases and 743 Controls were interviewed for social class, gender, age, exposure to urban pollution, occupation and smoking habits.
• It was found that continued smoking from a younger age and smoking a greater number of cigarettes correlated with incidence of lung cancer.

Anticholinergic drugs and risk of dementia: case-control study

• Richardson, K., Fox, C., Maidment, I., Steel, N., Loke, Y. K., Arthur, A., . . . Savva, G. M. (2018). Anticholinergic drugs and risk of dementia: case-control study. BMJ , 361, k1315. Retrieved from  http://www.bmj.com/content/361/bmj.k1315.abstract .
• A recent study linking the duration and level of exposure to Anticholinergic drugs and subsequent onset of dementia.
• Anticholinergic Cognitive Burden (ACB) was estimated in various drugs, the higher the exposure (measured as the ACB score) the greater likeliness of onset of dementia later in life.
• Antidepressant, urological, and antiparkinson drugs with an ACB score of 3 increased the risk of dementia. Gastrointestinal drugs with an ACB score of 3 were not strongly linked with onset of dementia.
• Tricyclic antidepressants such as Amitriptyline have an ACB score of 3 and are an example of a common area of concern.

Omega-3 deficiency associated with perinatal depression: Case-Control study 

• Rees, A.-M., Austin, M.-P., Owen, C., & Parker, G. (2009). Omega-3 deficiency associated with perinatal depression: Case control study. Psychiatry Research , 166(2), 254-259. Retrieved from  http://www.sciencedirect.com/science/article/pii/S0165178107004398 .
• During pregnancy women lose Omega-3 polyunsaturated fatty acids to the developing foetus.
• There is a known link between Omgea-3 depletion and depression
• Sixteen depressed and 22 non-depressed women were recruited during their third trimester
• High levels of Omega-3 were associated with significantly lower levels of depression.
• Women with low levels of Omega-3 were six times more likely to be depressed during pregnancy.

References and Further Reading

Doll, R., & Hill, A. B. (1950). Smoking and carcinoma of the lung; preliminary report. British Medical Journal, 2(4682), 739–748. Retrieved from https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2038856/

Greenhalgh, Trisha. How to Read a Paper: the Basics of Evidence-Based Medicine, John Wiley & Sons, Incorporated, 2014. ProQuest Ebook Central, http://ebookcentral.proquest.com/lib/deakin/detail.action?docID=1642418 .

Himmelfarb Health Sciences Library. (2019). Study Design 101: Case-Control Study. Retrieved from https://himmelfarb.gwu.edu/tutorials/studydesign101/casecontrols.cfm   

Hoffmann, T., Bennett, S., & Del Mar, C. (2017). Evidence-Based Practice Across the Health Professions (Third edition. ed.): Elsevier. 

Lewallen, S., & Courtright, P. (1998). Epidemiology in practice: case-control studies. Community Eye Health, 11(28), 57.  https://www.ncbi.nlm.nih.gov/pmc/articles/PMC1706071/  

Pelham, B. W. a., & Blanton, H. (2013). Conducting research in psychology : measuring the weight of smoke /Brett W. Pelham, Hart Blanton (Fourth edition. ed.): Wadsworth Cengage Learning. 

Rees, A.-M., Austin, M.-P., Owen, C., & Parker, G. (2009). Omega-3 deficiency associated with perinatal depression: Case control study. Psychiatry Research, 166(2), 254-259. Retrieved from http://www.sciencedirect.com/science/article/pii/S0165178107004398

Richardson, K., Fox, C., Maidment, I., Steel, N., Loke, Y. K., Arthur, A., … Savva, G. M. (2018). Anticholinergic drugs and risk of dementia: case-control study. BMJ, 361, k1315. Retrieved from http://www.bmj.com/content/361/bmj.k1315.abstract

Statistics How To. (2019). Case-Control Study: Definition, Real Life Examples. Retrieved from https://www.statisticshowto.com/case-control-study/  

• << Previous: Randomised Controlled Trial
• Next: Cross-Sectional Studies >>
• Last Updated: Feb 29, 2024 4:49 PM
• URL: https://deakin.libguides.com/quantitative-study-designs

Study Design 101: Case Control Study

• Case Report
• Case Control Study
• Cohort Study
• Randomized Controlled Trial
• Practice Guideline
• Systematic Review
• Meta-Analysis
• Helpful Formulas
• Finding Specific Study Types

A study that compares patients who have a disease or outcome of interest (cases) with patients who do not have the disease or outcome (controls), and looks back retrospectively to compare how frequently the exposure to a risk factor is present in each group to determine the relationship between the risk factor and the disease.

Case control studies are observational because no intervention is attempted and no attempt is made to alter the course of the disease. The goal is to retrospectively determine the exposure to the risk factor of interest from each of the two groups of individuals: cases and controls. These studies are designed to estimate odds.

Case control studies are also known as "retrospective studies" and "case-referent studies."

• Good for studying rare conditions or diseases
• Less time needed to conduct the study because the condition or disease has already occurred
• Lets you simultaneously look at multiple risk factors
• Useful as initial studies to establish an association
• Can answer questions that could not be answered through other study designs

Disadvantages

• Retrospective studies have more problems with data quality because they rely on memory and people with a condition will be more motivated to recall risk factors (also called recall bias).
• Not good for evaluating diagnostic tests because it's already clear that the cases have the condition and the controls do not
• It can be difficult to find a suitable control group

Design pitfalls to look out for

Care should be taken to avoid confounding, which arises when an exposure and an outcome are both strongly associated with a third variable. Controls should be subjects who might have been cases in the study but are selected independent of the exposure. Cases and controls should also not be "over-matched."

Is the control group appropriate for the population? Does the study use matching or pairing appropriately to avoid the effects of a confounding variable? Does it use appropriate inclusion and exclusion criteria?

Fictitious Example

There is a suspicion that zinc oxide, the white non-absorbent sunscreen traditionally worn by lifeguards is more effective at preventing sunburns that lead to skin cancer than absorbent sunscreen lotions. A case-control study was conducted to investigate if exposure to zinc oxide is a more effective skin cancer prevention measure. The study involved comparing a group of former lifeguards that had developed cancer on their cheeks and noses (cases) to a group of lifeguards without this type of cancer (controls) and assess their prior exposure to zinc oxide or absorbent sunscreen lotions.

This study would be retrospective in that the former lifeguards would be asked to recall which type of sunscreen they used on their face and approximately how often. This could be either a matched or unmatched study, but efforts would need to be made to ensure that the former lifeguards are of the same average age, and lifeguarded for a similar number of seasons and amount of time per season.

Real-life Examples

Boubekri, M., Cheung, I., Reid, K., Wang, C., & Zee, P. (2014). Impact of windows and daylight exposure on overall health and sleep quality of office workers: a case-control pilot study. Journal of Clinical Sleep Medicine : JCSM : Official Publication of the American Academy of Sleep Medicine, 10 (6), 603-611. https://doi.org/10.5664/jcsm.3780

This pilot study explored the impact of exposure to daylight on the health of office workers (measuring well-being and sleep quality subjectively, and light exposure, activity level and sleep-wake patterns via actigraphy). Individuals with windows in their workplaces had more light exposure, longer sleep duration, and more physical activity. They also reported a better scores in the areas of vitality and role limitations due to physical problems, better sleep quality and less sleep disturbances.

Togha, M., Razeghi Jahromi, S., Ghorbani, Z., Martami, F., & Seifishahpar, M. (2018). Serum Vitamin D Status in a Group of Migraine Patients Compared With Healthy Controls: A Case-Control Study. Headache, 58 (10), 1530-1540. https://doi.org/10.1111/head.13423

This case-control study compared serum vitamin D levels in individuals who experience migraine headaches with their matched controls. Studied over a period of thirty days, individuals with higher levels of serum Vitamin D was associated with lower odds of migraine headache.

Related Formulas

• Odds ratio in an unmatched study
• Odds ratio in a matched study

Related Terms

A patient with the disease or outcome of interest.

Confounding

When an exposure and an outcome are both strongly associated with a third variable.

A patient who does not have the disease or outcome.

Matched Design

Each case is matched individually with a control according to certain characteristics such as age and gender. It is important to remember that the concordant pairs (pairs in which the case and control are either both exposed or both not exposed) tell us nothing about the risk of exposure separately for cases or controls.

Observed Assignment

The method of assignment of individuals to study and control groups in observational studies when the investigator does not intervene to perform the assignment.

Unmatched Design

The controls are a sample from a suitable non-affected population.

Now test yourself!

1. Case Control Studies are prospective in that they follow the cases and controls over time and observe what occurs.

a) True b) False

2. Which of the following is an advantage of Case Control Studies?

a) They can simultaneously look at multiple risk factors. b) They are useful to initially establish an association between a risk factor and a disease or outcome. c) They take less time to complete because the condition or disease has already occurred. d) b and c only e) a, b, and c

Evidence Pyramid - Navigation

• Meta- Analysis
• Case Reports
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A Practical Overview of Case-Control Studies in Clinical Practice

Affiliations.

• 1 Department of Quantitative Health Sciences, Lerner Research Institute, Cleveland Clinic, Cleveland, OH; Center for Surgery and Public Health, Brigham and Women's Hospital, Harvard Medical School, Boston, MA. Electronic address: [email protected].
• 2 Department of Quantitative Health Sciences, Lerner Research Institute, Cleveland Clinic, Cleveland, OH; Department of Population and Quantitative Health Sciences, Case Western Reserve University, School of Medicine, Cleveland, OH.
• 3 Department of Statistics, University of Missouri, Columbia, MO.
• PMID: 32658653
• DOI: 10.1016/j.chest.2020.03.009

Case-control studies are one of the major observational study designs for performing clinical research. The advantages of these study designs over other study designs are that they are relatively quick to perform, economical, and easy to design and implement. Case-control studies are particularly appropriate for studying disease outbreaks, rare diseases, or outcomes of interest. This article describes several types of case-control designs, with simple graphical displays to help understand their differences. Study design considerations are reviewed, including sample size, power, and measures associated with risk factors for clinical outcomes. Finally, we discuss the advantages and disadvantages of case-control studies and provide a checklist for authors and a framework of considerations to guide reviewers' comments.

Keywords: OR; case-cohort; case-crossover; matching; nested case-control; relative risk.

Copyright © 2020 American College of Chest Physicians. Published by Elsevier Inc. All rights reserved.

Publication types

• Case-Control Studies*
• Guidelines as Topic
• Research Design / standards
• Research Design / statistics & numerical data*

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Types of Research Studies

Epidemiology studies.

Epidemiology is the study of the patterns and causes of disease in people.

The goal of epidemiology studies is to give information that helps support or disprove an idea about a possible link between an exposure (such as alcohol use) and an outcome (such as breast cancer) in people.

The 2 main types of epidemiology studies are:

• Observational studies ( prospective cohort or case-control )

Randomized controlled trials

Though they have the same goal, observational studies and randomized controlled trials differ in:

• The way they are conducted
• The strengths of the conclusions they reach

Observational studies

In observational studies, the people in the study live their daily lives as they choose. They exercise when they want, eat what they like and take the medicines their doctors prescribe. They report these activities to researchers.

There are 2 types of observational studies:

Prospective cohort studies

Case-control studies.

A prospective cohort study follows a large group of people forward in time.

Some people will have a certain exposure (such as alcohol use) and others will not.

Researchers compare the different groups (for example, they might compare heavy drinkers, moderate drinkers, light drinkers and non-drinkers) to see which group is more likely to develop an outcome (such as breast cancer).

In a case-control study, researchers identify 2 groups: cases and controls.

• Cases are people who already have an outcome (such as breast cancer).
• Controls are people who do not have the outcome.

The researchers compare the 2 groups to see if any exposure (such as alcohol use) was more common in the history of one group compared to the other.

In randomized controlled trials (randomized clinical trials), researchers divide people into groups to compare different treatments or other interventions.

These studies are called randomized controlled trials because people are randomly assigned (as if by coin toss) to a certain treatment or behavior.

For example, in a randomized trial of a new drug therapy, half the people might be randomly assigned to a new drug and the other half to the standard treatment.

In a randomized controlled trial on exercise and breast cancer risk, half the participants might be randomly assigned to walk 10 minutes a day and the other half to walk 2 hours a day. The researchers would then see which group was more likely to develop breast cancer, those who walked 10 minutes a day or those who walked 2 hours a day.

Many behaviors, such as smoking or heavy alcohol drinking, can’t be tested in this way because it isn’t ethical to assign people to a behavior known to be harmful. In these cases, researchers must use observational studies.

Patient series

A patient series is a doctor’s observations of a group of patients who are given a certain treatment.

There is no comparison group in a patient series. All the patients are given a certain treatment and the outcomes of these patients are studied.

With no comparison group, it’s hard to draw firm conclusions about the effectiveness of a treatment.

For example, if 10 women with breast cancer are given a new treatment, and 2 of them respond, how do we know if the new treatment is better than standard treatment?

If we had a comparison group of 10 women with breast cancer who got standard treatment, we could compare their outcomes to those of the 10 women on the new treatment. If no women in the comparison group responded to standard treatment, then the 2 women who responded to the new treatment would represent a success of the new treatment. If, however, 2 of the 10 women in the standard treatment group also responded, then the new treatment is no better than the standard.

The lack of a comparison group makes it hard to draw conclusions from a patient series. However, data from a patient series can help form hypotheses that can be tested in other types of studies.

Strengths and weaknesses of different types of research studies

When reviewing scientific evidence, it’s helpful to understand the strengths and weaknesses of different types of research studies.

Case-control studies have some strengths:

• They are easy and fairly inexpensive to conduct.
• They are a good way for researchers to study rare diseases. If a disease is rare, you would need to follow a very large group of people forward in time to have many cases of the disease develop.
• They are a good way for researchers to study diseases that take a long time to develop. If a disease takes a long time to develop, you would have to follow a group of people for many years for cases of the disease to develop.

Case-control studies look at past exposures of people who already have a disease. This causes some concerns:

• It can be hard for people to remember details about the past, especially when it comes to things like diet.
• Memories can be biased (or influenced) because the information is gathered after an event, such as the diagnosis of breast cancer.
• When it comes to sensitive topics (such as abortion), the cases (the people with the disease) may be much more likely to give complete information about their history than the controls (the people without the disease). Such differences in reporting bias study results.

For these reasons, the accuracy of the results of case-control studies can be questionable.

Cohort studies

Prospective cohort studies avoid many of the problems of case-control studies because they gather information from people over time and before the events being studied happen.

However, compared to case-control studies, they are expensive to conduct.

Nested case-control studies

A nested case-control study is a case-control study within a prospective cohort study.

Nested case-control studies use the design of a case-control study. However, they use data gathered as part of a cohort study, so they are less prone to bias than standard case-control studies.

All things being equal, the strength of nested case-control data falls somewhere between that of standard case-control studies and cohort studies.

Randomized controlled trials are considered the gold standard for studying certain exposures, such as breast cancer treatment. Similar to cohort studies, they follow people over time and are expensive to do.

Because people in a randomized trial are randomly assigned to an intervention (such as a new chemotherapy drug) or standard treatment, these studies are more likely to show the true link between an intervention and a health outcome (such as survival).

Learn more about randomized clinical trials , including the types of clinical trials, benefits, and possible drawbacks.

Overall study quality

The overall quality of a study is important. For example, the results from a well-designed case-control study can be more reliable than those from a poorly-designed randomized trial.

Finding more information on research study design

If you’re interested in learning more about research study design, a basic epidemiology textbook from your local library may be a good place to start. The National Cancer Institute also has information on epidemiology studies and randomized controlled trials.

Animal studies

Animal studies add to our understanding of how and why some factors cause cancer in people.

However, there are many differences between animals and people, so it makes it hard to translate findings directly from one to the other.

Animal studies are also designed differently. They often look at exposures in larger doses and for shorter periods of time than are suitable for people.

While animal studies can lay the groundwork for research in people, we need human studies to draw conclusions for people.

All data presented within this section of the website come from studies done with people.

Joining a research study

Research is ongoing to improve all areas of breast cancer, from prevention to treatment.

Whether you’re newly diagnosed, finished breast cancer treatment many years ago, or even if you’ve never had breast cancer, there may be breast cancer research studies you can join.

If you have breast cancer, BreastCancerTrials.org in collaboration with Susan G. Komen® offers a custom matching service that can help find a studies that fit your needs. You can also visit the National Institutes of Health’s website to find a breast cancer treatment study.

If you’re interested in being part of other studies, talk with your health care provider. Your provider may know of studies in your area looking for volunteers.

Learn more about joining a research study .

Learn more about clinical trials .

Learn what Komen is doing to help people find and participate in clinical trials .

Updated 12/16/20

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• Published: 08 April 2024

The PARTNER trial of neoadjuvant olaparib in triple-negative breast cancer

• Jean E. Abraham   ORCID: orcid.org/0000-0003-0688-4807 1 , 2 ,
• Karen Pinilla   ORCID: orcid.org/0000-0002-2723-0805 1 , 2 ,
• Alimu Dayimu 3 ,
• Louise Grybowicz 4 ,
• Nikolaos Demiris 5 ,
• Caron Harvey 4 ,
• Lynsey M. Drewett 6 ,
• Rebecca Lucey   ORCID: orcid.org/0000-0002-6226-447X 1 , 2 ,
• Alexander Fulton 1 , 2 ,
• Anne N. Roberts 4 ,
• Joanna R. Worley 1 , 2 ,
• Anita Chhabra   ORCID: orcid.org/0000-0002-9899-8010 7 ,
• Wendi Qian   ORCID: orcid.org/0000-0002-4238-3471 8 ,
• Anne-Laure Vallier 4 ,
• Richard M. Hardy 4 ,
• Steve Chan 9 ,
• Tamas Hickish 10 ,
• Devashish Tripathi 11 , 12 ,
• Ramachandran Venkitaraman 13 ,
• Mojca Persic 14 ,
• Shahzeena Aslam 15 ,
• Daniel Glassman 16 ,
• Sanjay Raj 17 , 18 , 19 ,
• Annabel Borley 20 ,
• Jeremy P. Braybrooke 21 ,
• Stephanie Sutherland 22 ,
• Emma Staples 23 ,
• Lucy C. Scott 24 ,
• Mark Davies 25 ,
• Cheryl A. Palmer 26 ,
• Margaret Moody 27 ,
• Mark J. Churn 28 , 29 , 30 ,
• Jacqueline C. Newby 31 ,
• Mukesh B. Mukesh 32 ,
• Amitabha Chakrabarti 33 ,
• Rebecca R. Roylance 34 ,
• Philip C. Schouten 35 ,
• Nicola C. Levitt 36 ,
• Karen McAdam 37 ,
• Anne C. Armstrong 38 ,
• Ellen R. Copson 39 ,
• Emma McMurtry 40 ,
• Marc Tischkowitz   ORCID: orcid.org/0000-0002-7880-0628 41 ,
• Elena Provenzano 35 &
• Helena M. Earl 1 , 2  

Nature ( 2024 ) Cite this article

Metrics details

We are providing an unedited version of this manuscript to give early access to its findings. Before final publication, the manuscript will undergo further editing. Please note there may be errors present which affect the content, and all legal disclaimers apply.

• Breast cancer
• Chemotherapy
• Targeted therapies

PARTNER is a prospective, phase II-III, randomised controlled clinical trial, which recruited patients with Triple Negative Breast Cancer (TNBC) 1,2 , who were gBRCA wild type (gBRCAwt) 3 . Patients (n=559) were randomised on a 1:1 basis to neoadjuvant carboplatin with paclitaxel +/- olaparib 150mg twice daily, days 3 to 14, for 4 cycles (gap schedule olaparib, research arm) followed by 3 cycles of anthracycline chemotherapy before surgery. The primary endpoint was pathological complete response (pCR) 4 , and secondary endpoints included event-free survival (EFS), and overall survival (OS) 5 . pCR was achieved in 51% in the research arm and 52% in the control arm (p=0.753). Estimated EFS at 36 months in research and control arms were 80% and 79% (log-rank p>0.9); OS were 90% and 87.2% (log-rank p=0.8) respectively. In patients with pCR, estimated EFS at 36 months was 90%, and with non-pCR was 70% (log-rank p < 0.001) and OS was 96% and 83% (log-rank p < 0.001) respectively. Neo-adjuvant olaparib did not improve pCR rates, EFS or OS when added to carboplatin/paclitaxel and anthracycline chemotherapy in patients with TNBC (gBRCAwt). This is in marked contrast to the major benefit of olaparib (gap schedule) in those with gBRCA pathogenic variants (gBRCAm) which is reported separately (gBRCAm article). ClinicalTrials.gov ID NCT03150576

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Author information

Authors and affiliations.

Precision Breast Cancer Institute, Department of Oncology, Department of Oncology, University of Cambridge, Cambridge, UK

Jean E. Abraham, Karen Pinilla, Rebecca Lucey, Alexander Fulton, Joanna R. Worley & Helena M. Earl

Cancer Research UK Cambridge Centre, University of Cambridge, Cambridge, UK

Cambridge Cancer Trials Centre, University of Cambridge, Cambridge, UK

Alimu Dayimu

Cambridge Cancer Trials Centre, Cambridge University Hospitals NHS Foundation Trust, Cambridge and the University of Cambridge, Cambridge, UK

Louise Grybowicz, Caron Harvey, Anne N. Roberts, Anne-Laure Vallier & Richard M. Hardy

Department of Statistics, Athens University of Economics and Business, Athens, Greece

Nikolaos Demiris

Royal Devon University Healthcare NHS Foundation Trust, Exeter, Devon, UK

Lynsey M. Drewett

Cambridge University Hospitals NHS Foundation Trust, Cambridge, UK

Anita Chhabra

Cambridge Clinical Trials Unit, Cambridge University Hospitals NHS Foundation Trust, Cambridge, UK

The City Hospital, Nottingham University Hospitals NHS Trust, Nottingham, UK

Royal Bournemouth General Hospital, Bournemouth, UK

Tamas Hickish

Royal Wolverhampton NHS Trust, Wolverhampton, UK

Devashish Tripathi

Russells Hall Hospital, Dudley, West Midlands, UK

Ipswich Hospital, East Suffolk and North Essex NHS Foundation Trust, Ipswich, UK

Ramachandran Venkitaraman

University Hospital of Derby and Burton, Derby, UK

Mojca Persic

Bedford Hospital, Bedfordshire Hospitals NHS Foundation Trust, Bedford, UK

Shahzeena Aslam

Pinderfields Hospital, Mid Yorkshire Teaching NHS Trust, Wakefield, UK

Daniel Glassman

University Hospitals Southampton and Hampshire Hospitals Foundation Trusts, Southampton, UK

Basingstoke & North Hampshire Hospital, Basingstoke, UK

Royal Hampshire Hospital, Winchester, UK

Velindre Cancer Centre, Cardiff, Wales, UK

Annabel Borley

University Hospitals Bristol and Weston NHS Foundation Trust, Bristol, UK

Jeremy P. Braybrooke

Mount Vernon Cancer Centre, Northwood, UK

Stephanie Sutherland

Queens Hospital, Barking, Havering and Redbridge University Hospitals NHS Trust, Romford, UK

Emma Staples

Beatson West Of Scotland Cancer Centre, Glasgow, Scotland, UK

Lucy C. Scott

Swansea Bay University Health Board, Swansea, Wales, UK

Mark Davies

Hinchingbrooke Hospital, North West Anglia NHS Foundation Trust, Huntingdon, UK

Cheryl A. Palmer

Macmillan Unit, West Suffolk Hospital NHS Foundation Trust, Bury Saint Edmunds, UK

Margaret Moody

Worcestershire Acute Hospitals NHS Trust, Worcester, UK

Mark J. Churn

Alexandra Redditch Hospital, Redditch, UK

Hospital, Kidderminster, Worcestershire, UK

Royal Free London NHS Foundation Trust, London, UK

Jacqueline C. Newby

Oncology Department, Colchester General Hospital, East Suffolk & North Essex NHS Trust, Colchester, UK

Mukesh B. Mukesh

University Hospitals Dorset NHS Foundation Trust, Poole, UK

Amitabha Chakrabarti

University College London Hospitals NHS Foundation Trust, London, UK

Rebecca R. Roylance

Department of Histopathology, Addenbrooke’s Hospital, Cambridge University Hospitals NHS Foundation Trust, Cambridge, UK

Philip C. Schouten & Elena Provenzano

Oxford University Hospital NHS Foundation Trust, Oxford, UK

Nicola C. Levitt

Peterborough City Hospital, North West Anglia NHS Foundation Trust, Peterborough, UK

Karen McAdam

The Christie NHS Foundation Trust and Division of Cancer Sciences, Manchester, UK

Anne C. Armstrong

Cancer Sciences Academic Unit, University of Southampton, Southampton, UK

Ellen R. Copson

EMC2 Clinical Consultancy Ltd, Sale, Manchester, UK

Emma McMurtry

Department of Medical Genetics, National Institute for Health Research, Cambridge Biomedical Research Centre, University of Cambridge, Cambridge, UK

Marc Tischkowitz

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Corresponding author

Correspondence to Jean E. Abraham .

Supplementary information

Supplementary information.

This file contains: 1. Summary from protocol; and 2. PARTNER Trial Consortium Members.

Reporting Summary

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Cite this article.

Abraham, J.E., Pinilla, K., Dayimu, A. et al. The PARTNER trial of neoadjuvant olaparib in triple-negative breast cancer. Nature (2024). https://doi.org/10.1038/s41586-024-07384-2

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Received : 06 February 2024

Accepted : 04 April 2024

Published : 08 April 2024

DOI : https://doi.org/10.1038/s41586-024-07384-2

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ORIGINAL RESEARCH article

This article is part of the research topic.

Eating Behavior and Chronic Diseases: Research Evidence from Population Studies

Comparison of Dutch healthy eating and healthy eating indexes and anthropometry in patients with major depression with health subjects: a case-control study Provisionally Accepted

• 1 Science and Research Branch, Islamic Azad University, Iran

The final, formatted version of the article will be published soon.

Background: Diseases and disorders related to mental health are spreading like other chronic diseases all around the world. Considering the role of food in the prevention and treatment of these disorders, including major depression, investigating the relationship between different food patterns and this disorder is of particular importance. The aim of this study was to compare Dutch healthy eating and healthy eating indexes and anthropometry in patients with major depression with healthy individuals.Methods: In this case-control study, the final analysis was performed on 67 men and 111 women with an age range of 20-30 years. Height (cm), weight (kg), food frequency questionnaire (FFQ), physical activity (MET-min/week), demographic and PHQ-9 questionnaires were taken from all participants. In the following, all the food ingredients and their components were extracted and used to calculate HEI-2015 and DHD. Statistical analysis was performed using SPSS software with independent t-test, logistic regression and chi-square.Results: It was found that people with major depression in this study were mostly women and occupied. The average HEI-2015 in healthy people and those with major depression was 58 and 54.3, respectively. Also, the average DHD in these people was 60.5 and 55, respectively. HEI-2015 and DHD had a significant negative correlation with depression score (r= -0.16, p-value= 0.03) (r= -0.19, p-value= 0.01). Also, in the logistic regression model, before and even after adjusting confounders, HEI-2015 and DHD had a reduced odds ratio in people suffering from major depression. The two groups did not differ significantly in terms of the average factors of height, weight and body mass index (BMI).Conclusion: It seems that HEI2015 and DHD have a significant relationship in reducing major depression. However, due to the small number of studies in this regard, especially in the field of DHD, the need for more studies seems necessary.

Keywords: major depression, Dutch Healthy Diet index, Healthy Eating Index 2015, PHQ9, HEI

Received: 14 Jan 2024; Accepted: 08 Apr 2024.

Copyright: © 2024 Tohidi-Nafe, Movahedi and Djazayery. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY) . The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

* Correspondence: Mrs. Melika Tohidi-Nafe, Science and Research Branch, Islamic Azad University, Tehran, Iran

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As marine resources continue to be exploited, the remarkable locomotion and coordination of fish provide an excellent source of inspiration for scientists and engineers to design and control the next -generation autonomous underwater vehicles within a bionic framework. Underwater biomimetic robots combine bionics and robot technology, and their biological characteristics offer a lot of convenience for the robot so that it can obtain better performance in adaptability and robustness. Recently, with the combination of bionics, mechanics, electronics, materials science, and automation, there has been great progress in developing underwater bionic robots with different structure types and energy supply modes. This paper summarizes the research status of underwater robots, focuses on the research status of underwater bionic robots with different materials, types and motion modes, and introduces the propulsion mechanism of underwater robots with different structures and the control methods adopted in the propulsion process. Finally, the broad application prospect and market potential of underwater biomimetic robot are introduced.

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1 Introduction

A bionic underwater robot, as the name suggests, is a new type of robot that imitates the propulsion mechanism and body structure of fish or other marine creatures living underwater using electromechanical components and intelligent materials (such as memory alloy materials, mixed materials, and rigid materials), which can adapt to different underwater environments and realize underwater propulsion (Chu et al. 2012 ). It has the characteristics of high efficiency, high mobility, and low noise (Chen et al. 2021a ). For a long time, scholars have been committed to studying marine biological propulsion models and bionic underwater robots. Underwater vehicles can be classified into two groups based on their structural design: cabled underwater vehicles, commonly known as remotely operated vehicles (ROVs), and cableless underwater robots, traditionally known as autonomous underwater vehicles (AUVs) (Wynn et al. 2014 ). Moreover, they can be categorized by use into underwater investigation robots (observation, measurement, test material collection, etc.) and underwater operation robots (underwater welding, pipe twisting, underwater construction, underwater cutting, etc.) (Vu et al. 2018 ).

At present, most underwater robots are frame-based, similar to the rotating elongated body of a submarine. With the continuous development of bionic technology, the bionic fish shape and control modes of underwater robots will also evolve (Xie et al. 2021 ). In this review, different control system algorithms are described, such as those developed for individual or cluster control of underwater robots (Khalaji and Zahedifar  2020 ). Underwater robots work in unknown and challenging marine environments. Complex marine environments, such as wind, waves, currents, and water pressure, severely interfere with robot motion and control, making communication and navigation of underwater robots very difficult. Thus, the development potential of underwater robots still needs to be continuously explored. In this paper, various underwater robots are reviewed and introduced from manufacturing materials, structural design, drive mechanism, and control strategy.

1.1 Shape memory alloy material

Shape memory alloys (SMAs) are solid, smart materials driven by current silently. The principle of operation is that when heated from low-temperature martensite to high-temperature austenite, SMA returns to the predetermined shape and generates activation, a process known as the reversed-phase transition (Yang et al. 2023 ). When cooled from austenite to martensite, SMA experiences a martensitic phase transition and returns to its initial state under bias stress (Hu et al. 2023 ). Previous works reported that the bionic starfish robot and the bionic manta ray robot fish were both powered by SMA.

The jellyfish robot, or Robojelly, developed by Virginia Tech, is driven by a bionic shape memory alloy composite actuator modeled after a jellyfish. With a body made of RTV silicone with a total mass of 242 g and a bell-shaped diameter of 164 mm, Robojelly can generate enough thrust to propel itself in static water conditions (Villanueva et al. 2011 ) (Fig.  1 a). Harbin Engineering University developed an underwater jellyfish microrobot prototype model based on SMA and ionic conductive polymer film (ICPF) as actuators to achieve swimming movement, with an overall size of microrobot of about 75 mm long, 55 mm in diameter, and 6.5 g weight. This tiny jellyfish-like robot has four tentacles (Fig.  1 b). Each mechanism consists of a restraint mechanism and an ICPF actuator, and each tentacle can work with an SMA driver to increase its range of motion and provide greater propulsion. The energized SMA shrinks the internal volume of the microrobot so that the water or other water-containing medium inside the microrobot is driven backward, thus forming a propulsion force (Yang et al. 2007 ). Another jet-propelled jellyfish bionic robot, MPA-O, developed by Harbin Engineering University, is made of SMA material. The length of the moving direction is 46.1 mm, and the section diameter is 36.3 mm. At an operating frequency of 0.6 Hz, the robot has a maximum speed of 6 mm/s (Guo et al. 2007 ) (Fig.  1 c).

SMA material underwater bionic robot. a Jellyfish robot (Villanueva et al. 2011 ); b  Jellyfish-like microrobot (Yang et al. 2007 ); c  Jellyfish-like micro robot that achieves MPA-O swimming mode using a hybrid actuator (Guo et al. 2007 ); d  Structure of the jellyfish-like robot (Ko et al. 2012 ); e  Microrobot manta ray (Wang et al. 2009 ); f  Fish skeleton structure including a latex-based skin for water protection (Rossi et al. 2011 )

The miniature jellyfish swimming robot, powered by the SMA system developed by Chonnam National University, has four flexible fins, each equipped with a permanent magnet for electromagnetic drive, and the body of the robot has a length of 17 mm and a thickness of 0.5 mm. The SMA driver can generate a uniform magnetic field in the desired direction in 3D space, which can bend the fins of the jellyfish-like microrobot. Thus, the cyclic changes in the uniform magnetic field will synchronize the fluctuations of the fins and generate a propulsive force for the robot in the desired direction (Ko et al. 2012 ) (Fig.  1 d). A miniature bionic manta ray robotic fish with a triangular pectoral fin driven by SMA, developed by the Harbin Institute of Technology, is based on the simplified pectoral fin model described in the joint. Each consists of a bionic fin on the leading edge and a latex film (0.2 mm thick) that forms the surface of the fin. The front part of the tail is attached to the body and is a flexible fin that can adjust the course (Wang et al. 2009 ) (Fig.  1 e). The SMA is used as a continuous backbone for curved fish, and the University of Madrid utilized six SMA-based actuators to make the skeleton of the robotic fish. Their length is 1/3 of their body length (8.5 cm, excluding the tail fins and head). They are positioned in pairs parallel to the body so that antagonistic motion can enable the robotic fish to resist higher water pressure (Rossi et al. 2011 ) (Fig.  1 f).

Jellyfish robots developed at Kagawa University achieved flutter-like motion with SMA-based actuators and positive spring elements (Najem et al. 2012 ). The robot was 63 mm long, 35 mm wide, and 18 mm high, the same size as the manta ray robot previously developed by the laboratory, which was constructed with SMA wires embedded in an elastic substrate (Xie et al. 2018 ). The jellyfish robot’s fluctuating motion is generated by 10 SMA actuators (5 on each side) with a maximum speed of 40 mm/s at 3.125 Hz, and the Department of Health Sciences and Technology of ETH Zurich (Vogel 2012 ) developed another jellyfish-like robot with jet propulsion via an SMA-based actuator. The drive is called bionic shape memory alloy composite (BISMAC). BISMAC is assembled from a steel spring and SMA wire embedded in a silicone precision connection (Ma et al. 2019 ) and has a length of 110 mm and thickness of 0.1 mm, while the bell has diameters of 134 and 82 mm. The robot is 242 mm long, 225 mm wide, and 52 mm high. Because its main component is silicone, it has greater hardness, strong compressive performance, and a speed of 35 mm/s. Traditional robots are machined from rigid materials, which often limits their ability to deform and adapt their shape to the external environment. Although these rigid robots have the advantages of large output force, high precision, and strong controllability, they often lack the multifunctional characteristics of natural organisms. Flexible robots comprising SMA materials can achieve elastic deformation and pass through narrow spaces without causing internal damage (Hu et al. 2019 ).

1.2 Ionic polymer–metal composite

Biomimetic artificial muscle material is a new type of intelligent material developed rapidly in the 1990s, constantly setting off a global research upsurge and has important application value in the aerospace, biomimetic robot, and biomedical engineering fields. Ionic polymer-metal composites (IPMC), as electrochemical actuators, are typical biomimetic artificial muscle materials (Şafak and Adams 2002 ) with a sandwich structure comprising two layers of electrodes and ionic polymers. Under the electric field, electrical and mechanical energy can be converted by the reversible dissociation process of ions at the electrode interface. IPMC material has the advantages of fast response, large drive displacement, and low drive voltage. However, it can only be used in wet environments and has huge limited applications in amphibious bionic robots (Cao et al. 2022 ).

IPMC is widely used in the manufacture of body or caudal-fin (BDF) swimming robots, and the fish-like robot developed by the New York Institute of Technology is designed with IPMC materials, which mimics the general swimming movement of a fish, protecting itself with its tail fin (Marras and Porfiri 2012 ). In 2010, Michigan State University developed a wireless bionic robotic fish that also successfully demonstrated the swimming mode of the BCF using a robot based on IPMC as the driving material, which had four different types of fins mounted on its tail to optimize the relationship between robot speed and fin shape (Brown and Clark 2010 ). The University of Science and Technology of China employed the IPMC brake as the tail fin of the robot fish for propulsion, which mainly comprises two servo motors, namely, angle rotating block pairs and brakes, and the main body is arranged symmetrically. The experiment confirms that the robot fish with the two degrees of freedom caudal-fin propulsion mechanism can realize various basic swimming movements by using a caudal fin (Zhou et al. 2017 ) (Fig.  2 a). The University of Nevada studied a biomimetic jellyfish robot powered by an IPMC placed inside a silicone dome. Because the selected jellyfish shell elastomer material is soft enough, the IMP can be easily driven without hindrance, and the robot can increase thrust production by approximately 1300% compared to a normal jellyfish (Trabia et al. 2016 ) (Fig.  2 b).

IPMC material robot fish. a Prototype of the robotic fish (Zhou et al. 2017 ); b  Robot jellyfish prototype (Trabia et al. 2016 ); c  IPMC material jellyfish robot (Yeom and Oh 2008 ); d  Robot fish propelled by IPMC (Hu and Zhou 2009 )

The University of Virginia developed a biomimetic robot that mimics a manta ray’s pectoral fin, which partially comprises a PDMS (polydimethylsiloxane) membrane using four IPMCs (0.28 mm thick) (Sankaranarayanan et al. 2008 ). Jeonnam National University utilized IPMC actuators to build and evaluate biomimetic jellyfish robots. The existing IPMC actuators limit their application fields due to their flat shape, which is a severe defect of this actuator material. To overcome the disadvantages of planar IPMC actuators, a curved IPMC actuator with predetermined initial deformation is developed. The expected initial deformation is acquired by heat treatment. The bionic input signal is generated by imitating the real movement of jellyfish (Yeom and Oh 2008 ) (Fig.  2 c). The experiment confirms that the jellyfish robot can move normally. IPMC is an important electroactive polymer (artificial muscle) with built-in drive and sensing capabilities. The robotic fish developed by the Intelligent Microsystems Laboratory at Michigan State University comprises IMPC material. Its motion mechanism includes the following: IPMC usually includes a thin ion exchange membrane, which is chemically plated on two surfaces with precious metals as electrodes. Application of voltage to the IPMC leads to the transport of hydrated cations and water molecules within the membrane and the associated electrostatic interactions to result in bending motion, leading to a driving effect (Hu and Zhou 2009 ) (Fig.  2 d). The artificial muscles of biomimetic robots’ balance drive the performance, power-to-weight ratio, and muscle form factors. As such, they are ideally suited as biomimetic actuators for various robotic applications. In the past decade, research and application of robotic artificial muscles have been developed (Wynn et al. 2014 ). More fundamental research is required regarding how artificial muscles can be manufactured, modeled, controlled, and engineered to acquire fish-like muscle properties and achieve muscle-like behavior.

1.3 Piezoelectric composite ceramics

A group of researchers from the Artificial Muscle Research Center at Konkuk University in South Korea developed a bionic fish robot that utilizes its tail fin to drive the swimming motion of BCF (Pham et al. 2023 ) and used a lightweight piezoelectric composite ceramic (PZT), a single crystal piezoelectric ceramic encased in glass/epoxy and carbon/epoxy resins, as the actuator material. The robot uses a crank, rack, and pinion structure (the size of the robot is increased by 400 mm due to the need for an additional device to achieve the movement). The robot has a maximum speed of 25.16 mm/s at an operating voltage of 300 vpp and an operating frequency of 0.9 Hz.

The miniature underwater mobile robot developed by Professor Toshio Fukuda of Nagoya University in Japan contains piezoelectric ceramics to drive the oscillation of two symmetrical legs to realize its movement. The two legs of the robot are equipped with a pair of symmetrical fins at a certain angle. The symmetrical structural design can offset the lateral force and strengthen the forward momentum. A 250-fold elastic hinge amplification mechanism is designed to amplify the PZT. The robot is 320 mm long and 190 mm wide, and the motion speed is 21.6–32.5 m/s. In 2009, the Marine Science Center of Northeastern University in the United States developed a robot fish with wave propulsion using PZT materials and chain rod structure (Zhou et al. 2008 ). Through lateral body fluctuations, the robotic eel drives itself through the water column and controls its floating depth. In 2008, DRAPER Lab launched VCUUV (Vorticity Control Unmanned Underwater Vehicle), a piezoelectric ceramic-driven robot fish designed after tuna (Suk and Hwan 2014 ). It is about 2.4 m long and weighs 300 lbs. Its maximum swing frequency is 1.5 Hz, with a maximum swimming speed of 1.25 m/s at 1 Hz. The goal of the laboratory is to develop an autonomous underwater vehicle using eddy current-controlled propulsion and show that PZT materials have good drag reduction characteristics, excellent maneuverability, depth-holding ability, and higher acceleration and deceleration ability through free swimming. Harbin Engineering University (Yue et al. 2015 ) developed a water microrobot with a PZT drive; the main feature of this drive is that it is a polymer material actuator only in water or wet environment work. The robot, which can be turned forward, left, or right, has a pair of driving wings driven by a pulse voltage to generate propulsion. PZT material can realize the continuous fluctuation deformation of the fluctuating fins of bionic fish, which makes it compact in structure, light in weight, and high in efficiency. This kind of robot has broad application prospects and value in microtubule detection and biomedicine.

1.4 Mixed materials

The underwater environment is complex, so the material requirements of the underwater bionic robot are very strict. Currently, polymer-metal composite materials are widely employed, combining the advantages of both the polymer and the metal. Polymers can withstand a certain degree of deformation in most environments. Both materials can make good adjustments to the impact of the external environment, with the polymer being lighter and the metal material being harder (Zheng et al. 2020 ). The robot fish developed by Shandong University of Technology is made of a resin-mixed material and a rigid motor, with four main parts: two laminated tail fins, a rigid fish body with a permanent magnet at the tail, a miniature battery, and a controller. During the driving process, electrical energy is converted into mechanical energy of the tail fin, producing the swimming motion of the robotic fish (Yan et al. 2021 ) (Fig.  3 a). Kagawa University has developed a medusa-like underwater bionic microrobot based on SMA and artificial muscles. It moves like a jellyfish, floats and sinks, and has two pectoral fins to achieve swimming motion (Shi et al. 2010 ) (Fig.  3 b). The mollusk developed by Zhejiang University includes a steering electronic server, a steering tail, and two SMA flapping wings. Two dielectric elastomer (DE) membranes are clamped onto the electrodes to form an artificial muscle. Precut frames and precut rebar are glued to each side of the muscle. The purpose of the insulation board is to prevent the feed pipe to make contact with the support frame. The flexible wavy fins provide power when the wings are in the flapping, stretching, or actuating state. When AC voltage is applied, the wing changes back and forth between the former state and the driven state, providing forward force (Zhang et al. 2021 ) (Fig.  3 c).

Mixed-material robot. a Composite robotic fish structure (Yan et al. 2021 ); b  Prototype jellyfish-like biomimetic underwater microrobot (Shi et al. 2010 ); c  Mechanism composition of the soft robotic fish (Zhang et al. 2021 ); d  Dolphin robot (Shen et al. 2013 ); e  Composite robotic fish (Xie et al. 2020 ); f  Illustration of the robotic fish (Marras and Porfiri 2012 )

DE, which is widely used in robot drives, has good softness, and its outstanding advantages are that the relative adjustment rate after shape change is fast, the response is quite rapid, the energy consumption is less, and the mechanical and electrical conversion efficiencies are high. The dielectric elastic material-driven robot developed by Kagawa University is a jet propulsion robot simulating a pike (Bal et al. 2019 ). The driver is composed of SMA, ICPF, and rubber materials. The length of the motion direction is 46.1 mm, the diameter of the section is 36.3 mm, and the maximum speed of the robot is 6 mm/s. The dolphin robot developed by Beihang University consists of three parts: (1) a rigid plastic shell that acts as a body, (2) IPMC stripes that act as muscles, and (3) a plastic sheet that mimics a tail fin. The shell is designed based on the proportions of the dolphin’s streamlined body, made of nylon plastic, using a 3D printer, and covered with a black matte resin varnish, leading to a smooth surface. The IPMC is attached to the body by two small rectangular conductive copper plates, which act as clamps, with a flexible fin attached to the end of the IPMC, which is designed based on the shape of a natural dolphin fin. The robot can jump and swim freely like a dolphin (Shen et al. 2013 ) (Fig.  3 d). The bionic robotic fish developed by the Chinese University of Hong Kong includes a rigid head, a wired-driven active body, and a flexible tail. A pair of SMA spring plates with the same stiffness pass through an active body comprising multiple connecting rods, which are like the backbone of a real fish, and then distribute a pair of wires along the spring plate to drive the moving body. The robotic fish tail is a flexible tail made of silicone and carbon fiber reinforced material that allows the robotic fish to swim in multiple modes, such as cruising, turning, rising, and descending (Xie et al. 2020 ) (Fig.  3 e). The robotic fish designed by the New York University consists of a rigid acrylonitrile butadiene styrene (ABS) plastic body shell and a tail consisting of rigid ABS elements and flexible polyester tail fins. The robot fish uses a waterproof servo motor to control the tail, and a flexible tail fin allows the tail to bend and undulate to mimic the swimming of a live fish. The tail beat frequency and amplitude of the robot are controlled by an external microcontroller. The signals driven by the servo motor generate the periodic sinusoidal movement of the flexible polyester tail fin to mimic the movement of fish (Marras and Porfiri 2012 ) (Fig.  3 f).

2 Underwater robot control system classification

At present, the commonly used motion control methods of underwater biomimetic robots are model-based control methods, sine controllers, and central mode generator (CPG)-based methods. As the structural components of marine biomimetic robots usually include power modules, sensors, chips, and driving components, the behavior of the bionic robot is controlled by the predefined program or the command controller (the power supply of the controller is mainly provided by traditional lithium batteries) (Chen et al. 2021b ). Depth adjustment of the robot in water is controlled by the controller and is mainly completed by the buoyancy unit. Thus, control can also be divided into rigid motor control and soft drive control.

2.1 Model control method

The model control method is performed by analyzing the dynamics and kinematics of the robot and then establishing a complex mathematical model. The mathematical model can accurately calculate the next movement of the robot to achieve the effect of precise control. However, due to the complex and changeable underwater environment, accurately modeling the robot is very difficult. Even if it can be accurately modeled, its control mode is very complex. In 2014, Inner Mongolia University of Technology (Li et al. 2014b ) developed a set of integrated and efficient driving devices that can control the swing of the fishtail to achieve different amplitudes, different frequencies, and different central positions and realize the functions of acceleration, deceleration, and steering of the released robot fish. Based on elastic plate deformation theory, the design size and motion input of the elastic plate are inversely solved according to the motion function of the actual fish, which makes the deformation motion of the elastic plate highly fit the fishtail swing in reality. The 3D modeling and fluid simulation of the fish body were performed, and the geometric size and motion mode of the prototype were optimized. The bionic robotic fish has good sealing properties in water and can adjust its posture to achieve the flipping and pitching functions. In 2019, the School of Mechanical Engineering, Baicheng Normal University (Wang et al. 2019a ) proposed the concept of 'fundamental wave', including deformation description and linear density description, established the fish body wave model of the bionic robotic fish, formed the control method system of the multijoint bionic robotic fish’s stable swimming propulsion, and achieved the efficient and stable swimming of the bionic robotic fish. In 2022, an underwater soft robot was successfully developed by a joint team from the Max Planck Institute for Intelligent Systems in Germany, Seoul National University in South Korea, and Harvard University in the United States (Ning et al. 2022 ). The robot can swim underwater like a fish and automatically adjust its swing in the water according to the speed of the water. To design the controller for the robotic fish, the research team developed a data-driven, lumped parameter modeling method, which allows for accurate but lightweight simulations using experimental data and genetic algorithms, and the model can accurately predict the robotic fish’s behavior at drive frequency and pressure amplitude, including the effects of antagonistic co-contraction on soft actuators (Li et al. 2023 ). Currently, most of the simplified mathematical models are used for control. Still, the accuracy of the simplified mathematical models is poor, and the robustness of the control system is poor, which makes the underwater bionic robots designed by this method have poor adaptability to the underwater environment.

2.2 Central pattern generator (CPG)

The main control principle of the CPG is to utilize the mathematical model of the neuron network to drive the joint movement by imitating the movement law and biological control mechanism of the animal itself. The School of Intelligent Systems Science and Engineering at Harbin Engineering University (Wang et al.  2019b ) used four oscillators to construct a CPG network model to control the pectoral fin and tail fin with two degrees of freedom of multimode bionic robotic fish, which introduces the angle between the head and tail axis and the horizontal plane and the yaw angle as feedback information to control the swimming posture of the robotic fish and conducted in-depth discussion on the motion control of the pectoral fin. The basic swimming strategy is developed based on Walker’s oscillating pectoral fin model. Based on the multijoint robot fish model, the National University of Singapore extracted two basic imitation swimming modes, 'cruise' and 'C-type sharp turn', from the swimming observation of real fish as training samples. The general internal model imitates the CPG of the nervous system used to learn and regenerate the coordinated behavior of fish. This learning method can use general function approximation capability and time/space scalability to generate the same or similar fish swimming patterns by adjusting two parameters. The learned swimming mode was realized in the experiment of multiarticular robotic fish (Ren et al. 2013 ) (Fig.  4 a). Waseda University built and studied a CPG network with nonlinear oscillators for the gait generation of robotic fish and developed a robot that uses a CPG for fish-like motion underwater. These studies reveal that CPG-based approaches are easy to design, fast to implement, and capable of online adjustments (Chen et al. 2020 ) (Fig.  4 b).

CPG controls the bionic robot. a Robotic fish covered with waterproof tape swimming in the water (Ren et al. 2013 ); b  Fabrication process of the silicone tail and the outer view of the robotic fish (Chen et al. 2020 ); c  Closed-loop CPG-based control can drive the robot fish (Chen et al. 2021b ); d  Prototype of multimode robotic fish (Zhao et al. 2006 )

The CPG model includes four input parameters, namely, flutter amplitude, flutter angular velocity, flutter offset, and the time ratio of the beat phase to the recovery phase in the flutter. The robot fish developed by the South China University of Technology is equipped with three infrared sensors installed on the left, front, and right sides of the robot fish, as well as an inertial measurement unit that can sense the surrounding obstacles and the direction of movement. Based on these sensor signals, CPG-based closed-loop control can drive the robotic fish to avoid obstacles and track the specified direction (Chen et al. 2021b ) (Fig.  4 c). The Peking University-developed robotic fish uses CPG modeling as a nonlinear oscillator for joints to realize coordination by altering the connection weights between joints. The online gait generation method based on CPG makes the transition between swimming gaits elegant and smooth to realize multimode swimming and achieve a more realistic movement. By changing the CPG parameters, various swimming patterns can be obtained to simulate the various movements of real fish in nature or designed based on special tasks (Zhao et al. 2006 ) (Fig.  4 d). The Chinese Academy of Sciences (Yu et al. 2016 ) proposed a particle swarm optimization (PSO)-based CPG control system for underwater vehicles. In general, the parameters of the CPG are determined manually based on experience and computer numerical simulation. In this method, the traveling wave parameters of robotic fish are given manually, and 19 parameters, such as the optimal CPG connection weight, self-inhibition coefficient, and time constant, are selected through the PSO algorithm according to the fish body wave equation. Simulation and experiment show the effectiveness of this method. The Hirose Laboratory of Tokyo Institute of Technology (Nagai and Shintake  2022 ) adopted the CPG control network comprising this oscillator to control the robot, that is, a multijoint snake robot. The robot has 10 actuating units, constituting a bilateral wave propulsion mechanism with bionic left and right counter muscles. The CPG control network can generate rhythm joint angle control signals and achieve the yaw maneuvering of the robot. The simulation test confirms the feasibility and effectiveness of the control system (Alexander  2017 ). This control method simulates the central nervous system well, generates continuous and coordinated control signals, and then gives timely feedback to different environments. This method is conducive to coordinated control and has a better environmental adaptation effect, so it is widely used.

2.3 Sinusoidal controller control method

A sine controller is a kind of control method that is widely used by researchers based on the fact that the waveforms and motion periods generated by how fish are propelled are similar to sine functions. Thus, the sine controller simplifies the motion process of fish into the frequency, amplitude, and waveform of the sine function and then controls the motion of each joint of the underwater bionic robot through these parameters. At the same time, it changes the motion state by relying on the phase difference of the motion between different joints of the robot. The advantages of this control mode are simplicity and easy controllability. In 2015, the robot fish 'Pike' was born at the Massachusetts Institute of Technology; the hardware system of the robot fish 'Pike' includes a head, a pectoral fin, a tail fin, a dorsal fin, a main servo sine controller system, a pectoral fin servo system, and a battery (Li 2015 ). In 2014, the Tokyo Institute of Technology developed a self-propelled robot dolphin with two joints and an autonomous drive controller (Nakashima and Karako 2014 ). The robot dolphin is a simplified model of a high-speed swimming marine creature with a length of 1.7 m, which is very close to the size of the actual dolphin. The robot dolphin has a linear body and a rectangular tail fin. An air motor drives the first joint, and the second is driven by a spring. A measurement system is developed to measure the torque and angle of the first joint. The Polytechnic University of Milan (Bottasso et al. 2008 ) successfully controlled a pair of pectoral fin joints and caudal-fin joints of a robotic fish by using a sinusoidal controller and vibrator (a topology with three oscillators adjacent to each other). By movement of pectoral and caudal joints, the robot can achieve various underwater swimming actions. The experimental results show that the control method can realize stable swimming. Due to the uniqueness of the function types in the controller, this method has limitations. If there is a motion mode that does not belong to the function characteristics, it cannot be accurately regulated. In addition, this control mode has poor adaptability when dealing with the sudden change of control parameters, and it cannot quickly adjust from one motion mode to another, leading to poor environmental adaptability of the robot.

2.4 Rigid motor drive

Most marine bionic robots are driven by rigid motors. Since motor-driven robots are easier to implement in terms of systems than flexible-driven robots, which can fully use the high energy density and high efficiency of motors, rigid motor-driven bionic robots are more convenient for specific purposes (Karthik 2014 ). They are currently more mature in development than flexible-driven bionic robots. For rigid motors, waterproof housing is often needed, with high sealing requirements and greater challenges in terms of water pressure (Dawson and Allison 2020 ).

For bionic robots driven by rigid motors, there are mainly single-motor drives and multimotor drives. Multimotor drive means that the system has more flexibility, but there are more limitations regarding structure and size, and it can carry many functional sensors. Examples include the UK Natural Environment Council’s (NERC) 5.5-m long 1800 kg-dry weight Autosub6000 AUV, which is rated to a depth of 6000 m, can be equipped with a variety of payloads for marine geoscience research, includes high-resolution multibeam echo sounders, seabed profilers, and side-scan sonar, color camera systems, conductivity, temperature, depth, and electrochemical redox (Eh) sensors. It has precise navigation and terrain tracking capabilities and has a sophisticated collision avoidance system (Wynn et al. 2014 ) (Fig.  5 a).

Rigid motor-driven robot. a AUV submarine (Wynn et al. 2014 ); b  SPC-I (Wang et al. 2005 ); c  SPC-II (Liang et al. 2011 ); d  Working environment of SPC-III in the Taihu Lake (Liang et al. 2011 ); e  G9 robotic fish profile (Liu and Hu 2006 ); f  Top view of the robotic fish representing the robot’s undulating tail (Kopman and Porfiri 2013 )

The Robotics Institute of Beihang University successfully developed the bionic robotic eel, bionic robotic dolphin, experimental small robotic fish, and trail-tail bionic robotic fish SPC-I, SPC-II, and SPC-III (Wang et al. 2005 ) (Fig.  5 b) driven by an electric motor and wireless remote-control rigid actuator (Li and Jiang 2012 ), as shown in Figs.  5 c and d. Compared with conventional motor-driven robots, the maneuverability of the bionic underwater robot is significantly enhanced. This series of robots were applied to underwater archaeological discovery, experimental teaching, ocean cruise experiments, and water quality detection and achieved good results. The Harbin Engineering University-developed bionic underwater robot is driven by two servo rigid motors with tail fins and an interactive gear system, which can achieve various complex movements, as well as two articulated serpentines, HRF-I and HRF-II bionic robotic fish (Tian et al. 2022a ). Compared with the former, the latter can achieve steering, snorkeling, and reversing, and the performance in all aspects has been greatly improved. The Department of Computer Science at the University of Essex conducted experiments with a rigidly driven robotic fish G9 equipped with a variety of sensors and found that it can respond to dynamic changes in its environment, capturing its position in the tank and the robot’s posture and internal state, with good drive performance (Liu and Hu 2006 ) (Fig.  5 e). The New York University Institute of Technology designed a robot’s body shell comprising a payload and a motor bay. The payload bay contains control electronics, batteries, and counterweights to enhance pitch and roll stability and achieve appropriate buoyancy. More specifically, buoyancy is set so the robot is almost completely submerged during operation. The cap provides a waterproof seal for the payload bay and extends toward the rear of the robot, partially covering the engine room. A toggle switch hidden in the lid extension turns the robot on or off. The motor compartment houses a Traxxas 2065 waterproof servo motor for the drive, which is connected to the rear by an improved servo motor horn. The caudal fin is snug in a slit at the free end of the caudal fin (Kopman and Porfiri 2013 ) (Fig.  5 f).

Single motor-driven marine bionic robots are often used in fish bionic robots, which have a single function and are not flexible enough in movement, such as the bionic fish studied by Northern Research Center for Science and Technology at Malek Ashtar University of Technology (Sabet and Nourmohammadi 2022 ) and the voice-activated soft robot fish studied by Robert. The Massachusetts Institute of Technology (MIT) Distributed Robotics Laboratory developed a single-motor driven robotic fish, a soft robotic fish system whose subcomponents include an elastomeric tail, an external gear pump, two diving surfaces, and control electronics, including an acoustic receiver and a fish eye-eye camera that can complete underwater reconnaissance missions (Katzschmann et al. 2018 ) (Fig.  6 a). The robotic fish designed by the College of Worcester employs a flexible body with embedded rigid actuators that mimic the elongated anatomical form of a fish. Also, the robot has a novel fluid drive system that drives body movement and has all the subsystems of traditional robots: power, drive, handling, and control. A set of fluid elastomer actuators is at the heart of the fish’s soft body. The soft robot has an input-output relationship similar to a biological fish, allowing it to be self-sufficient and capable of fast movement (Marchese et al. 2014 ) (Fig.  6 b). The Electrical Engineering and Computer Science Department of the University of Michigan (Ozog et al. 2017 ). The robot adjusts its height through a buoyancy module, and a motor in the tail provides power and adjusts its direction. The flexible part of the robotic fish, designed by the State Key Laboratory of Complex Systems Management and Control at the Institute of Automation, Chinese Academy of Sciences, consists of three joints connected by an aluminum exoskeleton. Each joint is connected to an R/C servo motor that controls the rotation angle of the joint. The rubber caudal fin is connected to the third segment by the peduncle and is crescent-shaped with good coordination (Yu et al. 2016 ) (Fig.  6 c). The robot fish designed by the University of the Chinese Academy of Sciences employs a magnetic actuator as a motor. The propulsion system is characterized by remote control using Bluetooth low power and easy operation through smart devices. By the electromagnetic induction law, the robot fish can swim quickly and turn flexibly. This miniature robot fish could be employed for animal behavior research and special underwater tasks (Chen et al. 2017 ) (Fig.  6 d).

Single motor-driven bionic robot. a Soft robotic fish and diver interface module (Katzschmann et al. 2018 ); b  Details of a soft-bodied robotic fish (Marchese et al. 2014 ); c  Prototype of the robotic fish applied to the underwater robot competition (Yu et al. 2016 ); d  Mechanical design of the robotic fish (Chen et al. 2017 ); e  FILOSE robot fish (Salumäe and Kruusmaa 2013 ); f  Robot fish with a wire-driven active body and compliant tail (Haji and Bamdad 2022 )

The Key Laboratory of Marine Engineering in Shandong Province developed a motor-driven robotic fish with artificial side-line sensors that can help enhance the fish’s maneuverability in dark environments. Artificial sidelines simulate the structure of fish sidelines, offering possibilities for underwater sensing technology and robotic fish control (Salumäe and Kruusmaa 2013 ) (Fig.  6 e). Researchers from Shahrud University of Technology studied a robotic fish with a streamlined drive body and a flexible tail, comprising a network of pressurized liquid-filled chambers embedded in an elastic beam. Viscous fluids with different pressures flow in the channel, producing normal and shear stresses in the channel, which can make the robot fish adapt to different water pressure environments (Haji and Bamdad 2022 ) (Fig.  6 f).

The salamander robot has a modular design comprising seven drive elements and a head element (with the same appearance as the others). The housing of each element includes two symmetrical parts molded with a lightweight polyurethane resin. These components are connected using compatible connectors fixed to the output shaft. All output axes are aligned, so plane motion is produced. To ensure that the robot is waterproof, a custom O-ring robot is used with a total length of 77 cm. Asymmetric friction with the ground, which is required to crawl on the ground correctly, is achieved by fixing a pair of passive wheels to each element, thus ensuring a coordinated transition between swimming and crawling of the robot (Crespi and Ijspeert 2008 ) (Fig.  7 a). The four-legged starfish-shaped soft swimming robot’s flexible and natural buoyancy offers many advantages for tasks such as underwater exploration, sample collection, and marine wildlife observations (Du et al. 2021 ) (Fig.  7 b). In Fig.  7 c, the swinging body of the bionic robotic fish is a multilink mechanism connected by hinges and equipped with multiple motors. In swimming, the required body curve can be acquired by adjusting the relative position of each connecting rod, optimizing its control performance and swimming efficiency compared with a single motor (Korkmaz et al. 2012 ). Inspired by the amphibious tortoise, the mother robot is designed with a spherical body, four legs, and two degrees of freedom. Powered by 4 vector water jets and 10 servo motors, it can walk on land and cruise underwater (Shi et al. 2013 ) (Fig.  7 d). The enhanced 3D printing, low cost, multifunction, high mobility, tortoise-like environmental monitoring, and data acquisition mobile amphibious spherical robot by Beijing Institute of Technology has good amphibious performance (Guo et al. 2018 ) (Fig.  7 e). The cuttlefish robot studied by the University of Nevada researchers is powered by two soft fins of multiple embedded IPMC drive motors connected to an Eco-Flex membrane. The traveling wave is generated on the soft fin by drive, the deformation and blocking force of IPMC on the soft fin are measured, and the actuator is characterized, which can have good wave swimming performance in water (Shen et al. 2020 ) (Fig.  7 f).

Multimotor driven bionic robot. a Salamander (left) and fish (right) robots (Crespi and Ijspeert 2008 ); b  Soft starfish (Du et al. 2021 ); c  Demonstration of the body curve fitting method (Korkmaz et al. 2012 ); d  Prototype of the spherical mother robot (Shi et al. 2013 ); e  Amphibious spherical robot (Guo et al. 2018 ); f  Multimotor driven fish robot (Shen et al. 2020 )

Recently, bionic amphibious robots have developed profoundly in bionic structure design, movement performance, and outdoor workability. Researchers from Harbin Engineering University (Li et al. 2021 ) developed a shape-shifted bionic turtle that can travel in water and walk on land. To enhance the reliability of bionic robots in the future, these robots designed for engineering applications are driven by electric motors and are constantly improved. However, due to their performance limitations, large size, and high power consumption, the size and range of motors have become significant limitations.

2.5 Soft actuator drive

For bionic robots driven by responsive soft actuators, often by imitating the movement patterns of marine organisms, artificial muscles are used to cause propulsion by deformation under control of voltage, and although their power and precision cannot be compared with those of electric motors, responsive soft actuators are stimulated to perform better in terms of high adaptability due to their excellent compliance.

Meanwhile, soft actuator-driven bionic robots are widely used in some miniature marine robots because of their smaller size requirements due to the absence of motors, and soft actuators also have a huge advantage regarding range because they usually consume less power when used compared to motor drives (Gao et al. 2022 ). In 2018, the Precision Engineering Institute designed a new robotic fish with an active and compliant propulsion mechanism, a maximum swimming speed of 2.15 body lengths per second, and a maximum instantaneous turning speed of 269°/s (Shintake et al. 2018 ). In 2014, Marche University of Technology designed a Carregi-shaped swimming robot through a multiphysics simulation environment, which can change from a bone-like motion to a Caran-shaped motion (Praczyk 2014 ).

The Harvard University-designed completely soft octopus robot has all parts of its body made by 3D printing technology and feels slightly slimy to the touch. The soft robot has morphing and cushioning and can travel through small, irregular spaces, which can be useful in the medical, military, and exploration fields (Wehner et al. 2016 ) (Fig.  8 a). The octopus robot, developed by Queen Mary University of London, is made entirely of soft materials and employs a new fluid drive mechanism that allows the robot to push forward, change direction, and rotate around its main axis. In addition, it can use multiple tentacles to grab objects or propel them underwater (Fras et al. 2018 ) (Fig.  8 b).

Soft actuator-driven bionic robot. a Octopus robot (Wehner et al. 2016 ); b  Multitentacle fish robot (Fras et al. 2018 ); c  Soft electronic fish (Li et al. 2017 ); d  Whole body stiffness research (Chen and Jiang 2019 )

The soft-bodied fish developed by Zhejiang University is powered entirely by a soft electroactive structure made of a DE and an ionic conducting hydrogel. The robot fish can swim at a speed of 6.4 cm/s (0.69 body length per second), which is much faster than a soft responsive material-powered previously reported soft robotic fish (Li et al. 2017 ) (Fig.  8 c). In Fig.  8 d, the flexible robotic fish is a transitional stage between rigid robotic fish and flexible robotic fish, with typical soft materials and traditional driving methods (Chen and Jiang 2019 ). Because the soft material has large elastic deformation, it can be restored to its original shape, and the soft material of the robot fish can be used to protect the actuator and waterproof (Liu and Jiang 2022 ). With the development of bionics and materials science, marine release robots are increasingly driven by a variety of methods, and typical stimulus-responsive actuators include IPMC, SMA, responsive hydrogels, pneumatic structures, chemically responsive expanded fluid networks, and living cells (Bai et al. 2021 ). Using simple principles and widely available materials, the highly integrated electric drive module not only eliminates bulky pumps, pipes, and other equipment but also enables precise control of deformation, while the compact form factor also increases portability.

3 Bionic robot drive mode and control strategy

Traditionally, underwater robots have been classified based on Breder’s fish classification: if a fish generates thrust by bending its body/or caudal fins, the resulting motion is classified as a BCF motion. Fish such as eel-shaped, flesh-capsule, tuna, eel and shark can be categorized into BCF types (Jiao et al. 2022 ). However, suppose that fish uses their mid-fin (including anal, dorsal, and pectoral fins) or paired fins (including ventral and pectoral fins) as propulsion mechanisms, the resulting swimming pattern is classified as a mid-fin or paired fin (MPF) movement (Wang and Wang 2014 ). Regardless of the mode of propulsion used, fish movements are characterized by deformed bodies, fluid forces, and their interactions. Moreover, each mode of motion can be classified by wave frequency as fluctuating and oscillating, as can be seen in fish movements.

Oscillatory motion can be applied when the fish generates propulsion from wave-like motion. Otherwise, if the fish uses a rotation-like motion to obtain thrust, this motion can be classified as oscillatory. These two classifications cannot be separated because oscillatory motion can be derived from the fluctuating motion of shorter wavelengths and vice versa. Eels, which usually use their whole body to produce wave-like motions, can be classified as fluctuating motions, while box fish, which only make their tail fins swing due to body inflexibility, can be classified as oscillatory motions. However, in this fish-based classification, problems emerge in the general classification of animal species (Zhang et al. 2017 ). Especially in robotics, there is no restriction to imitate the motion mechanism and shape of fish. Following the traditional fish classification is still difficult if the motion mechanism and shape of the robot are somewhat different from the target animal.

Thus, in this review, a simplified classification model for the robotics domain is put forward. First, similar to BCF- and MPF-type motions in the fish classification, robots can be classified as body or tail-end anal (BCA) and mid-end or paired anal (MPA) (Wang et al. 2022 ). BCA and MPA are classified based on where the drive occurs relative to the central axis and the direction of robot propulsion. BCA achieves propulsion through drive motion along the central axis. However, in MPA, the driving motion occurs outside the central axis. Similar to the fluctuating oscillation classification of fish, the subcategory is set to fluctuating oscillation motion based on the motion of the robot actuator. Like in the fish classification, the fluctuating motion can be expressed as the fluctuating motion in the actuator. In the same way, oscillatory motion refers to the propulsion structure that rotates on its fixture instead of the wave-like shape.

3.1 Robot drive mode classification

3.1.1 mpf model.

The movement modes of fish are classified by body parts used by fish for propulsion into BCF propulsion mode and MPF propulsion mode (Zhou et al. 2023 ). In MPF propulsion mode, the dorsal, ventral, pectoral, and anal fins are mainly utilized as the main propulsion parts, which can maintain high mobility, stability, and swimming efficiency at low speed. In general, it can achieve accurate six degrees of freedom movement, underwater position holding, and steering, but it is difficult to achieve high-speed swimming and acceleration performance is insufficient. Lampreys, an eel MPF swimming robot developed by the Marine Science Center of Northeastern University, uses 10 TiNi filaments of 250 μm to be energized and heated as a motor (Wu et al. 2013 ). It has a simple structure, no noise, and good stealth performance. The fishtail propulsion of the robot designed in this mode is quieter than the traditional propeller, which is especially important in future naval battles. It can greatly improve stealth ability. Japan developed the first MPF robotic fish that can swim freely underwater; this bionic robotic fish is 650 mm long, 500 mm wide, and 0.64 kg, with floating, diving, turn signal, and other functions, and the smooth shape of the robot fish makes the efficiency of the fishtail propeller up to 80% (Scaradozzi et al. 2017 ). It uses the three-joint bionic tail fin as the only power source, with low power consumption, which can extend the battery life and is suitable for long-term underwater cruises, tracking, and other tasks. In 2021, Osaka University developed a pair of miniature fish out of silicone, which was only the size of a hand but could swim at 0.1 m/s (Xie et al. 2021 ). In 2017, Festo, a German company, developed the pectoral fin bionic robotic fish aqua ray with a body length of 615 mm, a wingspan of 960 mm, and a maximum speed of 0.5 m/s (Saxena and Chauhan 2017 ). The mechanical operation process of forward, backward, differential turning, pitching, and other actions of the bionic robot was completed by experiments and tests, completing the goal of the project. In 2009, the China Academy of Automation developed a small robot dolphin that is 560 mm long and weighs about 3.3 kg, which can complete special tasks such as marching, chasing, and searching (Xia et al. 2023 ). The National University of Defense Technology in China produced a prototype of a bionic pectoral fin powered by multiple fins. In the water tank experiment, the robot’s left and right fins moved simultaneously, with a forward speed of 0.13 m/s and a backward speed of 0.15 m/s. Due to the symmetrical structure and movement of the wave fins of the robot, they could smoothly change the gait from forward to backward without turning and move laterally by sending inward counterpropagation waves.

The Institute of Robotics of Beihang University and the Chinese Academy of Sciences successfully developed SPC-II bionic robotic fish, the first practical application of MPF bionic robotic fish in China (Lou et al. 2017 ). The SPC-II bionic robotic fish is 1.23 m long, with a shiny black body, a total weight of 40 kg, and a maximum diving depth of 5 m. It has a prominent camera above its head that collects location data. The SPC-II bionic robotic fish can move, sink, and float freely and flexibly in waves. The MPF bionic robotic fish robot-ray I, robot-ray II, robot-ray III, and robot-ray IV series were developed by Beihang University (Wu et al. 2021a ). Among them, the best-performing robot-ray IV is 320 mm long with a wingspan of 560 mm. The maximum swimming speed is about 0.16 m/s. Moreover, the robot fish has high underwater speed and better load capacity, and the underwater movement trace is smaller. It can perform quick close-in intercepts, search for enemy divers, highly maneuverable patrols, and track underwater targets at high speeds. The bionic underwater vehicle based on the MPF long-wave propulsion principle has the advantages of high mobility, strong anti-interference ability, and environmental friendliness (Korkmaz et al. 2015 ). Thus, research on this bionic underwater vehicle has a broad market prospect and application value.

3.1.2 BCF model

BCF propulsion mode enables most fish to swim by waving or swinging part of the body and tail fin using eddy currents to push the water behind to use the water reaction force to achieve the forward movement of the fish body. When cruising at high speed, high swimming efficiency can be achieved, generally, more than 80%, and the acceleration and starting performance are good. The bionic bull nose shark designed by Beihang University is a BCF robotic fish (Wang et al. 2021 ). The width of the first-generation bull nose shark robots is 28–46 cm, while that of the second-generation one can reach more than 110 cm. The robot fish is driven by two motors on both sides of the pectoral fin (60W DC motor drive); the flexible pectoral fin comprises silicone rubber material, the main material is made up of relatively low-density glass fiber, and the addition of gyroscopes can achieve autonomous navigation function. A steering engine drives the BCF robot eel developed by the Beijing University of Technology. The fin material is a composite material that can be applied to the eddy current environment with a large water flow (Song et al. 2013 ). The robot shark, developed by St. Mary’s College, University of London, also adopts the BCF drive mode (Watts and McGookin 2014 ). It is larger and adopts silicone fins, and the head’s central processor controls the robot’s movement, which can swim upstream in the rapids. The robot shark simulates a shark’s shape and swimming mode, with little disturbance to the environment and no harm to underwater organisms. The multilink glider robot, developed by the China Academy of Electronics and Information Technology, can swim flexibly and glide efficiently in 3D space and is equipped with the main BCF of a three-degree-of-freedom buoyancy drive system as the main propulsion device for stable propulsion in water (Wang et al. 2021 ) (Fig.  9 a). A Lanzhou Jiaotong University-designed BCF-propelled four-fin bionic prototype based on modular design has high efficiency, rich turning modes, good maneuverability, and high turning speed (Li et al. 2018 ) (Fig.  9 b). Jilin University has developed a carpal bone robot fish with a four-degree-of-freedom tail. The robot fish has two modes of radio control and autonomous swimming. The BCF mode has outstanding performance of high speed and high efficiency (Yan et al. 2008 ) (Fig.  9 c). Ferat University in Turkey has developed a bionic boat-shaped autonomous robotic fish prototype with a double-link tail propulsion mechanism. To simulate the robust swimming gait of fish, a bionic motion control structure based on CPG is adopted. The unidirectional chain CPG network designed is inspired by the neural spinal cord of lampreys and is propelled by BCF. It produces a steady, rhythmic pattern of oscillations underwater (Ay et al. 2018 ) (Fig.  9 d).

BCF mode swimming robot fish. a Main components of the FishBot (Wang et al. 2021 ); b Prototype of the proposed robotic fish (Li et al. 2018 ); c  Mechanical structure of the robotic fish (Yan et al. 2008 ); d  Detailed mechanical configuration of the robotic fish (Ay et al. 2018 )

In 2015, the Harbin Institute of Technology successfully developed a double-jointed Karan-shaped fish robot, code-named 'HRF-I', with a swimming speed of 0.5 m/s (Wang et al. 2015 ). In 2018, the University of Science and Technology of China designed a four-joint bionic robotic fish based on the morphological structure and movement form of the Karan-shaped fish (Zhong et al. 2018 ). In 2016, a BCF model bionic eel robotic fish with eight joints was developed in the United States, and in 2017, Beihang University developed a series of fibular bionic robotic fish with two parallel joints in the tail stalk and tail fin, driven by a two-axis servo motor (Yu et al. 2017 ). The simulated or caudal-fin BCF pulsating underwater thruster, developed by Osaka University in Japan in 2017, has flexible fins on both sides and is driven by 16 DC servo motors via the top fins. The robot fish can realize flexible underwater movements such as surface, diving, steering, pitching, and hovering, which confirms the viability of the application of undulation fin bionic underwater propellers to future underwater robots (Ravalli et al. 2017 ). Several flexible fish species, such as dolphins, sharks, and tuna, swim in BCF mode and can swim with high speed and efficiency. Based on this design, the BCF mode robot produces thrust by bending the torso and swinging the tail fin, leading to high swimming speed, high efficiency, and fast starting performance; thus, the BCF mode is suitable for applications such as long distance and high-speed swimming, instantaneous acceleration, or fast steering (Rajamohamed and Raviraj 2015 ).

3.2 Bionic flutter rigid drive

The fluttering rigid drive mode is a structure of self-excited vibration consisting of skeletal, muscular, and nerve centers (Wang et al. 2021 ). It is the main mode of large aquatic animals with large spreading chord ratios and thickness, such as turtles and penguins. It uses periodic changes in the bending and sinking posture of the up and down swinging forelimbs to regulate the water’s angle of approach. It can be controlled independently of the winging posture to produce forward thrust of the swim front itself, where the forelimbs swing in a process that produces orthogonal directional (negative) drag and lift forces, prompting the body to keep advancing (Todd et al. 2020 ). Although large, this biological body has the advantages of explosive power, high efficiency, stability, low noise, excellent maneuverability, and operational performance. Several theoretical and experimental works have been conducted on marine fluttering organisms by combining bionics from several disciplines. Based on this, a series of bionic flutter wing propulsion devices have been developed with beneficial results. The Chinese Academy of Sciences designed a four-joint robotic fish head, which is a hollow, rigid, and streamlined shell made of molded glass fiber that provides enough space for electromechanical components such as control circuits, sensors, rechargeable batteries, and balancing heavy objects. To duplicate the movement of fish, a series of multilink rigid motors connected by yaw joints are used as the main propulsion mechanism, followed by a slender tail shaft made of polyvinyl chloride and then a polyurethane tail fin with some elasticity. All the rods, driven by DC servo motors, are connected in series to a metal skeleton covered with a flexible waterproof skin that allows for flexible turns in water up to 213° (Su et al. 2014 ) (Fig.  10 a). The robot adopts motor modularity to facilitate loading and unloading. In Fig.  10 b, the Nanyang knife-fish robot contains three independent modules, namely, the buoyancy box module, power cabin module, and wave fin module. Because these modules are designed in a modular manner, these modules can be easily replaced if the design changes or additional features need to be attached (Low 2009 ).

Flutter rigid drive robot. a Slim fish robotic prototypes applied to C-start experiments (Su et al. 2014 ); b  Southern Ocean knife-fish module (Low 2009 ); c  Schematic structure of a G9 series robotic fish (Liu and Hu 2010 ); d  Prototype of biomimetic fish, NAF-I (Chong et al. 2009 )

To investigate the effects of electric motors on robotic fish, the University of Essex in the United Kingdom performed production tests on the G9 series of robotic fish, which are about 52 cm long and have three or four servo motors and two DC motors (Liu and Hu 2010 ) (Fig.  10 c). The servo motor is connected at the tail as three joints; the head is fitted with a DC motor that changes the fish’s center of gravity, and another controls a miniature pump that adjusts the robot’s weight by pumping water. Enhancements in the mechanical structure and skin materials have improved the efficiency and robustness of the robotic fish. The robot fish, NAF-I, weighs about 6.8 kg and is 650 mm long, 100 mm wide, and 260 mm high. It is powered by a 15 V nickel-metal hydride battery, allowing the fish prototype to swim for up to 4 h when fully charged. One DC motor drives the oscillating tail fin, and the other drives the counterweight, and the robot swims in a straight line at a speed of about 0.35 m/s, equivalent to about half a body length per second. It is also confirmed that the greater the thrust of the motor on the robot fish, the faster its swimming speed (Chong et al. 2009 ) (Fig.  10 d). To produce greater thrust, the choice of motor parameters becomes very significant.

Research on bionic flutter drive systems has never stopped. Still, due to the complexity of the drive mechanism and its unique motion characteristics and the different research methods, the forms of flutter wing propulsion are also different (Zhu 2018 ). So far, it has been impossible to conduct a theoretical study for various bionic drive mechanisms because many crucial technical and theoretical problems remain in the research stage, and the technical design of various bionic propulsion systems is still very backward and far from practical application.

3.3 Bionic wave oscillation rigid drive

At present, the main biomimetic fish propulsion systems are BCF models, such as dolphins, which are propelled by the caudal fin, and MPF models, such as manta rays, which are propelled by the pectoral fin.

The propulsion model has high thrust, stability, and maneuverability (Jung et al. 2002 ). It has an excellent performance in fast swimming under hydrostatic conditions and better start and stop functions but poor maneuverability in low-speed turns and turbulent environments. Peking University developed a robot fish consisting of a rigid head, a flexible body, and a tail fin. The hard head houses a control unit, a wireless communication module, and a set of batteries. The battery is placed at the bottom of the head to ensure the vertical stability of the robot while swimming. A pair of pectoral fins are fixed on both sides of the head to ensure the stability of the fins in water. The flexible body comprises three joints, each connected to a servo motor to adjust the deflection angle of the joint. The rubber tail fin is fixed on the third joint and acts with the water flow to move forward in waves (Li et al. 2014a ) (Fig.  11 a). Developed by the Institute of International Education, the HRF is a new type of marine robot with different modes of motion to adapt to the complex marine environment. The motion mode of the hybrid robot fish mainly has two types, namely, sail drive and wave drive. The HRF includes tail fins, wings, steering rubber, collapsible sails, and a hull. In wind-driven mode, the sail is folded, while wave drive is used to drive the hydrofoil up and down with waves to provide power; thus, no extra energy is needed to move forward (Ma et al. 2020 ) (Fig.  11 b).

Wave rigid drive robot. a Prototype of the robotic fish (Li et al. 2014a ); b Prototype of the HRF in wind-driven mode (Ma et al. 2020 ); c  BCF mode swimming style (Chowdhury et al. 2011 ); d  Amphibious snake robot (Kelasidi et al. 2016 )

In 2002, MIT developed the world’s first robotic fish—bionic tuna—which can complete complex movements such as propulsion, turning, and ascent diving (Koch 2002 ). Its forward speed can reach 2 m/s, and the propulsion efficiency is as high as 91%. Building on this, the MIT team developed the reinforced fish Robopike and the steel-like underwater vehicle VCUUV in collaboration with Draper Lab in the United States. In 2016, the birth of these two robotic fish greatly improved the BCF mode propulsion technology (Kumar et al. 2016 ). A hydraulic bionic wave fin prototype is designed at the National University of Defense Technology, comprising a hydraulic pressure source, a hydraulic bionic wave fin principle prototype, and a data acquisition and processing system. The flow variation rule, the function principle of bionic oscillating joint movement, the underwater speed test, and the free navigation propulsion test were performed on the prototype. The National University of Singapore developed a fish-like underwater vehicle integrating fish-like swimming, modular link, and fin movement. The motor is used for simulation of the wave of the fish tail, that is, sinusoidal oscillation. The aim is to duplicate the BCF model’s propulsion technology to swim efficiently over long distances at impressive speeds (Chowdhury et al. 2011 ) (Fig.  11 c). Developed by the Norwegian University of Science and Technology, the amphibious snake robot has similar kinematics whether on land or in water; the snake robot constantly changes its body shape to reduce ground friction or hydrodynamic resistance to achieve forward propulsion, that is, when the snake robot follows a wavy gait pattern, it gains propulsion (Kelasidi et al. 2016 ) (Fig.  11 d).

3.4 Special drive mode

Various underwater organisms drive in different ways, and simulation methods have always been employed to explore their motion mechanism and optimize their motion to guide the design and production of underwater robots. Several strange underwater organisms also bring inspiration to researchers. For example, there is increasing research on underwater jellyfish octopus. The organism is flexible, and only by changing the size of the cavity does it achieve steering and fixed trajectory movement. However, its swimming stability is poor, and the direction is not easy to control, which is a huge issue to solve. Bionic water snake robots, like water snakes, can swim freely in water by swinging their tails. Their movement is flexible and can complete relatively complex task environments. They have good flexibility and freedom in some locations that divers or other underwater vehicles cannot reach because of their appearance. Turtles in water do not have the same slow movement as on the ground: they swim very fast and are very sensitive. Their unique way of propulsion also offers a lot of inspiration to researchers, especially those who study amphibious robot turtles.

3.4.1 Amphibian drive mode

Since the world’s first bionic amphibious robot was designed in 2013, it has gradually developed astonishing achievements. The working environment of the bionic amphibious robot consists of a beach, wetland, underwater, and other complex terrains, and the biological prototype mainly comprises aquatic and terrestrial organisms. Researchers have established many theoretical models such as 'resistance theory', 'slender body theory', and 'inverted pendulum model', but most of them are only applicable to static laboratory environments, and the working environment of bionic amphibious robots is complex and changeable. Thus, it needs to sense the external environment information, parameter change trend, and functional state in real time. In 2010, the Tokyo Institute of Technology Robotics Laboratory designed the serpentine amphibious robot ACM-R5 based on the previously developed HELIX, which had poor performance (Yang and Ma 2010 ). The robot has a 3D motion capability, and each module has a motion mode of two degrees of freedom, capable of pitching and yawing. It has many gaits on land, but its gait in water has not been studied yet. To make serpentine amphibious robots have more flexible mobility in water, the State Key Laboratory of Robotics of the Chinese Academy of Sciences developed a new amphibious robot called EXPLORER-III in 2020, which consists of nine waterproof modular universal units, each with two free-motion modes of pitch and yaw (Zheng et al. 2020 ). The robot has a total length of 117 cm, a trunk diameter of 7.5 cm, and a total mass of 6.75 kg. Since 2016, the State Key Laboratory of Robotics of the Shenyang Institute of Automation, Chinese Academy of Sciences, has conducted extensive research on another serpentine amphibious robot and developed a prototype (Yang et al. 2016 ). The robot is 700 mm long, 320 mm wide, and 150 mm high, with a total mass of 4.995 kg. Moreover, the robot can move at a speed of up to 0.45 m/s in water. Bionic amphibious robots will simplify amphibious drive structures by using soft actuators, improving energy efficiency, sensing the environment, and having a certain ability to make autonomous decisions.

Wheel-propeller-integrated amphibious robots tend to integrate multiple drive units, which can crawl in water and on the ground. Thus, the driving device does not need to be changed; only the mode of motion needs to be changed, which can result in good motion performance on land and in water (Liu and Jiang 2022 ). Thus, research on such robots worldwide has gradually increased, and researchers have achieved some great results. The Mechanical Engineering and Automation major of Beihang University designed an integrated wheel-propeller amphibious robot, which has a simple and compact structure and can realize autonomous movement in two environments (Wu et al. 2021b ). Shenyang Institute of Automation, Chinese Academy of Sciences developed an integrated wheel-propeller amphibious robot with dimensions (L × W × H) of 1.0 m × 0.96 m × 0.2 m. The total weight is 44 kg, the maximum crawling speed is 1 m/s, the maximum swimming speed is 0.7 cm/s, and the maximum working depth is 10 m (You et al. 2010 ). Individual motors drive all drives of the robot, and depending on the operating environment, the movement can be easily switched by rotating the wheel-propeller 90°, but it needs to consume a lot of energy, and the energy of bionic amphibious robots is extremely limited, and the efficiency of energy utilization is low, limiting its application. From the perspective of broadening income sources and reducing expenses, on the one hand, bionic amphibious robots must carry batteries with higher energy density and enhance outdoor energy collection capabilities.

Revealing the movement characteristics of biological prototypes is the premise of bionic design. Due to the rapid development of biology, chemistry, structural science, and other disciplines, research on the driving mechanism of various underwater and land animals has gradually entered the muscle tissue structure and microcell energy utilization process. More accurate mathematical models are required to offer a theoretical basis for designing underwater and land-driven robotic structures. In bionic engineering science, several motion characteristics and swimming mechanisms of aquatic organisms have not been fully explored, such as the effect of dynamic instability on swimming efficiency and the drag reduction function of aquatic organisms (Li et al. 2021 ). Thus, there remains a big gap between most underwater bionic robots and their prototypes. Enhancing the driving efficiency of wave motion and oscillation motion is one of the crucial problems in solving bionic wave motion, but so far, this problem has not been well solved. Thus, investigating the motion characteristics and swimming mechanism of the bionic prototype and applying it to the bionic system, exploring the hydrodynamic factors in the swimming process, and improving the bionic similarity are the key issues to achieving efficient swimming of the model (Serhat, 2022 ).

3.4.2 Bionic water jet soft drive

Aquatic cephalopods such as squid and jellyfish can control the contraction and expansion of the cavity through muscle fibers during swimming, and their movement is in an unstable state of acceleration and deceleration (Zhou et al. 2014 ). At the same time, they are propelled by forces in the opposite direction of the water jet, which enables mollusks such as jellyfish to move axially at extremely high instantaneous speeds and precisely position themselves in slow motion. However, the expansion and contraction of the cavity are not completed, and the air is slowly sucked in and out, leading to discontinuous propulsion and poor movement continuity. From the above theories, the research group of the Liquid Metal Laboratory of the Institute of Physics and Chemistry of the Chinese Academy of Sciences explored the motion characteristics of jellyfish expansion and water absorption, systematically discussed the theory and technology of the liquid metal robot jellyfish integrating the interaction of a fully flexible electromagnetic coil and a magnet for the first time, and designed a bionic robot jellyfish with more natural motion and propulsion (Zhou et al. 2018 ) called RoMan-III. This is driven by a completely soft electromagnetic actuator, which can realize a variety of soft swimming in response to different electrical signals. Based on further conceptual experiments and computational fluid dynamics simulations, Waseda University in Japan systematically explained the response mechanism of the robot jellyfish and various factors controlling its movement behavior, including the formation of vortices and the way of rising, diving, and levitation, and developed a bionic jellyfish with a spherical structure that can float better (Francis et al. 2002 ). By experiment, it was found that this structure can complete the retractable movement of jellyfish more smoothly.

The squid water jet propulsion process principle is as follows: First, the squid outer box membrane expands to form negative pressure, and water fills the chamber. Second, the mantle shrinks sharply after the water jet and funnel are closed. Finally, the air is rapidly ejected from the nozzle, and the body is subjected to a force in the opposite direction of the airflow. The compressed shell of the stingray robotic fish, developed at Nanjing University, is made of photosensitive resin, and the pectoral fin skeleton is composed of 12 carbon fiber rods. The robotic fish uses a thin rubber film to squeeze the water around it as it swims to generate thrust. The oscillation of fin rays causes the fluctuation of pectoral fins, and by controlling the amplitude, frequency, and phase difference between adjacent fins, different harmonic waveforms can be produced (Wang et al. 2014b ) (Fig.  12 a). In Fig.  12 b, the bull nose fish robot simulates the pleural motion and deformation of the bull nose rays. Each side of its internal skeleton comprises three fin-like rays, which are evenly distributed at the base of the fins along the chord. These fins play a significant role in propulsion. The tail fin functions like a lifting rudder, producing power by beating the current to help the pectoral fin float and dive (Cai et al. 2019 ).

Water spraying manta ray robot. a Robotic stingray design (Wang et al. 2014b ); b  Ox nose fish robot (Cai et al. 2019 ); c  Robo-Ray IIs (Kapetanovic et al. 2020 ); d  Underwater robot with elastic skin (Ma et al. 2015 )

California Institute of Technology established a piston jet model by studying the propulsion mechanism of a squid water jet (Wu et al. 2019 ) that used dynamic grid technology to simulate the formation process of vortex rings under different spindle ratios and backgrounds. The reasons for the formation of vortex rings were analyzed, and the consistency of simulation and experimental results was effectively confirmed. Harbin Institute of Technology developed a water film and bionic nozzle based on a cuttlefish jet system (Tian et al. 2022b ). The bending performance of the bionic nozzle was tested at different water temperatures and driving pulse conditions. Researchers used force sensors and high-definition cameras to capture and record the movement of the bionic jet system, effectively confirming the performance characteristics of the bionic jet system (Wang et al. 2017 ). A new bionic manta ray robot was developed by Beihang University. The real flexible deformation of pectoral fins can be well simulated by integrating flexible mechanisms and rigid support into the mechanical structure design of the robot. Second, the CPG control method is used to realize that the controller drives the rhythmic bionic movement, and the flapping wing shoots water to push the body forward and up and down (Kapetanovic et al. 2020 ) (Fig.  12 c). The bionic pectoral fin of the manta ray robot developed by Beihang University can produce an effective angle of attack, and the thrust generated by the interaction with the current can effectively propel the robot fish. The experimental results exhibit that the maximum forward speed of the robot fish can reach 0.43 m/s (0.94 times body length/second) when it is swimming in the tank, and it has good small radius turning maneuverability (Ma et al. 2015 ) (Fig.  12 d).

Due to different conditions, various bionic water jet propulsion systems cannot realize the same movement as real organisms, nor do they have extremely sensitive responses and fast movement ability. However, research on biomimetic water jet propulsion systems is still in its nascent stage: there is no relatively mature biomimetic propulsion system, the types of technologies are relatively small, there are several difficulties to be overcome, and there is a long way to go.

4 Applications

Oceans are vital to life on Earth; they are key to regulating climate and balancing various ecosystems (Park and Kim 2016 ). They are also home to countless creatures and diverse environments. In addition, the oceans are important channels for global transportation. They are indispensable sources of energy. Despite their vital significance, oceans remain underexplored due to their harsh conditions, making exploration impossible with traditional methods. Using underwater vehicles for ocean exploration is becoming increasingly popular as they allow people to conduct safe exploration in extreme environments for long periods. At present, underwater bionic robots are used in many fields, from oil and gas and fisheries to archaeology, search, rescue, and defense (Li et al. 2014c ). In addition, underwater robots are of use in scientific missions, such as mapping water composition and environmental parameters over time and space, exploring the characteristics of the seafloor in terms of depth, morphology, and composition, investigating glacial areas and icebergs, observing biological species in the environment, collecting biological and geological samples, searching for life in the deep ocean, and helping protect the environment from pollution.

4.1 Application status of underwater robots

Since the second half of the twentieth century, underwater robots have begun to assist human exploration of the ocean, and with the continuous advancement of human reach and exploration depth, underwater robots performing various tasks have also been born. In 2017, Professor Yang Canjun of Zhejiang University designed an underwater robot that can automatically clean marine life 100 m below the surface of water. In its first sea test, the robot sent back a 'selfie' video underwater: firmly attached to the wall of the tube, spraying water filled with bubbles, and the accumulated shells were 'swept' away. The robot is specially designed to clean the marine organisms attached to the surface of a steel pipe of an oil drilling platform and has been successfully tested in the Pinghu oil and gas field in the East China Sea. In 2018, the underwater unmanned robot enterprise Yoken Robot launched a new product—BW Space Pro—which is the world’s first underwater UAV with intelligent functions, which is widely used in diving entertainment, underwater shooting, underwater survey, sea fishing, marine environmental protection, marine biological research, aquaculture, underwater archaeology, underwater search and rescue, and other fields. In 2019, Dr. Erik Engeberg of Florida Atlantic University in the United States developed a jellyfish robot that can autonomically shuttle between coral reefs and monitor jellyfish robots at close range. Besides assisting in research, the jellyfish robot can shoulder the task of defending the ocean and serve as a small spearhead in the front line of protecting the environment. In July 2020, the team of Professor Wen Li of Beijing University of Aeronautics and Astronautics and Junzhi, a researcher from the Institute of Automation of the Chinese Academy of Sciences, designed and manufactured an underwater soft robot arm that can be applied to the natural environment of the near shallow sea, with the aim of establishing the kinematic model and rapid solution method of inverse kinematics to realize real-time kinematic control and finally realizing underwater grasp operations in the natural environment of the near shallow sea. With the upgrading and mature application of underwater robot technology, it can not only greatly reduce the risk of manual operation but also improve operation efficiency and reduce the corresponding expenditure cost. Meanwhile, driven by the integration of other innovative technologies, both the comprehensive performance and cost performance levels of underwater robots are continuing to improve, which can better complete the work and is conducive to promoting large-scale development of the industry.

4.2 Natural resource surveys

By duplicating the form of marine organisms, bionic robots can better adapt to harsh environments, such as high pressure, low temperature, and current, at the bottom of the sea. They are usually small in size and light in weight; thus, they can better collect various substances in their original conditions, which is of great significance for the study of natural resources at the bottom of the sea.

Underwater vehicles have been widely used in various marine geoscience research, initially focusing on seafloor mapping but more recently expanding to water column and oceanographic surveys. The first underwater vehicle dedicated to marine was probably the IFREMER AUV, which was used in the early 1980s to map deep-sea manganese nodule fields. A Woods Hole Oceanographic Institution (WHOI) Sentry AUV was used to map the Deepwater Horizon oil spill in the Gulf of Mexico, which resulted in a hydrocarbon plume (Levshonkov et al. 2020 ), using robots carrying detectors to assess its impact on animals and habitats. Many underwater vehicles were deployed in 1995 and 1996 at the Juan de Fuca Ridge in the northwestern United States to detect and map new lava flows (Stenius et al. 2022 ). To use magnetometers to measure young lava flows at 2200 m east longitude, WHOI developed the mixed-material underwater vehicle Nereus for scientific exploration at 11000 m in the deepest part of the ocean. This was almost twice the depth range of the AUV at the time. In 2013, the French National Center for Marine Exploitation built Orca, an unmanned cable-free underwater vehicle with a maximum depth of 6000 m (Gao et al. 2013 ). In 2020, the French National Sea Bomb Development Center cooperated with a company to jointly develop the 'Eret' acoustic remote-control diving robot, which is used for underwater drilling rig inspection, submarine oil rig installation, oil pipeline auxiliary installation, anchor cable reinforcement, and other complex operations. In China, the underwater vehicle was first used in 2022 for subglacial surveys in the Arctic Ocean. Shortly after the scientific survey ship 'Ocean' began the third leg of the expedition, 'Ocean' conducted its first underwater robot operation in the East Pacific Sea for the first time with the underwater robot 'Sea Dragon 2', which was used to observe a rare giant chimney in the 'Bird’s nest' black chimney area and carried a robotic arm used to accurately capture about 7 kg of vulcanized black chimney ventilation samples. 'Hailong 2' relying on accurate dynamic positioning, accurately landed on the seabed in the black chimney area of the 'Bird’s nest' and performed camera observation and measurement of hydrothermal environmental parameters. The discovery marks China as one of the few countries worldwide that can use underwater robots to conduct hydrothermal surveys and sampling studies at mid-ocean ridges. The robot fish has the concealment of integrating into the fish, which can be used to collect information on the fish or guide the fish to schedule the distribution or cluster of the fish according to some algorithms (Marras and Porfiri 2012 ) (Fig.  13 a). Thus, underwater bionic robots may effectively be used in marine environment observation, deep-sea resource exploration and development, and deep-sea and polar scientific investigation.

Application of voice-activated soft machine fish. a Robot fish collect information about shoals of fish (Marras and Porfiri 2012 ); b  Deep-sea exploration (Li et al. 2021 ); c  Underwater positioning (Wang et al. 2020 ); d  Underwater imaging (Katzschmann et al. 2018 )

4.3 Biodiversity research

Through the bionic robot’s similarity in appearance to marine life, marine life can be studied without disturbing its normal activities, enabling close observation of marine life and potentially becoming a new platform for studying and interacting with underwater species (Wang et al. 2020 ). Underwater bionic robots play an important role in marine ecological protection. First, they can be used to collect marine environmental data. Using underwater robots, scientists can obtain detailed geographic images of the ocean and the conditions at the bottom of the ocean. This data is crucial for understanding the health and pollution levels of marine ecosystems. Professor Li Tiefeng’s team at Zhejiang University began research on a bionic deep-sea soft robot based on lionfish. Based on the dispersion and fusion of lionfish head bones in soft tissues, the project team performed the mechanical design of the structure and material of electronic devices and soft matrix and optimized the stress state in the robot body under a high-pressure environment. By designing materials and structures that adjust the devices and software, the robot could withstand a deep-sea pressure of 10000 m without a pressure-resistant shell and successfully conducted exploration missions in the Mariana Trench (Li et al. 2021 ) (Fig.  13 b). Underwater robots can also be used to monitor the population and activity areas of marine life. With cameras and sensors, scientists can observe and record the behavior of many aquatic organisms in real time, providing evidence for their conservation.

In addition to data collection and monitoring, ROV maps can help protect marine life. They can remove debris and harmful substances from the ocean. Many marine creatures often die by ingesting waste. The underwater vehicle can collect this waste through its robotic arm and bring it to a safe location for disposal. Some underwater robot maps can even perform deep seabed cleanup operations to help restore the health of the ocean (Wang et al. 2002 ) (Fig.  13 c). The University of Icahnx developed a new kind of robotic fish for detecting pollution in river water and drawing 3D pollution maps of the river (Gomatam et al. 2012 ). Each robotic fish is about 50 cm long, 15 cm high, and 12 cm wide. Each is equipped with pollution detection sensors and Global Positioning System (GPS), can 'smell' harmful substances in the water, and can work together, even if there is no one to direct. When they 'sniff out' the harmful substances in the water, they communicate with each other through a Wi-Fi wireless connection. The GPS navigation system allows them to swim freely without human operation, and once they find pollutants, they will send an alert to the environmental protection department personnel (Skorohod et al. 2020 ).

Biosensors were first deployed on an underwater robot when an NERC autonomous submersible AUV was fitted with an in situ dissolved manganese analyzer (Skorohod et al. 2020 ). This deployment showed how an autonomous underwater robot carrying a biosensor could detect small-scale changes in species distribution that traditional sampling methods could not address. Since then, chemical sensors on underwater robots used for marine purposes have been used mainly to search the water column for active hydrothermal columns and to study species distributions, and a suite of sensors for detecting hazardous liquid spills have been deployed on underwater robots in the North Sea Sleipner project for frequent, high time scale studies of areas of potential spills to protect the ecological environment (Tran and Park 2020 ). By application of underwater robot mapping, people can better protect the diversity of marine ecosystems and marine life. They help people understand and solve the problems of the marine environment and provide a guarantee for the rational use of marine resources.

4.4 Underwater imaging

There is an increasing demand for exploration of the seabed environment, and the imaging requirements for marine resources and the underwater world are also getting higher and higher (Liang et al. 2010 ). Due to the uncertainty of the underwater environment, such as interference of the current and limited sensing ability, conventional underwater navigation equipment has limitations; thus, bionic robots designed for different underwater environments have great advantages.

The bionic underwater foot robot studied by the National Metrology Institute of Japan (Maeda et al. 2020 ) imitates the appearance and behavior of crabs and can walk and jump underwater. Compared to traditional AUV and ROV, it is better adapted to complex underwater terrains and has a higher affinity for underwater organisms. Due to their bionic appearance, the natural movements of underwater creatures can be well imaged. National Institute of Ocean Technology (Ramesh et al. 2017 ) used the bionic fish REMUS to map the habitat at 1–2 m water depth in the Juan Strait in the northern United States. It used underwater video data for ground truth measurements. Underwater robots have been used to map various seafloor morphological features, including under ice sheets inaccessible to research ships. For instance, State Marine Technical University (Siek and Sakovich 2019 ) used the underwater vehicle NERC Autosub3 to investigate the retreat of the Pine Island Glacier (PIG) in West Antarctica. The robot performed six missions in 94 h, collecting 510 km of orbital data under the PIG ice shelf 50 km above the ice surface.

Underwater vehicles are also being used to image sedimentary features in submarine canyons. The University of Kanagawa used an underwater vehicle carrying a high-resolution multibeam waveform acoustic system (0.7 m lateral resolution) and a submarine profiler (0.1 m vertical resolution) to conduct underwater imaging experiments, collecting data from La Jolla Canyon on the Southern California coast. To understand the processes that produce observational patterns on a scale comparable to the surface (Tsukioka et al. 2002 ), the Science and Technology on Underwater Vehicle Laboratory used underwater robotic fish diving to collect deep-sea data and provide vibration core samples for sediment dating (Liu et al. 2020 ) (Fig.  13 d). In the article on acoustically controlled soft robotic fish studied by the University of Zagreb (Kapetanovic et al. 2020 ), it is possible to approach underwater organisms without disturbing their normal life and to image underwater organisms and underwater landscapes through shape features similar to those of fish (Katzschmann et al. 2018 ).

When conducting underwater imaging, conventional underwater vehicles have higher accuracy in the tangential direction of the seabed and lower accuracy in the vertical direction of the seabed. In comparison, underwater bionic robots have lower accuracy in the tangential direction of the seabed and higher accuracy in the vertical direction of the seabed (Wang et al. 2014a ). Moreover, the underwater bionic robot has high stability and adaptability to the seabed environment, and the combination of the two can obtain higher-quality underwater imaging maps.

4.5 Underwater search and rescue

Underwater robots can be used to check whether explosives are installed on dams and bridge piers, remote-reconnaissance structural conditions or dangerous goods, and closely inspect underwater evidence. In 2010, underwater robots could walk at 3–6 km/h in the deepest underwater world of 6000 m (Brown and Clark  2010 ). The forward-looking and downward-looking radar gives it 'good eyesight'. The accompanying camera, video camera, and precise navigation system allow it to 'overlook'. The underwater robot WHOI provided in 2012 took just a few days to find the wreckage of an Air France flight in 4000 km 2 of ocean after two years of fruitless searching by various ships and aircraft. Underwater robots have great potential and application value in rescue missions. When encountering dangerous situations, underwater bionic robots can play a greater role in on-site situation assessment and positioning, providing important information for the next step. Through the underwater high-definition camera group, sonar, and a variety of sensors carried by the underwater robot itself, rescue workers can grasp the water depth and temperature on the shore. They can determine the obstacles in the water and remove the danger of entering the water (Wang et al. 2019c ). In salvage and other operations, the underwater robot can quickly locate the location of underwater objects. Armed with this information, commanders can better formulate a reasonable and efficient rescue plan. Another major advantage of underwater robots lies in search and rescue missions. In dangerous waters such as rapids and low temperatures, it can take the lead in entering underwater areas that rescuers cannot reach to detect the location and situation of trapped people. The robot operator can control the movement of the robot by manipulating the handle or wireless sensing device on the shore. Carrying tools such as robotic arms can also assist rescue workers in completing tasks such as clearing and salvaging. The water environment where the danger occurs is not always ideal, and low visibility is one of the most significant problems. Bionic fluorescent robot fish can provide rescuers with a light source, and rescuers can also determine the location of the target and search for risks by referring to the umbilical cable connected to the underwater robot (Asadnia et al. 2015 ). The emergence of underwater robots makes underwater rescue work safer and more efficient.

5 Summary and outlook

From the above summarized research results, it can be observed that research on bionic underwater robots has grown considerably. Rapid turning, path tracking, autonomous operation, and other actions have been achieved on some prototypes, and there is a great improvement in speed and mobility, but there is still a very obvious gap with real fish. Underwater bionic robot development is high-end manufacturing industry supported by the Chinese government and plays the role of a 'strategic commanding height'. In China and abroad, a series of work has been conducted on the mechanical structure design, materials, and control methods of underwater bionic robots, and the related research has grown considerably. Due to the complexity of underwater, the mechanical structure design and control technology of underwater robots still require further optimization and improvement to truly achieve a life-like system that integrates the structure and biological characteristics. By enhancing the characteristics of underwater robots, such as self-control and self-perception, and through the coordinated control of robot systems, underwater robots can better integrate into the underwater environment to complete the work, pursue sustainability on the road to development, and make this technology more mature.

Research on bionic underwater robots has become more in-depth and expanded, and some prototypes have realized multimodal motion, fast turning, path tracking, autonomous operation, and other actions, which have greatly improved in speed and maneuverability. However, there is still a very obvious gap with real fish. In the future, bionic underwater robots should be developed into autonomous, intelligent, and collaborative tools. To further improve the performance of the bionic underwater robot system, further work should be conducted in the following main research directions: (1) Mechanism design and optimization. Most bionic underwater robots are driven by motors. Research can be conducted in terms of streamlined low-resistance shapes, intelligent driving materials, and rigid and flexible coupling efficient transmission mechanisms to improve the motion performance of bionic underwater robots. (2) Underwater environment perception and modeling are significant for bionic underwater robots to perform underwater tasks. Information fusion technology of various sensors can be examined and combined with the technology to conduct underwater environment modeling and improve the autonomy intelligence of bionic underwater robots. (3) Intelligent control methods, such as artificial intelligence, are a hot field right now. Some artificial intelligence technologies, such as reinforcement learning and transfer learning, can be applied to the intelligent control of bionic underwater robots so that they can learn various motor skills independently. (4) Multibionic underwater robot cooperation. In nature, fish is often in the form of clusters for foraging, defense, and cruising. The use of multiple bionic underwater vehicles to form a cooperative system is helpful in improving operational efficiency. Due to the complexity of underwater, the particularity of the propulsion mechanism, and the bottleneck of underwater communication, sensing, positioning, and other technologies, the collaboration of multibionic underwater robots will be a very challenging direction.

Due to the complexity of the marine environment, underwater bionic robots will face problems such as the drastic change in water velocity, the difference in pressure under different water depths, and their waterproofing, which poses a great challenge to the structural design of robots. To address these issues, the structure of the future underwater bionic robot needs to be more detailed and more lightweight, and the application of materials should also meet the requirements of the underwater environment. Miniaturization is the current trend of robot development because small structures are easier to adapt to the environment, reduce the contact area, and thus reduce the impact of underwater pressure on the machine structure to a greater extent. The most prominent point is that miniaturized robots are closer to the physiological structure of marine organisms and fundamentally realize the bionic effect rather than just the imitation of appearance. Marine space is generally unsuitable for human survival, and large-scale development and utilization of marine resources have a great dependence on robotics technology. Replacing humans with robots to promote and realize unmanned marine equipment has far-reaching strategic significance. Thus, future bionic underwater robots should be further developed, mainly in the direction of autonomy, intelligence, and synergy, to enhance the performance of bionic underwater robotic systems.

Availability of data and materials

The data and materials used to support the findings of this study are included in the article.

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Acknowledgements

This work was supported by grants from the National Natural Science Foundation of China (Grant Nos. 62201537 and U20A20194), the Natural Science Foundation of Shandong Province (Grant No. ZR2022QF008), and the Central University Basic Research Fund of China (Grant No. 202312035). We thank Yanyue Teng at the Ocean University of China for the useful discussion on the soft actuator drive part of this review.

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Zhongao Cui, Liao Li, Yuhang Wang, Zhiwei Zhong & Junyang Li

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Zhongao Cui and Liao Li performed the literature survey, drafted the manuscript and revised it critically for the key content. Yuhang Wang conducted literature research and content verification. Zhiwei Zhong carried out the document sorting and figure modification. Junyang Li is the corresponding author, responsible for organizing the manuscript sequence alignment, proofreading and revising the manuscript, and giving the final approval of the version to be published. All authors read and approved the final manuscript.

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Cui, Z., Li, L., Wang, Y. et al. Review of research and control technology of underwater bionic robots. Intell. Mar. Technol. Syst. 1 , 7 (2023). https://doi.org/10.1007/s44295-023-00010-3

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What to know about the crisis of violence, politics and hunger engulfing Haiti

A long-simmering crisis over Haiti’s ability to govern itself, particularly after a series of natural disasters and an increasingly dire humanitarian emergency, has come to a head in the Caribbean nation, as its de facto president remains stranded in Puerto Rico and its people starve and live in fear of rampant violence. 

The chaos engulfing the country has been bubbling for more than a year, only for it to spill over on the global stage on Monday night, as Haiti’s unpopular prime minister, Ariel Henry, agreed to resign once a transitional government is brokered by other Caribbean nations and parties, including the U.S.

But the very idea of a transitional government brokered not by Haitians but by outsiders is one of the main reasons Haiti, a nation of 11 million, is on the brink, according to humanitarian workers and residents who have called for Haitian-led solutions. 

“What we’re seeing in Haiti has been building since the 2010 earthquake,” said Greg Beckett, an associate professor of anthropology at Western University in Canada. 

What is happening in Haiti and why?

In the power vacuum that followed the assassination of democratically elected President Jovenel Moïse in 2021, Henry, who was prime minister under Moïse, assumed power, with the support of several nations, including the U.S. 

When Haiti failed to hold elections multiple times — Henry said it was due to logistical problems or violence — protests rang out against him. By the time Henry announced last year that elections would be postponed again, to 2025, armed groups that were already active in Port-au-Prince, the capital, dialed up the violence.

Even before Moïse’s assassination, these militias and armed groups existed alongside politicians who used them to do their bidding, including everything from intimidating the opposition to collecting votes . With the dwindling of the country’s elected officials, though, many of these rebel forces have engaged in excessively violent acts, and have taken control of at least 80% of the capital, according to a United Nations estimate. 

Those groups, which include paramilitary and former police officers who pose as community leaders, have been responsible for the increase in killings, kidnappings and rapes since Moïse’s death, according to the Uppsala Conflict Data Program at Uppsala University in Sweden. According to a report from the U.N . released in January, more than 8,400 people were killed, injured or kidnapped in 2023, an increase of 122% increase from 2022.

“January and February have been the most violent months in the recent crisis, with thousands of people killed, or injured, or raped,” Beckett said.

Armed groups who had been calling for Henry’s resignation have already attacked airports, police stations, sea ports, the Central Bank and the country’s national soccer stadium. The situation reached critical mass earlier this month when the country’s two main prisons were raided , leading to the escape of about 4,000 prisoners. The beleaguered government called a 72-hour state of emergency, including a night-time curfew — but its authority had evaporated by then.

Aside from human-made catastrophes, Haiti still has not fully recovered from the devastating earthquake in 2010 that killed about 220,000 people and left 1.5 million homeless, many of them living in poorly built and exposed housing. More earthquakes, hurricanes and floods have followed, exacerbating efforts to rebuild infrastructure and a sense of national unity.

Since the earthquake, “there have been groups in Haiti trying to control that reconstruction process and the funding, the billions of dollars coming into the country to rebuild it,” said Beckett, who specializes in the Caribbean, particularly Haiti. 

Beckett said that control initially came from politicians and subsequently from armed groups supported by those politicians. Political “parties that controlled the government used the government for corruption to steal that money. We’re seeing the fallout from that.”

Many armed groups have formed in recent years claiming to be community groups carrying out essential work in underprivileged neighborhoods, but they have instead been accused of violence, even murder . One of the two main groups, G-9, is led by a former elite police officer, Jimmy Chérizier — also known as “Barbecue” — who has become the public face of the unrest and claimed credit for various attacks on public institutions. He has openly called for Henry to step down and called his campaign an “armed revolution.”

But caught in the crossfire are the residents of Haiti. In just one week, 15,000 people have been displaced from Port-au-Prince, according to a U.N. estimate. But people have been trying to flee the capital for well over a year, with one woman telling NBC News that she is currently hiding in a church with her three children and another family with eight children. The U.N. said about 160,000 people have left Port-au-Prince because of the swell of violence in the last several months. 

Deep poverty and famine are also a serious danger. Gangs have cut off access to the country’s largest port, Autorité Portuaire Nationale, and food could soon become scarce.

Haiti's uncertain future

A new transitional government may dismay the Haitians and their supporters who call for Haitian-led solutions to the crisis. 

But the creation of such a government would come after years of democratic disruption and the crumbling of Haiti’s political leadership. The country hasn’t held an election in eight years. 

Haitian advocates and scholars like Jemima Pierre, a professor at the University of British Columbia, Vancouver, say foreign intervention, including from the U.S., is partially to blame for Haiti’s turmoil. The U.S. has routinely sent thousands of troops to Haiti , intervened in its government and supported unpopular leaders like Henry.

“What you have over the last 20 years is the consistent dismantling of the Haitian state,” Pierre said. “What intervention means for Haiti, what it has always meant, is death and destruction.”

In fact, the country’s situation was so dire that Henry was forced to travel abroad in the hope of securing a U.N. peacekeeping deal. He went to Kenya, which agreed to send 1,000 troops to coordinate an East African and U.N.-backed alliance to help restore order in Haiti, but the plan is now on hold . Kenya agreed last October to send a U.N.-sanctioned security force to Haiti, but Kenya’s courts decided it was unconstitutional. The result has been Haiti fending for itself. 

“A force like Kenya, they don’t speak Kreyòl, they don’t speak French,” Pierre said. “The Kenyan police are known for human rights abuses . So what does it tell us as Haitians that the only thing that you see that we deserve are not schools, not reparations for the cholera the U.N. brought , but more military with the mandate to use all kinds of force on our population? That is unacceptable.”  

Henry was forced to announce his planned resignation from Puerto Rico, as threats of violence — and armed groups taking over the airports — have prevented him from returning to his country.  

Now that Henry is to stand down, it is far from clear what the armed groups will do or demand next, aside from the right to govern. 

“It’s the Haitian people who know what they’re going through. It’s the Haitian people who are going to take destiny into their own hands. Haitian people will choose who will govern them,” Chérizier said recently, according to The Associated Press .

Haitians and their supporters have put forth their own solutions over the years, holding that foreign intervention routinely ignores the voices and desires of Haitians. 

In 2021, both Haitian and non-Haitian church leaders, women’s rights groups, lawyers, humanitarian workers, the Voodoo Sector and more created the Commission to Search for a Haitian Solution to the Crisis . The commission has proposed the “ Montana Accord ,” outlining a two-year interim government with oversight committees tasked with restoring order, eradicating corruption and establishing fair elections. 

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CORRECTION (March 15, 2024, 9:58 a.m. ET): An earlier version of this article misstated which university Jemima Pierre is affiliated with. She is a professor at the University of British Columbia, Vancouver, not the University of California, Los Angeles, (or Columbia University, as an earlier correction misstated).

Patrick Smith is a London-based editor and reporter for NBC News Digital.

Char Adams is a reporter for NBC BLK who writes about race.

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• Indian J Dermatol
• v.61(2); Mar-Apr 2016

Methodology Series Module 2: Case-control Studies

Maninder singh setia.

Epidemiologist, MGM Institute of Health Sciences, Navi Mumbai, Maharashtra, India

Case-Control study design is a type of observational study. In this design, participants are selected for the study based on their outcome status. Thus, some participants have the outcome of interest (referred to as cases), whereas others do not have the outcome of interest (referred to as controls). The investigator then assesses the exposure in both these groups. The investigator should define the cases as specifically as possible. Sometimes, definition of a disease may be based on multiple criteria; thus, all these points should be explicitly stated in case definition. An important aspect of selecting a control is that they should be from the same ‘study base’ as that of the cases. We can select controls from a variety of groups. Some of them are: General population; relatives or friends; and hospital patients. Matching is often used in case-control control studies to ensure that the cases and controls are similar in certain characteristics, and it is a useful technique to increase the efficiency of the study. Case-Control studies can usually be conducted relatively faster and are inexpensive – particularly when compared with cohort studies (prospective). It is useful to study rare outcomes and outcomes with long latent periods. This design is not very useful to study rare exposures. Furthermore, they may also be prone to certain biases – selection bias and recall bias.

Introduction

Case-Control study design is a type of observational study design. In an observational study, the investigator does not alter the exposure status. The investigator measures the exposure and outcome in study participants, and studies their association.

In a case-control study, participants are selected for the study based on their outcome status. Thus, some participants have the outcome of interest (referred to as cases), whereas others do not have the outcome of interest (referred to as controls). The investigator then assesses the exposure in both these groups. Thus, by design, in a case-control study the outcome has to occur in some of the participants that have been included in the study.

As seen in Figure 1 , at the time of entry into the study (sampling of participants), some of the study participants have the outcome (cases) and others do not have the outcome (controls). During the study procedures, we will examine the exposure of interest in cases as well as controls. We will then study the association between the exposure and outcome in these study participants.

Example of a case-control study

Examples of Case-Control Studies

Smoking and lung cancer study.

In their landmark study, Doll and Hill (1950) evaluated the association between smoking and lung cancer. They included 709 patients of lung carcinoma (defined as cases). They also included 709 controls from general medical and surgical patients. The selected controls were similar to the cases with respect to age and sex. Thus, they included 649 males and 60 females in cases as well as controls.

They found that only 0.3% of males were non-smokers among cases. However, the proportion of non-smokers among controls was 4.2%; the different was statistically significant ( P = 0.00000064). Similarly they found that about 31.7% of the female were non-smokers in cases compared with 53.3% in controls; this difference was also statistically significant (0.01< p <0.02).

Melanoma and tanning (Lazovic et al ., 2010)

The authors conducted a case-control study to study the association between melanoma and tanning. The 1167 cases - individuals with invasive cutaneous melanoma – were selected from Minnesota Cancer Surveillance System. The 1101 controls were selected randomly from Minnesota State Driver's License list; they were matched for age (+/- 5 years) and sex.

The data were collected by self administered questionnaires and telephone interviews. The investigators assessed the use of tanning devices (using photographs), number of years, and frequency of use of these devices. They also collected information on other variables (such as sun exposure; presence of freckles and moles; and colour of skin, hair, among other exposures.

They found that melanoma was higher in individuals who used UVB enhances and primarily UVA-emitting devices. The risk of melanoma also increased with increase in years of use, hours of use, and sessions.

Risk factors for erysipelas (Pitché et al, 2015)

Pitché et al (2015) conducted a case-control study to assess the factors associated with leg erysipelas in sub-Saharan Africa. This was a multi-centre study; the cases and controls were recruited from eight countries in sub-Saharan Africa.

They recruited cases of acute leg cellulitis in these eight countries. They recruited two controls for each case; these were matched for age (+/- 5 years) and sex. Thus, the final study has 364 cases and 728 controls. They found that leg erysipelas was associated with obesity, lympoedema, neglected traumatic wound, toe-web intertrigo, and voluntary cosmetic depigmentation.

We have provided details of all the three studies in the bibliography. We strongly encourage the readers to read the papers to understand some practical aspects of case-control studies.

Selection of Cases and Controls

Selection of cases and controls is an important part of this design. Wacholder and colleagues (1992 a, b, and c) have published wonderful manuscripts on design and conduct of case-control of studies in the American Journal of Epidemiology. The discussion in the next few sections is based on these manuscripts.

Selection of case

The investigator should define the cases as specifically as possible. Sometimes, definition of a disease may be based on multiple criteria; thus, all these points should be explicitly stated in case definition.

For example, in the above mentioned Melanoma and Tanning study, the researchers defined their population as any histologic variety of invasive cutaneous melanoma. However, they added another important criterion – these individuals should have a driver's license or State identity card. This probably is not directly related to the clinic condition, so why did they add this criterion? We will discuss this in detail in the next few paragraphs.

Selection of a control

The next important point in designing a case-control study is the selection of control patients.

In fact, Wacholder and colleagues have extensively discussed aspects of design of case control studies and selection of controls in their article.

According to them, an important aspect of selecting a control is that they should be from the same ‘study base’ as that of the cases. Thus, the pool of population from which the cases and controls will be enrolled should be same. For instance, in the Tanning and Melanoma study, the researchers recruited cases from Minnesota Cancer Surveillance System; however, it was also required that these cases should either have a State identity card or Driver's license. This was important since controls were randomly selected from Minnesota State Driver's license list (this also included the list of individuals who have the State identity card).

Another important aspect of a case-control study is that we should measure the exposure similarly in cases and controls. For instance, if we design a research protocol to study the association between metabolic syndrome (exposure) and psoriasis (outcome), we should ensure that we use the same criteria (clinically and biochemically) for evaluating metabolic syndrome in cases and controls. If we use different criteria to measure the metabolic syndrome, then it may cause information bias.

Types of Controls

We can select controls from a variety of groups. Some of them are: General population; relatives or friends; or hospital patients.

Hospital controls

An important source of controls is patients attending the hospital for diseases other than the outcome of interest. These controls are easy to recruit and are more likely to have similar quality of medical records.

However, we have to be careful while recruiting these controls. In the above example of metabolic syndrome and psoriasis, we recruit psoriasis patients from the Dermatology department of the hospital as controls. We recruit patients who do not have psoriasis and present to the Dermatology as controls. Some of these individuals have presented to the Dermatology department with tinea pedis. Do we recruit these individuals as controls for the study? What is the problem if we recruit these patients? Some studies have suggested that diabetes mellitus and obesity are predisposing factors for tinea pedis. As we know, fasting plasma glucose of >100 mg/dl and raised trigylcerides (>=150 mg/dl) are criteria for diagnosis of metabolic syndrome. Thus, it is quite likely that if we recruit many of these tinea pedis patients, the exposure of interest may turn out to be similar in cases and controls; this exposure may not reflect the truth in the population.

Relative and friend controls

Relative controls are relatively easy to recruit. They can be particularly useful when we are interested in trying to ensure that some of the measurable and non-measurable confounders are relatively equally distributed in cases and controls (such as home environment, socio-economic status, or genetic factors).

Another source of controls is a list of friends referred by the cases. These controls are easy to recruit and they are also more likely to be similar to the cases in socio-economic status and other demographic factors. However, they are also more likely to have similar behaviours (alcohol use, smoking etc.); thus, it may not be prudent to use these as controls if we want to study the effect of these exposures on the outcome.

Population controls

These controls can be easily conducted the list of all individuals is available. For example, list from state identity cards, voter's registration list, etc., In the Tanning and melanoma study, the researchers used population controls. They were identified from Minnesota state driver's list.

We may have to use sampling methods (such as random digit dialing or multistage sampling methods) to recruit controls from the population. A main advantage is that these controls are likely to satisfy the ‘study-base’ principle (described above) as suggested by Wacholder and colleagues. However, they can be expensive and time consuming. Furthermore, many of these controls will not be inclined to participate in the study; thus, the response rate may be very low.

Matching in a Case-Control Study

Matching is often used in case-control control studies to ensure that the cases and controls are similar in certain characteristics. For example, in the smoking and lung cancer study, the authors selected controls that were similar in age and sex to carcinoma cases. Matching is a useful technique to increase the efficiency of study.

’Individual matching’ is one common technique used in case-control study. For example, in the above mentioned metabolic syndrome and psoriasis, we can decide that for each case enrolled in the study, we will enroll a control that is matched for sex and age (+/- 2 years). Thus, if 40 year male patient with psoriasis is enrolled for the study as a case, we will enroll a 38-42 year male patient without psoriasis (and who will not be excluded for other reason) as controls.

If the study has used ‘individual matching’ procedures, then the data should also reflect the same. For instance, if you have 45 males among cases, you should also have 45 males among controls. If you show 60 males among controls, you should explain the discrepancy.

Even though matching is used to increase the efficiency in case-control studies, it may have its own problems. It may be difficult to fine the exact matching control for the study; we may have to screen many potential enrollees before we are able to recruit one control for each case recruited. Thus, it may increase the time and cost of the study.

Nonetheless, matching may be useful to control for certain types of confounders. For instance, environment variables may be accounted for by matching controls for neighbourhood or area of residence. Household environment and genetic factors may be accounted for by enrolling siblings as controls.

If we use controls from the past (time period when cases did not occur), then the controls are sometimes referred to historic controls. Such controls may be recruited from past hospital records.

Strengths of a Case-Control Study

• Case-Control studies can usually be conducted relatively faster and are inexpensive – particularly when compared with cohort studies (prospective)
• It is useful to study rare outcomes and outcomes with long latent periods. For example, if we wish to study the factors associated with melanoma in India, it will be useful to conduct a case-control study. We will recruit cases of melanoma as cases in one study site or multiple study sites. If we were to conduct a cohort study for this research question, we may to have follow individuals (with the exposure under study) for many years before the occurrence of the outcome
• It is also useful to study multiple exposures in the same outcome. For example, in the metabolic syndrome and psoriasis study, we can study other factors such as Vitamin D levels or genetic markers
• Case-control studies are useful to study the association of risk factors and outcomes in outbreak investigations. For instance, Freeman and colleagues (2015) in a study published in 2015 conducted a case-control study to evaluate the role of proton pump inhibitors in an outbreak of non-typhoidal salmonellosis.

Limitations of a Case-control Study

• The design, in general, is not useful to study rare exposures. It may be prudent to conduct a cohort study for rare exposures

Since the investigator chooses the number of cases and controls, the proportion of cases may not be representative of the proportion in the population. For instance if we choose 50 cases of psoriasis and 50 controls, the prevalence of proportion of psoriasis cases in our study will be 50%. This is not true prevalence. If we had chosen 50 cases of psoriasis and 100 controls, then the proportion of the cases will be 33%.

• The design is not useful to study multiple outcomes. Since the cases are selected based on the outcome, we can only study the association between exposures and that particular outcome
• Sometimes the temporality of the exposure and outcome may not be clearly established in case-control studies
• The case-control studies are also prone to certain biases

If the cases and controls are not selected similarly from the study base, then it will lead to selection bias.

• Odds Ratio: We are able to calculate the odds ratios (OR) from a case-control study. Since we are not able to measure incidence data in case-control study, an odds ratio is a reasonable measure of the relative risk (under some assumptions). Additional details about OR will be discussed in the biostatistics section.

The OR in the above study is 3.5. Since the OR is greater than 1, the outcome is more likely in those exposed (those who are diagnosed with metabolic syndrome) compared with those who are not exposed (those who do are not diagnosed with metabolic syndrome). However, we will require confidence intervals to comment on further interpretation of the OR (This will be discussed in detail in the biostatistics section).

• Other analysis : We can use logistic regression models for multivariate analysis in case-control studies. It is important to note that conditional logistic regressions may be useful for matched case-control studies.

Calculating an Odds Ratio (OR)

Hypothetical study of metabolic syndrome and psoriasis

Additional Points in A Case-Control Study

How many controls can i have for each case.

The most optimum case-to-control ratio is 1:1. Jewell (2004) has suggested that for a fixed sample size, the chi square test for independence is most powerful if the number of cases is same as the number of controls. However, in many situations we may not be able recruit a large number of cases and it may be easier to recruit more controls for the study. It has been suggested that we can increase the number of controls to increase statistical power (if we have limited number of cases) of the study. If data are available at no extra cost, then we may recruit multiple controls for each case. However, if it is expensive to collect exposure and outcome information from cases and controls, then the optimal ratio is 4 controls: 1 case. It has been argued that the increase in statistical power may be limited with additional controls (greater than four) compared with the cost involved in recruiting them beyond this ratio.

I have conducted a randomised controlled trial. I have included a group which received the intervention and another group which did not receive the intervention. Can I call this a case-control study?

A randomised controlled trial is an experimental study. In contrast, case-control studies are observational studies. These are two different groups of studies. One should not use the word case-control study for a randomised controlled trial (even though you have a control group in the study). Every study with a control group is not a case-control study. For a study to be classified as a case-control study, the study should be an observational study and the participants should be recruited based on their outcome status (some have the disease and some do not).

Should I call case-control studies prospective or retrospective studies?

In ‘The Dictionary of Epidemiology’ by Porta (2014), the authors have suggested that even though the term ‘retrospective’ was used for case-control studies, the study participants are often recruited prospectively. In fact, the study on risk factors for erysipelas (Pitché et al ., 2015) was a prospective case case-control study. Thus, it is important to remember that the nature of the study (case-control or cohort) depends on the sampling method. If we sample the study participants based on exposure and move towards the outcome, it is a cohort study. However, if we sample the participants based on the outcome (some with outcome and some do not) and study the exposures in both these groups, it is a case-control study.

In case-control studies, participants are recruited on the basis of disease status. Thus, some of participants have the outcome of interest (referred to as cases), whereas others do not have the outcome of interest (referred to as controls). The investigator then assesses the exposure in both these groups. Case-control studies are less expensive and quicker to conduct (compared with prospective cohort studies at least). The measure of association in this type of study is an odds ratio. This type of design is useful for rare outcomes and those with long latent periods. However, they may also be prone to certain biases – selection bias and recall bias.

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Conflicts of interest.

There are no conflicts of interest.

Bibliography