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Enhancing the sample diversity of snowball samples: Recommendations from a research project on anti-dam movements in Southeast Asia

Julian kirchherr.

1 Faculty of Geosciences, Utrecht University, Utrecht, the Netherlands

2 School of Geography and the Environment, University of Oxford, Oxford, United Kingdom

Katrina Charles

Associated data.

All data underlying the study are within the paper and its Supporting Information files.

Snowball sampling is a commonly employed sampling method in qualitative research; however, the diversity of samples generated via this method has repeatedly been questioned. Scholars have posited several anecdotally based recommendations for enhancing the diversity of snowball samples. In this study, we performed the first quantitative, medium- N analysis of snowball sampling to identify pathways to sample diversity, analysing 211 reach-outs conducted via snowball sampling, resulting in 81 interviews; these interviews were administered between April and August 2015 for a research project on anti-dam movements in Southeast Asia. Based upon this analysis, we were able to refine and enhance the previous recommendations (e.g., showcasing novel evidence on the value of multiple seeds or face-to-face interviews). This paper may thus be of particular interest to scholars employing or intending to employ snowball sampling.

Introduction

Snowball sampling is a commonly employed sampling method in qualitative research, used in medical science and in various social sciences, including sociology, political science, anthropology and human geography [ 1 – 3 ]. As is typical of terms adopted by a variety of fields, however, the phrase ‘snowball sampling’ is used inconsistently across disciplines [ 4 ]. The most frequently employed definition, suggested by Patton [ 5 ], Atkinson and Flint [ 6 ], Cohen and Arieli [ 7 ] and Bhattacherjee [ 8 ], is as a sampling method in which one interviewee gives the researcher the name of at least one more potential interviewee. That interviewee, in turn, provides the name of at least one more potential interviewee, and so on, with the sample growing like a rolling snowball if more than one referral per interviewee is provided.

This definition can initially seem self-explanatory, which may explain why snowball sampling is rarely discussed in most peer-reviewed papers that employ it. Various scholars use snowball sampling in their empirical work, but most provide only limited information on the method (see, e.g., [ 9 – 13 ]). Similarly, qualitative research textbooks often lack substantive discussion of snowball sampling (e.g., [ 8 , 14 – 19 ]). Bailey [ 14 ], for instance, devotes only a half-page of his 595-page book on social research methods to snowball sampling, acknowledging that ‘snowball sampling procedures have been rather loosely codified’ ([ 14 ], p. 96), an observation echoed by Penrod et al. [ 3 ].

This paper focuses on snowball sampling procedures, which we define as those actions undertaken to initiate, progress and terminate the snowball sample [ 1 , 20 ]. Despite the lack of substantive writing on snowball sampling as a method, several authors [ 2 , 3 , 21 ] have provided recommendations for enhancing a sample’s diversity in snowball sampling procedures (we discuss this further in Section 4). However, as this advice is not based on a quantitative analysis of evidence, but only on anecdotal evidence, there is a risk that these recommendations are based on coincidence. The aim of this paper is to provide advice on enhancing the sample diversity of a snowball sample. This advice is grounded in a medium- N analysis of relevant evidence, thus reducing the probability of positing advice that is based on coincidence [ 22 ]. A medium- N analysis is generally based on 10–100 cases, whereas anecdotal evidence is usually based only on a handful of cases [ 23 , 24 ]. At the core of our work, we provide descriptive analyses of various commonly prescribed strategies for enhancing the sample diversity of a snowball sample. These analyses are based on reach-outs to 211 individuals via snowball sampling for a research project on anti-dam movements in Southeast Asia, resulting in 81 interviews conducted between April and August 2015. As far as we are aware, ours is the first medium- N analysis to focus on enhancing the sample diversity of a snowball sample.

The remainder of this paper is organised as follows: in Section 2, we discuss snowball sampling as a method; in Section 3, we present the research project on anti-dam movements in Southeast Asia that served as the basis for our medium- N analysis on snowball sampling procedures; in Section 4, we present and discuss insights on snowball sampling procedures based upon this analysis as well as our resulting recommendations; finally, in Section 5, we summarise our argument.

Throughout this paper, we employ social science methodology terminology. We define key terms for this paper such as ‘snowball sampling’ or ‘sampling’, since these terms are not consistently codified in the scholarly literature. Due to limited space, however, we refrain from defining terms we have deemed common in this field of study, referring only to the relevant literature.

On snowball sampling

Traditional sampling methods are comprised of two elements [ 25 , 26 ]. First, a full set of data sources is defined, creating a list of the members of the population to be studied, known as a sampling frame. Second, a specific sample of data is collected from this sampling frame. Snowball sampling defies both elements, since it does not rely upon a sampling frame [ 27 ] (which may indicate that a different term for snowball sampling would be more accurate). Snowball sampling is often employed when no sampling frame can be constructed.

Researchers frequently cannot construct a sampling frame if a difficult-to-reach population is to be studied. Difficult-to-reach-populations are also referred to as ‘hard-to-reach-populations’ [ 28 ], ‘hidden populations’ [ 29 ] or ‘concealed populations’ [ 21 ] in the scholarly literature. Although not all scholars may agree that these terms are interchangeable, we deem them interchangeable for the purposes of this paper. For further discussion of this terminology, see [ 30 , 31 ].

A difficult-to-reach population does not wish to be found or contacted (e.g., illegal drug users, illegal migrants, prostitutes or homeless people [ 6 , 31 ]). Snowball sampling was originally used by researchers to study the structure of social networks [ 32 ]. The earliest empirical account of snowball sampling is from 1955 [ 33 ], with snowball sampling first described as a method in 1958 [ 34 ]. While it is still used to study the structure of social networks [ 35 ], over the last few decades, the method’s key purpose has largely transformed ‘into […] an expedient for locating members of a [difficult-to-reach] population’ ([ 36 ], p. 141).

Researchers grounded in quantitative thinking, such as Lijphart [ 37 ] and King et al. [ 38 ], tend to view the drawing of a random sample from a sampling frame as the gold standard of data collection. Even these researchers may nevertheless consider non-probability sampling methods, such as snowball sampling, a ‘necessary and irreplaceable sampling [method]’ ([ 39 ], p. 367) when confronted with difficult-to-reach populations, particularly if the dismissal of snowball sampling would mean that no research could be conducted at all. Ultimately, ‘an important topic is worth studying even if very little [access to] information is available’ ([ 38 ], p. 6). Still, some of those grounded in quantitative thinking call snowball sampling a method ‘at the margin of research practice’ ([ 6 ], p. 1), since the lack of a sampling frame means that, unlike individuals in a random sample, individuals in a population of interest do not have the same probability of being included in the final sample. Findings from a snowball sample would therefore not be generalisable [ 40 ] (on generalisability, see [ 41 ]).

Several qualitative scholars rebut such criticism. Creswell, for instance, notes that ‘the intent [of qualitative research] is not to generalise to a population, but to develop an in-depth [and contextualised] exploration of a central phenomenon’ ([ 42 ], p. 203). Others [ 1 , 39 ] specifically oppose quantitative scholars’ negative framing of snowball sampling, arguing that this method would ‘generate a unique type of social knowledge’ ([ 1 ], p. 327). Due to the diversity of perspectives gathered, this knowledge would be particularly valuable for an in-depth and contextualised exploration of a central phenomenon. We therefore define the diversity of a sample as a measure of the range of viewpoints that have been gathered on a central phenomenon.

Researchers critical of snowball sampling respond to this defence by arguing that the method is unable to ensure sample diversity, which is a necessary condition for valid research findings. Indeed, some scholars have stated that snowball samples underrepresent and may even exclude those least keen to cooperate, since referrals may not materialise in an interview if a potential interviewee is only somewhat keen or not at all keen to be interviewed [ 3 , 43 ]. Similarly, potential interviewees with smaller networks may be underrepresented, as they are less likely to be referred for an interview [ 31 , 44 ]. Those with smaller networks may also be in a specific network whose different perspectives may be of interest but are excluded in the final sample. Meanwhile, snowball sampling is said to over represent those interviewees (and their respective networks) that the interviewer spoke with first; the relevant literature refers to this as ‘anchoring’ [ 20 , 39 ].

We do not aim to argue the ‘validity’ of the method, but rather to inform snowball sampling methodologies in order to promote sample diversity. From a qualitative perspective, ‘validity’ can be defined as ‘the correctness or credibility of a description, conclusion, explanation, interpretation or other sort of account’ ([ 45 ], p. 87), while quantitative researchers frequently use the terms ‘generalisability’ and ‘(external) validity’ interchangeably [ 46 , 47 ]. The term ‘validity’ is contested among qualitative researchers, and some qualitative researchers entirely reject the concept for qualitative work [ 48 , 49 ]. We do not aim to resolve this debate via this paper; instead, we focus on the (seemingly less-contested) term ‘sample diversity’. While we acknowledge that this term is not codified in qualitative textbooks such as the SAGE Encyclopedia of Qualitative Research Methods , sample diversity is considered desirable by the various qualitative scholars we reviewed. Boulton and Fitzpatrick demand, for instance, that qualitative researchers ‘ensure that the full diversity of individuals […] is included [in their sample]’ ([ 50 ], p. 84), a mandate echoed by other scholars [ 16 , 51 – 53 ].

In order to operationalise the concept of sample diversity, we used five key methodological recommendations to inform our research. In this paper, we use quantitative analyses from our experiences with snowball sampling to further reflect on these recommendations, which are briefly described below.

Prior personal contacts of the researcher are required

Patton ([ 5 ], p. 176) notes that snowball sampling ‘begins by asking well-situated people: “Who knows a lot about ____? Who should I talk to?”‘. In the absence of a sampling frame for the population of interest, however, the researcher must retain at least some prior personal or professional contacts in the population of interest which can serve as the seeds of the snowball sample [ 2 , 54 ]. Waters contends that building a diverse snowball sample ‘depend[s] almost exclusively on the researcher’s [prior personal or professional] contacts’ ([ 39 ], p. 372).

Sample seed diversity is important

Morgan [ 21 ] has claimed that the ‘best defence’ against a lack of sample diversity is to begin the sample with seeds that are as diverse as possible. Others echo this advice [ 3 , 39 , 55 ], arguing that it is ‘compulsory for the researcher to ensure that the initial set of respondents is sufficiently varied’ ([ 55 ], p. 55). The term ‘chain referral sampling’ has been used for snowball samples that are strategically built via multiple varying seeds [ 3 ].

Technology means face-to-face interviews are no longer required

Some researchers have argued that face-to-face interviews are obsolete. For instance, over 25 years ago, it was claimed there were ‘no remarkable differences’ ([ 56 ], p. 211) between information collected via telephone and information collected via face-to-face interviews. The increasing use of telecommunications in recent years is likely to have further reduced barriers to remote interviewing, and various scholars [ 57 , 58 ] continue to claim that ‘evidence is lacking that [telephone interviews] produce lower quality data’ ([ 59 ], p. 391). In particular, they have highlighted the benefits of using Skype for semi-structured interviews [ 57 ].

However, for snowball sampling, face-to-face interviews help to generate the trust that scholars claim is required in order to gain referrals [ 1 , 31 , 39 , 60 ]. Noy argues that ‘the quality of the referring process is naturally related to the quality of the interaction: […] if the researcher did not win the informant’s trust […], the chances the latter will supply the former referrals decrease’ ([ 1 ], p. 334).

Persistence is necessary to secure interviews

Although the value of persistence may be considered self-evident by some scholars, it is seen by multiple academics [ 61 – 63 ] as a central virtue of qualitative researchers. Many young career scholars who embrace snowball sampling are likely to hear such advice as, ‘If you cannot interview your envisaged interviewees initially, don’t give up!’. A ‘helpful hint’ for qualitative researchers seeking informants is, ‘Persevere–repeat contact’ [ 64 ].

More waves of sampling are required to access more reluctant interviewees

As a remedy for snowball sampling’s previously discussed bias towards excluding those least keen to be interviewed, multiple scholars suggest pursuing a snowball sample for multiple waves (with a new sampling wave reached once an interviewee introduces the interviewer to one or more potential interviewees) [ 65 – 68 ]. Those suggesting this remedy assume that pursuing more waves increases the likelihood of being referred to an interviewee from a particularly difficult-to-reach population who is at least somewhat keen to be interviewed.

Approval for this study was granted by the Central University Research Ethics Committee (CUREC) of the University of Oxford. Our population of interest for our research project were stakeholders in Southeast Asia’s dam industry. Since ‘the most dramatic conflicts over how to pursue sustainable development’ ([ 69 ], p. 83) have occurred over the construction of large dams, we see this industry as a conflict environment with widely varying viewpoints. A conflict environment is one in which people perceive their goals and interests to be contradicted by the goals or interests of the opposing side [ 70 ]. The major conflicting parties in the dam industry tend to be local and international non-governmental organisations (NGOs) and academics (usually keen not to construct a particular dam) versus international donors, the private sector and governments (usually keen to construct a particular dam) [ 71 , 72 ]. Each sub-population operating in a conflict environment can be considered difficult to reach since fear and mistrust are often pervasive [ 7 ]. Snowball sampling is a suitable research method in conflict environments because the introductions through trusted social networks that are at the core of this method can help interviewees to overcome fear and mistrust, which, in turn, ensures access [ 7 ]. This access is needed to gather the widely varying viewpoints in the hydropower industry, in particular viewpoints with regards to what constitutes just resettlement [ 73 , 74 ]. Based on this rationale, we chose snowball sampling as the main method for our research.

In order to ensure sample diversity for our research project on anti-dam movements in Southeast Asia, we aimed to gather perspectives mostly from six main sub-populations: (1) local NGOs, (2) international NGOs, (3) international donors, (4) academia, (5) the private sector and (6) the government. We hypothesized that ‘dam developers’, a main sub-category of the interviewee category ‘private sector’, would be the most significant challenge to ensuring the diversity of our sample. Early in our process, many of the scholars with whom we discussed our research project argued that it would be impossible to interview a dam developer from a Chinese institution; meanwhile, researchers from a comparable research project that ended approximately when our project started reported being unable to interview any dam developers from European institutions. We also initially failed to collect data from dam developers: for instance, a survey we initiated that was distributed by Aqua~Media (host of a major global dam developer conference) to more than 1,500 dam developers yielded just five responses, only one of which was complete. We considered this weak response rate to be due, at least in part, to the dam industry’s negative view of academicians since the publication of Ansar et al. [ 75 ], which Nombre ([ 76 ], p. 1), the president of the International Commission on Large Dams (ICOLD), called ‘[highly] misleading’.

None of our researchers had significant direct links to the dam industry upon the start of the project; however, we did retain a variety of indirect links. Our researchers had past links to a management consultancy that serves various dam industry players, (more limited) links to an international donor working in the hydropower sector and links to activists in Myanmar advocating against dam projects.

After a favourable ethics review of our study by the CUREC of the University of Oxford, we commenced semi-structured interviews in April 2015, mostly via cold calls (we include cold e-mails in the term ‘cold calls’ throughout this paper). Initially, we conducted research via telephone only. We then undertook field research in Singapore, Myanmar and Thailand from June to August 2015 and terminated our data collection in late August 2015.

In total, 81 semi-structured interviews were carried out during this period. From a qualitative perspective, this is a relatively large sample size (for instance, the average qualitative PhD dissertation is based on 31 interviews [ 77 ]); from a quantitative perspective, however, the sample size is quite small [ 78 ]. Of our 81 interviews, 48 (59%) were conducted via telephone, 26 (32%) face-to-face and 7 (9%) online, either via e-mail or an online survey. Most of our interviews (57%) were carried out in July in Myanmar. Of our 81 interviewees, only 24 (30%) were women. Researchers who employ snowball sampling frequently employ personal/professional contact seeds and cold call seeds to build their sample (e.g., [ 2 , 79 , 80 ] with a seed defined as the starting point of a sample [ 65 ]). Of the 81 interviews analysed, 53 (65%) were rooted in a personal or professional contact ( Fig 1 ) (i.e. the seed of the interview pathway was a contact we had already retained prior to the research project). The remaining 28 (35%) interviews were rooted in cold calls.

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Given the sensitive nature of the interview topic, all interviewees were assured anonymity. Thus, all of the interviews are coded, with the first letter indicating the mode of interview ( T for telephone, F for face-to-face, O for online survey or e-mail), the second letter indicating the category of interviewee ( A for academia, G for government, I for international donor, NI for international NGO, NL for national NGO, P for private sector) and the sequence of numbers indicating the interview number within a particular mode. Researcher A is indicated by RA , Researcher B by RB ; CON represents a conference event. Bold type indicates that an interview was completed, while X that an interview was not completed.

As outlined in the previous section, snowball sampling is sometimes criticised for producing samples that lack sample diversity. To address this criticism, we reviewed the (scarce) literature on enhancing sample diversity via snowball sampling procedures prior to commencing our study. Upon reflection during our research, we chose to pursue our analysis retrospectively in order to challenge some of the recommendations provided in literature. Our analysis is structured alongside the five core pieces of advice found in this literature ( Table 1 ). Our results are based on a quantitative analysis of the 81 interviews we conducted. Although we endeavoured to include all interview attempts, some initial cold calls may have been overlooked in this retrospective approach. Therefore, some of our analysis, particularly in Section 4.4, may be too optimistic. Overall, we were able reconstruct 211 reach-out attempts.

Sample diversity is measured by representation from five identified sub-groups.

Results and discussion

On prior personal and professional contacts.

Our analysis provides evidence that sample diversity can be reached even if no prior personal or professional contacts to the population of interest have been retained. The seeds of the interviews are depicted in Fig 2 , with the left side of the figure depicting the 53 interviews based on a personal or professional contact and the right side depicting the 28 interviews that were based on cold calls. This figure shows two main points of interest: first, both types of seeds include interviews in each interview category; second, the interview sub-category ‘dam developer’, which we hypothesised would be the most difficult to include in the sample, is also covered by both types of seeds. We can therefore conclude that a diverse sample could have been built even if we had relied solely on cold calls.

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It is acknowledged, however, that building a snowball sample from cold calls is particularly labour-intensive [ 39 ]: in our research, only 25% of our cold calls led to an interview, compared to 62% of the referrals. Significant differences in the value of referrals persist from one interviewee group to another ( Fig 3 ). We measure the value of referrals via a concept we call ‘network premium’. To gauge the network premium, we subtracted the cold call response rate (i.e., the number of interviews initiated via cold calls divided by the total number of cold calls) from the referral response rate (i.e. the number of interviews initiated via referrals divided by the total number of referrals). Referrals were the most valuable when contacting international donors and private sector players, with network premiums of 74% and 52%, respectively, indicating that these groups are particularly difficult-to-reach populations.

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(1) Unable to retrace for 13 identified reach-outs if initiated via referral or cold call; four reach-outs coded as ‘Other’. (2) Unable to retrace for one interview carried out via referral coded as ‘Other’. (3) Including personal contacts and contacts via conferences. (4) Referral response rate–Cold call response rate.

The overall results from these analyses are encouraging for scholars interested in researching a population to which no personal or professional contacts are retained prior to the research project. While personal or professional contacts maintained to the research population of interest can accelerate the research endeavour, our results also showcase that (at least for our topic of interest) a diverse sample can be built from cold calls if a researcher is willing to invest some time in reach-outs.

On seed variation

Our research confirms the scholars’ advice that seed diversity is important. Fig 4 (a variation of Fig 2 ) depicts the completed interviews from a seed perspective, with RA, RB and cold calls as the three main seeds of the sample. The sample built via RA, who has a background in the private sector, is largely biased towards this sector, with 47% of all interviews seeded via RA private sector interviews. RB conducted 57% of interviews, whose background is closest to local NGOs, were with local NGOs. Meanwhile, the sample built via cold calls indicates no significant biases towards any interviewee category. Interviews based on the network of RB included one (TNL17) with a leading activist from a remote area of Myanmar who provided unique insights into the early days of an anti-dam campaign. This insight helped us to develop a narrative of the campaign that was not skewed to the later days of the campaign and the activists prominent in these later days. The sample diversity ensured via RB was thus central to the quality of our research.

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It is noteworthy that the three different seeds in Fig 4 include interviews in all interviewee categories, including the sub-category ‘dam developer’ (the sole exception is the interviewee category ‘international NGO, which contains zero interviews for RB). This indicates that, at least for our topic of interest, a fairly diverse sample can be generated even if the researcher is unable to vary her or his seed, although the overall data suggest that seed variation can significantly enhance sample diversity. Fig 3 may therefore be viewed as a case for collaboration among researchers; if researchers with different backgrounds and different personal and professional contacts to the population of interest begin to collaborate, such collaborations are bound to contribute to sample diversity.

On face-to-face interviews

Our descriptive analysis provides evidence to further support the argument that face-to-face interviews are redundant, with our data indicating that face-to-face interviews can lead to more sought referrals than telephone interviews (perhaps since trust may be more readily established via face-to-face conversations than over the telephone). Fig 5 aims to quantify the value of face-to-face interviews. Overall, 30 (37%) of our interviews were initiated via prior face-to-face conversations, while prior telephone conversations and online contact each led to only eight interviews (10%). An examination shows that of the nine interviews conducted with dam developers, the interviewee sub-category deemed most difficult to access, seven (78%) were initiated via prior face-to-face interviews, while not a single telephone interview led to a referral to a dam developer. These interviews proved to be essential for our research. For instance, one Chinese dam developer challenged a claim from numerous NGOs that his company would not engage with NGOs, which, in turn, allowed us to present a more balanced portrayal of the interplay between Chinese dam developers and NGOs.

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(1) Comprises interviews with those already retaining a personal or professional contact prior to the research project.

While our research did not investigate whether face-to-face interviews lead to lower-quality data than telephone interviews, our data provide tentative evidence that face-to-face interviews are not obsolete; they can still be helpful for those employing or intending to employ snowball sampling, since these interviews can lead to more sought referrals and thus enhanced sample diversity. We acknowledge, however, that this finding may not be true for all populations. For instance, studies on individuals with sexually transmitted diseases have found that these interviewees (particularly men) tend to report more truthfully in an audio-computer-assisted self-interview (ACASI) than in a face-to-face interview, since interviewees tend to be more comfortable reporting on sexually transmitted diseases to a computer than to a live person [ 81 , 82 ].

On persistence

Our data suggest that persistence can indeed enhance sample diversity, but we can also conclude that excessive persistence does not necessarily yield dividends. Instead of distributing a great many interview reminders during our study, we reached out to the majority of our proposed interview subjects only once. Nevertheless, the scarce data we collected regarding persistence indicates its value. We map this data in Fig 6 , with the left side depicting our success rate in relation to the number of reach-outs (either one, two or three) and the right side depicting a deep dive on success rates achieved with two reach-outs (distinguishing between reach-out attempts to unknown potential interviewees and those to whom we were referred by other interviewees). We sent one interview reminder to 28 of our proposed interviewees. This led to 10 additional interviews, a success rate of 36%, equalling 12% of the total interviews analysed for this paper. Reminders appear to be only somewhat more helpful when contacting referrals in comparison to their usefulness with cold calls–a single reminder led to an interview in 39% of our cases for the former group and 38% for the latter. One of the most valuable interviews for our research gained via a reminder was with the CEO of a Burmese dam developer. This interviewee compared Chinese and European dam developers in Myanmar, which helped us to further refine our narrative on social-safeguard policy adherence by Chinese dam developers in Myanmar.

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(1) Number of reach-outs unknown for 32 reach-outs. Eight potential interviewees responded, but refused interview.

Excessive persistence, however, does not appear to be worthwhile. We sent three reminders to seven of our envisaged interviewees, but as Fig 6 shows, this did not lead to a single additional interview. While our data does not suggest that excessive persistence is helpful to researchers, it may also not be recommended for ethical reasons. A potential interviewee who does not respond to an interview request after two reach-outs may be indicating via this non-response that she or he is not interested in participating in the research. If a single request remains unanswered, the researcher may hypothesise that, for instance, the e-mail was overlooked, a hypothesis particularly likely when conducting interviews with time-pressed leaders of organisations. Indeed, all 10 interviews only carried out upon the second reach-out were interviews with interviewees in management positions.

Our data on persistence provide some evidence that those employing or intending to employ snowball sampling can enhance sample diversity if every reach-out is carefully tracked and followed by a reminder. We typically sent a reminder after one week if no response was obtained upon the first reach-out. This persistence may help to include those least keen to be interviewed for a research endeavour.

Our data show some evidence that, for our topic of study, pursuing interviews for even a few waves provided the perspectives of particularly difficult-to-reach populations and thus achieved sample diversity. More than 60% of our interviews were conducted in the zeroth or first wave ( Fig 7 ). These include seven of the nine interviews conducted with dam developers, the sub-category we deemed most challenging to interview. The remaining two interviews with dam developers were conducted in the second wave. However, not a single interview with a dam developer was carried out in the third wave and beyond, although a fifth of our total interviews were carried out in the third or later waves. Pursuing interviews for multiple waves nevertheless yielded novel insights. For instance, interview FNL12, which was conducted in the sixth wave, yielded insights on small dam construction in Myanmar–a topic of (some) interest to our research endeavour, but not covered in detail by previous interviews. Furthermore, we note that our finding regarding the limited value of multiple waves may also be specific to our population, with this finding perhaps indicating a low degree of network segmentation in the population in question [ 83 ]. Meanwhile, a high degree of network segmentation may impede the pursuance of multiple waves, since interviewees may lack the suitable contacts for a referral [ 84 ].

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While additional waves can lead to novel insights, our overall data on waves provide some evidence that the number of waves pursued is not a definitive indicator for sample diversity. Even very few waves can yield access to particularly difficult-to-access populations.

Our quantitative analysis of pathways to delivering sample diversity in snowball samples yielded the following revisions to the literature’s recommendations:

  • Prior personal contacts are not essential for achieving sample diversity but tend to be helpful, as generating new contacts during research can be labour-intensive.
  • Sample seed diversity is important to achieving sample diversity.
  • Face-to-face interviews build trust and can help to generate further referrals.
  • Persistence (within reason) is helpful in securing interviews.
  • Sample diversity is not necessarily enhanced if a seed is advanced over numerous waves.

We do not claim that these insights are comprehensive, but we believe that these interpretations of our data may serve as a starting point for future scholars using snowball sampling procedures. All of the analyses presented in this section are based only on descriptive statistics. This means, for instance, that we cannot control for confounds such as effort [ 85 ]. An experimental research design would yield the most robust insights on sampling procedures to enhance the sampling diversity of a snowball sample (with, for instance, one research project staffed with scholars with relevant personal or professional contacts and another staffed with scholars without relevant contacts).

Overall, this work aims to advance the literature on snowball sampling as a qualitative sampling approach. While snowball sampling procedures may qualify ‘as the least “sexy” facet of qualitative research’ ([ 1 ], p. 328), these procedures are ‘not self-evident or obvious’ ([ 20 ], p. 141), since the snowball sample does not ‘somehow magically’ ([ 20 ], p. 143) start, proceed and terminate when a scholar attempts to develop a diverse sample. Rather, continuous, deliberate effort by the researcher(s) is required. Our paper has attempted to provide some insights on this effort.

Unfortunately, we developed the idea to write this paper only during the course of our research project, and thus some of our data may be skewed. For instance, we may not have been able to trace all original reach-out attempts and our data on persistence may therefore be biased. Some of those scholars grounded in quantitative thinking may also claim that the insights outlined in Section 4 lack external validity since our sample size is relatively small from a quantitative methodological perspective. In addition, our population was very specific and thus may not be comparable to other difficult-to-reach populations, and we also did not adopt an experimental research design as described above. Hence, we encourage scholars to replicate our findings via their respective research projects that employ snowball sampling. With many scholars claiming to feel more pressed than ever to deliver research results with maximum efficiency, we hope that these initial descriptive analyses of snowball sampling procedures provide some valuable insights to those employing or intending to employ this method and aiming to improve their management of it.

Supporting information

Acknowledgments.

We wish to thank our reviewers at PLOS ONE who provided constructive thoughts on this piece of work. We also thank Ralf van Santen for his outstanding contributions to this work as a research assistant.

Funding Statement

The authors received no specific funding for this work.

Data Availability

No internet connection.

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Snowballing … #Prayforme: A Qualitative Study Using Snowball Sampling

  • By: Wendy M. Edmonds
  • Product: Sage Research Methods Cases Part 2
  • Publisher: SAGE Publications Ltd
  • Publication year: 2019
  • Online pub date: March 15, 2019
  • Discipline: Business and Management , Leadership
  • Methods: Snowball sampling , Focus groups , Purposive sampling
  • DOI: https:// doi. org/10.4135/9781526491039
  • Keywords: informants , key informants , population , survivors Show all Show less
  • Type: Indirect case info Sub Discipline: Leadership Online ISBN: 9781526491039 More information Less information

This case study discusses the experience of reaching an unknown population, the challenges that were encountered, and the need to be flexible to keep progressing in your research. The original research used followership, charismatic leadership, and sacrificial leadership as theoretical frameworks to focus on the survivors of the 1978 Jonestown massacre. Focus groups and individual interviewing methods were used to explore the lived experiences of the mass murder-suicide. In this case study, I discuss how conducting qualitative research required me to identify and interview a population who survived the most horrific event involving church members at that time. Although opposition was anticipated, selecting participants proved to be more challenging than I had imagined. I present the risks involved in choosing a sensitive subject matter that entails having participants to recall a difficult period of their life. There is discussion concerning time restraints imposed on the research, which caused me to swap my internship to conduct a pilot study. This phase was necessary as a turning point in determining whether or not I had the ability to reach the hidden population. Snowball sampling evolved through a process of having to confront rejection while balancing the reality of completing my dissertation. Although snowball sampling is a time-consuming process, it provided a population pool of potential participants. However, purposeful sampling was employed in an effort to ensure diversity among those who agreed to participate in the study.

Snowballing … #Prayforme: A Qualitative Study Using Snowball Sampling

Learning outcomes.

By the end of this case, students should be able to

  • Describe the methodological challenges involved in choosing participants associated with sensitive cases
  • Identify the strengths and weaknesses of snowball sampling in this case study
  • Identify key strategies used to recruit participants
  • Describe the reasons for employing purposeful sampling

Project Overview and Context

I remember November 18, 1978, very well. It was the day that 913 members of Peoples Temple were found dead from a mass murder-suicide in Guyana. I was glued to the television watching all of the special news reports. As a high school student, I wanted to read everything that I could to help me understand what happened. Why would anyone follow a leader that encourages extreme behavior?

Fast forward to November 2008, when special correspondent Soledad O’Brien hosted the untold stories in the documentary CNN Presents: Escape From Jonestown. It was going to air on television at 9:00 p.m. and again I found myself in a state of inquisitiveness. Coming from a Christian background, I always felt safe and secure in my house of worship. Church has always been my foundation for spiritual education, my source of energy, my sense of relief, and my place of restoration. However, church as I knew it and Peoples Temple were not parallel. Why would anyone follow a toxic leader unto death? There were survivors? Who are they? Where are they? What compelled them to be a follower?

These questions ignited the analytical side of me. The perfect time for exploration had just revealed itself! I was almost at the end of the course work in my doctoral program, which required me to complete a proposal for my dissertation. After having a conversation with one of my professors, permission came as no surprise as I was approved to conduct research regarding this event to fulfill the requirement. As I began my research, I noted that there were many stories depicting the leadership style of Jim Jones, the leader of Peoples Temple, except my interest related to the followers. I wanted to do more than send a survey and collect numbers to analyze. I wanted to meet the survivors. I wanted to spend time with them and feel the impact of their stories as it relates to followership.

Barbara Kellerman (2008) defines followership as the response of those in subordinate positions (followers) to those in superior ones (leaders). Although the study of followers is not as prevalent as leadership, it is ever increasing in the body of literature. Simply taking a moment to google the word “followership” initiates a response of 1,180,000 compared with 762,000 a year ago (Ramazzina, 2017) and less than that when I began my research.

It was one thing to understand the need for more studies in followership, yet trying to decide how to reach the survivors (followers) added a whole new dimension. While contemplating on what would be the best means to gather data for my study, taking a qualitative approach meant that I would have to be with the survivors. It was then that I realized the real challenge ahead of me. How much time would it take to identify the survivors? How would I contact any of them? Would they be interested? Getting the answer to these questions formulated new dimensions to my learning.

Research Practicalities

My study involved interviewing human participants. I was required to complete the University Institutional Review Board (IRB) forms. As a researcher, this step in the process was a reminder of the level of sensitivity involved in what I was about to engage in doing. This was not just another mundane practice, but rather a reminder of the importance of transparency involved in conducting live research with human participants. There was a time in the academic community when projects such as the Tuskegee Study of Untreated Syphilis in the Negro Male occurred (U.S. Department of Health and Human Services, 2017). This long-term study was conducted on impoverished African Americans in Macon County, Alabama, for the purpose of tracking the natural course of untreated syphilis (Brandt, 1978; Virtová, Stöckelová, & Krásná, 2018). These unethical practices, over a period of time, resulted in the deaths of the participants including some of the wives, widows, and children who were unknowingly infected (U.S. Department of Health and Human Services, 2017).

The IRB is a collective body comprised of research peers within the university (Martin & Inwood, 2012). They are responsible for ensuring that the scientific methodology employed poses no potential harm to the participants while obligating the researcher to work with integrity. Therefore, obtaining permission to allow them to participate in the study was essential. I completed the required IRB forms to ensure adherence to APA ethical principles. Included in my forms was specific documentation that detailed (a) participant consent, (b) confidentiality, (c) participants’ anonymity, and (d) participant privacy and right to withdraw from the study at any time (Creswell, 2007b). Initially, the forms were declined. Given the nature of the study, the IRB required me to be very specific regarding participants’ release.

This meant that I had to address the risks involved with participants re-living a traumatic experience. It was no easy task. I spent time reading articles regarding post-traumatic stress disorder. It was necessary for me to be clear about the healing process from traumatic events and what it means to raise painful memories. Outlining the steps for participants to opt out came as a result of perusing the U.S. Department of Health and Human Services, Substance Abuse and Mental Health Services Administration (SAMHSA), for information. Increasing my knowledge also heightened my sensitivity concerning trauma. Only then was I able to include a written section satisfying the IRB prerequisite, which included making an emphasis on the fact that everyone had a right to leave at any time during the interview.

After making the corrections and re-submitting, I received approval and was able to begin. Embarking on a research project of this nature provided no blueprint for me to follow. I felt as though I was on my own. While watching the CNN special, I took notes; especially at the end when the credits rolled on the screen. My next step was to contact the special correspondent, Soledad O’Brien, to solicit support in connecting me with people that would be interested in participating in my dissertation research, or at least tell me where to begin. The following business day I confidently placed a call to CNN introduced myself, described the purpose of my call, and asked to speak to Mrs. O’Brien. That nice, sweet voice on the other side of the phone let me know, in the politest manner, that I would most likely not get a return call. Rejection! I then crafted an email for approval to send with the following content:

Hello ___________,

I am a student in the Organizational Leadership doctoral program at University of Maryland Eastern Shore. I am in the process of gathering data for my research and would like to interview you to discuss your experience regarding the Jonestown survivors. Please call me or email me to let me know if your schedule permits. I look forward to hearing from you.

Wendy M. Edmonds

Sensing a numbness from being rejected previously left me with the feeling that my attempt to contact a survivor should be brief in my request and follow up with more details when someone contacted me with interest. The email told the potential participant who I was, what I was doing, and what I needed from them. There wasn’t even a participant information sheet provided as an attachment. That was a mistake. At the time, I thought it was a good plan as an honest attempt at being non-intrusive. My thought was to get the important information to them in the first few sentences, which would help them decide if they were interested. Of course, I read the literature around how the initial email leaves a perception about who you are. It’s true, sending an email to recruit potential participants is similar to going on an interview for a job … you have one time to make a good first impression. With that said, I had to defend developing a brief email prior to approval.

Not losing focus was important, so I continued moving forward conducting research on the Internet to see what books had been written by the survivors. What a tedious, time-consuming task. There are plenty newspaper articles, books, and blogs. Some have been written by survivors and some are not. What helped me to decipher the information was to go back and cross check the authors from the Internet research with the names of the survivors interviewed in the CNN special. That was a start. From there, the email distribution began; 48 hours later, I received my first response. I was so excited, thinking “this is good … right?” Wrong. To sum it up, the harsh email response indicated that they were not interested and preferred that I never contact them again. Rejection 2! What could I have done differently? Was there another way to ethically attempt to make contact? The sting from that email forced me to re-evaluate my approach. Perhaps being anxious about the time frame that I had to work within my program to conduct research, coupled with being excited about the possibilities of how my study would contribute to the body of literature, caused me to be over zealous.

Snowball Sampling

Suddenly, it occurred to me that casting the net was not fruitful. This was going to take time. I asked for approval to conduct a pilot study in place of completing an internship. A pilot study would help me to determine if I were capable of reaching a hidden population. Permission was granted. What type of sampling could I use to be effective? The most useful technique that seemed to fit was snowball sampling. In my mind, I thought of the perfect tweet that described how I was feeling at the time—Snowballing … #prayforme. According to Amy Ellard-Gray, Nicole Jeffrey, Melissa Choubak, and Sara Crann (2015), snowball sampling is a highly effective recruitment strategy that enables the researcher to gain access to vulnerable populations that are otherwise difficult to reach. I had to consider the reality that this population may not be accessible for many reasons including the fact that they were associated with Jonestown. The term alone has so many negative connotations. Hidden populations tend to be smaller compared with the general population for reasons related to stigma or those who are geographically dispersed, to name a few. Chaim Noy (2008) suggests that because of the sensitive nature of the discussion that would take place in my study, it would be beneficial as a researcher to rely on an informant to provide the contact information of others for me to gain access to those who may be willing to participate. Chain-referral sampling, as snowball sampling is sometimes referred to, is used to study a social structure as in the case of Jonestown and its former members. Through the use of informants, participants are chosen because they are relevant to the study. This individual provides information to the researcher regarding others who may be considered as a possible selection for the study (Griffith, Morris, & Thakar, 2016). The challenge with this method of sampling is that bias is introduced as the informant is given the responsibility of recruiting. Keeping that in mind, I continued marinating on snowball sampling techniques. I began reading some of the books written by the survivors, which provided more insight into understanding the personal journey. During this time, I received an email response from a news reporter who agreed to participate and then there was another email response from a survivor. The first two sentences read, “I apologize for not getting back to you sooner, I am honored and humbled by the outpouring of love. That is an honor for me” (Edmonds, 2011). What a relief.

Time had passed, but my program requirements remained the same. It was better for me to use this opportunity as a pilot study for my dissertation by interviewing the two who responded. D. J. Danelo (2017) suggests that when interviewing, you should enter into the discussion with a strategy. I needed participants. Without a population, there was no study. How do I tactfully reach other survivors? That was the most pressing unanswered question. Having devised a strategy to expand my outreach, my plan was to ask the two respondents to also participate in helping me develop a participant pool. I asked them to share thoughts about what would be the best way for me to navigate the process of conducting this research while being sensitive to the fact that participants may ignore requests such as mine for fear of being exploited. With that in mind, I designed an interview protocol.

Research Design

Both interviews for the pilot study were conducted over the phone. As the participants who agreed to be interviewed lived in California, that put me in a position to have to travel long distance. However, I wanted to reduce the cost associated with conducting this research as much as possible. Prior to the start of this portion of my research, I obtained written authorization from the participants to record during the interview. A conference call service was used to facilitate the recording process. Now that the technological aspect of the research had been taken care of, getting started with the interview had its own set of challenges. I wanted them to feel comfortable sharing with me. My concern was making sure that my genuine personality came across during the multiple phone calls with total strangers. Building a rapport with participants is critical to establish a sense of mutual trust. I was hopeful that my passion regarding followership and intent to remain sensitive throughout the entire process was evident in each conversation with the interviewees. According to Karin Klenke (2008), this can be facilitated by empathetic listening and egalitarian relationships between interviewer and interviewee. There came a time in the conversation where I had to follow up with probing questions. I started thinking, what if the question is not well received? My anxiety was at an all-time high. So, after asking the difficult questions, I listened. They began to discuss their childhood dreams, relationships with family members, their jobs, their faith, their fears; and I was moved by the candidness expressed as they shared their experiences without reserve. I was able to gain their trust by scheduling an initial phone call prior to the recording. It was during that time that I provide as much information about followership, an unfamiliar term to them, to help the participants understand how the research was going to be framed. While on a call with one of the participants, there was a moment when acknowledged the emotion in a delicate manner reminding them to take the time they needed before moving on in the discussion. The caring and pausing the conversation when necessary were some of the extra steps that were taken to build the trust factor. In doing that, it helped to foster an environment where the participants were willing to offer me recommendations concerning places to visit and events to attend.

Key Informants

However, when it came to suggestions regarding people to interview, things were a little different. The information did not flow as freely. I sensed that the hidden population I wanted to reach was a protected community … and for good reason. I understood how that came to be. I was given the name and contact information of one person. The participant instructed me to begin by having a conversation with the recommended person of interest and they would be able to help me move forward from there. While receiving the instruction, I detected a tone of confidence. Naturally I was filled with enthusiasm, as my pilot study was completed.

I was operating in confidence believing that finding my population was obtainable. I forged ahead as recommended, understanding the harsh reality that snowball sampling was going to be a slower process than previously expected. Nonetheless, following up on the lead was a stress reliever. Even though the informant was pleased with the feedback received from the participants in my pilot study, there was additional information that was needed before any supplementary material was disclosed. Suddenly my role had changed. I was no longer the interviewer. I had become the interviewee. The informant asked very pointed questions about my research: How prepared are you for the interview sessions because everyone’s experience was different and this can lead to strong discussion? Have you read any of the literature written by the survivors? What do you plan to do with your work when completed? At first I felt intimidated, but as time went on, it was clear to me that my answers were actually helping to provide enough substance for the informant to give direction in my study so that it would not duplicate works that already exist, but instead it was helpful in making my research journey a success.

In the end, the informant provided a wealth of information for me to carry on my research. I was given particulars regarding characteristics of the survivors who were potential participants, which helped in building a diverse group with a rich demographic. Some were children when they entered Peoples Temple and then there were those who willingly went joined as adults. We had conversation about the culture in Jonestown. There was a oneness among the people who loved each other. There were examples of how the members of Jonestown believed in the “agriculture project” and were proud of their accomplishment … building a community in the middle of the jungle—and then, there was Jim Jones. There were those who feared him, hated him, and yet obeyed him. I wanted to have the opportunity to recruit as many as I possibly could to bring the various perspectives to my research. My most memorable moment of all happened when I was given a lesson in etiquette for engaging this sensitive population. I was reminded to be patient with the recruiting process. The people that I planned to approach are those who have been deeply wounded. From a spiritual perspective, I was told that the survivors can be anywhere in the spectrum from having faith in God to not believing in anything at all. As a researcher, it was my responsibility to operate with respect and humility—and that is what I set out to do.

After receiving the contact information of several prospective participants, I followed up by speaking to all of them. Each of the prospective participants provided me with the name and contact information of another person to contact. This process went on for a period of weeks. The list of potential contributors was increasing. With the list compiled, I then had the task of reviewing the demographics to ensure that diversity was represented in the group of participants. In doing so, this posed a shift in the sampling technique. I was no longer using snowball sampling, but rather employing purposeful sampling.

Method in Action

Mildred Patten (2018) asserts that purposeful sampling is used in qualitative studies for researchers to look for participants who would be rich sources of information. In choosing the participants, a purposeful sampling strategy known as maximal variation sampling was used. According to John Creswell and Vicki Clark (2007), the central idea of this type of sampling is that the diversity in backgrounds of those who are chosen will provide a good qualitative study due to the different views on the key concept being explored. During the initial conversations that I followed up on, I captured demographic information (race, age range, ethnicity, and location on November 18, 1978) on each participant. Using criteria of this nature helped me to identify those who would invigorate a rich discussion.

Although most of Jonestown was populated with African Americans who were poverty stricken, there were members of other races including biracial members. The members came from all walks of life including ex-convicts as well as families from upper-middle-class communities. In some cases, children were sent to Jonestown with relatives. Some of the members of Jonestown were in Jim Jones’s inner circle, while others watched as the hierarchy took shape. Jonestown, a place that was once showcased as the community jewel that housed multiple members of families: mothers, fathers, grandparents, nieces, nephews, and cousins, was a place of dreadful memories. I took my time evaluating the contact information, demographics, and my journal notes.

After the identification process was completed, I developed a recruitment letter and prepared it for distribution via email. Below is the content of that letter:

Recruitment Letter

October 9, 2009

Dear ______________________, You are invited to take part in a research study conducted through the Organizational Leadership Doctoral Program—University of Maryland Eastern Shore Princess Anne, Maryland. I am a Ph.D. candidate in Organizational Leadership. I will be conducting focus group sessions to discuss your experiences in Jonestown and the effects these experiences had on your personal and professional lives since then. Please refer to my article at https://jonestown.sdsu.edu/?page_id=82834 for more details about my research. These sessions will take place at____(LOCATION)______and will include the participants and researcher. During this time you will be able to share your thoughts and experiences. Two sessions will be conducted each day as follows: Monday, November 16, 2009 10:00am - 12:00pm and 2:00pm - 4:00pm Tuesday, November 17, 2009 10:00am - 12:00pm and 2:00pm - 4:00pm. Participation is strictly voluntary and you may withdraw from the study at any time. All responses will be held confidential and anonymity is guaranteed. If you are interested in participating, please respond by October 31, 2009 with your date and time preference. I can be contacted via email: XXX or phone XXX. Thank you in advance for your support.

Wendy M. Edmonds, ABD

In all, nine survivors responded, though not at the same time. However, the first ones who replied, I reviewed their documents. It was obvious that no one had a date or time preference. I was puzzled … happy, but confused. What did this mean? I placed a call to my informant who told me that the location was changed to a place chosen by the group to ensure that they felt comfortable having such an intimate dialogue. They also selected one date and changed the time to later in the evening to accommodate schedules in hopes of increasing participation. Much to my surprise, the survivors were having their own conversations among the group and encouraging each other to participate. They realized that it had been years since they had seen each other and more importantly, it was going to be the first time they would all gather together in one setting to participate in a focus group.

Naturally, having one focus group changed the scope of my study. Initially, I was disappointed. However, later in the week I was contacted by two survivors for an individual interview. There were four participants present for the first focus group. At the end of the session, those who were unable to join in were contacted by the key informant. They asked me to hold another focus group because they really wanted to be a part of the research. Two months later, I returned and repeated the process. The second focus group had five survivors in attendance. One of the participants in the second focus group also participated in the first one as well. I ended up with a total of nine participants as the final number.

Focus groups and individual interviews with members from this group delivered an array of content that was captured. The participant pool included survivors who joined Peoples Temple as children and some as adults. Each had a different position while in Jonestown. There were those who entered into Jonestown married but returned to the United States without a spouse. There were those who were Biracial, African Americans, or Caucasians; all were in the age range category of 50 and up. Diversity brought a richness to the research that cannot be substituted.

Although the snowball sampling process was slow, it gave me time to reflect and make changes when necessary. However, purposeful sampling was more strategic and beneficial. Using this approach, I had to take into account the size of the sample being studied and what role they were in while in Jonestown (Creswell, 2007a). Beyond the demographic data, I had an initial brief conversation, which provided me with little nuggets of information to get a glimpse into what their social life was like among the members and what led to their decision to join Peoples Temple and follow Jim Jones to Jonestown. Furthermore, the interview protocol opened discussion to capture chronological details and other information regarding specific events such as the “White Nights” where the members of Jonestown were encouraged to commit revolutionary suicide in the event of a takeover. Material of this nature combined with the demographics created a structure for me to use as I facilitated the focus group discussion.

Moreover, I was able to ascertain from those who responded, whether or not I had a diverse group or if I needed to cast the net by re-sending the email again and get additional participants. According to the information supplied by the key informant, I had survivors who represented three different races and belonged in one of the four different age range groups—categories that delineate children, teens, and adults when they entered Jonestown. Although my sampling was small, my research did not lack variety as it relates to the survivors. There was, however, one group that I was unable to get any response from to participate in the research, and those were the survivors from the air strip where Congressman Leo Ryan along with others were gunned down while boarding the plane to leave Jonestown.

As for the survivors, the transcripts from the stories that were shared and the tears that were shed did leave a lasting impression on me. There was a point in my research where I questioned my sampling method. Snowball sampling seemed to have slowed the entire process. This time, I thought to myself, “Snowballing … #PrayForMe.” In the end, I value all that was accomplished by recruiting participants one-by-one. I respect the challenges I encountered, and I receive the lessons learned.

Practical Lessons Learned

Snowball sampling can slow the process.

Identifying a key informant takes time. Finding other informants takes more time. When I received the first email of rejection, it was painful because I thought I was careful enough not to offend potential participants. Sending out an email to the general population of survivors was insignificant. Spending time to learn as much as you can about the population you are studying prior to attempting to contact them is practical. As you look for an informant that will be able to support the goals of the research, a more targeted approach is recommended. Due to the extreme sensitive nature of the Jonestown murder-suicide, some survivors desire to have no connection with that part of their past and were not interested. Once you identify a key informant, compiling a list of people that you may want to reach out to and presenting it to the key informant for discussion is a better approach.

However, using key informants has its drawbacks. While I was grateful to have one, I also had reservations. As a researcher, relying on an informant is relinquishing control. I explained what I wanted in a focus group panel, but I did not know if the pool of people would be handpicked based on personal preference. That can pose a danger as the informant would then have the power to control the narrative. Fortunately, my key contact had a great understanding of the value of research, respected me, and viewed the work that I was doing using followership as a theoretical framework as a means of helping others.

Snowball Sampling Can Generate a Network of Potential Participants: Identify Eligibility Criteria to Employ Purposeful Sampling

To have a variety of experiences for all to share, developing criteria to use for selecting participants becomes crucial in building diversity among the group. One key informant explained to me that there were two types of survivors of the Jonestown Massacre. There were survivors who were members of Peoples Temple but not located in Jonestown, and then there were survivors who were on the compound or in the vicinity and escaped Jonestown on the day of the mass murder-suicide. Having that knowledge was helpful in segmenting the participants, but then there were other issues that plagued me.

Sending emails to a distribution list and recruiting potential participants over the phone works for initial contact. Moreover, another concern of mine was the fact that each participant had the right to leave the interviewing sessions whenever they wanted to. I was constantly thinking about what that would look like if all of those who agreed to participate were unable to stay the entire time. Despite making every effort to be satisfied with the number of respondents that I worked so hard to get, there was still overwhelming fear that I encountered all of the time.

As a result, I was open to having additional participants that met the criteria. It wasn’t until I went to California that I experienced the benefit of being with the victims of such a horrible tragedy. During my time in California, the survivors were able to interact with me. I later discovered the respect the survivors had for me because of the way I blended in at the events as opposed to acting as if I were a reporter trying to get a story. My ability to assimilate did not take place as a result of a polished skill; that happened because I too was quietly overtaken by the emotion of the events. As an observer, it was impossible to be there and not sense the pain, anger, and anguish that the families were experiencing. Employing my new found etiquette and expressing my sensitivity allowed the survivors in attendance to contact me with an interest in participating in the research. Although my expectations for an increased number of participants was my initial desire, I had to remember that the purpose of focus groups was to understand the perceptions of a phenomenon and through the process use discernment regarding the Jonestown survivors.

The focus groups in my study provided an opportunity for the participants to be together and share in a safe environment. I originally secured a conference room in a hotel to use when conducting the interviews and focus groups. That was not acceptable to the survivors, as some were not comfortable being in an unknown environment. Therefore, one of the survivors hosted at a location that all of them were familiar with and felt comfortable being in that space. This was going to be a time where they would be free to speak without judgment and having no fear. This was an essential benefit for all of them as they shared in the excitement of meeting together over 15 years to support research based on followership. The significance of building a diverse group of participants was evident as the stories that were shared among the participants filled in some of the blanks in their lives that had been left unanswered for over 31 years.

Snowball Sampling Resulting in Diversity Requires Practicing Facilitation and Interviewing Skills

As informants provide names and contact information, researchers ask questions to make sure that they are recruiting those who meet the criteria. This builds diversity among group members in areas such as personalities, experiences, and beliefs during discussion. For example, each participant joined Peoples Temple for different reasons and the content of the discussion presented various perspectives about their lives in Jonestown. While facilitating the focus groups, there were times when strong disagreements regarding the sequence of events and what precipitated certain events occurred. Prepare for the times when issues are strongly debated. There needs to be a balance between allowing participants to share their experiences and knowing when to move on without disregarding comments. As a facilitator, there may be times when in any other setting, you would ask a follow-up question. However, because of the sensitive nature of the subject in discussion, emotions may not dictate that you do so. I began by asking the first question in the protocol. That was followed by the next 3 min of tears from everyone in the focus group. It was time to pause. I gained respect from the participants by allowing them time to grieve. It is impractical to predict group discussion. Researchers should be prepared to anticipate the flow of the conversation and be prepared to make decisions to keep the discussion moving along or have the group re-visit the unanswered questions in the interview protocol (Krueger & Casey, 2009). As time moved on, the responses were so intense that some of my follow-up questions were answered through discussion. That is why practicing your interviewing skills will prepare you to respond in situations with similar conditions.

Conducting research is a journey. I am passionate about followership and applauded the opportunity to interview the survivors of such a tragedy to gain insight into leader–followership interdependencies. As any beginner researcher discovers, the challenges that occur encourage you to learn how to be flexible and creative in overcoming opposition. This may mean changing a strategy, increasing your literature intake, or supplementing your sampling technique. The information and examples I have provided allowed me to share the emotional upsets and the academic encounters that led to a successful completion of my study involving a population that had not previously participated in focus groups in 31 years since the event.

Exercises and Discussion Questions

  • (a) Discuss one of the advantages of a slow snowball sampling process.
  • 2. Identify areas where the researcher utilized self-reflexivity.
  • (a) Discuss some of the challenges the researcher encountered in the initial contact.
  • (b) What other creative measures could have been employed by the researcher to contact the survivors?
  • (a) Discuss strengths and weaknesses of snowball sampling.
  • (b) Discuss the issues the researcher encountered in obtaining informants.
  • (a) What do you think prompted that discussion?
  • (b) What are the benefits of etiquette when approaching potential participants?
  • 6. Describe the added value purposeful sampling made in the study.

Further Reading

Web resources.

Sampling knowledge: The hermeneutics of snowball sampling in qualitative research . Retrieved from https://www.tandfonline.com/doi/abs/10.1080/13645570701401305

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Methodology

  • What Is Snowball Sampling? | Definition & Examples

What Is Snowball Sampling? | Definition & Examples

Published on August 17, 2022 by Kassiani Nikolopoulou . Revised on June 22, 2023.

Snowball sampling is a non-probability sampling method where new units are recruited by other units to form part of the sample . Snowball sampling can be a useful way to conduct research about people with specific traits who might otherwise be difficult to identify (e.g., people with a rare disease).

Also known as chain sampling or network sampling , snowball sampling begins with one or more study participants. It then continues on the basis of referrals from those participants. This process continues until you reach the desired sample, or a saturation point.

A number of criteria are used for the selection:

  • The couple must have been together for a period of at least five years.
  • The couple must live together now.
  • The couple must live within a certain geographic area.
  • The couple must have examples of changes or challenges they have experienced together (e.g., long-distance, illness or loss of a loved one).

Table of contents

When to use snowball sampling, types of snowball sampling, advantages and disadvantages of snowball sampling, other interesting articles, frequently asked questions about snowball sampling.

Snowball sampling is a widely employed method in qualitative research , specifically when studying hard-to-reach populations .

These may include:

  • Populations that are small relative to the general population
  • Geographically dispersed populations
  • Populations possessing a social stigma or particular shared characteristic of interest

In all these cases, accessing members of the population can be difficult for non-members, as there is no sampling frame available.

Research in the fields of public health (e.g., drug users), public policy (e.g., undocumented immigrants), or niche genres (e.g., buskers) often uses snowball sampling.

This sampling method is also used to study sensitive topics, or topics that people may prefer not to discuss publicly. This is usually due to a perceived risk associated with self-disclosure. Snowball sampling allows you to access these populations while considering ethical issues , such as protecting their privacy and ensuring confidentiality.

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Snowball sampling begins with a convenience sample of one or more initial participants. Multiple data collection points (or waves) follow. These initial participants, called “seeds,” are used to recruit the first wave’s participants.

Wave 1 participants recruit wave 2 participants, and the sample expands, wave by wave, like a snowball growing in size as it rolls down a hill.

Depending on your research objectives , there are three different types of snowball sampling methods to choose from:

Linear snowball sampling

Exponential non-discriminative snowball sampling, exponential discriminative snowball sampling.

Linear snowball sampling relies on one referral per participant. In other words, the researcher recruits only one participant, and this participant, in turn, recruits only one participant. This process goes on until you have included enough participants in the sample.

Linear snowball sampling works best when there are few restrictions (called inclusion and exclusion criteria ) as to who is included in the sample.

As you finish up the interview , you ask them if they can refer someone else who also owns a tiny house. They happen to know someone, and pass the contact details to you. You interview them as well. Towards the end of the interview, you ask them to introduce you to one more person.

If more than two names are mentioned, it is a good idea to ask the interviewee how well they know those people, and then interview the person who is least known to them.

In exponential non-discriminative snowball sampling , the first participant provides multiple referrals. In other words, the researcher recruits the first participant, and this participant in turn recruits several others. The researcher includes all referrals in the sample. This type of snowball sampling is best used when you want to reach a larger sample.

In this method, participants give multiple referrals. However, the researcher screens those referrals, choosing only those who meet specific criteria to participate in the sample. The key difference between this and exponential non-discriminative snowball sampling is that not all referrals are included in the sample.

Exponential discriminative snowball sampling is most used when screening participants according to specific criteria is vital to your research goals.

As you inquire with your acquaintances, you find someone who bought a tiny house a year ago. At the end of the interview, you ask them if they know of other owners. You do not specify that the purchase has to be in the past three years.

As it happens, they do know of two more people who bought tiny houses in the same area as they did. You contact both, and find out that one bought the house four years ago and the other eight months ago. Since the one who bought the house four years ago does not meet your criteria, you only interview the other.

Like all research methods , snowball sampling has distinct advantages and disadvantages. It is important to be aware of these in order to determine whether it’s the best approach for your research design .

Advantages of snowball sampling

Depending on your research goals, there are advantages to using snowball sampling.

  • Snowball sampling helps you research populations that you would not be able to access otherwise . Members of stigmatized groups (e.g., people experiencing homelessness) may hesitate to participate in a research study due to fear of exposure. Snowball sampling helps in this situation, as participants refer others whom they know and trust to the researcher.
  • Since snowball sampling involves individuals recruiting other individuals, it is low-cost and easy to recruit a sample in this way.
  • Unlike probability sampling , where you draw your sample following specific rules and some form of random selection , snowball sampling is flexible . All you need is to identify someone who is willing to participate and introduce you to others.

Disadvantages of convenience sampling

Snowball sampling has disadvantages, too, and is not a good fit for every research design.

  • As the sample is not chosen through random selection , it is not representative of the population being studied. This means that you cannot make statistical inferences about the entire population and there is a high chance of research bias .
  • The researcher has little or no control over the sampling process and relies mainly on referrals from already-identified participants. Since people refer others whom they know (and share traits with), this sampling method has a high potential for sampling bias .
  • Relying on referrals may lead to difficulty reaching your sample . People may not want to cooperate with you, hesitate to reveal their identities, or mistrust researchers in general.

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

Snowball sampling is best used in the following cases:

  • If there is no sampling frame available (e.g., people with a rare disease)
  • If the population of interest is hard to access or locate (e.g., people experiencing homelessness)
  • If the research focuses on a sensitive topic (e.g., extramarital affairs)

Snowball sampling relies on the use of referrals. Here, the researcher recruits one or more initial participants, who then recruit the next ones.

Participants share similar characteristics and/or know each other. Because of this, not every member of the population has an equal chance of being included in the sample, giving rise to sampling bias .

Snowball sampling is a non-probability sampling method , where there is not an equal chance for every member of the population to be included in the sample .

This means that you cannot use inferential statistics and make generalizations —often the goal of quantitative research . As such, a snowball sample is not representative of the target population and is usually a better fit for qualitative research .

Snowball sampling is a non-probability sampling method . Unlike probability sampling (which involves some form of random selection ), the initial individuals selected to be studied are the ones who recruit new participants.

Because not every member of the target population has an equal chance of being recruited into the sample, selection in snowball sampling is non-random.

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Sampling Knowledge: The Hermeneutics of Snowball Sampling in Qualitative Research

Profile image of Chaim Noy

2008, International Journal of Social Research Methodology

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  1. Snowball Sampling: Definition + Examples

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  2. (PDF) Snowball Sampling: A Purposeful Method of Sampling in Qualitative

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  3. (PDF) Snowball sampling

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  4. What is snowball sampling: methods and examples

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  5. (PDF) Sampling Knowledge: The Hermeneutics of Snowball Sampling in

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  6. Schematic of the snowball sampling technique, including actual number

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VIDEO

  1. Snowball Sampling

  2. QUALITATIVE SAMPLING TECHNIQUES, CONVENIENCE, PURPOSIVE, SNOWBALL & QUOTA

  3. snowball sampling #sidangskripsi #kuliah #skripsi #kampus

  4. Types of qualItative data sampling

  5. SAMPLING METHODS #Shorts #Research

  6. Qualitative and quantitative Sampling in Research

COMMENTS

  1. Snowball Sampling: A Purposeful Method of Sampling in Qualitative Research

    Qualitative Research Snowball Sampling: A Purposeful Method of Sampling in Qualitative Research CC BY-NC 4.0 Authors: Mahin Naderifar Zabol University Of Medical Sciences Hamideh Goli...

  2. PDF Parker, C, Scott, S and Geddes, A (2019) Snowball Sampling. SAGE ...

    Snowball sampling is one of the most popular methods of sampling in qualitative research, ... Snowball Sampling and Qualitative Research . There is an abundance of research examples where a snowball sample has been used. Howard Becker's . Outsiders: Studies in the Sociology of Deviance

  3. Enhancing the sample diversity of snowball samples: Recommendations

    Abstract Snowball sampling is a commonly employed sampling method in qualitative research; however, the diversity of samples generated via this method has repeatedly been questioned. Scholars have posited several anecdotally based recommendations for enhancing the diversity of snowball samples.

  4. Enhancing the sample diversity of snowball samples ...

    Snowball sampling is a commonly employed sampling method in qualitative research; however, the diversity of samples generated via this method has repeatedly been questioned. Scholars have posited several anecdotally based recommendations for enhancing the diversity of snowball samples.

  5. [PDF] Snowball Sampling: A Purposeful Method of Sampling in Qualitative

    Snowball Sampling: A Purposeful Method of Sampling in Qualitative Research M. Naderifar, H. Goli, Fereshteh Ghaljaie Published 30 September 2017 Education Background and Objectives: Snowball sampling is applied when samples with the target characteristics are not easily accessible.

  6. Sage Research Methods Foundations

    Snowball Sampling By: Charlie Parker , Sam Scott & Alistair Geddes | Edited by: Paul Atkinson, Sara Delamont, Alexandru Cernat, Joseph W. Sakshaug & Richard A.Williams Publisher: SAGE Publications Ltd Publication year: 2019 Online pub date: September 17, 2019 Discipline: Sociology, Geography

  7. (PDF) Snowball sampling

    ... The questionnaire was distributed using snowball sampling. Snowball sampling is one of the most popular methods in qualitative research, with its core feature being networking and...

  8. (PDF) Sampling Knowledge: The Hermeneutics of Snowball Sampling in

    A qualitative research model was applied in the study, specifically using the snowball model from qualitative research models. A semi-structured interview form was used as the data collection tool.

  9. Sampling Knowledge: The Hermeneutics of Snowball Sampling in

    The latter have been overlooked, qualifying only as a 'technical' research stage. This article attends to snowball sampling via constructivist and feminist hermeneutics, suggesting that when viewed critically, this popular sampling method can generate a unique type of social knowledge—knowledge which is emergent, political and interactional.

  10. PDF Snowball Sampling: A Purposeful Method of Sampling in Qualitative Research

    Abstract Background and Objectives: Snowball sampling is applied when samples with the target characteristics are not easily accessible. This research describes snowball sampling as a...

  11. Snowballing … #Prayforme: A Qualitative Study Using Snowball Sampling

    Wendy M. Edmonds Product: Sage Research Methods Cases Part 2 Publisher: SAGE Publications Ltd Publication year: 2019 Online pub date: March 15, 2019 Discipline: Business and Management, Leadership Methods: Snowball sampling, Focus groups, Purposive sampling DOI: https:// doi. org/10.4135/9781526491039 Keywords:

  12. [PDF] Sampling Knowledge: The Hermeneutics of Snowball Sampling in

    Corpus ID: 53538877 Sampling Knowledge: The Hermeneutics of Snowball Sampling in Qualitative Research Chaim Noy Published 11 September 2008 Sociology International Journal of Social Research Methodology

  13. Snowball Sampling: Introduction

    Snowball sampling is a well-known, nonprobability method of survey sample selection that is commonly used to locate hidden populations. This method relies on referrals from initially sampled respondents to other persons believed to have the characteristic of interest.

  14. What Is Snowball Sampling?

    Revised on June 22, 2023. Snowball sampling is a non-probability sampling method where new units are recruited by other units to form part of the sample. Snowball sampling can be a useful way to conduct research about people with specific traits who might otherwise be difficult to identify (e.g., people with a rare disease).

  15. [PDF] When the snowball fails to roll and the use of 'horizontal

    Abstract Snowball sampling is frequently advocated and employed by qualitative social researchers. Under certain circumstances, however, it is prone to faltering and even failure. Drawing on two research projects where the snowball failed to roll, the paper identifies reasons for this stasis. It goes on to argue that there are alternative forms of networking that can be developed by the ...

  16. PDF Snowball sampling completion

    The snowball sampling, as a network research, presents numerous advantages in. registering "hidden populations" such as: drug consumers, people with deviant sexual behavior, people with rare diseases which are unapproved by society, illegal immigrants, people working in the. black market, but also presents a major disadvantage - the ...

  17. [PDF] Snowball Sampling—I

    1938. 220. PDF. Snowball sampling is a recruitment method in which an investigator enlists the help of a research subject in identifying, and possibly recruiting, additional subjects. It is useful when the investigator may not have access to a population of potential subjects who meet inclusion criteria, which may often be stigmatizing.

  18. (PDF) Snowball Sampling: A Purposeful Method of Sampling in Qualitative

    Snowball sampling can be effectively used to analyze vulnerable groups or individuals under special care. In fact, it allows researchers to access susceptible populations. Thus, it is suggested to consider snowball sampling strategies while working with the attendees of educational programs or samples of research studies. See Full PDF Download PDF

  19. (PDF) Sampling Knowledge: The Hermeneutics of Snowball Sampling in

    This article attends to snowball sampling via constructivist and feminist hermeneutics, suggesting that when viewed critically, this popular sampling method can generate a unique type of social knowledge—knowledge which is emergent, political and interactional.

  20. Enhancing the sample diversity of snowball samples ...

    Snowball sampling is a commonly employed sampling method in qualitative research; how-ever, the diversity of samples generated via this method has repeatedly been questioned. Scholars have posited several anecdotally based recommendations for enhancing the diver-sity of snowball samples.

  21. (PDF) Sampling Knowledge: The Hermeneutics of Snowball Sampling in

    Social Research Methodology Vol. 11, No. 4, October 2008, 327-344 Sampling Knowledge: The Hermeneutics of Snowball Sampling in Qualitative Research Chaim Noy Downloaded By: [Noy, Chaim] At: 15:11 11 September 2008 Received 12 July 2006; Accepted 19 February 2007 Taylor and Francis Ltd TSRM_A_240016.sgm During the past two decades we have ...

  22. PDF Snowball Sampling in Qualitative Research Sampling Knowledge: The

    This article attends to snowball sampling via constructivist and feminist hermeneutics, suggesting that when viewed critically, this popu-lar sampling method can generate a unique type of social knowledge—knowledge which is emergent, political and interactional.

  23. (PDF) Enhancing the sample diversity of snowball samples

    Snowball sampling is a commonly employed sampling method in qualitative research; however, the diversity of samples generated via this method has repeatedly been questioned. Scholars have...