cascades mental health clinic case study

Implementation and Mental Health Outcomes of a Service Cascade Linking Child Welfare and Children’s Mental Health Systems: A Case Study of the Gateway CALL Demonstration

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Published: 30 November 2022
Volume 50 , pages 327–341, ( 2023 )

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Alicia C. Bunger ORCID: orcid.org/0000-0002-6407-5111 1 ,
Susan Yoon 1 ,
Kathryn Maguire-Jack 2 ,
Rebecca Phillips 1 ,
Kristopher Y. West 3 ,
Gretchen Clark-Hammond 4 &
Christiana Kranich 5

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The mental health needs of children and youth involved in the child welfare system remain largely unmet. Service cascades are an emerging approach to systematizing mental health screening, assessment, and treatment referral processes. However, evidence is minimal and inconsistent regarding the effectiveness of such approaches for improving mental health service access and outcomes. In an effort to address this gap, this study presents a case-study of the implementation fidelity and treatment outcomes of the Gateway CALL service cascade. Study analyses involved longitudinal data collected as part of a larger evaluation of Gateway CALL. Specifically, descriptive and linear mixed model analyses were conducted to assess the implementation of service cascade components, and changes in mental health outcomes (behavior problems) among 175 children placed out-of-home during the study. Study analyses found that although fidelity was strong early in the service cascade, implementation began to break down once components involved more than one service system (child welfare, mental health). However, results also indicated that parent-reported child behavior problems decreased significantly over time, despite later cascade components being implemented with poor fidelity to the Gateway CALL service model. For children and youth involved in child welfare systems, service cascades like Gateway CALL have the potential to significantly improve both mental health service receipt and outcomes. To maximize the effectiveness of such approaches, later phases of implementation may require increased attention and support, particularly regarding processes and outcomes that cross child welfare and mental health service systems.

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Children and youth involved in the child welfare system have extensive mental health service needs that often remain unmet (Horwitz et al., 2012 ; Stein et al., 2016 ). Service cascades involve systematic screening and assessment in one system and referral to treatment in another (e.g., Belenko et al., 2017 ). When implemented in youth-serving systems, these interventions have potential to improve children’s access to mental health care, and ultimately, their well-being. However, implementing service cascades requires the introduction and alignment of multiple components across multiple organizations. The challenges of implementing service cascades with fidelity have been well-described (Akin et al., 2017 ; Van Deinse et al., 2019 ) and may explain, in part, mixed evidence of their effectiveness for improving treatment access and outcomes for children in child welfare (Bunger et al., 2021 ; Pullmann et al., 2018 ). This study examines the implementation fidelity of Gateway CALL (Consultation, Assessment, Linkage, and Liaison), a service cascade designed to improve access to mental health treatment for children in out-of-home placements and the effect of service receipt on children’s mental health.

Linking Child Welfare and Mental Health Systems to Address Unmet Service Needs

Experiencing abuse, neglect, and other traumas as a child can lead to emotional and behavioral problems (Garcia et al., 2017 ; Kisiel et al., 2017 ; Yoon et al., 2017 ; Zhang & Mersky, 2020 ). As a result, mental health problems are prevalent among children and youth involved in the child welfare system. Approximately 49% of all system-involved children have mental health service needs for various mental disorders including Attention-Deficit/Hyperactivity Disorder, conduct disorder, oppositional defiant disorder, anxiety, depressive disorders, and post-traumatic stress disorder (Bronsard et al., 2016 ). These rates are particularly high among children who enter out-of-home placements, such as foster care (Engler et al., 2022 ; Turney & Wildeman, 2016 ). For example, one study examined mental health problems among adolescents in the child welfare system and found that youth with prior out-of-home placement were 2.29 times more likely to report a mental health problem compared to those with no history of out-of-home placement (Heneghan et al., 2013 ). Despite high rates of mental health service needs, only about half of child welfare system-involved children receive mental health services (Horwitz et al., 2012 ; Stein et al., 2016 ), and even fewer receive care consistent with national standards for screening, assessment, and referral to treatment (Raghavan et al., 2010 ).

Contact with child welfare workers can serve as a gateway to mental health treatment (Leslie et al., 2005 ), and as a result, children and youth who enter foster care or other out-of-home placements are often more likely to receive mental health treatment than children who remain at home (Horwitz et al., 2012 ; Hurlburt et al., 2004 ; Kim et al., 2021 ; Raghavan et al., 2010 ). Although many foster care placement organizations (private organizations that recruit foster parents and place children in foster homes) deliver mental health services as part of a diverse set of case management and other support services (Chuang et al., 2014 ), children in out-of-home care have substantial unmet mental health service needs (Turney & Wildeman, 2016 ).

Unmet mental health service needs among children in out-of-home placements reflect serious missed opportunities to coordinate care and improve children’s well-being while they are in system custody. Formal collaborative partnerships between child welfare agencies and mental health providers can help foster linkages to services although front-line child welfare workers might need additional support to actualize these agency-level partnerships given the collaboration barriers they experience (Bai et al., 2009 ; Bunger et al., 2016 ; Fong et al., 2018 ; Hurlburt et al., 2004 ). For instance, child welfare workers might be untrained and unfamiliar with mental health issues (Dorsey et al., 2012 ), and find it difficult to prioritize children’s mental health service needs amid pressure to respond to safety concerns (Hoffman et al., 2016 ; Perez Jolles et al., 2019 ; Smith & Donovan, 2003 ). Even when child welfare workers identify children’s treatment needs, children can fail to receive care if workers are unfamiliar with treatment options (Bunger et al., 2009 ; Stiffman et al., 2000 , 2004 ) or when there is limited availability of high quality, evidence-based treatment among providers who accept Medicaid (which covers services for children in out-of-home care) (Bruns et al., 2016 ; Scheeringa et al., 2020 ; Steinman et al., 2012 ). Attending to these barriers across both child welfare and mental health settings could potentially improve children’s mental health service access and their well-being.

The Promise and Challenge of Implementing Service Cascade Models—The Gateway CALL Demonstration

Service cascades, similar to clinical pathways, are a type of cross-system intervention that link or integrate treatment services delivered in different systems to create a continuum of care from diagnosis to treatment (Belenko et al., 2017 ; Mugavero et al., 2013 ). When implemented at the intersection of child welfare and mental health, these interventions have potential to address the real-world barriers to identifying and connecting children to mental health treatment. Service cascades in this setting might include several sequenced components beginning with a screening and assessment in the child welfare system that lead to a referral and treatment in the mental health system (e.g. Barth et al., 2020 ).

Gateway CALL was a service cascade intervention designed and implemented within an urban county-based child welfare agency in a midwestern U.S. state that employs over 700 staff and serves 30,000 families annually. The agency designed Gateway CALL and implemented the intervention with children who entered child welfare custody and out-of-home placements to facilitate their access to mental health services and improve their mental health outcomes. The model included four components (screening, assessment, referral/linkage, and re-assessment) that address common challenges to identifying and connecting children to mental health services in typical child welfare practice. Gateway CALL was designed around an existing mental health assessment team (CALL clinicians) staffed by trained mental health clinicians from a local mental health provider. Having co-located mental health clinicians within the child welfare agency was a distinguishing feature of the intervention because it was intended to foster deeper integration of mental health expertise into service cascade components implemented within the child welfare agency and centralize coordination of mental health services for children.

The first component involved brief mental health and trauma screening conducted by intake workers in the child welfare agency to systematize identification of mental health service needs (instead of relying on worker discretion). In Gateway CALL, intake workers administered the Childhood Trust Events Survey (CTES; Pearl, 2000 ) to identify trauma exposure, and either the Devereaux Early Childhood Assessment (DECA; for children younger than six; LeBuffe & Naglieri, 1999 ) or the Strengths and Difficulties Questionnaire (SDQ, for children six or older; Goodman, 1997 ) to identify mental health disorder symptoms. Screenings were administered electronically on tablets with parents (and children who were 13 and older) during home visits at the time the case opened, and children were brought into child welfare custody. Children who scored above the threshold on either tool were electronically linked to a co-located CALL assessment team.

The second component included case consultation and a comprehensive diagnostic assessment conducted by the co-located CALL team. CALL team clinicians consulted with the child welfare intake workers to learn about the family context for each child and share screening results. CALL clinicians then completed a diagnostic interview with the child and caregiver(s), obtained external records of past treatment history and had parents complete the Child Behavior Checklist (CBCL) for each child who was screened into Gateway CALL, and also administered the Youth Self Report (YSR) to youth aged 13 or older (Achenbach, 1991a , 1991b ). Having a specialized mental health assessment team co-located within the child welfare agency was intended to expedite completion of a thorough diagnostic assessment (and intensive information gathering from parents) without children having to enter the mental health system, and foster information sharing and service coordination across systems.

Referral and Linkage

Third, CALL clinicians and ongoing child welfare workers (who assumed responsibility for coordinating child welfare service plans once cases were opened and transferred from intake) reviewed the results of the diagnostic assessment and made referrals/linkages to certified community-based mental health treatment providers who delivered high quality, specialty mental health services. As licensed and experienced mental health professionals, CALL clinicians had deep familiarity with local mental health providers, available evidence-based treatment modalities, and service quality to help drive referrals to appropriate treatment as indicated by assessment results. CALL clinicians also provided support to children’s caregivers to navigate the mental health system and link children to services. This is distinct from traditional child welfare practice where ongoing case workers refer children to services without the full information of a diagnostic assessment, robust understanding of treatment availability, consultation with a mental health clinician, or additional linkage supports.

Re-assessment and Case Monitoring

The fourth Gateway CALL component involved reassessments every 90 days while children remained in out-of-home care by the CALL team using the same CBCL and YSR assessments to monitor children’s progress in treatment. CALL clinicians shared results from the re-assessments with ongoing child welfare workers and provided consultation on treatment progress and child welfare case planning. (For additional intervention and implementation detail see Bunger et al., 2017 , 2021 ).

Despite a deliberate intervention design that emphasized strong collaboration, responded to well-known barriers, and was designed to fit the local organizational context, earlier analyses suggested that Gateway CALL left many children with unmet mental health service needs. Although nearly all the children in the demonstration had some type of mental health diagnosis, fewer than half (47%) received treatment. Based on a quasi-experimental evaluation design (using a matched comparison group) Gateway CALL appeared to have no impact on children’s likelihood of receiving mental health services, although it might have increased the number of children’s mental health service visits (Bunger et al., 2021 ). In evaluations of similar types of demonstrations (that did not include the same type of intensive co-location), these types of cascades have demonstrated promise for quickly identifying children with extensive needs and recommending them for treatment (Akin et al., 2021 ; Verbist et al., 2020 ). Although a substantial number of children with service needs remained unserved in other demonstrations (Pullmann et al., 2018 ), those who received treatment in the community experienced symptom improvement (Bartlett et al., 2016 , 2018 ). Taken together, while Gateway CALL and other similar types of models were designed to address barriers to identifying and linking children to mental health services, the effectiveness of these interventions remains unclear, though promising.

Implementation Challenges Can Limit Fidelity and Cascade Effectiveness

Fidelity refers to the degree to which an intervention is delivered as intended (Carroll et al., 2007 ; Proctor et al., 2011 ). Poor implementation fidelity can limit the effectiveness of promising interventions when they are translated into real-world settings (Dusenbury et al., 2003 ). Fidelity reflects implementation quality or adherence to the content or core components of an intervention (Carroll et al., 2007 ). However, fidelity can be difficult to achieve especially for complex interventions like service cascades because they involve multiple components (e.g. screening, assessment, referral), implemented in multiple organizational or system environments (e.g. child welfare and mental health) (Dusenbury et al., 2003 ; Seys et al., 2019 ). Emerging literature highlights some of the challenges implementing and aligning service cascades (Belenko et al., 2017 ; Juckett et al., 2020 ; Van Deinse et al., 2019 ).

Because these cascades involve sequencing practice components across multiple organizations, difficulty implementing with fidelity at any stage or organization can compromise the effectiveness of the service cascade for improving clients’ service access and outcomes. The effectiveness of Gateway CALL and other similar cascades might have been limited because of poor implementation fidelity. Difficulty implementing the screening, assessment, referral, or case plan monitoring components could reduce children’s likelihood of receiving mental health services, or enough mental health service visits to lead to meaningful improvements in their outcomes (such as a reduction in behavior problems or mental health symptoms).

Understanding where model fidelity breaks down (in the cascade sequence or setting) can inform how system leaders select and target strategies for implementing these complex models. However, the implementation of these models and implications for service access and outcomes has received limited empirical attention. This manuscript draws on the Gateway CALL project as a case study to (1) assess fidelity to each component of the Gateway CALL cascade, (2) examine change in children’s mental health outcomes (specifically, their behavior problems) over time, and (3) evaluate the role of mental health service receipt on children’s mental health outcomes.

Study Design

Gateway CALL was rolled out in two waves across eight child welfare intake units responsible for investigating screened-in reports of child maltreatment (selected by agency leadership) beginning in February 2015 through July 2016. The larger study used a quasi-experimental design to examine whether Gateway CALL improved mental health service receipt, safety, and permanence outcomes for children in out-of-home care (Bunger et al., 2021 ). To address the aims of this manuscript, we draw on the longitudinal data from the experimental group only, which followed children in the study through January 31, 2017. Procedures were reviewed and approved by the IRB at the lead author’s institution.

Participants

Participants included 175 children (from birth to age 18) who entered child welfare custody through one of the 8 experimental intake units between February 1, 2015 and July 30, 2016 and were placed in out-of-home care (e.g. foster care). Children were excluded if they were entering custody due to an event on an open case, were assigned to a managed care provider, or were in custody for fewer than two days (i.e., temporary emergency custody).

Data Sources and Variables

We linked three administrative data sources. First, we drew on child welfare case records from the Statewide Automated Child Welfare Information System (SACWIS) to track all eligible children’s pathways through the child welfare system and basic case information. Second, we linked these records to children’s screening, assessment and re-assessment reports generated as part of this project and maintained separately at the child welfare agency in paper or electronic format. These records contained screening and assessment dates, responses to individual screening and assessment items, and aggregated scores. Finally, we linked children’s child welfare case records, screening results, and assessment reports with Medicaid billing records that reflected mental health services delivered to each child. These linked records were used to assess fidelity and children’s outcomes.

Fidelity was measured using four indicators that correspond with the four key stages of the intervention. Screening fidelity was operationalized as the percentage of Gateway CALL eligible children who received a mental health screening based on screening records linked with SACWIS data. Assessment fidelity was operationalized as the percentage of Gateway CALL eligible children who scored above the screening threshold and received an initial mental health assessment based on assessment reports. Service fidelity was operationalized as the percentage of Gateway CALL eligible children who scored above the screening threshold, had an initial assessment, and received specialty mental health treatment during the study observation period (between the time of mental health screening and January 31, 2017) as reflected in Medicaid billing records. To most closely capture treatment delivered by the children’s mental health system, specialty mental health treatment was defined as any service visit billed by a provider who was certified by the state Medicaid program as a mental health professional (e.g., psychiatrist, psychologist, or social worker). Reassessment fidelity was operationalized as the percentage of children who scored above the screening threshold, had an initial assessment, and at least one follow-up re-assessment approximately 90 days afterwards as reflected in the assessment and re-assessment reports. Higher percentages of children who received each phase of the intervention reflect stronger fidelity (with a goal of reaching 100%).

Mental Health Outcomes (Behavior Problems)

We examined children’s mental health outcomes based on both caregiver and youth reports of their behavior problems. Caregiver reports were assessed for children who received the Gateway CALL intervention (experimental group only) using the developmentally appropriate form of the CBCL (Achenbach, 1991a ). The CBCL is a standardized caregiver-report measure that includes 113 items about children’s emotional and behavior problems. Caregivers rated their child on a 3-pont response scale (0 = not true, 1 = somewhat or sometimes true, 2 = very true or often true). Internalizing behavior problems (i.e., social withdrawal, somatic complaints, and anxiety/depression) were measured using the internalizing subscale and externalizing behavior problems (i.e., delinquency and aggressive behavior) were measured using the externalizing subscale. The total behavior problems were calculated by summing the internalizing and externalizing scores. The gender- and age-standardized T scores were used, with higher scores indicating greater symptoms. The CBCL was administered to caregivers by CALL assessment team members within 10 days of their child entering custody. The CBCL was re-administered with the primary caregiver within the child’s current placement every 90 days thereafter for the duration of the custody episode or until the end of the study observation period.

Youth ages 11–18 who received the Gateway CALL intervention also completed the YSR, a standardized, child self-report measure that is identical to the CBCL in content and structure (e.g., response categories) (Achenbach, 1991b ). The YSR consists of 112 items that assess emotional and behavioral problems in the past 6 months. The same procedures described in the above (CBCL) were used to create internalizing, externalizing, and total behavior problem scores, at the same time intervals (upon entering custody and every 90 days afterwards). For both CBCL and YSR, T scores less than 60 are considered in the normal range, 60–63 represent borderline scores, and scores greater than 63 are in the clinical range.

Demographics

We extracted several child and family demographic features from SACWIS including age (in years as of January 31, 2017), sex (male or female). Children’s race and ethnicity was assessed categorically and reflecting major regional demographic groups (Black, white, or other). We also extracted information to understand other factors that might also drive children’s mental health service needs including the number of prior traditional (non-alternative response) screened-in reports of child abuse or neglect ( prior CAN ). From the most recent safety and risk assessment, we also extracted information about whether a child had special medical and behavioral needs, or a history of delinquency; or whether caregivers had substance misuse or domestic violence concerns (all dichotomous indicators where 1 = yes).

To understand fidelity to the Gateway CALL model for Aim 1, we used frequency analysis to examine the percentage of children (out of the 175 children in the intervention) who received each model component. To understand change in mental health outcomes (behavior problems) over time for Aim 2, we examined descriptively the percentage of children who scored above the clinical threshold (T score > 63) at initial and last assessment for each scale and based on both parent and youth report. We also used paired-samples t-tests to compare baseline behavior problems scores (the CBCL and YSR internalizing, externalizing, and total T scores) to scores on the final assessment. For Aim 3, we used linear mixed models to examine the relationship between mental health service receipt and change in symptom scores (internalizing, externalizing, and total) as reported by both parents and youth. Data were managed and analyzed using Stata (StataCorp, 2017 ) and SPSS v. 27 (IBM Corp, 2020 ).

Sample Characteristics

Table 1 includes the demographic information of the sample. Children who participated in Gateway CALL were an average of 13.1 years old (SD = 5.4) and a slight majority were female (53.4%), 44% were Black, 35.6% were white, and 20.4% were some other race/ethnicity, including Asian, Hispanic, or multi-racial. On average, children had experienced an average of 2.9 prior child abuse or neglect reports (SD = 2.9), and 35.4% had a special need or history of delinquency indicated in their records. Over a third of children (37.1%) had lived in a home with caregiver domestic violence and 15.4% had caregiver substance use disorders indicated in their records.

Aim 1: Fidelity to Gateway CALL

Fidelity to the screening, assessment, service receipt, and reassessment/case monitoring phases of the Gateway CALL intervention are illustrated in Figs. 1 and 2 ; Table 2 .

Children’s pathways through gateway CALL (n = 175 children)

Fidelity to gateway CALL by component (n = 175 children)

Screening Fidelity

Of the 175 children entering the Gateway CALL units during the observation period, 165 (94.3%) were screened, and only 10 children (5.7%) were missed suggesting strong screening fidelity. A total of 117 children (66.9% of the 175 children in Gateway CALL, and 70.9% of the 165 screened) scored above the threshold on either the trauma exposure or mental health symptoms screening tools indicating a need for additional mental health assessment and services. At this stage, 48 children of the 175 children entering Gateway CALL (27.4%) scored below the threshold on both screening tools.

Assessment Fidelity

Children who screened positive on either screening tool were intended to be linked to the co-located CALL assessment team. Of the 175 children entering Gateway CALL, 110 (62.9%) received an initial mental health assessment, with either a completed parent or youth self-report. This number represents 94.0% of the children who scored above the screening thresholds indicating strong assessment fidelity. Only seven children (4.0%) were not assessed at this phase, in addition to the 10 children (5.7%) missed during the screening phase.

Service Fidelity

According to the model, we anticipated that most children who were assessed would be referred to specialty mental health treatment services, and because children in out-of-home placements are Medicaid-eligible, these treatment services should be captured in Medicaid billing records. However, only 49 children who received an assessment had any record of receiving a mental health visit in the Medicaid billing records suggesting poor service fidelity. These children who received mental health care after screening positive and receiving an assessment reflect only 28% of the 175 children in Gateway CALL. Records also suggest that some of the children who were missed in earlier screening and assessment phases (n = 9) or who screened negative (n = 10) also went on to receive mental health services, resulting in a total of 68 children (or 38.9% of the 175 children in Gateway CALL) who received services. A greater percentage of children who screened positive, and received an assessment (n = 61, 55.5% of those assessed and 34.9% of those in Gateway CALL) had no record of receiving mental health services in Medicaid billing records, reflecting unmet service needs.

Re-assessment Fidelity

In the final stage of Gateway CALL, all children who received an initial mental health assessment were to be reassessed every 90 days until the end of the demonstration or their stay in child welfare custody. A total of 81 children were reassessed (at least one record of a parent or youth self-report measure of behavior problems). These children account for only 46.3% of all 175 children in Gateway CALL, but 77% of the 110 children who received an initial mental health assessment suggesting that fidelity to the reassessment component was fairly strong. Most of those who were not reassessed (83%) left child welfare custody before the first 90-day reassessment would have been completed. The number of follow-up reassessments ranged from two to seven (Table 3 ). Of the children reassessed, 38 received mental health treatment as reflected in billing records; these children accounted for only 21.7% of all children in Gateway CALL. A slight majority of the 81 children who were reassessed (n = 43, 53%) did not receive treatment (according to billing records).

Aim 2: Change in Mental Health Outcomes (Behavior Problems)

Of the 81 children with at least one re-assessment, all 81 had at least-one parent reported re-assessment score, and 68 had at least one youth self-reported re-assessment score (Table 3 ). Behavior problems and their severity declined over time according to both parents and youth (Table 4 ; Fig. 3 ). Based on parent reports, the average total CBCL T-scores declined significantly from a baseline average of 66.89 (SD = 12.00) to a final average of 58.84 (SD = 10.97) [ t (80) = 5.708, p < .001] which falls below the threshold for clinically significant behavior problems (T-score > 63). Similarly significant declines in parent reported internalizing [ t (80) = 3.735, p < .001] and externalizing behavior problems [ t (80) = 6.839, p < .001] were also observed. The percentage of children scoring above the clinically significant threshold for total parent-reported behavior problems declined from 75.3% at baseline to 39.5% at final reassessment, and similar decreases were observed for internalizing and externalizing behavior problems.

Change in percent of children scoring above the clinical threshold over time

Changes in youth self-report of behavior problems were similar to those in the parent reports. Average total youth self-report T-scores declined significant from a baseline average of 57.99 (SD = 13.19), which is below the clinical cutoff, to a final average of 52.72 (SD = 11.97) [ t (67) = 3.935, p < .001]. T-scores on youth self-reported internalizing [ t (67) = 3.668, p < .001] and externalizing behavior problems [ t (67) = 3.806, p < .001] also declined significantly. The percentage of children who scored above the clinically significant threshold on youth self-reported total behavior problems declined from 36.8% at baseline to 22.1% at the final reassessment.

Aim 3: Mental Health Service Receipt and Mental Health Outcomes (Behavior Problems)

Table 5 summarizes the results from linear mixed models examining factors related to changes in parent reported behavior problems. Results suggest that the more mental health service visits a child received (in Medicaid billing records), the greater the decrease in parent reported internalizing ( b = − .02, SE = .01, p = .019) and total behavior problems ( b = − .02, SE = .01, p = .041). Children’s age was positively associated with parent reported internalizing behavior problems ( b = .49, SE = .23, p = .038) suggesting that internalizing behaviors increased over time for older children. Child race, sex, maltreatment history, and whether or not children received any mental health services (as reflected in billing records) were not statistically significantly associated with changes in parent reported externalizing behavior problems.

Table 6 presents the results from linear mixed models examining factors related to changes in youth self-reported behavior problems. Child age was negatively associated with changes in youth self-reported externalizing ( b = − 1.75, SE = .64, p = .007) and total behavior problems ( b = − 1.56, SE = .73, p = .035), suggesting that younger children reported greater decreases in their externalizing and overall behavior problems over time. Child race, sex, maltreatment history, and mental health service receipt (as reflected in Medicaid billing records) was not significantly associated with changes in youth self-reported behavior problems.

Service cascades that link clients in one system (e.g. child welfare) to services in another (e.g. mental health) have potential to improve service access and client well-being although implementation challenges might compromise their effectiveness. In this study, we examined the implementation and child mental health outcomes of Gateway CALL, a system demonstration designed to link children in out-of-home placements to mental health care by implementing a sequence of mental health screening, assessment, referral, and case monitoring practice components within a child welfare agency. In earlier phases of the cascade (e.g. screening and assessment) where a mental health partner was well-integrated within the child welfare agency and practice, fidelity was strong. However, we found that implementation fidelity was poor for the later components (service receipt and reassessment) leaving many children with unmet mental health service needs. Despite these implementation breakdowns, children’s behavior problems improved over time; as children received more mental health service visits their parent-reported behavioral problems appeared to improve significantly. These results suggest that with special attention to implementation fidelity (especially at the point at which children are linked to the mental health system in the community) service cascade models have even greater potential for impact.

Gateway CALL Fidelity

Implementation fidelity varied across Gateway CALL phases. Fidelity was strong across the initial screening and assessment cascade components implemented within the child welfare agency. It was clear that the child welfare intake workers and co-located CALL team clinicians successfully carried out the screenings and assessments together since there were few children missed during these phases. These results might reflect strong coordination between child welfare intake workers and CALL team clinicians, perhaps because of the co-location arrangement. However, fidelity dropped at the point at which children should have been referred to and received treatment in the mental health system. Only 28% of the children in Gateway CALL received at least one mental health service visit (with a certified mental health professional), even though over 63% had demonstrated need and received a full assessment. It is possible that children received supportive services (e.g., support groups, individual sessions) from outside of the mental health system. Besides the mental health system, children might often receive services in schools (Duong, et al., 2021 ). However, Gateway CALL occurred at a time when evidence-based mental health was limited in schools. It also may be that children received supportive services at other community-based organizations from professionals who were not certified mental health professionals (which would not be reflected in the Medicaid claims).

Although most children remained in child welfare custody for at least 90 days and were re-assessed by the CALL team at least once afterwards (where case workers and CALL team members may have followed up on missed service linkages), children still failed to receive specialty services. This suggests that later phases of the service cascade were not fully implemented and offers explanation for why children in Gateway CALL were no more likely to receive mental health services than children in a matched comparison group (Bunger et al., 2021 ).

Fidelity to the Gateway CALL model broke down at the point when children should have been referred and transitioned into community-based mental health services. Based on available data, it is difficult to pinpoint the problem—it is unclear whether children failed to receive specialized mental health services due to child welfare workers’ unfamiliarity or difficulty making referrals to certified providers (e.g. Bunger et al., 2009 ), limited mental health treatment availability and long waitlists for care (e.g. Barnett et al., 2018 ; Scheeringa et al., 2020 ; Steinman et al., 2012 ), or the challenges foster parents experience in bringing children to appointments (because the child refused, the provider was too far, scheduling, concerns about appropriateness, etc.) (Cao et al., 2019 ; Pasztor et al., 2006 ).

There were several collaboration breakdowns between the child welfare agency and its external partners that might explain why implementation suffered. First, there was a disruption in the contract for the co-located CALL assessment team leading to a change in provider halfway through the observation period. Contracting challenges in child welfare are common (e.g. Willging et al., 2015 ) and in our study, this provider change disrupted referral relationships which might have compromised implementation of the referral, treatment access, and re-assessment components. Second, limited collaboration with private foster care placement providers could have contributed to the drop off in mental health service receipt. In this agency, contracted placement providers (private non- and for-profit organizations) were responsible for placing children in foster care and arranging services in accordance with the case plan. Many of these providers preferred to conduct their own assessments and deliver in-house support services (perhaps for liability or billing reasons). As a result, these providers may not have accepted or supported the CALL team’s recommendations for specialized mental health services at other providers. Notably, while children might have received services delivered by contracted placement providers, unless they were delivered by a certified mental health professional and billed to Medicaid, they would not be considered specialty mental health services.

There were also issues within the child welfare agency that could have contributed to poor fidelity. High turnover rates among front-line staff, supervisors, and administrators could have undermined consistent follow-up with children and collaboration with mental health providers. Turnover can also contribute to institutional knowledge loss, decreased stakeholder buy-in, collaboration deterioration, and delays for necessary reorientation and partnership rebuilding (Gopalan et al., 2020 ; Whitaker et al., 2020 ) which affects implementation (Aarons et al., 2011 ; Rollins et al., 2010 ) particularly for service cascades (and other cross-system) interventions (Gopalan et al., 2021 ). Additionally, the intervention’s timing could have been problematic since screening occurred around the time children were removed from their home. This is a volatile time in a case, making it challenging to connect children to services; initiating the service cascade sooner (in the lifecycle of a family’s involvement in child welfare) might have led to better fidelity.

Given how service cascades are a series of interdependent steps, difficulty implementing even one component of the model can lead to overall implementation failures as we observed. These breakdowns might have been linked to difficulty collaborating effectively with external partners. The collaboration and implementation issues we experienced were not unique. Other demonstration sites also encountered significant challenges related to establishing strong collaboration across child welfare and children’s mental health systems (Akin et al., 2019 ; Barnett et al., 2016 , 2018 ; Lang et al., 2017 ; Tullberg et al., 2017 ). It can take years to build capacity for working across systems (Connell et al., 2019 ), if at all (Jankowski et al., 2019 ) and these gains in collaboration can be difficult to maintain over time (Winters et al., 2020 ). Together the insights from Gateway CALL and other similar demonstrations suggest that effective collaboration strategies (e.g., co-locating staff, contracts with providers for expedited service access, clearly operationalized referral procedures) are likely essential for implementation success. Additional research on collaboration strategies could clarify how child welfare (and other human service systems) partner effectively with behavioral health organizations to implement cross-system models (Bunger et al., 2020 ; Hurlburt et al., 2004 ). This may be especially useful to child welfare systems partnering with behavioral health and other human service providers to scale up evidence-based parenting, mental health, and substance use treatment programs in communities as part of the Families First Prevention Services Act.

Improvements in Mental Health Outcomes (Behavior Problems)

Despite poor implementation fidelity to the service receipt phase of Gateway CALL, children’s behavior problems and their severity declined over time. Notably, average final behavior problems scores fell below the threshold for clinically significant behavior problem. This suggests that children’s mental health improved. While the severity of children’s behavior problems might improve naturally over time once their living situations have stabilized (Rubin et al., 2007 ), the results of our linear mixed models suggest that children’s behavior problems improved more with greater numbers of mental health service visits. Our study design does not allow us to make inferences about whether service visits caused these improvements, although our earlier study findings suggest that the Gateway CALL intervention was effective for increasing the number of mental health service visits (Bunger et al., 2021 ). Attending more mental health service visits denotes stronger treatment retention, which is likely necessary for delivering a full dose of evidence-based interventions, and has been linked to better functioning outcomes for children (Foster, 2000 ). Thus, our results suggest that interventions like Gateway CALL have potential for improving children’s mental health by increasing the number of service visits they receive—if implemented with fidelity (where more children accessed mental health services), these models have real potential for broad impact for children in the child welfare system.

Limitations and Future Directions

There are several methodological limitations that warrant consideration when interpreting our results. First, it is important to note that the measure of fidelity used during the study reflected model adherence only; our measure did not capture other dimensions of fidelity to the Gateway CALL model (e.g., dosage, quality) (Carroll et al., 2007 ) or whether services children received in the community were evidence-based which might also explain mental health outcomes (Ahn et al., 2016 ). Second, we were unable to gather data on mental health outcomes within the larger study’s comparison group, which limited our ability to infer causal relationships between service receipt and outcomes. During initial intervention and evaluation design, there were concerns about the ethics of administering diagnostic assessments or other measures about mental health symptoms to children in this population without also intervening. Additional controlled studies are needed to determine whether improvements in reported symptom severity are a result of treatment or other factors. Third, generalizability of this study’s findings are limited to similar types of urban county-based agencies situated within robust mental health service systems. Future studies are needed to understand whether this model yields similar outcomes when implemented in rural settings with more limited service availability (Cummings et al., 2016 ).

Fourth, the re-assessments might not have generated reliable and valid depictures of change in children’s behavior problems over time. Although the CBCL is a gold standard measure, it is completed by parents; in Gateway CALL, parents (or primary caregiver) completed the initial assessment, but because children were placed in out of home care, foster parents completed the re-assessments. For older children, we addressed this limitation by asking them to complete the YSR. While re-assessments completed by foster parents still generated useful clinical information for practice, our results about change in behavior problems among young children especially might be limited by this issue.

Finally, evidence from this study could be limited due to the use of administrative data; in particular, our data sources did not include an accurate and reliable indicator of mental health service referrals. As a result, we could not determine if Gateway CALL model fidelity broke down because the caseworker (or CALL clinician) did not refer children for services, or because of other problems that foster parents or others encountered while trying to follow through on the referral. Robust integrated data systems that reflect critical practice components are essential for testing and evaluating cross-system interventions like Gateway CALL.

Service cascade models like Gateway CALL have potential to address unmet mental health service needs for children and youth in out-of-home placements. However, implementation issues can compromise their benefits. Our study demonstrates how children’s behavior problems improved with greater receipt of mental health services, but model fidelity can break down at the point where children transition across system boundaries compromising their service linkages. Our results suggest that strong and effective cross-system collaborations are essential for implementing and expanding the benefits of service cascades and other cross-system interventions.

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Acknowledgments

This work was supported by the Department of Health and Human Services, Administration for Children, Youth, and Families, Children’s Bureau (Grant #90CO1104). This study was also funded in part by the Ohio Department of Medicaid, through the MEDTAPP program administered by the Ohio Colleges of Medicine Government Resource Center. Views stated in this manuscript are those of the researchers only and are not attributed to the study sponsors, the Ohio Department of Medicaid or to the Federal Medicaid Program. MEDTAPP HCA initiative funding supports teaching and training to improve the delivery of Medicaid services. MEDTAPP funding does not support the delivery of Medicaid eligible services.

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Bunger, A.C., Yoon, S., Maguire-Jack, K. et al. Implementation and Mental Health Outcomes of a Service Cascade Linking Child Welfare and Children’s Mental Health Systems: A Case Study of the Gateway CALL Demonstration. Adm Policy Ment Health 50 , 327–341 (2023). https://doi.org/10.1007/s10488-022-01238-7

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DOI : https://doi.org/10.1007/s10488-022-01238-7

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Implementation and Mental Health Outcomes of a Service Cascade Linking Child Welfare and Children's Mental Health Systems: A Case Study of the Gateway CALL Demonstration

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1 College of Social Work, The Ohio State University, Columbus, OH, 43210, USA. [email protected].
2 College of Social Work, The Ohio State University, Columbus, OH, 43210, USA.
3 School of Social Work, University of Michigan, Ann Arbor, MI, 48109, USA.
4 Nationwide Children's Hospital, Columbus, OH, 43205, USA.
5 Mighty Crow Media, LLC, Worthington, OH, 43214, USA.
6 Government Resource Center, Ohio Colleges of Medicine, Columbus, OH, 43210, USA.
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DOI: 10.1007/s10488-022-01238-7

Keywords: Access; Child welfare; Children’s mental health services; Implementation; Service cascade.

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v.14(3); 2022 Mar

Suicidality Among Men in Russia: A Review of Recent Epidemiological Data

Val bellman.

1 Psychiatry, University of Missouri, Kansas City School of Medicine, Kansas City, USA

Vaishalee Namdev

2 Medicine and Surgery, Mahatma Gandhi Medical College and Research Institute, Indore, IND

Suicide is a phenomenon that is not related to a specific class of countries but is a problem worldwide. Many studies have attempted to explain gender differences in suicidal behaviors. Unfortunately, Russia holds the world’s top place for the number of suicides committed by its male citizens. Russia is still demonstrating unusually high death rates due to non-natural causes, and these demographic trends are concerning. We analyzed suicidality among men in Russia over the past 20 years using official data published by the Federal State Statistics Service (Rosstat) and secondary sources. We also discussed male suicide as a social problem, analyzed, and evaluated male suicidality in Russia from 2000 to 2020, and reviewed the factors influencing the prevalence of male suicides over female suicides in Russia.

Russia is still going through one of the most significant historical changes in the last 100 years. Our analysis showed discrepancies between official numbers and data published by non-government organizations in Russia. Unemployment, low socioeconomic status, underdiagnosed and/or untreated mental illness, and substance abuse are major risk factors for suicide in Russian men. Cultural influences also make suicidal behavior socially scripted in Russia.

By providing examples and analyzing data, we aspire to encourage improvements in the practice of mental wellbeing in Russia and other post-Soviet countries. The recommendations within this report are intended as a starting point for dialogue to guide effective suicide prevention in this country.

Introduction

Suicides and self-harming behaviors are significant public health and social problems in post-Soviet Russia. Suicide is one of the leading causes of death worldwide [ 1 ], accounting for over 58,000 deaths annually in Europe [ 2 ] and 16,546 deaths in Russia in 2020 [ 3 ]. According to experts, there are 11.4 suicides per 100,000 people in the world, which equates to 804,000 suicides annually [ 4 ]. Although the suicide rates in Russia are gradually decreasing (39.1/100,000 in 2000 to 23.4/100,000 in 2010 and 11.3/100,000 in 2020 [ 3 ]), the number of suicides among men is significantly higher than among Russian females [ 5 , 6 ].

The suicide rates vary greatly between Russian cities and within the country, and the difference between regions varies tenfold. The suicide rates are higher in rural communities when compared with their urban counterparts. Social deprivation, economic depression, unemployment, heavy alcohol consumption, etc. are also more prevalent in rural areas of Russia. Indigenous peoples around the country are burdened with a markedly increased suicide rate, which may be associated with a challenging social situation, inadequate family support, lower socioeconomic status, and an increased prevalence of alcohol and psychoactive substances, which also act as suicide risk factors in general [ 7 , 8 ]. The suicide rates among men in Russia (26.1 per 100,000) were over three times higher than among women (6.9 per 100,000) in 2016. Committing suicide appears to be a male phenomenon over the past 20 years in post-Soviet Russia [ 9 ]. For suicide attempts, the level estimated by the World Health Organization (WHO) is 20 times higher than the suicide rate [ 10 ]; the gender gap is less pronounced.

This phenomenon, when men commit suicide more frequently than women while women are much likelier to commit suicide attempts, is known as the gender paradox of suicidal behavior [ 2 , 6 ]. All Russian citizens are expected to receive medical care that meets the highest standards, regardless of their race, religion, national origin, sexual orientation, gender identity, or expression. Although the Russian healthcare system remains gender-neutral, Russian men are not considered a “risk” group and are not involved in targeted state-sponsored suicide prevention programs [ 11 ].

Materials and methods

Data on the population and male suicide rates were taken from the official reports of Rosstat and the Ministry of Health of the Russian Federation for 2001-2020. Secondary data were obtained from international databases and published studies in Russian and English. We used descriptive statistics to summarize the information about the population being studied. This methodology helped us summarize data in the form of simple quantitative measures, such as percentages and means, or visual summaries, such as diagrams and bar charts. The literature review attempted to bring together all available evidence on a specific, clearly defined topic.

Published studies were identified through ‘pearl growing’, citation chasing, a search of databases, using the filters, and the authors’ topic knowledge. The articles were searched in MEDLINE, PubMed, EMBASE, COCHRANE, eLibrary, and CyberLeninka. A search of databases was undertaken in December 2021 using predefined keywords. Citation chasing was conducted by analyzing the references for each included study. A total of 122 potential papers were identified. We also included at least 20 Russian biomedical journals listed in databases, which were translated into English. The summary document contained the list of included and excluded articles; the inclusion status for each article was based on a review of the full-text manuscript. The inclusion criteria were articles with the target population, specific location, investigated epidemiological trends, or the comparison between two-to-three studied regions (cities, states, or districts). Exclusion criteria were unrelated, duplicated, unavailable full texts published before 2001. Data were abstracted from 60 eligible papers. Some of these sources had English-language abstracts, but other articles’ texts had to be translated. The evidence was graded for each source based on the quantity and quality of studies and potential data flaws. The quality, validity, and type of published data were considered.

The citation management system EndNote allowed us to organize our literature databases with internet searches and have add-ons for Office programs, which made the process of literature citation convenient. However, the majority of articles in Russian could not be captured by the citation management system. Additionally, the search for article content was sometimes unavailable for search engines. The authors had to enter this information manually to ensure consistency in the referencing of studies. Some Russian sources were originally published as extensive PDF files of the entire journal issue without dividing it into separate articles and providing no descriptors, making manual, time-consuming input of information the only possibility.

Not only are men likelier to die of suicide than women between the ages of 10 and 60 years, but the suicide rate among men also grows with every decade of life, reaching a peak at 50 [ 12 , 13 ]. Russian men become increasingly inclined to commit suicide before their 60th birthday, usually via firearms or strangulation. Although men aged 60, 70, and 80 die from suicide less often than men aged 40 to 59, gender differences prevail. The suicide rate among men over 60 is about 30 cases, compared to about 10 (per 100,000 people) among women of the same age [ 11 , 12 ].

Official data illustrate that suicide rates among men have gradually decreased over the past 20 years. While in 2000 it was 68.4 cases per 100,000 people, in 2010, it was 41 cases per 100,000 people, gradually decreasing to 29.3, 27.6, 21.7, 20.5, and 19.8 cases in 2015, 2016, 2018, 2019, and 2020, respectively, per 100,000 people. Suicide mortality among women is significantly lower than among men. In 2015-2016, it was nearly four times lower than among men and amounted to 7.5 and 7.1 cases per 100,000 people, respectively, in 2015 and 2016. The suicide rate among men in 2000-2020 per 100,000 people is shown in Figure Figure1 1 [ 3 ].

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According to official data, the suicide rate among all age groups decreased. In recent years, the suicide rate among adult men has varied. Data demonstrate that the suicide rate among men increases with every decade of life, reaching a peak of 50 years. Thus, at the age of 15-19 years, the mortality rate from suicide among men was 10-12 cases in 2015-2016 per 100,000 people, at the age of 20-24 years: 18-20 cases, 25-29 years: 24-26 cases, 30-34 years: 31-35 cases, 35-39 years: 37-40 cases, and reaching a maximum in the age group of 50-54 years at 38-41 cases, then decreases gradually. Figure Figure2 2 summarizes data on male suicide mortality in 2015-2016, depending on the age per 100,000 people [ 12 ].

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The data show that the suicide mortality rate among the male population in various age groups has been steadily decreasing since 2002. Between 2000-2003, all age groups of the male population demonstrated a growth in the number of suicide cases. It peaked in this period (2000-2020), except for the 15-29 age group. Between 2004 and 2010, there was the fastest decline in the suicide mortality rate among the male population in different age groups, after which the rate of decline in the mortality rate slowed, which may have been due to the financial and economic crisis in Russia (2008-2010). Figures Figures3 3 - -5 5 summarize the changes in the suicide mortality rate among men in different age groups in 2000-2020 [ 3 ].

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Between 2000-2020, the male suicide rate was variable across all levels of urbanization with higher rates in nonmetropolitan/rural areas than in medium or large metropolitan clusters. Geographic disparities (specific federal districts versus Russia overall) in suicide rates might reflect suicide risk factors known to be prevalent in less urban areas, such as limited access to mental health care, social isolation, and substance abuse.

Official data show that in 2015-2017, the suicide mortality rates among the male population in the Central Federal District, the city of Moscow, and the North Caucasian Federal District were lower than the average for the Russian Federation. The lowest rates were seen in the city of Moscow and the North Caucasian Federal District. In the Northwestern Federal District, suicide mortality rates among the male population were about the same as those in the Russian Federation overall. In the Volga Federal District, Ural Federal District, Siberian Federal District, and Far Eastern Federal District, suicide mortality rates among the male population were higher than the average in Russia. Figure Figure6 6 summarizes the male suicide mortality rates in various federal districts and the Russian Federation in 2015-2017 [ 11 , 12 ].

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Interestingly, Mal et al. (2020) stated that the highest suicide mortality rates were in five Russian federal districts: Northwestern, Volga, Ural, Siberian, and Far Eastern; however, their analysis focused on suicide mortality rates in general. Additionally, the authors indicated that suicide mortality rates were significantly lower in Central, Southern, and North Caucasian Federal Districts [ 14 ].

The impact of urbanization on suicidality in Russian men and on the mental health of the general population remains underestimated [ 15 ]. The highest degree of urbanization was recorded in the Northwestern Federal District of Russia, where almost 85 percent of the inhabitants lived in city areas. The extent to which the suicide rate in urban areas is influenced by exposure to risk factors other than urbanization remains unknown due to a lack of data. The lowest male suicide mortality rates in the Northwestern Federal District are seen in the city of St. Petersburg, where these numbers are lower than the indicators for the Northwestern Federal District. Suicide mortality rates among the male population in the Northwestern Federal District decreased in 2015-2017. The most significant decrease occurred in the Novgorod region. Figure Figure7 7 shows the suicide mortality rates among the male population in various regions of the Northwestern Federal District in 2015-2017 [ 11 , 12 ].

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Interestingly, the regions located in the Northern Caucasus demonstrate significantly lower male suicide rates compared to the rest of the nation [ 16 ]. These numbers and demographic trends were noted almost 20 years ago and remain consistent with our data. The published data suggest that the highest suicide mortality rates among the male population in the North Caucasian Federal District were in the Republic of Alania, being higher than the indicators for the North Caucasian Federal District by about 15%. The lowest male suicide mortality rates were in the Republic of Ingushetia. The numbers are lower than these indicators for the whole North Caucasian Federal District by over two times. These male suicide mortality rates are the lowest of those discussed in this report. However, higher suicide rates were found among male soldiers who served in the Chechen wars and/or were actively serving in other areas of the Caucasus [ 17 ]. Figure Figure8 8 shows suicide mortality rates among the male population in various regions of the North Caucasian Federal District in 2015-2017 [ 11 , 12 ].

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Interestingly, the Russian Southern Federal District borders the republics of the North Caucasus. While some parts of that district are ethnically like the North Caucasus, the male suicide mortality rates are like other regions of Russia with a predominantly Slavic population. Data on male suicide mortality rates in various regions of the Southern Federal District from 2015-2017 showed a gradual tendency to decrease, but those numbers are still significantly higher than in the North Caucasus region. In the Republic of Kalmykia, suicide mortality rates among the male population in 2015-2017 were higher than in the Southern Federal District by about 20%. In the Rostov region, suicide mortality rates among the male population in 2015-2017 were about 15% lower than those in the Southern Federal District. Figure Figure9 9 illustrates suicide mortality rates among the male population in various regions of the Southern Federal District in 2015-2017.

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The Central Federal District is located in the center of the European part of Russia. It is the district with the highest density of population in Russia-60.30 people per square kilometer: a high level of urbanization, as about 50% of the population lives in the Moscow region. This region has a high level of economic and social activity and a presumably better socioeconomic situation. However, male suicide mortality rates vary between cities. Suicide mortality rates among the male population in the Belgorod Region and the city of Moscow were lower than in the whole Central Federal District. In the Kursk and Moscow regions, mortality rates were about the same as in the Central Federal District, especially in 2017. In the regions of Bryansk, Vladimir, Voronezh, Ivanovo, Kaluga, Smolensk, Tver, and Yaroslavl, suicide mortality rates among the male population were higher than in the Central Federal District. In 2015-2017, nearly all regions of the Central Federal District demonstrated decreased male suicide mortality rates. The fastest rates of decline were observed in the regions of Belgorod, Kursk, Smolensk, and Tver. In the Voronezh region, there was an increase in the death rate from suicide among the male population. In Moscow in 2016, the suicide mortality rate increased among the male population compared to 2015. In 2017, this index dropped again. Males aged 55 years and older were more likely to die from suicide than any other age group for both males and females. Figure Figure10 10 shows male suicide mortality rates in various regions of the Central Federal District and the Russian Federation in 2015-2017 [ 11 , 12 ].

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The red column (4.3) is the suicide mortality rate among the female population in Moscow in 2016 [ 11 , 12 ]

Male suicides in the Volga Federal District showed a linear trend of decline in 2015-2017, despite the risk factors for suicide generally increasing. The most significant decrease in male suicide mortality rates among the male population was observed in the Saratov region, which initially showed an unexpected increase in male suicide rates (higher than in the Volga Federal District by about 23%) [ 11 , 12 ]. Suicide mortality rates among the male population in the Ural Federal District in 2015-2017 also showed a tendency to decrease [ 11 , 12 ].

Social marginalization and depopulation are particularly widespread in regions of the Asian part of the country. Despite the implementation of additional state-run social and demographic incentives, the impoverishment of human capital is still evident in this region. This region is far removed from Russia’s European core and financial centers but remains uncomfortably close to dynamic and powerful China. Despite the oil and gas resources of East Siberia and the Far East Federal District, its regional product amounts to just 5-6 percent of Russia’s total gross domestic product (GDP).

These two regions have long been known as underdeveloped and socially challenging. Despite these circumstances, the suicide mortality rates among the male population in the Siberian Federal District (SFD) in 2015-2017 also showed a tendency to decrease. The most significant decrease in suicide mortality rates among the male population occurred in the Altai Republic. In the Krasnoyarsk Region, the Irkutsk region, the indicators were fairly even, like the rates for the Siberian Federal District. Interestingly, in Omsk, suicide mortality rates among the male population in 2015-2017 were about 10% lower than those in the entire Siberian Federal District. The official data show that the highest male suicide mortality rates in the Far Eastern Federal District were in the Amur and Sakhalin Regions, being higher than these rates for the Far Eastern Federal District by 28% and 23%, respectively. Interestingly, the lowest male suicide mortality rates were in the Kamchatsky Territory, where these numbers were lower than the indicators for the Far Eastern Federal District by about 10-15%. Figures Figures11 11 and 12 summarize data regarding male suicide mortality rates in various regions of the SFD and the Far Eastern Federal District in 2015-2017 [ 11 , 12 ].

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Data accuracy issues

According to the World Bank, Russia ranks third in the world in the suicide mortality rate, and this rate in 2019 was 25.10/100,000 per year. However, this rate is disproportionally higher for men. It is important to mention that these rates have been declining over the past 20 years. The available data highlight that the suicide mortality rate among Russian men was as high as 96.7/100,000 in 2000 and decreased to 43.60 in 2019 [ 18 ]. Interestingly, these numbers do not correlate with the data provided by Rosstat [ 3 ]. Table Table1 1 provides additional information on this matter.

Adopted from macrotrends.com [ 18 ].

The research data published in Russia are not always transparent. For example, the “event of undetermined intent” has shown exponential growth since 2014 and has exceeded suicide mortality rates [ 19 ]. The researchers believe that this subcategory includes “latent homicides and suicides,” while actual suicide mortality rates remain unclear. Local coding and data recording standards vary significantly and can negatively affect the transparency of the data. Specifically, many suicides are frequently listed within the “external causes of morbidity and mortality” subcategory [ 19 ]. The ICD-10 classification category includes multiple “environmental events and circumstances as the cause of injury, and other adverse effects,” where potential suicides can be included without any further systematization. “Latent suicides” include falls from heights, poisoning, and hanging with unspecified intent. They account for a significant proportion of suicide mortality. Since they are counted as events of undetermined intent, statistics show a sharp drop in suicide mortality rates, which has a linear trend [ 20 ]. This approach serves as a perfect example of data distortion practices. Moreover, there is no distinct updated information regarding suicides committed in Chechnya and in other North Caucasus republics. Yumaguzin (2019) indicated that suicide rates are significantly underestimated, while ill-defined causes of death are used to misinterpret data related to suicide and self-harming behaviors [ 19 ].

According to Verbitskaya [ 21 ], 80% of publications in Russian have methodological issues or unacceptable research designs. Based on our analysis, many studies conducted or published in Russia have methodological flaws (e.g., incomparable populations, lack of standards, internationally approved scales, and different designs). An analysis of the literature published in Russian showed that many journals have no specific or evidence-based standards for the description and presentation of research results. Although these issues are not directly related to our assessment of men’s suicide rates, it is important to mention these flaws to facilitate positive changes in data reporting. No matter how much the data vary, male suicide mortality rates remain exceptionally high.

Socioeconomic environment

Many experts agree that male suicide mortality rates are a consequence of social, economic, psychological, and demographic issues. Some of Russia’s cultural norms can be attributed to the nation’s tumultuous history, such as that of the former Soviet Union. With the fall of communism, the nation experienced social and economic hardships that adversely affected many Russians’ mental health. Some theorize that such monumental societal changes during that time have had long-term effects, persisting until the present day. However, there has been a downward trend in suicide rates over the last two decades because the nation has improved on many socioeconomic indicators [ 22 ]. The number of suicides correlates with social changes, such as resettlement, assimilation, and the destruction of the conventional social structure.

Financial struggles can be attributed to increased suicidality in men. The three main economic indicators, which are GDP, unemployment rate, and consumer price index, are associated with suicidal ideas, suicide attempts, and suicides [ 23 ]. In the economic crises of the 1990s, unemployment and a decrease in personal income were directly correlated with growing suicide rates, especially among men [ 24 ]. Another study evaluated how certain socioeconomic factors influenced suicide patterns within Russia. The findings demonstrated a significant decline in the male suicide rate with the country’s improvement in economic indicators (e.g., income per capita, GRP growth rate, etc.). The study also evaluated the effects of marriage and divorce on suicide rates among men. Marriage has negative effects on suicide rates, while divorce has positive effects on suicide rates [ 25 ]. Russian men are more prone to relocate and tend to move to large cities to obtain employment and work on a shift basis. These difficulties have also led to the insufficient development of institutions expected to address these social issues [ 26 ].

Geographical aspects

People living in rural areas of Russia are at a greater risk of suicide than those living in urban areas or big cities. The strength of the connection between intoxication and suicide also depends on the geographical region in Russia. Specifically, the data show that rates increase from the south and west to the north and east of the country [ 24 ].

Not only are suicide rates significantly lower in the Northern Caucasus, but other factors also make it important to consider other psychosocial factors. For example, a higher proportion of Muslims in these regions results in a different cultural context in the Northern Caucasus than in the rest of Russia, plus religious differences and Islamic scriptures against suicide. Furthermore, the intersection of these cultural factors with social institutions means that several of the measures included here as controls are confounded with a location in this area.

Average alcohol consumption in central Russia is high with a relatively large proportion of unrecorded consumption ranging from almost zero to 21 liters [ 27 ]. The rates of heavy alcohol consumption (more than 40 g of pure alcohol per day) among men were the lowest in Kabardino-Balkaria and Karachay-Cherkessia (2.3 L of ethanol per adult/year) and the highest in Magadan region (24.3 L per adult/year) [ 28 ]. Alcohol consumption is lower in these regions, and wine products are more often consumed here than in the rest of the country, meaning that the preference for vodka is not as strong as elsewhere in Russia.

Cultural aspects

The Russian mentality is characterized by a man destined to serve the motherland, the army, and his family. Russian culture is rooted in rigid gender roles, and these norms are present even at the institutional level. In The ABC for Men, the author determined that Russia has over a dozen laws that discriminate against men. For example, Russian law supports the idea of motherhood among women, yet no laws exist that support fatherhood. Although there is no concept of "single father" in Russian law, the number of families consisting of single fathers with children is slowly growing in Russia (1.18% in 2002 vs. 1.27% in 2010. According to Russian law, these men are eligible for the same benefits as single mothers [ 29 , 30 , 31 ]. Russian legislators have attempted to pass several similar bills that, although unsuccessful, highlight the inequities between males and females.

Along these lines, men experience different expectations in terms of occupation. Women are not allowed to work certain jobs that are considered difficult or dangerous. Likewise, these occupations consist solely of male employees, allowing men easier access to suicide modalities at hazardous places of work. Such methods, such as pesticides or firearms, are more lethal. Not only this, but a man’s age of retirement is a full five years later than that of a woman [ 31 ]. These policies indicate Russian cultural pressures, which may adversely affect men’s mental health and suicide rates. Finally, 40-50 percent of all marriages in Russia will end in divorce or separation. High divorce rates may also contribute to the likelihood of higher suicide rates in this country [ 32 ].

Child and adolescent suicidality in Russia

Across all post-Soviet countries, Russia has one of the highest rates of child and adolescent suicide [ 33 ]. Parental neglect, such as physical, sexual, or emotional abuse in childhood (PSEA), is very common in Russian families. The link between PSEA and the risk of suicide throughout life has been confirmed by published research data [ 34 ].

According to multiple reports, Russia has often outstripped Europe when it comes to teen suicide rates [ 35 ]. The adolescent suicide rates (specifically between ages 15-34) have steadily increased since 1996, more so than the older age groups. Suicide among young Russian males is four times more common than among young females (32.8 per 100,000 people versus 7.6 in 2004), and it occurs among ever-younger males, some in their early teens [ 36 ]. Although younger groups have had consistently lower suicide rates than middle-aged and older adults, young Russian men have attempted suicide almost twice as often as female youth since 1989. According to reports, almost 4,000 teen suicide attempts were registered in Russia annually, and as many as 1,500 of them resulted in death. In 2016, an ominous report by journalist Galina Mursaliyeva in the Russian newspaper Novaya Gazeta surfaced, which brought to light the presence of online “death groups” on the social media platform vk.com , which influenced countless teenagers to commit suicide worldwide [ 37 ], the biggest proportion of which were Russian teenagers.

In turn, the administrations’ knee-jerk reactions to increasing internet censorship did little to address the situation. There was a 14% spike in emergency room trips for potential suicides by children and adolescents in 2018 compared to 2017 (692 in 2017 versus 788 in 2018), according to findings reported by state officials [ 38 ]. Local media reports estimated that adolescent suicide rates remained relatively unchanged in 2018-2019. Interestingly, local experts noted that increasingly more Russian teenagers wanted to participate in or “supervise” online suicide games in 2020-2021 [ 39 ].

The underlying conditions that deem these children more susceptible to suicidal ideations are social isolation, a dysfunctional family system (e.g. families with interpersonal conflicts, misbehavior, child abuse or neglect), increased social isolation due to stigma surrounding mental health, an inability to relate to the opposite sex, and intolerance toward LGBTQ+ youth [ 40 , 41 ]. Additionally, decreased attention by caregivers to a child’s emotional needs has been the norm for a long time.

Multiple support groups, such as Your Territory and Deti 404, have since emerged on Vk.com to give teenagers a platform to express their frustrations with a skilled support network that provides counseling and mental health support [ 40 ].

Mental health and stigma

Studies of the relationship between psychopathology, substance abuse, and suicide consistently indicate that around 70% of people who die from suicide suffer from an identifiable mental disorder before death. Episodes of major depression associated with a major depressive disorder or bipolar disorder account for at least half of suicide cases [ 42 ]. The prevalence of affective disorders in Russia ranges from 30-40%. The majority of cases remain underdiagnosed and undertreated [ 43 ]. Among suicides, there are usually many factors that can increase underlying risks or interact with depression and increase suicide risk, such as alcohol- and drug-related disorders, which are more common in men [ 44 ].

In almost all regions across the country, men consistently live shorter lives than women. Especially among middle-aged Russian men, high alcohol consumption and ongoing mental health problems contributed to gender differences in all-cause mortality [ 45 ].

In Russia, there is a stigma associated with mental health and consequent suicide. Many Russians consider mental health disorders to be self-inflicted and do not believe in treatment. This stigma can extend to a suicidal individual’s friends, family, and mental health professionals.

Binge drinking is commonplace among Slavic nations, with Russia being one of them. Suicides among men in Russia are specifically associated with high rates of alcoholism. Russia’s cultural pressures also affect the physical health of the country’s men. Men are discouraged from coping with life stressors in healthy ways, and many men turn to drinking or smoking to cope [ 31 ]. Data have shown that many Russian men drink alcohol to cope with stress, unemployment, depression - in situations in which they would otherwise have difficulty coping. High levels of alcoholism in Russia existed before the collapse of the Soviet Union. However, a sharp rise began in the early 1990s and has risen to one of the highest worldwide. Local officials have estimated that alcohol consumption is up to 15 liters per person per year, while consumption in the European Union and the United States is between 7 and 10 liters [ 31 ].

Vodka accounts for roughly 75% of the nation’s alcohol consumption, and approximately one-third of Russian men report binge drinking vodka at least once monthly [ 46 ]. While inebriated, individuals are more susceptible to existing mental health issues and maybe likelier to act on suicidal thoughts. It was shown that life expectancy decreased by 12% between 1990 and 1994, which was directly related to alcohol mortality [ 24 ]. Researchers estimate that 61% of male suicides in Russia involve alcohol, compared to 22% of deaths worldwide that involve alcohol [ 47 ].

Future trends

Russia is witnessing extremely high male suicide rates. As the high suicide rate among Russian males is multifaceted, it can be difficult to develop effective solutions. Current thinking suggests that access to mental health services can lessen suicide rates. Considering all the difficulties, the transition of primarily descriptive results to specialized suicide prevention programs among men turned out to be a challenging task that requires complex medical and social approaches [ 48 - 50 ].

In the last two decades, the Russian Federation has introduced many measures that have yielded tangible results. In the early 2000s, the state became fully involved in the control of the alcohol market [ 46 ]. In 2006, Russia implemented an alcohol policy to control the alcohol market and contain alcohol-related poisonings. President Putin implemented the law in January 2006, which regulated the volume and quality of alcohol products. The patterns thereafter revealed important learnings as to how alcohol consumption affects suicide rates. One study determined that the 2006 policy yielded a 9% decrease in male suicide mortality. This translates into 40, 000 male lives saved yearly from suicide by restricting alcohol [ 24 ].

The WHO published data that, in 2003, both alcohol-related mortality and the amount of alcohol consumed per year decreased significantly [ 51 ]. In this way, the mortality of men has decreased by as much as 40%, while men’s life expectancy has increased from 57 to 68 years over the past 15 years [ 51 ]. In the early stages of the COVID-19 crisis, local experts suggested that the pandemic might lead to an increase in suicide among Russians. Official data released by Rosstat suggested that for the entire year 2020, the standardized mortality ratio due to suicides dropped by 4.1%. However, WHO experts concluded that suicide mortality in Russia is worse than officially reported. According to their report, “Suicide Worldwide in 2019: Global Health Estimates,” the suicide rates (per 100 000) were 25.1 (crude suicide rate) and 21.6 (age-standardized suicide rate), or at least twice as high as the official data [ 52 ]. Given these discrepancies in the data, it is almost impossible to predict future tendencies in men’s suicide mortality. Algorithms used to estimate suicide mortality in men are no longer valid since the data are often inaccurate.

Several effective suicide prevention programs have been implemented in Russia. For example, school- and college-based suicide prevention programs [ 53 - 55 ] have proven effective in reducing the number of suicide attempts among students. Programs aimed at meeting the needs of elderly people from high-risk groups were less effective due to the questionable design of those interventions [ 56 ], none of which have been implemented since 2019.

Laws that prevent access to a particular method, be they stricter firearm control laws, restriction of access and use of blister packs of pills, lockable pesticide boxes, or bridge barriers (often in combination with a crisis intervention telephone hotline), may affect the suicide rate, even if some adjustments to those methods may occur over time [ 57 ].

While Russia, unlike the United States, does not have anything like the Second Amendment in its Constitution, it does provide its citizens with the constitutional right to self-defense. Additionally, background checks before the ownership of guns are more rigorous and consider an individual’s medical and psychological history [ 58 ]. Despite stricter laws, certain individuals could easily bypass background checks either via corrupt measures or obtain firearms via illegal channels, which is a huge market. This problem was brought to the fore, especially after the mass shooting incident in the Russian city of Kazan in May 2021, when a 19-year-old went on a shooting spree, killing nine people and injuring 23. The authorities quickly passed stricter gun control laws, which included more stringent background checks and control over illegal gun trafficking [ 59 ].

The country also saw a spate of physician deaths during the COVID-19 pandemic, in which two healthcare workers died, and one suffered serious injuries due to falling from a building. While the cause of death is still a matter of speculation, it brought into light a system underequipped to deal with the pandemic due to a short supply of equipment and manpower. Reports also highlight the apathy of the hospital administration in dealing with the sudden spike of COVID-19 cases and caring for healthcare workers, many of whom worked tirelessly even after becoming symptomatic [ 60 ].

Conclusions

Although the suicide statistics in Russia are profound, the suicide rate may be even higher than what has been reported. One of the biggest drivers of male suicidality in Russia is the country’s cultural norms. Russia remains very rooted in tradition, and within this tradition lies unique societal pressures. Cultural and psychosocial aspects of the Russian male experience, such as gender norms, low quality of life, and alcohol consumption, are likely key contributors to the country’s high suicide rates.

Our analysis of official reports and secondary sources in Russia also confirmed that there are too many publications of poor-quality study design and statistical analysis. Finally, continuous improvement of public health policy and fundamental and translational research can contribute to reducing the future suicide rate among the male population in Russia.

The content published in Cureus is the result of clinical experience and/or research by independent individuals or organizations. Cureus is not responsible for the scientific accuracy or reliability of data or conclusions published herein. All content published within Cureus is intended only for educational, research and reference purposes. Additionally, articles published within Cureus should not be deemed a suitable substitute for the advice of a qualified health care professional. Do not disregard or avoid professional medical advice due to content published within Cureus.

The authors have declared that no competing interests exist.

Human Ethics

Consent was obtained or waived by all participants in this study

Animal Ethics

Animal subjects: All authors have confirmed that this study did not involve animal subjects or tissue.

IMAGES

SOLVED: CASE 10 CASCADES MENTAL HEALTH CLINIC VARIANCE ANALYSIS
Solved CASCADES MENTAL HEALTH VARIANCE ANALYSIS CASCADES
Cascades Mental Health Clinic by Brian Richards
CASE CASCADES MENTAL HEALTH CLINIC VARIANCE ANALYSIS
SOLUTION: Cascade Mental Health Clinic Variance Analysis
SOLUTION: Cascade Mental Health Clinic Variance Analysis

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