The Family Check-Up and Youth Suicide: Assessing Indirect Effects of Improving Self-Regulation and Reducing Depression in Promoting Long-Term Resilience.

The Family Check-Up and youth suicide: Assessing indirect effects of improving self-regulation and reducing depression in promoting long-term resilience - PMC Skip to main content An official website of the United States government Here's how you know Here's how you know Search Log in Primary site navigation Search Log in Search PMC Full-Text Archive Search in PMC Journal List User Guide As a library, NLM provides access to scientific literature. Inclusion in an NLM database does not imply endorsement of, or agreement with, the contents by NLM or the National Institutes of Health. Learn more: PMC Disclaimer | PMC Copyright Notice Suicide Life Threat Behav . Author manuscript; available in PMC: 2026 Jun 1. Published in final edited form as: Suicide Life Threat Behav. 2025 Jun;55(3):e70029. doi: 10.1111/sltb.70029 The Family Check-Up and youth suicide: Assessing indirect effects of improving self-regulation and reducing depression in promoting long-term resilience Samuel Seidman 1 , Sarah Danzo 2 , Arin Connell 3 , Beth Stormshak 4 Author information Copyright and License information 1 Columbia University Irving Medical Center 2 University of Washington 3 Case Western Reserve University 4 University of Oregon ✉ Corresponding author’s address Samuel Seidman, 352 Varick Street, Apt 3, Jersey City, New Jersey 07302, sbs2245@cumc.columbia.edu PMC Copyright notice PMCID: PMC12247049  NIHMSID: NIHMS2087270  PMID: 40470833 The publisher's version of this article is available at Suicide Life Threat Behav Abstract Rates of suicide in youth have continued to escalate at alarming rates in the last two decades making identifying effective prevention efforts an important goal for researchers. The Family Check-Up (FCU) is a family-focused, prevention program originally developed to reduce externalizing behaviors which has demonstrated improvements in internalizing behaviors and suicide. The present study attempted a conceptual replication of previous results from a separate trial of the FCU initiated in early childhood, that found that the FCU predicts reductions in suicide-risk via improvements in youth self-regulation. The current study examined whether the FCU would predict reductions in youth suicidality via improvements in self-regulatory ability, in an independent trial of the FCU initiated in early adolescence. The current study partially replicated prior results, suggesting that improvements in self-regulatory skills in early adolescence support long-term reductions in suicide-risk into early adulthood. However, the indirect effect of the FCU on suicide-related outcomes was only observed at the level of statistical trend in the current trial. Findings are discussed in the context of broader suicide treatments for youth involving family members and targeting important mechanisms of risk. Keywords: Suicide, Prevention, Family Check Up, Parenting, Childhood, Adolescence Introduction In 2017, suicide became the second leading cause of death for individuals 10 – 24 years old, with an estimated rate of 10.6 per 100,000 youth aged 10 – 24 in the U.S. (CDC, 2019). Moreover, suicide related thoughts and behaviors (e.g., ideation, attempts) are common experiences in youth, with suicidal ideation rates in youth estimated at 19.8% to 24% and rates of suicide attempts at 3.1% to 8.8% ( Cha, et al., 2018 ). The onset of suicide related thoughts and behaviors (STBs) in youth is complex with both family factors and self-regulatory deficits identified as important risk factors ( Brent, 2019 ; Bridge, Goldstein, & Brent, 2006 ). Moreover, there is evidence that family-focused interventions can be effective for reducing STBs in youth (Connell, et al., 2022). The Family Check-Up, a family-focused prevention program, in several independent trials has demonstrated efficacy at reducing youth suicide risk ( Connell, McKillop, & Dishion, 2016 ) and reducing established risk factors for STBs like poor self-regulation (Chang, Shaw, Dishion, Gardner, & Wilson, 2014) and depression ( Connell, et al., 2021 ). Prior examination of STB outcomes in early adolescence from the FCU initiated in early childhood showed that improvements in self-regulatory skills across childhood mediated family intervention effects on suicide risk reductions ( Connell, et al., 2019 ). The current study represents an attempt to replicate and extend this important result in a second independent sample initiated in early adolescence through early adulthood by looking at reductions in self-regulation and depression as important mechanisms of the FCU’s effect on STBs. Family-Focused Prevention A growing body of research supports the benefits of family-focused interventions for protecting against suicide-related behaviors ( Connell, et al., 2021 ; Diamond, et al., 2022 ) through improvements in related risk factors like depression ( Diamond, et al., 2010 ) and self-regulation ( Connell, et al., 2019 ). One such intervention with demonstrated effects improving suicide-related behaviors is the Family Check-Up (FCU). The FCU is a family-focused prevention program which utilizes motivational interviewing techniques to support effective parenting practices (see Dishion & Stormshak, 2007 ). The FCU utilizes an individualized, ecological approach (Bronfrenbrenner, 1974) to support adaptive parenting behaviors. While initially developed to address externalizing and high-risk behaviors in youth, the FCU also has documented efficacy in protecting against youth depression ( Connell, et al., 2021 ; Seidman, et al., 2022) and STBs (e.g. Connell, et al., 2019 ; Connell, et al., 2022). However, the mechanisms of the FCU’s effect on internalizing behaviors and STBs remain unclear. A potential mechanism of this effect may be in improvement of related risk factors, such as depression and poor self-regulation. Across several trials, the FCU has been shown to reduce both depressive symptoms in youth (Connell et al., 2008; 2018 ) and the likelihood of depression diagnosis ( Connell & Dishion, 2017 ). Similarly, trials of the FCU administered both in childhood and in adolescence have been shown to enhance self-regulation ability in youth. Self-regulation is the ability to inhibit inappropriate responses to given demands and is conceptualized as a complex process consisting of cognitive and affective components including impulse control, emotion regulation, and effortful control (see Nigg, 2017 ). For example, in an early childhood trial initiated when children were 2 years old, the FCU was shown to significantly enhance children’s self-regulation ability at age 4 ( Lunkenheimer, et al., 2008 ). A follow-up study demonstrated that effects of the trial on self-regulation ability continued through age 7, with youth in the intervention experiencing greater development of self-regulation abilities across early and late childhood (Chang, et al., 2014). Similar effects were observed in an adolescent trial of the FCU (the current sample) with improvements in self-regulation ability observed across the middle school years (grades 7 and 8; Stormshak, Fosco, & Dishion, 2010 ; Stormshak, et al., 2017). Self-regulation, depression, and suicide risk Deficits in self-regulation have been linked with risk for a range of emotional and behavior problems in youth, including the development of internalizing symptoms and STBs ( Auerbach, Stewart, & Johnson, 2017 ; Nigg, 2017 ). Youth self-regulation ability is shaped in the context of the family (Eisenberg, Cumberland, & Spinrad, 1998) with family discord inhibiting the development of self-regulation ability ( Moilanen, et al., 2010 ). For example, family contexts which are characterized by harsh or coercive parenting styles may impair the development of self-regulation in youth ( Baron & Malmberg, 2017 ), making family-focused interventions ideal for improving self-regulation. Theoretically, deficits in self-regulation may make disengaging from negative cognitions a challenge (e.g., rumination) and result in depression and STB onset. Deficits in self-regulation have been associated with the risk for suicidal behaviors in youth ( Gvion & Apter, 2011 ; Venables et al., 2015 ). Indeed, Connell, et al., (2019) argued that poor self-regulation and inhibitory problems may be associated with depression and suicide risk through cognitive mechanisms, including difficulty disengaging from negative events or memories, thereby predicting escalating rumination and hopelessness, which then lead to escalating depression and heightened risk for suicidality in adolescence ( Miranda, Tsypes, Gallagher, & Rajappa, 2013 ). Correspondingly, the improvements in self-regulation may mediate the FCU’s observed protection against the onset of depression and STBs ( Connell et al., 2019 ). Indeed, the development of adaptive self-regulation is associated with a host of adaptive outcomes in youth including physical well-being (Schwebel, 2004) and educational attainment (Veronneau, et al., 2014). Similarly, this comports with other prevention programs which have found improvements in regulatory ability to mediate important outcomes (e.g., academic performance; Bierman, Nix, Greenbert, Blair, & Domitrovich, 2008 ; Raver et al., 2011 ). However, to date only one study of the FCU has directly examined the mediating effect of self-regulation on STBs (i.e., Connell et al., 2019 ). In their study, Connell and colleagues found administering the FCU in early childhood was associated with later improvements in self-regulatory ability across childhood and subsequent reductions in adolescent suicidality. In contrast, the FCU has demonstrated efficacy in improving depression through improvements in self-regulation (e.g., Hentges, et al., 2020 ). Therefore, examining reductions in depression may be an important mechanism of the effect of improvements in self-regulation on STBs. Present Study The current study represents a conceptual replication and extension of Connell and colleagues 2019’s study, examining the indirect effects of the FCU administered in adolescence on suicide-related outcomes in early adulthood via improvements in self-regulatory skills and reductions in depressive symptoms. We extend the previous work by examining a trial of the FCU delivered in adolescence. Further, in the current study, we extend this work to examine the role of self-regulation in reducing depression as an important step to reducing long-term STB onset in early adulthood. We hypothesized that the FCU would be associated with improvements in self-regulatory ability at follow-up. These improvements would then be associated with reductions in depressive symptoms in late adolescence and reduced STBs in adulthood in the intervention group compared to the control group. Method Participants Demographic data is shown in Table 1 . Families with a child in the sixth grade (782 families) were recruited from three public middle schools located in an urban area of the United States. Of those, 593 families (76%) agreed to participate, the sample was 50.7% female and relatively representative of the local racial/ethnic demographics (34.9% White, 17.2% Hispanic or Latino, 14.7% African American, 6.8% Asian American, 2.8% Indigenous, 1.9% Pacific Islander, and 21.3% identified as multiracial). After initial contact and assessment, families were contacted for follow up visits approximately a year later. Average age at each wave was as follows: 11 years 10 months (wave 1, baseline pre-treatment), 13 years 1 month (wave 2), 14 years 1 month (wave 3), 15 years (wave 4), 20 years (wave 6), 21 years 6 months (wave 7), 22 years 11 months (wave 8). The final sample (N=469) includes adolescents and families who participated and completed follow-up assessments through age 22. Families were randomly assigned to receive the intervention (N=295, 62.8%) or “school as usual” (N=174, 37%). Randomization used an unbalanced approach to increase the power to examine patterns of intervention engagement. Table 1. Frequencies of Youth Suicidal Thoughts and Behaviors in overall sample. Youth report Parent report Either Suicidal ideation 118 (25.2%) 37 (7.8%) 155 (33%) Self-harm or suicide attempt 56 (11.9%) 31 (6.6%) 87 (18.5%) Any 174 (37%) 68 (14.4%) 242 (51.6%) Open in a new tab Procedures The University of Oregon Institutional Review Board approved all procedures. After informed consent was obtained, assessments were conducted every spring between 6 th and 9 th grade. For grades 6 – 9, participants completed a questionnaire in school adapted from Metzler and colleagues (2001), which assessed a wide range of domains. In the case of a family moving, assessments were mailed. Students received $20 for each completed assessment. Follow-up assessments were completed in person and participants received $100 each year they participated in this follow-up assessment. Measures Youth Depressive Symptoms. Depression symptoms were assessed using a 14-item self-report measure of the youth’s own symptoms. Items assessed participants’ symptoms including feeling sad, moody, or hopeless, somatic symptoms of depression (e.g., sleep problems), and other relevant diagnostic criteria for depression. Youth answered on a 5-point scale indicating if they “never or almost never” to “always or almost always” experienced the symptom in the past month. This measure has shown high internal reliability and convergent validity ( Connell, Stormshak, Dishion, Fosco, & Van Ryzin, 2018 ) and in the present study demonstrated good reliability across the waves (e.g., Cronbach’s alpha between 0.92 and 0.95 across time points). Youth Suicide Behaviors. Parents and youth completed the 99-item Adult Behavior Checklist and Adult Self Report surveys, respectively (ABCL, ASR; Achenbach & Rescorla, 2000) at ages 20, 21.5, and 23 years old. The present study utilized the two items from the ABCL and the ASR reflecting suicide-related behaviors (“Talks about killing self” and “Deliberately harms self or attempts suicide”), rated on a 3-point scale (0 = not true , 1 = somewhat/sometimes true , 2 = very true/often true ). Suicide related items from the Achenbach instruments have demonstrated good validity in identifying youth who have engaged in STBs ( Van Meter, et al., 2018 ). Final analyses pooled both parent and youth report on items reflecting suicidal ideation and attempts to create a categorical, dichotomous variable indicating the presence or absence of STBs across reporters and time points. This was done, in part, to increase statistical power given the low base-rate of STBs by either reporter at any wave. Self-regulation. Youth completed the Early Adolescent Temperament Questionnaire (EATQ; Ellis & Rothbart, 2005), which includes a 16-item self-report measure assessing several aspects of self-regulation at each year of the study. The current analyses included data from ages 11 and 13 years old. Participants were asked to report how true they felt a series of statements addressing aspects of self-regulation were for them including things such as concentration, self-control, finishing things on time, planning, and goal setting. Participants were asked to report how true they felt each statement was for them on a 5-point scale ranging from “almost always untrue of you” to “almost always true of you”. For analyses, the average across items was used. Alpha reliability was calculated for the Wave 1 (α = 0.68) and Wave 2 (α = 0.69), showing acceptable internal reliability across waves. Intervention Protocol The current study used data from a randomized, multilevel, school-based prevention trial of the FCU (see Dishion and Stormshak, 2007 for a full discussion). The FCU consists of an assessment phase assessment based on motivational interviewing principles. Following an initial assessment, a family feedback session is conducted with the goal of collaboratively discussing follow-up services tailored to the family’s needs and goals. Based on the goals of the individual family, follow-up sessions focus on supporting effective parenting and family management practices ( Dishion, Stormshak, & Kavanagh, 2012 ). Further intervention includes delivery of a parent-management program targeting parental positive reinforcement, limit setting, and communication skills ( Dishion & Stormshack 2007 ; Kazdin, 2005 ). Families in the intervention condition were offered enrollment in two phases: once in middle-school (n = 163) with a subsequent offering either in high school or in early adulthood (n = 134). Analysis Plan Analyses were conducted in Mplus 8.7 (Muthen & Muthen, 1998–2021), using a path model including families in the intervention and control conditions. Main effect analyses examined intervention effects on early adulthood STBs. Analyses also controlled for demographic covariates (i.e., gender, ethnicity, and two parent household). To test indirect effects, a path model was constructed by first establishing the necessary growth parameters to ensure good model fit indicated by non-significant Chi-square value, CFI values above .90, and RMSEA/SRMR values less than .08 (e.g., Hu & Bentler, 1999). The model was then constructed to test indirect effects of age 13 self-regulation predicted by intervention condition, age 15 depression and early adulthood STBs were then regressed on age 13 self-regulation. Results Descriptive data, main effects, & covariates Frequencies for reported STBs across time points by different reporters from the measures detailed above, are shown in Table 1 . As shown in Table 1 , 107 youth endorsed suicidal ideation, attempts, or both based on parent or youth assessment across ages 20–23 years. Across the two conditions 21.4% of youth (N = 63) in the treatment condition endorsed STBs while 25.3% of youth (N = 44) in the control condition endorsed STBs. Chi-squares analyses showed no significant differences between treatment and control conditions on STBs at adult assessment waves (ages 20–23), 𝜒 2 (1) = .96, p = .36. Independent samples t-tests were conducted to examine potential differences on outcome variables by known demographic risk factors using dichotomized variables for gender (female/male) and race/ethnicity (White/non-White). Results indicated that for gender, significant differences existed for depression scores at wave 4 (age 15), t (466)= 5.59 p < .001. Results indicated no other significant differences across test variables by gender. For race/ethnicity, results indicated that differences existed across wave 1 (age 11) t (575)= −3.63 p < .001 and wave 2 (age 13) t (520)= −4.23 p < .001. Results indicated no other differences across test variables for race/ethnicity. Direct effects A path model demonstrated good fit for the data (χ 2 = 283.16, df = 24, CFI = 1.00, RMSEA = .00, SRMR = .09). Nested model comparisons were conducted to examine whether model fit was improved by allowing paths to differ by gender or ethnic model comparisons. Neither test provided better model fit so in the final model, paths were not allowed to vary by gender or race/ethnicity. There were several significant effects from baseline assessment to first follow-up (mean age 13). Intervention assignment at age 11was related to improvements in self-regulation skills at age 13 for youth in the intervention condition (p = .03). Youth self-regulation at baseline was significantly, positively associated with youth self-regulation at the first follow-up (p < .001). However, youth depression at baseline (age 11) was negatively associated with self-regulation at first follow-up (p < .01). Self-regulation at the first follow-up predicted a significant reduction in reported depression at age 15 (p = < .001). Youth depression at age 11 was significantly, positively associated with age 15 youth depressive symptoms (p = < .001). And finally, depressive symptoms at age 15 were significantly associated with increased reports of suicide behaviors in early adulthood (p = < .001). The intervention had no significant direct effects on either depressive symptoms or on early adulthood suicide behaviors. Indirect effects of the intervention For the hypothesized relationship between intervention, self-regulation, depression, and suicide behaviors a trend level relationship was detected. In particular, intervention assignment was associated, at the level of a statistical trend, with decreases in depressive symptoms at age 15 through increases in self-regulation at the first follow-up (age 13) (β = −.03, SE = .02, p = .055). Further, there was an indirect path from intervention group to early adulthood STBs at the level of a statistical trend through improvements in self-regulation at first follow-up (age 13) and depressive symptoms at the age 15 (β = −.01, SE = .01, p = .08; Figure 1 ). Figure 1. Open in a new tab Indirect effects model of self-regulation on suicide risk outcomes. Discussion The present study sought to examine whether the FCU, a family-focused intervention originally designed to target behavior problems and substance use, had long-term effects on STBs. While no direct effect of the FCU on suicide-related outcomes was observed in the current study, we did see a trend-level indirect effect of the FCU on STBs via improvements in self-regulation and earlier depressive symptoms. This trend-level indirect effect is consistent with previous work on the FCU across early childhood ( Connell, et al., 2019 ), and represents a partial replication of these previous findings. The steps in this overall pathway are discussed, in turn. First, assignment in the FCU intervention group was associated with an increase in self-regulation at the first follow-up post-intervention (mean age 13 years old), replicating findings in previous work (Fosco et al., 2013; Moilanen, et al., 2010 ; Stormshak et al., 2018). This finding also replicates similar studies done with younger age groups showing that administering the FCU in childhood is associated with better self-regulation ability in adolescence (Chang, Shaw, Dishion, Gardner, & Wilson, 2014). Targeting of these transdiagnostic risk factors are in line with current priorities for the National Institute of Mental Health (e.g., Insel, et al., 2010) and can help maximize protections from life-threatening outcomes ( Lockwood, et al., 2017 ). In terms of indirect effects, these findings replicate and extend research from prior trials of the FCU administered in childhood ( Connell, et al., 2019 ) and adolescence ( Connell, et al., 2016 ) demonstrating reductions of STBs. In particular, the findings from Connell and colleague’s 2019 study that show intervention related improvements in self-regulation buffer against STBs extends to adolescent trials. First, intervention group status was associated, at the level of a statistical trend, with reductions in depressive symptoms via increases in self-regulation. This corresponds with previous findings which have shown that the FCU is associated with reductions in depressive symptoms ( Connell & Dishion, 2008 ; Fosco, Van Ryzin, Connell & Stormshak, 2016). Further, there was a trend-level pathway from intervention condition at age 11 to reduced STBs in early adulthood (i.e. ages 20 – 23) via increases in self-regulation ability at age 13 and reductions in depression symptoms at age 15. While Connell and colleague’s 2019 study found significant indirect effects of the intervention on suicide, the present study demonstrated a similar path only at trend level. The weaker effects might, in part, reflect developmental differences across the two samples. For instance, family factors may be more centrally related to suicide-risk across early childhood, while suicide-risk across adolescence may be more complex, involving a broader network of risk factors (e.g. peer, relational, vocational risks), which may effect the strength of FCU effects on suicide-risk. Finally, these results demonstrate the broad transdiagnostic importance of family-focused interventions given the effects on protective (e.g., self-regulation ability) and unique risk factors (e.g., depression, suicide), and suggests potential promise for family-focused intervention trials with adolescents which target internalizing disorders and STBs. As noted, the inability to inhibit oneself (often developed in childhood and adolescence) may leave youth particularly vulnerable to ruminative tendencies and depression, which in turn, may leave youth particularly vulnerable to suicide behaviors, particularly given the multiple risk factors associated with suicide onset (Cha, Franz, Guzmán, Glenn, Kleiman, & Nock, 2018). Limitations & Future Directions While the present study has many advantages including a large, diverse sample and longitudinal design, several limitations should be addressed in future studies. Many of the study’s limitations relate to the method by which suicide behaviors were assessed which relate primarily to the low base rate of suicide behaviors in the study sample. First, the present study collapsed suicide behaviors across categories (i.e., attempts and ideation) into a single variable. As such we were not able to observe any differences between individuals with ideation, attempt, or ideation and attempts. Previous work has demonstrated meaningful differences in terms of risk behaviors and outcomes for individuals who attempt suicide versus those with suicide ideation only ( May & Klonsky, 2016 ). Similarly, our study used either parent or youth report of suicide behaviors to indicate the presence of suicide behaviors. While this may have enhanced our sensitivity in detecting suicide behaviors, disagreement between reporters on the presence of suicide behaviors suggest conclusions should be interpreted somewhat cautiously. Previous work on the relationship between parent and child-reports of wellbeing show little relationship between the two ( Waters, Stewart-Brown, & Fitzpatrick, 2003 ), future research should examine differences in reporters. In terms of future directions, while the present study found promising results, the pathway from treatment condition to self-regulation ability to suicide behaviors was only significant at the level trend. While replication studies tend to find slightly weaker effects compared to the original findings (see Anderson & Maxwell, 2016 for a discussion), the same direction of effect was nevertheless observed in a second, independent trial of the FCU in a different age-range. Future studies should seek to replicate the present study in additional adolescent samples, as well as extend these hypotheses to other age groups. Moreover, additional mediators may be examined such as family environment and parenting behaviors which are primary targets for the FCU should be considered as potentially altering the effects. Finally, future suicide prevention efforts in youth samples should consider the role of more specific self-regulatory capacities (e.g., effortful control) in their design and outcome. Table 2. Correlations for model variables. Variable 1 2 3 4 5 6 1. Intervention status - 2. Self-regulation Age 11 .02 - 3. Self-regulation Age 13 .15** .60** - 4. Depression Age 11 −.03 −.37** −.31** − 5. Depression Age 15 .01 −.21** −.27** .29** − 6. Suicide risk −.05 −.09 −.09 .14** .22** − Open in a new tab Acknowledgements We acknowledge the contribution of the Project Alliance staff and Portland Public schools, as well as the contribution of the participating families and youth. Funding statement This research was supported by the National Institute on Drug Abuse Grant DA018374 to Elizabeth Stormshak. Footnotes Conflict of interest disclosure The authors have no conflicts of interest to report. Ethics approval statement All study procedures were approved by the University of Oregon Institutional Review Board (IRB). Patient consent statement All participating families provided signed consent forms. Clinical trial registration ID NCT01490307 Contributor Information Samuel Seidman, Columbia University Irving Medical Center. Sarah Danzo, University of Washington. Arin Connell, Case Western Reserve University. Beth Stormshak, University of Oregon. Data availability statement Any questions regarding data can be directed to the corresponding author. References Anderson SF & Maxwell SE (2016). There’s more than one way to conduct a replication study: Beyond statistical significance. Psychological Methods, 21(1), 1–12. [ DOI ] [ PubMed ] [ Google Scholar ] Auerbach RP, Stewart JG, & Johnson SL (2017). Impulsivity and suicidality in adolescent inpatients. Journal of Abnormal Child Psychology, 45, 91–103. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] Baron A & Malmberg L (2017). A vicious or auspicious cycle: The reciprocal relation between harsh parental discipline and children’s self-regulation. European Journal of Developmental Psychology, 3(16), 1–16. [ Google Scholar ] Beautrais AL (2000). Risk factors for suicide and attempted suicide among young people. Australian and New Zealand Journal of Psychiatry, 34, 420–436. [ DOI ] [ PubMed ] [ Google Scholar ] Bierman KL, Nix RL, Greenberg MT, Blair C, & Domitrovich CE (2008). Executive functions and school readiness intervention: Impact, moderation, and mediation in the Head Start REDI program. Development and Psychopathology, 20, 821–843. doi: 10.1017/S0954579408000394 [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] Borowsky IW, Ireland M, & Resnick MD (2001). Adolescent suicide attempts: Risk and protectors. Pediatrics, 107, 485–493. [ DOI ] [ PubMed ] [ Google Scholar ] Brennan LM, Shelleby EC, Shaw DS, Gardner F, Dishion TJ, Wilson M (2013). Indirect effects of the Family Check-Up on school-age academic achievement through improvements in parenting in early childhood. Journal of Education Psychology, 105(3). [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] Brent DA (2019). Master clinician review: Saving Holden Caulfield: Suicide prevention in children and adolescents. Journal of the American Academy of Child & Adolescent Psychiatry, 58(1), 25–35. [ DOI ] [ PubMed ] [ Google Scholar ] Brent DA & Mann JJ (2005). Family genetic studies, suicide, and suicidal behavior. American Journal of Medical Genetics, 133C, 13–24. [ DOI ] [ PubMed ] [ Google Scholar ] Brent DA, McMakin DL, Kennard BD, Goldstein TR, Mayes TL, & Douaihy AB (2013). Protecting adolescents from self-harm: A critical review of intervention studies. Journal of the American Academy of Child and Adolescent Psychiatry, 51(12), 1260–1271. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] Brent DA, Melhem NM, Oquendo M, Burke A, Birmaher B, Stanley B, Biernesser C, Keilp J, Kolko D, Ellis S, Porta G, Zelazny J, Iyengar S, & Mann JJ (2015). Familial pathways to early-onset suicide attempt: A 5.6-year prospective study. Journal of the American Medical Association Psychiatry, 72(2), 160–168. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] Brent DA, Oquendo M, Birmaher B, Greenhill L, Kolko D, Stanley B, Zelazny, Brodsky B., Bridge J, Ellis S, Salazar O, Mann JJ (2002). Familial pathways to early-onset suicide attempt: Risk for suicidal behavior in offspring of mood-disordered suicide attempters. Archives of General Psychiatry, 59, 801–807. [ DOI ] [ PubMed ] [ Google Scholar ] Bridge JA, Goldstein TR, & Brent DA (2006). Adolescent suicide and suicidal behavior. Journal of Child Psychology and Psychiatry, 47, 372–394. [ DOI ] [ PubMed ] [ Google Scholar ] Busby DR, Hatkevich C, McGuire TC, & King CA (2020). Evidence-based interventions for youth suicide risk. Current Psychiatry Reports, 22(5). [ DOI ] [ PubMed ] [ Google Scholar ] Cha CB, Franz PJ, Guzman EM, Glenn CR, Kleiman EM, & Nock MK (2018). Annual research review: Suicide among youth – epidemiology, (potential) etiology, and treatment. Journal of Child Psychology and Psychaitry, 59(4), 460–482. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] Connell AM & Dishion TJ (2008). Reducing depression among at-risk adolescents: Three-year effects of a family-centered intervention embedded within schools. Journal of Family Psychology, 22(3), 574–585. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] Connell AM, & Dishion TJ (2017). Long-term effects of the Family Check-Up in public secondary school on diagnosed major depressive disorder in adulthood. Journal of youth and adolescence, 46, 570–581. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] Connell AM, Magee K, Stormshak E, Ha T, Westling E, Wilson M, & Shaw D (2021). Long-term cross-over effects of the family check-up prevention program on child and adolescent depression: Integrative data anlysis of three randomized trials. Journal of Consulting and Clinical Psychology, 89(9), 773–782. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] Connell AM, McKillop HN, & Dishion TJ (2016). Long-term effects of the Family Check-Up in early adolescence on risk of suicide in early adulthood. Suicide and Life-Threatening Behavior, 46, S15–S22. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] Connell AM, Shaw D, Wilson M, Danzo S, Weaver-Krug C, Lemery-Chalfant K, & Dishion TJ (2019). Indirect effects of the early childhood Family Check-Up on adolescent suicide risk: The mediating role of inhibitory control. Development and Psychopathology, 31, 1901–1910 [ DOI ] [ PubMed ] [ Google Scholar ] Connell AM, Stormshak E, Dishion T, Fosco G, & Van Ryzin M (2018). The Family Check Up and adolescent depression: An examination of treatment responders and non-responders. Prevention Science, 19, 16–26. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] Czyz EK & King CA (2015). Longitudinal trajectories of suicidal ideation and subsequent suicide attempts among adolescent inpatients. Journal of Clinical Child and Adolescent Psychology, 44(1), 181–193. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] Deville DC, Whalen D, Breslin FJ, Morris AS, Khalsa SS, Paulus MP, Barch DM (2020). Prevalence and family-related factors associated with suicidal ideation, suicide attempts, and self-injury in children aged 9 to 10 years. Journal of the American Medical Association, 3(2). [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] Diamond GS, Kodish T. Karuthamer Ewing, E.S., Hunt QA, Russon JM (2022). Family processes: Risk, protective and treatment factors for youth at risk for suicide. Aggression and Violent Behavior, 64. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] Diamond GS, Wintersteen MB, Brown GK, Diamond GM, Gallop R, Shelef K, & Levy S (2010). Attachement-Based Family Therapy for adolescents with suicidal ideation: A randomized controlled trial. Journal of the American Academy of Child and Adolescent Psychiatry, 49(2), 122–131. [ DOI ] [ PubMed ] [ Google Scholar ] Dishion T & Stormshack E (2007). Intervening in children’s lives: an ecological, family-centered approach in mental health care. Washington, DC: American Psychological Association. [ Google Scholar ] Dishion TJ, Stormshak EA, & Kavanagh KA (2012). Everyday parenting: A professional’s guide to building family management skills. Research Press. [ Google Scholar ] Gallagher ML & Miller AB (2018). Suicidal thoughts and behavior in children and adolescents: An ecological model of resilience. Adolescent Research Review, 3(2), 123–154. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] Gould MS, Fisher P, Parides M, Flory M, & Shaffer D (1996). Psychosocial risk factors of child and adolescent completed suicide. Archives of General Psychiatry, 53, 1155–1162. [ DOI ] [ PubMed ] [ Google Scholar ] Gould MS, Greenberg T, Velting DM, & Shaffer D (2003). Youth suicide risk and preventive interventions: A review of the past 10 years. Journal of the American Academy of Child and Adolescent Psychiatry, 42(4), 386–405. [ DOI ] [ PubMed ] [ Google Scholar ] Gvion Y & Apter A 2011). Aggression, impulsivity, and suicide behavior: A review of the literature. Archives of Suicide Research, 15, 93–112. [ DOI ] [ PubMed ] [ Google Scholar ] Hentges RF, Weaver Krug CM, Shaw DS, Wilson MN, Dishion TJ, & Lemery-Chalfant K (2020). The long-term indirect effect of the early Family Check-Up intervention on adolescent internalizing and externalizing symptoms via inhibitory control. Development and Psychopathology, 32, 1544–1554. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] Hooven C, Walsh E, Pike KC, & Herting JR (2012). Promoting CARE: Including parents in youth suicide prevention. Family and Community Health, 35(3), 225–235. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] Kazdin AE (2005). Parent management training: treatment for oppositional, aggressive, and antisocial behavior in children and adolescents. New York: Oxford University Press. [ Google Scholar ] Lockwood J, Daley D, Townsend E & Sayal K (2017) Impulsivity and self-harm in adolescence: a systematic review. Eur Child Adolesc Psychiatry, 26, 387–402 [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] Luebbe AM, Bell DJ Positive and Negative Family Emotional Climate Differentially Predict Youth Anxiety and Depression via Distinct Affective Pathways. Journal of Abnormal Child Psychology 42, 897–911 (2014). 10.1007/s10802-013-9838-5 [ DOI ] [ PubMed ] [ Google Scholar ] Lunkenheimer ES, Dishion TJ, Shaw DS, Connell AM, Gardner F, Wilson MN, & Skuban EM (2008). Collateral benefits of the Family Check-Up on early childhood school readiness: Indirect effects of parents’ positive behavior support. Developmental Psychology, 44(6), 1737–1752. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] MacGregor EK, Grunebaum MF, Galfalvy HC, Melhem N, Burke AK, Brent DA, Oquendo MA, & Mann JJ (2014). Depressed parents’ attachment: Effects on offspring suicidal behavior in a longitudinal, family study. Journal of Clinical Psychiatry, 75(8), 879–885. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] May AM & Klonsky ED (2016). What distinguishes suicide attempters from suicide ideators? A meta-analysis of potential factors. Clinical Psychology Science and Practice, 23, 5–20. [ Google Scholar ] Mehlum L, Tormoen AJ, Ramberg M, Haga E, Diep LM, Laberg S, Larsson BS, Stanley BH, Miller AL, Sund AM, & Groholt B (2014). Dialectical Behavior Therapy for Adolescents with repeated suicidal and self-harming behavior: A randomized trial. Journal of the American Academy of Child and Adolescent Psychiatry, 53(10), 1082–1091. [ DOI ] [ PubMed ] [ Google Scholar ] Miller W & Rollnick S (2002). Motivational interviewing: preparing people for change. New York: Guildford press. [ Google Scholar ] Miranda R, Tsypes A, Gallagher M, & Rajappa K (2013). Rumination and hopelessness as mediators of the relation between perceived emotion dysregulation and suicidal ideation. Cognitive Therapy and Research, 37, 786–795. doi: 10.1007/s10608-013-9524-5 [ DOI ] [ Google Scholar ] Moilanen KL, Shaw DS, Dishion TJ, Gardner F, & Wilson M (2010). Predictors of longitudinal growth in inhibitory control in early childhood. Social Development, 19(2), 326–347. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] Nigg JT (2017). Annual research review: On the relations among self-regulation, self-control, executive functioning, effortful control, cognitive control, impulsivity, risk-taking, and inhibition for developmental psychopathology. Journal of Child Psychology and Psychiatry, 58(4), 361–383. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] Ougrin D, Tranah T, Stahl D, Moran P, & Asarnow JR (2015). Therapeutic interventions for suicide attempts and self-harm in adolescents: Systematic review and meta-analysis. Journal of the American Academy of Child and Adolescent Psychiatry, 54(2), 97–107. [ DOI ] [ PubMed ] [ Google Scholar ] Pineda J & Dadds MR (2013). Family intervention for adolescents with suicidal behavior: A randomized controlled trial and mediation analysis. Journal of the American Academy of Child and Adolescent Psychiatry, 52(8), 851–862. [ DOI ] [ PubMed ] [ Google Scholar ] Raver CC, Jones SM, Li-Grining C, Zhai F, Bub K, & Pressler E (2011). CSRP’s impact on low-income preschoolers’ preacademic skills: Self-regulation as a mediating mechanism. Child Development, 82, 362–378. doi: 10.1111/j.1467-8624.2010.01561.x [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] Shaw DS, Connell AM, Dishion TJ, Wilson MN, & Gardner F (2009). Improvements in maternal depression as a mediator of intervention effects on early childhood problem behavior. Development and Psychopathology, 21, 417–439. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] Stormshak EA, Fosco GM, & Dishion TJ (2010). Implementing interventions with families in schools to increase youth school engagement: The Family Check-Up model. School Mental Health, 2, 82–92. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] Van Meter AR, Algorta GP, Youngstrom EA, Lechtman Y, Youngstrom JK, Feeny NC, & Findling RL (2018). Assessing for suicidal behavior in youth using the Achenbach System of Empirically Based Assessment. European child & adolescent psychiatry, 27(2), 159–169. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] Venables NC, Sellbom M, Sourander A, Kendler KS, Joiner TE, Drislane LE, Sillanmaki L, Elonheimo H, Parkkola K, Multimaki P, and Patrick CJ (2015). Separate and interactive contributions of weak inhibitory control and threat sensitivity to prediction of suicide risk. Psychiatry Research, 226(2–3), 461–466. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] Waters Stewart-Brown, & Fitzpatrick, 2003). Agreement between adolescent self-report and parent reports of health and well-being: results of an epidemiological study. Child: Care, Health, and Development, 29(6), 501–509. [ DOI ] [ PubMed ] [ Google Scholar ] Zalsman G, Hawton K, Wasserman D, Heeringen K, Arensman E, Sarchiapone M, . . . Zohar J (2016). Suicide prevention strategies revisited: 10-year systematic review. Lancet Psychiatry, 3, 646–659. [ DOI ] [ PubMed ] [ Google Scholar ] Associated Data This section collects any data citations, data availability statements, or supplementary materials included in this article. Data Availability Statement Any questions regarding data can be directed to the corresponding author. 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