Who Responds to CAMS? Latent Profiles of Patients Who Received the Collaborative Assessment and Management of Suicidality

Who Responds to CAMS? Latent Profiles of Patients Who Received the Collaborative Assessment and Management of Suicidality | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Who Responds to CAMS? Latent Profiles of Patients Who Received the Collaborative Assessment and Management of Suicidality Josephine Sheron Au, David A. Jobes, Kathryn A. Degnan This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6581494/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 17 Oct, 2025 Read the published version in Journal of Contemporary Psychotherapy → Version 1 posted 7 You are reading this latest preprint version Abstract Background : Identifying typologies of patients who are suicidal have important clinical implications. The Suicide Status Form (SSF) of the Collaborative Assessment and Management of Suicidality (CAMS) is a well-validated suicide assessment tool that may help derive clinical subtypes. Despite the strong psychometric properties of different sections of the SSF, no prior studies have examined all SSF variables in aggregate. Method : This study uses latent profile analysis (LPA) to statistically generate subtypes of patients who are suicidal based on a diverse and aggregate sample from three clinical trials conducted in an inpatient setting, an active-duty Army outpatient clinic, and a university counseling center. Results : Based on fit indices, the four-profile model yielded the best fit with the data. The four profiles were characterized by (1) acute stress, (2) history of multiple attempts, (3) female gender and features of borderline personality disorder, and (3) male gender and externalizing traits. The fourth profile reported the lowest ratings of suicide risk at termination, overall, while there was preliminary evidence showing that those in profile one and two were at elevated risk of attempting suicide. Limitations : A limitation is that the sample size is relatively small for LPA, despite the stability of the profiles. Conclusion : This study identified four distinct suicide typologies based on both qualitative and quantitative factors related to suicide risk, as derived from a widely used clinical assessment tool. These typologies were found to vary according to sex, history of suicide attempt, acute stressors, borderline personality traits, and externalizing behaviors. Clinical implications and future directions for research are also discussed. Typologies suicide risk suicide attempts CAMS latent profile analysis Figures Figure 1 Figure 2 Introduction Suicide continues to be a leading cause of death across age groups in the United States, with over 49,000 deaths reported in 2023—equating to approximately one death every 11 minutes (Centers for Disease Control and Prevention [CDC], 2025a). This reflects a 36% increase in suicide rates between 2000 and 2022 (CDC, 2025b). Beyond fatalities, a significant number of individuals experience suicidal thoughts and behaviors. In 2022, approximately 12.8 million adults seriously considered suicide, 3.7 million made a suicide plan, and 1.5 million attempted suicides (CDC, 2024a). These figures underscore the broader and ongoing mental health crisis in the United States. In the face of a patient who screened positive for suicide risk (SR) and with the daunting number of over three thousand identified risk factors (Franklin et al., 2017), many clinicians are simply under-equipped to make decisions regarding treatment assignment and triage care. Although there are organizational guidelines that help with risk stratification (National Institute of Mental Health, 2023; SAMHSA, 2009) and models for risk assessment, SR assessment is still an “inexact science” that requires extensive evaluation of multiple contextual and personal factors (Betz & Boudreaux, 2016; Pisani et al., 2016). The Case for Subtypes Alternatively, suicidologists have attempted to identify subtypes of individuals who engage in suicidal behaviors. About four decades ago, Schwartz (1979) describes two types of patients who are suicidal: those whose suicidality is “ego-syntonic” (consistent with or in harmony with one’s self-image) versus those whose suicidality is “ego-dystonic” (in conflict or dissonance with one’s self-image). He and his colleagues argued that those whose suicidality is more egosyntonic, when compared to those whose suicidality is more ego-dystonic, are more likely to experience chronic suicidality, and that treatments should be adapted accordingly (Schwartz, 1979; Schwartz et al., 1974). These descriptions correspond with Rudd’s (2006) “fluid vulnerability theory,” which postulates suicidal mode is time-limited in nature. He also noted that certain individuals’ suicidal mode is more easily triggered (e.g., among those with multiple previous attempts) than others’ due to differences in physiological, affective, and behavioral deficits. This theoretical distinction is supported by subsequent treatment research that differentiates “acute resolvers” from “chronic non-resolvers” (Jobes et al., 1997), as well as neurobiological studies that separate a “stress-responsive” pattern of suicidal thoughts from a “non-stress-responsive” pattern, all of which show that suicide is an equifinal outcome from distinct pathological processes (Bernanke et al., 2017a). Such distinctions are consequential as certain interventions, such as hospitalization, may only benefit a subgroup of patients but iatrogenic for others (Koerner & Linehan, 2000; Ross et al., 2023; Ward-Ciesielski & Rizvi, 2020). Latent Class/Profile Analysis To this end, earlier studies often used cluster analysis to statistically categorize these individuals (Engström et al., 1996; Rapeli & Botega, 2005). More recent studies adopt latent class/profile analysis (LCA/LPA) to statistically generate and compare these clusters. LCA/LPA is now a popular method to identify these different clusters, all of which find at least two subtypes of individuals who are suicidal (Au et al., 2021; Bernanke et al., 2017b; Dhingra et al., 2016; Freitag et al., 2023; Klonsky & Olino, 2008; Logan et al., 2011; Tairi et al., 2018). For instance, one study identified that there are at least two sets of individuals who are at risk of SI, one group that experiences depressive symptoms that possibly drive their SI and another group that report feeling desperate, hopeless, and lonely, but not depressed (Bernanke et al., 2017b). Unlike commonly used statistical methods that adopt a variable-centered approach (e.g., factor analysis, structural equation modeling, regression analysis), LPA adopts a person-centered lens that aims to classify individuals into unobserved subgroups that evidence less variability within the group than between groups (Muthén & Muthén, 2000). It relies on objective statistical models to estimate the probability of class membership instead of relying on an ad hoc algorithm that relies on subjective decisions (Everitt & Hand, 1981). Additionally, instead of strictly predicting the membership of an individual in a group, the flexibility of LPA allows for an estimation of the probability of such membership (DiStefano & Kamphaus, 2006). The maximum likelihood estimation procedure created latent classes based on calculations of model parameters that best explain the proposed relationships among the observed data, and individuals are assigned to the latent class for which they have the highest posterior probability of membership (Dayton, 1998; McCutcheon, 1987; Muthén, 2004). The fact that the studies consistently identify more than one class corroborates theories that emphasize the heterogeneity of suicidal experiences (Jobes, 1995; Rudd, 2006; Schwartz, 1979). However, depending on the variables, methods, and samples used in these studies, the subtypes generated can vary. In addition, no study to date has examined the treatment outcomes associated with these subtypes. The Collaborative Assessment and Management of Suicidality (CAMS) and the Suicide Status Form (SSF) CAMS is one of the few evidence-based suicide-specific interventions with replicated findings on its effectiveness in reducing suicidal ideation (Jobes et al., 2023; Swift et al. 2021). It is a recommended clinical framework to assess and treat SR as it captures the idiosyncratic nature of suicide and is designed to avoid involuntary hospitalization that may exacerbate long-term risk of suicide or damage treatment alliance (Oquendo & Bernanke, 2017). CAMS has a strong focus on the collaboration between the therapist and patient in suicide assessment and treatment planning, as well as the identification and treatment of patient-identified "drivers" of suicide (Tucker et al., 2015). Each CAMS session includes sections of the session where the therapist and patient sit next to each other to complete the Suicide Status Form (SSF), which allows patients to describe their suicidality quantitatively and qualitatively. The SSF is a well-studied and validated multipurpose clinical assessment, treatment planning, risk tracking, and outcome evaluation clinical tool used in CAMS (Brancu et al., 2016; Conrad et al., 2009; Corona et al., 2018; Jobes et al., 2004; Lento et al., 2013; O’Connor et al., 2012; Romanowicz et al., 2013). Despite strong theoretical and empirical evidence supporting the use of the SSF, the different constructs assessed on the SSF are typically studied independently from each other. This can contribute to not-well-informed providers making clinical decisions based on estimates of interactions among these variables to predict SR – a common problem faced by clinicians (Fowler, 2012). Therefore, it would be important to provide a concise heuristic to guide decision making (Joiner et al., 1999). Present Study The present investigation used LPA to explore the psychometric properties and predictive validity of the initial session SSF to inform our understanding of the typologies of patients who present to a suicide-focused intervention. The goal of the study is to identify psychological profiles of patients in relation to treatment responses to CAMS in hopes of optimizing care with implications for triage and disposition. Based on previous research on the typologies of suicide, the following hypotheses were generated: (1) There would be more than one latent profile of patients who are suicidal. However, since no other study has attempted this approach with the SSF initial session data, the exact type and number of profiles is an exploratory question. (2) The generated latent profiles will show differential treatment outcomes. No specific hypotheses regarding the relationship between specific profiles and treatment outcomes were stipulated. Although this study focuses solely on the CAMS approach to assessing and treating SR, the findings regarding typologies of patients who were suicidal have implications for both triage and post treatment dispositional care. Method This is a longitudinal exploratory study based on CAMS data collected from three different clinical trials. This retrospective archival study was approved by the Institutional Review Board of The Catholic University of America (18–062). Sample Participants of this study were drawn from three treatment studies on CAMS ( N = 168), including individuals from an inpatient psychiatric sample (Ellis et al., 2012), an active-duty U.S Army Soldier sample (Jobes et al., 2017 ), and a college counseling center student sample (Pistorello et al., 2018 ). The first sample included 51 patients who were suicidal and admitted to an inpatient psychiatric hospital in the South Central region of the U.S. and enrolled in three different adult treatment programs (Ellis et al., 2015 ). The second sample included 86 active-duty U.S. Army Soldiers who were suicidal and received CAMS within a RCT funded by the Department of Defense (Jobes et al., 2017 ). These Soldiers were recruited from an infantry instillation and had a score of > 12 on the Beck Scale for Suicide Ideation – Current (SSI-C; Beck et al., 1997 ; Comtois et al., 2011 ). Over half of the sample, i.e., 50 (58.14%), had been deployed at least once. The third sample included 31 college students enrolled in a mid-sized public university in the intermountain west of the U.S. who presented to the university's counseling center with moderate to severe SR (Pistorello et al., 2018 , 2021 ). Those who scored a 2 or above on the Counseling Center Assessment of Psychological Symptoms-34 (CCAPS-34) question, “I have thoughts of ending my life” (range is 0 “not at all like me” to 4 “extremely like me” ) were recruited to participate. Demographic characteristics and history of suicide attempt of the three samples are summarized in Table 1 . Table 1 Descriptive Statistics of Demographic Variables Demographic variables Categories Inpatient Military Counseling Center M SD M SD M SD Age at recruitment 31.13 13.11 26.77 6.04 19.48 1.48 n % n % n % Gender Female 32 69.57 17 19.77 20 64.52 Race White/Caucasian 44 95.65 46 54.12 16 51.61 Black/African 0 0.00 19 22.35 2 6.45 Asian 1 2.17 1 1.18 4 12.90 Mexican/Chicano - - 2 2.35 - - Puerto Rican - - 8 9.41 - - Native Hawaiian/other Pacific Islander 1 2.17 1 1.18 - - Multiracial/other - - 6 7.06 6 19.35 Ethnicity Latinx/Hispanic 2 4.35 13 15.48 3 9.68 Single - - 19 24.68 - - Married 8 17.39 39 46.99 - - Have children - - 41 57.75 - - Heterosexual - - 70 85.37 17 62.96 Education Some high school - - 1 1.41 - - High school diploma/GED 4 8.70 20 28.17 - - Some college 18 39.13 30 42.25 - - Technical/Associate degree 3 6.52 3 4.23 - - Bachelor's degree 10 21.74 5 7.04 - - Master's degree 7 15.22 1 1.41 - - Professional degree 4 8.70 1 1.41 - - History of suicide attempt 0 11 23.91 30 40.54 19 61.29 1 12 26.09 26 35.14 8 25.81 > 1 23 50.00 18 24.32 4 12.90 Measures Profile indicators and outcome measures are listed in Table 2 . Readers can refer to the SSF and related papers for more detailed information about related variables (see Lento et al., 2013 ; Stone, 2011). Additional demographic variables and non-SSF psychological measures often included in CAMS studies, including the SSI-C (Beck et al., 1997 , 1979 ), the Beck Hopelessness Scale (BHS; Beck, et al., 1974 ) were also used. Not all data are available across the three samples but those measures that are available in at least two samples were included in the analyses. Table 2 List of Profile Indicator and Outcome Variables Continuous variables Categorical variables Dichotomous variables Profile indicators *Psychological pain Race + Sex *Stress Motivation Marital status *Agitation Education level Suicide plan *Hopelessness Attempt history type Access to means *Self-Hate Sexual orientation Suicide preparation *SR (patient-rated) Suicide rehearsal *Suicidal t/f related to self History of suicidal behaviors *Suicidal t/f related to others Current intent *Number of RFL Impulsivity *Number of RFD Substance abuse *Wish to live Significant loss *Wish to die Interpersonal isolation *SIS Relationship problems *SR (clinician-rated) Burden to others Age Health problems SSI-C Physical pain BHS Legal problems Shame Sleep problems BPD Outcome Length of treatment *SR (patient-rated) *Psychological pain *Past week suicidal t/f *Stress *Past week managed t/f *Agitation *Past week suicidal behavior *Hopelessness *Continued outpatient therapy *Self-Hate *Mutual termination *SR (clinician-rated) *Patient discontinued BHS unilaterally SSI-C 1-mo SSI-C 3-mo *SSF variables + Race was excluded from LPA due to lack of strong relationships with other variables. Two of our three samples also included a measure of BPD. The military sample used the Structured Clinical Interview for DSM-IV Axis II BPD (First, 1997 ) after baseline assessment and within a month after treatment started (Jobes et al., 2017 ). The counseling center sample included a baseline measure of the Personality Assessment Inventory - Borderline Features scale (PAI-BOR; Morey, 1991 ). Using the recommended cut off score of 38 in the counseling center sample (Ayduk et al., 2008 ; Trull, 1995 ) and the clinical diagnosis based on the SCID given in the military sample, respondents in these two samples were given a dichotomous coding of 0 or 1 to indicate the presence of BPD. Data Analyses Analyses were conducted using Version 8.2 of Mplus (Muthén & Muthén, 2018 ). Preliminary Analyses The distributions of the profile continuous variables were all within the acceptable range of skewness between − 2 and + 2 (George & Mallery, 2010 ). As for outcome continuous variables, the skewness of length of treatment, SSI-C at one-month, and patient-rated overall SR were outside of the acceptable range. The first two variables were log-transformed. However, self-rated SR at the end of treatment, which had a significant floor effect, was recoded into a binary variable (0 = rating of 1; 1 = rating > 1). In addition, Pearson’s correlations, t -tests, and ANOVAs were run among all profile indicators and outcome variables to make sure that they are reasonably related before entering the LPA. Latent Profile Analysis and BCH Method Often, latent categorical variables (C) are first generated based on a set of indicators (U) (Asparouhov & Muthén, 2018 ). After classes are generated, researchers are often interested in understanding the relationship between the classes and other auxiliary variables, such as observed predictor (X) and distal outcome (Y) variables. A common problem when auxiliary variables are included in the mixture model is that the forming of classes can be affected. Such shifts can be so significant that the classes render meaningless. The newer BCH method uses the weighted multiple group analysis, which prevents class shifting, and it performs well even when there is substantial variance in the auxiliary variable across classes, thus outperforming the other approaches such as the DCON command method (Bakk & Vermunt, 2014 ; Bray et al., 2014 ; Lanza et al., 2013 ). The main analyses of this study followed the steps described above. As for model fit indices, there is no consensus of the best criteria for class enumeration as classes are used to interpret results and make inferences (Nylund et al., 2007 ). The determination of the best fitting model in the first run is typically evaluated by a combination of criteria and interpretability of the classes (Lanza et al., 2003 ; Nylund et al., 2007 ; Porcu & Giambona, 2016 ). The most commonly used Information Criteria (ICs) include the Akaike IC (AIC), Bayesian IC (BIC), and sample-size adjusted-BIC (ABIC) (Nylund et al., 2007 ). Researchers generally recommend the use of the Loglikelihood, AIC, BIC, ABIC, the Lo-Mendell-Rubin (LMR) test using the TECH11 command, the bootstrapped parametric likelihood ratio test (BLRT) using the TECH14 command in Mplus, as well as Entropy when determining the number of classes (Asparouhov & Muthén, 2008 , 2012 ; Nylund et al., 2007 ). The posterior probabilities and class sizes were also examined to determine the distribution of profile membership. AIC, BIC, and ABIC guard against the model from overfitting the data by penalizing the model for the number of parameters estimated, and smaller numbers indicate better model fit (D'Unger et al., 1998 ). The LMR test and BLRT both test a k -1 versus k -class model, and significant p -values in these tests mean that the k -1 class model should be rejected in favor of the k -class model (Asparouhov & Muthén, 2012 ). Entropy is an indicator of classification certainty that ranges from zero to one, with values closer to one indicating higher certainty (Celeux & Soromenho, 1996 ). All described indicators were used to evaluate the model fit. Results Preliminary Results A series of correlation, t - and ANOVA tests demonstrated strong relations among most profile indicators and with treatment suicide-related outcome data. Race was the only non-clinical variable unrelated to other baseline and outcomes measures, thus it was excluded from subsequent analyses. Table 3 Proportions of Patients in Each Latent Profile and Model Fit Indices for One- to Six-Profile Models Profile 1 Profile 2 Profile 3 Profile 4 Profile 5 Profile 6 Proportion of individuals in each profile 2 0.56 0.44 3 0.26 0.40 0.34 4 0.26 0.26 0.31 0.17 5 0.25 0.27 0.26 0.20 0.02 6 0.16 0.20 0.25 0.22 0.15 0.03 Model fit indices Loglikelihood -7308 -6976.9 -6873.8 -6778.8 -6771.9 -6681.7 # free parameters 71 126 181 236 296 346 AIC 14758 14205.9 14109.7 14029.7 14135.8 14055.4 BIC 14979.8 14599.5 14675.1 14766.9 15060.4 15136.3 ABIC 14755 14200.5 14102.1 14019.7 14123.2 14040.8 LMR - 0.78 0.77 0.77 0.77 0.76 BLRT - 0 0 0 0 0 Entropy - 0.93 0.94 0.94 0.95 0.96 Note : Abbreviations: AIC, Akaike information criterion; BIC, Bayesian information criterion; BLRT, parametric bootstrapped likelihood ratio test; LMR, Lo-Mendell-Rubin-adjusted likelihood ratio test. The bolded numbers indicate the best fit indices across models. Latent Profile Model Comparisons Latent profile models with two to six profiles were then run and compared to determine the optimal number of typologies of patients who were suicidal based on the BIC, ABIC, LMR, and BLRT. As summarized in Table 3 (see above), the entropy values of all the models were high (entropy > .80 is considered as good). The LMR and BLRT failed to differentiate the fit among tested models. As for other indices, the two-profile model yielded the lowest BIC (which tends to underestimate the number of classes when the sample is small) and the four-profile model yielded the lowest AIC and ABIC. In addition, the Loglikelihoods of the models increased steadily from the one- to four-profile model, until it reached the five-profile model, suggesting that the four-profile model is a better fit than the two- and three-profile models. Increasing the number of profiles from four to five profiles did not significantly improve the model fit, and the fit increased again between the five- to six-profile model but the best loglikelihood of the six-profile model could not be replicated, meaning that the model is not trustworthy (Berlin, Williams, & Parra, 2014). The posterior probabilities were also high (> .90) across profiles. Characteristics of Profiles The profiles that ranked highest in each continuous indicator as well as significant pairwise comparisons between profiles on categorical indicators are presented visually in Figs. 1 and 2 and verbally as follows. Profile one was most likely to be classified as self-oriented and rated Stress level the highest. Compared to Profile two, Profile one was significantly less likely to have a history of suicidal behaviors, current intent, reported health problems, and met criteria for BPD. Compared to Profile three, Profile one was less likely to report being impulsive, feeling like a burden to others, experience shame, and have BPD. Compared to Profile four, Profile one was significantly more likely to be categorized as death-motivated, less likely to experience physical pain, and less likely to be male. Overall, Profile one was more likely to report higher stress levels, and experienced legal and sleep problems than the other three profiles. This can be described as an acute stress profile. Profile two rated highest in Psychological Pain, Agitation, Hopelessness, Self-Hate, self-rated SR, wish to die (WTD), Suicide Index Score (SIS), and clinician-rated SR from the SSF, as well as in SSI-C and BHS. Those classified in profile two also had the fewest reasons for living (RFL), the lowest rating for wish to live (WTL) and were most likely to be classified as death-motivated. Compared to Profile three, Profile two was significantly more likely to be death-motivated, less likely to have a suicide plan and access to means, less likely to report being impulsive, less likely to report relationship problems or feeling like a burden to others, and less likely to report feelings of shame. Compared to Profile four, Profile two was significantly more likely to be categorized as death-motivated, and less likely to be male. Overall, Profile two characterizes a group of individuals with a history of multiple suicide attempts, a high level of psychological pain, agitation, hopelessness, self-hate, low numbers of RFL, high numbers of RFD, weak WTL, strong WTD, were most likely to exhibit suicide preparatory behaviors, were high in current suicide intent, more likely to experience significant losses and health problems, and felt isolated. This can be described as the multiple attempts profile with high current SR. Profile three had the highest rating on suicidal thoughts and feelings related to self among the four profiles. Compared to Profile four, Profile three was more likely to be death-motivated, reported health and legal problems, and be female respondents. Overall, this group was the most likely to report that their suicidal thoughts and feelings are related to themselves, was more likely to have a suicide plan and access to means, describe themselves as impulsive, experience relationship problems, feel like a burden to others, feel shame, more likely to be female, least likely to be married, and most likely to meet criteria for BPD. This can be described as the female-BPD profile. Profile four had the highest rating for suicidal thoughts and feelings related to others among the four profiles. Overall, this profile was more likely than other profiles to report that they have substance abuse problem, experience physical pain, be male, and was least likely to meet criteria for BPD. This can be described as the male-externalizing profile. Treatment Outcomes No significant differences based on pairwise comparisons were found among profiles in terms of length of treatment and past week suicidal thoughts and feelings. Some outcome variables did not converge with the profiles at least partially because data source (i.e., covariate predictor variable) had an effect on the profiles and pattern of missing data. A closer look at the data revealed that data source indeed had a significantly relationship with Profile two (multiple attempts), X 2 (6, N = 168) = 40.71, p < .01, with those in the military sample (29 out of 86) being more likely to be in Profile two (multiple attempts) than those in the counseling center (2 out of 31). The influence of data source on profiles generated was controlled in the last step of the analyses when profiles were linked to treatment outcomes. Regarding rank order, those in Profile one (acute stress) were in treatment the longest, reported the highest level of Stress, and were most likely to report past week suicidal thoughts and feelings. Profile two (multiple attempts) had the highest level of Psychological Pain, Agitation, Hopelessness, Self-Hate, and clinician-rated SR at T2, but the lowest level of self-rated SR. Profile three (female-BPD) had the highest level of self-rated SR and lowest level of clinician-rated SR. Profile four (male-externalizing) had the shortest length of treatment, lowest levels of Psychological Pain, Stress, Agitation, Hopelessness, and Self-Hate at T2. Results of pairwise comparisons are presented in Table 4 (see next page). For categorical outcome variables excluded from the main analyses due to lack of data availability or significant floor effects, Chi-square tests revealed that only suicide attempt during the assessment period was significantly different across the four profiles, X 2 (3, N = 104) = 10.86, p = .01, with 5 out of 24 of those in Profile one (acute stress) having at least one attempt and 2 out of 36 of those in Profile two (multiple attempts) having at least one attempt during their treatment. Table 4 Means and Standard Errors of Treatment Outcome Variables for the Four Profiles Profile 1 2 3 4 Variables M S.E. M S.E. M S.E. M S.E. sig. pairs Length of treatment 1.832 0.093 1.651 0.087 1.719 0.088 1.467 0.101 n.s. T2 Psychological pain 1.912 0.187 2.191 0.209 2.124 0.19 1.577 0.205 1–4, 3–4, 2–4 T2 Stress 3.007 0.19 2.926 0.219 2.753 0.196 2.425 0.245 1–4. 2–4 T2 Agitation 2.192 0.213 2.575 0.239 2.23 0.177 2.073 0.236 1–3, 1–4 T2 Hopelessness 1.889 0.184 2.228 0.215 1.869 0.142 1.504 0.179 2–3 T2 Self-Hate 1.605 0.158 2.107 0.238 1.852 0.14 1.255 0.111 2–3 T2 Overall risk of suicide (patient-rated) 1.251 0.099 1.171 0.083 1.423 0.17 1.179 0.083 1–3, 1–4, 2–3, 2–4 T2 BHS 6.737 1.13 10.674 1.763 4.212 0.755 1.766 1.446 N/A SSI-C 1-mo 1.436 - 2.792 - 1.937 - 8.161 - N/A SSI-C 3-mo 2.531 0.975 7.667 1.817 2.655 1.579 2.342 1.171 N/A SR (clinician-rated) 0.172 0.066 0.225 0.073 0.113 0.049 0.12 0.068 1–4, 2–3, 3–4, 2–4 Past week suicidal t/f 0.348 0.095 0.246 0.094 0.288 0.103 0.188 0.088 n.s. Past week managed t/f - - - - - - - - N/A Continued outpatient therapy 0.857 0.068 0.851 0.072 0.915 0.061 0.909 0.063 N/A Mutual termination 0.071 0.05 0.231 0.084 0.043 0.044 0.045 0.046 N/A Patient discontinued unilaterally 0.096 0.054 0.034 0.039 0.191 0.078 -0.006 0.003 N/A Discussion Our findings support our first hypothesis that there are different subtypes of patients who are suicidal. Specifically, the four-profile model had a better model fit to the data and was able to capture more clinical nuances than the two-profile model; thus, the four-profile model was deemed superior overall. The four profiles generated can be characterized by the following: acute levels of stress with sleep and legal problems, history of multiple attempts and high baseline risk, BPD features and predominantly female, and externalizing profile and predominantly male. In terms of ranking, at treatment termination, the acute stress profile exhibited the highest stress score. The multiple attempts profile scored highest in all SSF Core Assessment items and clinician-rated suicide risk (SR), but lowest in self-rated SR. The female-BPD profile scored highest in self-rated SR and lowest in clinician-rated SR. The male-externalizing profile had the lowest scores in Core Assessment items and the shortest treatment length. Notably, there is also preliminary evidence suggesting that the acute stress profile (5 out of 24) and the multiple attempts profile (2 out of 36) had higher probabilities of attempting suicide during the study period than the male-externalizing and female-BPD profiles. Of note, data source had a significant effect on Profile two (i.e., multiple attempts profile), with those in the active-military sample having a significantly higher probability of being classified into this profile than those in the counseling center sample. Such an effect was controlled in the last of the main analyses in which profiles were linked to treatment outcomes. Clinical Implications These results are significant in several ways. First, this study provides empirical support for theories that argue for subtypes of suicidality and against a unified stress-diathesis model in predicting SR (Oquendo et al., 2014 ). For instance, the distinction between the acute stress profile and the female-BPD profile echoes previous findings that life events play a unique role in predicting suicidal behaviors among individuals who do not have BPD (Oquendo et al., 2014 ). Similarly, the results of this study conceptually replicated those of previous CAMS studies that identified an “acute” and a “chronic” group of patients who are suicidal (Conrad et al., 2009 ; Jobes et al., 1997 ), as well as studies that demonstrated how stress plays a distinct role in predicting SR (Brausch et al., 2020 ; Conrad et al., 2009 ). Findings regarding the heightened current risk of the multiple attempts profile also align well with Rudd’s ( 2006 ) “fluid vulnerability theory,” which postulates that individuals with a history of multiple suicide attempts may have an elevated baseline level of suicidality due to chronic risk factors both before and after the presence of acute stressors. This highlights the importance of assessing both acute and chronic risk when treating patients who are suicidal (Paris, 2002 ). There is also support for the construct of egosyntonic versus egodystonic (Schwartz et al., 1974 ) or intrapsychic versus interpsychic (Jobes, 1995 ) suicidality, both of which postulate that those whose suicidality is egosyntonic and self-oriented are more likely to experience chronic suicidality and less responsive to treatment. Our findings show that female-BPD profile had the highest score regarding suicidal thoughts and feelings related to self and the male-externalizing profile had the highest score regarding suicidal thoughts and feelings related to others, suggesting that individuals who are female and exhibit BPD symptoms may experience more chronic suicidality due to its egosyntonic nature, and that males who adapt through externalized symptoms may experience more egodystonic and more easily resolved suicidality. However, given that males have higher rates of dying by suicide than females (Curtin & Warner, 2016 ) and tend to use more lethal methods (Cibis et al., 2012 ), it would be important to explore whether such result is an indication of denial and lack of awareness of distress, genuinely resolved suicidality, or a reflection of sampling bias (e.g., that males are more likely to die by suicide before they seek care). This study also partially replicated previous findings that the suicidality of those who are more self-oriented responded to treatment to a lesser extent (Brancu et al., 2016 ), as the acute stress profile (that was most likely to be classified as self-oriented) were the most likely to have attempted suicide during the study period. Second, the results regarding the distinction between those with a history of multiple attempts and those who are high in BPD symptoms corroborate previous research demonstrating that history of multiple attempts is a distinct predictor of suicidality from BPD (Forman et al., 2004 ). Although chronic suicidality is a symptom of BPD (Lieb et al., 2004 ), the findings of this study suggest that it is important to not assume repeated suicide attempts as attention seeking behaviors or merely as a symptom of BPD (Aviram et al., 2006 ). This provides further support that the common perception of patients who are suicidal not having “real problems” (Pompili et al., 2005 ; Suominen et al., 2007 ) is presumptuous as history of multiple attempts is the most robust predictor of suicide deaths (Ribeiro et al., 2016). This is not to mention that individuals with BPD are also at increased risk of dying by suicide compared to the general population and that their SR should be addressed appropriately (Paris & Zweig-Frank, 2001 ). Third, this study highlights that gender, BPD, and externalizing symptoms can play a significant role in identifying different subtypes of patients who are suicidal. BPD is characterized by a pervasive pattern of unstable sense of self, relationships, impulsivity, and affect (Lieb et al., 2004 ), which corresponds with the characteristics of Profile three (female-BPD profile). This is likely a profile more effectively treated by Dialectical Behavior Therapy (Linehan et al., 2015 ). On the contrary, Profile four (male-externalizing profile) may be better candidates for CAMS as indicated by the relatively positive treatment outcomes of this group. This distinction also conceptually resembles the findings of Jobes et al.’s ( 2009 ) study, which showed that female patients were more likely to be classified as chronically suicidal (as defined by previous SAs, hospitalizations, and cluster B personality disorder) and have higher ratings of SR at admission than their male counterparts, who were more likely to be classified as acutely suicidal. Limitations and Future Directions This study provides strong evidence that clinically informative latent profiles can be generated through SSF data. However, there remains a number of limitations. First, findings regarding some treatment outcomes could not be converged with the profiles due to uneven distribution of sample across profiles, limited treatment outcome data, or floor effect, restricting our clinical understanding of such classifications. Future studies can focus on increasing the power and by standardizing the treatment outcome measures across studies. Second, the scope of this study also does not allow us to explore whether the differences in treatment outcomes across subtypes is specific to CAMS. Clinical trials that compare the effectiveness of two active interventions (e.g., Andreasson et al., 2014 ), or efficacy studies designed to mimic a stepped care approach (e.g., Pistorello et al., 2018 , 2021 ) would better inform decision making during the triage process. Third, having a relatively small sample size can lead to an under extraction of classes as they fail to capture the nuances in the data set (Dziak et al., 2014 ; Nylund et al., 2007 ). Although earlier research on LCA/LPA recommend using a minimum sample size of 300 to 500, subsequent research by Wurpts and Geiser ( 2014 ) shows a relatively clear limit of N = 70 being infeasible due to generation of uninterpretable profiles. Nonetheless, the number of profile indicators ( n = 42) and inclusion of a covariate may compensate for this potential problem (Wurpts & Geiser, 2014 ). In addition, the number of respondents statistically assigned to each profile were also relatively even across the four profiles, with high class certainty (as indicated by entropy), suggesting that these profiles are reliable. Lastly, the source of the data has a significant effect on one of the profiles (i.e., those from the active military sample were more likely to be classified into the multiple attempts profile than those from the counseling center sample). Replicating the profiles generated with a representative sample may clarify whether individuals in active military are more likely to have history of multiple suicide attempts compared to those in other clinical settings. Conclusions Through statistically generating clinically meaningful latent profiles based on CAMS treatment data, this study corroborates theories and adds to a growing body of research that supports the notion of suicide typologies. Findings of this study demonstrate that suicide risk is not a unidimensional construct, and that there are clusters of risk factors that may indicate differential prospective suicide risk. Due to the exploratory nature of this study and the low base rates of suicidal behaviors, we were unable to draw strong conclusions regarding which latent profile has the highest risk of attempting or dying by suicide. Quantitative results suggest that males with a more externalizing profile had the lowest risk at termination. Preliminary results (with a total of 7 attempts during the study periods) also show that those experiencing acute levels of stress were more likely to have attempted suicide during the study period, followed by those with a history of multiple attempts. Replications of these profiles and a better understanding of the trajectory of their corresponding suicide risk will help inform triage care. Declarations Competing Interests FundingDavid A. Jobes receives funding from the National Institute of Mental Health (NIMH), book royalties from Guilford Press, and is the founder and co-owner of CAMS-care, LLC (a professional training and consultation company). No additional funding was received for the preparation of this manuscript.Competing InterestsJosephine S. Au serves as a consultant and trainer for CAMS-care, LLC. The authors have no other relevant financial or non-financial interests to disclose. Author Contribution JSA: Conceptualization, Methodology, Software, Formal analysis, Writing – Original Draft, Visualization. KAD: Methodology, Software, Writing – Review & Editing and Supervision. DAJ: Writing – Review & Editing and Supervision. Acknowledgement Research assistants Thomas Ingram, Justin Thomas, and Kathleen Roszyk from the Suicide Prevention Lab (SPL) at The Catholic University of America helped with the coding of the Suicide Status Form. Dr. Katrina Rufino, Dr. Rene Lento, and Dr. Samantha Chalker were also vital in helping our research team access clinical trial data. Dr. Stephen O’Connor, who served on the first author’s dissertation committee, also contributed significantly to the project at earlier stages of the project. Data Availability The datasets generated and analyzed during the current study are not publicly available due to participant privacy and institutional restrictions. Reasonable requests for access to de-identified data may be directed to the corresponding author. References Andreasson, K., Krogh, J., Rosenbaum, B., Gluud, C., Jobes, D. A., & Nordentoft, M. (2014). The DiaS trial: Dialectical Behavior Therapy versus Collaborative Assessment and Management of Suicidality on self-harm in patients with a recent suicide attempt and borderline personality disorder traits - study protocol for a randomized controlled trial. Trials , 15 (1), 194. https://doi.org/10.1186/1745-6215-15-194 Asparouhov, T., & Muthén, B. (2008). Pearson and Log-likelihood Chi-square Test of Fit for Latent Class Analysis Estimated with Complex Samples. Retrieved from https://www.statmodel.com/download/Chi2Complex4.pdf Asparouhov, T., & Muthén, B. (2012). Using Mplus TECH11 and TECH14 to test the number of latent classes. Retrieved from http://www.statmodel.com/examples/webnotes/webnote14.pdf Asparouhov, T., & Muthén, B. (2018). Auxiliary variables in mixture modeling: Using the BCH method in Mplus to estimate a distal outcome model and an arbitrary secondary model. Retrieved from http://www.statmodel.com/examples/webnotes/webnote21.pdf Au, J. S., Martinez de Andino, A., Mekawi, Y., Silverstein, M. W., & Lamis, D. A. (2021). Latent class analysis of bipolar disorder symptoms and suicidal ideation and behaviors. Bipolar Disorders , 23 (2), 186–195. https://doi.org/10.1111/bdi.12967 Aviram, R. B., Brodsky, B. S., & Stanley, B. (2006). Borderline personality disorder, stigma, and treatment implications. Harvard Review of Psychiatry , 14 (5), 249–256. https://doi.org/10.1080/10673220600975121 Ayduk, O., Zayas, V., Downey, G., Cole, A. B., Shoda, Y., & Mischel, W. (2008). Rejection sensitivity and executive control: Joint predictors of borderline personality features. Journal of Research in Personality , 42 (1), 151–168. https://doi.org/10.1016/j.jrp.2007.04.002 Bakk, Z., & Vermunt, J. K. (2014). Robustness of stepwise latent class modeling with continuous distal outcomes. Forthcoming in Structural Equation Modeling: A Multidisciplinary Journal. http://members.home.nl/jeroenvermunt/bakk2014.pdf Beck, A. T., Brown, G. K., & Steer, R. A. (1997). Psychometric characteristics of the Scale for Suicide Ideation with psychiatric outpatients. Behaviour Research and Therapy , 35 (11), 1039–1046. https://doi.org/10.1016/S0005-7967(97)00073-9 Beck, A. T., Kovacs, M., & Weissman, A. (1979). Assessment of suicidal intention: The Scale for Suicide Ideation. Journal of Consulting and Clinical Psychology , 47 (2), 343–352. https://doi.org/10.1037/0022-006X.47.2.343 Beck, A. T., Weissman, A., Lester, D., & Trexler, L. (1974). The measurement of pessimism: The Hopelessness Scale. Journal of Consulting and Clinical Psychology , 42 (6), 861–865. https://doi.org/10.1037/h0037562 Bernanke, J. A., Stanley, B. H., & Oquendo, M. A. (2017a). Toward fine-grained phenotyping of suicidal behavior: The role of suicidal subtypes. Molecular Psychiatry , 22 (8), 1080–1081. https://doi.org/10.1038/mp.2017.123 Bernanke, J., Galfalvy, H. C., Mortali, M. G., Hoffman, L. A., Moutier, C., Nemeroff, C. B., & Oquendo, M. A. (2017b). Suicidal ideation and behavior in institutions of higher learning: A latent class analysis. Journal of Psychiatric Research , 95 , 253–259. https://doi.org/10.1016/j.jpsychires.2017.09.003 Betz, M. E., & Boudreaux, E. D. (2016). Managing suicidal patients in the emergency department. Annals of Emergency Medicine , 67 (2), 276–282. https://doi.org/10.1016/j.annemergmed.2015.09.001 Brancu, M., Jobes, D., Wagner, B. M., Greene, J. A., & Fratto, T. A. (2016). Are there linguistic markers of suicidal writing that can predict the course of treatment? A repeated measures longitudinal analysis. Archives of Suicide Research , 20 (3), 438–450. https://doi.org/10.1080/13811118.2015.1040935 Brausch, A. M., O'Connor, S. S., Powers, J. T., McClay, M. M., Gregory, J. A., & Jobes, D. A. (2020). Validating the suicide status form for the collaborative assessment and management of suicidality in a psychiatric adolescent sample. Suicide and Life-Threatening Behavior , 50 (1), 263–276. https://doi.org/10.1111/sltb.12587 Bray, B. C., Lanza, S. T., & Tan, X. (2014). Eliminating bias in classify-analyze approaches for latent class analysis. Forthcoming in Structural Equation Modeling: A Multidisciplinary Journal. http://dx.doi.org/10.1080/10705511.2014.935265 Cibis, A., Mergl, R., Bramesfeld, A., Althaus, D., Niklewski, G., Schmidtke, A., & Hegerl, U. (2012). Preference of lethal methods is not the only cause for higher suicide rates in males. Journal of Affective Disorders , 136 (1–2), 9–16. https://doi.org/10.1016/j.jad.2011.08.032 Celeux, G., & Soromenho, G. (1996). An entropy criterion for assessing the number of clusters in a mixture model. Journal of Classification , 13 (2), 195–212. https://doi.org/10.1007/BF01246098 Centers for Disease Control and Prevention (2025a, March 26). Suicide data and statistics. Retrieved from https://www.cdc.gov/suicide/facts/data.html Centers for Disease Control and Prevention (2025b, March 26). Facts About Suicide. Retrieved from https://www.cdc.gov/suicide/facts/index.html Comtois, K. A., Jobes, D. A., O’Connor, S., Atkins, S., Janis, D. C., Chessen, K. E., & Yuodelis-Flores, C., C (2011). Collaborative Assessment and Management of Suicidality (CAMS): Feasibility trial for next-day appointment services. Depression and Anxiety , 28 (11), 963–972. https://doi.org/10.1002/da.20895 Conrad, A. K., Jacoby, A. M., Jobes, D. A., Lineberry, T. W., Shea, C. E., Ewing, A., & Grenell, T. D., J. A (2009). A psychometric investigation of the Suicide Status Form II with a psychiatric inpatient sample. Suicide and Life-Threatening Behavior , 39 (3), 307–320. https://doi.org/10.1521/suli.2009.39.3.307 Corona, C. D., Ellis, T. E., & Jobes, D. A. (2018). Word count as an indicator of suicide risk in an inpatient setting. Bulletin of the Menninger Clinic , 82 (2), 115–135. https://doi.org/10.1521/bumc.2018.82.2.115 Curtin, S. C., & Warner, M. (2016). Suicide Rates for Females and Males by Race and Ethnicity: United States, 1999 and 2014. Retrieved from https://www.cdc.gov/nchs/data/hestat/suicide/rates_1999_2014.pdf D'Unger, A. V., Land, K. C., McCall, P. L., & Nagin, D. S. (1998). How many latent classes of delinquent/criminal careers? Results from mixed Poisson regression analyses. American Journal of Sociology , 103 (6), 1593–1630. Dayton, C. M., & Fox, J. (1998). Latent class scaling analysis (No. 126) . Sage. Dhingra, K., Boduszek, D., & Sharratt, K. (2016). Victimization profiles, non-suicidal self-injury, suicide attempt, and post-traumatic stress disorder symptomology. Journal of Interpersonal Violence , 31 (14), 2412–2429. https://doi.org/10.1177/0886260515576967 Dimeff, L. A., Jobes, D. A., Chalker, S. A., Piehl, B. M., Duvivier, L. L., Lok, B. C., & Koerner, K. (2018). A novel engagement of suicidality in the emergency department: Virtual Collaborative Assessment and Management of Suicidality. General Hospital Psychiatry. https://doi.org/10.1016/J.GENHOSPPSYCH.2018.05.005 DiStefano, C., & Kamphaus, R. W. (2006). Investigating subtypes of child development: A comparison of cluster analysis and latent class cluster analysis in typology creation. Educational and Psychological Measurement , 66 (5), 778–794. https://doi.org/10.1177/0013164405284033 Dziak, J. J., Lanza, S. T., & Tan, X. (2014). Effect size, statistical power and sample size requirements for the bootstrap likelihood ratio test in latent class analysis. Structural Equation Modeling: A Multidisciplinary Journal , 21 (4), 534–552. https://doi.org/10.1080/10705511.2014.919819 Ellis, T. E., Rufino, K. A., Allen, J. G., Fowler, J. C., & Jobes, D. A. (2015). Impact of a suicide-specific intervention within inpatient psychiatric care: The Collaborative Assessment and Management of Suicidality. Suicide and Life-Threatening Behavior , 45 (5), 556–566. https://doi.org/10.1111/sltb.12151 Engström, G., Alsén, M., Gustavsson, P., Schalling, D., & Träskman-Bendz, L. (1996). Classification of suicide attempters by cluster analysis: A study of the temperamental heterogeneity in suicidal patients. Personality and Individual Differences , 21 (5), 687–695. https://doi.org/10.1016/0191-8869(96)00102-X Everitt, B. S., & Hand, D. J. (1981). Finite Mixture Distributions. Monographs on Applied Probability and Statistics (Vol. 2). Springer Netherlands. https://doi.org/10.1007/978-94-009-5897-5 First, M. B. (1997). User’s guide for the structured clinical interview for DSM-IV Axis II personality disorders: SCID-II . American Psychiatric. Forman, E. M., Berk, M. S., Henriques, G. R., Brown, G. K., & Beck, A. T. (2004). History of multiple suicide attempts as a behavioral marker of severe psychopathology. The American Journal of Psychiatry, 1613(161), 437–443. Retrieved from http://ajp.psychiatryonline.org Fowler, J. C. (2012). Suicide risk assessment in clinical practice: Pragmatic guidelines for imperfect assessments. Psychotherapy. https://doi.org/10.1037/a0026148 Freitag, S., Au, J. S., Liu, D. Y., Mekawi, Y., & Lamis, D. A. (2023). Do bipolar disorder symptom profiles matter for suicide risk? A latent class approach to investigating differences in suicidal desire and acquired capability. Suicide and Life-Threatening Behavior , 54 (1), 24–37. https://doi.org/10.1111/sltb.13013 Franklin, J. C., Ribeiro, J. D., Fox, K. R., Bentley, K. H., Kleiman, E. M., Huang, X., & Nock, M. K. (2017). Risk factors for suicidal thoughts and behaviors: A meta-analysis of 50 years of research. Psychological Bulletin , 143 (2), 187. https://doi.org/10.1037/bul0000084 George, D., & Mallery, P. (2010). SPSS for Windows Step by Step: A Simple Guide and Reference 17.0 Update. 10th Edition, Pearson, Boston. Jobes, D. A. (1995). The challenge and the promise of clinical suicidology. Suicide and Life-Threatening Behavior , 25 (4), 437–449. https://doi.org/10.1111/J.1943-278X.1995.TB00237.X Jobes, D. A. (2023). Managing suicidal risk: A collaborative approach . Guilford. Jobes, D. A., Au, J. S., & Siegelman, A. (2015). Psychological approaches to suicide treatment and prevention. Current Treatment Options in Psychiatry , 2 (4), 363–370. Jobes, D. A., Comtois, K. A., Gutierrez, P. M., Brenner, L. A., Huh, D., Chalker, S. A., & Crow, B. (2017). A randomized controlled trial of the Collaborative Assessment and Management of Suicidality versus enhanced care as usual with suicidal Soldiers. Psychiatry , 80 (4), 339–356. https://doi.org/10.1080/00332747.2017.1354607 Jobes, D. A., Jacoby, A. M., Cimbolic, P., & Hustead, L. A. T. (1997). Assessment and treatment of suicidal clients in a university counseling center. Journal of Counseling Psychology , 44 (4), 368–377. https://doi.org/10.1037/0022-0167.44.4.368 Jobes, D. A., Kahn-Greene, E., Greene, J. A., & Goeke-Morey, M. (2009). Clinical improvements of suicidal outpatients: Examining suicide status form responses as predictors and moderators. Archives of Suicide Research , 13 (2), 147–159. Jobes, D. A., Nelson, K. N., Peterson, E. M., Pentiuc, D., Downing, V., Francini, K., & Kiernan, A. (2004). Describing suicidality: An investigation of qualitative SSF responses. Suicide and Life-Threatening Behavior , 34 (2), 99–112. https://doi.org/10.1521/suli.34.2.99.32788 Joiner, T. E., Walker, R. L., Rudd, M. D., & Jobes, D. A. (1999). Scientizing and routinizing the assessment of suicidality in outpatient practice. Professional Psychology: Research and Practice , 30 (5), 447–453. https://doi.org/10.1037/0735-7028.30.5.447 Klonsky, E. D., & Olino, T. M. (2008). Identifying clinically distinct subgroups of self-injurers among young adults: A latent class analysis. Journal of Consulting and Clinical Psychology , 76 (1), 22–27. https://doi.org/10.1037/0022-006X.76.1.22 Koerner, K., & Linehan, M. M. (2000). Research on dialectical behavior therapy for patients with borderline personality disorder. Psychiatric Clinics of North America , 23 (1), 151–167. Lanza, S. T., Flaherty, B. P., & Collins, L. M. (2003). Latent class and latent transition analysis. Handbook of Psychology (pp. 663–685). John Wiley & Sons, Inc. https://doi.org/10.1002/0471264385.wei0226 Lanza, S. T., Tan, X., & Bray, B. C. (2013). Latent class analysis with distal outcomes: A flexible model-based approach. Structural Equation Modeling , 20 , 1–26. Lento, R. M., Ellis, T. E., Hinnant, B. J., & Jobes, D. A. (2013). Using the Suicide Index Score to predict treatment outcomes among psychiatric inpatients. Suicide and Life-Threatening Behavior , 43 (5). https://doi.org/10.1111/sltb.12038 . n/a-n/a Lieb, K., Zanarini, M. C., Schmahl, C., Linehan, M. M., & Bohus, M. (2004). Borderline personality disorder. The Lancet , 364 (9432), 453–461. https://doi.org/10.1016/S0140-6736(04)16770-6 Linehan, M. M., Korslund, K. E., Harned, M. S., Gallop, R. J., Lungu, A., Neacsiu, A. D., & Murray-Gregory, A. M. (2015). Dialectical behavior therapy for high suicide risk in individuals with borderline personality disorder. JAMA Psychiatry , 72 (5), 475. https://doi.org/10.1001/jamapsychiatry.2014.3039 Logan, J., Hall, J., & Karch, D. (2011). Suicide categories by patterns of known risk factors: a latent class analysis. Archives of General Psychiatry , 68 (9), 935–941. https://doi.org/10.1001/archgenpsychiatry.2011.85 McCutcheon, A. L. (1987). Latent class analysis (p. 64). Sage. Morey, L. C. (1991). Personality Assessment Inventory: Professional Manual . Psychological Assessment Resources. Muthén, B. (2004). Latent variable analysis. The Sage handbook of quantitative methodology for the social sciences , 345 (368), 106–109. Muthén, B., & Muthén, L. K. (2000). Integrating person-centered and variable‐centered analyses: Growth mixture modeling with latent trajectory classes. Alcoholism: Clinical and experimental research , 24 (6), 882–891. Muthén, L. K., & Muthén, B. O. (2018). Mplus: Statistical Analysis with Latent Variables - User’s Guide. Retrieved from www.StatModel.com. National Institute of Mental Health (2023). Suicide Risk Screening Pathway in Emergency Department Chart Description. Retrieved from https://www.nimh.nih.gov/research/research-conducted-at-nimh/asq-toolkit-materials/youth-ed/suicide-risk-screening-pathway-emergency-department-chart-description Nylund, K. L., Asparouhov, T., & Muthén, B. O. (2007). Deciding on the number of classes in latent class analysis and growth mixture modeling: A Monte Carlo simulation study. Structural Equation Modeling , 14 (4), 535–569. https://doi.org/10.1080/10705510701575396 O’Connor, S. S., Jobes, D. A., Yeargin, M. K., FitzGerald, M. E., Rodríguez, V. M., Conrad, A. K., & Lineberry, T. W. (2012). A cross-sectional investigation of the suicidal spectrum: typologies of suicidality based on ambivalence about living and dying. Comprehensive Psychiatry , 53 (5), 461–467. https://doi.org/10.1016/j.comppsych.2011.09.007 Oquendo, M. A., & Bernanke, J. A. (2017). Suicide risk assessment: Tools and challenges. World Psychiatry , 16 (1), 28. Oquendo, M. A., Perez-Rodriguez, M. M., Poh, E., Sullivan, G., Burke, A. K., Sublette, M. E., & Galfalvy, H. (2014). Life events: a complex role in the timing of suicidal behavior among depressed patients. Molecular Psychiatry , 19 (8), 902–909. https://doi.org/10.1038/mp.2013.128 Paris, J. (2002). Chronic suicidality among patients with borderline personality disorder. Psychiatric Services , 53 (6), 738–742. https://doi.org/10.1176/appi.ps.53.6.738 Paris, J., & Zweig-Frank, H. (2001). A 27-year follow-up of patients with borderline personality disorder. Comprehensive Psychiatry , 42 (6), 482–487. https://doi.org/10.1053/comp.2001.26271 Pisani, A. R., Murrie, D. C., & Silverman, M. M. (2016). Reformulating suicide risk formulation: from prediction to prevention. Academic Psychiatry , 40 , 623–629. Pistorello, J., Jobes, D. A., Compton, S. N., Locey, N. S., Walloch, J. C., Gallop, R., & Goswami, S. (2018). Developing adaptive treatment strategies to address suicidal risk in college students: A pilot sequential, multiple assignment, randomized trial (SMART). Archives of Suicide Research , 22 (4), 644–664. https://doi.org/10.1080/13811118.2017.1392915 Pistorello, J., Jobes, D. A., Gallop, R., Compton, S. N., Locey, N. S., Au, J. S., & Jeffcoat, T. (2021). A randomized controlled trial of the collaborative assessment and management of suicidality (CAMS) versus treatment as usual (TAU) for suicidal college students. Archives of Suicide Research , 25 (4), 765–789. Pompili, M., Girardi, P., Ruberto, A., & Tatarelli, R. (2005). Suicide in the epilepsies: a meta-analytic investigation of 29 cohorts. Epilepsy & Behavior , 7 (2), 305–310. Porcu, M., & Giambona, F. (2016). Introduction to latent class analysis with applications. Journal of Early Adolescence , 37 (1), 129–158. https://doi.org/10.1177/0272431616648452 Rapeli, C. B., & Botega, N. J. (2005). Clinical profiles of serious suicide attempters consecutively admitted to a university-based hospital: a cluster analysis study. Revista Brasileira de Psiquiatria , 27 (4), 285–289. https://doi.org/10.1590/S1516-44462005000400006 Ross, E. L., Bossarte, R. M., Dobscha, S. K., Gildea, S. M., Hwang, I., Kennedy, C. J., & Kessler, R. C. (2023). Estimated average treatment effect of psychiatric hospitalization in patients with suicidal behaviors: a precision treatment analysis . JAMA Psychiatry. Rudd, M. D. (2006). Fluid vulnerability theory: A cognitive approach to understanding the process of acute and chronic suicide risk. Cognition and suicide: Theory, research, and therapy (pp. 355–368). American Psychological Association. Schwartz, D. A. (1979). The suicidal character. Psychiatric Quarterly , 51 (1), 64–70. https://doi.org/10.1007/BF01064720 Schwartz, D. A., Flinn, D. E., & Slawson, P. F. (1974). Treatment of the suicidal character. American Journal of Psychotherapy , 28 (2), 194–207. https://doi.org/10.1176/appi.psychotherapy.1974.28.2.194 Stone, D. M., Simon, T. R., Fowler, K. A., Kegler, S. R., Yuan, K., Holland, K. M., & Crosby, A. E. (2018). Vital signs: Trends in state suicide rates — United States, 1999–2016 and circumstances contributing to suicide — 27 States, 2015. Morbidity and Mortality Weekly Report , 67 (22), 617–624. https://doi.org/10.15585/mmwr.mm6722a1 Suominen, K., Suokas, J., & Lönnqvist, J. (2007). Attitudes of general hospital emergency room personnel towards attempted suicide patients. Nordic Journal of Psychiatry , 61 (5), 387–392. https://doi.org/10.1080/08039480701643381 Swift, J. K., Trusty, W. T., & Penix, E. A. (2021). The effectiveness of the Collaborative Assessment and Management Of Suicidality (CAMS) compared to alternative treatment conditions: A meta-analysis. Suicide and Life-Threatening Behavior , 51 (5), 882–896. Tairi, T., Milojev, P., & Zilikis, N. (2018). Clinical profiles among greek adolescent suicide attempters. Crisis , 39 , 1–9. https://doi.org/10.1027/0227-5910/a000506 Trull, T. J. (1995). Borderline personality disorder features in nonclinical young adults: Identification and validation. Psychological Assessment , 7 (1), 33–41. 10.1037/1040-3590.7.1.33 Tucker, R. P., Crowley, K. J., Davidson, C. L., & Gutierrez, P. M. (2015). Risk factors, warning signs, and drivers of suicide: What are they, how do they differ, and why does it matter? Suicide and Life-Threatening Behavior , 45 (6), 679–689. https://doi.org/10.1111/sltb.12161 Wurpts, I. C., & Geiser, C. (2014). Is adding more indicators to a latent class analysis beneficial or detrimental? Results of a Monte-Carlo study. Frontiers in Psychology , 5 , 920. https://doi.org/10.3389/fpsyg.2014.00920 Additional Declarations Competing interest reported. Funding David A. Jobes receives funding from the National Institute of Mental Health (NIMH), book royalties from Guilford Press, and is the founder and co-owner of CAMS-care, LLC (a professional training and consultation company). No additional funding was received for the preparation of this manuscript. Competing Interests Josephine S. Au serves as a consultant and trainer for CAMS-care, LLC. The authors have no other relevant financial or non-financial interests to disclose. Cite Share Download PDF Status: Published Journal Publication published 17 Oct, 2025 Read the published version in Journal of Contemporary Psychotherapy → Version 1 posted Editorial decision: Revision requested 17 Jun, 2025 Reviews received at journal 02 Jun, 2025 Reviewers agreed at journal 06 May, 2025 Reviewers invited by journal 06 May, 2025 Editor assigned by journal 03 May, 2025 Submission checks completed at journal 03 May, 2025 First submitted to journal 02 May, 2025 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-6581494","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":453994050,"identity":"948ee65c-4d0f-4d28-9c02-146ed0e4436e","order_by":0,"name":"Josephine Sheron Au","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA5UlEQVRIiWNgGAWjYBACxgYg8QHEkkASlcCqFkkL4wwggwesLIEILSDAzEOSFuYG5mfStjts8u2lmw9+/PnDJt+cgfngbR68DmMzk849k2bZI3MsWZonIc1yZwNbsjV+LQxALW2HDXgkcgykGRIOGxgc4DGTxq+F/Zu0JVhL/uefPxL+A7XwfyOgBWgmI8QWNgmehAMgW9jwa2nmKbbsbUsz4LmRZmbNk5ZsYHCYzdhyDh4thu3tG2/8bLMxYJ+R/PjmDxs7A4PjzQ9vvMGnpRlDiBmPchCQJyA/CkbBKBgFo4CBAQALjUGsp7LRtwAAAABJRU5ErkJggg==","orcid":"","institution":"Northeastern University","correspondingAuthor":true,"prefix":"","firstName":"Josephine","middleName":"Sheron","lastName":"Au","suffix":""},{"id":453994051,"identity":"55ee8f47-35ad-4797-9614-325a8dab5a00","order_by":1,"name":"David A. Jobes","email":"","orcid":"","institution":"Catholic University of America","correspondingAuthor":false,"prefix":"","firstName":"David","middleName":"A.","lastName":"Jobes","suffix":""},{"id":453994052,"identity":"2ed468ec-4dcb-4fe3-b4f5-b801b6e8d6f6","order_by":2,"name":"Kathryn A. Degnan","email":"","orcid":"","institution":"Catholic University of America","correspondingAuthor":false,"prefix":"","firstName":"Kathryn","middleName":"A.","lastName":"Degnan","suffix":""}],"badges":[],"createdAt":"2025-05-03 02:53:13","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6581494/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6581494/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1007/s10879-025-09691-9","type":"published","date":"2025-10-17T15:57:37+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":82580946,"identity":"18c5cf2c-86e0-4700-b06c-5380559e1c5c","added_by":"auto","created_at":"2025-05-13 06:37:08","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":40319,"visible":true,"origin":"","legend":"\u003cp\u003eMeans of continuous profile indicator variables for four-profile model.\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-6581494/v1/b1925d796dacaf5291a63226.png"},{"id":82580948,"identity":"40fe264e-af2d-450a-b54c-79363058f814","added_by":"auto","created_at":"2025-05-13 06:37:08","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":73514,"visible":true,"origin":"","legend":"\u003cp\u003eMeans of categorical profile indicator variables for four-profile model.\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-6581494/v1/6eb1ba7fe8507e101159ed10.png"},{"id":93955982,"identity":"1449e0a7-677d-40ba-8583-a1e188e0ebf4","added_by":"auto","created_at":"2025-10-20 16:08:49","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1354731,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6581494/v1/da952f13-9446-4e2d-b577-19d43183fb69.pdf"}],"financialInterests":"Competing interest reported. Funding\nDavid A. Jobes receives funding from the National Institute of Mental Health (NIMH), book royalties from Guilford Press, and is the founder and co-owner of CAMS-care, LLC (a professional training and consultation company). No additional funding was received for the preparation of this manuscript.\n\nCompeting Interests\nJosephine S. Au serves as a consultant and trainer for CAMS-care, LLC. The authors have no other relevant financial or non-financial interests to disclose.","formattedTitle":"Who Responds to CAMS? Latent Profiles of Patients Who Received the Collaborative Assessment and Management of Suicidality","fulltext":[{"header":"Introduction","content":"\u003cp\u003eSuicide continues to be a leading cause of death across age groups in the United States, with over 49,000 deaths reported in 2023\u0026mdash;equating to approximately one death every 11 minutes (Centers for Disease Control and Prevention [CDC], 2025a). This reflects a 36% increase in suicide rates between 2000 and 2022 (CDC, 2025b). Beyond fatalities, a significant number of individuals experience suicidal thoughts and behaviors. In 2022, approximately 12.8 million adults seriously considered suicide, 3.7 million made a suicide plan, and 1.5 million attempted suicides (CDC, 2024a). These figures underscore the broader and ongoing mental health crisis in the United States.\u003c/p\u003e\n\u003cp\u003eIn the face of a patient who screened positive for suicide risk (SR) and with the daunting number of over three thousand identified risk factors (Franklin et al., 2017), many clinicians are simply under-equipped to make decisions regarding treatment assignment and triage care. Although there are organizational guidelines that help with risk stratification (National Institute of Mental Health, 2023; SAMHSA, 2009) and models for risk assessment, SR assessment is still an \u0026ldquo;inexact science\u0026rdquo; that requires extensive evaluation of multiple contextual and personal factors (Betz \u0026amp; Boudreaux, 2016; Pisani et al., 2016).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eThe Case for Subtypes\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAlternatively, suicidologists have attempted to identify subtypes of individuals who engage in suicidal behaviors.\u0026nbsp;About four decades ago, Schwartz (1979) describes two types of patients who are suicidal: those whose suicidality is \u0026ldquo;ego-syntonic\u0026rdquo; (consistent with or in harmony with one\u0026rsquo;s self-image) versus those whose suicidality is \u0026ldquo;ego-dystonic\u0026rdquo; (in conflict or dissonance with one\u0026rsquo;s self-image). He and his colleagues argued that those whose suicidality is more egosyntonic, when compared to those whose suicidality is more ego-dystonic, are more likely to experience chronic suicidality, and that treatments should be adapted accordingly (Schwartz, 1979; Schwartz et al., 1974). These descriptions correspond with Rudd\u0026rsquo;s (2006) \u0026ldquo;fluid vulnerability theory,\u0026rdquo; which postulates suicidal mode is time-limited in nature. He also noted that certain individuals\u0026rsquo; suicidal mode is more easily triggered (e.g., among those with multiple previous attempts) than others\u0026rsquo; due to differences in physiological, affective, and behavioral deficits. This theoretical distinction is supported by subsequent treatment research that differentiates \u0026ldquo;acute resolvers\u0026rdquo; from \u0026ldquo;chronic non-resolvers\u0026rdquo; (Jobes et al., 1997), as well as neurobiological studies that separate a \u0026ldquo;stress-responsive\u0026rdquo; pattern of suicidal thoughts from a \u0026ldquo;non-stress-responsive\u0026rdquo; pattern, all of which show that suicide is an equifinal outcome from distinct pathological processes (Bernanke et al., 2017a). Such distinctions are consequential as certain interventions, such as hospitalization, may only benefit a subgroup of patients but iatrogenic for others (Koerner \u0026amp; Linehan, 2000; Ross et al., 2023; Ward-Ciesielski \u0026amp; Rizvi, 2020).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eLatent Class/Profile Analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTo this end, earlier studies often used cluster analysis to statistically categorize these individuals (Engstr\u0026ouml;m et al., 1996; Rapeli \u0026amp; Botega, 2005). More recent studies adopt latent class/profile analysis (LCA/LPA) to statistically generate and compare these clusters. LCA/LPA is now a popular method to identify these different clusters, all of which find at least two subtypes of individuals who are suicidal (Au et al., 2021; Bernanke et al., 2017b; Dhingra et al., 2016; Freitag et al., 2023; Klonsky \u0026amp; Olino, 2008; Logan et al., 2011; Tairi et al., 2018). For instance, one study identified that there are at least two sets of individuals who are at risk of SI, one group that experiences depressive symptoms that possibly drive their SI and another group that report feeling desperate, hopeless, and lonely, but not depressed (Bernanke et al., 2017b).\u003c/p\u003e\n\u003cp\u003eUnlike commonly used statistical methods that adopt a variable-centered approach (e.g., factor analysis, structural equation modeling, regression analysis), LPA adopts a person-centered lens that aims to classify individuals into unobserved subgroups that evidence less variability within the group than between groups (Muth\u0026eacute;n \u0026amp; Muth\u0026eacute;n, 2000). It relies on objective statistical models to estimate the probability of class membership instead of relying on an ad hoc algorithm that relies on subjective decisions (Everitt \u0026amp; Hand, 1981). Additionally, instead of strictly predicting the membership of an individual in a group, the flexibility of LPA allows for an estimation of the probability of such membership (DiStefano \u0026amp; Kamphaus, 2006). The maximum likelihood estimation procedure created latent classes based on calculations of model parameters that best explain the proposed relationships among the observed data, and individuals are assigned to the latent class for which they have the highest posterior probability of membership (Dayton, 1998; McCutcheon, 1987; Muth\u0026eacute;n, 2004).\u003c/p\u003e\n\u003cp\u003eThe fact that the studies consistently identify more than one class corroborates theories that emphasize the heterogeneity of suicidal experiences (Jobes, 1995; Rudd, 2006; Schwartz, 1979). However, depending on the variables, methods, and samples used in these studies, the subtypes generated can vary. In addition, no study to date has examined the treatment outcomes associated with these subtypes. \u0026nbsp;\u003c/p\u003e\n\u003cp id=\"_Toc1312025\"\u003e\u003cstrong\u003eThe Collaborative Assessment and Management of Suicidality (CAMS)\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;and the Suicide Status Form (SSF)\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eCAMS is one of the few evidence-based suicide-specific interventions with replicated findings on its effectiveness in reducing suicidal ideation (Jobes et al., 2023; Swift et al. 2021). It is a recommended clinical framework to assess and treat SR as it captures the idiosyncratic nature of suicide and is designed to avoid involuntary hospitalization that may exacerbate long-term risk of suicide or damage treatment alliance (Oquendo \u0026amp; Bernanke, 2017). CAMS has a strong focus on the collaboration between the therapist and patient in suicide assessment and treatment planning, as well as the identification and treatment of patient-identified \u0026quot;drivers\u0026quot; of suicide (Tucker et al., 2015). Each CAMS session includes sections of the session where the therapist and patient sit next to each other to complete the Suicide Status Form (SSF), which allows patients to describe their suicidality quantitatively and qualitatively.\u003c/p\u003e\n\u003cp\u003eThe SSF is a well-studied and validated multipurpose clinical assessment, treatment planning, risk tracking, and outcome evaluation clinical tool used in CAMS (Brancu et al., 2016; Conrad et al., 2009; Corona et al., 2018; Jobes et al., 2004; Lento et al., 2013; O\u0026rsquo;Connor et al., 2012; Romanowicz et al., 2013). Despite strong theoretical and empirical evidence supporting the use of the SSF, the different constructs assessed on the SSF are typically studied independently from each other. This can contribute to not-well-informed providers making clinical decisions based on estimates of interactions among these variables to predict SR \u0026ndash; a common problem faced by clinicians (Fowler, 2012). Therefore, it would be important to provide a concise heuristic to guide decision making (Joiner et al., 1999).\u003c/p\u003e\n\u003ch2 id=\"_Toc1312030\"\u003ePresent Study\u0026nbsp;\u003c/h2\u003e\n\u003cp\u003eThe present investigation used LPA to explore the psychometric properties and predictive validity of the initial session SSF to inform our understanding of the typologies of patients who present to a suicide-focused intervention. The goal of the study is to identify psychological profiles of patients in relation to treatment responses to CAMS in hopes of optimizing care with implications for triage and disposition. Based on previous research on the typologies of suicide, the following hypotheses were generated: (1) There would be more than one latent profile of patients who are suicidal. However, since no other study has attempted this approach with the SSF initial session data, the exact type and number of profiles is an exploratory question. (2) The generated latent profiles will show differential treatment outcomes. No specific hypotheses regarding the relationship between specific profiles and treatment outcomes were stipulated. Although this study focuses solely on the CAMS approach to assessing and treating SR, the findings regarding typologies of patients who were suicidal have implications for both triage and post treatment dispositional care.\u003c/p\u003e"},{"header":"Method","content":"\u003cp\u003eThis is a longitudinal exploratory study based on CAMS data collected from three different clinical trials. This retrospective archival study was approved by the Institutional Review Board of The Catholic University of America (18\u0026ndash;062).\u003c/p\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eSample\u003c/h2\u003e \u003cp\u003eParticipants of this study were drawn from three treatment studies on CAMS (\u003cem\u003eN\u0026thinsp;=\u003c/em\u003e\u0026thinsp;168), including individuals from an inpatient psychiatric sample (Ellis et al., 2012), an active-duty U.S Army Soldier sample (Jobes et al., \u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e2017\u003c/span\u003e), and a college counseling center student sample (Pistorello et al., \u003cspan citationid=\"CR70\" class=\"CitationRef\"\u003e2018\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe first sample included 51 patients who were suicidal and admitted to an inpatient psychiatric hospital in the South Central region of the U.S. and enrolled in three different adult treatment programs (Ellis et al., \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2015\u003c/span\u003e). The second sample included 86 active-duty U.S. Army Soldiers who were suicidal and received CAMS within a RCT funded by the Department of Defense (Jobes et al., \u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). These Soldiers were recruited from an infantry instillation and had a score of \u0026gt;\u0026thinsp;12 on the Beck Scale for Suicide Ideation \u0026ndash; Current (SSI-C; Beck et al., \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e1997\u003c/span\u003e; Comtois et al., \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2011\u003c/span\u003e). Over half of the sample, i.e., 50 (58.14%), had been deployed at least once. The third sample included 31 college students enrolled in a mid-sized public university in the intermountain west of the U.S. who presented to the university's counseling center with moderate to severe SR (Pistorello et al., \u003cspan citationid=\"CR70\" class=\"CitationRef\"\u003e2018\u003c/span\u003e, \u003cspan citationid=\"CR71\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Those who scored a 2 or above on the Counseling Center Assessment of Psychological Symptoms-34 (CCAPS-34) question, \u0026ldquo;I have thoughts of ending my life\u0026rdquo; (range is 0 \u003cem\u003e\u0026ldquo;not at all like me\u0026rdquo;\u003c/em\u003e to 4 \u003cem\u003e\u0026ldquo;extremely like me\u0026rdquo;\u003c/em\u003e) were recruited to participate. Demographic characteristics and history of suicide attempt of the three samples are summarized in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003e\u003cem\u003eDescriptive Statistics of Demographic Variables\u003c/em\u003e\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"8\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eDemographic variables\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eCategories\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003eInpatient\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e \u003cp\u003eMilitary\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c8\" namest=\"c7\"\u003e \u003cp\u003eCounseling Center\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003eM\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cem\u003eSD\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cem\u003eM\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cem\u003eSD\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cem\u003eM\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cem\u003eSD\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge at recruitment\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e31.13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e13.11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e26.77\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e6.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e19.48\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1.48\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003en\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cem\u003en\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cem\u003en\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGender\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e32\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e69.57\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e19.77\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e64.52\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRace\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eWhite/Caucasian\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e44\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e95.65\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e46\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e54.12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e51.61\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBlack/African\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e22.35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e6.45\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAsian\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e12.90\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMexican/Chicano\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2.35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePuerto Rican\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e9.41\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNative Hawaiian/other Pacific Islander\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMultiracial/other\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e7.06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e19.35\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEthnicity\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLatinx/Hispanic\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4.35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e15.48\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e9.68\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSingle\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e24.68\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMarried\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e17.39\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e39\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e46.99\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHave children\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e41\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e57.75\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHeterosexual\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e70\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e85.37\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e62.96\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEducation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSome high school\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.41\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHigh school diploma/GED\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e8.70\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e28.17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSome college\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e39.13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e42.25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTechnical/Associate degree\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e6.52\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e4.23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBachelor's degree\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e21.74\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e7.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMaster's degree\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e15.22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.41\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eProfessional degree\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e8.70\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.41\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eHistory of suicide attempt\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e23.91\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e40.54\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e61.29\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e26.09\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e35.14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e25.81\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026gt;\u0026thinsp;1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e50.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e24.32\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e12.90\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eMeasures\u003c/h3\u003e\n\u003cp\u003eProfile indicators and outcome measures are listed in Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e. Readers can refer to the SSF and related papers for more detailed information about related variables (see Lento et al., \u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e2013\u003c/span\u003e; Stone, 2011). Additional demographic variables and non-SSF psychological measures often included in CAMS studies, including the SSI-C (Beck et al., \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e1997\u003c/span\u003e, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e1979\u003c/span\u003e), the Beck Hopelessness Scale (BHS; Beck, et al., \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e1974\u003c/span\u003e) were also used. Not all data are available across the three samples but those measures that are available in at least two samples were included in the analyses.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003e\u003cem\u003eList of Profile Indicator and Outcome Variables\u003c/em\u003e\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eContinuous variables\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCategorical variables\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eDichotomous variables\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eProfile indicators\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e*Psychological pain\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eRace\u003csup\u003e+\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eSex\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e*Stress\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMotivation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eMarital status\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e*Agitation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eEducation level\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eSuicide plan\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e*Hopelessness\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eAttempt history type\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eAccess to means\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e*Self-Hate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSexual orientation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eSuicide preparation\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e*SR (patient-rated)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eSuicide rehearsal\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e*Suicidal t/f related to self\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eHistory of suicidal behaviors\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e*Suicidal t/f related to others\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eCurrent intent\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e*Number of RFL\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eImpulsivity\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e*Number of RFD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eSubstance abuse\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e*Wish to live\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eSignificant loss\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e*Wish to die\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eInterpersonal isolation\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e*SIS\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eRelationship problems\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e*SR (clinician-rated)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eBurden to others\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAge\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eHealth problems\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSSI-C\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003ePhysical pain\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBHS\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eLegal problems\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eShame\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eSleep problems\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eBPD\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOutcome\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLength of treatment\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e*SR (patient-rated)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e*Psychological pain\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e*Past week suicidal t/f\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e*Stress\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e*Past week managed t/f\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e*Agitation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e*Past week suicidal behavior\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e*Hopelessness\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e*Continued outpatient therapy\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e*Self-Hate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e*Mutual termination\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e*SR (clinician-rated)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e*Patient discontinued\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBHS\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eunilaterally\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSSI-C 1-mo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSSI-C 3-mo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"4\"\u003e*SSF variables\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003csup\u003e+\u003c/sup\u003eRace was excluded from LPA due to lack of strong relationships with other variables.\u003c/p\u003e \u003cp\u003eTwo of our three samples also included a measure of BPD. The military sample used the Structured Clinical Interview for DSM-IV Axis II BPD (First, \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e1997\u003c/span\u003e) after baseline assessment and within a month after treatment started (Jobes et al., \u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). The counseling center sample included a baseline measure of the Personality Assessment Inventory - Borderline Features scale (PAI-BOR; Morey, \u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e1991\u003c/span\u003e). Using the recommended cut off score of 38 in the counseling center sample (Ayduk et al., \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2008\u003c/span\u003e; Trull, \u003cspan citationid=\"CR83\" class=\"CitationRef\"\u003e1995\u003c/span\u003e) and the clinical diagnosis based on the SCID given in the military sample, respondents in these two samples were given a dichotomous coding of 0 or 1 to indicate the presence of BPD.\u003c/p\u003e \u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003eData Analyses\u003c/h2\u003e \u003cp\u003eAnalyses were conducted using Version 8.2 of \u003cem\u003eMplus\u003c/em\u003e (Muth\u0026eacute;n \u0026amp; Muth\u0026eacute;n, \u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e2018\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003ePreliminary Analyses\u003c/h2\u003e \u003cp\u003eThe distributions of the profile continuous variables were all within the acceptable range of skewness between \u0026minus;\u0026thinsp;2 and +\u0026thinsp;2 (George \u0026amp; Mallery, \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e2010\u003c/span\u003e). As for outcome continuous variables, the skewness of length of treatment, SSI-C at one-month, and patient-rated overall SR were outside of the acceptable range. The first two variables were log-transformed. However, self-rated SR at the end of treatment, which had a significant floor effect, was recoded into a binary variable (0\u0026thinsp;=\u0026thinsp;rating of 1; 1\u0026thinsp;=\u0026thinsp;rating\u0026thinsp;\u0026gt;\u0026thinsp;1). In addition, Pearson\u0026rsquo;s correlations, \u003cem\u003et\u003c/em\u003e-tests, and ANOVAs were run among all profile indicators and outcome variables to make sure that they are reasonably related before entering the LPA.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003eLatent Profile Analysis and BCH Method\u003c/h2\u003e \u003cp\u003eOften, latent categorical variables (C) are first generated based on a set of indicators (U) (Asparouhov \u0026amp; Muth\u0026eacute;n, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). After classes are generated, researchers are often interested in understanding the relationship between the classes and other auxiliary variables, such as observed predictor (X) and distal outcome (Y) variables. A common problem when auxiliary variables are included in the mixture model is that the forming of classes can be affected. Such shifts can be so significant that the classes render meaningless. The newer BCH method uses the weighted multiple group analysis, which prevents class shifting, and it performs well even when there is substantial variance in the auxiliary variable across classes, thus outperforming the other approaches such as the DCON command method (Bakk \u0026amp; Vermunt, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2014\u003c/span\u003e; Bray et al., \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2014\u003c/span\u003e; Lanza et al., \u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e2013\u003c/span\u003e). The main analyses of this study followed the steps described above.\u003c/p\u003e \u003cp\u003eAs for model fit indices, there is no consensus of the best criteria for class enumeration as classes are used to interpret results and make inferences (Nylund et al., \u003cspan citationid=\"CR63\" class=\"CitationRef\"\u003e2007\u003c/span\u003e). The determination of the best fitting model in the first run is typically evaluated by a combination of criteria and interpretability of the classes (Lanza et al., \u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e2003\u003c/span\u003e; Nylund et al., \u003cspan citationid=\"CR63\" class=\"CitationRef\"\u003e2007\u003c/span\u003e; Porcu \u0026amp; Giambona, \u003cspan citationid=\"CR73\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). The most commonly used Information Criteria (ICs) include the Akaike IC (AIC), Bayesian IC (BIC), and sample-size adjusted-BIC (ABIC) (Nylund et al., \u003cspan citationid=\"CR63\" class=\"CitationRef\"\u003e2007\u003c/span\u003e). Researchers generally recommend the use of the Loglikelihood, AIC, BIC, ABIC, the Lo-Mendell-Rubin (LMR) test using the TECH11 command, the bootstrapped parametric likelihood ratio test (BLRT) using the TECH14 command in Mplus, as well as Entropy when determining the number of classes (Asparouhov \u0026amp; Muth\u0026eacute;n, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2008\u003c/span\u003e, \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2012\u003c/span\u003e; Nylund et al., \u003cspan citationid=\"CR63\" class=\"CitationRef\"\u003e2007\u003c/span\u003e). The posterior probabilities and class sizes were also examined to determine the distribution of profile membership.\u003c/p\u003e \u003cp\u003eAIC, BIC, and ABIC guard against the model from overfitting the data by penalizing the model for the number of parameters estimated, and smaller numbers indicate better model fit (D'Unger et al., \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e1998\u003c/span\u003e). The LMR test and BLRT both test a \u003cem\u003ek\u003c/em\u003e-1 versus \u003cem\u003ek\u003c/em\u003e-class model, and significant \u003cem\u003ep\u003c/em\u003e-values in these tests mean that the \u003cem\u003ek\u003c/em\u003e-1 class model should be rejected in favor of the \u003cem\u003ek\u003c/em\u003e-class model (Asparouhov \u0026amp; Muth\u0026eacute;n, \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2012\u003c/span\u003e). Entropy is an indicator of classification certainty that ranges from zero to one, with values closer to one indicating higher certainty (Celeux \u0026amp; Soromenho, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e1996\u003c/span\u003e). All described indicators were used to evaluate the model fit.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003ePreliminary Results\u003c/h2\u003e \u003cp\u003eA series of correlation, \u003cem\u003et\u003c/em\u003e- and ANOVA tests demonstrated strong relations among most profile indicators and with treatment suicide-related outcome data. Race was the only non-clinical variable unrelated to other baseline and outcomes measures, thus it was excluded from subsequent analyses.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003e\u003cem\u003eProportions of Patients in Each Latent Profile and Model Fit Indices for One- to Six-Profile Models\u003c/em\u003e\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eProfile 1\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eProfile 2\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eProfile 3\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eProfile 4\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eProfile 5\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eProfile 6\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"4\" nameend=\"c4\" namest=\"c1\"\u003e \u003cp\u003eProportion of individuals in each profile\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.56\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.44\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.34\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.31\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.27\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.03\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eModel fit indices\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLoglikelihood\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-7308\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-6976.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-6873.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-6778.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-6771.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-6681.7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e# free parameters\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e71\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e126\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e181\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e236\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e296\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e346\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAIC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e14758\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e14205.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e14109.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e14029.7\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e14135.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e14055.4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBIC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e14979.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e14599.5\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e14675.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e14766.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e15060.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e15136.3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eABIC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e14755\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e14200.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e14102.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e14019.7\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e14123.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e14040.8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLMR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.78\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.77\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.77\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.77\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.76\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBLRT\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEntropy\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.93\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.94\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.94\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.95\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.96\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cem\u003eNote\u003c/em\u003e: Abbreviations: AIC, Akaike information criterion; BIC, Bayesian information criterion; BLRT, parametric bootstrapped likelihood ratio test; LMR, Lo-Mendell-Rubin-adjusted likelihood ratio test. The bolded numbers indicate the best fit indices across models.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec15\" class=\"Section2\"\u003e \u003ch2\u003eLatent Profile Model Comparisons\u003c/h2\u003e \u003cp\u003eLatent profile models with two to six profiles were then run and compared to determine the optimal number of typologies of patients who were suicidal based on the BIC, ABIC, LMR, and BLRT. As summarized in Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e (see above), the entropy values of all the models were high (entropy\u0026thinsp;\u0026gt;\u0026thinsp;.80 is considered as good). The LMR and BLRT failed to differentiate the fit among tested models. As for other indices, the two-profile model yielded the lowest BIC (which tends to underestimate the number of classes when the sample is small) and the four-profile model yielded the lowest AIC and ABIC. In addition, the Loglikelihoods of the models increased steadily from the one- to four-profile model, until it reached the five-profile model, suggesting that the four-profile model is a better fit than the two- and three-profile models. Increasing the number of profiles from four to five profiles did not significantly improve the model fit, and the fit increased again between the five- to six-profile model but the best loglikelihood of the six-profile model could not be replicated, meaning that the model is not trustworthy (Berlin, Williams, \u0026amp; Parra, 2014). The posterior probabilities were also high (\u0026gt;\u0026thinsp;.90) across profiles.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec16\" class=\"Section2\"\u003e \u003ch2\u003eCharacteristics of Profiles\u003c/h2\u003e \u003cp\u003eThe profiles that ranked highest in each continuous indicator as well as significant pairwise comparisons between profiles on categorical indicators are presented visually in Figs.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e and \u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e and verbally as follows.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eProfile one was most likely to be classified as self-oriented and rated Stress level the highest. Compared to Profile two, Profile one was significantly less likely to have a history of suicidal behaviors, current intent, reported health problems, and met criteria for BPD. Compared to Profile three, Profile one was less likely to report being impulsive, feeling like a burden to others, experience shame, and have BPD. Compared to Profile four, Profile one was significantly more likely to be categorized as death-motivated, less likely to experience physical pain, and less likely to be male. Overall, Profile one was more likely to report higher stress levels, and experienced legal and sleep problems than the other three profiles. This can be described as an \u003cem\u003eacute stress\u003c/em\u003e profile.\u003c/p\u003e \u003cp\u003eProfile two rated highest in Psychological Pain, Agitation, Hopelessness, Self-Hate, self-rated SR, wish to die (WTD), Suicide Index Score (SIS), and clinician-rated SR from the SSF, as well as in SSI-C and BHS. Those classified in profile two also had the fewest reasons for living (RFL), the lowest rating for wish to live (WTL) and were most likely to be classified as death-motivated. Compared to Profile three, Profile two was significantly more likely to be death-motivated, less likely to have a suicide plan and access to means, less likely to report being impulsive, less likely to report relationship problems or feeling like a burden to others, and less likely to report feelings of shame. Compared to Profile four, Profile two was significantly more likely to be categorized as death-motivated, and less likely to be male. Overall, Profile two characterizes a group of individuals with a history of multiple suicide attempts, a high level of psychological pain, agitation, hopelessness, self-hate, low numbers of RFL, high numbers of RFD, weak WTL, strong WTD, were most likely to exhibit suicide preparatory behaviors, were high in current suicide intent, more likely to experience significant losses and health problems, and felt isolated. This can be described as the \u003cem\u003emultiple attempts\u003c/em\u003e profile with high current SR.\u003c/p\u003e \u003cp\u003eProfile three had the highest rating on suicidal thoughts and feelings related to self among the four profiles. Compared to Profile four, Profile three was more likely to be death-motivated, reported health and legal problems, and be female respondents. Overall, this group was the most likely to report that their suicidal thoughts and feelings are related to themselves, was more likely to have a suicide plan and access to means, describe themselves as impulsive, experience relationship problems, feel like a burden to others, feel shame, more likely to be female, least likely to be married, and most likely to meet criteria for BPD. This can be described as the \u003cem\u003efemale-BPD\u003c/em\u003e profile.\u003c/p\u003e \u003cp\u003eProfile four had the highest rating for suicidal thoughts and feelings related to others among the four profiles. Overall, this profile was more likely than other profiles to report that they have substance abuse problem, experience physical pain, be male, and was least likely to meet criteria for BPD. This can be described as the \u003cem\u003emale-externalizing\u003c/em\u003e profile.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec17\" class=\"Section2\"\u003e \u003ch2\u003eTreatment Outcomes\u003c/h2\u003e \u003cp\u003eNo significant differences based on pairwise comparisons were found among profiles in terms of length of treatment and past week suicidal thoughts and feelings. Some outcome variables did not converge with the profiles at least partially because data source (i.e., covariate predictor variable) had an effect on the profiles and pattern of missing data. A closer look at the data revealed that data source indeed had a significantly relationship with Profile two (multiple attempts), \u003cem\u003eX\u003c/em\u003e\u003csup\u003e\u003cem\u003e2\u003c/em\u003e\u003c/sup\u003e (6, \u003cem\u003eN\u003c/em\u003e\u0026thinsp;=\u0026thinsp;168)\u0026thinsp;=\u0026thinsp;40.71, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;.01, with those in the military sample (29 out of 86) being more likely to be in Profile two (multiple attempts) than those in the counseling center (2 out of 31). The influence of data source on profiles generated was controlled in the last step of the analyses when profiles were linked to treatment outcomes.\u003c/p\u003e \u003cp\u003eRegarding rank order, those in Profile one (acute stress) were in treatment the longest, reported the highest level of Stress, and were most likely to report past week suicidal thoughts and feelings. Profile two (multiple attempts) had the highest level of Psychological Pain, Agitation, Hopelessness, Self-Hate, and clinician-rated SR at T2, but the lowest level of self-rated SR. Profile three (female-BPD) had the highest level of self-rated SR and lowest level of clinician-rated SR. Profile four (male-externalizing) had the shortest length of treatment, lowest levels of Psychological Pain, Stress, Agitation, Hopelessness, and Self-Hate at T2. Results of pairwise comparisons are presented in Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e (see next page).\u003c/p\u003e \u003cp\u003eFor categorical outcome variables excluded from the main analyses due to lack of data availability or significant floor effects, Chi-square tests revealed that only suicide attempt during the assessment period was significantly different across the four profiles, \u003cem\u003eX\u003c/em\u003e\u003csup\u003e\u003cem\u003e2\u003c/em\u003e\u003c/sup\u003e (3, \u003cem\u003eN\u003c/em\u003e\u0026thinsp;=\u0026thinsp;104)\u0026thinsp;=\u0026thinsp;10.86, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;.01, with 5 out of 24 of those in Profile one (acute stress) having at least one attempt and 2 out of 36 of those in Profile two (multiple attempts) having at least one attempt during their treatment.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003e\u003cem\u003eMeans and Standard Errors of Treatment Outcome Variables for the Four Profiles\u003c/em\u003e\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"10\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eProfile\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c9\" namest=\"c8\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariables\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eM\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003eS.E.\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cem\u003eM\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cem\u003eS.E.\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cem\u003eM\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cem\u003eS.E.\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cem\u003eM\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u003cem\u003eS.E.\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003esig. pairs\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLength of treatment\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.832\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.093\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.651\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.087\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.719\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.088\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1.467\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.101\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003en.s.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eT2 Psychological pain\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.912\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.187\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.191\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.209\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2.124\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1.577\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.205\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e1\u0026ndash;4, 3\u0026ndash;4, 2\u0026ndash;4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eT2 Stress\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3.007\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.926\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.219\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2.753\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.196\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e2.425\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.245\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e1\u0026ndash;4. 2\u0026ndash;4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eT2 Agitation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.192\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.213\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.575\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.239\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2.23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.177\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e2.073\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.236\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e1\u0026ndash;3, 1\u0026ndash;4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eT2 Hopelessness\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.889\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.184\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.228\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.215\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.869\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.142\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1.504\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.179\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e2\u0026ndash;3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eT2 Self-Hate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.605\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.158\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.107\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.238\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.852\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1.255\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.111\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e2\u0026ndash;3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eT2 Overall risk of suicide \u003c/p\u003e \u003cp\u003e(patient-rated)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.251\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.099\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.171\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.083\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.423\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1.179\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.083\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e1\u0026ndash;3, 1\u0026ndash;4, 2\u0026ndash;3, 2\u0026ndash;4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eT2 BHS\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6.737\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e10.674\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.763\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e4.212\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.755\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1.766\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e1.446\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003eN/A\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSSI-C 1-mo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.436\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.792\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.937\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e8.161\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u003cb\u003e-\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003eN/A\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSSI-C 3-mo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.531\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.975\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e7.667\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.817\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2.655\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1.579\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e2.342\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e1.171\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003eN/A\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSR (clinician-rated)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.172\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.066\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.225\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.073\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.113\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.049\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.068\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e1\u0026ndash;4, 2\u0026ndash;3, 3\u0026ndash;4, 2\u0026ndash;4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePast week suicidal t/f\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.348\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.095\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.246\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.094\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.288\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.103\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.188\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.088\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003en.s.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePast week managed t/f\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003eN/A\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eContinued outpatient therapy\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.857\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.068\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.851\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.072\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.915\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.061\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.909\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.063\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003eN/A\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMutual termination\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.071\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.231\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.084\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.043\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.044\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.045\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.046\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003eN/A\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePatient discontinued unilaterally\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.096\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.054\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.034\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.039\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.191\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.078\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e-0.006\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.003\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003eN/A\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eOur findings support our first hypothesis that there are different subtypes of patients who are suicidal. Specifically, the four-profile model had a better model fit to the data and was able to capture more clinical nuances than the two-profile model; thus, the four-profile model was deemed superior overall. The four profiles generated can be characterized by the following: acute levels of stress with sleep and legal problems, history of multiple attempts and high baseline risk, BPD features and predominantly female, and externalizing profile and predominantly male. In terms of ranking, at treatment termination, the acute stress profile exhibited the highest stress score. The multiple attempts profile scored highest in all SSF Core Assessment items and clinician-rated suicide risk (SR), but lowest in self-rated SR. The female-BPD profile scored highest in self-rated SR and lowest in clinician-rated SR. The male-externalizing profile had the lowest scores in Core Assessment items and the shortest treatment length. Notably, there is also preliminary evidence suggesting that the acute stress profile (5 out of 24) and the multiple attempts profile (2 out of 36) had higher probabilities of attempting suicide during the study period than the male-externalizing and female-BPD profiles.\u003c/p\u003e \u003cp\u003eOf note, data source had a significant effect on Profile two (i.e., multiple attempts profile), with those in the active-military sample having a significantly higher probability of being classified into this profile than those in the counseling center sample. Such an effect was controlled in the last of the main analyses in which profiles were linked to treatment outcomes.\u003c/p\u003e \u003cdiv id=\"Sec19\" class=\"Section2\"\u003e \u003ch2\u003eClinical Implications\u003c/h2\u003e \u003cp\u003eThese results are significant in several ways. First, this study provides empirical support for theories that argue for subtypes of suicidality and against a unified stress-diathesis model in predicting SR (Oquendo et al., \u003cspan citationid=\"CR66\" class=\"CitationRef\"\u003e2014\u003c/span\u003e). For instance, the distinction between the acute stress profile and the female-BPD profile echoes previous findings that life events play a unique role in predicting suicidal behaviors among individuals who do not have BPD (Oquendo et al., \u003cspan citationid=\"CR66\" class=\"CitationRef\"\u003e2014\u003c/span\u003e). Similarly, the results of this study conceptually replicated those of previous CAMS studies that identified an \u0026ldquo;acute\u0026rdquo; and a \u0026ldquo;chronic\u0026rdquo; group of patients who are suicidal (Conrad et al., \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2009\u003c/span\u003e; Jobes et al., \u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e1997\u003c/span\u003e), as well as studies that demonstrated how stress plays a distinct role in predicting SR (Brausch et al., \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Conrad et al., \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2009\u003c/span\u003e). Findings regarding the heightened current risk of the multiple attempts profile also align well with Rudd\u0026rsquo;s (\u003cspan citationid=\"CR76\" class=\"CitationRef\"\u003e2006\u003c/span\u003e) \u0026ldquo;fluid vulnerability theory,\u0026rdquo; which postulates that individuals with a history of multiple suicide attempts may have an elevated baseline level of suicidality due to chronic risk factors both before and after the presence of acute stressors. This highlights the importance of assessing both acute and chronic risk when treating patients who are suicidal (Paris, \u003cspan citationid=\"CR67\" class=\"CitationRef\"\u003e2002\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThere is also support for the construct of egosyntonic versus egodystonic (Schwartz et al., \u003cspan citationid=\"CR78\" class=\"CitationRef\"\u003e1974\u003c/span\u003e) or intrapsychic versus interpsychic (Jobes, \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e1995\u003c/span\u003e) suicidality, both of which postulate that those whose suicidality is egosyntonic and self-oriented are more likely to experience chronic suicidality and less responsive to treatment. Our findings show that female-BPD profile had the highest score regarding suicidal thoughts and feelings related to self and the male-externalizing profile had the highest score regarding suicidal thoughts and feelings related to others, suggesting that individuals who are female and exhibit BPD symptoms may experience more chronic suicidality due to its egosyntonic nature, and that males who adapt through externalized symptoms may experience more egodystonic and more easily resolved suicidality. However, given that males have higher rates of dying by suicide than females (Curtin \u0026amp; Warner, \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2016\u003c/span\u003e) and tend to use more lethal methods (Cibis et al., \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2012\u003c/span\u003e), it would be important to explore whether such result is an indication of denial and lack of awareness of distress, genuinely resolved suicidality, or a reflection of sampling bias (e.g., that males are more likely to die by suicide before they seek care). This study also partially replicated previous findings that the suicidality of those who are more self-oriented responded to treatment to a lesser extent (Brancu et al., \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2016\u003c/span\u003e), as the acute stress profile (that was most likely to be classified as self-oriented) were the most likely to have attempted suicide during the study period.\u003c/p\u003e \u003cp\u003eSecond, the results regarding the distinction between those with a history of multiple attempts and those who are high in BPD symptoms corroborate previous research demonstrating that history of multiple attempts is a distinct predictor of suicidality from BPD (Forman et al., \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e2004\u003c/span\u003e). Although chronic suicidality is a symptom of BPD (Lieb et al., \u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e2004\u003c/span\u003e), the findings of this study suggest that it is important to not assume repeated suicide attempts as attention seeking behaviors or merely as a symptom of BPD (Aviram et al., \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2006\u003c/span\u003e). This provides further support that the common perception of patients who are suicidal not having \u0026ldquo;real problems\u0026rdquo; (Pompili et al., \u003cspan citationid=\"CR72\" class=\"CitationRef\"\u003e2005\u003c/span\u003e; Suominen et al., \u003cspan citationid=\"CR80\" class=\"CitationRef\"\u003e2007\u003c/span\u003e) is presumptuous as history of multiple attempts is the most robust predictor of suicide deaths (Ribeiro et al., 2016). This is not to mention that individuals with BPD are also at increased risk of dying by suicide compared to the general population and that their SR should be addressed appropriately (Paris \u0026amp; Zweig-Frank, \u003cspan citationid=\"CR68\" class=\"CitationRef\"\u003e2001\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThird, this study highlights that gender, BPD, and externalizing symptoms can play a significant role in identifying different subtypes of patients who are suicidal. BPD is characterized by a pervasive pattern of unstable sense of self, relationships, impulsivity, and affect (Lieb et al., \u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e2004\u003c/span\u003e), which corresponds with the characteristics of Profile three (female-BPD profile). This is likely a profile more effectively treated by Dialectical Behavior Therapy (Linehan et al., \u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e2015\u003c/span\u003e). On the contrary, Profile four (male-externalizing profile) may be better candidates for CAMS as indicated by the relatively positive treatment outcomes of this group. This distinction also conceptually resembles the findings of Jobes et al.\u0026rsquo;s (\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e2009\u003c/span\u003e) study, which showed that female patients were more likely to be classified as chronically suicidal (as defined by previous SAs, hospitalizations, and cluster B personality disorder) and have higher ratings of SR at admission than their male counterparts, who were more likely to be classified as acutely suicidal.\u003c/p\u003e \u003cdiv id=\"Sec20\" class=\"Section3\"\u003e \u003ch2\u003eLimitations and Future Directions\u003c/h2\u003e \u003cp\u003eThis study provides strong evidence that clinically informative latent profiles can be generated through SSF data. However, there remains a number of limitations. First, findings regarding some treatment outcomes could not be converged with the profiles due to uneven distribution of sample across profiles, limited treatment outcome data, or floor effect, restricting our clinical understanding of such classifications. Future studies can focus on increasing the power and by standardizing the treatment outcome measures across studies. Second, the scope of this study also does not allow us to explore whether the differences in treatment outcomes across subtypes is specific to CAMS. Clinical trials that compare the effectiveness of two active interventions (e.g., Andreasson et al., \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2014\u003c/span\u003e), or efficacy studies designed to mimic a stepped care approach (e.g., Pistorello et al., \u003cspan citationid=\"CR70\" class=\"CitationRef\"\u003e2018\u003c/span\u003e, \u003cspan citationid=\"CR71\" class=\"CitationRef\"\u003e2021\u003c/span\u003e) would better inform decision making during the triage process.\u003c/p\u003e \u003cp\u003eThird, having a relatively small sample size can lead to an under extraction of classes as they fail to capture the nuances in the data set (Dziak et al., \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2014\u003c/span\u003e; Nylund et al., \u003cspan citationid=\"CR63\" class=\"CitationRef\"\u003e2007\u003c/span\u003e). Although earlier research on LCA/LPA recommend using a minimum sample size of 300 to 500, subsequent research by Wurpts and Geiser (\u003cspan citationid=\"CR85\" class=\"CitationRef\"\u003e2014\u003c/span\u003e) shows a relatively clear limit of \u003cem\u003eN\u003c/em\u003e\u0026thinsp;=\u0026thinsp;70 being infeasible due to generation of uninterpretable profiles. Nonetheless, the number of profile indicators (\u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;42) and inclusion of a covariate may compensate for this potential problem (Wurpts \u0026amp; Geiser, \u003cspan citationid=\"CR85\" class=\"CitationRef\"\u003e2014\u003c/span\u003e). In addition, the number of respondents statistically assigned to each profile were also relatively even across the four profiles, with high class certainty (as indicated by entropy), suggesting that these profiles are reliable.\u003c/p\u003e \u003cp\u003eLastly, the source of the data has a significant effect on one of the profiles (i.e., those from the active military sample were more likely to be classified into the multiple attempts profile than those from the counseling center sample). Replicating the profiles generated with a representative sample may clarify whether individuals in active military are more likely to have history of multiple suicide attempts compared to those in other clinical settings.\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e"},{"header":"Conclusions","content":"\u003cp\u003eThrough statistically generating clinically meaningful latent profiles based on CAMS treatment data, this study corroborates theories and adds to a growing body of research that supports the notion of suicide typologies. Findings of this study demonstrate that suicide risk is not a unidimensional construct, and that there are clusters of risk factors that may indicate differential prospective suicide risk.\u003c/p\u003e \u003cp\u003eDue to the exploratory nature of this study and the low base rates of suicidal behaviors, we were unable to draw strong conclusions regarding which latent profile has the highest risk of attempting or dying by suicide. Quantitative results suggest that males with a more externalizing profile had the lowest risk at termination. Preliminary results (with a total of 7 attempts during the study periods) also show that those experiencing acute levels of stress were more likely to have attempted suicide during the study period, followed by those with a history of multiple attempts. Replications of these profiles and a better understanding of the trajectory of their corresponding suicide risk will help inform triage care.\u003c/p\u003e"},{"header":"Declarations","content":"\u003ch2\u003eCompeting Interests\u003c/h2\u003e\u003cp\u003eFundingDavid A. Jobes receives funding from the National Institute of Mental Health (NIMH), book royalties from Guilford Press, and is the founder and co-owner of CAMS-care, LLC (a professional training and consultation company). No additional funding was received for the preparation of this manuscript.Competing InterestsJosephine S. Au serves as a consultant and trainer for CAMS-care, LLC. The authors have no other relevant financial or non-financial interests to disclose.\u003c/p\u003e\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eJSA: Conceptualization, Methodology, Software, Formal analysis, Writing \u0026ndash; Original Draft, Visualization. KAD: Methodology, Software, Writing \u0026ndash; Review \u0026amp; Editing and Supervision. DAJ: Writing \u0026ndash; Review \u0026amp; Editing and Supervision.\u003c/p\u003e\u003ch2\u003eAcknowledgement\u003c/h2\u003e\u003cp\u003eResearch assistants Thomas Ingram, Justin Thomas, and Kathleen Roszyk from the Suicide Prevention Lab (SPL) at The Catholic University of America helped with the coding of the Suicide Status Form. Dr. Katrina Rufino, Dr. Rene Lento, and Dr. Samantha Chalker were also vital in helping our research team access clinical trial data. Dr. Stephen O\u0026rsquo;Connor, who served on the first author\u0026rsquo;s dissertation committee, also contributed significantly to the project at earlier stages of the project.\u003c/p\u003e\u003ch2\u003eData Availability\u003c/h2\u003e\u003cp\u003eThe datasets generated and analyzed during the current study are not publicly available due to participant privacy and institutional restrictions. Reasonable requests for access to de-identified data may be directed to the corresponding author.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eAndreasson, K., Krogh, J., Rosenbaum, B., Gluud, C., Jobes, D. A., \u0026amp; Nordentoft, M. (2014). The DiaS trial: Dialectical Behavior Therapy versus Collaborative Assessment and Management of Suicidality on self-harm in patients with a recent suicide attempt and borderline personality disorder traits - study protocol for a randomized controlled trial. \u003cem\u003eTrials\u003c/em\u003e, \u003cem\u003e15\u003c/em\u003e(1), 194. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1186/1745-6215-15-194\u003c/span\u003e\u003cspan address=\"10.1186/1745-6215-15-194\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAsparouhov, T., \u0026amp; Muth\u0026eacute;n, B. (2008). Pearson and Log-likelihood Chi-square Test of Fit for Latent Class Analysis Estimated with Complex Samples. Retrieved from \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.statmodel.com/download/Chi2Complex4.pdf\u003c/span\u003e\u003cspan address=\"https://www.statmodel.com/download/Chi2Complex4.pdf\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAsparouhov, T., \u0026amp; Muth\u0026eacute;n, B. (2012). Using Mplus TECH11 and TECH14 to test the number of latent classes. Retrieved from \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://www.statmodel.com/examples/webnotes/webnote14.pdf\u003c/span\u003e\u003cspan address=\"http://www.statmodel.com/examples/webnotes/webnote14.pdf\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAsparouhov, T., \u0026amp; Muth\u0026eacute;n, B. (2018). Auxiliary variables in mixture modeling: Using the BCH method in Mplus to estimate a distal outcome model and an arbitrary secondary model. Retrieved from \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://www.statmodel.com/examples/webnotes/webnote21.pdf\u003c/span\u003e\u003cspan address=\"http://www.statmodel.com/examples/webnotes/webnote21.pdf\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAu, J. S., Martinez de Andino, A., Mekawi, Y., Silverstein, M. W., \u0026amp; Lamis, D. A. (2021). Latent class analysis of bipolar disorder symptoms and suicidal ideation and behaviors. \u003cem\u003eBipolar Disorders\u003c/em\u003e, \u003cem\u003e23\u003c/em\u003e(2), 186\u0026ndash;195. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1111/bdi.12967\u003c/span\u003e\u003cspan address=\"10.1111/bdi.12967\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAviram, R. B., Brodsky, B. S., \u0026amp; Stanley, B. (2006). Borderline personality disorder, stigma, and treatment implications. \u003cem\u003eHarvard Review of Psychiatry\u003c/em\u003e, \u003cem\u003e14\u003c/em\u003e(5), 249\u0026ndash;256. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1080/10673220600975121\u003c/span\u003e\u003cspan address=\"10.1080/10673220600975121\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAyduk, O., Zayas, V., Downey, G., Cole, A. B., Shoda, Y., \u0026amp; Mischel, W. (2008). Rejection sensitivity and executive control: Joint predictors of borderline personality features. \u003cem\u003eJournal of Research in Personality\u003c/em\u003e, \u003cem\u003e42\u003c/em\u003e(1), 151\u0026ndash;168. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.jrp.2007.04.002\u003c/span\u003e\u003cspan address=\"10.1016/j.jrp.2007.04.002\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBakk, Z., \u0026amp; Vermunt, J. K. (2014). Robustness of stepwise latent class modeling with continuous distal outcomes. Forthcoming in Structural Equation Modeling: A Multidisciplinary Journal. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://members.home.nl/jeroenvermunt/bakk2014.pdf\u003c/span\u003e\u003cspan address=\"http://members.home.nl/jeroenvermunt/bakk2014.pdf\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBeck, A. T., Brown, G. K., \u0026amp; Steer, R. A. (1997). Psychometric characteristics of the Scale for Suicide Ideation with psychiatric outpatients. \u003cem\u003eBehaviour Research and Therapy\u003c/em\u003e, \u003cem\u003e35\u003c/em\u003e(11), 1039\u0026ndash;1046. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/S0005-7967(97)00073-9\u003c/span\u003e\u003cspan address=\"10.1016/S0005-7967(97)00073-9\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBeck, A. T., Kovacs, M., \u0026amp; Weissman, A. (1979). Assessment of suicidal intention: The Scale for Suicide Ideation. \u003cem\u003eJournal of Consulting and Clinical Psychology\u003c/em\u003e, \u003cem\u003e47\u003c/em\u003e(2), 343\u0026ndash;352. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1037/0022-006X.47.2.343\u003c/span\u003e\u003cspan address=\"10.1037/0022-006X.47.2.343\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBeck, A. T., Weissman, A., Lester, D., \u0026amp; Trexler, L. (1974). The measurement of pessimism: The Hopelessness Scale. \u003cem\u003eJournal of Consulting and Clinical Psychology\u003c/em\u003e, \u003cem\u003e42\u003c/em\u003e(6), 861\u0026ndash;865. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1037/h0037562\u003c/span\u003e\u003cspan address=\"10.1037/h0037562\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBernanke, J. A., Stanley, B. H., \u0026amp; Oquendo, M. A. (2017a). Toward fine-grained phenotyping of suicidal behavior: The role of suicidal subtypes. \u003cem\u003eMolecular Psychiatry\u003c/em\u003e, \u003cem\u003e22\u003c/em\u003e(8), 1080\u0026ndash;1081. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1038/mp.2017.123\u003c/span\u003e\u003cspan address=\"10.1038/mp.2017.123\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBernanke, J., Galfalvy, H. C., Mortali, M. G., Hoffman, L. A., Moutier, C., Nemeroff, C. B., \u0026amp; Oquendo, M. A. (2017b). Suicidal ideation and behavior in institutions of higher learning: A latent class analysis. \u003cem\u003eJournal of Psychiatric Research\u003c/em\u003e, \u003cem\u003e95\u003c/em\u003e, 253\u0026ndash;259. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.jpsychires.2017.09.003\u003c/span\u003e\u003cspan address=\"10.1016/j.jpsychires.2017.09.003\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBetz, M. E., \u0026amp; Boudreaux, E. D. (2016). Managing suicidal patients in the emergency department. \u003cem\u003eAnnals of Emergency Medicine\u003c/em\u003e, \u003cem\u003e67\u003c/em\u003e(2), 276\u0026ndash;282. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.annemergmed.2015.09.001\u003c/span\u003e\u003cspan address=\"10.1016/j.annemergmed.2015.09.001\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBrancu, M., Jobes, D., Wagner, B. M., Greene, J. A., \u0026amp; Fratto, T. A. (2016). Are there linguistic markers of suicidal writing that can predict the course of treatment? A repeated measures longitudinal analysis. \u003cem\u003eArchives of Suicide Research\u003c/em\u003e, \u003cem\u003e20\u003c/em\u003e(3), 438\u0026ndash;450. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1080/13811118.2015.1040935\u003c/span\u003e\u003cspan address=\"10.1080/13811118.2015.1040935\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBrausch, A. M., O'Connor, S. S., Powers, J. T., McClay, M. M., Gregory, J. A., \u0026amp; Jobes, D. A. (2020). Validating the suicide status form for the collaborative assessment and management of suicidality in a psychiatric adolescent sample. \u003cem\u003eSuicide and Life-Threatening Behavior\u003c/em\u003e, \u003cem\u003e50\u003c/em\u003e(1), 263\u0026ndash;276. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1111/sltb.12587\u003c/span\u003e\u003cspan address=\"10.1111/sltb.12587\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBray, B. C., Lanza, S. T., \u0026amp; Tan, X. (2014). Eliminating bias in classify-analyze approaches for latent class analysis. Forthcoming in Structural Equation Modeling: A Multidisciplinary Journal. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://dx.doi.org/10.1080/10705511.2014.935265\u003c/span\u003e\u003cspan address=\"10.1080/10705511.2014.935265\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCibis, A., Mergl, R., Bramesfeld, A., Althaus, D., Niklewski, G., Schmidtke, A., \u0026amp; Hegerl, U. (2012). Preference of lethal methods is not the only cause for higher suicide rates in males. \u003cem\u003eJournal of Affective Disorders\u003c/em\u003e, \u003cem\u003e136\u003c/em\u003e(1\u0026ndash;2), 9\u0026ndash;16. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.jad.2011.08.032\u003c/span\u003e\u003cspan address=\"10.1016/j.jad.2011.08.032\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCeleux, G., \u0026amp; Soromenho, G. (1996). An entropy criterion for assessing the number of clusters in a mixture model. \u003cem\u003eJournal of Classification\u003c/em\u003e, \u003cem\u003e13\u003c/em\u003e(2), 195\u0026ndash;212. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1007/BF01246098\u003c/span\u003e\u003cspan address=\"10.1007/BF01246098\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCenters for Disease Control and Prevention (2025a, March 26). Suicide data and statistics. Retrieved from \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.cdc.gov/suicide/facts/data.html\u003c/span\u003e\u003cspan address=\"https://www.cdc.gov/suicide/facts/data.html\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCenters for Disease Control and Prevention (2025b, March 26). Facts About Suicide. Retrieved from \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.cdc.gov/suicide/facts/index.html\u003c/span\u003e\u003cspan address=\"https://www.cdc.gov/suicide/facts/index.html\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eComtois, K. A., Jobes, D. A., O\u0026rsquo;Connor, S., Atkins, S., Janis, D. C., Chessen, K. E., \u0026amp; Yuodelis-Flores, C., C (2011). Collaborative Assessment and Management of Suicidality (CAMS): Feasibility trial for next-day appointment services. \u003cem\u003eDepression and Anxiety\u003c/em\u003e, \u003cem\u003e28\u003c/em\u003e(11), 963\u0026ndash;972. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1002/da.20895\u003c/span\u003e\u003cspan address=\"10.1002/da.20895\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eConrad, A. K., Jacoby, A. M., Jobes, D. A., Lineberry, T. W., Shea, C. E., Ewing, A., \u0026amp; Grenell, T. D., J. A (2009). A psychometric investigation of the Suicide Status Form II with a psychiatric inpatient sample. \u003cem\u003eSuicide and Life-Threatening Behavior\u003c/em\u003e, \u003cem\u003e39\u003c/em\u003e(3), 307\u0026ndash;320. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1521/suli.2009.39.3.307\u003c/span\u003e\u003cspan address=\"10.1521/suli.2009.39.3.307\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCorona, C. D., Ellis, T. E., \u0026amp; Jobes, D. A. (2018). Word count as an indicator of suicide risk in an inpatient setting. \u003cem\u003eBulletin of the Menninger Clinic\u003c/em\u003e, \u003cem\u003e82\u003c/em\u003e(2), 115\u0026ndash;135. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1521/bumc.2018.82.2.115\u003c/span\u003e\u003cspan address=\"10.1521/bumc.2018.82.2.115\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCurtin, S. C., \u0026amp; Warner, M. (2016). Suicide Rates for Females and Males by Race and Ethnicity: United States, 1999 and 2014. Retrieved from \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.cdc.gov/nchs/data/hestat/suicide/rates_1999_2014.pdf\u003c/span\u003e\u003cspan address=\"https://www.cdc.gov/nchs/data/hestat/suicide/rates_1999_2014.pdf\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eD'Unger, A. V., Land, K. C., McCall, P. L., \u0026amp; Nagin, D. S. (1998). How many latent classes of delinquent/criminal careers? Results from mixed Poisson regression analyses. \u003cem\u003eAmerican Journal of Sociology\u003c/em\u003e, \u003cem\u003e103\u003c/em\u003e(6), 1593\u0026ndash;1630.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDayton, C. M., \u0026amp; Fox, J. (1998). \u003cem\u003eLatent class scaling analysis (No. 126)\u003c/em\u003e. Sage.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDhingra, K., Boduszek, D., \u0026amp; Sharratt, K. (2016). Victimization profiles, non-suicidal self-injury, suicide attempt, and post-traumatic stress disorder symptomology. \u003cem\u003eJournal of Interpersonal Violence\u003c/em\u003e, \u003cem\u003e31\u003c/em\u003e(14), 2412\u0026ndash;2429. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1177/0886260515576967\u003c/span\u003e\u003cspan address=\"10.1177/0886260515576967\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDimeff, L. A., Jobes, D. A., Chalker, S. A., Piehl, B. M., Duvivier, L. L., Lok, B. C., \u0026amp; Koerner, K. (2018). A novel engagement of suicidality in the emergency department: Virtual Collaborative Assessment and Management of Suicidality. General Hospital Psychiatry. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/J.GENHOSPPSYCH.2018.05.005\u003c/span\u003e\u003cspan address=\"10.1016/J.GENHOSPPSYCH.2018.05.005\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDiStefano, C., \u0026amp; Kamphaus, R. W. (2006). Investigating subtypes of child development: A comparison of cluster analysis and latent class cluster analysis in typology creation. \u003cem\u003eEducational and Psychological Measurement\u003c/em\u003e, \u003cem\u003e66\u003c/em\u003e(5), 778\u0026ndash;794. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1177/0013164405284033\u003c/span\u003e\u003cspan address=\"10.1177/0013164405284033\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDziak, J. J., Lanza, S. T., \u0026amp; Tan, X. (2014). Effect size, statistical power and sample size requirements for the bootstrap likelihood ratio test in latent class analysis. \u003cem\u003eStructural Equation Modeling: A Multidisciplinary Journal\u003c/em\u003e, \u003cem\u003e21\u003c/em\u003e(4), 534\u0026ndash;552. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1080/10705511.2014.919819\u003c/span\u003e\u003cspan address=\"10.1080/10705511.2014.919819\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eEllis, T. E., Rufino, K. A., Allen, J. G., Fowler, J. C., \u0026amp; Jobes, D. A. (2015). Impact of a suicide-specific intervention within inpatient psychiatric care: The Collaborative Assessment and Management of Suicidality. \u003cem\u003eSuicide and Life-Threatening Behavior\u003c/em\u003e, \u003cem\u003e45\u003c/em\u003e(5), 556\u0026ndash;566. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1111/sltb.12151\u003c/span\u003e\u003cspan address=\"10.1111/sltb.12151\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eEngstr\u0026ouml;m, G., Als\u0026eacute;n, M., Gustavsson, P., Schalling, D., \u0026amp; Tr\u0026auml;skman-Bendz, L. (1996). Classification of suicide attempters by cluster analysis: A study of the temperamental heterogeneity in suicidal patients. \u003cem\u003ePersonality and Individual Differences\u003c/em\u003e, \u003cem\u003e21\u003c/em\u003e(5), 687\u0026ndash;695. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/0191-8869(96)00102-X\u003c/span\u003e\u003cspan address=\"10.1016/0191-8869(96)00102-X\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eEveritt, B. S., \u0026amp; Hand, D. J. (1981). \u003cem\u003eFinite Mixture Distributions. Monographs on Applied Probability and Statistics\u003c/em\u003e (Vol. 2). Springer Netherlands. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1007/978-94-009-5897-5\u003c/span\u003e\u003cspan address=\"10.1007/978-94-009-5897-5\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eFirst, M. B. (1997). \u003cem\u003eUser\u0026rsquo;s guide for the structured clinical interview for DSM-IV Axis II personality disorders: SCID-II\u003c/em\u003e. American Psychiatric.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eForman, E. M., Berk, M. S., Henriques, G. R., Brown, G. K., \u0026amp; Beck, A. T. (2004). History of multiple suicide attempts as a behavioral marker of severe psychopathology. The American Journal of Psychiatry, 1613(161), 437\u0026ndash;443. Retrieved from \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://ajp.psychiatryonline.org\u003c/span\u003e\u003cspan address=\"http://ajp.psychiatryonline.org\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eFowler, J. C. (2012). Suicide risk assessment in clinical practice: Pragmatic guidelines for imperfect assessments. Psychotherapy. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1037/a0026148\u003c/span\u003e\u003cspan address=\"10.1037/a0026148\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eFreitag, S., Au, J. S., Liu, D. Y., Mekawi, Y., \u0026amp; Lamis, D. A. (2023). Do bipolar disorder symptom profiles matter for suicide risk? A latent class approach to investigating differences in suicidal desire and acquired capability. \u003cem\u003eSuicide and Life-Threatening Behavior\u003c/em\u003e, \u003cem\u003e54\u003c/em\u003e(1), 24\u0026ndash;37. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1111/sltb.13013\u003c/span\u003e\u003cspan address=\"10.1111/sltb.13013\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eFranklin, J. C., Ribeiro, J. D., Fox, K. R., Bentley, K. H., Kleiman, E. M., Huang, X., \u0026amp; Nock, M. K. (2017). Risk factors for suicidal thoughts and behaviors: A meta-analysis of 50 years of research. \u003cem\u003ePsychological Bulletin\u003c/em\u003e, \u003cem\u003e143\u003c/em\u003e(2), 187. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1037/bul0000084\u003c/span\u003e\u003cspan address=\"10.1037/bul0000084\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGeorge, D., \u0026amp; Mallery, P. (2010). \u003cem\u003eSPSS for Windows Step by Step: A Simple Guide and Reference 17.0 Update.\u003c/em\u003e 10th Edition, Pearson, Boston.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eJobes, D. A. (1995). The challenge and the promise of clinical suicidology. \u003cem\u003eSuicide and Life-Threatening Behavior\u003c/em\u003e, \u003cem\u003e25\u003c/em\u003e(4), 437\u0026ndash;449. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1111/J.1943-278X.1995.TB00237.X\u003c/span\u003e\u003cspan address=\"10.1111/J.1943-278X.1995.TB00237.X\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eJobes, D. A. (2023). \u003cem\u003eManaging suicidal risk: A collaborative approach\u003c/em\u003e. Guilford.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eJobes, D. A., Au, J. S., \u0026amp; Siegelman, A. (2015). Psychological approaches to suicide treatment and prevention. \u003cem\u003eCurrent Treatment Options in Psychiatry\u003c/em\u003e, \u003cem\u003e2\u003c/em\u003e(4), 363\u0026ndash;370.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eJobes, D. A., Comtois, K. A., Gutierrez, P. M., Brenner, L. A., Huh, D., Chalker, S. A., \u0026amp; Crow, B. (2017). A randomized controlled trial of the Collaborative Assessment and Management of Suicidality versus enhanced care as usual with suicidal Soldiers. \u003cem\u003ePsychiatry\u003c/em\u003e, \u003cem\u003e80\u003c/em\u003e(4), 339\u0026ndash;356. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1080/00332747.2017.1354607\u003c/span\u003e\u003cspan address=\"10.1080/00332747.2017.1354607\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eJobes, D. A., Jacoby, A. M., Cimbolic, P., \u0026amp; Hustead, L. A. T. (1997). Assessment and treatment of suicidal clients in a university counseling center. \u003cem\u003eJournal of Counseling Psychology\u003c/em\u003e, \u003cem\u003e44\u003c/em\u003e(4), 368\u0026ndash;377. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1037/0022-0167.44.4.368\u003c/span\u003e\u003cspan address=\"10.1037/0022-0167.44.4.368\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eJobes, D. A., Kahn-Greene, E., Greene, J. A., \u0026amp; Goeke-Morey, M. (2009). Clinical improvements of suicidal outpatients: Examining suicide status form responses as predictors and moderators. \u003cem\u003eArchives of Suicide Research\u003c/em\u003e, \u003cem\u003e13\u003c/em\u003e(2), 147\u0026ndash;159.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eJobes, D. A., Nelson, K. N., Peterson, E. M., Pentiuc, D., Downing, V., Francini, K., \u0026amp; Kiernan, A. (2004). Describing suicidality: An investigation of qualitative SSF responses. \u003cem\u003eSuicide and Life-Threatening Behavior\u003c/em\u003e, \u003cem\u003e34\u003c/em\u003e(2), 99\u0026ndash;112. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1521/suli.34.2.99.32788\u003c/span\u003e\u003cspan address=\"10.1521/suli.34.2.99.32788\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eJoiner, T. E., Walker, R. L., Rudd, M. D., \u0026amp; Jobes, D. A. (1999). Scientizing and routinizing the assessment of suicidality in outpatient practice. \u003cem\u003eProfessional Psychology: Research and Practice\u003c/em\u003e, \u003cem\u003e30\u003c/em\u003e(5), 447\u0026ndash;453. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1037/0735-7028.30.5.447\u003c/span\u003e\u003cspan address=\"10.1037/0735-7028.30.5.447\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKlonsky, E. D., \u0026amp; Olino, T. M. (2008). Identifying clinically distinct subgroups of self-injurers among young adults: A latent class analysis. \u003cem\u003eJournal of Consulting and Clinical Psychology\u003c/em\u003e, \u003cem\u003e76\u003c/em\u003e(1), 22\u0026ndash;27. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1037/0022-006X.76.1.22\u003c/span\u003e\u003cspan address=\"10.1037/0022-006X.76.1.22\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKoerner, K., \u0026amp; Linehan, M. M. (2000). Research on dialectical behavior therapy for patients with borderline personality disorder. \u003cem\u003ePsychiatric Clinics of North America\u003c/em\u003e, \u003cem\u003e23\u003c/em\u003e(1), 151\u0026ndash;167.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLanza, S. T., Flaherty, B. P., \u0026amp; Collins, L. M. (2003). Latent class and latent transition analysis. \u003cem\u003eHandbook of Psychology\u003c/em\u003e (pp. 663\u0026ndash;685). John Wiley \u0026amp; Sons, Inc. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1002/0471264385.wei0226\u003c/span\u003e\u003cspan address=\"10.1002/0471264385.wei0226\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLanza, S. T., Tan, X., \u0026amp; Bray, B. C. (2013). Latent class analysis with distal outcomes: A flexible model-based approach. \u003cem\u003eStructural Equation Modeling\u003c/em\u003e, \u003cem\u003e20\u003c/em\u003e, 1\u0026ndash;26.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLento, R. M., Ellis, T. E., Hinnant, B. J., \u0026amp; Jobes, D. A. (2013). Using the Suicide Index Score to predict treatment outcomes among psychiatric inpatients. \u003cem\u003eSuicide and Life-Threatening Behavior\u003c/em\u003e, \u003cem\u003e43\u003c/em\u003e(5). \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1111/sltb.12038\u003c/span\u003e\u003cspan address=\"10.1111/sltb.12038\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003en/a-n/a\u003c/span\u003e\u003cspan address=\"http://n/a-n/a\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLieb, K., Zanarini, M. C., Schmahl, C., Linehan, M. M., \u0026amp; Bohus, M. (2004). Borderline personality disorder. \u003cem\u003eThe Lancet\u003c/em\u003e, \u003cem\u003e364\u003c/em\u003e(9432), 453\u0026ndash;461. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/S0140-6736(04)16770-6\u003c/span\u003e\u003cspan address=\"10.1016/S0140-6736(04)16770-6\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLinehan, M. M., Korslund, K. E., Harned, M. S., Gallop, R. J., Lungu, A., Neacsiu, A. D., \u0026amp; Murray-Gregory, A. M. (2015). Dialectical behavior therapy for high suicide risk in individuals with borderline personality disorder. \u003cem\u003eJAMA Psychiatry\u003c/em\u003e, \u003cem\u003e72\u003c/em\u003e(5), 475. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1001/jamapsychiatry.2014.3039\u003c/span\u003e\u003cspan address=\"10.1001/jamapsychiatry.2014.3039\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLogan, J., Hall, J., \u0026amp; Karch, D. (2011). Suicide categories by patterns of known risk factors: a latent class analysis. \u003cem\u003eArchives of General Psychiatry\u003c/em\u003e, \u003cem\u003e68\u003c/em\u003e(9), 935\u0026ndash;941. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1001/archgenpsychiatry.2011.85\u003c/span\u003e\u003cspan address=\"10.1001/archgenpsychiatry.2011.85\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMcCutcheon, A. L. (1987). \u003cem\u003eLatent class analysis\u003c/em\u003e (p. 64). Sage.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMorey, L. C. (1991). \u003cem\u003ePersonality Assessment Inventory: Professional Manual\u003c/em\u003e. Psychological Assessment Resources.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMuth\u0026eacute;n, B. (2004). Latent variable analysis. \u003cem\u003eThe Sage handbook of quantitative methodology for the social sciences\u003c/em\u003e, \u003cem\u003e345\u003c/em\u003e(368), 106\u0026ndash;109.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMuth\u0026eacute;n, B., \u0026amp; Muth\u0026eacute;n, L. K. (2000). Integrating person-centered and variable‐centered analyses: Growth mixture modeling with latent trajectory classes. \u003cem\u003eAlcoholism: Clinical and experimental research\u003c/em\u003e, \u003cem\u003e24\u003c/em\u003e(6), 882\u0026ndash;891.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMuth\u0026eacute;n, L. K., \u0026amp; Muth\u0026eacute;n, B. O. (2018). Mplus: Statistical Analysis with Latent Variables - User\u0026rsquo;s Guide. Retrieved from www.StatModel.com.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eNational Institute of Mental Health (2023). Suicide Risk Screening Pathway in Emergency Department Chart Description. Retrieved from \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.nimh.nih.gov/research/research-conducted-at-nimh/asq-toolkit-materials/youth-ed/suicide-risk-screening-pathway-emergency-department-chart-description\u003c/span\u003e\u003cspan address=\"https://www.nimh.nih.gov/research/research-conducted-at-nimh/asq-toolkit-materials/youth-ed/suicide-risk-screening-pathway-emergency-department-chart-description\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eNylund, K. L., Asparouhov, T., \u0026amp; Muth\u0026eacute;n, B. O. (2007). Deciding on the number of classes in latent class analysis and growth mixture modeling: A Monte Carlo simulation study. \u003cem\u003eStructural Equation Modeling\u003c/em\u003e, \u003cem\u003e14\u003c/em\u003e(4), 535\u0026ndash;569. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1080/10705510701575396\u003c/span\u003e\u003cspan address=\"10.1080/10705510701575396\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eO\u0026rsquo;Connor, S. S., Jobes, D. A., Yeargin, M. K., FitzGerald, M. E., Rodr\u0026iacute;guez, V. M., Conrad, A. K., \u0026amp; Lineberry, T. W. (2012). A cross-sectional investigation of the suicidal spectrum: typologies of suicidality based on ambivalence about living and dying. \u003cem\u003eComprehensive Psychiatry\u003c/em\u003e, \u003cem\u003e53\u003c/em\u003e(5), 461\u0026ndash;467. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.comppsych.2011.09.007\u003c/span\u003e\u003cspan address=\"10.1016/j.comppsych.2011.09.007\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eOquendo, M. A., \u0026amp; Bernanke, J. A. (2017). Suicide risk assessment: Tools and challenges. \u003cem\u003eWorld Psychiatry\u003c/em\u003e, \u003cem\u003e16\u003c/em\u003e(1), 28.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eOquendo, M. A., Perez-Rodriguez, M. M., Poh, E., Sullivan, G., Burke, A. K., Sublette, M. E., \u0026amp; Galfalvy, H. (2014). Life events: a complex role in the timing of suicidal behavior among depressed patients. \u003cem\u003eMolecular Psychiatry\u003c/em\u003e, \u003cem\u003e19\u003c/em\u003e(8), 902\u0026ndash;909. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1038/mp.2013.128\u003c/span\u003e\u003cspan address=\"10.1038/mp.2013.128\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eParis, J. (2002). Chronic suicidality among patients with borderline personality disorder. \u003cem\u003ePsychiatric Services\u003c/em\u003e, \u003cem\u003e53\u003c/em\u003e(6), 738\u0026ndash;742. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1176/appi.ps.53.6.738\u003c/span\u003e\u003cspan address=\"10.1176/appi.ps.53.6.738\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eParis, J., \u0026amp; Zweig-Frank, H. (2001). A 27-year follow-up of patients with borderline personality disorder. \u003cem\u003eComprehensive Psychiatry\u003c/em\u003e, \u003cem\u003e42\u003c/em\u003e(6), 482\u0026ndash;487. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1053/comp.2001.26271\u003c/span\u003e\u003cspan address=\"10.1053/comp.2001.26271\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePisani, A. R., Murrie, D. C., \u0026amp; Silverman, M. M. (2016). Reformulating suicide risk formulation: from prediction to prevention. \u003cem\u003eAcademic Psychiatry\u003c/em\u003e, \u003cem\u003e40\u003c/em\u003e, 623\u0026ndash;629.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePistorello, J., Jobes, D. A., Compton, S. N., Locey, N. S., Walloch, J. C., Gallop, R., \u0026amp; Goswami, S. (2018). Developing adaptive treatment strategies to address suicidal risk in college students: A pilot sequential, multiple assignment, randomized trial (SMART). \u003cem\u003eArchives of Suicide Research\u003c/em\u003e, \u003cem\u003e22\u003c/em\u003e(4), 644\u0026ndash;664. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1080/13811118.2017.1392915\u003c/span\u003e\u003cspan address=\"10.1080/13811118.2017.1392915\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePistorello, J., Jobes, D. A., Gallop, R., Compton, S. N., Locey, N. S., Au, J. S., \u0026amp; Jeffcoat, T. (2021). A randomized controlled trial of the collaborative assessment and management of suicidality (CAMS) versus treatment as usual (TAU) for suicidal college students. \u003cem\u003eArchives of Suicide Research\u003c/em\u003e, \u003cem\u003e25\u003c/em\u003e(4), 765\u0026ndash;789.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePompili, M., Girardi, P., Ruberto, A., \u0026amp; Tatarelli, R. (2005). Suicide in the epilepsies: a meta-analytic investigation of 29 cohorts. \u003cem\u003eEpilepsy \u0026amp; Behavior\u003c/em\u003e, \u003cem\u003e7\u003c/em\u003e(2), 305\u0026ndash;310.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePorcu, M., \u0026amp; Giambona, F. (2016). Introduction to latent class analysis with applications. \u003cem\u003eJournal of Early Adolescence\u003c/em\u003e, \u003cem\u003e37\u003c/em\u003e(1), 129\u0026ndash;158. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1177/0272431616648452\u003c/span\u003e\u003cspan address=\"10.1177/0272431616648452\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eRapeli, C. B., \u0026amp; Botega, N. J. (2005). Clinical profiles of serious suicide attempters consecutively admitted to a university-based hospital: a cluster analysis study. \u003cem\u003eRevista Brasileira de Psiquiatria\u003c/em\u003e, \u003cem\u003e27\u003c/em\u003e(4), 285\u0026ndash;289. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1590/S1516-44462005000400006\u003c/span\u003e\u003cspan address=\"10.1590/S1516-44462005000400006\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eRoss, E. L., Bossarte, R. M., Dobscha, S. K., Gildea, S. M., Hwang, I., Kennedy, C. J., \u0026amp; Kessler, R. C. (2023). \u003cem\u003eEstimated average treatment effect of psychiatric hospitalization in patients with suicidal behaviors: a precision treatment analysis\u003c/em\u003e. JAMA Psychiatry.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eRudd, M. D. (2006). Fluid vulnerability theory: A cognitive approach to understanding the process of acute and chronic suicide risk. \u003cem\u003eCognition and suicide: Theory, research, and therapy\u003c/em\u003e (pp. 355\u0026ndash;368). American Psychological Association.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSchwartz, D. A. (1979). The suicidal character. \u003cem\u003ePsychiatric Quarterly\u003c/em\u003e, \u003cem\u003e51\u003c/em\u003e(1), 64\u0026ndash;70. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1007/BF01064720\u003c/span\u003e\u003cspan address=\"10.1007/BF01064720\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSchwartz, D. A., Flinn, D. E., \u0026amp; Slawson, P. F. (1974). Treatment of the suicidal character. \u003cem\u003eAmerican Journal of Psychotherapy\u003c/em\u003e, \u003cem\u003e28\u003c/em\u003e(2), 194\u0026ndash;207. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1176/appi.psychotherapy.1974.28.2.194\u003c/span\u003e\u003cspan address=\"10.1176/appi.psychotherapy.1974.28.2.194\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eStone, D. M., Simon, T. R., Fowler, K. A., Kegler, S. R., Yuan, K., Holland, K. M., \u0026amp; Crosby, A. E. (2018). Vital signs: Trends in state suicide rates \u0026mdash; United States, 1999\u0026ndash;2016 and circumstances contributing to suicide \u0026mdash; 27 States, 2015. \u003cem\u003eMorbidity and Mortality Weekly Report\u003c/em\u003e, \u003cem\u003e67\u003c/em\u003e(22), 617\u0026ndash;624. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.15585/mmwr.mm6722a1\u003c/span\u003e\u003cspan address=\"10.15585/mmwr.mm6722a1\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSuominen, K., Suokas, J., \u0026amp; L\u0026ouml;nnqvist, J. (2007). Attitudes of general hospital emergency room personnel towards attempted suicide patients. \u003cem\u003eNordic Journal of Psychiatry\u003c/em\u003e, \u003cem\u003e61\u003c/em\u003e(5), 387\u0026ndash;392. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1080/08039480701643381\u003c/span\u003e\u003cspan address=\"10.1080/08039480701643381\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSwift, J. K., Trusty, W. T., \u0026amp; Penix, E. A. (2021). The effectiveness of the Collaborative Assessment and Management Of Suicidality (CAMS) compared to alternative treatment conditions: A meta-analysis. \u003cem\u003eSuicide and Life-Threatening Behavior\u003c/em\u003e, \u003cem\u003e51\u003c/em\u003e(5), 882\u0026ndash;896.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eTairi, T., Milojev, P., \u0026amp; Zilikis, N. (2018). Clinical profiles among greek adolescent suicide attempters. \u003cem\u003eCrisis\u003c/em\u003e, \u003cem\u003e39\u003c/em\u003e, 1\u0026ndash;9. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1027/0227-5910/a000506\u003c/span\u003e\u003cspan address=\"10.1027/0227-5910/a000506\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eTrull, T. J. (1995). Borderline personality disorder features in nonclinical young adults: Identification and validation. \u003cem\u003ePsychological Assessment\u003c/em\u003e, \u003cem\u003e7\u003c/em\u003e(1), 33\u0026ndash;41. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1037/1040-3590.7.1.33\u003c/span\u003e\u003cspan address=\"10.1037/1040-3590.7.1.33\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eTucker, R. P., Crowley, K. J., Davidson, C. L., \u0026amp; Gutierrez, P. M. (2015). Risk factors, warning signs, and drivers of suicide: What are they, how do they differ, and why does it matter? \u003cem\u003eSuicide and Life-Threatening Behavior\u003c/em\u003e, \u003cem\u003e45\u003c/em\u003e(6), 679\u0026ndash;689. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1111/sltb.12161\u003c/span\u003e\u003cspan address=\"10.1111/sltb.12161\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWurpts, I. C., \u0026amp; Geiser, C. (2014). Is adding more indicators to a latent class analysis beneficial or detrimental? Results of a Monte-Carlo study. \u003cem\u003eFrontiers in Psychology\u003c/em\u003e, \u003cem\u003e5\u003c/em\u003e, 920. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.3389/fpsyg.2014.00920\u003c/span\u003e\u003cspan address=\"10.3389/fpsyg.2014.00920\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"journal-of-contemporary-psychotherapy","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"jocp","sideBox":"Learn more about [Journal of Contemporary Psychotherapy](http://link.springer.com/journal/10879)","snPcode":"10879","submissionUrl":"https://submission.springernature.com/new-submission/10879/3?","title":"Journal of Contemporary Psychotherapy","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"Typologies, suicide risk, suicide attempts, CAMS, latent profile analysis","lastPublishedDoi":"10.21203/rs.3.rs-6581494/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6581494/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground\u003c/strong\u003e: Identifying typologies of patients who are suicidal have important clinical implications. The Suicide Status Form (SSF) of the Collaborative Assessment and Management of Suicidality (CAMS) is a well-validated suicide assessment tool that may help derive clinical subtypes. Despite the strong psychometric properties of different sections of the SSF, no prior studies have examined all\u003cem\u003e \u003c/em\u003eSSF variables in aggregate.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethod\u003c/strong\u003e: This study uses latent profile analysis (LPA) to statistically generate subtypes of patients who are suicidal based on a diverse and aggregate sample from three clinical trials conducted in an inpatient setting, an active-duty Army outpatient clinic, and a university counseling center.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults\u003c/strong\u003e: Based on fit indices, the four-profile model yielded the best fit with the data. The four profiles were characterized by (1) acute stress, (2) history of multiple attempts, (3) female gender and features of borderline personality disorder, and (3) male gender and externalizing traits. The fourth profile reported the lowest ratings of suicide risk at termination, overall, while there was preliminary evidence showing that those in profile one and two were at elevated risk of attempting suicide.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eLimitations\u003c/strong\u003e: A limitation is that the sample size is relatively small for LPA, despite the stability of the profiles.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusion\u003c/strong\u003e: This study identified four distinct suicide typologies based on both qualitative and quantitative factors related to suicide risk, as derived from a widely used clinical assessment tool. These typologies were found to vary according to sex, history of suicide attempt, acute stressors, borderline personality traits, and externalizing behaviors. Clinical implications and future directions for research are also discussed.\u003c/p\u003e","manuscriptTitle":"Who Responds to CAMS? Latent Profiles of Patients Who Received the Collaborative Assessment and Management of Suicidality","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-05-13 06:37:03","doi":"10.21203/rs.3.rs-6581494/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2025-06-17T14:05:10+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-06-02T09:36:16+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"53166709657980759164970213742167402483","date":"2025-05-06T13:00:52+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-05-06T11:58:43+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-05-03T08:27:20+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-05-03T08:25:06+00:00","index":"","fulltext":""},{"type":"submitted","content":"Journal of Contemporary Psychotherapy","date":"2025-05-03T02:39:54+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"journal-of-contemporary-psychotherapy","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"jocp","sideBox":"Learn more about [Journal of Contemporary Psychotherapy](http://link.springer.com/journal/10879)","snPcode":"10879","submissionUrl":"https://submission.springernature.com/new-submission/10879/3?","title":"Journal of Contemporary Psychotherapy","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"c8bfe4d6-6a73-4f07-a1ed-9cfa71d7b21a","owner":[],"postedDate":"May 13th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2025-10-20T16:01:49+00:00","versionOfRecord":{"articleIdentity":"rs-6581494","link":"https://doi.org/10.1007/s10879-025-09691-9","journal":{"identity":"journal-of-contemporary-psychotherapy","isVorOnly":false,"title":"Journal of Contemporary Psychotherapy"},"publishedOn":"2025-10-17 15:57:37","publishedOnDateReadable":"October 17th, 2025"},"versionCreatedAt":"2025-05-13 06:37:03","video":"","vorDoi":"10.1007/s10879-025-09691-9","vorDoiUrl":"https://doi.org/10.1007/s10879-025-09691-9","workflowStages":[]},"version":"v1","identity":"rs-6581494","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6581494","identity":"rs-6581494","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}