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Suicidal and nonsuicidal self-harm thoughts and behaviors (SHTBs) are a global public health concern, with estimates suggesting that >14.6 million individuals are affected by self-harm (defined as any form of deliberate self-injury irrespective of motivation or intent) each year and >700,000 deaths per year are attributable to suicide []. Understanding factors that contribute to the development of SHTBs is essential for prevention and early intervention.
The integrated motivational-volitional model (IMV) is one of the leading theoretical models of suicidal behavior, developed by O’Connor [] and later refined by O’Connor and Kirtley [] ( []). The IMV model consists of 3 phases: the premotivational stage, describing the biopsychosocial context in which suicidal thoughts and behavior may emerge; the motivational phase, describing the factors that lead to the development of suicidal thoughts; and the volitional phase, describing the factors that predict the transition from thoughts to behaviors [].
Figure 1. The integrated motivational-volitional model of suicidal behavior (adapted with permission from O’Connor and Kirtley []). MM: motivational moderators; TSM: threat-to-self moderators; VM: volitional moderators. Core constructs of the motivational phase include feelings of defeat, humiliation, and entrapment, which drive the emergence of suicidal thoughts. These can be facilitated or impeded by the presence of moderating variables, termed “threat to self,” and “motivational” moderators. The transition from suicidal thoughts to behaviors is, in turn, influenced by the presence of “volitional moderators” [,]. Although the IMV model was developed in relation to suicidal thoughts and behavior, the central concepts of the model can also be applied to nonsuicidal SHTBs [].
A recent systematic review of studies testing the IMV model of suicidal behavior yielded support for the central components of the model (ie, the defeat-entrapment–suicidal ideation [SI] pathway)—but called for more focus on the constructs referred to as threat-to-self and motivational moderators in the model []. The review identified extensive testing of the model using cross-sectional retrospective methods while highlighting the need for more prospective (including intensive longitudinal) testing of IMV constructs [].
Ecological Momentary AssessmentRecent technological advances have made it easier for researchers to gain insights into SHTBs in real time using intensive longitudinal methods [-]. These methods are commonly referred to in the literature as experience sampling methods (ESMs), ambulatory assessment, daily diaries, and ecological momentary assessment (EMA). From this point onward, for brevity, we use the term EMA to refer to this methodology. EMA is a diary-based method involving repeated and frequent assessment of feelings, behaviors, and contexts in an individual’s natural environment. This minimizes recall bias, maximizes ecological validity, and enables dynamic processes to be captured. Assessment may be once daily (daily diaries); repeated throughout the day at pseudorandomized or specific times in a signal-contingent sampling scheme; or repeated based on reporting of a specific event, such as an act of nonsuicidal self-injury (NSSI; event contingent) []. Despite concerns regarding the demands placed on research participants from intensive sampling, it has been found to be both acceptable and feasible, with generally good compliance reported []. While there have been further concerns about the repeated reporting of mental states having an influence on an individual’s mental state, there is no strong evidence of such iatrogenic effects [,].
Existing EMA studies of suicidal thoughts have shown them to be highly variable over time [,]; however, less is known about the extent to which proximal risk factors for SHTBs, such as those proposed by the IMV model, fluctuate in daily life. Understanding the dynamic nature of risk factors (within-person variability) and their moderators is essential to tailoring interventions and risk assessments. It is important to understand whether risk factors and moderators are better characterized by individual differences (between-person variability) or momentary changes in experiences (within-person variability) [,]. Examining intraclass correlation coefficients (ICCs—see the Data Analysis section for more details) enables distinction between trait-level risk factors (high ICC and high between-person variability)—supporting longer-term strategies for intervention—and state-level risk factors (low ICC and high within-person variability)—for which acute, timely, and situation-specific intervention may be more appropriate []. A recent proliferation of EMA studies in the field of suicide and self-harm has prompted the need for a comprehensive synthesis of this literature. While others have reviewed EMA literature on self-harm [-], suicidal thoughts [,,,], and interpersonal processes in an SHTB context [], EMA studies specifically assessing key constructs across both the motivational and volitional phases of the IMV model have not yet been synthesized. In addition, existing reviews of EMA studies have typically focused on the relationship between risk factors and SHTBs, and less attention has been paid to the characteristics of the risk factors themselves.
We conducted a systematic review of the SHTB literature in which constructs from the motivational and volitional phases of the IMV model were assessed using EMA. We offer a narrative synthesis, describing how IMV constructs were assessed in daily life, characterizing their within-person variability, and summarizing the evidence of the proximal relationships between each IMV construct and SHTBs. We identified gaps in the evidence base and proposed directions for future research.
Primary Review QuestionsThe review questions are as follows:
Which of the key constructs in the IMV model have been assessed in EMA studies—in the context of suicidal or nonsuicidal SHTBs—and how have they been assessed?Do different constructs from the IMV model show fluctuation in daily life when measured in the context of suicidal or nonsuicidal SHTBs, and what is their within-person variability?Secondary Review QuestionThe secondary review question is as follows:
What is the relationship between the different IMV constructs and suicidal and nonsuicidal SHTBs in daily life?This review was preregistered on the PROSPERO database (CRD42022349514) and on the Open Science Framework (OSF) []. The PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines were followed (), in addition to the Non-Intervention, Reproducible, and Open Systematic Review guidelines []. We searched the databases Web of Science, Embase, MEDLINE, PsycINFO, and Europe PMC Preprints. We also hand searched reference lists and citations of the included papers for additional papers not returned by the database searches.
The full search terms and strategy are available on the OSF []. We searched for studies that used intensive longitudinal methods, often referred to as EMA, experience sampling, ambulatory assessment, or daily diary methods. We did not establish a date limit on the search. The initial search was conducted in October 2022, yielding 40 papers, with an updated search in November 2023 yielding an additional 13 papers. A final presubmission updated search conducted in March 2024 yielded an additional 6 studies over 5 papers.
Records were exported to, stored, and managed using the application Rayyan (Rayyan Systems Inc). In total, 2 (blinded) authors independently screened the papers for inclusion based on the titles and abstracts simultaneously against the inclusion and exclusion criteria, with disagreements resolved through discussion. One author conducted full screening of the selected papers based on the full text. Full details are available in the corresponding OSF project page [].
Inclusion and Exclusion CriteriaWe included studies that had assessed at least one of the IMV constructs in daily life using intensive longitudinal data collection methods (ie, EMA). These factors include the core motivational phase factors (defeat, shame, humiliation, and entrapment), threat-to-self moderators (problem-solving, coping, memory bias, and rumination), motivational moderators (thwarted belongingness, burdensomeness, future thinking, goals, norms, resilience, social support, and attitudes), and volitional moderators (suicide planning, exposure to self-harm, impulsiveness, pain sensitivity, fearlessness about death, and imagery). To be included, the studies needed to report details of within-person variability in IMV constructs (ie, ICC; see the Data Analysis section). Where not reported, we contacted the authors to request this information. If ICCs were not available and no association between at least one IMV construct and SHTBs was reported, the study was excluded.
We included PhD theses published on the internet and excluded studies that were meta-analyses, reviews, editorials, or commentaries, as well as articles not written in English. We did not limit the inclusion of studies according to population or participant characteristics, and both clinical and nonclinical samples were included.
We will not describe the assessment of SHTBs in this study as this has been covered by previous reviews [,,,].
Data AnalysisData extraction (template available on the OSF []) included a range of descriptive data for each study, including demographic information about the sample, whether the study sampled a clinical or community-based population, study design, and information about the IMV constructs measured. ICCs were extracted to describe the level of within-person variability in each construct. ICCs indicate the proportion of a variable’s variance that is due to between- and within-person variability []. The within-person variability is calculated as 1 minus the ICC. When within-person variability is low, this means that the variability in a construct is mostly due to differences between people and there is little fluctuation in the construct in people (ie, the construct may be considered more traitlike than statelike). For example, a hypothetical ICC of 0.83 would indicate just 17% within-person variance, suggesting that the construct is more traitlike and shows little fluctuation in people. Conversely, an ICC of 0.26 would indicate 74% within-person variance, suggesting that the construct is more statelike and shows large fluctuation in people over time.
Where studies tested associations between IMV constructs and SHTBs—either concurrent or lagged—these associations were also extracted. Quality assessment of the reporting of the studies was conducted according to an EMA-specific quality assessment tool []. Example reporting criteria included participant training in the EMA protocol being detailed in the Methods section, justification of the sample size, compliance rate and reasons for noncompliance, discussion of EMA-specific limitations, and open code for analysis (the full criteria are available on the OSF []).
A total of 53 studies (unique samples) were included in this review ( provides the PRISMA flowchart) across 58 papers, all from higher-income countries, with most from North America (n=40, 75%), the United Kingdom (n=3, 6%), and Germany (n=3, 6%). The studies varied substantially in terms of population, sample size, design, and constructs measured. Several papers (11/58, 19%) reported different analyses using the same study sample (ie, the same sample was used to report different IMV constructs across different papers). To avoid double counting of samples and designs, reports a summary of 53 studies (58 papers reporting results from 53 independent samples).
Figure 2. PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) flow diagram. IMV: integrated motivational-volitional model. Table 1. Overview of the samples of the included studies (n=53).a69.8% female (women, female gender identity, or assigned female at birth where gender identity was not reported).
The sample sizes ranged from 10 to 743 participants (mean sample size 85.3, SD 105.4; median 54, IQR-38.5-94.5). Most studies (47/53, 89%) included largely female samples (69.8% of the total combined sample were female); in 4% (2/53) of the studies, all participants were female or women [,]; in 8% (4/53) of the studies, participants were mostly male or men [-]; 28% (15/53) of the studies included a small number of transgender, nonbinary, or gender nonconforming participants; and, in 2% (1/53) of the studies, all participants were transgender or gender diverse []. In 55% (29/53) of the studies, most participants were White; 19% (10/53) of the studies did not report the participants’ race or ethnicity. The mean sample age ranged from 15.0 to 47.7 years, with 28% (15/53) of the studies using a sample of young people (aged ≤25 years). In 26% (14/53) of the studies, participants were recruited from the general population, with 23% (12/53) of the studies recruiting from universities and the samples in the remaining studies being recruited from clinical settings or a mix of clinical and community settings.
Approximately a quarter of the studies (15/53, 28%) adopted a daily diary design with 1 assessment per day. Of the remaining 72% (38/53) of the EMA studies, the number of measurements ranged from 2 to 10 per day (mean 4.2, SD 2.3 measurements), and most (33/53, 62%) were delivered using a signal-contingent sampling scheme at pseudorandomized intervals. Study duration ranged from 3.4 to 90 days (mean 19.8, SD 18.5; median 14.0 days), with some studies (6/53, 11%) reporting varying durations based on length of hospitalization [,,-]. In the 85% (45/53) of the studies in which study duration was consistent for all participants, we found a small negative correlation (r=–0.14) between study duration (in days) and the number of assessments per day. EMA smartphone apps were most often used for data collection, including Illumivu, MetricWire, and movisensXS.
Which of the Key Constructs in the IMV Model Were Assessed in EMA Studies, and How Were They Assessed?In this section, we refer to the 58 individual papers. In total, 3% (2/58) of the papers [,] each reported 2 independent samples. Several other papers (11/58, 19%) reported the same sample but different IMV constructs [,]. A total of 45% (26/58) of the papers reported more than one IMV construct. In 12% (7/58) of the papers [,,-], the study used a signal-contingent (pseudorandom) sampling scheme with multiple daily assessments, but one or more IMV constructs were assessed once per day, or an aggregated daily measure was used.
Across the 58 papers included in this review, the motivational moderators in the IMV model were most frequently assessed in EMA studies (). The constructs measured most frequently were thwarted belongingness (24/58, 41% of the papers), positive or negative thoughts about the future (20/58, 34% of the papers), and perceived burdensomeness (16/58, 28% of the papers). The least frequently measured constructs were humiliation, social problem-solving, mental imagery, physical pain sensitivity, and fearlessness about death. None of the included papers measured memory biases, goals, norms, or resilience using EMA.
Table 2. Integrated motivational-volitional model constructs measured using intensive longitudinal methods by the number of assessments per daya.aSuicidal thoughts and behaviors are not included in our results as these outcomes have been widely reported and discussed in other reviews of ecological momentary assessment studies.
bTotal includes 1 event contingent study.
Do Different Constructs From the IMV Model Show Fluctuation in Daily Life, and What Is Their Within-Person Variability?OverviewICCs were available in 78% (45/58) of the papers. These estimates varied substantially but, for most constructs, showed an overall pattern of at least moderate within-person variance (). A small number of constructs showed levels of within-person variance of <20% across a small number of papers (6/58, 10%), suggesting a more stable and traitlike construct in these particular samples.
There was variability across studies measuring the same IMV construct; however, no consistent patterns were observed in comparisons between IMV constructs measured in clinical versus community populations or in comparisons between different sampling frequency (number of assessments per day; see [-] for full details). The findings are described for each construct in the following sections and summarized in and .
Table 3. Proportion of within-person variance reported for each integrated motivational-volitional model construct by sample typea.aWithin-person variance=1 – intraclass correlation coefficient.
bNumber of studies indicated in parentheses.
cNo studies reporting within-person variance.
Table 4. Overview of the included studies.StudyReport typeCountrySample typeSample size, NAge (y), mean (SD)Gender or sexEthnicity or raceMental health profileStudy duration (days)Assessments per day, NCompliance (%), mean (SD)Constructs measuredICCa reportedAadahl et al [], 2021Peer-reviewed articleUnited KingdomMixed (clinical and community)2734.2 (13.9)66% female; 34% male93% White British; 7% White otherRecent SIb; 26% personality disorder; 45% affective disorder; 7% psychotic disorder; 3% eating disorder; 19% not stated7649Defeat, entrapment, and hopelessnessNo ICCs reportedAl-Dajani and Czyz [], 2022Peer-reviewed articleUnited StatesClinical (inpatient)7815.2 (1.4)68% assigned female at birth83% White; 6% Black; 5% Asian; 5% American Indian or Alaska Native; 4% otherRecent SI or SAc28172Perceived burdensomeness, peer belongingness, and family belongingnessPerceived burdensomeness: 0.40; peer belongingness: 0.59; family belongingness: 0.43Al-Dajani and Uliaszek [], 2021Peer-reviewed articleUnited StatesMixed clinical and nonclinical (including university students)3930.9 (8.8)67% female; 26% male; 5% nonbinary or transgender49% White; 19% Black; 16% other; 10% East Asian; 8% South Asian59% lifetime SA14468Hopelessness0.49Al-Dajani et al [], 2022 (Same sample as the study by Al-Dajani and Czyz [], 2022Peer-reviewed articleUnited StatesClinical (inpatient)7815.2 (1.4)68% assigned female at birth83% White; 6% Black; 5% Asian; 5% American Indian or Alaska Native; 4% otherRecent SI or SA28172Coping (personal support, professional support, noncognitive, cognitive, perceived helpfulness, and total strategies used)Coping—personal support: 0.49; coping—professional support: 0.27; coping—noncognitive: 0.38; coping—cognitive: 0.55; coping—perceived helpfulness: 0.42; coping—total strategies used: 0.51Ammerman et al [], 2017Peer-reviewed articleUnited StatesNonclinical5128.8 (9.8)75% female52% African American; 33% White; 10% Asian; 6% other65% lifetime NSSId; 100% BPDe and depressive disorder74Not reportedImpulsivityNo ICCs reportedBaryshnikov et al [], 2024Peer-reviewed articleFinlandClinical (inpatient)6737.3 (12.5)66% female; 27% male; 7% otherNot reported37% suicidal behavior; 100% unipolar depressionVaried (mean 3.4 days)3Not reportedHopelessnessNo ICCs reportedBayliss et al [], 2024Peer-reviewed articleAustraliaNonclinical7536.5 (10.8)64% female; 24% male; 12% otherNot reported67% lifetime SA14474.5 (0.2)Mental imagery, fearlessness about death, pain sensitivity, and access to meansMental imagery: 0.28; fearlessness about death: 0.69; pain sensitivity: 0.71; access to means: 0.55Bentley et al [], 2021Peer-reviewed articleUnited StatesClinical (inpatient)8338.4 (13.6)52% male; 42% female; 4% transgender; 2% other83% European descent; 5% Black or African American; 5% Asian; 6% other100% recent SI or SAVaried (mean 8.52, SD 5.73; range: 2-46 days)452Humiliation (shame)0.82Ben-Zeev et al [], 2012Peer-reviewed articleUnited StatesClinical (inpatient)3139.3 (11.0)77% female67% White; 13% African American; 3% Latinx; 17% other58% lifetime SA; 100% depressive disorder76Not reportedHelplessness, hopelessnessNo ICCs reportedBurke et al [], 2021Peer-reviewed articleUnited StatesUniversity students6020.1 (2.1)92% female68% White; 20% Asian; 7% mixed; 3% other100% lifetime history of repetitive NSSI10389ImpulsivityNo ICCs reportedChristensen et al [], 2023Peer-reviewed articleUnited StatesNonclinical9323.5 (4.3)14% cisgender men; 56% cisgender women; 5% transgender men; 23% gender queer or gender nonconforming; 2% another gender identity67% non-Hispanic or Latinx White; 14% Hispanic or Latinx White; 3% Black; 6% Asian; 10% multiracial100% recent NSSI urges7-14676Social support0.78Cloos et al [], 2020Peer-reviewed articleGermanyUniversity students1924.6 (4.5)100% femaleNot reported100% recent NSSI; 89% personality disorder; 95% affective disorder10199Entrapment, mental imagery compellingness, mental imagery vividness, mental imagery controllability, mental imagery nowness, mental imagery distress, and mental imagery comfortEntrapment: 0.37; mental imagery compellingness: 0.21; mental imagery vividness: 0.29; mental imagery controllability: 0.22; mental imagery nowness: 0.29; mental imagery distress: 0.33; mental imagery comfort: 0.44Coppersmith et al [], 2019Peer-reviewed articleUnited StatesNonclinical5323.5 (4.3)77% female75% White; 8% Asian; 2% Black or African American; 15% other100% past-year SA28167% completed at least 14 days of responsesSocial support0.44Czyz et al [], 2019Peer-reviewed articleUnited StatesClinical (inpatient)3415.5 (1.4)77% female85% White; 9% Black or African American;9% Asian100% recent SI or SA; 85% depressive disorder; 71% anxiety disorder; 18% ADHDf28169Hopelessness, perceived burdensomeness, and connectednessHopelessness: 0.67; perceived burdensomeness: 0.69; connectedness: 0.63Czyz et al [], 2019 (Same sample as the study by Czyz et al [], 2019)Peer-reviewed articleUnited StatesClinical (inpatient)3415.5 (1.4)77% female85% White; 9% Black or African American;9% Asian100% recent SI or SA; 85% depressive disorder; 71% anxiety disorder; 18% ADHD28169Coping (number of strategies used)No ICCs reportedCzyz et al [], 2021 (Same sample as the study by Al-Dajani and Czyz [], 2022Peer-reviewed articleUnited StatesClinical (inpatient)7815.2 (1.4)68% assigned female at birth83% White; 6% Black; 5% Asian; 5% American Indian or Alaska Native; 4% otherRecent SI or SA28172Hopelessness, perceived burdensomeness, connectedness to friends, connectedness to family, and ruminationHopelessness: 0.58; perceived burdensomeness: 0.62; connectedness to friends: 0.44; connectedness to family: 0.59; rumination: 0.47Czyz et al [], 2023Peer-reviewed articleUnited StatesClinical (outpatient)10220.9 (2.1)81.4% female; 18.6% male75% White; 9% more than one category; 6% Asian; 5% Black or African American; 5% other100% recent SI or SA56464Rumination, hopelessness, perceived burdensomeness, thwarted belongingness (closeness to others), and copingRumination: 0.59; hopelessness: 0.73; perceived burdensomeness: 0.71; thwarted belongingness (closeness to others): 0.59; coping: 0.48\Defayette et al [], 2023Peer-reviewed articleUnited StatesUniversity students4219.6 (1.3)Sex at birth: 83.3% female and 16.7% male; gender identity: 73.8% women, 16.7% men, and 9.5% nonbinary45% White; 17% African American; 17% Asian; 14% multiracial; 7% other100% recent SI28672 (29.6)Thwarted belongingness (social exclusion)No ICCs reportedEwing and Hamza [], 2024Peer-reviewed articleCanadaUniversity students16019.7 (1.8)83% female; 12% male; 5% transgender, unsure, nonbinary, or agender persons44% White; 22% East Asian; 11% South Asian; 23% Filipino, Latin American, Black, Arab or West Asian, South East Asian, or Aboriginal100% recent NSSI urges and past-year NSSI14189Coping (problem focused, avoidant, emotion focused, and socially supported)Coping—problem focused: 0.58; coping—avoidant: 0.63; coping—emotion focused: 0.72; coping—socially supported: 0.63Gerner et al [], 2023Peer-reviewed articleUnited StatesUniversity students4319.1 (1.3)70% women; 14% men; 12% gender nonconforming; 5% not listed63% White; 21% Black or African American; 7% Asian or Asian American; 5% Latinx; 15% biracial100% recent SI10586Thwarted belongingness, perceived burdensomeness, and hopelessnessThwarted belongingness: 0.64; perceived burdensomeness: 0.53; hopelessness: 0.37Glenn et al [], 2022Peer-reviewed articleUnited StatesClinical (outpatient)4815.0 (1.6)65% female; 17% male; 19% nonbinary77% White; 14% Hispanic; 10% mixed; 8% Black; 2% American Indian100% lifetime SI; 85% lifetime SA; 94% anxiety disorder; 28% ADHD; 83% major depressive disorder283Not reportedThwarted belongingness8 items ranging from 0.67 to 0.78Hallard et al [], 2021Peer-reviewed articleUnited KingdomClinical (inpatient) and nonclinical2435.3 (14.3)67% female92% White British; 8% White other100% recent SI; 79% lifetime SA; 50% mood disorder; 30% personality disorder6748RuminationNo ICCs reportedHallensleben et al [], 2019Peer-reviewed articleGermanyClinical (inpatient)7937.6 (14.3)72% femaleNot reported100% lifetime SI; 34% lifetime SA; 87% depressive disorder61090Hopelessness, perceived burdensomeness, and thwarted belongingnessHopelessness: 0.74; perceived burdensomeness: 0.66; thwarted belongingness: 0.57Harper [], 2019ThesisUnited StatesUniversity students14520.1 (5.4)72% female; 27% male46% White; 33% African American; 15% Hispanic; 8% AsianNot reported7385Thwarted belongingness (loneliness)0.50Hughes et al [], 2019Peer-reviewed articleUnited StatesNonclinical4719.1 (1.8)62% female; 30% male; 2% transgender38% White; 19% Asian; 17% Hispanic; 15% Black or African American; 11% mixed100% recent SHg14584% of participants had at least 80% complianceRumination0.70Jacobucci et al [], 2023Peer-reviewed articleUnited StatesNonclinical3525.9 (5.8)63% identified as female; 20% identified as male; 14% identified as transgender and other69% identified as White; 6% identified as Black; 11% Identified as Asian; 12% identified as other or more than one race100% past-year SHTBs; 70% “seeing someone for emotional, psychiatric or substance use problems”30461Perceived burdensomeness, and thwarted belongingnessNo ICCs reportedJeong et al [], 2021Peer-reviewed articleSouth KoreaNonclinical2340.0 (8.7)78% maleNot reportedNot reported15186Impulsivity0.41Kaurin et al [], 2022Peer-reviewed articleUnited StatesClinical and nonclinical18633.7 (9.4)80% female76% White; 15% Black or African American; 4% Asian; 3% Pacific Islander; 2% other56% lifetime SA; 82% BPD21Event contingentNot reportedImpulsivity (during a social interaction)0.54Kaurin et al [], 2023Peer-reviewed articleUnited StatesClinical and nonclinical15333.6 (9.6)81% femaleNot reported69% lifetime SA; 100% BPD21678ImpulsivityNo ICCs reportedKellerman et al [], 2022Peer-reviewed articleUnited StatesClinical (inpatient)11815.8 (1.8)80% female81%non-Hispanic White; 4% Asian; 4% African American; 4% Hispanic87% lifetime SI; 63% lifetime NSSI; 54% lifetime SA; 77% depressive disorder; 49% anxiety disorderVaried (mean 6.1, SD 6.1 days)1Not reportedSocial support from staff, social support from other patients, social support from family members, and social support from friendsSocial support from staff: 0.71; social support from other patients: 0.73; social support from family members: 0.74; social support from friends: 0.81Kirtley et al [], 2022Peer-reviewed articleBelgiumNonclinical74316.9 (2.4)59% femaleNot reported7% recent SI61070Short-term future thinking (once per day)0.30Kleiman et al [], 2017Peer-reviewed articleGlobalNonclinical5423.2 (5.3)80% female72% European descent; 7% Hispanic; 7% Asian; 14% other100% past-year SA28463Hopelessness, loneliness, and perceived burdensomenessHopelessness: 0.57; loneliness: 0.49; perceived burdensomeness: 0.58Kleiman et al [], 2017Peer-reviewed articleUnited StatesClinical (inpatient)3647.7 (13.1)44% female82% European descent; 6% Hispanic; 6% Asian; 6% other100% recent SA or SIVaried (mean 10.3, SD 6.5 days)462Hopelessness, and thwarted belongingness (loneliness)Hopelessness: 0.66; thwarted belongingness (loneliness): 0.61Krall et al [], 2024Peer-reviewed articleUnited StatesUniversity students12920.0 (1.6)76% female biological sex assigned at birth; 24% male biological sex assigned at birth49 % White; 38% Asian; 7% Black or African American; all others endorsed another or multiple races100% SI56764Pain (once per day) and hopelessnessPain : 0.39; hopelessness: 0.78Kudinova et al [], 2023Peer-reviewed articleUnited StatesClinical (inpatient)15815.2 (1.4)68% were assigned female sex at birth; 61% identified as female; 32% identified as male1% Asian; 9% Black or
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