Integrating a functional view on suicide risk into idiographic statistical models

Collaborative care interventions to reduce suicidal behavior among patients with depression or at risk of suicide in primary-care settings: A systematic review and meta-analysis

INTRODUCTION

Suicide is a leading cause of preventable death worldwide. While Collaborative Care (CC) effectively treats depression in primary care led by general practitioners, its impact on reducing suicide behavior remains uncertain. Additionally, the optimal intensity and duration of CC interventions are unclear.

OBJECTIVE

This systematic review and meta-analysis aimed to evaluate the effect of CC interventions on suicidal behavior in patients with depression or at risk of suicide in primary care settings.

METHODS

We searched PubMed, Embase, and Cochrane databases from inception to April 2024. Two researchers independently performed data selection, extraction, and quality assessment. Data were pooled using the odds ratio (OR) and a random-effects model. The main outcome was suicidal behavior, including attempts and ideation. Subgroup analyses assessed the effectiveness of intensity and duration. A meta-analysis was conducted using the R "meta" package, and the protocol was registered with PROSPERO (CRD 42023477655).

RESULTS

From 3696 articles, 10 randomized controlled trials with 20,110 participants were included. CC interventions significantly reduced suicidal behavior compared to controls (pooled OR = 0.66; 95 % CI, 0.46-0.96). High-intensity interventions were particularly effective (pooled OR = 0.56; 95 % CI, 0.40-0.78). However, no significant relationship was found between intervention duration and suicidal behavior. There was no clear evidence of publication bias.

CONCLUSIONS

CC interventions can reduce suicidal behavior in primary care settings, especially with high-intensity interventions. However, caution is needed due to study heterogeneity and low quality.

A call to integrate menstrual cycle influences into just-in-time adaptive interventions for suicide prevention

This paper discusses the scientific rationale and methodological considerations for incorporating the menstrual cycle as a time-varying intra-individual factor in personalized medicine models, such as Just-In-Time Adaptive Interventions (JITAIs). Among patients, accumulating evidence suggests that the normal hormone fluctuations of the menstrual cycle represent a time-varying factor that can trigger or exacerbate psychiatric symptoms, including but not limited to affective dysregulation, suicidality, and irritability. While only a minority of the general female population experiences significant cyclical changes, this hormone-sensitive response appears to be greater among patients with psychiatric disorders, with studies demonstrating that a majority of patients recruited for past-month suicidal ideation demonstrate worsening of their suicidality around menses. However, no interventions target suicidality during this monthly period of elevated risk despite evidence of a clear recurring biological trigger. This unique and recurrent "biotype" of suicidality is well-suited for JITAIs. In addition to providing a rationale for the inclusion of the cycle in JITAI, we provide illustrative options and examples regarding the measurement and implementation of cycle variables in JITAIs. We discuss how JITAIs might be leveraged to use menstrual cycle data to identify states of vulnerability within people and strategically select and deploy interventions based upon their receptivity at various phases in the cycle. Furthermore, we discuss how to integrate passive measures for tracking the menstrual cycle. Although much research is needed before implementation, we maintain that the menstrual cycle represents a critically understudied time-varying feature that may markedly improve the accuracy of JITAI models for predicting suicidality.

Examining heterogeneity in the affect-regulating function of suicidal ideation: Person-specific analyses in male inpatients with depression

INTRODUCTION

Men have an increased risk to die by suicide compared to women but are underrepresented in suicide research. To improve individual risk prediction for suicide-related thoughts and behaviors (STBs), risk factors are increasingly being studied at an individual level. The possible affect-regulatory function of suicidal ideation has hardly been investigated ideographically and has not yet been tested in a male sample.

METHODS

We investigated the bidirectional associations between suicidal ideation and negative and positive affect in a sample of n = 21 male inpatients with unipolar depression and a history of suicidal ideation both at the group level and at the individual level. Participants underwent an intensive ecological momentary assessment for 6 days with 10 data points per day.

RESULTS

We found no evidence for an affect-regulatory function of suicidal ideation at the group level, neither for effects of affect on subsequent suicidal ideation (antecedent affect-regulatory hypothesis) nor for effects of suicidal ideation on subsequent affect (consequence affect-regulatory hypothesis). Person-specific analyses revealed substantial variability in strength and direction of the considered associations, especially for the associations representing the antecedent hypothesis.

CONCLUSION

The demonstrated between-person heterogeneity points to the necessity to individualize the investigation of risk factors to enhance prediction and prevention of STBs.

Weekly links among irritability and suicidal thoughts and behaviors in high-risk youth

BACKGROUND

Previous studies demonstrate a link between irritability and suicidal thoughts and behaviors (STBs) in youth samples. However, they have mostly assessed irritability in community samples and as a largely dispositional (i.e. trait-like) construct. Thus, it remains unclear to what extent links between irritability and STBs reflect within-person processes of elevated risk in clinically meaningful time periods.

METHODS

The present study used clinical data from 689 adolescents aged 12-19 years attending a total of 6,128 visits at a specialty Intensive Outpatient Program for depressed and suicidal youth to examine patterns in weekly assessments of irritability and STBs throughout treatment, including associations among trends and fluctuations departing from these trends via multilevel structural equation modeling. Youth completed self-report measures of irritability, depression, and STBs weekly as part of standard IOP clinical care.

RESULTS

Overall, two-thirds of variance in weekly irritable mood was accounted for by between-person differences and the remaining portion by weekly fluctuations. After controlling for depression, during weeks when youth were more irritable they experienced increased STBs. Rates of change in irritability and STBs tended to track together at early stages of treatment, but these effects were generally accounted for by depression severity.

CONCLUSIONS

Our results suggest that although changes in STBs are best accounted for by depression, irritability can be understood as a specific, proximal risk factor for youth STBs that exacerbates youth STBs in clinically informative timeframes above and beyond depression.

Beyond one-size-fits-all suicide prediction: Studying idiographic associations of risk factors for suicide in a psychiatric sample using ecological momentary assessment

The Interpersonal Psychological Theory of Suicide (IPTS) states that thwarted belongingness (TB), perceived burdensomeness (PB), and hopelessness are risk factors for suicidal ideation. This ecological momentary assessment (EMA) study aimed to (1) demonstrate that there is substantial between-person variability in the association between IPTS predictors and suicidal ideation, (2) identify clusters of patients for which the predictors differently predict suicidal ideation, and (3) examine whether identified clusters are characterized by specific patient characteristics. EMA data were collected ten times per day for six days in 74 psychiatric inpatients and was analyzed with dynamic structural equation modelling. Idiographic associations were obtained and clustered using k-means clustering. We found substantial between-person variability in associations between IPTS predictors and suicidal ideation. Four distinct clusters were identified and different risk factors were relevant for different clusters. In the largest cluster (n = 36), none of the IPTS predictors predicted suicidal ideation. Clusters in which associations between IPTS variables and suicidal ideation were stronger showed higher suicidal ideation, depression, and lower positive affect. These findings suggest that a one-size-fits-all model may not adequately reflect idiosyncratic processes leading to suicidal ideation. A promising avenue might be to use idiographic approaches to personalize prediction and interventions.

Examining missingness at the momentary level in clinical research using ecological momentary assessment: Implications for suicide research

The use of intensive time sampling methods, such as ecological momentary assessment (EMA), has increased in clinical, and specifically suicide, research during the past decade. While EMA can capture dynamic intraindividual processes, repeated assessments increase participant burden, potentially resulting in low compliance. This study aimed to shed light on study-level and psychological variables, including suicidal ideation (SI), that may predict momentary prompt (i.e., prompt-to-prompt) completion. We combined data from three EMA studies examining mental health difficulties (N = 103; 10,656 prompts; 7144 completed), using multilevel models and machine learning to determine how well we can predict prompt-to-prompt completion and which variables are most important. The two most important variables in prompt-to-prompt completion were hours since the last prompt and time in study. Psychological variables added little predictive validity; similarly, trait-level SI demonstrated a small effect on prompt-to-prompt completion. Our study showed how study-level characteristics can be used to explain prompt-to-prompt compliance rates in EMA research, highlighting the potential for developing adaptive assessment schedules to improve compliance.

Person-specific dynamics between negative emotions and suicidal thoughts

INTRODUCTION

Recent technology has enabled researchers to collect ecological momentary assessments (EMA) to examine within-person correlates of suicidal thoughts. Prior studies examined generalized temporal dynamics of emotions and suicidal thinking over brief periods, but it is not yet known how variable these processes are across people.

METHOD

We use data EMA data delivered over two weeks with youth/young adults (N = 60) who reported past year self-injurious thoughts/behaviors. We used group iterative multiple model estimation (GIMME) to model group- and person-specific associations of negative emotions (i.e., fear, sadness, shame, guilt, and anger) and suicidal thoughts.

RESULTS

29 participants (48.33%) reported at least one instance of a suicidal thought and were included in GIMME models. In group level models, we consistently observed autoregressive effects for suicidal thoughts (e.g., earlier thoughts predicting later thoughts), although the magnitude and direction of this link varied from person-to-person. Among emotions, sadness was most frequently associated with contemporaneous suicidal thoughts, but this was evident for less than half of the sample, while other emotional correlates of suicidal thoughts broadly differed across people. No emotion variable was linked to future suicidal thoughts in >14% of the sample, CONCLUSIONS: Emotion-based correlates of suicidal thoughts are heterogeneous across people. Better understanding of the individual-level pathways maintaining suicidal thoughts/behaviors may lead to more effective, personalized interventions.

Predicting Lifetime Suicide Attempts in a Community Sample of Adolescents Using Machine Learning Algorithms

Suicide is a major global health concern and a prominent cause of death in adolescents. Previous research on suicide prediction has mainly focused on clinical or adult samples. To prevent suicides at an early stage, however, it is important to screen for risk factors in a community sample of adolescents. We compared the accuracy of logistic regressions, elastic net regressions, and gradient boosting machines in predicting suicide attempts by 17-year-olds in the Millennium Cohort Study (N = 7,347), combining a large set of self- and other-reported variables from different categories. Both machine learning algorithms outperformed logistic regressions and achieved similar balanced accuracies (.76 when using data 3 years before the self-reported lifetime suicide attempts and .85 when using data from the same measurement wave). We identified essential variables that should be considered when screening for suicidal behavior. Finally, we discuss the usefulness of complex machine learning models in suicide prediction.

Using GIMME to model the emotional context of suicidal ideation based on clinical data: From research to clinical practice

Research and clinical experience highlight the variability of suicidal ideation (SI) within and between individuals. Although the idiographic emotional contexts in which SI occurs may offer explanations for its dynamic nature, most statistical methods focus on nomothetic patterns, making it difficult to advance our understanding of SI. Furthermore, the gap between nomothetic methods and a need for idiographic understanding of SI poses challenges to translating empirical knowledge into individualized clinical treatment. Group iterative multiple model estimation (GIMME) is a method that may bridge the idiographic-nomothetic divide by analyzing temporal relationships among a network of variables at both group- and individual-levels. This study explored the feasibility and clinical utility of GIMME applied to examine the relationships between various emotions and SI among individuals with borderline personality disorder who underwent Dialectical Behavior Therapy. We present graphic outputs that emerged throughout treatment and discuss how they could aid clinical assessment and case formulation (ClinicalTrials.gov Identifier: NCT03123198.).

Characterizing heterogeneity in early adolescent reward networks and individualized associations with behavioral and clinical outcomes

Associations between connectivity networks and behavioral outcomes such as depression are typically examined by comparing average networks between known groups. However, neural heterogeneity within groups may limit the ability to make inferences at the individual level as qualitatively distinct processes across individuals may be obscured in group averages. This study characterizes the heterogeneity of effective connectivity reward networks among 103 early adolescents and examines associations between individualized features and multiple behavioral and clinical outcomes. To characterize network heterogeneity, we used extended unified structural equation modeling to identify effective connectivity networks for each individual and an aggregate network. We found that an aggregate reward network was a poor representation of individuals, with most individual-level networks sharing less than 50% of the group-level network paths. We then used Group Iterative Multiple Model Estimation to identify a group-level network, subgroups of individuals with similar networks, and individual-level networks. We identified three subgroups that appear to reflect differences in network maturity, but this solution had modest validity. Finally, we found numerous associations between individual-specific connectivity features and behavioral reward functioning and risk for substance use disorders. We suggest that accounting for heterogeneity is necessary to use connectivity networks for inferences precise to the individual.

The Detection of Acute Risk of Self-injury Project: Protocol for an Ecological Momentary Assessment Study Among Individuals Seeking Treatment

BACKGROUND

Nonsuicidal self-injury (NSSI) is a major mental health concern. Despite increased research efforts on establishing the prevalence and correlates of the presence and severity of NSSI, we still lack basic knowledge of the course, predictors, and relationship of NSSI with other self-damaging behaviors in daily life. Such information will be helpful for better informing mental health professionals and allocating treatment resources. The DAILY (Detection of Acute rIsk of seLf-injurY) project will address these gaps among individuals seeking treatment.

OBJECTIVE

This protocol paper presents the DAILY project's aims, design, and materials used. The primary objectives are to advance understanding of (1) the short-term course and contexts of elevated risk for NSSI thoughts, urges, and behavior; (2) the transition from NSSI thoughts and urges to NSSI behavior; and (3) the association of NSSI with disordered eating, substance use, and suicidal thoughts and behaviors. A secondary aim is to evaluate the perspectives of individuals seeking treatment and mental health professionals regarding the feasibility, scope, and utility of digital self-monitoring and interventions that target NSSI in daily life.

METHODS

The DAILY project is funded by the Research Foundation Flanders (Belgium). Data collection involves 3 phases: a baseline assessment (phase 1), 28 days of ecological momentary assessment (EMA) followed by a clinical session and feedback survey (phase 2), and 2 follow-up surveys and an optional interview (phase 3). The EMA protocol consists of regular EMA surveys (6 times per day), additional burst EMA surveys spaced at a higher frequency when experiencing intense NSSI urges (3 surveys within 30 minutes), and event registrations of NSSI behavior. The primary outcomes are NSSI thoughts, NSSI urges, self-efficacy to resist NSSI, and NSSI behavior, with disordered eating (restrictive eating, binge eating, and purging), substance use (binge drinking and smoking cannabis), and suicidal thoughts and behaviors surveyed as secondary outcomes. The assessed predictors include emotions, cognitions, contextual information, and social appraisals.

RESULTS

We will recruit approximately 120 individuals seeking treatment aged 15 to 39 years from mental health services across the Flanders region of Belgium. Recruitment began in June 2021 and data collection is anticipated to conclude in August 2023.

CONCLUSIONS

The findings of the DAILY project will provide a detailed characterization of the short-term course and patterns of risk for NSSI and advance understanding of how, why, and when NSSI and other self-damaging behaviors unfold among individuals seeking treatment. This will inform clinical practice and provide the scientific building blocks for novel intervention approaches outside of the therapy room that support people who self-injure in real time.

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID)

DERR1-10.2196/46244.

The use of advanced technology and statistical methods to predict and prevent suicide

In the past decade, two themes have emerged across suicide research. First, according to meta-analyses, the ability to predict and prevent suicidal thoughts and behaviours is weaker than would be expected for the size of the field. Second, review and commentary papers propose that technological and statistical methods (such as smartphones, wearables, digital phenotyping and machine learning) might become solutions to this problem. In this Review, we aim to strike a balance between the pessimistic picture presented by these meta-analyses and the optimistic picture presented by review and commentary papers about the promise of advanced technological and statistical methods to improve the ability to understand, predict and prevent suicide. We divide our discussion into two broad categories. First, we discuss the research aimed at assessment, with the goal of better understanding or more accurately predicting suicidal thoughts and behaviours. Second, we discuss the literature that focuses on prevention of suicidal thoughts and behaviours. Ecological momentary assessment, wearables and other technological and statistical advances hold great promise for predicting and preventing suicide, but there is much yet to do.

Suicidal urges and attempted suicide at multiple time scales in borderline personality disorder

BACKGROUND

There is strong evidence for an enduring suicidal diathesis among individuals with a history of suicide attempts, particularly among people diagnosed with borderline personality disorder (BPD). However, the progression of suicidal crises among people predisposed to suicidal behavior remains poorly understood.

METHODS

Via multilevel structural equation modeling we tested the hypothesis that a history of attempted suicide predicts a stronger dynamic link between affect and impulsivity with suicidal ideation (i.e., suicidal urges) - both moment-to-moment and day-to-day. 153 patients diagnosed with BPD, 105 of whom had a history of medically serious suicide attempts completed a 21-day ecological momentary assessment protocol (17,926 total assessments).

RESULTS

Individuals with higher average levels of negative affect reported more suicidal thoughts. Moments characterized by more negative affect, hostility, impulsivity, and less positive affect were also characterized by elevated suicidal ideation. For hostility and positive affect, these significant links generalized to the daily level. At the same time, for negative affect and hostility the within-person coupling was stronger among attempters in comparison to non-attempters, and these effects did not significantly differ across timescales.

LIMITATIONS

Follow-up studies replicating our findings of the dysregulation-suicidality nexus in clinically more diverse samples are needed.

CONCLUSIONS

The diathesis for suicidal behavior manifests in tighter dynamic links between negative affect or hostility and suicidal ideation. Because these within-person links were amplified in attempters compared to non-attempters, differential coupling patterns may index potentially lethal processes that generalize beyond BPD reflecting distinct diathesis components.

Preparing a Workforce of Care Coordinators to Address Patient Mental Health Needs in the Digital Age: Training and Needs Identification

Introduction

Care coordinators (CCs) are specialized healthcare providers and often the primary point of contact for patients with multiple medical and mental health comorbidities in integrated healthcare settings. Prior work shows CCs have lower comfort addressing mental health than physical health concerns. Digital mental health interventions can support CCs' management of patient mental health needs, but training gaps must be addressed prior to a digital mental health intervention's implementation.

Methods

As part of a quality improvement initiative, a 1-hour training focused on the assessment and management of depression and suicide-related thoughts and behaviors was delivered to CCs within a large midwestern healthcare system's Division of Ambulatory Care Coordination. CCs completed online surveys prior to and following the training.

Conclusion

Training resulted in increased comfort working with clinical populations, including patients who experience suicide-related thoughts and behaviors. Gains around screening for suicide risk were modest. Brief trainings for CCs can address training gaps, however, ongoing training and case consultation may also be indicated.

Idiographic Dynamics between Suicide Ideation and Depression, Anxiety and Posttraumatic Stress Symptoms in Persons Living with HIV: A Pilot Study

BACKGROUND

Given that suicide ideation (SI) fluctuates drastically over short periods of time and is heterogenous across individuals, idiographic suicide research is warranted. In this pilot study, we used intensive ecological momentary assessment (EMA) to examine whether anxiety, depression, and PTSD symptoms on a given day predicted next-day SI on a person-to-person basis.

METHODS

PLWH (N = 10) with past-month SI completed daily randomly assessed ratings of suicidal urges using the Suicide-Visual Analogue Scale (S-VAS) and daily assessed ratings of anxiety, depression, and PTSD symptoms for 28 days. We used N = 1 Dynamic Structural Equation Modeling to test whether depression, anxiety or PTSD symptoms in the prior day predicted next-day S-VAS for each individual.

RESULTS

Across all participants, S-VAS on a given day was not predicted by prior-day anxiety, PTSD symptoms or S-VAS. In one participant, higher depression symptoms predicted lower next-day S-VAS.

CONCLUSIONS

Daily-level data may be insufficient to predict near-term increases in suicide risk based on anxiety, depression, or PTSD symptoms in PLWH. These findings suggest the importance of finer-grained assessments (e.g., assessing suicide risk and its correlates multiple times per day) to better understand changes in suicide risk over time among PLWH.

Prospective associations of text-message-based sentiment with symptoms of depression, generalized anxiety, and social anxiety

OBJECTIVE

Language patterns may elucidate mechanisms of mental health conditions. To inform underlying theory and risk models, we evaluated prospective associations between in vivo text messaging language and differential symptoms of depression, generalized anxiety, and social anxiety.

METHODS

Over 16 weeks, we collected outgoing text messages from 335 adults. Using Linguistic Inquiry and Word Count (LIWC), NRC Emotion Lexicon, and previously established depression and stress dictionaries, we evaluated the degree to which language features predict symptoms of depression, generalized anxiety, or social anxiety the following week using hierarchical linear models. To isolate the specificity of language effects, we also controlled for the effects of the two other symptom types.

RESULTS

We found significant relationships of language features, including personal pronouns, negative emotion, cognitive and biological processes, and informal language, with common mental health conditions, including depression, generalized anxiety, and social anxiety (ps < .05). There was substantial overlap between language features and the three mental health outcomes. However, after controlling for other symptoms in the models, depressive symptoms were uniquely negatively associated with language about anticipation, trust, social processes, and affiliation (βs: -.10 to -.09, ps < .05), whereas generalized anxiety symptoms were positively linked with these same language features (βs: .12-.13, ps < .001). Social anxiety symptoms were uniquely associated with anger, sexual language, and swearing (βs: .12-.13, ps < .05).

CONCLUSION

Language that confers both common (e.g., personal pronouns and negative emotion) and specific (e.g., affiliation, anticipation, trust, and anger) risk for affective disorders is perceptible in prior week text messages, holding promise for understanding cognitive-behavioral mechanisms and tailoring digital interventions.

Self-injurious thoughts and behaviors and alterations in positive valence systems: A systematic review of the literature

Self-injurious thoughts and behaviors (SITBs), which include suicidal ideation (SI), suicide attempts (SA), and nonsuicidal self-injury (NSSI), are prevalent and associated with impairments in functioning and elevated risk of suicide deaths. Preventing suicide is a complex problem, with numerous systems likely contributing to the onset and maintenance of SITBs, and there is a critical need to identify more precise predictors of risk. Positive valence systems (PVS) are an understudied domain with promise for improving understanding of risk processes underlying SITBs. In this systematic review, we evaluate the evidence for the potential role of altered PVS function in SI, SA, and/or NSSI, including alterations in reward responsiveness, learning, and valuation assessed through behavioral, physiological and circuit measures. Results provide preliminary support for associations between distinct aspects of PVS function and alterations in SITBs. Specifically, SI appears to be characterized by low reward responsiveness, whereas little research has examined reward responsiveness in SA, and NSSI has been characterized by hyper-responsiveness to rewards. Alterations in reward learning and valuation are commonly examined in SA, with some evidence that they may be more strongly associated with attempts than SI or NSSI. At the same time, the literature is limited in that some constructs are commonly examined in one form of SITBs but not others. Further, research is predominantly cross-sectional and focused on adults, raising questions about the role of PVS function in developmental pathways to SITBs. We conclude by integrating the research to date and highlighting promising directions for future research.

A meta-analysis on the affect regulation function of real-time self-injurious thoughts and behaviours

Prominent theories suggest that self-injurious thoughts and behaviours are negatively reinforced by decreased negative affect. The present meta-analysis quantifies effects from intensive longitudinal studies measuring negative affect and self-injurious thoughts and behaviours. We obtained data from 38 of the 79 studies (48%, 22 unique datasets) involving N = 1,644 participants (80% female, 75% white). Individual-participant data meta-analyses revealed changes in affect pre/post self-injurious thoughts and behaviours. In antecedent models, results supported increased negative affect before nonsuicidal self-injurious behaviour (k = 14, 95% CI 0.09 to 0.31) and suicidal thoughts (k = 14, 95% CI 0.03 to 0.19). For consequence models, negative affect was reduced following nonsuicidal self-injurious thoughts (k = 6, 95% CI -0.79 to -0.44), nonsuicidal self-injurious behaviours (k = 14, 95% CI -0.73 to -0.19) and suicidal thoughts (k = 13, 95% CI -0.79 to -0.23). Findings, which were not moderated by sampling strategies or sample composition, support the affect regulation function of self-injurious thoughts and behaviours.

Can we rewire criminal mind via non-invasive brain stimulation of prefrontal cortex? Insights from clinical, forensic and social cognition studies

Non-compliance with social and legal norms and regulations represents a high burden for society. Social cognition deficits are frequently called into question to explain criminal violence and rule violations in individuals diagnosed with antisocial personality disorder (APD), borderline personality disorder (BPD), and psychopathy. In this article, we proposed to consider the potential benefits of non-invasive brain stimulation (NIBS) to rehabilitate forensic population. We focused on the effects of NIBS of the prefrontal cortex, which is central in social cognition, in modulating aggression and impulsivity in clinical disorders, as well as in forensic population. We also addressed the effect of NIBS on empathy, and theory of mind in non-clinical and/or prison population. The reviewed data provide promising evidence on the beneficial effect of NIBS on aggression/impulsivity dyscontrol and social cognitive functions, suggesting its relevance in promoting reintegration of criminals into society.

Just-in-Time Adaptive Interventions for Suicide Prevention: Promise, Challenges, and Future Directions

The suicide rate (currently 14 per 100,000) has barely changed in the United States over the past 100 years. There is a need for new ways of preventing suicide. Further, research has revealed that suicidal thoughts and behaviors and the factors that drive them are dynamic, heterogeneous, and interactive. Most existing interventions for suicidal thoughts and behaviors are infrequent, not accessible when most needed, and not systematically tailored to the person using their own data (e.g., from their own smartphone). Advances in technology offer an opportunity to develop new interventions that may better match the dynamic, heterogeneous, and interactive nature of suicidal thoughts and behaviors. Just-In-Time Adaptive Interventions (JITAIs), which use smartphones and wearables, are designed to provide the right type of support at the right time by adapting to changes in internal states and external contexts, offering a promising pathway toward more effective suicide prevention. In this review, we highlight the potential of JITAIs for suicide prevention, challenges ahead (e.g., measurement, ethics), and possible solutions to these challenges.