JMIR Publications

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  Depression and Mood Disorders;...

  May 2, 2024

  Emerging Trends of Self-Harm Using Sodium Nitrite in an Online Suicide Community: Observational Study Using Natural Language Processing Analysis

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  Authors List:

  • Sudeshna Das  
  • Drew Walker  
  • Swati Rajwal  
  • Sahithi Lakamana  
  • Steven A Sumner  
  • Karin A Mack  
  • Wojciech Kaczkowski  
  • Abeed Sarker  

  Abstract:

  Background: There is growing concern around the use of sodium nitrite (SN) as an emerging means of suicide, particularly among younger people. Given limited information on the topic from traditional public health surveillance sources, we studied posts made to a suicide discussion online forum, ‘Sanctioned Suicide’, a primary source of information on use and procurement of SN. Objective: This study aims to determine the trends in SN purchase and usage, as obtained from data mining of the online forum ‘Sanctioned Suicide’. We also determine substances and topics commonly co-occurring with SN, and the geographical distribution of users and sources of SN. Methods: We collected all publicly available posts on Sanctioned Suicide from its inception in March 2018 to October 2022. Using data-driven methods including natural language processing and machine learning, we analyzed the trends in SN mentions over time, including the locations of SN consumers, and the sources from which SN are procured. We developed a transformer-based source/location classifier to determine the geographical distribution of the sources of SN. Results: Posts pertaining to SN show a rise in popularity and statistically significant correlations with real-life usage of SN with suicidal intent when compared to data from CDC Wonder (⍴=0.7266, P<.001) and the National Poison Data System (⍴=0.86587, P=.001). We observed frequent co-mentions of antiemetics, benzodiazepines, and acid regulators with SN. Our proposed machine learning based source/location classifier is able to detect potential sources of SN with an accuracy of 72.92%, and showed consumption in the United States and elsewhere. Conclusions: Vital information about SN and other emerging mechanisms of suicide can be obtained from online forums.

  • JMIR Ment Health 2024;11(1):e53730

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  Depression and Mood Disorders;...

  May 1, 2024

  Asynchronous Versus Synchronous Screening for Depression and Suicidality in a Primary Health Care System: Quality Improvement Study

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  Authors List:

  • Amelia Sattler  
  • Julia Dunn  
  • Marleni Albarran  
  • Charlotte Berger  
  • Ana Calugar  
  • John Carper  
  • Lalitha Chirravuri  
  • Nadine Jawad  
  • Mira Zein  
  • Mark McGovern  

  Abstract:

  Background: Despite being a debilitating, costly, and potentially life-threatening condition, depression is often underdiagnosed and undertreated. Pre-visit Patient Health Questionnaire–9s (PHQ-9) may help primary care health systems identify symptoms of severe depression and prevent suicide through early intervention. Little is known about the impact of pre-visit web-based PHQ-9s on patient care and safety. Objective: Investigate differences among patient characteristics and provider clinical responses for patients who complete a web-based (asynchronous) versus in-clinic (synchronous) PHQ-9. Methods: This quality improvement study was conducted at 33 clinic sites across two health systems in Northern California from November 1, 2020 to May 31, 2021 and evaluated 1,683 (0.9% of total PHQs completed) records of patients endorsing thoughts that they would be better off dead or of self-harm (Q#9) following implementation of a depression screening program that included automated electronic pre-visit PHQ-9 distribution. Patient demographics and providers’ clinical response (suicide risk assessment, triage nurse connection, medication management, electronic consultation with psychiatrist, referral to social worker or psychiatrist) were compared for patients with asynchronous versus synchronous PHQ-9 completion. Results: Of the 1,683 patients (63.7% female, 80.5% non-Hispanic, and 51.6% White), Hispanic and Latino patients were 40% less likely to complete a PHQ-9 asynchronously (OR=0.6; 95% CI: 0.45-0.8; p<0.001). Patients with Medicare insurance were 36% (OR=0.64; 95% CI: 0.51-0.79) less likely to complete a PHQ-9 asynchronously than patients with private insurance. Those with moderate to severe depression were 1.61 times more likely (95% CI: 1.21-2.15; p=0.001) to complete a PHQ-9 asynchronously than those with no or mild symptoms. Patients who completed a PHQ-9 asynchronously were twice as likely to complete a Columbia-Suicide Severity Rating Scale (OR=2.41; 95% CI: 1.89-3.06; p<0.001) and 77% less likely to receive a referral to psychiatry (OR=0.23; 95% CI: 0.16-0.34; p<0.001). Those who endorsed Q#9 “more than half the days” (OR=1.62; 95% CI: 1.06-2.48) and “nearly every day” (OR=2.38; 95% CI: 1.38-4.12) were more likely to receive a referral to psychiatry than those who endorsed Q#9 “several days” (p=0.002). Conclusions: Shifting depression screening from in-clinic to pre-visit led to a dramatic increase in PHQ-9 completion without sacrificing patient safety. Asynchronous PHQ-9s can decrease workload on frontline clinical team members, increase patient self-reporting, and elicit more intentional clinical responses from providers. Observed disparities will inform future improvement efforts.

  • JMIR Ment Health 2024;11(1):e50192

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  Problematic Internet Use, Online...

  Apr 29, 2024

  Digital Phenotypes for Early Detection of Internet Gaming Disorder in Adolescent Students: Explorative Data-Driven Study

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  Authors List:

  • Kwangsu Cho  
  • Minah Kim  
  • Youngeun Cho  
  • Ji-Won Hur  
  • Do Hyung Kim  
  • Seonghyeon Park  
  • Sunghyun Park  
  • Moonyoung Jang  
  • Chang-Gun Lee  
  • Jun Soo Kwon  

  Abstract:

  Background: Limited awareness, social stigma, and access to mental health professionals hinder early detection and intervention of internet gaming disorder (IGD), which has emerged as a significant concern among young individuals. Prevalence estimates vary between 0.7% and 15.6%, and its recognition in the International Classification of Diseases, 11th Revision and Diagnostic and Statistical Manual of Mental Disorders, 5th Edition underscores its impact on academic functioning, social isolation, and mental health challenges. Objective: This study aimed to uncover digital phenotypes for the early detection of IGD among adolescents in learning settings. By leveraging sensor data collected from student tablets, the overarching objective is to incorporate these digital indicators into daily school activities to establish these markers as a mental health screening tool, facilitating the early identification and intervention for IGD cases. Methods: A total of 168 voluntary participants were engaged, consisting of 85 students with IGD and 83 students without IGD. There were 53% (89/168) female and 47% (79/168) male individuals, all within the age range of 13-14 years. The individual students learned their Korean literature and mathematics lessons on their personal tablets, with sensor data being automatically collected. Multiple regression with bootstrapping and multivariate ANOVA were used, prioritizing interpretability over predictability, for cross-validation purposes. Results: A negative correlation between IGD Scale (IGDS) scores and learning outcomes emerged (r₁₆₆=–0.15; P=.047), suggesting that higher IGDS scores were associated with lower learning outcomes. Multiple regression identified 5 key indicators linked to IGD, explaining 23% of the IGDS score variance: stroke acceleration (β=.33; P<.001), time interval between keys (β=–0.26; P=.01), word spacing (β=–0.25; P<.001), deletion (β=–0.24; P<.001), and horizontal length of strokes (β=–0.21; P=.02). Multivariate ANOVA cross-validated these findings, revealing significant differences in digital phenotypes between potential IGD and non-IGD groups. The average effect size, measured by Cohen d, across the indicators was 0.40, indicating a moderate effect. Notable distinctions included faster stroke acceleration (Cohen d=0.68; P=<.001), reduced word spacing (Cohen d=.57; P=<.001), decreased deletion behavior (Cohen d=0.33; P=.04), and longer horizontal strokes (Cohen d=0.34; P=.03) in students with potential IGD compared to their counterparts without IGD. Conclusions: The aggregated findings show a negative correlation between IGD and learning performance, highlighting the effectiveness of digital markers in detecting IGD. This underscores the importance of digital phenotyping in advancing mental health care within educational settings. As schools adopt a 1-device-per-student framework, digital phenotyping emerges as a promising early detection method for IGD. This shift could transform clinical approaches from reactive to proactive measures.

  • JMIR Ment Health 2024;11(1):e50259

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  Methods and New Tools in Mental...

  Apr 25, 2024

  Remote Short Sessions of Heart Rate Variability Biofeedback Monitored With Wearable Technology: Open-Label Prospective Feasibility Study

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  Authors List:

  • Robert P Hirten  
  • Matteo Danieletto  
  • Kyle Landell  
  • Micol Zweig  
  • Eddye Golden  
  • Renata Pyzik  
  • Sparshdeep Kaur  
  • Helena Chang  
  • Drew Helmus  
  • Bruce E Sands  
  • Dennis Charney  
  • Girish Nadkarni  
  • Emilia Bagiella  
  • Laurie Keefer  
  • Zahi A Fayad  

  Abstract:

  Background: Heart rate variability (HRV) biofeedback is often performed with structured education, laboratory-based assessments, and practice sessions. It has been shown to improve psychological and physiological function across populations. However, a means to remotely use and monitor this approach would allow for wider use of this technique. Advancements in wearable and digital technology present an opportunity for the widespread application of this approach. Objective: The primary aim of the study was to determine the feasibility of fully remote, self-administered short sessions of HRV-directed biofeedback in a diverse population of health care workers (HCWs). The secondary aim was to determine whether a fully remote, HRV-directed biofeedback intervention significantly alters longitudinal HRV over the intervention period, as monitored by wearable devices. The tertiary aim was to estimate the impact of this intervention on metrics of psychological well-being. Methods: To determine whether remotely implemented short sessions of HRV biofeedback can improve autonomic metrics and psychological well-being, we enrolled HCWs across 7 hospitals in New York City in the United States. They downloaded our study app, watched brief educational videos about HRV biofeedback, and used a well-studied HRV biofeedback program remotely through their smartphone. HRV biofeedback sessions were used for 5 minutes per day for 5 weeks. HCWs were then followed for 12 weeks after the intervention period. Psychological measures were obtained over the study period, and they wore an Apple Watch for at least 7 weeks to monitor the circadian features of HRV. Results: In total, 127 HCWs were enrolled in the study. Overall, only 21 (16.5%) were at least 50% compliant with the HRV biofeedback intervention, representing a small portion of the total sample. This demonstrates that this study design does not feasibly result in adequate rates of compliance with the intervention. Numerical improvement in psychological metrics was observed over the 17-week study period, although it did not reach statistical significance (all P>.05). Using a mixed effect cosinor model, the mean midline-estimating statistic of rhythm (MESOR) of the circadian pattern of the SD of the interbeat interval of normal sinus beats (SDNN), an HRV metric, was observed to increase over the first 4 weeks of the biofeedback intervention in HCWs who were at least 50% compliant. Conclusions: In conclusion, we found that using brief remote HRV biofeedback sessions and monitoring its physiological effect using wearable devices, in the manner that the study was conducted, was not feasible. This is considering the low compliance rates with the study intervention. We found that remote short sessions of HRV biofeedback demonstrate potential promise in improving autonomic nervous function and warrant further study. Wearable devices can monitor the physiological effects of psychological interventions.

  • JMIR Ment Health 2024;11(1):e55552

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  Virtual Reality Interventions in...

  Apr 25, 2024

  Immersive Technologies for Depression Care: Scoping Review

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  Authors List:

  • C Mahony Reategui-Rivera  
  • David Villarreal-Zegarra  
  • Kelly De La Cruz-Torralva  
  • Paquita Díaz-Sánchez  
  • Joseph Finkelstein  

  Abstract:

  Background: Depression significantly impacts quality of life, affecting approximately 280 million people worldwide. However, only 16.5% of those affected receive treatment, indicating a substantial treatment gap. Immersive technologies (IMTs) such as virtual reality (VR) and augmented reality offer new avenues for treating depression by creating immersive environments for therapeutic interventions. Despite their potential, significant gaps exist in the current evidence regarding the design, implementation, and use of IMTs for depression care. Objective: We aim to map the available evidence on IMT interventions targeting depression treatment. Methods: This scoping review followed a methodological framework, and we systematically searched databases for studies on IMTs and depression. The focus was on randomized clinical trials involving adults and using IMTs. The selection and charting process involved multiple reviewers to minimize bias. Results: The search identified 16 peer-reviewed articles, predominantly from Europe (n=10, 63%), with a notable emphasis on Poland (n=9, 56%), which contributed to more than half of the articles. Most of the studies (9/16, 56%) were conducted between 2020 and 2021. Regarding participant demographics, of the 16 articles, 5 (31%) exclusively involved female participants, and 7 (44%) featured participants whose mean or median age was >60 years. Regarding technical aspects, all studies focused on VR, with most using stand-alone VR headsets (14/16, 88%), and interventions typically ranging from 2 to 8 weeks, predominantly in hospital settings (11/16, 69%). Only 2 (13%) of the 16 studies mentioned using a specific VR design framework in planning their interventions. The most frequently used therapeutic approach was Ericksonian psychotherapy, used in 56% (9/16) of the studies. Notably, none of the articles reported using an implementation framework or identified barriers and enablers to implementation. Conclusions: This scoping review highlights the growing interest in using IMTs, particularly VR, for depression treatment but emphasizes the need for more inclusive and comprehensive research. Future studies should explore varied therapeutic approaches and cost-effectiveness as well as the inclusion of augmented reality to fully realize the potential of IMTs in mental health care.

  • JMIR Ment Health 2024;11(1):e56056

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  Innovations in Mental Health Systems

  Apr 23, 2024

  A Web-Based and Mobile Intervention Program Using a Spaced Education Approach for Workplace Mental Health Literacy: Cluster Randomized Controlled Trial

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  Authors List:

  • Lawrence T Lam  
  • Mary K P Lam  

  Abstract:

  Background: Workplace mental health is one of the global health concerns. Preventing mental health problems and promoting mental well-being in the workplace are important aspects of ensuring population health. This can be achieved by improving the mental health literacy of the public, particularly workers. Objective: This study aims to evaluate the purposely built mHealth platform as a health-related App. It also aims to examine the efficacy of a mHealth psychoeducation program on mental health literacy in the workplace. The main interest of this report is the immediate and medium-term effect of the program on the mental health literacy of workers. Methods: This phase III wait-listed cluster randomised controlled trial recruited 456 employees of specific industries with high levels of work-related stress. A separate sample of 70 individuals was used for the evaluation of the mHealth platform. The Australian National Mental Health Literacy and Stigma Survey and the Mobile Apps Rating Scale (MARS) were used to assess mental health literacy and to evaluate the App. For the trial and follow-up data, they were analysed by the Generalised Linear Latent And Mixed Model (GLLAMM) with adjustments for the clustering effect of work sites and repeated measures. Results: Evaluation of the mHealth program, using a sample of 70 respondents, resulted in average scores of the four major domains ranging from 3.8 to 4.2, with Engagement having the lowest score (s.d.=0.6). Of the 456 participants of the trial, 236 responded to the follow-up survey. Most MHL outcomes obtained significant results immediately after the intervention and across time. After adjusting for the clustering effect, the post-intervention weighted mean scores were significantly higher in the intervention group for correct recognition of a mental problem, help-seeking, and stigmatisation, in comparison to the controls with 0.2 (s.e.=0.1), 0.9 (s.e.=0.2), 1.8 (s.e.=0.4) respectively. There was a significant increase in help-seeking intention (P=0.014) and a reduction in stigmatisation and social distancing (P<0.001) at a 3-month follow-up. Conclusions: The mHealth platform is evaluated with satisfactory performance in terms of functionality, aesthetics, information content, and utility in enhancing mental health literacy. The psychoeducation intervention program, using this platform, has immediate and medium-term effects of retaining and improving mental health literacy. It is anticipated that ongoing development in Digital Health will provide great benefits in improving the mental health of the global population. Clinical Trial: The trial was registered with the Australian New Zealand Clinical Trials Registry (ANZCTR, Registration number: ACTRN12619000464167).

  • JMIR Ment Health 2024;11(1):e51791

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  Anxiety and Stress Disorders

  Apr 19, 2024

  Testing the Efficacy of a Brief, Self-Guided Mindfulness Ecological Momentary Intervention on Emotion Regulation and Self-Compassion in Social Anxiety...

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  Authors List:

  • Nur Hani Zainal  
  • Hui Han Tan  
  • Ryan Yee Shiun Hong  
  • Michelle Gayle Newman  

  Abstract:

  Background: Theories propose that brief, mobile, self-guided mindfulness ecological momentary interventions (MEMIs) could enhance emotion regulation (ER) and self-compassion. Such changes are posited to be mechanisms of change. However, rigorous tests of these theories have not been conducted. Objective: In this assessor-blinded, parallel-group randomized controlled trial, we aimed to test these theories in social anxiety disorder (SAD). Methods: Participants with SAD (defined as having a prerandomization cut-off score ≥20 on the Social Phobia Inventory self-report) were randomized to a 14-day fully self-guided MEMI (96/191, 50.3%) or self-monitoring app (95/191, 49.7%) arm. They completed web-based self-reports of 6 clinical outcome measures at prerandomization, 15-day postintervention (administered the day after the intervention ended), and 1-month follow-up time points. ER and self-compassion were assessed at preintervention and 7-day midintervention time points. Multilevel modeling determined the efficacy of MEMI on ER and self-compassion domains from pretrial to midintervention time points. Bootstrapped parallel multilevel mediation analysis examined the mediating role of pretrial to midintervention ER and self-compassion domains on the efficacy of MEMI on 6 clinical outcomes. Results: Participants demonstrated strong compliance, with 78% (149/191) engaging in at least 80% of the MEMI and self-monitoring prompts. MEMI was more efficacious than the self-monitoring app in decreasing ER goal–directed behavior difficulties (between-group Cohen d=−0.24) and lack of emotional clarity (Cohen d=0.16) and increasing self-compassion social connectedness (Cohen d=0.19), nonidentification with emotions (Cohen d=0.16), and self-kindness (Cohen d=0.19) from pretrial to midintervention time points. The within-group effect sizes from pretrial to midintervention were larger in the MEMI arm than in the self-monitoring app arm (ER goal–directed behavior difficulties: Cohen d=−0.73 vs −0.29, lack of emotional clarity: Cohen d=−0.39 vs −0.21, self-compassion domains of social connectedness: Cohen d=0.45 vs 0.19, nonidentification with emotions: Cohen d=0.63 vs 0.48, and self-kindness: Cohen d=0.36 vs 0.10). Self-monitoring, but not MEMI, alleviated ER emotional awareness issues (between-group Cohen d=0.11 and within-group: Cohen d=−0.29 vs −0.13) and reduced self-compassion acknowledging shared human struggles (between-group Cohen d=0.26 and within-group: Cohen d=−0.23 vs 0.13). No ER and self-compassion domains were mediators of the effect of MEMI on SAD symptoms (P=.07-<.99), generalized anxiety symptoms (P=.16-.98), depression severity (P=.20-.94), repetitive negative thinking (P=.12-.96), and trait mindfulness (P=.18-.99) from pretrial to postintervention time points. Similar nonsignificant mediation effects emerged for all of these clinical outcomes from pretrial to 1-month follow-up time points (P=.11-.98). Conclusions: Brief, fully self-guided, mobile MEMIs efficaciously increased specific self-compassion domains and decreased ER difficulties associated with goal pursuit and clarity of emotions from pretrial to midintervention time points. Higher-intensity MEMIs may be required to pinpoint the specific change mechanisms in ER and self-compassion domains of SAD. Trial Registration: Open Science Framework (OSF) Registries; osf.io/m3kxz https://osf.io/m3kxz

  • JMIR Ment Health 2024;11(1):e53712

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  Depression and Mood Disorders;...

  Apr 18, 2024

  Time-Varying Network Models for the Temporal Dynamics of Depressive Symptomatology in Patients With Depressive Disorders: Secondary Analysis of Longitudinal...

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  Authors List:

  • Björn Sebastian Siepe  
  • Christian Sander  
  • Martin Schultze  
  • Andreas Kliem  
  • Sascha Ludwig  
  • Ulrich Hegerl  
  • Hanna Reich  

  Abstract:

  Background: As depression is highly heterogenous, an increasing number of studies investigate person-specific associations of depressive symptoms in longitudinal data. However, most studies in this area of research conceptualize symptom interrelations to be static and time invariant, which may lead to important temporal features of the disorder being missed. Objective: To reveal the dynamic nature of depression, we aimed to use a recently developed technique to investigate whether and how associations among depressive symptoms change over time. Methods: Using daily data (mean length 274, SD 82 d) of 20 participants with depression, we modeled idiographic associations among depressive symptoms, rumination, sleep, and quantity and quality of social contacts as dynamic networks using time-varying vector autoregressive models. Results: The resulting models showed marked interindividual and intraindividual differences. For some participants, associations among variables changed in the span of some weeks, whereas they stayed stable over months for others. Our results further indicated nonstationarity in all participants. Conclusions: Idiographic symptom networks can provide insights into the temporal course of mental disorders and open new avenues of research for the study of the development and stability of psychopathological processes.

  • JMIR Ment Health 2024;11(1):e50136

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  Depression and Mood Disorders;...

  Apr 15, 2024

  Examining the Efficacy of Extended Reality–Enhanced Behavioral Activation for Adults With Major Depressive Disorder: Randomized Controlled Trial

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  Authors List:

  • Margot Paul  
  • Kim Bullock  
  • Jeremy Bailenson  
  • David Burns  

  Abstract:

  Background: Major depressive disorder (MDD) is a global concern with increasing prevalence. While many evidence-based psychotherapies (EBPs) have been identified to treat MDD, there are numerous barriers to patients accessing them. Virtual reality (VR) has been used as a treatment enhancement for a variety of mental health disorders, but few studies have examined its clinical use in treating MDD. Behavioral activation (BA) is a simple yet effective and established first-line EBP for MDD that has the potential to be easily enhanced and adapted with VR technology. A previous report by our group explored the feasibility and acceptability of VR-enhanced BA in a small clinical proof-of-concept pilot. This study examines the clinical efficacy of a more immersive extended reality (XR)–enhanced BA (XR-BA) prototype. This is the first clinical efficacy test of an XR-BA protocol. Objective: This study examined whether XR-BA was feasible and efficacious in treating MDD in an ambulatory telemedicine clinic. Methods: A nonblinded between-subject randomized controlled trial compared XR-BA to traditional BA delivered via telehealth. The study used a previously established, brief 3-week, 4-session BA EBP intervention. The experimental XR-BA participants were directed to use a Meta Quest 2 (Reality Labs) VR headset to engage in simulated pleasant or mastery activities and were compared to a control arm, which used only real-life mastery or pleasant activities as between-session homework. The Patient Health Questionnaire (PHQ)–9 was the primary outcome measure. Independent-sample and paired-sample t tests (2-tailed) were used to determine statistical significance and confirmed using structural equation modeling. Results: Overall, 26 participants with MDD were randomized to receive either XR-BA (n=13, 50%) or traditional BA (n=13, 50%). The mean age of the 26 participants (n=6, 23% male; n=19, 73% female; n=1, 4% nonbinary or third gender) was 50.3 (SD 17.3) years. No adverse events were reported in either group, and no substantial differences in dropout rates or homework completion were observed. XR-BA was found to be statistically noninferior to traditional BA (t_18.6=−0.28; P=.78). Both the XR-BA (t₉=2.5; P=.04) and traditional BA (t₁₀=2.3; P=.04) arms showed a statistically significant decrease in PHQ-9 and clinical severity from the beginning of session 1 to the beginning of session 4. There was a significant decrease in PHQ-8 to PHQ-9 scores between the phone intake and the beginning of session 1 for the XR-BA group (t₁₁=2.6; P=.03) but not the traditional BA group (t₁₁=1.4; P=.20). Conclusions: This study confirmed previous findings that XR-BA may be a feasible, non-inferior, and acceptable enhancement to traditional BA. Additionally, there was evidence that supports the potential of XR to enhance expectation or placebo effects. Further research is needed to examine the potential of XR to improve access, outcomes, and barriers to MDD care. Trial Registration: ClinicalTrials.gov NCT05525390; https://clinicaltrials.gov/study/NCT05525390

  • JMIR Ment Health 2024;11(1):e52326

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  Theme Issue 2023 : Responsible...

  Apr 9, 2024

  Assessing the Alignment of Large Language Models With Human Values for Mental Health Integration: Cross-Sectional Study Using Schwartz’s Theory of Basic...

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  Authors List:

  • Dorit Hadar-Shoval  
  • Kfir Asraf  
  • Yonathan Mizrachi  
  • Yuval Haber  
  • Zohar Elyoseph  

  Abstract:

  Background: Large language models (LLMs) hold potential for mental health applications. However, their opaque alignment processes may embed biases that shape problematic perspectives. Evaluating the values embedded within LLMs that guide their decision-making have ethical importance. Schwartz’s theory of basic values (STBV) provides a framework for quantifying cultural value orientations and has shown utility for examining values in mental health contexts, including cultural, diagnostic, and therapist-client dynamics. Objective: This study aimed to (1) evaluate whether the STBV can measure value-like constructs within leading LLMs and (2) determine whether LLMs exhibit distinct value-like patterns from humans and each other. Methods: In total, 4 LLMs (Bard, Claude 2, Generative Pretrained Transformer [GPT]-3.5, GPT-4) were anthropomorphized and instructed to complete the Portrait Values Questionnaire—Revised (PVQ-RR) to assess value-like constructs. Their responses over 10 trials were analyzed for reliability and validity. To benchmark the LLMs’ value profiles, their results were compared to published data from a diverse sample of 53,472 individuals across 49 nations who had completed the PVQ-RR. This allowed us to assess whether the LLMs diverged from established human value patterns across cultural groups. Value profiles were also compared between models via statistical tests. Results: The PVQ-RR showed good reliability and validity for quantifying value-like infrastructure within the LLMs. However, substantial divergence emerged between the LLMs’ value profiles and population data. The models lacked consensus and exhibited distinct motivational biases, reflecting opaque alignment processes. For example, all models prioritized universalism and self-direction, while de-emphasizing achievement, power, and security relative to humans. Successful discriminant analysis differentiated the 4 LLMs’ distinct value profiles. Further examination found the biased value profiles strongly predicted the LLMs’ responses when presented with mental health dilemmas requiring choosing between opposing values. This provided further validation for the models embedding distinct motivational value-like constructs that shape their decision-making. Conclusions: This study leveraged the STBV to map the motivational value-like infrastructure underpinning leading LLMs. Although the study demonstrated the STBV can effectively characterize value-like infrastructure within LLMs, substantial divergence from human values raises ethical concerns about aligning these models with mental health applications. The biases toward certain cultural value sets pose risks if integrated without proper safeguards. For example, prioritizing universalism could promote unconditional acceptance even when clinically unwise. Furthermore, the differences between the LLMs underscore the need to standardize alignment processes to capture true cultural diversity. Thus, any responsible integration of LLMs into mental health care must account for their embedded biases and motivation mismatches to ensure equitable delivery across diverse populations. Achieving this will require transparency and refinement of alignment techniques to instill comprehensive human values.

  • JMIR Ment Health 2024;11(1):e55988

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  Depression and Mood Disorders;...

  Apr 9, 2024

  Feasibility, Acceptability, and Preliminary Efficacy of a Smartphone App–Led Cognitive Behavioral Therapy for Depression Under Therapist Supervision: Open...

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  Authors List:

  • Sabine Wilhelm  
  • Emily E Bernstein  
  • Kate H Bentley  
  • Ivar Snorrason  
  • Susanne S Hoeppner  
  • Dalton Klare  
  • Jennifer L Greenberg  
  • Hilary Weingarden  
  • Thomas H McCoy  
  • Oliver Harrison  

  Abstract:

  Background: Major depressive disorder affects approximately 1 in 5 adults during their lifetime and is the leading cause of disability worldwide. Yet, a minority receive adequate treatment due to person-level (eg, geographical distance to providers) and systems-level (eg, shortage of trained providers) barriers. Digital tools could improve this treatment gap by reducing the time and frequency of therapy sessions needed for effective treatment through the provision of flexible, automated support. Objective: This study aimed to examine the feasibility, acceptability, and preliminary clinical effect of Mindset for Depression, a deployment-ready 8-week smartphone-based cognitive behavioral therapy (CBT) supported by brief teletherapy appointments with a therapist. Methods: This 8-week, single-arm open trial tested the Mindset for Depression app when combined with 8 brief (16-25 minutes) video conferencing visits with a licensed doctoral-level CBT therapist (n=28 participants). The app offers flexible, accessible psychoeducation, CBT skills practice, and support to patients as well as clinician guidance to promote sustained engagement, monitor safety, and tailor treatment to individual patient needs. To increase accessibility and thus generalizability, all study procedures were conducted remotely. Feasibility and acceptability were assessed via attrition, patient expectations and feedback, and treatment utilization. The primary clinical outcome measure was the clinician-rated Hamilton Depression Rating Scale, administered at pretreatment, midpoint, and posttreatment. Secondary measures of functional impairment and quality of life as well as maintenance of gains (3-month follow-up) were also collected. Results: Treatment credibility (week 4), expectancy (week 4), and satisfaction (week 8) were moderate to high, and attrition was low (n=2, 7%). Participants self-reported using the app or practicing (either on or off the app) the CBT skills taught in the app for a median of 50 (IQR 30-60; week 4) or 60 (IQR 30-90; week 8) minutes per week; participants accessed the app on an average 36.8 (SD 10.0) days and completed a median of 7 of 8 (IQR 6-8) steps by the week 8 assessment. The app was rated positively across domains of engagement, functionality, aesthetics, and information. Participants’ depression severity scores decreased from an average Hamilton Depression Rating Scale score indicating moderate depression (mean 19.1, SD 5.0) at baseline to a week 8 mean score indicating mild depression (mean 10.8, SD 6.1; d=1.47; P<.001). Improvement was also observed for functional impairment and quality of life. Gains were maintained at 3-month follow-up. Conclusions: The results show that Mindset for Depression is a feasible and acceptable treatment option for individuals with major depressive disorder. This smartphone-led treatment holds promise to be an efficacious, scalable, and cost-effective treatment option. The next steps include testing Mindset for Depression in a fully powered randomized controlled trial and real-world clinical settings. Trial Registration: ClinicalTrials.gov NCT05386329; https://clinicaltrials.gov/study/NCT05386329?term=NCT05386329

  • JMIR Ment Health 2024;11(1):e53998

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  Reviews in Digital Mental Health

  Apr 4, 2024

  Studies of Social Anxiety Using Ambulatory Assessment: Systematic Review

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  Authors List:

  • Javier Fernández-Álvarez  
  • Desirée Colombo  
  • Juan Martín Gómez Penedo  
  • Maitena Pierantonelli  
  • Rosa María Baños  
  • Cristina Botella  

  Abstract:

  Background: There has been an increased interest in understanding social anxiety (SA) and SA disorder (SAD) antecedents and consequences as they occur in real time, resulting in a proliferation of studies using ambulatory assessment (AA). Despite the exponential growth of research in this area, these studies have not been synthesized yet. Objective: This review aimed to identify and describe the latest advances in the understanding of SA and SAD through the use of AA. Methods: Following the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines, a systematic literature search was conducted in Scopus, PubMed, and Web of Science. Results: A total of 70 articles met the inclusion criteria. The qualitative synthesis of these studies showed that AA permitted the exploration of the emotional, cognitive, and behavioral dynamics associated with the experience of SA and SAD. In line with the available models of SA and SAD, emotion regulation, perseverative cognition, cognitive factors, substance use, and interactional patterns were the principal topics of the included studies. In addition, the incorporation of AA to study psychological interventions, multimodal assessment using sensors and biosensors, and transcultural differences were some of the identified emerging topics. Conclusions: AA constitutes a very powerful methodology to grasp SA from a complementary perspective to laboratory experiments and usual self-report measures, shedding light on the cognitive, emotional, and behavioral antecedents and consequences of SA and the development and maintenance of SAD as a mental disorder.

  • JMIR Ment Health 2024;11(1):e46593

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