Human Support in App-Based Cognitive Behavioral Therapies for Emotional Disorders: Scoping Review

The future of psychological treatments: The Marburg Declaration

Although psychological treatments are broadly recognized as evidence-based interventions for various mental disorders, challenges remain. For example, a substantial proportion of patients receiving such treatments do not fully recover, and many obstacles hinder the dissemination, implementation, and training of psychological treatments. These problems require those in our field to rethink some of our basic models of mental disorders and their treatments, and question how research and practice in clinical psychology should progress. To answer these questions, a group of experts of clinical psychology convened at a Think-Tank in Marburg, Germany, in August 2022 to review the evidence and analyze barriers for current and future developments. After this event, an overview of the current state-of-the-art was drafted and suggestions for improvements and specific recommendations for research and practice were integrated. Recommendations arising from our meeting cover further improving psychological interventions through translational approaches, improving clinical research methodology, bridging the gap between more nomothetic (group-oriented) studies and idiographic (person-centered) decisions, using network approaches in addition to selecting single mechanisms to embrace the complexity of clinical reality, making use of scalable digital options for assessments and interventions, improving the training and education of future psychotherapists, and accepting the societal responsibilities that clinical psychology has in improving national and global health care. The objective of the Marburg Declaration is to stimulate a significant change regarding our understanding of mental disorders and their treatments, with the aim to trigger a new era of evidence-based psychological interventions.

The use of coaching in smartphone app-based cognitive behavioral therapy for body dysmorphic disorder

Background

Body dysmorphic disorder (BDD) is severe and undertreated. Digital mental health could be key to expanding access to evidence-based treatments, such as cognitive behavioral therapy for BDD (CBT-BDD). Coach guidance is posited to be essential for effective uptake of digital interventions. However, little is known about how different patients may use coaching, what patterns correspond to meaningful outcomes, and how to match coaching to patient needs.

Methods

Participants were 77 adults who received a 12-week guided smartphone CBT-BDD. Bachelor's-level coaches were available via asynchronous messaging. We analyzed the 400 messages sent by users to coaches during treatment. Message content was coded using the efficiency model of support (i.e., usability, engagement, fit, knowledge, and implementation). We aimed to clarify when and for what purposes patients with BDD used coaching, and if we can meaningfully classify patients by these patterns. We then assessed potential baseline predictors of coach usage, and whether distinct patterns relate to clinical outcomes.

Results

Users on average sent 5.88 messages (SD = 4.51, range 1-20) and received 9.84 (SD = 5.74, range 2-30). Regarding frequency of sending messages, latent profile analysis revealed three profiles, characterized by: (1) peak mid-treatment (16.88 %), (2) bimodal/more communication early and late in treatment (10.39 %), and (3) consistent low/no communication (72.73 %). Regarding content, four profiles emerged, characterized by mostly (1) engagement (51.95 %), (2) fit (15.58 %), (3) knowledge (15.58 %), and (4) miscellaneous/no messages (16.88 %). There was a significant relationship between frequency profile and age, such that the early/late peak group was older than the low communication group, and frequency profile and adherence, driven by the mid-treatment peak group completing more modules than the low contact group. Regarding content, the engagement and knowledge groups began treatment with more severe baseline symptoms than the fit group. Content profile was associated with dropout, suggesting higher dropout rates in the miscellaneous/no contact group and reduced rates in the engagement group. There was no relationship between profile membership and other outcomes.

Discussion

The majority of participants initiated little contact with their coach and the most common function of communications was to increase engagement. Results suggest that older individuals may prefer or require more support than younger counterparts early in treatment. Additionally, whereas individuals using coaching primarily for engagement may be at lower risk of dropping out, those who do not engage at all may be at elevated risk. Findings can support more personalized, data-driven coaching protocols and more efficient allocation of coaching resources.

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

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.

LiveWell, a smartphone-based self-management intervention for bipolar disorder: Intervention participation and usability analysis

BACKGROUND

Understanding how individuals utilize and perceive digital mental health interventions may improve engagement and effectiveness. To support intervention improvement, participant feedback was obtained and app use patterns were examined for a randomized clinical trial evaluating a smartphone-based intervention for individuals with bipolar disorder.

METHODS

App use and coaching engagement were examined (n = 124). Feedback was obtained via exit questionnaires (week 16, n = 81) and exit interviews (week 48, n = 17).

RESULTS

On average, over 48 weeks, participants used the app for 4.4 h and engaged with the coach for 3.9 h. Participants spent the most time monitoring target behaviors and receiving adaptive feedback and the least time viewing self-assessments and skills. Participants reported that the daily check in helped increase awareness of target behaviors but expressed frustration with repetitiveness of monitoring and feedback content. Participants liked personalizing their wellness plan, but its use did not facilitate skills practice. App use declined over time which participants attributed to clinical stability, content mastery, and time commitment. Participants found the coaching supportive and motivating for app use.

LIMITATIONS

App engagement based on viewing time may overestimate engagement. The delay between intervention delivery and the exit interviews and low exit interview participation may introduce bias.

CONCLUSION

Utilization patterns and feedback suggest that digital mental health engagement and efficacy may benefit from adaptive personalization of targets monitored combined with adaptive monitoring and feedback to support skills practice and development. Increasing engagement with supports may also be beneficial.

Lessons and Untapped Potential of Smartphone-Based Physical Activity Interventions for Mental Health: Narrative Review

BACKGROUND

Physical activity has well-known and broad health benefits, including antidepressive and anxiolytic effects. However, only approximately half of Americans meet even the minimum exercise recommendations. Individuals with anxiety, depression, or related conditions are even less likely to do so. With the advent of mobile sensors and phones, experts have quickly noted the utility of technology for the enhanced measurement of and intervention for physical activity. In addition to being more accessible than in-person approaches, technology-driven interventions may uniquely engage key mechanisms of behavior change such as self-awareness.

OBJECTIVE

This study aims to provide a narrative overview and specific recommendations for future research on smartphone-based physical activity interventions for psychological disorders or concerns.

METHODS

In this paper, we summarized early efforts to adapt and test smartphone-based or smartphone-supported physical activity interventions for mental health. The included articles described or reported smartphone-delivered or smartphone-supported interventions intended to increase physical activity or reduce sedentary behavior and included an emotional disorder, concern, or symptom as an outcome measure. We attempted to extract details regarding the intervention designs, trial designs, study populations, outcome measures, and inclusion of adaptations specifically for mental health. In taking a narrative lens, we drew attention to the type of work that has been done and used these exemplars to discuss key directions to build on.

RESULTS

To date, most studies have examined mental health outcomes as secondary or exploratory variables largely in the context of managing medical concerns (eg, cancer and diabetes). Few trials have recruited psychiatric populations or explicitly aimed to target psychiatric concerns. Consequently, although there are encouraging signals that smartphone-based physical activity interventions could be feasible, acceptable, and efficacious for individuals with mental illnesses, this remains an underexplored area.

CONCLUSIONS

Promising avenues for tailoring validated smartphone-based interventions include adding psychoeducation (eg, the relationship between depression, physical activity, and inactivity), offering psychosocial treatment in parallel (eg, cognitive restructuring), and adding personalized coaching. To conclude, we offer specific recommendations for future research, treatment development, and implementation in this area, which remains open and promising for flexible, highly scalable support.

Attrition in Conversational Agent-Delivered Mental Health Interventions: Systematic Review and Meta-Analysis

BACKGROUND

Conversational agents (CAs) or chatbots are computer programs that mimic human conversation. They have the potential to improve access to mental health interventions through automated, scalable, and personalized delivery of psychotherapeutic content. However, digital health interventions, including those delivered by CAs, often have high attrition rates. Identifying the factors associated with attrition is critical to improving future clinical trials.

OBJECTIVE

This review aims to estimate the overall and differential rates of attrition in CA-delivered mental health interventions (CA interventions), evaluate the impact of study design and intervention-related aspects on attrition, and describe study design features aimed at reducing or mitigating study attrition.

METHODS

We searched PubMed, Embase (Ovid), PsycINFO (Ovid), Cochrane Central Register of Controlled Trials, and Web of Science, and conducted a gray literature search on Google Scholar in June 2022. We included randomized controlled trials that compared CA interventions against control groups and excluded studies that lasted for 1 session only and used Wizard of Oz interventions. We also assessed the risk of bias in the included studies using the Cochrane Risk of Bias Tool 2.0. Random-effects proportional meta-analysis was applied to calculate the pooled dropout rates in the intervention groups. Random-effects meta-analysis was used to compare the attrition rate in the intervention groups with that in the control groups. We used a narrative review to summarize the findings.

RESULTS

The systematic search retrieved 4566 records from peer-reviewed databases and citation searches, of which 41 (0.90%) randomized controlled trials met the inclusion criteria. The meta-analytic overall attrition rate in the intervention group was 21.84% (95% CI 16.74%-27.36%; I2=94%). Short-term studies that lasted ≤8 weeks showed a lower attrition rate (18.05%, 95% CI 9.91%- 27.76%; I2=94.6%) than long-term studies that lasted >8 weeks (26.59%, 95% CI 20.09%-33.63%; I2=93.89%). Intervention group participants were more likely to attrit than control group participants for short-term (log odds ratio 1.22, 95% CI 0.99-1.50; I2=21.89%) and long-term studies (log odds ratio 1.33, 95% CI 1.08-1.65; I2=49.43%). Intervention-related characteristics associated with higher attrition include stand-alone CA interventions without human support, not having a symptom tracker feature, no visual representation of the CA, and comparing CA interventions with waitlist controls. No participant-level factor reliably predicted attrition.

CONCLUSIONS

Our results indicated that approximately one-fifth of the participants will drop out from CA interventions in short-term studies. High heterogeneities made it difficult to generalize the findings. Our results suggested that future CA interventions should adopt a blended design with human support, use symptom tracking, compare CA intervention groups against active controls rather than waitlist controls, and include a visual representation of the CA to reduce the attrition rate.

TRIAL REGISTRATION

PROSPERO International Prospective Register of Systematic Reviews CRD42022341415; https://www.crd.york.ac.uk/prospero/display_record.php?ID=CRD42022341415.

Coaching with Internet-Based Mental Health Program: Patient and Coach Experiences

Introduction: The COVID-19 pandemic has laid bare the need for mental health treatment and the shortage of available providers. Internet-based, asynchronous mental health programs that incorporate coaching with a licensed provider address this widespread challenge. This study provides an in-depth exploration of both the patient and provider experience in webSTAIR, a coached, internet-based psychoeducational program, where coaching took place over video-telehealth. We focus on how patients and licensed mental health providers understood their coaching relationship in an internet-based mental health program. Materials and Methods: We interviewed a purposive sample of 60 patients who completed the coached, internet-based program and all 9 providers who provided coaching from 2017 to 2020. The project team and interviewers took notes during interviews. Patient interviews were studied using content and matrix analysis. Coach interviews were studied using thematic analysis. Results: Interviews across patients and coaches reveal the continued importance of relationship building and rapport and emphasized the central role of the coach in providing content clarification and application of skills. Discussion: For patients, coaches were critical for understanding and completing the internet-based program. As well, positive relationship with their coach further enhanced their experience in the program. Providers echoed the importance of relationship building and rapport for program success and saw their main role as helping patients to understand content and apply skills.

Equipping fathers to support distressed mothers: What do mothers want fathers to know and do?

ISSUE ADDRESSED

Up to one in five new mothers experience depression or anxiety, and their partners are often the first line of social and practical support. However, many fathers are unprepared for their role as support person. The SMS4dads program (www.sms4dads.com) provides text-based support to new fathers but lacks specific messages addressing maternal mental distress.

METHODS

A mixed methods process engaged mothers with lived experience of perinatal mental distress to identify message content for co-designing texts in SMS4dads. Participants completed surveys derived from research literature and parenting websites using the theoretical framework of support domains: emotional or affectionate support, informational support, tangible support and positive social interaction. Mothers also indicated the most appropriate timing of support: at the point of identifying the distress (emerging), with ongoing symptoms (persistent) or during recovery (easing). Free text comments from mothers were linked to survey topics to provide examples of wording suitable for text messages to fathers.

RESULTS

Fifty-five mothers with lived experience completed the surveys. All support items were more often endorsed as helpful rather than not helpful by mothers. Emotional support was thought helpful in the early stages, tangible support was valued with ongoing symptoms and social interaction appreciated as symptoms eased.

CONCLUSIONS

Mothers experiencing perinatal depression and anxiety require a range of supportive actions by their partners, including household tasks and baby-care, encouragement, listening and managing relationships with family and friends. SO WHAT?: Information provided by distressed mothers can provide guidance to professionals when designing information for fathers/partners. Digital delivery of this co-designed information to fathers across urban and rural areas may enhance the competence of fathers working to support mothers experiencing mental distress in the perinatal period.

The impact of guided versus supportive coaching on mental health app engagement and clinical outcomes

Although mobile mental health apps have the unique potential to increase access to care, evidence reveals engagement is low unless coupled with coaching. However, most coaching protocols are limited in their scalability. This study assesses how human support and guidance from a Digital Navigator (DN), a scalable coach, can impact mental health app engagement and effectiveness on anxiety and depressive symptoms. This study aims to detach components of coaching, specifically personalized recommendations versus general support, to inform scalability of coaching models for mental health apps. 156 participants were split into the DN Guide versus DN Support groups for the 6-week study. Both groups utilized the mindLAMP app for the duration of the study and had equal time with the DN, but the Guide group received personalized app recommendations. The Guide group completed significantly more activities than the Support group. 34% (49/139) of all participants saw a 25% decrease in PHQ-9 scores and 38% (53/141) saw a 25% decrease in GAD-7 scores. These findings show mental health apps, especially when supported by DNs, can reduce depression and anxiety symptoms when coupled with coaching, suggesting a feasible path for large-scale deployment.

Validation of the Attitudes Towards Psychological Online Interventions Questionnaire Among Black Americans: Cross-cultural Confirmatory Factor Analysis

BACKGROUND

Acceptability of digital mental health interventions is a significant predictor of treatment-seeking behavior and engagement. However, acceptability has been conceptualized and operationalized in various ways, which decreases measurement precision and leads to heterogeneous conclusions about acceptability. Standardized self-report measures of acceptability have been developed, which have the potential to ameliorate these problems, but none have demonstrated evidence for validation among Black communities, which limits our understanding of attitudes toward these interventions among racially minoritized groups with well-documented barriers to mental health treatment.

OBJECTIVE

This study aims to examine the psychometric validity and reliability of one of the first and most widely used measures of acceptability, the Attitudes Towards Psychological Online Interventions Questionnaire, among a Black American sample.

METHODS

Participants (N=254) were recruited from a large southeastern university and the surrounding metropolitan area and completed the self-report measure via a web-based survey. A confirmatory factor analysis using mean and variance adjusted weighted least squares estimation was conducted to examine the validity of the underlying hierarchical 4-factor structure proposed by the original authors of the scale. An alternative, hierarchical 2-factor structure model and bifactor model were examined for comparative fit.

RESULTS

The findings indicated that the bifactor model demonstrated a superior fit (comparative fit index=0.96, Tucker-Lewis index=0.94, standardized root mean squared residual=0.03, and root mean square error of approximation=0.09) compared with both 2- and 4-factor hierarchical structure models.

CONCLUSIONS

The findings suggest that, within a Black American sample, there may be greater utility in interpreting the Attitudes Towards Psychological Online Interventions Questionnaire subscales as attitudinal constructs that are distinct from the global acceptability factor. The theoretical and practical implications for culturally responsive measurements were explored.

Providing Human Support for the Use of Digital Mental Health Interventions: Systematic Meta-review

BACKGROUND

Digital mental health interventions (DMHIs) have been increasingly deployed to bridge gaps in mental health care, particularly given their promising efficacy. Nevertheless, attrition among DMHI users remains high. In response, human support has been studied as a means of improving retention to and outcomes of DMHIs. Although a growing number of studies and meta-analyses have investigated the effects of human support for DMHIs on mental health outcomes, systematic empirical evidence of its effectiveness across mental health domains remains scant.

OBJECTIVE

We aimed to summarize the results of meta-analyses of human support versus no support for DMHI use across various outcome domains, participant samples, and support providers.

METHODS

We conducted a systematic meta-review of meta-analyses, comparing the effects of human support with those of no support for DMHI use, with the goal of qualitatively summarizing data across various outcome domains, participant samples, and support providers. We used MEDLINE, PubMed, and PsycINFO electronic databases. Articles were included if the study had a quantitative meta-analysis study design; the intervention targeted mental health symptoms and was delivered via a technology platform (excluding person-delivered interventions mediated through telehealth, text messages, or social media); the outcome variables included mental health symptoms such as anxiety, depression, stress, posttraumatic stress disorder symptoms, or a number of these symptoms together; and the study included quantitative comparisons of outcomes in which human support versus those when no or minimal human support was provided.

RESULTS

The results of 31 meta-analyses (505 unique primary studies) were analyzed. The meta-analyses reported 45 effect sizes; almost half (n=22, 48%) of them showed that human-supported DMHIs were significantly more effective than unsupported DMHIs. A total of 9% (4/45) of effect sizes showed that unsupported DMHIs were significantly more effective. No clear patterns of results emerged regarding the efficacy of human support for the outcomes assessed (including anxiety, depression, posttraumatic stress disorder, stress, and multiple outcomes). Human-supported DMHIs may be more effective than unsupported DMHIs for individuals with elevated mental health symptoms. There were no clear results regarding the type of training for those providing support.

CONCLUSIONS

Our findings highlight the potential of human support in improving the effects of DMHIs. Specifically, evidence emerged for stronger effects of human support for individuals with greater symptom severity. There was considerable heterogeneity across meta-analyses in the level of detail regarding the nature of the interventions, population served, and support delivered, making it difficult to draw strong conclusions regarding the circumstances under which human support is most effective. Future research should emphasize reporting detailed descriptions of sample and intervention characteristics and describe the mechanism through which they believe the coach will be most useful for the DMHI.

An exploratory analysis of the effect size of the mobile mental health Application, mindLAMP

Objectives

Despite the proliferation of mobile mental health apps, evidence of their efficacy around anxiety or depression is inadequate as most studies lack appropriate control groups. Given that apps are designed to be scalable and reusable tools, insights concerning their efficacy can also be assessed uniquely through comparing different implementations of the same app. This exploratory analysis investigates the potential to report a preliminary effect size of an open-source smartphone mental health app, mindLAMP, on the reduction of anxiety and depression symptoms by comparing a control implementation of the app focused on self-assessment to an intervention implementation of the same app focused on CBT skills.

Methods

A total of 328 participants were eligible and completed the study under the control implementation and 156 completed the study under the intervention implementation of the mindLAMP app. Both use cases offered access to the same in-app self-assessments and therapeutic interventions. Multiple imputations were utilized to impute the missing Generalized Anxiety Disorder-7 and Patient Health Questionnaire-9 survey scores of the control implementation.

Results

Post hoc analysis revealed small effect sizes of Hedge's g = 0.34 for Generalized Anxiety Disorder-7 and Hedge's g = 0.21 for Patient Health Questionnaire-9 between the two groups.

Conclusions

mindLAMP shows promising results in improving anxiety and depression outcomes in participants. Though our results mirror the current literature in assessing mental health apps' efficacy, they remain preliminary and will be used to inform a larger, well-powered study to further elucidate the efficacy of mindLAMP.

Protocol for a randomised controlled trial evaluating the effectiveness of a CBT-based smartphone application for improving mental health outcomes in adolescents: the MobiliseMe study

BACKGROUND

Depression is a leading cause of disability in adolescents, however few receive evidence-based treatment. Despite having the potential to overcome barriers to treatment uptake and adherence, there are very few CBT-based smartphone apps for adolescents. To address this gap, we developed ClearlyMe®, a self-guided CBT smartphone app for adolescent depression and anxiety. ClearlyMe® consists of 37 brief lessons containing core CBT elements, accessed either individually or as part of a 'collection'. Here, we describe the protocol for a randomised controlled trial aiming to evaluate the effect of ClearlyMe® on depressive symptoms and secondary outcomes, including engagement, anxiety and wellbeing, when delivered with and without guided support compared to an attention matched control.

METHODS

We aim to recruit 489 adolescents aged 12-17 years with mild to moderately-severe depressive symptoms. Participants will be screened for inclusion, complete the baseline assessment and are then randomly allocated to receive ClearlyMe® (self-directed use), ClearlyMe® with guided SMS support (guided use) or digital psychoeducation (attention-matched control). Depressive symptoms and secondary outcomes will be assessed at 6-weeks (primary endpoint) and 4-months post-baseline (secondary endpoint). Engagement, conceptualised as uptake, adherence and completion, will also be assessed 6-weeks post-baseline. Mixed-effects linear modelling will be used to conduct intention-to-treat analyses to determine whether reductions in depressive symptoms and secondary outcomes are greater for conditions receiving ClearlyMe® relative to control at 6-weeks and 4-months post-baseline and greater for intervention adherers relative to non-adherers. To minimise risk, participants will be encouraged to use the Get Help section of the app and can also opt to receive a call from the team clinical psychologist at baseline, and at the 6-week and 4-month post-baseline assessments when reporting suicidal ideation.

DISCUSSION

This is the first clinical trial examining a CBT smartphone app specifically designed for adolescent depression. It will provide empirical evidence on the effects of ClearlyMe® on depressive symptoms when used with and without guided support.

TRIAL REGISTRATION

Australian New Zealand Clinical Trials Registry (ACTRN12622000131752).

UNIVERSAL TRIAL NUMBER

U1111-1271-8519.

Addressing burgeoning unmet needs in college mental health

America is experiencing burgeoning mental health needs of their college students. Measuring the impact of mental health challenges for these students and the natural ways they adapt to them might enable smart triage of limited mental health resources. This may, in part, be achieved through a combination of technology-assisted personalized measurement-based care, treatment matching, and peer-support. Helping students self-monitor and organize their personal peer networks can destigmatize and increase accessibility to timely mental health care, especially for students of marginalized identities, who might otherwise be hesitant to receive care or be misdiagnosed. A collaborative effort among students, educators, clinicians, and health technology innovators may provide more tractable solutions for student unmet needs than any single entity or resource alone. Novel resources, tailored through a healthy equity lens that is individualized and culturally-sensitive, may meaningfully meet a student's needs, preferences, and acceptability, and translate to daily use and informed decision-making.