Transdiagnostic Mobile Health: Smartphone Intervention Reduces Depressive Symptoms in People With Mood and Psychotic Disorders

Inclusion of Individuals With Lived Experiences in the Development of a Digital Intervention for Co-Occurring Depression and Cannabis Use: Mixed Methods Investigation

BACKGROUND

Existing interventions for co-occurring depression and cannabis use often do not treat both disorders simultaneously and can result in higher rates of symptom relapse. Traditional in-person interventions are often difficult to obtain due to financial and time limitations, which may further prevent individuals with co-occurring depression and cannabis use from receiving adequate treatment. Digital interventions can increase the scalability and accessibility for these individuals, but few digital interventions exist to treat both disorders simultaneously. Targeting transdiagnostic processes of these disorders with a digital intervention-specifically positive valence system dysfunction-may yield improved access and outcomes.

OBJECTIVE

Recent research has highlighted a need for the inclusion of individuals with lived experiences to assist in the co-design of interventions to enhance scalability and relevance of an intervention. Thus, the purpose of this study is to describe the process of eliciting feedback from individuals with elevated depressed symptoms and cannabis use and co-designing a digital intervention, Amplification of Positivity-Cannabis Use Disorder (AMP-C), focused on improving positive valence system dysfunction in these disorders.

METHODS

Ten individuals who endorsed moderate to severe depressive symptoms and regular cannabis use (2-3×/week) were recruited online via Meta ads. Using a mixed methods approach, participants completed a 1-hour mixed methods interview over Zoom (Zoom Technologies Inc) where they gave their feedback and suggestions for the development of a mental health app, based on an existing treatment targeting positive valence system dysfunction, for depressive symptoms and cannabis use. The qualitative approach allowed for a broader investigation of participants' wants and needs regarding the engagement and scalability of AMP-C, and the quantitative approach allowed for specific ratings of intervention components to be potentially included.

RESULTS

Participants perceived the 13 different components of AMP-C as overall helpful (mean 3.9-4.4, SD 0.5-1.1) and interesting (mean 4.0-4.9, SD 0.3-1.1) on a scale from 1 (not at all) to 5 (extremely). They gave qualitative feedback for increasing engagement in the app, including adding a social component, using notifications, and being able to track their symptoms and progress over time.

CONCLUSIONS

This study highlights the importance of including individuals with lived experiences in the development of interventions, including digital interventions. This inclusion resulted in valuable feedback and suggestions for improving the proposed digital intervention targeting the positive valence system, AMP-C, to better match the wants and needs of individuals with depressive symptoms and cannabis use.

Leveraging Personal Technologies in the Treatment of Schizophrenia Spectrum Disorders: Scoping Review

BACKGROUND

Digital mental health is a rapidly growing field with an increasing evidence base due to its potential scalability and impacts on access to mental health care. Further, within underfunded service systems, leveraging personal technologies to deliver or support specialized service delivery has garnered attention as a feasible and cost-effective means of improving access. Digital health relevance has also improved as technology ownership in individuals with schizophrenia has improved and is comparable to that of the general population. However, less digital health research has been conducted in groups with schizophrenia spectrum disorders compared to other mental health conditions, and overall feasibility, efficacy, and clinical integration remain largely unknown.

OBJECTIVE

This review aims to describe the available literature investigating the use of personal technologies (ie, phone, computer, tablet, and wearables) to deliver or support specialized care for schizophrenia and examine opportunities and barriers to integrating this technology into care.

METHODS

Given the size of this review, we used scoping review methods. We searched 3 major databases with search teams related to schizophrenia spectrum disorders, various personal technologies, and intervention outcomes related to recovery. We included studies from the full spectrum of methodologies, from development papers to implementation trials. Methods and reporting follow the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines.

RESULTS

This search resulted in 999 studies, which, through review by at least 2 reviewers, included 92 publications. Included studies were published from 2010 to 2023. Most studies examined multitechnology interventions (40/92, 43%) or smartphone apps (25/92, 27%), followed by SMS text messaging (16/92, 17%) and internet-based interventions (11/92, 12%). No studies used wearable technology on its own to deliver an intervention. Regarding the stage of research in the field, the largest number of publications were pilot studies (32/92, 35%), followed by randomized control trials (RCTs; 20/92, 22%), secondary analyses (16/92, 17%), RCT protocols (16/92, 17%), development papers (5/92, 5%), and nonrandomized or quasi-experimental trials (3/92, 3%). Most studies did not report on safety indices (55/92, 60%) or privacy precautions (64/92, 70%). Included studies tend to report consistent positive user feedback regarding the usability, acceptability, and satisfaction with technology; however, engagement metrics are highly variable and report mixed outcomes. Furthermore, efficacy at both the pilot and RCT levels report mixed findings on primary outcomes.

CONCLUSIONS

Overall, the findings of this review highlight the discrepancy between the high levels of acceptability and usability of these digital interventions, mixed efficacy results, and difficulties with sustained engagement. The discussion highlights common patterns that may underscore this observation in the field; however, as this was a scoping review, a more in-depth systematic review or meta-analysis may be required to better understand the trends outlined in this review.

Hybrid mHealth care: Patient perspectives of blended treatments for psychosis. A systematic review

BACKGROUND

mHealth interventions use mobile and wireless technologies to deliver aspects of healthcare, and have been extensively employed in mental health research, showcasing their potential to address the significant treatment gap. While numerous studies underscore the advantages and functionalities of mHealth, challenges persist regarding patient uptake and sustained engagement among individuals with psychosis spectrum disorder. This review aims to explore individual-level barriers and facilitators to engagement with hybrid digital systems, which involves the integration of digital tools alongside in-person care.

METHOD

Four electronic databases (Medline, Web of Science, CINAHL, and PsychINFO) were systematically searched to identify hybrid digital interventions for psychosis spectrum disorders. Studies that only reported the efficacy of the interventions were excluded. 16 studies were included in the final review.

RESULTS

Six themes were identified in this review, including mHealth as a tool to aid communication, the central role of the therapist, an increased sense of support through the provision of digital support, allowing greater insight into auditory hallucinations, enabling technologies and barriers to engagement.

CONCLUSIONS

This review demonstrated the factors impacting engagement in hybrid interventions for psychosis spectrum disorder. By identifying barriers and facilitators, the findings could offer valuable guidance for the design of innovative digital interventions. These findings also underscore the importance of prioritising trustworthiness in digital systems. Future research should focus on establishing and implementing trustworthy digital systems to enhance engagement and effectively integrate mobile health into conventional healthcare practices.

Internet- and mobile-based anxiety and depression interventions for children and adolescents: efficacy and negative effects - a systematic review and meta-analysis

Mental disorders, most commonly anxiety disorders and fourth most common depression, are prevalent in children and adolescents. Internet- and mobile-based interventions might represent a scalable approach to improve mental health care, however, evidence so far is inconclusive and systematic reports on negative effects are missing. Four data-bases were searched for randomized controlled trials evaluating internet- and mobile-based interventions (IMIs) targeting anxiety disorders or depression in children and adolescents up to 18 years exhibiting clinically relevant symptoms. Meta-analytic evaluations were conducted in comparison to active and passive control groups, furthermore, pre-defined sub-groups were explored and reported negative effects examined. Pooled estimates showed a moderate positive effect for IMIs targeting anxiety disorders compared to passive control groups (g = -0.69; CI -0.94 to -0.45; k = 8; n = 559; p ≤ 0,001), but not for depression. Pooled estimates compared to active control groups remained non-significant. Subgroup analyses were largely omitted due to an insufficient number of trials or were non-significant. Negative effects were mainly reported as drop-out rates and (non)-response rates, while additional negative effects, such as deterioration rates or the development of additional symptoms, were reported by only one third of included studies. The focus on children and adolescents with clinically relevant symptoms allowed the present findings to complement previous work, however, the limited amount of trials hindered many planned comparisons. The overview of reported negative effects highlighted that negative effects are being neglected in the majority of RCTs. Hence, in the future RCTs should include more information about potential negative effects, at best a combination of quantitative and qualitative information. Open Science Framework (osf.io/ch5nj).

Developing the Workforce of the Digital Future: mHealth Competency and Fidelity Measurement in Community-Based Care

Integrating mobile health (mHealth) interventions into settings that serve diverse patient populations requires that prerequisite professional competencies are delineated and that standards for clinical quality assurance can be pragmatically assessed. Heretofore, proposed mHealth competencies have been broad and have lacked a framework to support specific applications. We outline the meta-competencies identified in the literature relevant to mHealth interventions and demonstrate how these meta-competencies can be integrated with population- and intervention-related competencies to help guide a pragmatic approach to competency assessment. We present a use case based on FOCUS-an evidence-based mHealth intervention designed for individuals with serious mental illness and currently being implemented in geographically and demographically diverse community behavioral health settings. Subsequent to identifying the cross-cutting competencies relevant to the target population (outpatients experiencing psychotic symptoms), substratal intervention (Cognitive Behavioral Therapy for psychosis), and treatment modality (mHealth), we detail the development process of an mHealth fidelity monitoring system (mHealth-FMS). We adhered to a published sequential 5-step process to design a fidelity monitoring system that aligns with our integrated mHealth competency framework and that was guided by best practices prescribed by the Treatment Fidelity Workgroup of the National Institutes of Health Behavior Change Consortium. The mHealth-FMS is intended to enhance both clinical and implementation outcomes by grounding the mHealth interventionist and the system of care in which they operate in the core functions, tasks, knowledge, and competencies associated with system-integrated mHealth delivery. Future research will explore acceptability and feasibility of the mHealth-FMS.

Psychotherapists’ perspective of the use of eHealth services to enhance positive mental health promotion

Objective

Keyes’s two-continua model of mental health proposes that mental illness and positive mental health are two separate, correlated, unipolar dimensions. eHealth services have been used to deliver mental health care, though the focus remained largely on symptom reduction and management of negative aspects of mental health. The potential of eHealth services to promote positive mental well-being, however, has not been tapped sufficiently. The present study aims to explore psychotherapists’ perspective on the feasibility of eHealth services to enhance positive mental health promotion.

Methods

Seven focus group discussions were conducted among professionals ( n = 38) who delivered psychotherapy to examine positive mental health in their practice. Responses related to the use of e-psychotherapy to promote mental well-being were extracted for use in a secondary analysis of data in this study. Thematic analysis of data via inductive approach was conducted to allow emergence of common themes.

Results

Three main themes related to psychotherapists’ perspective on the feasibility of eHealth intervention in enhancing positive mental health were identified: (1) use of eHealth to educate and improve positive mental health; (2) concerns on incorporating psychotherapy into online services; (3) other factors that affect uptake or effectiveness of eHealth intervention for positive mental health.

Conclusions

The study generally found support among psychotherapists for the feasibility of eHealth intervention in promoting positive mental health among clients. Potential difficulties in implementation and practicality concerns were discussed.

Smartphone-based interventions in bipolar disorder: Systematic review and meta-analyses of efficacy. A position paper from the International Society for Bipolar Disorders (ISBD) Big Data Task Force

BACKGROUND

The clinical effects of smartphone-based interventions for bipolar disorder (BD) have yet to be established.

OBJECTIVES

To examine the efficacy of smartphone-based interventions in BD and how the included studies reported user-engagement indicators.

METHODS

We conducted a systematic search on January 24, 2022, in PubMed, Scopus, Embase, APA PsycINFO, and Web of Science. We used random-effects meta-analysis to calculate the standardized difference (Hedges' g) in pre-post change scores between smartphone intervention and control conditions. The study was pre-registered with PROSPERO (CRD42021226668).

RESULTS

The literature search identified 6034 studies. Thirteen articles fulfilled the selection criteria. We included seven RCTs and performed meta-analyses comparing the pre-post change in depressive and (hypo)manic symptom severity, functioning, quality of life, and perceived stress between smartphone interventions and control conditions. There was significant heterogeneity among studies and no meta-analysis reached statistical significance. Results were also inconclusive regarding affective relapses and psychiatric readmissions. All studies reported positive user-engagement indicators.

CONCLUSION

We did not find evidence to support that smartphone interventions may reduce the severity of depressive or manic symptoms in BD. The high heterogeneity of studies supports the need for expert consensus to establish ideally how studies should be designed and the use of more sensitive outcomes, such as affective relapses and psychiatric hospitalizations, as well as the quantification of mood instability. The ISBD Big Data Task Force provides preliminary recommendations to reduce the heterogeneity and achieve more valid evidence in the field.

A Smartphone Intervention for People With Serious Mental Illness: Fully Remote Randomized Controlled Trial of CORE

Background

People with serious mental illness (SMI) have significant unmet mental health needs. Development and testing of digital interventions that can alleviate the suffering of people with SMI is a public health priority.

Objective

The aim of this study is to conduct a fully remote randomized waitlist-controlled trial of CORE, a smartphone intervention that comprises daily exercises designed to promote reassessment of dysfunctional beliefs in multiple domains.

Methods

Individuals were recruited via the web using Google and Facebook advertisements. Enrolled participants were randomized into either active intervention or waitlist control groups. Participants completed the Beck Depression Inventory-Second Edition (BDI-II), Generalized Anxiety Disorder-7 (GAD-7), Hamilton Program for Schizophrenia Voices, Green Paranoid Thought Scale, Recovery Assessment Scale (RAS), Rosenberg Self-Esteem Scale (RSES), Friendship Scale, and Sheehan Disability Scale (SDS) at baseline (T1), 30-day (T2), and 60-day (T3) assessment points. Participants in the active group used CORE from T1 to T2, and participants in the waitlist group used CORE from T2 to T3. Both groups completed usability and accessibility measures after they concluded their intervention periods.

Results

Overall, 315 individuals from 45 states participated in this study. The sample comprised individuals with self-reported bipolar disorder (111/315, 35.2%), major depressive disorder (136/315, 43.2%), and schizophrenia or schizoaffective disorder (68/315, 21.6%) who displayed moderate to severe symptoms and disability levels at baseline. Participants rated CORE as highly usable and acceptable. Intent-to-treat analyses showed significant treatment×time interactions for the BDI-II (F_1,313=13.38; P<.001), GAD-7 (F_1,313=5.87; P=.01), RAS (F_1,313=23.42; P<.001), RSES (F_1,313=19.28; P<.001), and SDS (F_1,313=10.73; P=.001). Large effects were observed for the BDI-II (d=0.58), RAS (d=0.61), and RSES (d=0.64); a moderate effect size was observed for the SDS (d=0.44), and a small effect size was observed for the GAD-7 (d=0.20). Similar changes in outcome measures were later observed in the waitlist control group participants following crossover after they received CORE (T2 to T3). Approximately 41.5% (64/154) of participants in the active group and 60.2% (97/161) of participants in the waitlist group were retained at T2, and 33.1% (51/154) of participants in the active group and 40.3% (65/161) of participants in the waitlist group were retained at T3.

Conclusions

We successfully recruited, screened, randomized, treated, and assessed a geographically dispersed sample of participants with SMI entirely via the web, demonstrating that fully remote clinical trials are feasible in this population; however, study retention remains challenging. CORE showed promise as a usable, acceptable, and effective tool for reducing the severity of psychiatric symptoms and disability while improving recovery and self-esteem. Rapid adoption and real-world dissemination of evidence-based mobile health interventions such as CORE are needed if we are to shorten the science-to-service gap and address the significant unmet mental health needs of people with SMI during the COVID-19 pandemic and beyond.

Trial Registration

ClinicalTrials.gov NCT04068467; https://clinicaltrials.gov/ct2/show/NCT04068467

Significant reduction in depressive symptoms among patients with moderately-severe to severe depressive symptoms after participation in a therapist-supported, evidence-based mobile health program delivered via a smartphone app

Depression is a debilitating disorder associated with poor health outcomes, including increased comorbidity and early mortality. Despite the advent of new digital health interventions, few have been tested among patients with more severe forms of depression. As such, in an intent-to-treat study we examined whether 218 patients with at least moderately severe depressive symptoms (PHQ-9 ≥ 15) experienced significant reductions in depressive symptoms after participation in a therapist-supported, evidence-based mobile health (mHealth) program, Meru Health Program (MHP). Patients with moderately severe and severe depressive symptoms at pre-program assessment experienced significant decreases in depressive symptoms at end-of treatment (mean [standard deviation] PHQ-9 reduction = 8.30 [5.03], Hedges' g = 1.64, 95% CI [1.44, 1.85]). Also, 34% of patients with at least moderately severe depressive symptoms at baseline and 29.9% of patients with severe depressive symptoms (PHQ-9 ≥ 20) at baseline responded to the intervention at end-of-treatment, defined as experiencing ≥50% reduction in PHQ-9 score and a post-program PHQ-9 score lower than 10. Limitations include use lack of a control group and no clinical diagnostic information. Future randomized trials are warranted to test the MHP as a scalable solution for patients with more severe depressive symptoms.

Reducing the rate of psychiatric re-admissions in bipolar disorder using smartphones-The RADMIS trial

OBJECTIVES

The MONARCA I and II trials were negative but suggested that smartphone-based monitoring may increase quality of life and reduce perceived stress in bipolar disorder (BD). The present trial was the first to investigate the effect of smartphone-based monitoring on the rate and duration of readmissions in BD.

METHODS

This was a randomized controlled single-blind parallel-group trial. Patients with BD (ICD-10) discharged from hospitalization in the Mental Health Services, Capital Region of Denmark were randomized 1:1 to daily smartphone-based monitoring including a feedback loop (+ standard treatment) or to standard treatment for 6 months. Primary outcomes: the rate and duration of psychiatric readmissions.

RESULTS

We included 98 patients with BD. In ITT analyses, there was no statistically significant difference in rates (hazard rate: 1.05, 95% CI: 0.54; 1.91, p = 0.88) or duration of readmission between the two groups (B: 3.67, 95% CI: -4.77; 12.11, p = 0.39). There was no difference in scores on the Hamilton Depression Rating Scale (B = -0.11, 95% CI: -2.50; 2.29, p = 0.93). The intervention group had higher scores on the Young Mania Rating Scale (B: 1.89, 95% CI: 0.0078; 3.78, p = 0.050). The intervention group reported lower levels of perceived stress (B: -7.18, 95% CI: -13.50; -0.86, p = 0.026) and lower levels of rumination (B: -6.09, 95% CI: -11.19; -1.00, p = 0.019).

CONCLUSIONS

Smartphone-based monitoring did not reduce rate and duration of readmissions. There was no difference in levels of depressive symptoms. The intervention group had higher levels of manic symptoms, but lower perceived stress and rumination compared with the control group.

Can Smartphone Apps Assist People with Serious Mental Illness in Taking Medications as Prescribed?

Adherence research commonly happens in a silo, focused on a particular disease state or type of therapy. Learning from outside disciplines can bring new insights and ideas. This article presents adherence research as related to people with a diagnosis of a serious mental illness (SMI) and medication adherence through smartphone applications (apps). Individuals with SMI have high rates of not taking medication, increasing risks of relapse and hospitalization. Advances in technology may be advantageous in promoting taking medication. Smartphones apps have been designed for people with SMI. Further research is needed to evaluate their efficacy on improving rates of taking medication.

Evaluation of Treatment Descriptions and Alignment With Clinical Guidance of Apps for Depression on App Stores: Systematic Search and Content Analysis

BACKGROUND

The use of apps for the treatment of depression shows great promise. However, there is uncertainty regarding the alignment of publicly available apps for depression with clinical guidance, their treatment fidelity and evidence base, and their overall safety.

OBJECTIVE

Built on previous analyses and reviews, this study aims to explore the treatment and safety issues of publicly available apps for depression.

METHODS

We conducted a content analysis of apps for depression in the 2 main UK app stores (Google Play and Apple App Store). App store listings were analyzed for intervention content, treatment fidelity, and fit with the National Institute for Health and Care Excellence (NICE) guidelines for the treatment of depression in adults.

RESULTS

A total of 353 apps for depression were included in the review. App descriptions reported the use of 20 treatment approaches and 37 treatment strategies. Many apps used transdiagnostic (155/353, 43.9%) and multitheoretical interventions to treat multiple disorders including depression. Although many interventions appeared to be evidence-informed, there were issues with treatment fidelity, research evidence, and fit with clinical guidelines. None of the apps fully aligned with the NICE guidelines for depression.

CONCLUSIONS

App developers have adopted many evidence-informed treatments in their interventions; however, more work is needed to improve clinical validity, treatment fidelity, and the safety of apps. We urge developers to consult relevant guidelines and standards, and to engage in reflective questioning on treatment and safety to address these issues and to improve treatment content and intervention design.

Clinician's Guide to Evaluating and Developing eHealth Interventions for Mental Health

Objective

This review aimed to examine key information regarding technology‐delivered interventions for patients with mental health and/or substance use disorders and to provide support for efforts by psychiatrists and other mental health professionals in recommending applications or helping to develop new technology‐delivered interventions.

Methods

The authors reviewed existing information about the appraisal, development, and evaluation of technology‐delivered interventions (eHealth interventions).

Results

High‐level guidance is available for clinicians who want to evaluate eHealth applications for their patients. Clinicians should be familiar with existing models of eHealth intervention development and with traditional as well as unique elements in the evaluation of efficacy for these approaches. However, existing intervention development models have not been empirically validated, and only one includes empirical optimization as an inherent part of its process.

Conclusions

Because of the proliferation of eHealth interventions, mental health professionals should bring to this area the same level of content knowledge, understanding of development and evaluation processes, and rigorous skepticism as they do for pharmacotherapy and therapist‐delivered behavioral interventions.

eHealth interventions are rapidly transforming mental health treatment.

Clinicians should apply the same rigor to evaluating eHealth interventions that they apply to pharmacological treatments or other behavioral therapies.

High‐level guidance and recommendations regarding ideal eHealth intervention development are available to aid in such evaluation, but empirical evidence in support of these guidelines is lacking.

Development of an Emotion-Sensitive mHealth Approach for Mood-State Recognition in Bipolar Disorder

Internet- and mobile-based approaches have become increasingly significant to psychological research in the field of bipolar disorders. While research suggests that emotional aspects of bipolar disorders are substantially related to the social and global functioning or the suicidality of patients, these aspects have so far not sufficiently been considered within the context of mobile-based disease management approaches. As a multiprofessional research team, we have developed a new and emotion-sensitive assistance system, which we have adapted to the needs of patients with bipolar disorder. Next to the analysis of self-assessments, third-party assessments, and sensor data, the new assistance system analyzes audio and video data of these patients regarding their emotional content or the presence of emotional cues. In this viewpoint, we describe the theoretical and technological basis of our emotion-sensitive approach and do not present empirical data or a proof of concept. To our knowledge, the new assistance system incorporates the first mobile-based approach to analyze emotional expressions of patients with bipolar disorder. As a next step, the validity and feasibility of our emotion-sensitive approach must be evaluated. In the future, it might benefit diagnostic, prognostic, or even therapeutic purposes and complement existing systems with the help of new and intuitive interaction models.

Digital interventions in adult mental healthcare settings: recent evidence and future directions

PURPOSE OF REVIEW

Internet and mobile-based interventions (IMI) can be used as online delivered forms of psychotherapeutic mental health treatments. These interventions can be an effective as well as time and cost-efficient treatment with the potential to scale up mental healthcare. In this review, we map implementation possibilities into routine mental healthcare settings and provide the most recent evidence.

RECENT FINDINGS

Fourteen articles on digital mental healthcare approaches published in the last 18 months were included. Despite the limited number, the studies provide evidence for the effectiveness of IMI in treating inpatients and outpatients with various disorders in different mental healthcare settings. IMI were investigated as stand-alone interventions, in combination with other treatment forms (blended-care), or as aftercare.

SUMMARY

Although there is encouraging evidence for the effectiveness of IMI in mental healthcare settings, several limitations have to be considered. The small number of studies conducted within the healthcare system, especially with inpatient samples, calls for more collaboration between researchers and clinical practitioners to unravel barriers and develop efficient protocols for the integration into routine care. Nonetheless, IMI are a promising tool for the endeavour of closing the treatment gap and should, therefore, be further explored in varying settings.

mHealth in affective disorders: hype or hope? A focused narrative review

The constant growth and widespread availability of mobile technologies (i.e. smartphones and wearables) over the last decades have been a subject of intense interest and research in the affective disorders (AD) field. The potential of mHealth for collecting a new kind of passive and active information while providing cost-effective and tailored interventions have raised many hopes. However, until now, despite some encouraging results, research in the field has not been translated to reach real-world clinical settings or to develop additional evidence-based mHealth tools for people suffering from AD. Meanwhile, commercial untested apps and wearables are already being increasingly used and adopted by patients for the self-management of their illnesses. Hence, there is a latent need and demand from service users to integrate mHealth in their care, which the field cannot yet fulfil. In this article, through a focused narrative review, we discuss the evidence available for the use, validity and efficacy of mHealth tools in AD. Challenges in the academic field hampering the advancement of these technologies and its implementation into clinical practice are discussed. Lastly, we propose a framework to overcome these issues, which may facilitate mHealth solutions reaching service users.

Burnout, Perceived Stress, Sleep Quality, and Smartphone Use: A Survey of Osteopathic Medical Students

Context

Burnout is a psychological syndrome that results from prolonged exposure to stressful work activities and includes 3 dimensions: emotional exhaustion (EE), depersonalization (DP), and low sense of personal accomplishment (PA). Burnout is a widespread problem in numerous professions but is particularly high among medical students, residents, and early-career physicians compared with college graduates of similar age. However, minimal research has addressed burnout in osteopathic medical students.

Objective

To assess levels of burnout in osteopathic medical students and to examine the relationship among burnout, perceived stress, sleep quality, and smartphone use.

Methods

This study used a cross-sectional study design and an anonymous, electronic questionnaire service to administer the Maslach Burnout Inventory, the Perceived Stress Scale-4, the Pittsburgh Sleep Quality index, and the Smartphone Addiction Scale Short Version.

Results

A total of 385 participants (mean [SD] age, 25 [2.4] years; 208 [54.0%] women; 286 [74.3%] white; 138 [35.8%] second-year osteopathic medical students [OMSs]) completed the survey. Of the 385 participants, 9 (2.3%) reported high EE, 67 (17.4) reported high DP, and 310 (80.5) reported a high level of low PA. When comparing dimensions of burnout by gender, only levels of PA differed by gender, with men reporting higher levels of burnout compared with women (χ1 2=5.2, P=.022). Further, levels of DP differed by year in medical school (χ2=17.3, P=.008), with post-hoc comparisons showing differences between OMS I and OMS III (F=4.530, df=3, P=.004). Linear regression models showed that higher perceived stress (standardized β=0.5, P<.001), poorer sleep quality (standardized β=0.2, P=.001), and higher smartphone addiction scores (standardized β=0.1, P<.001) were associated with higher EE. Similarly, higher perceived stress (standardized β=0.2, P<.001), poorer sleep quality (standardized β=0.2, P=.001), and higher smartphone addiction scores (standardized β=0.2, P=.001) were associated with higher DP. Only higher perceived stress was associated with higher levels of low PA (standardized β=−0.4, P<.001).

Conclusions

These findings suggest independent associations with EE, DP, perceived stress, sleep quality, and smartphone use. Additional research with a larger, more diverse sample is needed to confirm these findings. If confirmed, wellness interventions can be designed to target 2 modifiable factors: sleep quality and smartphone use.