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Evaluation of Digital Mental Health Technologies in the United States: Systematic Literature Review and Framework Synthesis. | LitMetric

Background: Digital mental health technologies (DMHTs) have the potential to enhance mental health care delivery. However, there is little information on how DMHTs are evaluated and what factors influence their use.

Objective: A systematic literature review was conducted to understand how DMHTs are valued in the United States from user, payer, and employer perspectives.

Methods: Articles published after 2017 were identified from MEDLINE, Embase, PsycINFO, Cochrane Library, the Health Technology Assessment Database, and digital and mental health congresses. Each article was evaluated by 2 independent reviewers to identify US studies reporting on factors considered in the evaluation of DMHTs targeting mental health, Alzheimer disease, epilepsy, autism spectrum disorder, or attention-deficit/hyperactivity disorder. Study quality was assessed using the Critical Appraisal Skills Program Qualitative and Cohort Studies Checklists. Studies were coded and indexed using the American Psychiatric Association's Mental Health App Evaluation Framework to extract and synthesize relevant information, and novel themes were added iteratively as identified.

Results: Of the 4353 articles screened, data from 26 unique studies from patient, caregiver, and health care provider perspectives were included. Engagement style was the most reported theme (23/26, 88%), with users valuing DMHT usability, particularly alignment with therapeutic goals through features including anxiety management tools. Key barriers to DMHT use included limited internet access, poor technical literacy, and privacy concerns. Novel findings included the discreetness of DMHTs to avoid stigma.

Conclusions: Usability, cost, accessibility, technical considerations, and alignment with therapeutic goals are important to users, although DMHT valuation varies across individuals. DMHT apps should be developed and selected with specific user needs in mind.

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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC11399741PMC
http://dx.doi.org/10.2196/57401DOI Listing

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