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Record W4226078097 · doi:10.2196/35057

A Web-Based Stratified Stepped Care Mental Health Platform (TourHeart): Semistructured Interviews With Stakeholders

2022· article· en· W4226078097 on OpenAlexvenueno aff
Emily W. S. Tsoi, Winnie W. S. Mak, Connie Y Y Ho, Gladys T. Y. Yeung

Bibliographic record

VenueJMIR Human Factors · 2022
Typearticle
Languageen
FieldPsychology
TopicDigital Mental Health Interventions
Canadian institutionsnot available
Fundersnot available
KeywordsMental healthPsychoeducationCoachingThematic analysisService providerNonprobability samplingPsychological interventionPersonalizationPsychologyMental illnessApplied psychologyQualitative researchService (business)NursingMedical educationMedicineWorld Wide WebComputer sciencePsychiatryBusinessPsychotherapist

Abstract

fetched live from OpenAlex

BACKGROUND: TourHeart, a web-based stratified stepped care mental health platform, is a one-stop solution that integrates psychoeducation and other well-being promotional tools for mental health promotion and mental illness prevention and evidence-based, low-intensity psychological interventions for the treatment of people with anxiety and depressive symptoms. Instead of focusing only on symptom reduction, the platform aims to be person-centered and recovery-oriented, and continual feedback from stakeholders is sought. Understanding the perspectives of users and service providers enables platform developers to fine-tune both the design and content of the services for enhanced service personalization and personal recovery. OBJECTIVE: This qualitative study evaluated a web-based mental health platform by incorporating the perspectives of both users and service providers who administered the platform and provided coaching services. The platform included both web-based and offline services targeting adults along the mental health spectrum based on the two-continua model of mental health and mental illness. METHODS: Interview questions were designed based on the Reach, Effectiveness, Adoption, Implementation, and Maintenance framework (RE-AIM). Views on offline services, the design of the web-based platform, user experience, and the contents of the platform were explored using semistructured interviews. A total of 27 service users and 22 service providers were recruited using purposive criterion sampling. A hybrid thematic analysis was performed to identify salient aspects of users' and providers' experiences with and views of the platform. RESULTS: Totally, 3 broad themes (namely, the quality of the platform, drivers for platform use, and coaching services) emerged from the interview data that highlighted users' views of and experiences with the web-based platform. The platform's general esthetics, operations, and contents were found to be critical features and drivers for continued use. Although coaching services were indispensable, participants preferred the autonomy and anonymity associated with web-based mental health services. CONCLUSIONS: This study highlights the importance of web-based mental health services being easy to navigate and understand, being user-centric, and providing adequate guidance in self-help. It also confirms existing design standards and recommendations and suggests that more rigorous, iterative user experience research and robust evaluation should be conducted in the future adaptation of web-based stratified stepped care services, so that they can be more personalized and better promote personal recovery.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.102
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0070.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.100
GPT teacher head0.383
Teacher spread0.282 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designNot applicable
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations10
Published2022
Admission routes1
Has abstractyes

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