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Record W4411895175 · doi:10.1177/20552076251355345

“You can’t categorize lived experiences”: Understanding youth engagement in mobile health in an integrated youth services setting

2025· article· en· W4411895175 on OpenAlexaffabout
Xiaoxu Ding, Liisa Holsti, Julia Schmidt, Natalie Parde, Brodie M. Sakakibara, Skye Barbic

Bibliographic record

VenueDigital Health · 2025
Typearticle
Languageen
FieldHealth Professions
TopicMobile Health and mHealth Applications
Canadian institutionsCentre for Advancing Health OutcomesSpinal Cord Injury BCUniversity of British Columbia, Okanagan CampusUniversity of British Columbia
Fundersnot available
KeywordsThematic analysisYouth engagementmHealthMental healthKnowledge managementPsychologyPublic relationsMedicineQualitative researchNursingPsychological interventionPolitical scienceComputer scienceSociology

Abstract

fetched live from OpenAlex

Objective: Youth mental health is a global challenge often compounded by fragmented services limiting access. In Canada, Integrated Youth Services (IYS) provide centralized access to youth health services, with youth engagement playing a key role during development and implementation. This study aims to identify key factors influencing youth engagement in mobile health (mHealth) development within an IYS setting. Methods: We conducted 23 semi-structured interviews with youth, clinical service providers, and non-clinical staff involved in mHealth services at Foundry. The Consolidated Framework for Implementation Research guided deductive thematic analysis. Results: We identified key facilitators and barriers across five domains: Recognizing core value of engagement, improving external coordination, addressing internal organizational challenges, mitigating power imbalances, and tailoring implementation strategies. Conclusion: The findings highlight the need for inclusive approaches, regulatory frameworks, and strategies to engage underrepresented youth. Future efforts should prioritize iterative learning systems and safe, supportive spaces for meaningful youth engagement.

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)0.003
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.250
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.002
Science and technology studies0.0020.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.002
Insufficient payload (model declined to judge)0.0000.000

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 head0.102
GPT teacher head0.426
Teacher spread0.324 · 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 designQualitative
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

Citations0
Published2025
Admission routes2
Has abstractyes

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