Cultural and Contextual Adaptation of an eHealth Intervention for Youth Receiving Services for First-Episode Psychosis: Adaptation Framework and Protocol for Horyzons-Canada Phase 1
Bibliographic record
Abstract
BACKGROUND: eHealth interventions have the potential to address challenges related to access, service engagement, and continuity of care in the delivery of mental health services. However, the initial development and evaluation of such interventions can require substantive amounts of financial and human resource investments to bring them to scale. Therefore, it may be warranted to pay greater attention to policy, services, and research with respect to eHealth platforms that have the potential to be adapted for use across settings. Yet, limited attention has been placed on the methods and processes for adapting eHealth interventions to improve their applicability across cultural, geographical, and contextual boundaries. OBJECTIVE: In this paper, we describe an adaptation framework and protocol to adapt an eHealth intervention designed to promote recovery and prevent relapses in youth receiving specialized services for first-episode psychosis. The Web-based platform, called Horyzons, was initially developed and tested in Australia and is now being prepared for evaluation in Canada. METHODS: Service users and service providers from 2 specialized early intervention programs for first-episode psychosis located in different provinces will explore a beta-version of the eHealth intervention through focus group discussions and extended personal explorations to identify the need for, and content of contextual and cultural adaptations. An iterative consultation process will then take place with service providers and users to develop and assess platform adaptations in preparation for a pilot study with a live version of the platform. RESULTS: Data collection was completed in August 2017, and analysis and adaptation are in process. The first results of the study will be submitted for publication in 2018 and will provide preliminary insights into the acceptability of the Web-based platform (eg, perceived use and perceived usefulness) from service provider and service user perspectives. The project will also provide knowledge about the adaptations and process needed to prepare the platform for evaluation in Canada. CONCLUSIONS: This study contributes to an important gap in the literature pertaining to the specific principles, methods, and steps involved in adapting eHealth interventions for implementation and evaluation across a diverse range of cultural, geographical, and health care settings.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".