A Mobile Phone App to Support Young People in Making Shared Decisions in Therapy (Power Up): Study Protocol
Bibliographic record
Abstract
BACKGROUND: Evidence suggests that young people want to be active participants in their care and involved in decisions about their treatment. However, there is a lack of digital shared decision-making tools available to support young people in child and adolescent mental health services (CAMHS). OBJECTIVE: The primary aim of this paper is to present the protocol of a feasibility trial for Power Up, a mobile phone app to empower young people in CAMHS to make their voices heard and participate in decisions around their care. METHODS: In the development phase, 30 young people, parents, and clinicians will take part in interviews and focus groups to elicit opinions on an early version of the app. In the feasibility testing phase, 60 young people from across 7 to 10 London CAMHS sites will take part in a trial looking at the feasibility and acceptability of measuring the impact of Power Up on shared decision making. RESULTS: Data collection for the development phase ended in December 2016. Data collection for the feasibility testing phase will end in December 2017. CONCLUSIONS: Findings will inform the planning of a cluster controlled trial and contribute to the development and implementation of a shared decision-making app to be integrated into CAMHS. TRIAL REGISTRATION: ISRCTN77194423; http://www.isrctn.com/ISRCTN77194423 (Archived by WebCite at http://www.webcitation.org/6td6MINP0). ClinicalTrials.gov NCT02987608; https://clinicaltrials.gov/ct2/show/NCT02987608 (Archived by WebCite at http://www.webcitation.org/6td6PNBZM).
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.029 | 0.028 |
| Meta-epidemiology (narrow) | 0.002 | 0.003 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.005 | 0.003 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.005 | 0.008 |
| Insufficient payload (model declined to judge) | 0.092 | 0.026 |
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 source (direct Gemma or distilled Codex), 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".