TechCare: mobile assessment and therapy for psychosis – an intervention for clients in the Early Intervention Service: A feasibility study protocol
Why this work is in the frame
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Bibliographic record
Abstract
OBJECTIVES: Technological advances in healthcare have shown promise when delivering interventions for mental health problems such as psychosis. The aim of this project is to develop a mobile phone intervention for people with psychosis and to conduct a feasibility study of the TechCare App. METHODS: The TechCare App will assess participant's symptoms and respond with a personalised guided self-help-based psychological intervention with the aim of exploring feasibility and acceptability. The project will recruit 16 service users and 8-10 health professionals from the Lancashire Care NHS Foundation Trust Early Intervention Service. RESULTS: In strand 1 of the study, we will invite people to discuss their experience of psychosis and give their opinions on the existing evidence-based treatment (cognitive behavioural therapy) and how the mobile app can be developed. In strand 2, we will complete a test run with a small number of participants (n = 4) to refine the mobile intervention (TechCare). Finally, in strand 3 of the study, the TechCare App will be examined in a feasibility study with 12 participants. CONCLUSION: It has been suggested that there is a need for a rapid increase in the efforts to develop the evidence base for the clinical effectiveness of digital technologies, considering mHealth research can potentially be helpful in addressing the demand on mental health services globally.
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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 | 0.004 | 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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 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 it