Using Digital Tools to Engage Patients With Psychosis and Their Families in Research: Survey Recruitment and Completion in an Early Psychosis Intervention Program
Bibliographic record
Abstract
BACKGROUND: Barriers to recruiting and retaining people with psychosis and their families in research are well-established, potentially biasing clinical research samples. Digital research tools, such as online platforms, mobile apps, and text messaging, have the potential to address barriers to research by facilitating remote participation. However, there has been limited research on leveraging these technologies to engage people with psychosis and their families in research. OBJECTIVE: The objective of this study was to assess the uptake of digital tools to engage patients with provisional psychosis and their families in research and their preferences for different research administration methods. METHODS: This study used Research Electronic Data Capture (REDCap)-a secure web-based platform with built-in tools for data collection and storage-to send web-based consent forms and surveys on service engagement via text message or email to patients and families referred to early psychosis intervention services; potential participants were also approached or reminded about the study in person. We calculated completion rates and timing using remote and in-person methods and compensation preferences. RESULTS: A total of 447 patients with provisional psychosis and 187 of their family members agreed to receive the web-based consent form, and approximately half of the patients (216/447, 48.3%) and family members (109/187, 58.3%) consented to participate in the survey. Most patients (182/229, 79.5%) and family members (75/116, 64.7%) who completed the consent form did so remotely, with more family members (41/116, 35.3%) than patients (47/229, 20.5%) completing it in person. Of those who consented, 77.3% (167/216) of patients and 72.5% (79/109) of family members completed the survey, and most did the survey remotely. Almost all patients (418/462, 90.5%) and family members (174/190, 91.6%) requested to receive the consent form and survey by email, and only 4.1% (19/462) and 3.2% (6/190), respectively, preferred text message. Just over half of the patients (91/167, 54.5%) and family members (42/79, 53.2%) preferred to receive electronic gift cards from a coffee shop as study compensation. Most surveys were completed on weekdays between 12 PM and 6 PM. CONCLUSIONS: When offered the choice, most participants with psychosis and their families chose remote administration methods, suggesting that digital tools may enhance research recruitment and participation in this population, particularly in the context of the COVID-19 global pandemic.
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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 | 0.021 | 0.045 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".