How do people living with psychotic disorders access and use information and communication technology: a scoping review
Bibliographic record
Abstract
Background: Community participation and social connection are important in the recovery process for people living with psychotic disorders. Information and Communication Technology (ICT) can play an important role in recovery by supporting community participation and social connection, but little is known about patterns of use or impact of this use among people living with psychotic disorders. There is a need to synthesize this interdisciplinary literature to establish guidelines for practice. Methods: We conducted a scoping review to answer the primary question; "What has been written about how people living with psychotic disorders access or use ICT for social connection and community participation?". Sub-questions include: (1) "What are barriers and facilitators to using ICT for people living with psychotic disorders?" and (2) "What are risks and benefits to using ICT for people living with psychotic disorders?". We searched six interdisciplinary databases to identify relevant peer-reviewed studies for this scoping review. Two authors independently screened titles and abstracts, and the first author reviewed all full-text articles meeting the inclusion criteria, extracting relevant data pertaining to the research question, with the second author reviewing for consensus. A qualitative content analysis was conducted to capture key trends in existing literature related to the research question. Results: Nineteen studies were included in this analysis. Findings were categorized into four key areas: 1) differences and similarities in ICT use between participants with psychotic disorders and other populations; 2) moderators of ICT use and access; 3) potential benefits of ICT use and access; and 4) potential risks of ICT. Conclusions: The results of this review suggest that ICT could be an important and influential tool for participants living with psychotic disorders, despite the existence of significant risks. People living with psychotic disorders are at risk of being left behind the general population in terms of access to technology because of the costs associated with many devices and lack of access to digital literacy education and support for their use; this is an issue of equity and justice. It is essential that future practice and research focus upon how to include this population equitably in this critical occupation through direct intervention. Systematic Review Registration: https://osf.io/, identifier 10.17605/OSF.IO/YUQXD.
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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 | 0.018 | 0.086 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.005 |
| Bibliometrics | 0.017 | 0.017 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.006 | 0.006 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.004 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".