Preferences of Young Adults With First-Episode Psychosis for Receiving Specialized Mental Health Services Using Technology: A Survey Study
Bibliographic record
Abstract
BACKGROUND: Despite the potential and interest of using technology for delivering specialized psychiatric services to young adults, surprisingly limited attention has been paid to systematically assess their perspectives in this regard. For example, limited knowledge exists on the extent to which young people receiving specialized services for a first-episode psychosis (FEP) are receptive to using new technologies as part of mental health care, and to which types of technology-enabled mental health interventions they are amenable to. OBJECTIVE: The purpose of this study is to assess the interest of young adults with FEP in using technology to receive mental health information, services, and supports. METHODS: This study uses a cross-sectional, descriptive survey design. A convenience sample of 67 participants between the ages of 18 and 35 were recruited from two specialized early intervention programs for psychosis. Interviewer-administered surveys were conducted between December 2013 and October 2014. Descriptive statistics are reported. RESULTS: Among the 67 respondents who completed the survey, the majority (85%, 57/67) agreed or strongly agreed with YouTube as a platform for mental health-related services and supports. The top five technology-enabled services that participants were amenable to were (1) information on medication (96%, 64/67); (2) information on education, career, and employment (93%, 62/67); (3) decision-making tools pertaining to treatment and recovery (93%, 62/67); (4) reminders for appointments via text messaging (93%, 62/67); and (5) information about mental health, psychosis, and recovery in general (91%, 61/67). The top self-reported barriers to seeking mental health information online were lack of knowledge on how to perform an Internet search (31%, 21/67) and the way information is presented online (27%, 18/67). Two thirds (67%; 45/67) reported being comfortable in online settings, and almost half (48%; 32/67) reported a preference for mixed formats when viewing mental health information online (eg, text, video, visual graphics). CONCLUSIONS: Young people diagnosed with FEP express interest in using the Internet, social media, and mobile technologies for receiving mental health-related services. Increasing the awareness of young people in relation to various forms of technology-enabled mental health care warrants further attention. A consideration for future research is to obtain more in-depth knowledge on young people's perspectives, which can help improve the design, development, and implementation of integrated technological health innovations within the delivery of specialized mental health care.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".