Preferences for Internet-Based Mental Health Interventions in an Adult Online Sample: Findings From an Online Community Survey
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
BACKGROUND: Despite extensive evidence that Internet interventions are effective in treating mental health problems, uptake of Internet programs is suboptimal. It may be possible to make Internet interventions more accessible and acceptable through better understanding of community preferences for delivery of online programs. OBJECTIVE: This study aimed to assess community preferences for components, duration, frequency, modality, and setting of Internet interventions for mental health problems. METHODS: A community-based online sample of 438 Australian adults was recruited using social media advertising and administered an online survey on preferences for delivery of Internet interventions, along with scales assessing potential correlates of these preferences. RESULTS: Participants reported a preference for briefer sessions, although they recognized a trade-off between duration and frequency of delivery. No clear preference for the modality of delivery emerged, although a clear majority preferred tailored programs. Participants preferred to access programs through a computer rather than a mobile device. Although most participants reported that they would seek help for a mental health problem, more participants had a preference for face-to-face sources only than online programs only. Younger, female, and more educated participants were significantly more likely to prefer Internet delivery. CONCLUSIONS: Adults in the community have a preference for Internet interventions with short modules that are tailored to individual needs. Individuals who are reluctant to seek face-to-face help may also avoid Internet interventions, suggesting that better implementation of existing Internet programs requires increasing acceptance of Internet interventions and identifying specific subgroups who may be resistant to seeking help.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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