Public views on e-mental health services –a systematic review of the current evidence
Bibliographic record
Abstract
Background: Considering both the Internet becoming a common mental health advisor and the unmet needs among various European mental health populations due to limited care resources, lacking health literacy or stigmatised beliefs, e-mental health services are suggested as appropriate option to improve the access to professional help. To overcome such barriers, however, knowledge about users´ preferences predicting the acceptability and perceived helpfulness of online self-help is required. Therefore, this review aims to determine the evidence on attitudes toward e-mental-health in the general population. Methods: A systematic search through Medline, PsycINFO and Cochrane Library was carried out, including research papers published in peer-reviewed journals between 2010 and 2015. Inclusion criteria contained studies focussing on preferences and attitudes toward e-mental health among adults. Clinical trials or surveys on the views of providers, participants in an intervention (e.g. clients) or specific risk groups were excluded. Findings: From the 63 results identified in electronic databases, four papers met the inclusion criteria. Sample sizes ranged from N=217 to 2.411. Data mainly stem from Canada, Australia and Austria, respectively Germany. Methodology varied across the studies. Overall, results indicated type-specific differences for preferences. Despite the low likelihood of e-mental health use in the future observed in most samples, health literacy and e-awareness tended to be associated with positive attitudes. Conclusions: Currently, the evidence on users´ preferences and attitudes toward e-mental health services remains scarce. Due to the limited research available, and methodological issues, further research is recommended in order to enable informed decisions.
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How this classification was reachedexpand
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 | 0.005 | 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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.004 |
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 teacher head, 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".