A systematic review of electronic mental health interventions for Indigenous youth: Results and recommendations
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
Electronic health interventions involve health services delivered using the Internet and related communication technologies. These services can be particularly relevant for Indigenous populations who often have differential access to health-care services compared to general populations, especially within rural and remote areas. As the popularity of electronic health interventions grows, there is an increased need for evidence-based recommendations for the effective use of these technologies. The current study is a systematic review of peer-reviewed and available grey literature with the aim of understanding outcomes of electronic health interventions for mental health concerns among Indigenous people. Studies used electronic health technologies for substance use treatment or prevention, suicide prevention, parenting supports, goal setting and behaviour change and consultation services. Various technological platforms were used across interventions, with both novel and adapted intervention development. Most studies provided qualitative results, with fewer studies focusing on quantitative outcomes. Some preliminary results from the engagement of Indigenous individuals with electronic health services has been demonstrated, but further research is needed to confirm these results. Identified barriers and facilitators are identified from the reviewed literature. Recommendations for future development of electronic health interventions for Indigenous youth are provided.
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 | 0.004 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.004 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 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