Uptake of telemental health services in Alberta: A success, but not in all regions
Bibliographic record
Abstract
There is relatively little information on the routine use of telemental health (TMH). As part of a Canadian-Finnish project, we reviewed the use of TMH in Alberta. Using administrative data, numbers and types of TMH consultations in the province's health regions were compared with earlier published data for Alberta, and with data for Finland and other Canadian provinces. Since the first year of routine use (1997) there has been a six-fold increase in the use of TMH, and numbers of consultations per head of population are higher than elsewhere in Canada or in Finland. TMH accounts for 8% of mental health clinic consultations in the seven rural health regions. However, two regions have made negligible use of clinical TMH. TMH provides only a small proportion of all outpatient mental health services. TMH in Alberta is established in rural health regions, although with variable coverage, but remains a niche technique when all mental health services are considered.
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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 | 0.003 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".