Five Years of Youth Engagement with Kids Help Phone Canada (Part 2): Issues Discussed Over Phone, Chat, Text, and Peer-to-Peer Services by Age Range
Bibliographic record
Abstract
Background:There is substantial unmet need for child and youth mental health problems in Canada. Charitable organizations, such as Kids Help Phone (KHP), are critical to filling system gaps, offering 24/7 e-mental health services outside the formal health care system. Methods:For the 5-year period from January 2018 to December 2022, we describe issues discussed by young people accessing KHP's services, and examine variations across different service platforms and age groups. Results:The most discussed issues across all service platforms and age groups were anxiety/stress, depression/sadness, and relationships. Suicide was most frequently discussed over text and Live Chat compared with other services, and was proportionally most discussed by young people 10–13 years of age on the phone and text services compared with other age ranges. Sexual abuse and violence were most frequently discussed by children 0–5 and 6–9 years of age across services. Discussion:Our analysis provides a unique snapshot into the concerns faced by children and youth across Canada, as well as the issues for which KHP is seen as an accessible place to seek support. Our findings can guide the future development of health promotion activities, and assist in new service development.
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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 | 0.002 | 0.002 |
| Science and technology studies | 0.006 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".