Accessibilité à la psychothérapie subventionnée par l’État : comparaisons entre les perspectives des psychologues et des psychothérapeutes
Bibliographic record
Abstract
Objectives Within the Quebec context, as well as the larger Canadian and International context, increasing access to mental health care treatment has become a major health care priority (see Peachey, Hicks, & Adams, 2013). Initiatives to increase access through government-funded psychotherapy have been successfully implemented in Australia and the United Kingdom. The current study sought to document how licensed psychologists and psychotherapists in Quebec differ in their attitudes about the components of these government-funded psychotherapy programs and increasing access to psychotherapy treatment.Methods The target population for the study included both psychologists and psychotherapists whom were licensed to practice psychotherapy with the Ordre of Psychologists of Quebec. Participants (N = 1 275) were recruited by email to participate in an online questionnaire focusing on components such as the services that should be offered in a new government-funded psychotherapy model (eg., individual therapy, family therapy; including employment and debt counselling), the choice and autonomy clinicians have in their treatment interventions, the role of the referring General Practitioner (GP), the fees per psychotherapy hour, the hiring structure (e.g., in the public sector versus reimbursing private psychotherapy services), among others.Results The results indicated that psychotherapists were more in favour of including family and couple therapy, and employment/vocational counselling than psychologists. Psychologists were more in favour of using evidence-based practices as well as tracking treatment outcomes using validated measures, and publishing treatment satisfaction ratings to the public. Psychotherapists were more in favour of being paid on a session-to-session basis as opposed to be being hired on a salaried basis to offer government-funded psychotherapy.Conclusions Given that psychologists and psychotherapists differ in their training background and have historically played different roles in the health care system, it is important to understand how they differ in their perspectives on accessibility to psychotherapy. The implications for implementing government-funded psychotherapy initiatives in Quebec given the different professional perspectives of the two groups are discussed.
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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 | 0.008 | 0.023 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.007 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.012 | 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".