The relationship between consultation modality and mental health professional type and perceived quality of care and mental health outcomes: A comparison between employed and unemployed individuals
Bibliographic record
Abstract
Mental health is becoming increasingly acknowledged as a critical factor to one's well-being. Poor mental health can have serious impacts, particularly among working and non-working adults, requiring the need for effective treatments and interventions tailored to them. The type of mental health professional consulted and the type of consultation modality may be associated with individuals' perceptions of the quality of care that they receive as well as their mental health outcomes. Therefore, this study aims to examine the relationship between the type of consultation with different mental health professionals and the perceived quality of care and mental health outcomes among employed and unemployed Canadians. Data was utilized from the 2024 Mental Health and Access to Care Survey by Statistics Canada. Independent variables included the type of mental health professional consulted (psychiatrist, family doctor, psychologist, and social worker) and consultation modality (in-person, remote, and hybrid). Primary outcome variables were self-reported quality of care and perceived mental health outcomes. Multivariable logistic regression models were used to calculate odds ratios and 95% confidence intervals, controlling for age, gender, marital status, and visible minority status. A total of 1,222 participants were analyzed. Unemployed participants who accessed hybrid psychiatry services were significantly less likely, about one-sixth, to report lower quality of care than those using in-person services (AOR: 0.16; 95% CI: 0.02-0.98). Similarly, those who used hybrid family doctor services were less likely, about one-fifth, to report lower quality of care (AOR: 0.21; 95% CI: 0.07-0.66). No statistically significant differences in mental health outcomes were found across consultation modality and professional type for both employed and unemployed groups. By analyzing both the modality of care and the professional consulted, notable differences emerged in self-reported quality of care. Future research should further explore how inter-professional collaboration can improve the quality of care and mental health outcomes.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".