Interactive mental health assessments for Chinese Canadians: A pilot randomized controlled trial in nurse <scp>practitioner‐led</scp> primary care clinic
Bibliographic record
Abstract
INTRODUCTION: Mental health conditions like depression and anxiety are on the rise, but access to care remains a challenge. Immigrants and racialized communities including Chinese Canadians experience high level of access barriers including communication with clinicians. With the aim to facilitate mental health communications, we tested an Interactive Computer-assisted Client Assessment Survey (iCCAS) in Cantonese/Mandarin and English at a nurse practitioner-led primary care clinic in Toronto. The iCCAS offers a touch-screen, pre-consultation survey with questions on depression, anxiety, post-traumatic stress, alcohol abuse, and social context. The program generates point-of-care reports for the clinician and patient. METHODS: A pilot randomized controlled trial examined the intervention impact on mental health discussion and symptom detection, compared with the usual care, followed by clinicians' qualitative interviews. RESULTS: Fifty self-identified Chinese adult patients participated (iCCAS = 26, Usual Care = 24), response rate 79.4%. Participant mean age was 44.8 years and 92% were immigrants. There was an increase of 19% and 15% in the mental health discussion and detection of symptoms in the iCCAS group compared with the usual care. More participants in the iCCAS group were referred to a social worker or psychiatrist. Patients found the use of iCCAS easy and clinicians identified its benefits for themselves (eg, early identification and comfort) and patients (eg, self-awareness and anonymity) and proposed practice-integration. DISCUSSION: The studied tool holds promise for enhancing clinician-patient mental health communications in primary care settings for overseas Chinese. Implications are discussed for in-person and virtual healthcare which could also inform responses to mental health crisis related to COVID-19.
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How this classification was reachedexpand
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".