Identifying barriers and facilitators to screening for depression among newcomers: a survey study
Bibliographic record
Abstract
Background And Research Aim: Clinical depression among newcomers (immigrants, refugees, and/or asylum seekers) is a significant concern, and guidelines remain unclear on effective screening methods. There are patient-level, provider-level, and system-level factors that contribute to screening challenges, such as (but not limited to) lack of allied health supports, limited community services for positive screens, and unavailability of language translation services. This study aims to survey office-based family physicians in the Kingston, Frontenac, Lennox, and Addington (KFL&A) region of Ontario, Canada to identify potential facilitators and barriers to screening. Methods: A 10-minute online survey was developed using the Qualtrics platform, guided by the following working hypotheses: 1) Most family physicians in the region are not routinely screening newcomers for clinical depression. 2) Barriers to routine screening will include lack of time during clinical encounters, lack of personnel to complete screening, the inability to facilitate continuity of care with the correct mental health services, and potentially stigma around mental health conversations. 3) Facilitators to routine screening will include allied health teams that can screen before clinical visits, practice-type (notably team-based care models), geographical location (urban compared to rural), and access to continued mental health services. Data will be analyzed with descriptive, bivariate, and multivariable statistical methods. To enhance content validity and clarity, a structured pre-testing process was pursued. Experts in the field of newcomer medicine were consulted first for their feedback, followed by feedback from another set of physicians working in diverse practice models, ahead of finalizing the questionnaire. The survey questionnaire is now being actively circulated across the KFL&A region and data collection is ongoing. Preliminary results will be shared at the conference. Next Steps And Possible Future Research Directions: The next steps of this research include completing data collection and analysis and disseminating results to both academic audiences and regional health policy leadership. If research resources allow expansion into a mixed-methods project, we may add a qualitative component with semi-structured interviews of physicians to further understand their experiences. The survey questionnaire (and potentially interview guide, if expanded) may be eventually adapted for scale-up research to examine the perspectives of physicians from across Canada and internationally. Significance And Implications: Newcomers represent an equity-deserving group facing significant challenges in both health and social status; thus, this research is meaningful from an Equity, Diversity, and Inclusion (EDI) lens. Previous studies have evaluated the efficacy of screening, but there is limited research on the implementation of screening and on understanding the barriers family physicians face. Research results can inform improvement of local, culturally appropriate resources and screening approaches. Investigating primary and secondary prevention of newcomer mental health leads into the conversation of better implementing allied health into care teams. This research can inform expansion of culturally competent team-based care that is integrated with allied health and community services. By critically evaluating our current policies, this research may provide suggestions for new, more holistic practices that aim for collaborative efforts within communities.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".