Pharmacogenomic Testing for Major Depression: A Qualitative Study of the Perceptions of People with Lived Experience and Professional Stakeholders
Bibliographic record
Abstract
OBJECTIVES: With increasing evidence for the clinical utility of pharmacogenomic (PGx) testing for depression, there is a growing need to consider issues related to the clinical implementation of this testing. The perspectives of key stakeholders (both people with lived experience [PWLE] and providers) are critical, but not frequently explored. The purpose of this study was to understand how PWLE and healthcare providers/policy experts (P/HCPs) perceive PGx testing for depression, to inform the consideration of clinical implementation within the healthcare system in British Columbia (BC), Canada. METHODS: We recruited two cohorts of participants to complete individual 1-h, semi-structured interviews: (a) PWLE, recruited from patient and research engagement networks and organizations and (b) P/HCPs, recruited via targeted invitation. Interviews were audiotaped, transcribed verbatim, de-identified, and analysed using interpretive description. RESULTS: Seventeen interviews were completed with PWLE (7 with experience of PGx testing for depression; 10 without); 15 interviews were completed with P/HCPs (family physicians, psychiatrists, nurses, pharmacists, genetic counsellors, medical geneticists, lab technologists, program directors, and insurers). Visual models of PWLE's and P/HCP's perceptions of and attitudes towards PGx testing were developed separately, but both were heavily influenced by participants' prior professional and/or personal experiences with depression and/or PGx testing. Both groups expressed a need for evidence and numerous considerations for the implementation of PGx testing in BC, including the requirement for conclusive economic analyses, patient and provider education, technological and clinical support, local testing facilities, and measures to ensure equitable access to testing. CONCLUSIONS: While hopeful about the potential for therapeutic benefit from PGx testing, PWLE and P/HCPs see the need for robust evidence of utility, and BC-wide infrastructure and policies to ensure equitable and effective access to PGx testing. Further research into the accessibility, effectiveness, and cost-effectiveness of various implementation strategies is needed to inform PGx testing use in BC.
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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 | 0.014 | 0.019 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.010 | 0.011 |
| Scholarly communication | 0.004 | 0.005 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.002 | 0.004 |
| 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".