Key informant perspectives on pharmacogenomic (PGx) testing for antidepressant prescribing in primary care in Ontario, Canada: a qualitative description study
Bibliographic record
Abstract
OBJECTIVES: Many patients with major depressive disorder must try multiple antidepressants before they identify a drug that is both effective and tolerable. Pharmacogenomic (PGx) testing may provide clinicians with guidance around medication choice based on a patient's drug response-related genetic variants. However, this technology is not routinely used in clinical care in Canada, and the views of key actors in the implementation process are largely unknown. The objective of this study was to qualitatively elicit the perspectives and attitudes of clinicians, scientists, policy actors and members of industry about PGx testing to guide antidepressant prescribing in primary care via interviews to help inform implementation policies for this technology. DESIGN: We conducted a qualitative description study. Data analysis proceeded in parallel with data collection and consisted of an inductive qualitative content analysis. SETTING: The focus of this study was implementation of PGx testing in primary care in Ontario, Canada. PARTICIPANTS: We conducted semistructured interviews with 28 individuals who had professional experience relevant to the implementation of PGx testing for depression care ('key informants'). Geographical limits for recruitment were applied based on the transferability of key informants' expertise to the Ontario setting; included participants worked in Canada, the USA and Europe. RESULTS: Participants described views about PGx testing relating to benefits and harms of this technology; their interpretation of the evidence base; implementation-oriented considerations and industry involvement. Overall, participants spoke enthusiastically about PGx testing, but emphasised genetic information is only one component of decision-making about medication prescription. Most endorsed implementation in primary care and felt a pre-emptive approach to testing would be ideal. CONCLUSIONS: Key informants consider the use of PGx testing to guide antidepressant prescribing in primary care as having both patient-level and system-level benefits. Concerns raised centred primarily around clinician education and barriers to access. Future research should focus on questions relating to feasibility of system-wide implementation.
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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 | 0.015 | 0.019 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.023 | 0.016 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 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".