Determinants of guideline-concordant breast cancer screening by family physicians for women aged 40–49 years: a qualitative analysis
Bibliographic record
Abstract
BACKGROUND: Although the current Canadian Task Force on Preventive Health Care guideline recommends that physicians should inform women aged 40-49 years of the potential benefits and harms of screening mammography to support individualized decisions, previous reports of variation in clinical practice at the physician level suggest a lack of guideline-concordant care. We explored determinants (barriers and facilitators) of guideline-concordant care by family physicians regarding screening mammography in this age group. METHODS: We conducted qualitative semi-structured interviews by phone with family physicians in the Greater Toronto Area from January to November 2020. We structured interviews using the Theoretical Domains Framework to explore determinants (barriers and facilitators) of 5 physician screening behaviours, namely risk assessment, discussion regarding benefits and harms, decision or referral for mammography, referral for genetic counselling and referral to high-risk screening programs. Two independent researchers iteratively analyzed interview transcripts and deductively coded for each behaviour by domain to identify key behavioural determinants until saturation was reached. RESULTS: We interviewed 18 physicians (mean age 48 yr, 72% self-identified as women). Risk assessment was influenced by physicians' knowledge of risk factors, skills to synthesize risk and beliefs about utility. Physicians had beliefs in their capabilities to have informed patient-centred discussions, but insufficient knowledge regarding the harms of screening. The decision or referral for mammography was affected by emotions related to past patient outcomes, social influences of patients and radiology departments, and knowledge and beliefs about consequences (benefits and harms of screening). Referrals for genetic counselling and to high-risk screening programs were facilitated by their availability and by the knowledge and skills to complete forms. Lack of knowledge regarding which patients qualify and beliefs about consequences were barriers to referral. INTERPRETATION: Insufficient knowledge and skills for performance of risk assessment, combined with a tendency to overestimate benefits of screening relative to harms affected provision of guideline-concordant care. These may be effective targets for future interventions to improve guideline-concordant care.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".