Identifying strategies for implementing a clinical guideline for cancer-related fatigue: a qualitative study
Bibliographic record
Abstract
BACKGROUND: Clinical practice guidelines assist health professionals' (HPs) decisions. Costly to develop, many guidelines are not implemented in clinical settings. This paper describes an evaluation of contextual factors to inform clinical guideline implementation strategies for the common and distressing problem of cancer-related fatigue (CRF) at an Australian cancer hospital. METHODS: A qualitative inquiry involving interviews and focus groups with consumers and multidisciplinary HPs explored key Canadian CRF guideline recommendations. Four HP focus groups examined the feasibility of a specific recommendation, while a consumer focus group examined experiences and preferences for managing CRF. Audio recordings were analysed using a rapid method of content analysis designed to accelerate implementation research. Strategies for implementation were guided by the Consolidated Framework for Implementation Research. RESULTS: Five consumers and 31 multidisciplinary HPs participated in eight interviews and five focus groups. Key HP barriers to fatigue management were insufficient knowledge and time; and lack of accessible screening and management tools or referral pathways. Consumer barriers included priority for cancer control during short health consultations, limited stamina for extended or extra visits addressing fatigue, and HP attitudes towards fatigue. Enablers of optimal fatigue management were alignment with existing healthcare practices, increased HP knowledge of CRF guidelines and tools, and improved referral pathways. Consumers valued their HPs addressing fatigue as part of treatment, with a personal fatigue prevention or management plan including self-monitoring. Consumers preferred fatigue management outside clinic appointments and use of telehealth consultations. CONCLUSIONS: Strategies that reduce barriers and leverage enablers to guideline use should be trialled. Approaches should include (1) accessible knowledge and practice resources for busy HPs, (2) time efficient processes for patients and their HPs and (3) alignment of processes with existing practice. Funding for cancer care must enable best practice supportive care.
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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 | 0.021 | 0.028 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.008 | 0.006 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.002 | 0.002 |
| 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".