The impact of knowledge, attitudes and beliefs on the engagement of primary and community-based healthcare professionals in cancer care: a literature review
Bibliographic record
Abstract
BACKGROUND: Primary health services are well placed to reinforce prevention, early intervention, and connected care. Despite this important role, primary care providers (PCPs) have a limited capacity to meet the varied needs of people with cancer and their carers - furthermore, the reasons for this largely remain unexplored. SCOPE: To identify: (1) the knowledge, attitudes, and beliefs held by health professionals and patients that can influence the engagement of PCPs with the early detection of cancer and follow-up care; (2) evidence that attitudes and beliefs can be modified with measureable impact on the engagement of PCPs with cancer care; and (3) potential targets for intervention. This was achieved through a review of English publications from 2000 onwards, sourced from six academic databases and complemented with a search for grey literature. FINDINGS: A total of 4212 articles were reviewed to identify studies conducted in the UK, Canada, Holland (or The Netherlands), Australia, or New Zealand given the comparable role of PCPs. Several factors hinder PCP participation in cancer care, all of which are related to knowledge, attitudes, and beliefs. Patients and specialists are uncertain about the role that primary care could play and whether their primary care team has the necessary expertise. PCPs have varied opinions about the ideal content of follow-up programs. Study limitations include: the absence of well accepted definitions of key terms; the indexing systems used by databases to code publications, which may have obscured all relevant publications; the paucity of robust research; and possible researcher bias which was minimized through independent review by trained reviewers and the implementation of rigorous inter-rater reliability measures. CONCLUSIONS: Knowledge, attitudes, and beliefs influence PCP engagement in cancer care. It is important to develop shared understandings of these terms because the knowledge, attitudes, and beliefs of PCPs, specialists, patients, and their families can influence the effectiveness of treatment plans.
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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 | 0.006 | 0.002 |
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.004 |
| 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".