Viewpoints about collaboration between primary care and public health in Canada
Bibliographic record
Abstract
BACKGROUND: Although there is a global movement toward health system integration and collaboration, little is known about values, beliefs, and attitudes towards collaboration between stakeholders in public health (i.e. promotion, protection, and prevention with vulnerable groups and/or at the population level) and primary care (i.e., family practices, nurse-led clinics). The purpose of this study was to explore viewpoints of key stakeholders regarding primary care (PC) and public health (PH) collaboration in Canada. METHODS: We used Q-methodology to identify common viewpoints held by participants who attended a national meeting in Canada in 2010 to discuss PC and PH collaboration. The study was conducted in two phases. In Phase 1 a Q-sample, a Q-sort table, and a short demographic questionnaire were developed which were used in Phase 2 for data collection. The Q-sorts then were analysed to identify the salient factors and consensus statements. RESULTS: In total, 25 multidisciplinary individuals including researchers, policy-makers, directors, managers, and practitioners (e.g., nurses, family physicians, dietitians) participated. Using a by-person factor analysis, three factors (salient viewpoints) emerged. Factors were named based on their distinguishing statements as follows: a) System Driven Collaborators, b) Cautious Collaborators, and c) Competent Isolationists. System Driven Collaborators strongly believed that a clear mandate from the top is needed to enable PH, PC and the rest of the health system to effectively work together and that people in different branches in the Ministry/ Ministries have to strongly believe in collaboration, actively support it, and develop directed policies to foster organizations work together. Cautious Collaborators strongly supported the idea of having better consciousness-raising about what collaborations might be possible and beneficial, and also reflecting on the collaborations already in place. The Competent Isolationists strongly believed that it is necessary for PC and PH sectors to spend time to ensure that both parties clearly understand the differences between their roles. They believe that physicians, nurses, and social workers will not see the value in collaboration because they lack inter-professional educational programs. CONCLUSIONS: Different viewpoints are held by stakeholders around PC and PH collaboration which have the potential to influence the success of collaborations. Understanding and managing these differences is important to assist change management processes required to build and maintain strong PC and PH collaborations.
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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 | 0.012 | 0.022 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.029 | 0.007 |
| Scholarly communication | 0.008 | 0.002 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.002 | 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".