The rules of engagement: physician engagement strategies in intergroup contexts
Bibliographic record
Abstract
PURPOSE: Recognition of the importance and difficulty of engaging physicians in organisational change has sparked an explosion of literature. The social identity approach, by considering engagement in terms of underlying group identifications and intergroup dynamics, may provide a framework for choosing among the plethora of proposed engagement techniques. This paper seeks to address this issue. DESIGN/METHODOLOGY/APPROACH: The authors examined how four disparate organisations engaged physicians in change. Qualitative methods included interviews (109 managers and physicians), observation, and document review. FINDINGS: Beyond a universal focus on relationship-building, sites differed radically in their preferred strategies. Each emphasised or downplayed professional and/or organisational identity as befit the existing level of inter-group closeness between physicians and managers: an independent practice association sought to enhance members' identity as independent physicians; a hospital, engaging community physicians suspicious of integration, stressed collaboration among separate, equal partners; a developing integrated-delivery system promoted alignment among diverse groups by balancing "systemness" with subgroup uniqueness; a medical group established a strong common identity among employed physicians, but practised pragmatic co-operation with its affiliates. RESEARCH LIMITATIONS/IMPLICATIONS: The authors cannot confirm the accuracy of managers perceptions of the inter-group context or the efficacy of particular strategies. Nonetheless, the findings suggested the fruitfulness of social identity thinking in approaching physician engagement. PRACTICAL IMPLICATIONS: Attention to inter-group dynamics may help organisations engage physicians more effectively. ORIGINALITY/VALUE: This study illuminates and explains variation in the way different organisations engage physicians, and offers a theoretical basis for selecting engagement strategies.
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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 | 0.036 | 0.056 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.011 | 0.042 |
| Scholarly communication | 0.019 | 0.015 |
| Open science | 0.002 | 0.015 |
| Research integrity | 0.005 | 0.005 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".