A dual process model linking dispositional resistance to perceived benefits and change self-efficacy: a study amongst Canadian healthcare professionals
Bibliographic record
Abstract
PURPOSE: This study aims to explore the dual process model linking dispositional resistance to change with perceived benefits and change self-efficacy among healthcare professionals. It investigates how individual differences in resistance to change affect their perceptions and abilities during the early stages of organizational change. DESIGN/METHODOLOGY/APPROACH: A two-wave prospective study was conducted with 222 healthcare professionals in a Canadian healthcare setting, with a four-month time lag between waves. The model integrates two pathways: an affective pathway through uncertainty of change and a cognitive pathway through the legitimacy of change, to examine their mediation roles in the relationship between dispositional resistance and change outcomes. FINDINGS: The study yielded three key findings. First, dispositional resistance to change was not directly associated with change outcomes. Second, uncertainty of change, acting as an affective mediator, significantly influenced the relationship between dispositional resistance and perceived benefits and self-efficacy in change implementation. Third, legitimacy of change, as a cognitive mediator, also played a crucial role in this process. PRACTICAL IMPLICATIONS: These findings highlight the importance of addressing both emotional and cognitive factors in managing change in healthcare settings. Interventions that reduce uncertainty and enhance the perceived legitimacy of change may improve healthcare professionals' ability to perceive its benefits and integrate it effectively. ORIGINALITY/VALUE: This study provides new insights into the mechanisms through which dispositional resistance affects individuals' responses to organizational change, particularly in the context of healthcare. It underscores the need for a dual-process approach in understanding and managing resistance to change.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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".