Safewards in acute medical/surgical care wards: Capability, Opportunity, Motivation and Behaviour model and Theoretical Domains Framework analysis
Bibliographic record
Abstract
BACKGROUND: Safewards is an evidence-based practice improvement model to minimise conflict in inpatient mental health units. There is limited published research on implementing Safewards in acute medical/surgical care wards. OBJECTIVE: To identify, from nurses' perspectives, barriers, and facilitators to implement four Safewards interventions in acute medical/surgical care wards. METHODS: This article reports qualitative findings from a funded mixed-method evaluation of the Safewards Acute Care Pilot Project. Six focus group interviews comprising 35 nursing staff from four hospitals in Victoria, Australia were completed between April and October 2022. The semi-structured interview guide included questions developed using the Capability, Opportunity, Motivation and Behaviour model. Data was thematically analysed and mapped to a matrix combining Capability, Opportunity, Motivation and Behaviour model and the Theoretical Domains Framework to elucidate barriers and facilitators to implementing four Safewards interventions in acute medical/surgical care wards. RESULTS: Three components in the Capability, Opportunity, Motivation and Behaviour model and three Theoretical Domains Framework domains were identified as barriers to the adoption of Safewards in acute medical/surgical care wards. Specific barriers included physical opportunity challenges related to the environmental context and resources domains. The key themes included time constraints and competing priorities; lack of physical space and infrastructure; and poor patient uptake due to lack of understanding. Gaps emerged as a psychological capability barrier within the Theoretical Domains Framework knowledge domain. Additionally, resistance to practice changes was associated with the motivation component of the Capability, Opportunity, Motivation and Behaviour model. Conversely, six TDF domains were relevant to facilitating the implementation of the Safewards interventions: memory, attention, and decision processes; physical skills; social influences; social/professional role and identity; goals; and beliefs about consequences. Key facilitators included the Safewards interventions serving as reminders to focus on compassionate nursing care; nursing staff possessing the skillset for interventions; peer pressure and mandated change; supportive and passionate leadership; presence of champions to drive momentum; belief in nursing staff ownership and expertise for leading implementation; personal commitment to improve work environments and care quality; and the belief that Safewards would improve ward culture. CONCLUSIONS: Addressing barriers and leveraging facilitators can inform strategies for enhancing staff capability to implement Safewards in acute care wards. Specifically, a tailored, multilayered approach focusing on leadership support, training, resources, patient input, and feedback can promote effective adoption of the Safewards model and adaptation of discrete interventions. TWEETABLE ABSTRACT: Safewards adaptation: Addressing barriers like resources, space, and patient awareness; leveraging peer modelling and leadership strategies for success.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".