https://journal.achsm.org.au/index.php/achsm <p>The Asia Pacific Journal of Health Management (APJHM) is a peer-reviewed journal for managers of organisations offering healthcare and aged care services. The APJHM aims to promote the discipline of health management throughout the region by facilitating the transfer of knowledge among readers by widening the evidence base for management practices.<br /><br />*Print 1(1);2006 - 5(1);2010 Online 4(2);2009 - current<br />*ISSN 2204-3136 (online); ISSN 1833-3818 (print)</p> Australasian College of Health Service Management en-US Asia Pacific Journal of Health Management 1833-3818 https://journal.achsm.org.au/index.php/achsm/article/view/6513 <h1>Abstract</h1> <p>Hospitals are adopting artificial intelligence (AI) faster than they are learning how nurses respond to it. Drawing on job demands–resources (JD-R) theory, this study examines whether nurses' AI self-efficacy, a personal resource, is related to their innovative work behavior through two parallel mechanisms: a resource-gain path through schedule idiosyncratic deals (i-deals) and a resistance-reduction path through active innovation resistance. Survey data were collected in person from 355 registered nurses in hospitals in Lahore, Pakistan, and analyzed with confirmatory factor analysis, path analysis and 5,000 bootstrap resamples. AI self-efficacy was positively related to innovative work behavior (<em>B</em> = 0.890, <em>p</em> &lt; .001) and schedule I-deals (<em>B</em> = 0.600, <em>p</em> &lt; .001) and negatively related to active innovation resistance (<em>B</em> = −0.872, <em>p</em> &lt; .001). Both indirect effects were significant (through schedule i-deals: 0.088, 95% CI [0.044, 0.168]; through active innovation resistance: 0.058, 95% CI [0.021, 0.119]), and a strong direct effect remained, indicating complementary partial mediation. Confident nurses thus appear to innovate more partly because they secure greater control over their working time and partly because they evaluate AI less negatively, although these mechanisms carry only a modest share of the total effect. The findings extend JD-R theory by showing that a technology-specific personal resource operates through both the acquisition of job resources and the appraisal of a new demand, identify AI self-efficacy as an antecedent of i-deals, and suggest that hospitals should combine AI capability building with flexible rostering and participative implementation.</p> <p>&nbsp;</p> Fahad Saddique Copyright (c) 21 1 https://journal.achsm.org.au/index.php/achsm/article/view/6512 <p><strong>Objective: </strong>To describe temporal, geographic, institutional, and perpetrator patterns of publicly reported violence involving healthcare workers (HCWs) and healthcare institutions in Nepal; examine associations between patient death and selected forms of violence; and summarize documented legal responses.</p> <p><strong>Design: </strong>Retrospective descriptive study of publicly reported incidents from January 1, 2006, to May 31, 2025.</p> <p><strong>Setting: </strong>Nepal; national and regional media reports, healthcare watchdog platforms, and official institutional notices or statements.</p> <p><strong>Main outcome measures: </strong>Incident frequency and characteristics, including location, institution, setting, violence type, perpetrator, patient-death context, and documented legal or administrative outcomes. Associations between patient death and physical assault or property damage were expressed as odds ratios (ORs) with 95% confidence intervals (CIs).</p> <p><strong>Results: </strong>We identified 280 unique incidents. Reported incidents increased significantly over time, particularly from 2016 onward (p &lt; 0.05), and were concentrated in urban districts and high-acuity hospital settings. Patient relatives were identified as perpetrators in 72.9% of incidents, and multiple perpetrators were involved in 83.9%. Patient death was reported in 67.1% of incidents. Patient death was associated with lower odds of physical assault (OR 0.13, 95% CI 0.07–0.24) and higher odds of property damage (OR 3.43, 95% CI 1.85–6.37). Documented legal consequences were uncommon.</p> <p><strong>Conclusions:</strong> Publicly reported violence involving HCWs and healthcare institutions in Nepal is a persistent and increasingly reported problem. Strengthening institutional prevention, communication and grievance mechanisms, incident reporting, security, and enforcement of existing legal protections should be prioritized.</p> <p><strong>Key words:</strong> Healthcare workers; occupational violence; workplace violence; patient safety; Nepal</p> Sulabh Kumar Shrestha Copyright (c) 21 1