This study explores the application of Weiner's cognitive-emotional model of helping behaviour to care staff responses to challenging behaviour of people with learning disabilities. Participants were 20 residential care staff who worked with people with challenging behaviour and 20 who did not. Six examples of challenging behaviour were presented, and for each behaviour participants were asked to give a probable cause, rate attributions of stability, internality, globality and controllability for their cause, their optimism for change of the behaviour, their evaluation of the behaviour and a person showing the behaviour, their emotional response to the behaviour and their willingness to put extra effort in to helping change the behaviour. Data were analysed using correlation and regression methods. Carers working with people with challenging behaviour were more likely to evaluate the person more positively and report they would be more likely to offer extra effort in helping. A path analysis showed that helping behaviour was best predicted by optimism, which was best predicted by negative emotion which was best predicted by the attribution of controllability. We conclude that attributions and emotions reported by carers in response to challenging behaviour are consistent with Weiner's cognitive-emotional model of helping behaviour. Formulating carer behaviour using such models offers the possibility of using cognitive-behavioural methods in working with staff beliefs, emotions and behaviour in response to challenging behaviour.
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http://dx.doi.org/10.1111/j.2044-8260.1998.tb01279.x | DOI Listing |
J Infect Dev Ctries
December 2024
Faculty of Medicine, Eastern Mediterranean University, Famagusta, N. Cyprus via Mersin 10, Turkey.
Introduction: The global healthcare system faced unparalleled challenges during the coronavirus disease 2019 (COVID-19) pandemic, potentially reshaping antibiotic usage trends. This study aimed to evaluate the knowledge, perceptions, and observations of community pharmacists concerning antibiotic utilization during and after the pandemic; and offer crucial insights into its impact on antibiotic usage patterns and infection dynamics.
Methodology: This cross-sectional study involved 162 community pharmacists in Northern Cyprus.
J Infect Dev Ctries
December 2024
Faculdade de Medicina de Campos, Campos dos Goytacazes, Brazil.
Introduction: Despite efforts by health organizations to share evidence-based information, fake news hindered the promotion of social distancing and vaccination during the coronavirus disease 2019 (COVID-19) pandemic. This study analyzed COVID-19 knowledge and practices in a vulnerable area in northern Rio de Janeiro, acknowledging the influence of the complex social and economic landscape on public health perceptions.
Methodology: This cross-sectional study was conducted in Novo Eldorado - a low-income, conflict-affected neighborhood in Campos dos Goytacazes - using a structured questionnaire, following the peak of COVID-19 deaths in Brazil (July-December 2021).
Soc Work Health Care
January 2025
Faculty of Clinical Medicine, Hanoi University of Public Health, Hanoi, Vietnam.
Studies on the hospital social work workforce in global contexts remain unexplored. This study aims to describe the workforce status for hospital social work in Vietnam. This study involved 676 central, provincial, and district hospitals in Vietnam.
View Article and Find Full Text PDFBMC Health Serv Res
January 2025
Australian Centre for Health Services Innovation and Centre for Healthcare Transformation, School of Public Health and Social Work, Faculty of Health, Queensland University of Technology, Brisbane, QLD, Australia.
Background: Unwarranted clinical variation presents a major challenge in contemporary healthcare, indicating potential inequalities and inefficiencies, and unrealised potential for better outcomes. Despite an increasing focus on unwarranted clinical variation, and consideration of efforts to address this challenge, evidence-based strategies which achieve this are limited. Audit and feedback of healthcare processes (process auditing) and clinician engagement are important tools which may help to reduce unwarranted clinical variation, however their application in maternity care is yet to be thoroughly explored.
View Article and Find Full Text PDFBMC Nurs
January 2025
Nursing Department, Hamad Medical Corporation, Doha, P.O. Box 3050, Qatar.
Background: Artificial Intelligence (AI) is increasingly applied in healthcare to boost productivity, reduce administrative workloads, and improve patient outcomes. In nursing, AI offers both opportunities and challenges. This study explores nurses' perspectives on implementing AI in nursing practice within the context of Jordan, focusing on the perceived benefits and concerns related to its integration.
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