RESUMEN
The COVID-19 pandemic presented many psychological stressors which affected healthcare worker wellbeing. The aim of this study was to understand the factors that affect the wellbeing of healthcare professionals in the Kingdom of Saudi Arabia using Job-Demand and Resource (JD-R) Model. The proposal model consisted of demand factors (Work load-job demand, loneliness-personal demand), support factors (organizational support-job resource, and resilience-personal resource), mediators (burnout and work engagement), and outcome (wellbeing) A cross-sectional, descriptive study was conducted across 276 healthcare workers from hospitals and primary healthcare centers, including healthcare professionals, health associate professionals, personal care workers, health management and support personnel, and health service providers, and others between February-March 2022. The proposed model was tested using partial least squares structural equation modeling. Among the respondents, the majority were female (198, 71,7%), married (180, 65.2%), healthcare professionals (206, 74.6%), being more than 10 years in the profession (149, 51.6%), and non-Saudi nationality (171, 62.0%). Burnout accounted for a significant effect on wellbeing. Of the demands (workload and loneliness) and the resources (organizational support and resilience), workload had the greatest impact on burnout. Healthcare organizations should invest in reducing workloads and promoting resilience to reduce burnout and increase healthcare worker wellbeing.
Asunto(s)
Agotamiento Profesional , COVID-19 , Personal de Salud , Carga de Trabajo , Humanos , Femenino , Personal de Salud/psicología , Estudios Transversales , Masculino , Adulto , Carga de Trabajo/psicología , COVID-19/epidemiología , COVID-19/psicología , Agotamiento Profesional/psicología , Agotamiento Profesional/epidemiología , Arabia Saudita/epidemiología , Persona de Mediana Edad , Satisfacción en el Trabajo , SARS-CoV-2 , Soledad/psicología , Encuestas y Cuestionarios , Resiliencia Psicológica , Pandemias , Compromiso Laboral , Estrés Psicológico/epidemiología , Estrés Psicológico/psicologíaRESUMEN
BACKGROUND: Personal health records (PHRs) are eHealth tools designed to support patient engagement, patient empowerment, and patient- and person-centered care. Endorsement of a PHR by health care providers (HCPs) facilitates patient acceptance. As health care organizations in the Kingdom of Saudi Arabia begin to adopt PHRs, understanding the perspectives of HCPs is important because it can influence patient adoption. However, no studies evaluated HCPs' acceptance of PHRs in the Kingdom of Saudi Arabia. OBJECTIVE: The aim of this study was to identify predictors of HCPs' acceptance of PHRs using behavioral intention to recommend as a proxy for adoption. METHODS: This cross-sectional study was conducted among HCPs (physicians, pharmacists, nurses, technicians, others) utilizing a survey based on the Unified Theory of Acceptance and Use of Technology. The main theory constructs of performance expectancy, effort expectancy, social influence, facilitating conditions, and positive attitude were considered independent variables. Behavioral intention was the dependent variable. Age, years of experience, and professional role were tested as moderators between the main theory constructs and behavioral intention using partial least squares structural equation modeling. RESULTS: Of the 291 participants, 246 were included in the final analysis. Behavioral intention to support PHR use among patients was significantly influenced by performance expectancy (ß=.17, P=.03) and attitude (ß=.61, P<.01). No moderating effects were present. CONCLUSIONS: This study identified performance expectancy and attitude as predictors of HCPs' behavioral intention to recommend PHR to patients. To encourage HCPs to endorse PHRs, health care organizations should involve HCPs in the implementation and provide training on the features available as well as expected benefits. Future studies should be conducted in other contexts and include other potential predictors.