Intention to use personal health records and associated factors among healthcare providers in southwest Oromia region referral hospitals, Ethiopia: using the modified unified theory of acceptance and use technology 2 model

Frontiers in Digital Health, Год журнала: 2025, Номер 7

Опубликована: Фев. 25, 2025

A well-informed decision needs the collection of accurate and organized data, which is becoming more essential in healthcare industry due to increasing integration various technologies. The literature has revealed that magnitude intention use personal health records among providers low. Consequently, this study aimed assess providers' intentions its factors Ethiopia. facility-based cross-sectional was conducted 781 referral hospitals Southwest Oromia region, simple sampling technique used select participants providers. pretested self-administered questionnaire collect data. degree correlation between exogenous endogenous variables described validated using structural equation modeling AMOS 26. proportion 57.6%, 95% CI (53.9-61.2). Factors positively associated with were performance expectancy (β = 0.325, P < 0.01), effort 0.289, social influence 0.216, facilitating condition 0.242, 0.01). Age 0.269, 0.040, β 0.326, 0.001) moderated relationship expectancy, conditions records. In general, promising. Healthcare significantly influenced by influence, conditions. Hence, implementers need give priority enhancing provision a better system, knowledge skills providers, awareness creation staff providing continuous training.

Язык: Английский

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Transcultural Adaptation, Validation, Psychometric Analysis, and Interpretation of the 22-Item Thai Senior Technology Acceptance Model for Mobile Health Apps: Cross-Sectional Study

JMIR Aging, Год журнала: 2025, Номер 8, С. e60156 - e60156

Опубликована: Март 11, 2025

The rapid advancement of technology has made mobile health (mHealth) a promising tool to mitigate problems, particularly among older adults. Despite the numerous benefits mHealth, assessing individual acceptance is required address specific needs people and promote their intention use mHealth. This study aims adapt validate senior model (STAM) questionnaire for mHealth in Thai context. In this cross-sectional study, we adapted original, 38-item, English version STAM using 10-point Likert scale acceptability population. We translated into forward backward translation. A total 15 adults experts completed pilot were interviewed assess its validity. items then reworded revised better comprehension cross-cultural compatibility. construct validity was evaluated by multidimensional approach, including exploratory confirmatory factor analysis nonparametric item response theory analysis. Discriminative indices consisting sensitivity, specificity, area under receiver operating characteristic (AUROC) used determine appropriate banding discriminant Internal consistency assessed Cronbach α McDonald ω coefficients. Out 1100 participants with mean age 62.3 (SD 8.8) years, 360 (32.7%) aged 45-59 740 (67.3%) 60 years older. Of 40-item questionnaire, identified 22 loadings >0.4 across 7 principal components, explaining 91.45% variance. Confirmatory confirmed that 9-dimensional sets had satisfactory fit (comparative index=0.976, Tucker-Lewis index=0.968, root square error approximation=0.043, standardized squared residual=0.044, R2 each item>0.30). score D (low≤151, moderate 152-180, high≥181) preferred as optimal 22-item cutoff based on highest sensitivity 89% (95% CI 86.1%-91.5%) AUROC 72.4% 70%-74.8%) predicting final STAM, items, exhibited remarkable internal consistency, evidenced 0.88 0.87-0.89) 0.85 0.83-0.87). For all corrected item-total correlations ranged between 0.26 0.71. demonstrated psychometric properties both reliability. potential serve practical pre-older

Язык: Английский

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Integrating artificial intelligence (AI) in healthcare: advancing older adults’ health management in Saudi Arabia through AI-powered chatbots

PeerJ Computer Science, Год журнала: 2025, Номер 11, С. e2773 - e2773

Опубликована: Март 27, 2025

Background The healthcare sector is experiencing rapid digital advancements, with patients increasingly seeking quick and seamless interactions. Artificial intelligence (AI)-driven chatbots are becoming an integral part of elderly care, transforming provider-patient engagement supporting health behavior goals tailored to individual preferences, needs, limitations. Methods This study developed a comprehensive research framework incorporating various theoretical perspectives explore the determinants sustained use AI-powered among older adults. also examined mediating influence perceived humanness. model was evaluated using partial least squares structural equation modeling (PLS-SEM) on cross-sectional data collected from 158 individuals aged 60 above. Results findings show that satisfaction significantly influenced by facilitating conditions, hedonic motivation, confirmation, performance expectancy, effort expectancy. Perceived security plays critical role in shaping intention continue these chatbots. Moreover, analysis revealed humanness mediates relationship between continuous intentions users Saudi Arabia. Discussion provides valuable insights into factors influencing adults’ acceptance AI Arabia, particularly post-COVID-19 era. These enrich academic discourse offer actionable recommendations for organizations adapting evolving landscape.

Язык: Английский

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Navigation, Adoption, and Use of Digital Health Technologies for IBS Self-Management: Focus Group Study on Patient Experience and Decision-making (Preprint)

Опубликована: Март 26, 2025

Irritable bowel syndrome (IBS) is a common chronic gastrointestinal disorder that impairs functions and patients’ overall quality of life. IBS-focused digital health technologies (DHTs), including online resources mobile (mHealth) apps, have recently proliferated for patient use. However, research exploring experiences with navigating, adopting, or using commercial publicly available DHTs IBS self-management limited. To explore user decision-making in disease self-management. Semi-structured focus group interviews were conducted virtually to DHTs, their perspectives towards design features, process recommendations on improving experience uptake. Canadian-based patients who used mHealth apps manage symptoms recruited through purposive sampling from previous IBS-related studies. Discussions transcribed verbatim, inductive thematic analysis was performed NVivo 14. A modified version the Expanded Unified Theory Acceptance Use Technology (UTAUT2) model applied guide interpretation dynamic relationship between influences participants’ decisions around DHTs. Among eight participants (all females, mean age 55.3 years), two themes identified: (1) uncertainty impacts trustworthiness (2) drive adopt use The observed aligned constructs UTAUT2 (performance expectancy, effort social influence, facilitating conditions, hedonic motivation, price value, habit), addition trust risk decision-making. Digital literacy engagement also raised as crucial components Findings this study highlight current landscape existing gaps challenges While generally viewed positively value potential, consider several coexisting factors trade-offs Further investigations could enhance future developments iterations these tools improve confidence

Язык: Английский

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Effect of digital technologies on employee wellbeing and mental health

Behaviour and Information Technology, Год журнала: 2025, Номер unknown, С. 1 - 13

Опубликована: Апрель 3, 2025

Язык: Английский

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