Research Article
Mental Wellness Needs Among Staff at Machakos County Referral Hospital: A Cross‑Sectional Study
Issue:
Volume 15, Issue 3, June 2026
Pages:
37-45
Received:
27 January 2026
Accepted:
10 March 2026
Published:
22 July 2026
DOI:
10.11648/j.pbs.20261503.11
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Abstract: Background: Healthcare workers are increasingly exposed to occupational stressors that predispose them to poor mental wellbeing and burnout, particularly in resource-constrained public health settings. Understanding staff mental wellness needs is essential for informing effective institutional wellness interventions. Objective: This study assessed the prevalence of work-related stress and burnout, coping mechanisms, utilization of mental health services, and staff perceptions regarding the need for a structured wellness program at Machakos County Referral Hospital. Methods: A descriptive cross-sectional online Survey was conducted among 182 clinical and non-clinical staff members. Data was collected using a structured self-administered questionnaire covering demographic characteristics, Self-reported stress frequency, mental wellbeing, Self-reported exhaustion experience, coping strategies, organizational support, awareness and utilization of mental health services, and preferred wellness interventions. Descriptive statistics and chi-square tests were used for data analysis. Results: Work-related stress was highly prevalent, with 91.2% of respondents reporting feeling stressed at least sometimes. Self-reported exhaustion was nearly universal, reported by 93.4% of participants. Only 7.1% rated their mental wellbeing as excellent, while 20.3% rated it as poor or very poor. High workload, lack of support, and lack of recognition were the most cited contributors to burnout. Gender, age, employment type, job role, and years of service were not significantly associated with burnout (p > 0.05). Coping strategies were predominantly informal, including talking to colleagues, rest, and prayer, while professional mental health service utilization was low (15.4%), mainly due to confidentiality concerns and fear of stigma. Despite moderate awareness of available services (65.9%), utilization remained limited. A strong majority (92.9%) expressed the need for a structured staff wellness program, with stress management workshops and recreational activities being the most preferred interventions. Conclusion: There is a high burden of stress and self-reported exhaustion among staff at Machakos County Referral Hospital, coupled with low utilization of formal mental health services. Staff demonstrate strong readiness for structured wellness interventions. Institutional investment in comprehensive, confidential, and accessible staff wellness programs is urgently required to promote workforce wellbeing and sustain quality healthcare delivery.
Abstract: Background: Healthcare workers are increasingly exposed to occupational stressors that predispose them to poor mental wellbeing and burnout, particularly in resource-constrained public health settings. Understanding staff mental wellness needs is essential for informing effective institutional wellness interventions. Objective: This study assessed ...
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Research Article
Algorithmic Mediation, Learner Agency, and Cognitive Autonomy in AI-Enhanced Online Learning Environments
Cristina-Georgiana Voicu*
Issue:
Volume 15, Issue 3, June 2026
Pages:
46-52
Received:
3 January 2026
Accepted:
15 January 2026
Published:
22 July 2026
DOI:
10.11648/j.pbs.20261503.12
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Abstract: This article examined the psychological and behavioral implications of artificial intelligence integration in online learning environments, with a focus on algorithmic mediation and its influence on learner agency, cognitive autonomy, and self-regulated learning. AI-enhanced platforms increasingly employ personalization algorithms, predictive analytics, and adaptive feedback to structure learning pathways and guide learner behavior. Using a conceptual-analytical research design, the study synthesized peer-reviewed literature from psychology, behavioral sciences, and educational research to analyze how these algorithmic mechanisms interact with cognitive and motivational processes. The analysis drew on established theoretical frameworks in self-determination theory, cognitive psychology, and behavioral regulation to map algorithmic guidance onto learner perceptions of control, responsibility, and autonomy. Findings indicated that adaptive sequencing and continuous feedback may enhance perceived competence and reduce cognitive load, while simultaneously externalizing decision-making processes that are central to autonomous learning. Algorithmic nudging and data-driven recommendations were shown to recalibrate self-regulatory behaviors by shifting regulation from internally driven metacognitive processes toward externally mediated cues embedded in system design. Variations in the intensity of algorithmic guidance were associated with corresponding differences in perceived autonomy, intrinsic motivation, and reliance on external regulation. By clarifying the cognitive and behavioral mechanisms through which AI-mediated systems shape learning behavior, the study contributed to psychological understandings of autonomy in digital learning environments and provided a theoretically grounded perspective relevant to the design of autonomy-supportive AI-enhanced educational systems.
Abstract: This article examined the psychological and behavioral implications of artificial intelligence integration in online learning environments, with a focus on algorithmic mediation and its influence on learner agency, cognitive autonomy, and self-regulated learning. AI-enhanced platforms increasingly employ personalization algorithms, predictive analy...
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