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Emerging Technologies to Promote Psychosocial and Occupational Well-Being in University...
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Emerging Technologies to Promote Psychosocial and Occupational Well-Being in University Students and Healthcare Workers: Innovation and Public Health Challenges

A special issue of Healthcare (ISSN 2227-9032).

Deadline for manuscript submissions: 31 August 2026 | Viewed by 1429

Special Issue Editors

Dr. Cesar Ivan Aviles Gonzalez

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Guest Editor
Department of Medicine and Surgery, University of Enna Kore, 94100 Enna, Italy
Interests: mental health; anxiety; depression; psychodiagnostics; psychosomatics; nursing care
Special Issues, Collections and Topics in MDPI journals
Dr. Ermanno Vitale

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Guest Editor
Department of Medicine and Surgery, University of Enna Kore, 94100 Enna, Italy
Interests: occupational medicine; aerospace and aeronautical medicine; work-related diseases; health and safety at work; occupational epidemiology; biomedical risk assessment; legal medicine; occupational stress and burnout; preventive medicine; workplace ergonomics and surveillance
Special Issues, Collections and Topics in MDPI journals
Dr. Giovanni Gioiello

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Guest Editor
Department of Medicine and Surgery, University of Enna Kore, 94100 Enna, Italy
Interests: organizational well-being; nursing skills; leadership and public health
Dr. Felice Curcio

E-Mail Website
Guest Editor
Faculty of Medicine and Surgery, University of Sassari (UNISS), 07100 Sassari, Italy
Interests: occupational well-being; psychosocial risks; person-centered care; nursing education; academic stress; mentoring in healthcare; organizational resilience; healthcare workforce; quality of working life; soft skills in nursing
Dr. Alina Renghea

E-Mail Website
Guest Editor
Faculty of Health Sciences and Faculty of Medicine, Francisco de Vitoria University, Majadahonda, 28223 Madrid, Spain
Interests: palliative care; nursing ethics; health education; quality of life; transcultural nursing; community nursing; nursing education; disability; dependence

Special Issue Information

Dear Colleagues, 

The increasing digitalization of educational and healthcare environments has profoundly transformed conditions in areas of study and in the workplace. In this evolving landscape, both university students and healthcare workers face high levels of stress, emotional overload, anxiety, and risk of burnout, which directly impact their health and performance.

This Special Issue aims to explore how emerging technologies—such as virtual reality, artificial intelligence, e-health platforms, mobile mental health applications, and biofeedback—can serve as effective tools to promote psychosocial and occupational well-being, while also reducing mental health risks among these key populations.

We are seeking original research articles; quantitative, qualitative, or mixed-methods studies; systematic reviews; pilot projects; and theoretical contributions from researchers, healthcare professionals, technologists, psychologists, educators, and public health policymakers analyzing the impact, accessibility, effectiveness, and ethical challenges of these technologies in academic and clinical settings.

Dr. Cesar Ivan Aviles Gonzalez
Dr. Ermanno Vitale
Dr. Giovanni Gioiello
Dr. Felice Curcio
Dr. Alina Renghea
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 250 words) can be sent to the Editorial Office for assessment.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Healthcare is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2700 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • psychosocial well-being 
  • emerging technologies 
  • mental health in healthcare workers 
  • university students 
  • academic and clinical burnout 
  • virtual reality and e-health 
  • mental health promotion 
  • digital interventions 
  • digital public health 
  • artificial intelligence in healthcare

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Further information on MDPI's Special Issue policies can be found here.

Published Papers (2 papers)

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Research

27 pages, 1622 KB  
Article
Detecting Burnout Among Undergraduate Computing Students with Supervised Machine Learning
by Eldar Yeskuatov, Lee Kien Foo and Sook-Ling Chua
Healthcare 2025, 13(23), 3182; https://doi.org/10.3390/healthcare13233182 - 4 Dec 2025
Viewed by 426
Abstract
Background: Academic burnout significantly impacts students’ cognitive and psychological well-being and may result in adverse behavioral changes. An effective and timely detection of burnout in the student population is crucial as it enables educational institutions to mobilize necessary support systems and implement intervention [...] Read more.
Background: Academic burnout significantly impacts students’ cognitive and psychological well-being and may result in adverse behavioral changes. An effective and timely detection of burnout in the student population is crucial as it enables educational institutions to mobilize necessary support systems and implement intervention strategies. However, current survey-based detection methods are susceptible to response biases and administrative overhead. This study investigated the feasibility of detecting academic burnout symptoms using machine learning trained exclusively on university records, eliminating reliance on psychological surveys. Methods: We developed models to detect three burnout dimensions—exhaustion, cynicism, and low professional efficacy. Five machine learning algorithms (i.e., logistic regression, support vector machine, naive Bayes, decision tree, and extreme gradient boosting) were trained using features engineered from administrative data. Results: Results demonstrated considerable variability across burnout dimensions. Models achieved the highest performance for exhaustion detection, with logistic regression obtaining an F1 score of 68.4%. Cynicism detection showed moderate performance, while professional efficacy detection has the lowest performance. Conclusions: Our findings showed that automated detection using passively collected university records is feasible for identifying signs of exhaustion and cynicism. The modest performance highlights the challenges of capturing psychological constructs through administrative data alone, providing a foundation for future research in unobtrusive student burnout detection. Full article
(This article belongs to the Special Issue Emerging Technologies to Promote Psychosocial and Occupational Well-Being in University Students and Healthcare Workers: Innovation and Public Health Challenges)
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15 pages, 259 KB  
Article
Who Thrives in Medical School? Intrinsic Motivation, Resilience, and Satisfaction Among Medical Students
by Julia Terech, Pola Sarnowska, Klaudia Bikowska, Mateusz Guziak and Maciej Walkiewicz
Healthcare 2025, 13(23), 3049; https://doi.org/10.3390/healthcare13233049 - 25 Nov 2025
Viewed by 544
Abstract
Background: Medical education is highly demanding and often entails stress, pressure, and competition. Understanding what drives students’ satisfaction is essential to support learning and well-being. This study aims to identify factors associated with satisfaction with medical education among Polish medical students, focusing on [...] Read more.
Background: Medical education is highly demanding and often entails stress, pressure, and competition. Understanding what drives students’ satisfaction is essential to support learning and well-being. This study aims to identify factors associated with satisfaction with medical education among Polish medical students, focusing on motivation, personal circumstances, resilience, and the long-term impact of COVID-19. Methods: In a cross-sectional online survey, 334 students from years one, four, and six completed measures of satisfaction with medical studies (nineteen items), motivation (ten items), resilience (using the Brief Resilience Scale), self-rated health, financial situation, global life satisfaction, and study-related stress, plus eight items on COVID-19 impact. Associations were assessed using Spearman correlations and Mann–Whitney U tests. Results: Higher satisfaction was associated with intrinsic motivation (e.g., personal decision to study medicine or interest in medicine), more favorable personal circumstances (better health, financial situation, higher global life satisfaction, and lower stress), and greater individual resilience. Students reporting pandemic-related setbacks (knowledge gaps, reduced confidence, curtailed clinical exposure, and interpersonal skills) showed lower satisfaction with overall experience, relationships, theoretical and practical classes, and perceived future competence. Conclusions: Intrinsic motivation, resilience, and supportive personal circumstances were linked to higher satisfaction, whereas enduring pandemic disruptions coincided with lower satisfaction across domains. Targeted strategies that cultivate intrinsic motivation and resilience and address financial/health stressors and COVID-19 learning gaps may enhance student satisfaction. Full article
(This article belongs to the Special Issue Emerging Technologies to Promote Psychosocial and Occupational Well-Being in University Students and Healthcare Workers: Innovation and Public Health Challenges)
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