Mental Health and Adaptation in Chronic Illness: Risky Factors and Resilience

Special Issue Editors


E-Mail Website
Guest Editor
Department of Psychology, University of Bologna, 40127 Bologna, Italy
Interests: psychological assessment; psychopathology; mental illness; clinical health psychology; sleep disorders; dyadic coping
Special Issues, Collections and Topics in MDPI journals

E-Mail Website
Guest Editor
Department of Psychology, Catholic University of Sacred Heart, Milan, Italy
Interests: body image and eating behavior psychopathology; obesity; psycho-cardiology; clinical health psychology; doctor–patient communication; effectiveness of psychotherapies; costs in clinical psychology and psychotherapy; motivational interventions for promoting healthy lifestyles; telemedicine and online therapy
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

In recent years, partly due to the increase in life expectancy and improvements in health care and pharmacotherapy, there has been an exponential increase in chronic illnesses. A chronic illness significantly affects a person’s physical and mental health, while also shaping their sense of identity, relationships with family, and social roles. Managing such a condition is a lifelong commitment, requiring major lifestyle changes, strict compliance with medications and treatments, and the adoption of preventive strategies. Psychological resilience and resources could facilitate the process of self-management. Furthermore, informal caregivers—often partners, spouses, relatives, or friends—are crucial to this process. They take on a variety of challenging responsibilities, including handling emergencies, mediating disagreements between patients and healthcare providers, aiding in treatment decisions, and supporting both the emotional and practical needs of the patient.

This Special Issue aims to explore the multifaceted effects of chronic illness on patients as well as risk and protective factors associated with health and psychological wellbeing to highlight emerging strategies and interventions to improve their quality of life and care. Furthermore, a focus on relational factors which could influence patient outcomes is also appreciated.

We invite you to submit original articles (quantitative analysis, both cross-sectional and longitudinal studies) and systematic review works.

Dr. Giada Rapelli
Dr. Giada Pietrabissa
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 100 words) can be sent to the Editorial Office for announcement on this website.

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. European Journal of Investigation in Health, Psychology and Education is an international peer-reviewed open access monthly 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 1400 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

  • chronic disease
  • self-management
  • health outcome
  • psychological adjustment
  • risk and protective factors
  • caregiving

Benefits of Publishing in a Special Issue

  • Ease of navigation: Grouping papers by topic helps scholars navigate broad scope journals more efficiently.
  • Greater discoverability: Special Issues support the reach and impact of scientific research. Articles in Special Issues are more discoverable and cited more frequently.
  • Expansion of research network: Special Issues facilitate connections among authors, fostering scientific collaborations.
  • External promotion: Articles in Special Issues are often promoted through the journal's social media, increasing their visibility.
  • e-Book format: Special Issues with more than 10 articles can be published as dedicated e-books, ensuring wide and rapid dissemination.

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

Published Papers (1 paper)

Order results
Result details
Select all
Export citation of selected articles as:

Research

17 pages, 1614 KiB  
Article
Risk Assessment Profiles for Caregiver Burden in Family Caregivers of Persons Living with Alzheimer’s Disease: An Exploratory Study with Machine Learning
by Laura Brito, Beatriz Cepa, Cláudia Brito, Ângela Leite and M. Graça Pereira
Eur. J. Investig. Health Psychol. Educ. 2025, 15(3), 41; https://doi.org/10.3390/ejihpe15030041 - 20 Mar 2025
Viewed by 522
Abstract
Alzheimer’s disease (AD) places a profound global challenge, driven by its escalating prevalence and the multifaceted strain it places on individuals, families, and societies. Family caregivers (FCs), who are pivotal in supporting family members with AD, frequently endure substantial emotional, physical, and psychological [...] Read more.
Alzheimer’s disease (AD) places a profound global challenge, driven by its escalating prevalence and the multifaceted strain it places on individuals, families, and societies. Family caregivers (FCs), who are pivotal in supporting family members with AD, frequently endure substantial emotional, physical, and psychological demands. To better understand the determinants of family caregiving strain, this study employed machine learning (ML) to develop predictive models identifying factors that contribute to caregiver burden over time. Participants were evaluated across sociodemographic clinical, psychophysiological, and psychological domains at baseline (T1; N = 130), six months (T2; N = 114), and twelve months (T3; N = 92). Results revealed three distinct risk profiles, with the first focusing on T2 data, highlighting the importance of distress, forgiveness, age, and heart rate variability. The second profile integrated T1 and T2 data, emphasizing additional factors like family stress. The third profile combined T1 and T2 data with sociodemographic and clinical features, underscoring the importance of both assessment moments on distress at T2 and forgiveness at T1 and T2, as well as family stress at T1. By employing computational methods, this research uncovers nuanced patterns in caregiver burden that conventional statistical approaches might overlook. Key drivers include psychological factors (distress, forgiveness), physiological markers (heart rate variability), contextual stressors (familial dynamics, sociodemographic disparities). The insights revealed enable early identification of FCs at higher risk of burden, paving the way for personalized interventions. Such strategies are urgently needed as AD rates rise globally, underscoring the imperative to safeguard both patients and the caregivers who support them. Full article
Show Figures

Figure 1

Back to TopTop