The Impact of Psychosocial Factors on Health Behaviors

A special issue of Behavioral Sciences (ISSN 2076-328X). This special issue belongs to the section "Health Psychology".

Deadline for manuscript submissions: 30 November 2025 | Viewed by 893

Special Issue Editor


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Guest Editor
School of Interdisciplinary Arts and Sciences, University of Washington Tacoma, Tacoma, WA 98402-3100, USA
Interests: the impact of psychosocial factors; implicit attitudes; reinforcement sensitivity; health behaviors; adaptation of a comprehensive model of health status; psychological measurement

Special Issue Information

Dear Colleagues,

There has been a lot of research investigating the prediction of psychological factors for health behaviors, including smoking, drinking, physical activity, diet, risky sexual behavior, and health-seeking behavior in clinical health psychology. The goal of these research studies must be to contribute to improving the health status in various populations by changing the psychological factors and thus health behaviors in a timely manner. However, this transition has not been very smooth since the relationship between psychological factors and health behavior or health behavior change is very complicated. For example, it is hard to decide or select specific psychological factors among many others to explain health behavior; the prediction of psychological factors is different in various health behaviors; psychological factors and health behavior are not a single factor or behavior (e.g., quit attempts vs. cessation maintenance as quitting smoking), which diversifies variables or measurements for the same factor or behavior; the relationship between psychological factors and health behaviors is different among various ethnic, racial, or social groups; and it is difficult to explain when and how the psychological factors have an impact on health behavior. Therefore, we still need more studies in this area of research. In this Special Issue of Behavioral Sciences, we welcome studies that successfully address these issues or limits, or imply potential solutions in the future, and that significantly expand the current level of understanding of the impact of cognitive, emotional, behavioral, and environmental factors on various health behaviors for improving the health status in populations.

Dr. Hyoung Suk Lee
Guest Editor

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Keywords

  • psychological factors
  • cognitive factors
  • emotional factors
  • health behavior
  • substance use
  • physical activity
  • diet
  • health seeking behavior

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Published Papers (1 paper)

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Research

19 pages, 630 KiB  
Article
Primary and Emergency Care Use: The Roles of Health Literacy, Patient Activation, and Sleep Quality in a Latent Profile Analysis
by Dietmar Ausserhofer, Verena Barbieri, Stefano Lombardo, Timon Gärtner, Klaus Eisendle, Giuliano Piccoliori, Adolf Engl and Christian J. Wiedermann
Behav. Sci. 2025, 15(6), 724; https://doi.org/10.3390/bs15060724 - 24 May 2025
Viewed by 127
Abstract
Background/Objectives: Healthcare utilization is a behavioral phenomenon influenced by psychosocial factors. This study took place in South Tyrol, a culturally diverse autonomous province in northern Italy, and aimed to identify latent profiles of primary healthcare users based on health literacy, patient activation, sleep [...] Read more.
Background/Objectives: Healthcare utilization is a behavioral phenomenon influenced by psychosocial factors. This study took place in South Tyrol, a culturally diverse autonomous province in northern Italy, and aimed to identify latent profiles of primary healthcare users based on health literacy, patient activation, sleep quality, and service use, and to examine the sociodemographic and health-related predictors of profile membership. Methods: A cross-sectional survey was conducted with a representative adult sample (n = 2090). The participants completed the questionnaire in German or Italian. Latent profiles were identified via model-based clustering using Gaussian mixture modeling and four z-standardized indicators: total primary healthcare contacts (general practice and emergency room visits), HLS-EU-Q16 (health literacy), PAM-10 (patient activation), and B-PSQI (sleep quality). The optimal cluster solution was selected using the Bayesian Information Criterion (BIC). Kruskal–Wallis and chi-square tests were used for between-cluster comparisons of the data. Multinomial logistic regression was used to examine the predictors of cluster membership. Results: Among the 1645 respondents with complete data, a three-cluster solution showed a good model fit (BIC = 19,518; silhouette = 0.130). The identified profiles included ‘Balanced Self-Regulators’ (72.8%), ‘Struggling Navigators’ (25.8%), and ‘Hyper-Engaged Users’ (1.4%). Sleep quality could be used to differentiate between different levels of service use (p < 0.001), while low health literacy and patient activation were key features of the high-utilization groups. Poor sleep and inadequate health literacy were associated with increased healthcare contact. Conclusions: The latent profiling revealed distinct patterns in health care engagement. Behavioral segmentation can inform more tailored and culturally sensitive public health interventions in diverse settings such as South Tyrol. Full article
(This article belongs to the Special Issue The Impact of Psychosocial Factors on Health Behaviors)
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