Psychological Factors in Health Behaviors

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

Deadline for manuscript submissions: closed (31 August 2023) | Viewed by 3580

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Clinical Psychology, Fielding Graduate University, Santa Barbara, CA 93105, USA
Interests: cognitive behavioral therapy; trauma recovery; posttraumatic stress disorder; health psychology
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Special Issue Information

Dear Colleague,

According to the World Health Organization, seven of the top ten causes of death worldwide are noncommunicable illness with ischemic heart disease ranking number one accounting for 16% of the world’s deaths (World Health Organization, 2020). Many deaths due to chronic illnesses are preventable if lifestyle factors can be implemented to control or reduce the impact of the illness. For example, diabetes mellitus, the ninth leading cause of death worldwide, is significantly impacted by behavioral factors related to exercise, nutrition, and following medical protocols related to regular glucose monitoring and control. Similarly, outcomes secondary to ischemic heart disease are largely impacted by similar behavioral factors.

In addition to the clear role of health behaviors in noncommunicable illness, the COVID-19 pandemic has highlighted the role of personal behavior in the transmission of the virus. Simple actions such as choosing to wear facial coverings, maintaining social distancing, or deciding to get a vaccination clearly impacted the transmission of the virus. Much interest and research has begun to focus on psychological factors related to people’s decisions to engage in preventative public health behaviors related to communicable illnesses.

There are many theories explaining the interconnectedness of psychological constructs, health behavior, and health outcomes in both communicable and noncommunicable illnesses. Models such as the Health Belief Model and Theory of Planned Behavior attempt to connect constructs such as attitude, psychological barriers, and intentions with behavioral outcomes, which are in turn linked to illness outcomes. In addition, the Biopsychosocial Model has been widely accepted by both medical and mental health providers as one such holistic model of health.

There is a wealth of research supporting such models.

These psychological theories of health recognize that health behaviors can both negatively and positively impact health. Examples of negative health behaviors include smoking, lack of physical activity, poor dietary choices, and excessive alcohol consumption, to name a few. Some health behaviors that have a positive impact on health include engaging in regular physical activity, consuming a “healthy” diet, and engaging in stress management. Psychological constructs in such models include beliefs, attitudes, perceived barriers, and self-efficacy, among others. They also recognize the importance of environmental and cultural factors. Such theories attempt to create a broad and holistic understanding of the role of the individual and health care system in health outcomes.

This Special Issue of Healthcare entitled Psychological Factors in Health Behaviors encourages theoretically informed research that examines the impact of psychological constructs on health behaviors and outcomes. Research papers which take a holistic perspective examining the role of environmental, cultural, demographic, psychological, and behavioral factors on both communicable and noncommunicable illness are welcome.

References:

World Health Organization. (9 December 2020). The Top 10 Causes of Death. Retrieved from https://www.who.int/news-room/fact-sheets/detail/the-top-10-causes-of-death.

Dr. Connie Veazey
Guest Editor

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Keywords

  • health behavior
  • health outcomes
  • health psychology
  • chronic medical conditions
  • biopsychosocial model

Published Papers (2 papers)

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Research

11 pages, 895 KiB  
Article
Psychosocial Factors Associated with Self-Management in Patients with Diabetes
by Rodrigo León-Hernández, Andrea C. Rodríguez-Pérez, Yessica M. Pérez-González, María I. P. de Córdova, Raúl de León-Escobedo, Tranquilina Gómez-Gutiérrez and Filiberto Toledano-Toledano
Healthcare 2023, 11(9), 1284; https://doi.org/10.3390/healthcare11091284 - 30 Apr 2023
Cited by 1 | Viewed by 1520
Abstract
Despite the significant advances in research on diabetes, relatively few researchers have examined the theoretical and empirical usefulness of explanatory models that contribute to self-management of the disease. In response to the theoretical and empirical approaches related to this topic, the objective of [...] Read more.
Despite the significant advances in research on diabetes, relatively few researchers have examined the theoretical and empirical usefulness of explanatory models that contribute to self-management of the disease. In response to the theoretical and empirical approaches related to this topic, the objective of this research was to assess a hypothetical model to explain self-management behavior in patients with type II diabetes through structural equation modeling in a population of users of the services of the State Health Department of Tamaulipas, Mexico. The study used a cross-sectional and explanatory design. The sample was intentional. A total of 183 patients with a diabetes diagnosis completed a sociodemographic data questionnaire, the Partners in Health Scale, the Duke-UNC-11, the Family Apgar, the Self-Efficacy Scale, the Personal Health Questionnaire and the Physical Activity Scale. The results indicated that the hypothetical model was improved by excluding the exercise variable. The appropriate model was used to determine the effects of depression, social support, self-efficacy, family functioning, years of formal education and years with a diagnosis on self-management. The goodness-of-fit indices (GFIs) were good, i.e., χ2/gl = 0.89 (p = 0.529), root mean square error of approximation (RMSEA) = 0.000, and comparative fit index (CFI) = 1.000, with an acceptable degree of parsimony (PNFI = 0.409 and PGFI = 317). The model explained 33.6% of the variance. Therefore, this model represents an important advance in knowledge concerning self-management and provides empirical and theoretical evidence, particularly for the Mexican or Latino population. Full article
(This article belongs to the Special Issue Psychological Factors in Health Behaviors)
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17 pages, 873 KiB  
Article
The Brain Overwork Scale: A Population-Based Cross-Sectional Study on the Psychometric Properties of a New 10-Item Scale to Assess Mental Distress in Mongolia
by Battuvshin Lkhagvasuren, Tetsuya Hiramoto, Enkhnaran Tumurbaatar, Enkhjin Bat-Erdene, Gantsetseg Tumur-Ochir, Vijay Viswanath, Joshua Corrigan and Tsolmon Jadamba
Healthcare 2023, 11(7), 1003; https://doi.org/10.3390/healthcare11071003 - 31 Mar 2023
Cited by 6 | Viewed by 1490
Abstract
Identifying mental distress is a complex task, particularly when individuals experience physical symptoms. Traditional self-report questionnaires that detect psychiatric symptoms using emotional words may not work for these individuals. Consequently, there is a need for a screening tool that can identify both the [...] Read more.
Identifying mental distress is a complex task, particularly when individuals experience physical symptoms. Traditional self-report questionnaires that detect psychiatric symptoms using emotional words may not work for these individuals. Consequently, there is a need for a screening tool that can identify both the physical and mental symptoms of mental distress in individuals without a clinical diagnosis. Our study aimed to develop and validate a scale that measures mental distress by measuring the extent of brain overwork, which can be extrapolated as the burden of mental distress. In this population-based cross-sectional study, we recruited a total of 739 adults aged 16–65 years from 64 sampling centers of a cohort in Mongolia to validate a 10-item self-report questionnaire. Internal consistency was measured using McDonald’s ω coefficient. Test–retest reliability was analyzed using intraclass correlation coefficients. Construct and convergent validities were examined using principal component analysis (PCA) and confirmatory factor analysis (CFA). The Hospital Anxiety and Depression Scale (HADS) and the abbreviated version of World Health Organization Quality of Life (WHOQOL-BREF) were used to evaluate criterion validity. Among the participants, 70.9% were women, 22% held a bachelor’s degree or higher, 38.8% were employed, and 66% were married. The overall McDonald’s ω coefficient was 0.861, demonstrating evidence of excellent internal consistency. The total intraclass correlation coefficient of the test–retest analysis was 0.75, indicating moderate external reliability. PCA and CFA established a three-domain structure that provided an excellent fit to the data (RMSEA = 0.033, TLI = 0.984, CFI = 0.989, χ2 = 58, p = 0.003). This 10-item scale, the Brain Overwork Scale (BOS-10), determines mental distress in three dimensions: excessive thinking, hypersensitivity, and restless behavior. All the items had higher item-total correlations with their corresponding domain than they did with the other domains, and correlations between the domain scores had a range of 0.547–0.615. BOS-10 correlated with HADS, whereas it was inversely correlated with WHOQOL-BREF. In conclusion, the results suggest that BOS-10 is a valid and reliable instrument for assessing mental distress in the general population. The scale screens for mental distress that is characterized by subjective symptoms such as excessive thinking, hypersensitivity, and restless behavior. The current findings also demonstrate that the BOS-10 is quantitative, simple, and applicable for large group testing. This scale may be useful for identifying at-risk individuals who may require further evaluation and treatment for mental distress. Full article
(This article belongs to the Special Issue Psychological Factors in Health Behaviors)
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