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Age-Specific Differences in Association Between Personality and Changes in Outing Behaviors During the COVID-19 Pandemic in Japan: Cross-Sectional Web-Based Questionnaire Survey

Age-Specific Differences in Association Between Personality and Changes in Outing Behaviors During the COVID-19 Pandemic in Japan: Cross-Sectional Web-Based Questionnaire Survey

For implementation to be adequate, it must be recognized that people’s preventive behavior is influenced by factors such as their health and information literacy, gender, age, and personality traits [18-30]. Personality traits have been reported to be associated with various types of behaviors related to the pandemic [25-28,30].

Kaori Yamaguchi, Takemi Akahane, Emi Yasuda, Manabu Akahane

Online J Public Health Inform 2025;17:e63120

Fear of Missing Out, Social Media Addiction, and Personality Traits Among Nursing Students: Cross-Sectional Study

Fear of Missing Out, Social Media Addiction, and Personality Traits Among Nursing Students: Cross-Sectional Study

Personality traits have a considerable role in individuals’ susceptibility to FOMO and SMA. Research has identified several personality traits that may contribute to these phenomena [7]. For example, individuals high in neuroticism, considered by tendencies toward anxiety and other negative emotions, may be more prone to experiencing FOMO and engaging in excessive social media use as a means of stress-coping strategy [7,9].

Amira Alshowkan, Emad Shdaifat

JMIR Nursing 2025;8:e71502

Evaluating Older Adults’ Engagement and Usability With AI-Driven Interventions: Randomized Pilot Study

Evaluating Older Adults’ Engagement and Usability With AI-Driven Interventions: Randomized Pilot Study

An individual’s personality can influence acceptance and needs to be considered as a part of usability and the engagement with technology-driven interventions [16]. In younger populations, openness to experience and agreeableness, have been shown to be positively related to usability of technology [17]. Personality traits are characteristics of individuals that typically remain stable over the adult life course.

Marcia Shade, Changmin Yan, Valerie K Jones, Julie Boron

JMIR Form Res 2025;9:e64763

The Association of Psychological Factors With Willingness to Share Health-Related Data From Technological Devices: Cross-Sectional Questionnaire Study

The Association of Psychological Factors With Willingness to Share Health-Related Data From Technological Devices: Cross-Sectional Questionnaire Study

Research has identified not only digital literacy, older age, and privacy knowledge as factors associated with willingness to share technology data but also psychological factors such as personality traits and generalized trust [13,16,17]. However, there is a knowledge gap regarding the magnitude of associations between psychological factors and willingness to share personal health technology data.

Marijn Eversdijk, Emma Rixt Douma, Mirela Habibovic, Willem Johan Kop

JMIR Form Res 2025;9:e64244

Personality and Health-Related Quality of Life of Older Chinese Adults: Cross-Sectional Study and Moderated Mediation Model Analysis

Personality and Health-Related Quality of Life of Older Chinese Adults: Cross-Sectional Study and Moderated Mediation Model Analysis

The HRQo L of older adults is affected by a variety of physical, psychological, and social factors, among which personality plays a nonnegligible role [3]. Personality is a unique and relatively stable indicator in adulthood, affecting an individual’s thoughts, feelings, and behaviors across situations [4,5]. A systematic review showed that personality accounted for up to 45% of psychosocial HRQo L and 39% of physical HRQo L [6].

Xing-Xuan Dong, Yueqing Huang, Yi-Fan Miao, Hui-Hui Hu, Chen-Wei Pan, Tianyang Zhang, Yibo Wu

JMIR Public Health Surveill 2024;10:e57437

A Machine Learning Model to Predict Patients’ Adherence Behavior and a Decision Support System for Patients With Metastatic Breast Cancer: Protocol for a Randomized Controlled Trial

A Machine Learning Model to Predict Patients’ Adherence Behavior and a Decision Support System for Patients With Metastatic Breast Cancer: Protocol for a Randomized Controlled Trial

The tuning of the model permits adding additional predictors (personality traits, self-efficacy for coping with cancer, sense of coherence, pain, anxiety, depression, risk perception, and Qo L) known to influence medication adherence behavior and that are not available retrospectively [10]. These data are used to improve the predictive power of the machine learning model and its capacity to profile patients’ adherence behaviors and to provide an individual risk value of nonadherence.

Marianna Masiero, Gea Elena Spada, Virginia Sanchini, Elisabetta Munzone, Ricardo Pietrobon, Lucas Teixeira, Mirtha Valencia, Aline Machiavelli, Elisa Fragale, Massimo Pezzolato, Gabriella Pravettoni

JMIR Res Protoc 2023;12:e48852

Cancer Pain Experience Through the Lens of Patients and Caregivers: Mixed Methods Social Media Study

Cancer Pain Experience Through the Lens of Patients and Caregivers: Mixed Methods Social Media Study

First, given that the data were retrieved from an online social network, demographics and user personal characteristics (eg, personality, anxiety, depression, etc) were missing from our analyses. As for interpersonal characteristics, we could not match patients to their caregivers. The source of the data (the cancer subreddit) did not provide such information.

Chiara Filipponi, Mariam Chichua, Marianna Masiero, Davide Mazzoni, Gabriella Pravettoni

JMIR Cancer 2023;9:e41594

Identifying Personality Characteristics and Indicators of Psychological Well-Being Associated With Attrition in the Motivation Makes the Move! Physical Activity Intervention: Randomized Technology-Supported Trial

Identifying Personality Characteristics and Indicators of Psychological Well-Being Associated With Attrition in the Motivation Makes the Move! Physical Activity Intervention: Randomized Technology-Supported Trial

Personality characteristics have been regarded as among the most essential contributors to behavioral choices [19]. Personality reflects individual differences in thinking, feeling, and behaving, and it matures through age. In the widely acknowledged 5-factor model of personality (ie, the “Big Five” model), personality characteristics are categorized into 5 broader continuums [20,21]. Individuals scoring high in neuroticism tend to experience negative emotions, such as anger, fear, and stress.

Kaisa Kaseva, Mari Tervaniemi, Enni Heikura, Kaisamari Kostilainen, Maritta Pöyhönen-Alho, J Kevin Shoemaker, Robert J Petrella, Juha E Peltonen

JMIR Form Res 2022;6(11):e30285