Cognitive and emotional factors in health behaviour: Dual-process reasoning, cognitive styles and optimism as predictors of healthy lifestyle, healthy behaviours and medical adherence

Tomljenović, Helena; Bubić, Andreja

doi:10.1007/s12144-019-00268-z

Cited by 16 publications

(11 citation statements)

References 49 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…This is because persons with heightened ADS have been theorized to be inclined to repeatedly avoid expending mental effort to gather and evaluate facts as part of optimal problem solving and decision-making processes (Dalgleish & Werner-Seidler, 2014;Patzelt, Kool, Millner, & Gershman, 2019). Moreover, elevated ADS can compromise analytical thinking, goal-directed pursuits, and reality testing skills (Culbreth, Westbrook, & Barch, 2016;Tomljenovic & Bubic, 2019;Zainal & Newman, 2019), as well as increase vulnerability to cognitive distortions (e.g., jumping to conclusions, black-and-white thinking) over long durations (Barron et al, 2018). Thus, based on this scar theory (Allemand, Grünenfelder-Steiger, & Flückiger, 2018;Schmidt, Lerew, & Joiner, 2000), increased ADS would likely relate to lower trait NFC across time.…”

Section: Revised Manuscript (Clean Version)mentioning

confidence: 99%

Curiosity helps: Growth in need for cognition bidirectionally predicts future reduction in anxiety and depression symptoms across 10 years

Zainal

Newman

2022

Journal of Affective Disorders

View full text Add to dashboard Cite

Introduction: Decreased motivational tendency to seek out, engage in, and enjoy investing in complex cognitive processes in a sustained manner (need for cognition; NFC) may be a predictor and consequence of heightened anxiety and depression symptoms (ADS).However, the majority of investigations on this topic have been cross-sectional, which hinders causal inferences. Methods: The current study thus determined the within-person relations between NFC and ADS by using random intercept cross-lagged panel model (RI-CLPM) and bivariate dual latent change score (BLCS) approaches to separate between-and within-person effects. RI-CLPM and BLCS also present with advantages of adjusting for regression to the mean, baseline scores, autoregressive and lagged effects, and minimizing measurement error. Community-dwelling adults (n = 6750) completed the Mental Health Inventory-5 and trait-level NFC scales approximately every one year across 10 years. Results: RI-CLPM showed that within persons, lower level of NFC predicted higher future level of ADS, and vice versa (d = -0.852 to -0.498). Likewise, BLCS demonstrated that within persons, smaller change in NFC forecasted larger subsequent increase in ADS, and conversely (d = -0.631 to -0.519). Findings remained after adjusting for socio-demographic covariates. Conclusion: Consistent with theories, findings suggested that the within-person level-to-future level and change-to-future change relations among NFC and ADS were bi-directional and negative, with moderate-to-large effect sizes. Targeting NFC may treat or prevent the emergence of depression and anxiety disorders. Such efforts may include augmenting or personalizing evidence-based cognitive behavioral therapeutic strategies for individuals with or at-risk for heightened ADS.

show abstract

Section: Revised Manuscript (Clean Version)mentioning

confidence: 99%

Curiosity helps: Growth in need for cognition bidirectionally predicts future reduction in anxiety and depression symptoms across 10 years

Zainal

Newman

2022

Journal of Affective Disorders

View full text Add to dashboard Cite

show abstract

“…This theory has been confirmed by previous empirical studies in various contexts, including in the health context. Instead of focusing on the theory to explain people's healthy behaviors (e.g., Hamilton, Gibbs, Keech, & Hagger, 2020 ; Strobach, Englert, Jekauc, & Pfeffer, 2020 ; Thoma, Weiss-Cohen, Filkuková, & Ayton, 2021 ; Tomljenovic & Bubic, 2021 ), this research demonstrated the information processing routes in regard to how people form their views on vaccines. The findings showed that people's vaccine skepticism is formed by cyberchondria (affective aspect) and the perceived risk of the vaccine (cognitive aspect) due to information overload in the COVID-19 pandemic context.…”

Section: Discussionmentioning

confidence: 87%

How does information overload about COVID-19 vaccines influence individuals’ vaccination intentions? The roles of cyberchondria, perceived risk, and vaccine skepticism

Honora

Wang

Chih

2022

Computers in Human Behavior

View full text Add to dashboard Cite

This research proposes and tests an integrated model to explain how information overload influence vaccine skepticism and vaccination intention. In addition, this research investigates the effectiveness of using a celebrity endorsement strategy in promoting vaccination and compares its effectiveness with other endorsement types. A survey study (Study 1) was conducted to examine the mechanism underlying the impact of the COVID-19 vaccine information overload on vaccine skepticism that, subsequently, affects vaccination intention. It also examined the moderating role of celebrity endorsement trustworthiness. The results indicate that information overload positively influenced vaccine skepticism through cyberchondria and perceived risk of the vaccine, which subsequently reduces vaccination intention. The negative effect of vaccine skepticism on vaccination intention was weakened by the celebrity endorsement that was considered trustworthy. A follow-up experimental study (Study 2) was performed to compare the effectiveness of celebrity endorsement with other endorsement types (i.e., government official and medical expert endorsements). The results showed that the celebrity endorsement was more effective in mitigating the negative effect of vaccine skepticism on vaccination intention compared to government official and medical expert. The findings provide practical insights into how governments can minimize people's vaccine skeptical views and increase their vaccination intentions.

show abstract

“…interpersonal trust (H2b) and less prone to normalize patient passivity (H3) will more frequently engage in non-adherence behaviors (e.g. [42][43]). Non-adherence was also examined with regards to sociodemographic variables, self-assessed health status, BMI, and smoking, but without speci c assumptions as to how they relate to non-adherence behaviors -this part of the analysis was exploratory.…”

Section: Current Studymentioning

confidence: 99%

Intentional non-adherence to official medical recommendations: An irrational choice or negative experience with the healthcare system?

Purić

Petrović

Živanović

et al. 2022

Preprint

View full text Add to dashboard Cite

Background: The World Health Organization recognizes non-adherence to treatment recommendations as a growing global problem. Questionnaires typically focus on only one non-adhering behavior, e.g., medication-taking, and target people with specific health conditions. In this preregistered study, we aimed to (1) develop a novel instrument suitable to the general population, consisting of non-adherence to prescribed therapy, self-medication, and avoidance to seek medical treatment, capturing intentional non-adherence (iNAR), (2) differentiate it from habitual non-adherence, such as smoking, and (3) relate iNAR to patient-related factors, such as sociodemographics, health status, and endorsement of irrational beliefs (conspiratorial thinking and superstitions), and to a set of healthcare-related beliefs and experiences. Methods: First, medical doctors provided a list of non-adherence behaviors in a focus group. To this list we added behaviors that fitted our definition of intentional non-adherence, identified in a thorough literature search. This initial list of 22 behaviors was further refined by a public health expert. The instrument was then tested on a sample of 583 participants, sufficiently powered to detect effects for all preregistered statistical analysis. Participants were recruited using an online snowballing procedure and via social networks. Results: Factor analysis yielded a one-factor solution, and the final 12-item iNAR questionnaire had satisfactory internal reliability (Cronbach’s alpha = .72). A hierarchical linear regression showed that, as expected, health condition variables and healthcare-related beliefs and experiences accounted for 14% of the variance of iNAR behaviors, whereas sociodemographics and irrational beliefs did not additionally contribute. In comparison, the same regression model with smoking (representative of habitual non-adherence) as a criterion variable, accounted for less than 3% of the variance, with education as the only significant predictor. Conclusions: We have constructed a brief, comprehensive, and reliable measure of iNAR behaviors. Normalization of patients’ passivity and, in particular, negative experiences with the healthcare system contributed to intentional, but not habitual non-adherence. We believe that public health interventions designed to discourage intentional non-adherence should foremost attempt to improve all patients' experiences with the system and build trust with their healthcare practitioners rather than aim at specific demographic groups or at correcting patients' unfounded beliefs.

show abstract

Cognitive and emotional factors in health behaviour: Dual-process reasoning, cognitive styles and optimism as predictors of healthy lifestyle, healthy behaviours and medical adherence

Cited by 16 publications

References 49 publications

Curiosity helps: Growth in need for cognition bidirectionally predicts future reduction in anxiety and depression symptoms across 10 years

Curiosity helps: Growth in need for cognition bidirectionally predicts future reduction in anxiety and depression symptoms across 10 years

How does information overload about COVID-19 vaccines influence individuals’ vaccination intentions? The roles of cyberchondria, perceived risk, and vaccine skepticism

Intentional non-adherence to official medical recommendations: An irrational choice or negative experience with the healthcare system?

Contact Info

Product

Resources

About