The relationship of health-related expectancies, fruit and vegetable intake, and positive mood: expectancies are important, but not in the way you expect

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Elliot Smith ◽  
Richard Stevenson ◽  
Leah Dudley ◽  
Heather Francis

PurposeGreater fruit and vegetable (F&V) intake has been linked to more positive mood. Here, the purpose of this paper is to examine if this relationship is mediated by expectancies about their benefit to health/mental health.Design/methodology/approachParticipants completed a new questionnaire to assess expectancies related to F&V intake. This was administered alongside a validated food-frequency measure of F&V intake, an assessment of positive and negative mood state and other measures.FindingsParticipants held strongly positive expectations about the physical and mental health benefits of consuming F&V. The authors observed a significant relationship between self-reported F&V intake and positive mood (d = 0.52). Importantly, this effect was largely (but not completely) independent of expectancies. The authors also observed that expectancies about F&V intake were independently predictive of positive mood (d = 0.47).Originality/valueThis is the first study to explore expectancy effects in the mental health benefits of F&V intake. These data suggest that positive expectancies about F&V intake, and F&V intake itself, are both predictive of positive mood. The former finding is probably a placebo effect, whereby people believe they are consuming sufficient F&V (even if they are not) and so experience mood-related benefits due to their positive expectations. The latter finding is consistent with F&V exerting a biologically beneficial effect on the brain.

2020 ◽  
Vol 16 (6) ◽  
pp. 276-277
Author(s):  
Jay Kara

There are huge physical and mental health benefits of exercise, even more so during these unprecedented times. Here, fitness coach Jay Kara offers his guide to the perfect home workout


Author(s):  
Kory Floyd ◽  
Benjamin E. Custer

Affectionate communication constitutes verbal behaviors (e.g., saying “I love you”), nonverbal gestures (e.g., hugging, handholding), and socially supportive behaviors (e.g., helping with a project) that humans employ to develop and maintain close relationships with others. In addition to its relational benefits, affectionate communication contributes to health and wellness for both senders and receivers. Affection exchange theory (AET) addresses the questions of why humans engage in affectionate communication and why diverse benefits are associated with such behaviors. A robust empirical literature supports AET’s contention that both expressing and receiving affectionate behavior are associated with physical and mental health benefits. Despite these contributions, however, some compelling questions about affectionate communication remain to be addressed, and AET can provide a useful framework for doing so.


Author(s):  
Dr. Navin Banarase

Waking up at Brahmya Muhurta is one of the most important procedure in Ayurveda, because our Dinacharya starts with this procedure. The physical and mental health benefits of waking up early has been mentioned in many literatures, but the physiological correlation between Modern Science and Ayurveda has not been explained anywhere. This article will elaborate the Sharira concept of Brahmya Muhurta according to Ayurveda and Modern Medical Science.


2020 ◽  
Vol 2020 (6) ◽  
pp. 20-22
Author(s):  
Heather Henry

Heather Henry explains the physical and mental health benefits of vocal exercises for young people


2013 ◽  
Vol 27 (1) ◽  
pp. 30-41 ◽  
Author(s):  
Erin E. Horn ◽  
Yishan Xu ◽  
Christopher R. Beam ◽  
Eric Turkheimer ◽  
Robert E. Emery

2021 ◽  
Author(s):  
Chad Stecher ◽  
Vincent Berardi ◽  
Rylan Fowers ◽  
Jaclyn Christ ◽  
Yunro Chung ◽  
...  

BACKGROUND Using contextual cues for performing daily behaviors is one proven method for establishing healthy habits, but objective measures of this habit formation process do not currently exist. Mobile health (mHealth) tools provide the detailed, longitudinal data necessary for constructing objective measures of habit strength, which can improve our understanding of habit formation and help design more effective mHealth interventions for promoting healthier habits. OBJECTIVE Use behavioral data from a commercial mindfulness mediation mobile phone app to construct a measure of meditation habit strength and estimate the association between meditation habits and app users’ perceived mental health benefits. METHODS App usage data were analyzed for 2,771 paying subscribers of a meditation mobile phone app who also volunteered to complete a survey assessing their perceived changes in physical and mental health from using the app. An objective measure of meditation habit strength was calculated based on the similarity in the timing of app usage between consecutive days. Receiver operating characteristic (ROC) curve analysis was used to validate the habit measure as a strong predictor of users’ future behavior, and variable importance statistics from random forest models were used to corroborate these findings. Logistic regressions were used to estimate the association between the meditation habit measure and self-reported physical and mental health benefits. RESULTS The temporal similarity in users’ daily app use before completing the survey, as measured by the dynamic time warping (DTW) distance between app usage on consecutive days, significantly predicted app usage 28 days and six months after the survey, even after controlling for users’ demographic and socioeconomic characteristics, total app sessions, duration of app use, and number of days with any app use. Additionally, the temporal similarity measure significantly increased in the area under the ROC curve (AUC) for models predicting any future app use in 28 days (AUC = 0.868 with DTW and AUC = 0.850 without DTW [P < 0.001]) and for models predicting any app use in six months (AUC = 0.821 with DTW and AUC = 0.802 without DTW [P < 0.001]). Finally, a one-percent increase in the temporal similarity of users’ daily meditation practice with the app over the six weeks prior to the survey was associated with an increased odds of reporting mental health improvements by 2.94 OR (95% CI: 1.832 – 6.369). CONCLUSIONS The temporal similarity of meditation app use was a significant predictor of future behavior, which suggests that this measure captures important components of the cued habit formation process. Additionally, temporal similarity was associated with greater perceived mental health benefits, which demonstrates additional mental health benefits may be derived from forming strong meditation habits. Future research should examine how temporal similarity measures characterize habits using mHealth data in other behavioral settings.


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