scholarly journals Utilizing Participatory Research to Engage Underserved Populations to Improve Health-Related Outcomes in Delaware

Nutrients ◽  
2021 ◽  
Vol 13 (7) ◽  
pp. 2353
Author(s):  
Shannon M. Robson ◽  
Samantha M. Rex ◽  
Katie Greenawalt ◽  
P. Michael Peterson ◽  
Elizabeth Orsega-Smith
Keyword(s):  
Physical Activity ◽  
Health Behavior ◽  
Health Behaviors ◽  
Participatory Research ◽  
Cooperative Extension ◽  
Underserved Populations ◽  
Community Outreach ◽  
Outreach Program ◽  
Health Related ◽  
Improve Health

Cooperative Extension is a community outreach program. Despite its large reach, there is a need for the evaluation of changes in health-related outcomes for individuals engaged with Cooperative Extension. A team-based challenge was developed using community-engaged participatory research integrated with Cooperative Extension to encourage healthy eating and physical activity behaviors through Cooperative Extension programming. Thus, the primary purpose of this secondary analysis was to (1) evaluate changes in anthropometric outcomes and (2) evaluate changes in health behavior outcomes. Associations of anthropometric changes and health behavior changes with engagement in the three-month team-based challenge were explored. Anthropometrics were measured using standard procedures, and intake of fruits and vegetables and physical activity were self-reported. Of the 145 participants in the community-engaged participatory research portion of the study, 52.4% (n = 76) had complete anthropometrics before and after the team-based challenge and were included in this study. At 3 months, there was a significant reduction in body mass index (−0.3 kg/m2, p = 0.024) and no significant change in waist circumference (p = 0.781). Fruit and vegetable intake significantly increased (+0.44 servings/day, p = 0.018). Physical activity did not significantly change based on (1) the number of days 30 or more minutes of physical activity was conducted (p = 0.765) and (2) Godin Leisure-Time Exercise Questionnaire scores (p = 0.612). Changes in anthropometrics and health behaviors were not associated with engagement in the team-based challenge. Using community-engaged participatory research with community outreach programs, such as Cooperative Extension, can improve health-related outcomes in underserved populations. However, despite a participatory approach, changes in anthropometrics and health behaviors were not associated with engagement in the developed team-based challenge.

scholarly journals Can Health-Promoting Schools Contribute to Better Health Behaviors? Physical Activity, Sedentary Behavior, and Dietary Habits among Israeli Adolescents

2021 ◽  
Vol 18 (3) ◽  
pp. 1183
Author(s):  
Hila Beck ◽  
Riki Tesler ◽  
Sharon Barak ◽  
Daniel Sender Moran ◽  
Adilson Marques ◽  
...  
Keyword(s):  
Physical Activity ◽  
Health Behavior ◽  
Confidence Interval ◽  
Health Behaviors ◽  
Sedentary Behavior ◽  
Dietary Habits ◽  
Group Differences ◽  
Time Behavior ◽  
Health Promoting ◽  
The Mean

Schools with health-promoting school (HPS) frameworks are actively committed to enhancing healthy lifestyles. This study explored the contribution of school participation in HPS on students’ health behaviors, namely, physical activity (PA), sedentary behavior, and dieting. Data from the 2018/2019 Health Behavior in School-aged Children study on Israeli adolescents aged 11–17 years were used. Schools were selected from a sample of HPSs and non-HPSs. Between-group differences and predictions of health behavior were analyzed. No between-group differences were observed in mean number of days/week with at least 60 min of PA (HPS: 3.84 ± 2.19 days/week, 95% confidence interval of the mean = 3.02–3.34; non-HPS: 3.93 ± 2.17 days/week, 95% confidence interval of the mean = 3.13–3.38). Most children engaged in screen time behavior for >2 h/day (HPS: 60.83%; non-HPS: 63.91%). The odds of being on a diet were higher among more active children (odds ratio [OR] = 1.20), higher socio-economic status (OR = 1.23), and female (OR = 2.29). HPS did not predict any health behavior. These findings suggest that HPSs did not contribute to health behaviors more than non-HPSs. Therefore, health-promoting activities in HPSs need to be improved in order to justify their recognition as members of the HPS network and to fulfill their mission.

Abstract 04: Racial Disparities in Cardiovascular Health Behaviors are Partially Explained by Socioeconomic, Psychosocial and Environmental Factors: the Coronary Artery Risk Development in Young Adults (CARDIA) Study

Circulation ◽  
2017 ◽  
Vol 135 (suppl_1) ◽  
Author(s):  
Kara M Whitaker ◽  
David R Jacobs ◽  
Kiarri N Kershaw ◽  
John N Booth ◽  
David C Goff ◽  
...  
Keyword(s):  
Physical Activity ◽  
Environmental Factors ◽  
Health Behavior ◽  
Health Behaviors ◽  
Socioeconomic Factors ◽  
Racial Differences ◽  
Fast Food ◽  
Cardiovascular Health ◽  
Race Difference ◽  
Explanatory Role

Introduction: There are known racial differences in cardiovascular health behaviors, including smoking, physical activity, and diet quality. A better understanding of factors that explain these differences may suggest novel intervention targets for reducing disparities in cardiovascular disease. Objective: To examine whether socioeconomic, psychosocial and environmental factors mediate racial differences in health behaviors. Methods: We studied 3,028 Black or White CARDIA participants who were enrolled at age 18-30 years in 1985-86 and completed the 30 year follow-up visit in 2015-2016. Health behaviors included smoking (current, former ≤ 12 months, never smoker/quit >12 months), physical activity (inactive, active but not meeting guidelines, meeting guidelines), and a surrogate for healthy eating using fast food and sugar-sweetened beverage consumption (frequency per week ≥ 2, some but < 2, none). Each behavior was assigned a value of 0 for poor, 1 for intermediate or 2 for ideal and summed to calculate an overall health behavior score for each participant (range 0-6). The race difference (β) in health behavior score was estimated using linear regression. Formal mediation analyses computed the proportion of the total effect of race on health behavior score explained by socioeconomic, psychosocial, and environmental factors (see Table footnote). Results: Blacks had a lower health behavior score than Whites in crude analyses (mean difference: -1.04, p<0.001). After adjustment for sex, age and field center, socioeconomic factors mediated 50.5% of the association between race and the health behavior score, psychosocial factors 26.8% and environmental factors 9.0% (p<0.05 for all). Joint associations mediated 58.1% of the race-health behavior score association. Conclusions: Observed racial differences in the health behavior score are predominately mediated by socioeconomic factors, which appear to play a stronger explanatory role than psychosocial and environmental factors.

scholarly journals Fear of Cancer Recurrence: A Model Examination of Physical Symptoms, Emotional Distress, and Health Behavior Change

2019 ◽  
Vol 15 (9) ◽  
pp. e787-e797 ◽  
Author(s):  
Daniel L. Hall ◽  
Rachel B. Jimenez ◽  
Giselle K. Perez ◽  
Julia Rabin ◽  
Katharine Quain ◽  
...  
Keyword(s):  
Physical Activity ◽  
Health Behavior ◽  
Behavior Change ◽  
Health Behaviors ◽  
Emotional Distress ◽  
Cancer Recurrence ◽  
Health Behavior Change ◽  
Physical Symptoms ◽  
Fear Of Cancer Recurrence ◽  
Fear Of Cancer

PURPOSE: Fear of cancer recurrence is highly prevalent among adult survivors of cancer. The role of fear of recurrence in the emotional distress of survivors of cancer, as well as health behaviors that may directly affect their health, remains unclear. To advance oncology practice, this study sought to examine the extent to which fear of recurrence stemming from physical symptoms accounts for emotional distress in a large sample of adult survivors of cancer and to extend the model to explain postdiagnosis self-reported health behavior change. METHODS: In 2016, 258 survivors of cancer at an academic hospital completed a survey of psychosocial needs. Items assessed physical symptoms (checklist), fear of cancer recurrence (Assessment of Survivor Concerns), emotional distress (anxiety and depressed mood), and health behaviors (current alcohol use, physical activity, diet, and sunscreen use, as well as changes after cancer diagnosis) informed by National Comprehensive Cancer Network survivorship guidelines. Indirect effects regression models accounting for relevant covariates (age and treatment history) used 5,000-iteration bootstrapping. RESULTS: Higher fear of cancer recurrence was associated with greater number of physical symptoms ( P < .001), greater emotional distress ( P < .05), lower moderate or vigorous physical activity ( P < .05), higher sunscreen use ( P < .05), and postdiagnosis increases in alcohol use ( P < .01) and reductions in physical activity ( P < .01). Fear of cancer recurrence models accounted for almost half of the variance in distress of survivors of cancer ( R2 = 0.44, P < .001) and, to a lesser yet significant extent, changes in alcohol consumption ( R2 = 0.09, P < .001) and physical activity ( R2 = 0.06, P = .003). CONCLUSION: Fear of cancer recurrence plays a central role in the emotional distress and key health behaviors of survivors of cancer. These findings support fear of cancer recurrence as a potential target for emotional health and health behavior change interventions.

scholarly journals Impact of goal priority and goal conflict on the intention–health-behavior relationship: Tests on physical activity and other health behaviors.

2016 ◽  
Vol 35 (9) ◽  
pp. 1017-1026 ◽  
Author(s):  
Mark Conner ◽  
Charles Abraham ◽  
Andrew Prestwich ◽  
Russell Hutter ◽  
Jennifer Hallam ◽  
...  
Keyword(s):  
Physical Activity ◽  
Health Behavior ◽  
Health Behaviors ◽  
Goal Conflict

scholarly journals Archetypes of Gamification: Analysis of mHealth Apps

10.2196/19280 ◽  
2020 ◽  
Vol 8 (10) ◽  
pp. e19280
Author(s):  
Manuel Schmidt-Kraepelin ◽  
Philipp A Toussaint ◽  
Scott Thiebes ◽  
Juho Hamari ◽  
Ali Sunyaev
Keyword(s):  
Best Practices ◽  
Health Behavior ◽  
Health Behaviors ◽  
Mobile Health ◽  
Positive Reinforcement ◽  
Mobile Apps ◽  
Health Behavior Change ◽  
Future Research ◽  
Research Approach ◽  
Health Related

Background Nowadays, numerous health-related mobile apps implement gamification in an attempt to draw on the motivational potential of video games and thereby increase user engagement or foster certain health behaviors. However, research on effective gamification is still in its infancy and researchers increasingly recognize methodological shortcomings of existing studies. What we actually know about the phenomenon today stems from fragmented pieces of knowledge, and a variety of different perspectives. Existing research primarily draws on conceptual knowledge that is gained from research prototypes, and isolated from industry best practices. We still lack knowledge on how gamification has been successfully designed and implemented within the industry and whether certain gamification approaches have shown to be particularly suitable for certain health behaviors. Objective We address this lack of knowledge concerning best practices in the design and implementation of gamification for health-related mobile apps by identifying archetypes of gamification approaches that have emerged in pertinent health-related mobile apps and analyzing to what extent those gamification approaches are influenced by the underlying desired health-related outcomes. Methods A 3-step research approach is employed. As a first step, a database of 143 pertinent gamified health-related mobile apps from the Apple App Store and Google Play Store is set up. Second, the gamification approach of each app within the database is classified based on an established taxonomy for gamification in health-related apps. Finally, a 2-step cluster analysis is conducted in order to identify archetypes of the most dominant gamification approaches in pertinent gamified health-related mobile apps. Results Eight archetypes of gamification emerged from the analysis of health-related mobile apps: (1) competition and collaboration, (2) pursuing self-set goals without rewards, (3) episodical compliance tracking, (4) inherent gamification for external goals, (5) internal rewards for self-set goals, (6) continuous assistance through positive reinforcement, (7) positive and negative reinforcement without rewards, and (8) progressive gamification for health professionals. The results indicate a close relationship between the identified archetypes and the actual health behavior that is being targeted. Conclusions By unveiling salient best practices and discussing their relationship to targeted health behaviors, this study contributes to a more profound understanding of gamification in mobile health. The results can serve as a foundation for future research that advances the knowledge on how gamification may positively influence health behavior change and guide practitioners in the design and development of highly motivating and effective health-related mobile health apps.

Conscientiousness and Cardiometabolic Risk: A Test of the Health Behavior Model of Personality Using Structural Equation Modeling

2021 ◽  
Author(s):  
Mark C Thomas ◽  
Katherine A Duggan ◽  
Thomas W Kamarck ◽  
Aidan G C Wright ◽  
Matthew F Muldoon ◽  
...  
Keyword(s):  
Physical Activity ◽  
Substance Use ◽  
Health Behavior ◽  
Health Behaviors ◽  
Latent Variable ◽  
Structural Equation ◽  
Cardiometabolic Risk ◽  
Equation Modeling ◽  
Inverse Association ◽  
Subjective Sleep Quality

Abstract Background High trait conscientiousness is associated with lower cardiometabolic risk, and health behaviors are a putative but relatively untested pathway that may explain this association. Purpose To explore the role of key health behaviors (diet, physical activity, substance use, and sleep) as links between conscientiousness and cardiometabolic risk. Methods In a cross-sectional analysis of 494 healthy, middle-aged working adults (mean age = 42.7 years, 52.6% women, 81.0% White), participants provided self-reports of conscientiousness, physical activity, substance use, diet, and sleep, and wore monitors over a 7-day monitoring period to assess sleep (Actiwatch-16) and physical activity (SenseWear Pro3). Cardiometabolic risk was expressed as a second-order latent variable from a confirmatory factor analysis involving insulin resistance, dyslipidemia, obesity, and blood pressure. Direct, indirect, and specific indirect effect pathways linking conscientiousness to health behaviors and cardiometabolic risk were examined. Unstandardized indirect effects for each health behavior class were computed separately using bootstrapped samples. Results After controlling for demographics (sex, age, race, and education), conscientiousness showed the predicted, inverse association with cardiometabolic risk. Among the examined health behaviors, objectively-assessed sleep midpoint variability (b = −0.003, p = .04), subjective sleep quality (b = −0.003, p = .025), and objectively-assessed physical activity (b = −0.11, p = .04) linked conscientiousness to cardiometabolic risk. Conclusions Physical activity and sleep partially accounted for the relationship between conscientiousness and cardiometabolic risk.

Physical Activity Levels and Self-Reported Risk-Taking Behavior among Rural Australian and American 7th–9th Grade Adolescents

1998 ◽  
Vol 17 (4) ◽  
pp. 345-360 ◽  
Author(s):  
Michael P. Savage ◽  
Derek R. Holcomb
Keyword(s):  
Physical Activity ◽  
Body Weight ◽  
Health Behaviors ◽  
Risk Taking ◽  
The United States ◽  
Activity Level ◽  
Future Research ◽  
Drinking Alcohol ◽  
Health Related ◽  
Risk Taking Behaviors

This study compares self-reported physical activities and selected health behaviors (i.e., participation in physical activity, alcohol and cigarette use, perceived level of energy, and satisfaction with body weight) of a sample of seventh and ninth grade adolescents from Australia and the United States. A modified version of the Personal Wellness Profile 400™ (PWP 400) was used to measure adolescents' participation in physical activity and health behaviors. Five of the seven items studied showed significant differences ( p < .05). Ninety-seven percent of Australian adolescents reported they engaged in physical activity long enough to work up a sweat four or more times per week, compared to 94 percent of U.S. adolescents. The Australian cohort, however, reported a significantly higher level of ever smoking (34.1% vs. 12.3%), and drinking alcohol during the past year than did U.S. adolescents (55.0% vs. 16.0%). Male adolescents demonstrated significant differences on five of the seven items measured. Australian males reported greater participation in physical activity, smoking and drinking, and reported they had higher levels of energy than did U.S. males. The female adolescents also demonstrated significant differences on five of the seven items measured, e.g., over 76 percent of Australian females reported engaging in strength exercises at least once a week compared to 59 percent of U.S. females, and only 23 percent of Australian females reported they were sedentary compared to 41 percent of U.S. females. Finally, the relationship between physical activity and involvement with risk-taking behaviors and health-related attitudes for both samples was examined. Increased activity was associated with less smoking, more satisfaction with body weight, and perceived higher energy level for U.S. adolescents. Drinking alcohol was not associated with activity level for U.S. adolescents. For Australian adolescents there was no association between physical activity and risk-taking behaviors and health-related attitudes. Future research should continue to examine cultural differences.

Sign in / Sign up

Export Citation Format

Share Document