scholarly journals Implementation Tells Us More Beyond Pooled Estimates: Secondary Analysis of a Multicountry mHealth Trial to Reduce Blood Pressure (Preprint)

2018 ◽  
Author(s):  
Rodrigo M Carrillo-Larco ◽  
Safia S Jiwani ◽  
Francisco Diez-Canseco ◽  
Rebecca Kanter ◽  
Andrea Beratarrechea ◽  
...  
Keyword(s):  
Physical Activity ◽  
Blood Pressure ◽  
Readiness To Change ◽  
Secondary Analysis ◽  
Text Messages ◽  
Phone Calls ◽  
Health Related Behaviors ◽  
Stage Of Readiness ◽  
Health Related ◽  
Intervention Uptake

BACKGROUND The uptake of an intervention aimed at improving health-related lifestyles may be influenced by the participant’s stage of readiness to change behaviors. OBJECTIVE We conducted secondary analysis of the Grupo de Investigación en Salud Móvil en América Latina (GISMAL) trial according to levels of uptake of intervention (dose-response) to explore outcomes by country, in order to verify the consistency of the trial’s pooled results, and by each participant’s stage of readiness to change a given lifestyle at baseline. The rationale for this secondary analysis is motivated by the original design of the GISMAL study that was independently powered for the primary outcome—blood pressure—for each country. METHODS We conducted a secondary analysis of a mobile health (mHealth) multicountry trial conducted in Argentina, Guatemala, and Peru. The intervention consisted of monthly motivational phone calls by a trained nutritionist and weekly tailored text messages (short message service), over a 12-month period, aimed to enact change on 4 health-related behaviors: salt added to foods when cooking, consumption of high-fat and high-sugar foods, consumption of fruits or vegetables, and practice of physical activity. Results were stratified by country and by participants’ stage of readiness to change (precontemplation or contemplation; preparation or action; or maintenance) at baseline. Exposure (intervention uptake) was the level of intervention (<50%, 50%-74%, and ≥75%) received by the participant in terms of phone calls. Linear regressions were performed to model the outcomes of interest, presented as standardized mean values of the following: blood pressure, body weight, body mass index, waist circumference, physical activity, and the 4 health-related behaviors. RESULTS For each outcome of interest, considering the intervention uptake, the magnitude and direction of the intervention effect differed by country and by participants’ stage of readiness to change at baseline. Among those in the high intervention uptake category, reductions in systolic blood pressure were only achieved in Peru, whereas fruit and vegetable consumption also showed reductions among those who were at the maintenance stage at baseline in Argentina and Guatemala. CONCLUSIONS Designing interventions oriented toward improving health-related lifestyle behaviors may benefit from recognizing baseline readiness to change and issues in implementation uptake. CLINICALTRIAL ClinicalTrials.gov NCT01295216; http://clinicaltrials.gov/ct2/show/NCT01295216 (Archived by WebCite at http://www.webcitation.org/72tMF0B7B).

Abstract P234: Associations of Clinical Characteristics and Health-related Behaviors With Physical Activity Levels in Stage B Heart Failure Patients

Circulation ◽  
2020 ◽  
Vol 141 (Suppl_1) ◽  
Author(s):  
Maira Tristao Parra ◽  
Meredith A Pung ◽  
Kathleen Wilson ◽  
Christopher Pruitt ◽  
Barry H Greenberg ◽  
...  
Keyword(s):  
Physical Activity ◽  
Heart Failure ◽  
Clinical Characteristics ◽  
Well Being ◽  
Physically Active ◽  
Heart Failure Patients ◽  
Health Related Behaviors ◽  
Health Related ◽  
Active Patients

Hypothesis: insufficiently active heart failure patients will report poorer QoL, more fatigue and depressive mood compared to active patients. Aims: To characterize clinical characteristics and health-related behaviors according to physical activity (PA). Also, to explore predicting factors of quality of life (QoL). Methods: Cross-sectional analysis of a cohort of Stage B HF patients. PA classification was set as active, moderately active or insufficiently active, according to the LTEQ questionnaire. For QoL, the SF-36 questionnaire was used. ANOVAS, Chi-Square tests or likelihood ratios and unadjusted multiple regression models were calculated. Significance was set at p ≤ 0.05. Results: In this cohort, 277 HF patients completed the PA questionnaire. The prevalence of active patients was higher than moderately active and insufficiently active (53.3% vs 15.2% and 29.6%), respectively. Younger age (p = 0.044), lower waist circumference (WC) (p = 0.002), and lower waist-to-hip ratio (p = 0.046) were associated with being active. The prevalence of Type II diabetes mellitus (T2DM) in the active groups was significantly lower (p = 0.001). Physically active groups had cases of mild LV enlargement (1.4% and 7.5%, respectively), while no cases were observed among insufficiently active patients (p = 0.017). PA was positively associated with less fatigue (p= 0.002), more vigor (p = 0.001), more self-efficacy (p < 0.001), and better quality of life (p = 0.002). Patients who were less physically active had more inflammation (CRP, p = 0.015; IL-6, p <0.001; TNF-α: p = 0.033, and IL-1ra, p = 0.001). WC (β =-0.16, p = 0.008), glucose (β =-0.12, p < 0.001) and fatigue (β = - 0.39, p < 0.001) predicted general health perception (R 2 = 0.449). For physical functioning (high scores reflects performing PA without limitations due to health), WC (β = - 0.28, p = 0.001), sleep (β = - 1.50, p = 0.003) and fatigue (β = - 0.32, p = 0.018) were significant predictors (R 2 = 0.422); while age (β = 0.36, p <0.001) physical activity (β = 0.051, p = 0.055), sleep (β = 0.50, p =0.046), fatigue (β = -0.37, p <0.001) and depression (β = -1.12, p <0.001) predicted emotional well-being (R 2 = 0.696). Conclusion: Physically active heart failure patients had a better anthropometric profile and lower prevalence of T2DM. In this cohort, PA was not a significant predictor for general and physical functioning, but it remained relevant for predicting emotional well-being.

scholarly journals Preliminary Evidence-Based Recommendations for Return to Learn: a novel pilot study tracking concussion recovery in college students

Neurology ◽  
2019 ◽  
Vol 93 (14 Supplement 1) ◽  
pp. S33.3-S34
Author(s):  
Zachary Bevilacqua ◽  
Mary Kerby ◽  
David Fletcher ◽  
Zhongxue Chen ◽  
Becca Merritt ◽  
...  
Keyword(s):  
Physical Activity ◽  
Longitudinal Design ◽  
Text Messages ◽  
Return To Play ◽  
Evidence Based ◽  
Full Time ◽  
Symptom Resolution ◽  
Phone Calls ◽  
Return To Learn ◽  
Concussion Recovery

ObjectiveInvestigate the potential factors influencing resolution of chief concussion symptoms in a longitudinal design. Second, assess subjects’ perception of their concussion recovery and what types of activities and accommodations appeared beneficial.BackgroundAthletes re-entering the academic setting after a concussion is commonly referred as return-to-learn (RTL), which has appeared secondary to the abundantly researched return-to-play protocols implemented ubiquitously. Importantly, every concussed collegiate, adolescent, and pediatric athlete is first and foremost a student-athlete, with “student” holding the emphasis. To date, very few studies have examined the RTL aspect of concussion recovery, and the effects premature classroom attendance may cause.Design/MethodsNine concussed, college aged (18-26 years), full-time students were monitored longitudinally throughout their recovery from diagnosis to full symptom-free academic participation. Symptom severity for five prevalent symptoms were recorded 4 times per day, along with a daily phone call to report participant’s diet, duration of screen-time usage and music listened to, physical activity participation, and types of classes attended.ResultsResponse rates to text messages and phone calls yielded a mean 92% and 93% respectively across the nine subjects. Additionally, five variables were significantly associated with symptom resolution (music, sleep, physical activity, water, and time) (p = 0.0004 to p = 0.036). Lastly, subjects reported math and computer-oriented courses as the most difficult (33% and 44% respectively). Additional time on assignments/exams and reducing screen brightness were the most beneficial accommodations (66% and 56% respectively).ConclusionsOur findings introduce a novel and robust approach to monitoring concussed students throughout their recovery. Furthermore, this methodology is the first to produce holistic evidence-based results concerning re-integrating students to the classroom. Lastly, it appears that dietary and social behaviors can indeed influence symptom resolution.

scholarly journals Associations between markers of health and playing golf in an Australian population

2019 ◽  
Vol 5 (1) ◽  
pp. e000517 ◽  
Author(s):  
Brad Stenner ◽  
Amber D Mosewich ◽  
Jonathan D Buckley ◽  
Elizabeth S Buckley
Keyword(s):  
Quality Of Life ◽  
Physical Activity ◽  
Secondary Analysis ◽  
Health Related Quality ◽  
Australian Population ◽  
Physically Active ◽  
Related Quality ◽  
Health Related ◽  
Activity Survey

ObjectiveTo investigate associations between markers of health and playing golf in an Australian population.MethodsSecondary analysis of data from the Australian National Nutrition and Physical Activity Survey to compare selected health outcomes between golfers (n=128) and non-golfers (n=4999).ResultsGolfers were older than non-golfers (mean±SD 57.7±14.2 years, 48.5±17.6 years, p<0.05). A higher proportion of golfers were overweight or obese compared with non-golfers (76% vs 64%, p<0.05), and golfers were more likely to have been diagnosed with ischaemic heart disease (IHD) at some time in their life (OR 2.8, 95% CI 1.0 to 7.8). However, neither the risk of being overweight or obese (OR 1.4, 95% CI 0.9 to 2.2) or having been diagnosed with IHD (OR 2.1, 95% CI 0.8 to 5.8), were significant after controlling for age. Golfers were more physically active than non-golfers (8870±3810 steps/day vs 7320±3640 steps/day, p<0.05) and more likely to report high health-related quality of life (HRQoL) than non-golfers (OR 1.8; 95% CI 1.0 to 3.3), but not after adjusting for physical activity (OR 1.4, 95% CI 0.9 to 2.2).ConclusionCompared with non-golfers, golfers were more likely to be overweight or obese and to have been diagnosed with IHD, but not after adjusting for golfers being older. Golfers were more likely to report a higher HRQoL, but not after adjusting for golfers being more physically active. There may be an association between golfers being more physically active than non-golfers and reporting a higher HRQoL.

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