scholarly journals Increasing physical activity in older adults: Walking by prescription in primary care

2017 ◽  
Vol 6 (1) ◽  
pp. 128-140
Author(s):  
Vera Paisana Morais ◽  
Jorge Encantado ◽  
Maria Isabel Santos ◽  
Pedro Almeida ◽  
Isabel Pereira Leal ◽  
...  
Keyword(s):  
Physical Activity ◽  
Older Adults ◽  
Longitudinal Design ◽  
Action Planning ◽  
Activity Levels ◽  
Coping Planning ◽  
Recent Developments ◽  
The Moment ◽  
And Coping ◽  
Goal Intention

Aim The present study (PTDC/SAU-SAP/110799/2009) funded by the Portuguese Government (Fundação para a Ciência e Tecnologia – FCT) aimed to test the effectiveness of a behaviour based intervention combined with a cognitive based one, designed to increase physical activity levels in older adults at Primary Health Care Centres. Method A total of 108 participants aged over 65 years participated in the study. Participants were referred by their General Practitioner (GP) and randomized by gender and marital status at the moment they started the program (single vs. couple), and allocated into one of three conditions: goal intention, action planning, action planning and coping planning. All participants received a pedometer and a logbook and were asked to register their daily number of steps for a period of 24 weeks. Study follows a longitudinal design with five assessments over a 6-month after baseline. Results The test between subjects’ effects revealed an interaction between condition and participating in the study as single vs. couple. Older adults participating as singles walked more steps on average in the condition goal intention plus action planning and coping planning, whereas participants that entered in the study with their spouse, goal intention without any other planning intervention was the most effective intervention. Conclusion The 24-week physical activity program based on the recent developments of behavioural-cognitive framework, has proven useful increasing older adults daily walking behaviour.

scholarly journals Effectiveness of the mHealth intervention ‘MyDayPlan’ to increase physical activity: an aggregated single case approach

2021 ◽  
Vol 18 (1) ◽  
Author(s):  
L. Degroote ◽  
A. De Paepe ◽  
I. De Bourdeaudhuij ◽  
D. Van Dyck ◽  
G. Crombez
Keyword(s):  
Physical Activity ◽  
Single Case ◽  
Adult Population ◽  
Self Regulation ◽  
Action Planning ◽  
Intervention Phase ◽  
Mhealth Intervention ◽  
Coping Planning ◽  
Carry Over ◽  
And Coping

Abstract Background e- and mHealth interventions using self-regulation techniques like action and coping planning have the potential to tackle the worldwide problem of physical inactivity. However, they often use one-week self-regulation cycles, providing support toward an active lifestyle on a weekly basis. This may be too long to anticipate on certain contextual factors that may fluctuate from day to day and may influence physical activity. Consequently, the formulated action and coping plans often lack specificity and instrumentality, which may decrease effectiveness of the intervention. The aim of this study was to evaluate effectiveness of a self-regulation, app-based intervention called ‘MyDayPlan’. “MyDayPlan’ provides an innovative daily cycle in which users are guided towards more physical activity via self-regulation techniques such as goal setting, action planning, coping planning and self-monitoring of behaviour. Methods An ABAB single-case design was conducted in 35 inactive adults between 18 and 58 years (M = 40 years). The A phases (A1 and A2) were the control phases in which the ‘MyDayPlan’ intervention was not provided. The B phases (B1 and B2) were the intervention phases in which ‘MyDayPlan’ was used on a daily basis. The length of the four phases varied within and between the participants. Each phase lasted a minimum of 5 days and the total study lasted 32 days for each participant. Participants wore a Fitbit activity tracker during waking hours to assess number of daily steps as an outcome. Single cases were aggregated and data were analysed using multilevel models to test intervention effects and possible carry-over effects. Results Results showed an average intervention effect with a significant increase in number of daily steps from the control to intervention phases for each AB combination. From A1 to B1, an increase of 1424 steps (95% CI [775.42, 2072.32], t (1082) = 4.31,p < .001), and from A2 to B2, an increase of 1181 steps (95% CI [392.98, 1968.16], t (1082) = 2.94, p = .003) were found. Furthermore, the number of daily steps decreased significantly (1134 steps) when going from the first intervention phase (B1) to the second control phase (A2) (95% CI [− 1755.60, − 512.38], t (1082) = − 3.58, p < .001). We found no evidence for a difference in trend between the two control (95% CI [− 114.59, 197.99], t (1078) = .52, p = .60) and intervention phases (95% CI [− 128.79,284.22], t (1078) = .74, p = .46). This reveals, in contrast to what was hypothesized, no evidence for a carry-over effect after removing the ‘MyDayPlan’ app after the first intervention phase (B1). Conclusion This study adds evidence that the self-regulation mHealth intervention, ‘MyDayPlan’ has the capacity to positively influence physical activity levels in an inactive adult population. Furthermore, this study provides evidence for the potential of interventions adopting a daily self-regulation cycle in general.

Effects of action planning and coping planning within the theory of planned behaviour: A physical activity study of patients undergoing haemodialysis

2011 ◽  
Vol 12 (6) ◽  
pp. 609-614 ◽  
Author(s):  
Amir H. Pakpour ◽  
Isa Mohammadi Zeidi ◽  
Nikos Chatzisarantis ◽  
Stig Molsted ◽  
Adrian P. Harrison ◽  
...  
Keyword(s):  
Physical Activity ◽  
Theory Of Planned Behaviour ◽  
Action Planning ◽  
Planned Behaviour ◽  
Coping Planning ◽  
And Coping

scholarly journals Habitual Physical Activity and Diabetes Control in Young and Older Adults with Type II Diabetes: A Longitudinal Correlational Study

2021 ◽  
Vol 18 (3) ◽  
pp. 1330
Author(s):  
Chia-Hsun Chang ◽  
Ching-Pyng Kuo ◽  
Chien-Ning Huang ◽  
Shiow-Li Hwang ◽  
Wen-Chun Liao ◽  
...  
Keyword(s):  
Physical Activity ◽  
Older Adults ◽  
Type Ii Diabetes ◽  
Daily Physical Activity ◽  
Diabetes Control ◽  
Moderate Intensity ◽  
Correlational Study ◽  
Activity Levels ◽  
Daily Physical Activities ◽  
Activity Questionnaire

This study aimed to determine whether daily physical activity in young and older adults with T2DM is associated with diabetes control. A prospective correlational study involving 206 young (≤65 years) and older (>65 years) adults was conducted. The International Physical Activity Questionnaire was used to assess their daily physical activity levels. Patients’ mean HbA1c level was 7.8% (±1.4), and 95.9% of patients had unsatisfactory diabetes control. Performing more minutes per week of moderate-intensity daily physical activity was associated with a lower risk of glycemia in both young and older adults. Furthermore, moderate daily physical activity significantly lowered the risk of glycemia. Health personnel must encourage patients to engage in moderate daily physical activities to improve diabetes control.

379 Do Depressive Symptoms Mediate the Association Between Insomnia and Physical Activity?

SLEEP ◽  
2021 ◽  
Vol 44 (Supplement_2) ◽  
pp. A150-A151
Author(s):  
Jamie Walker ◽  
Rebecca Campbell ◽  
Ivan Vargas
Keyword(s):  
Physical Activity ◽  
Depressive Symptoms ◽  
Online Survey ◽  
Longitudinal Design ◽  
Energy Levels ◽  
Depression Scale ◽  
Severity Index ◽  
Future Research ◽  
Activity Levels ◽  
Insomnia Symptoms

Abstract Introduction Insomnia and depression are highly comorbid and have been shown to be independently associated with lower levels of physical activity. It is not clear, however, if being less physically active is a risk factor for or consequence of depression and insomnia. The factors that explain the associations between insomnia, depression, and physical activity are likely complex and overlapping. For example, insomnia may predict inactivity by impacting one’s energy levels, leaving them too tired to exercise. Insomnia may also interfere with one’s motivation to exercise due to low mood, as insomnia is associated with the development of depressive symptoms. The purpose of the present study was to explore whether depression mediated the link between insomnia and low levels of physical activity. Methods A national online survey was conducted from April-June 2020. Participants completed surveys to assess demographics, mood, sleep, and physical activity. Depressive symptoms were estimated with the Center for Epidemiologic Studies Depression Scale (CES-D). Insomnia symptoms were estimated with the Insomnia Severity Index (ISI). Physical activity levels were estimated with the International Physical Activity Questionnaire (IPAQ). Analyses were conducted using multiple linear regression, with separate models for depression, insomnia, and the combination of the two, on levels of physical activity. Results 3,952 adults (Mage = 46.9 years) completed the survey. According to the unadjusted models, greater insomnia symptoms were associated with greater depressive symptoms (b = 0.4523, SE = 0.019593, p &lt; .001), and lower levels of physical activity (b = -38.741, SE = 18.236, p = 0.0337). The relationship between insomnia and physical activity was no longer significant, however, when controlling for depression (b = -6.140, SE = 19.274, p = 0.75). According to the mediation analyses, there was an indirect effect of insomnia on physical activity that was explained by differences in depressive symptoms (Sobel Test = -4.895, SE = 6.518, p &lt; .001). Conclusion Our findings support previous research indicating associations between symptoms of insomnia and depression and physical activity. Future research should examine if these same results hold using a longitudinal design. Support (if any) Vargas: K23HL141581

Physical activity levels in older adults with ID are extremely low

2012 ◽  
Vol 3 ◽  
pp. S48-S49
Author(s):  
T. Hilgenkamp ◽  
R. Van Wijck ◽  
H. Evenhuis
Keyword(s):  
Physical Activity ◽  
Older Adults ◽  
Activity Levels ◽  
Physical Activity Levels
Sign in / Sign up

Export Citation Format

Share Document