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.

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.

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 Action planning and coping planning for long-term lifestyle change: theory and assessment

2005 ◽  
Vol 35 (4) ◽  
pp. 565-576 ◽  
Author(s):  
Falko F. Sniehotta ◽  
Ralf Schwarzer ◽  
Urte Scholz ◽  
Benjamin Schüz
Keyword(s):  
Change Theory ◽  
Action Planning ◽  
Lifestyle Change ◽  
Coping Planning ◽  
And Coping

scholarly journals Which behaviour change techniques are effective to promote physical activity and reduce sedentary behaviour in adults: a factorial randomized trial of an e- and m-health intervention

2020 ◽  
Author(s):  
Helene Schroé ◽  
Delfien Van Dyck ◽  
Annick De Paepe ◽  
Louise Poppe ◽  
Wen Wei Loh ◽  
...  
Keyword(s):  
Physical Activity ◽  
Sedentary Behaviour ◽  
Behaviour Change ◽  
Action Planning ◽  
Health Intervention ◽  
Health Interventions ◽  
Behaviour Change Techniques ◽  
Self Monitoring ◽  
Coping Planning ◽  
The Impact

Abstract BackgroundE- and m-health interventions are promising to change health behaviour. Many of these interventions use a large variety of behaviour change techniques (BCTs), but it’s not known which BCTs or which combination of BCTs contribute to their efficacy. Therefore, this study investigated the efficacy of three BCTs (i.e. action planning, coping planning and self-monitoring) and their combinations on physical activity (PA) and sedentary behaviour (SB).MethodsIn a 2(action planning: present vs absent) x2(coping planning: present vs absent) x2(self-monitoring: present vs absent) factorial trial, 473 adults from the general population used the self-regulation based e- and m-health intervention ‘MyPlan2.0’ for five weeks. All combinations of BCTs were considered, resulting in eight groups. Participants selected their preferred target behaviour, either PA (n = 335,age = 35.8,28.1% men) or SB (n = 138,age = 37.8,37.7% men), and were then randomly allocated to the experimental groups. Levels of PA (MVPA in minutes/week) or SB (total sedentary time in hours/day) were assessed at baseline and post-intervention using self-reported questionnaires. Linear mixed-effect models were fitted to assess the impact of the different combinations of the BCTs on PA and SB.ResultsFirst, overall efficacy of each BCT was examined. The delivery of self-monitoring increased PA (t = 2.735,p = 0.007) and reduced SB (t=-2.573,p = 0.012) compared with no delivery of self-monitoring. Also, the delivery of coping planning increased PA (t = 2.302,p = 0.022) compared with no delivery of coping planning. Second, we investigated to what extent adding BCTs increased efficacy. Using the combination of the three BCTs was most effective to increase PA (x2 = 8,849,p = 0.003) whereas the combination of action planning and self-monitoring was most effective to decrease SB (x2 = 3.918,p = 0.048). To increase PA, action planning was always more effective in combination with coping planning (x2 = 5.590,p = 0.014;x2 = 17.722,p < 0.001;x2 = 4.552,p = 0.033) compared with using action planning without coping planning. Of note, the use of action planning alone reduced PA compared with using coping planning alone (x2 = 4.389,p = 0.031) and self-monitoring alone (x2 = 8.858,p = 003), respectively.ConclusionsThis study provides indications that different (combinations of) BCTs may be effective to promote PA and reduce SB. More experimental research to investigate the effectiveness of BCTs is needed, which can contribute to improved design and more effective e- and m-health interventions in the future.Trial registrationThis study was preregistered as a clinical trial (ID number: NCT03274271). Release date: 20 October 2017, http://clinicaltrials.gov/ct2/show/NCT03274271

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