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Regular physical activity (PA) reduces the risks of multiple health problems among all age groups, also when health problems are already present. This project aims to generate new scientific and practical knowledge and insights relevant to stimulate and maintain PA in different subpopulations of adults (adults, older adults, healthy and patient populations) using innovative online interventions. We explicitly focus on vulnerable populations, such as people with low education, low digital and health skills ((e-)health literacy), as they are most deprived with regard to both their health as well as their PA.

 

Our research group successfully developed several theory based online computer tailored interventions to increase PA. These diverse online interventions proved their efficacy in improving PA among their participants:

1) Active Plus for healthy adults aged over 50;

2) Active Plus65 for adults aged over 65 who have a chronic impairment;

3) I Move for adults aged 18 to 65;

4) OncoActive for cancer patients during or after their primary treatment;

5) Cancer Aftercare Guide for former cancer patients in the first year after treatment.

 

Scientific studies into these interventions have resulted in 8 large-scale data-sets on effectiveness and implementation in practice with a combined N of over 5000 participants, each with multiple data-points. Combining these data-sets provides an excellent opportunity to gain in depth knowledge concerning the optimization of future online PA interventions, to validate these findings within our own data-sets and to apply this new knowledge in actual practice. Further, we aim to get additional insights on innovative add-on applications that can be used to increase intervention use and effects on PA.

 

These insights are provided through 4 work packages (WPs):

 

WP1 (months 1-24): Through data science methods (machine learning algorithms) 8 large-scale existing data-sets from 5 proven effective online interventions to stimulate PA will be analysed in combination (N>5000), all with longitudinal data on (objectively or subjectively measured) PA, personal characteristics, determinants of PA and feasibility data. WP1 aims to provide knowledge on which (combination of) relevant demographic factors (e.g. age, education), determinants of PA and behaviour change techniques are most relevant to increase intervention use and PA among (healthy or diseased) adults and/or elderly to enhance both effect-sizes and (long-term) effectiveness of online computer tailored PA interventions.

 

WP2 (months 1-24): Parallel to WP1 we will develop three online interactive applications and test them in one experimental Randomised Controlled Trial with four arms (3 experimental conditions, 1 control group; N=200 per condition). The 3 add-on online applications apply interactive innovative strategies, to strengthen PA intervention use and effects on PA: a) monitoring PA through activity trackers; b) an EMA/EMI (Ecological Momentary Assessment/Intervention) based smartphone application to provide direct feedback on PA issues; c) an interactive virtual coach (chatbot). We will develop these applications in close cooperation with the target population (through 3-6 focus group sessions). Prototypes of the applications will be pilot tested for effects, usability and acceptability (n=30, high/low SES, men/women).

 

WP3 (months 24-30): Findings from WP1 and WP2 are incorporated in (as yet) two of the five proven large-scale effective online interventions. The choice for the two out of five interventions will be made by the consortium partners based on expected societal and scientific impact, and based on the results of WP1 and WP2. WP1 provides knowledge on preserving and strengthening the current most effective online intervention elements, WP2 provides additional elements that can be integrated in the ongoing interventions, for example interactive online coaching or adding monitoring PA through wearable activity trackers. WP3 is the integration of the new knowledge of WP1 and WP2, founding the basis concerning content and technolo

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