Assessing physical behavior through accelerometry – State of the science, best practices and future directions

Burchartz, Alexander; Anedda, Bastian; Auerswald, Tina; Giurgiu, Marco; Hill, Holger; Ketelhut, Sascha; Kolb, Simon; Mall, Christoph; Manz, Kristin; Nigg, Claudio R.; Reichert, Markus; Sprengeler, Ole; Wunsch, Kathrin; Matthews, Charles E.

doi:10.1016/j.psychsport.2020.101703

Cited by 60 publications

(54 citation statements)

References 116 publications

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“… Adequate and validated measurement tools should be used. Regarding PA measurement, objective measurement should be the means of choice [ 66 ] to conduct a comprehensive quantification of PA. If for feasibility reasons or large sample size requirements PA has to be measured by self-report, validated tools like the IPAQ [ 45 ] should be used instead of single items to increase study quality.…”

Section: Discussionmentioning

confidence: 99%

The Tridirectional Relationship among Physical Activity, Stress, and Academic Performance in University Students: A Systematic Review and Meta-Analysis

Wunsch

Fiedler

Bachert

et al. 2021

IJERPH

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Higher education students often suffer from physiological and psychological health problems caused by stress, which may negatively impact their academic performance (AP). Physical activity (PA) can be a promising strategy to buffer these stress-induced complaints. Therefore, the aim of this investigation was to summarize evidence for the tridimensional construct of PA, stress, and AP, as well as to quantify the relationships among these variables. Five databases (PubMed, Scopus, SMEI, ERIC, and Web of Science) were systematically searched in November 2019 for publications that examined PA, stress, and AP of university students, without any restrictions regarding the publication period. The systematic review includes four original research studies with a moderate-to-high risk of bias. Results of included studies were narratively summarized and quantified in a meta-analysis using random effect models. Whereas study results point to a positive relation between PA and AP, relationships between PA and stress seem to be negative, while the relation between stress and AP is undecided. The meta-analysis found no significant associations and considerable heterogeneity of the results. Findings indicate a research gap concerning the connection of PA, stress, and AP in university students. Future studies should use validated measuring tools and consider the timepoint of data collection in order to extract truly stressful periods.

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Section: Discussionmentioning

confidence: 99%

The Tridirectional Relationship among Physical Activity, Stress, and Academic Performance in University Students: A Systematic Review and Meta-Analysis

Wunsch

Fiedler

Bachert

et al. 2021

IJERPH

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“…comparison of different epoch lengths [ 69 ]). The most promising aspect of device-measured outcomes and accelerometry in particular is the assessment of valid PA and SB data in real-time, resulting in a variety of outcome parameters which have the potential to be easily compared throughout different studies [ 60 ]. While device-measured assessments for HE are rarely used (but becoming more and more available [ 70 ]), HE interventions should only include validated tools and be aware of the advantages of each assessment to ensure the quality of results [ 71 ].…”

Section: Discussionmentioning

confidence: 99%

“…regular/last week/month PA recall via questionnaire or measured PA during a defined time via accelerometry) [59]. Furthermore, the earliest study included in the reviews was published in 1997 and the complexity and capacity of sensors evolved rapidly since that time [60], allowing for more precise measurements and the combination of PA data with physiological parameters like heartrate or blood sugar [61]. This potential influence of different sensors on intervention effectiveness however, has not been considered in the reviews.…”

Section: Effectiveness Of E/mhealth Interventionsmentioning

confidence: 99%

Key facets to build up eHealth and mHealth interventions to enhance physical activity, sedentary behavior and nutrition in healthy subjects – an umbrella review

et al. 2020

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Background Electronic (eHealth) and mobile (mHealth) health interventions can provide a large coverage, and are promising tools to change health behavior (i.e. physical activity, sedentary behavior and healthy eating). However, the determinants of intervention effectiveness in primary prevention has not been explored yet. Therefore, the objectives of this umbrella review were to evaluate intervention effectiveness, to explore the impact of pre-defined determinants of effectiveness (i.e. theoretical foundations, behavior change techniques, social contexts or just-in-time adaptive interventions), and to provide recommendations for future research and practice in the field of primary prevention delivered via e/mHealth technology. Methods PubMed, Scopus, Web of Science and the Cochrane Library were searched for systematic reviews and meta-analyses (reviews) published between January 1990 and May 2020. Reviews reporting on e/mHealth behavior change interventions in physical activity, sedentary behavior and/or healthy eating for healthy subjects (i.e. subjects without physical or physiological morbidities which would influence the realization of behaviors targeted by the respective interventions) were included if they also investigated respective theoretical foundations, behavior change techniques, social contexts or just-in-time adaptive interventions. Included studies were ranked concerning their methodological quality and qualitatively synthesized. Results The systematic search revealed 11 systematic reviews and meta-analyses of moderate quality. The majority of original research studies within the reviews found e/mHealth interventions to be effective, but the results showed a high heterogeneity concerning assessment methods and outcomes, making them difficult to compare. Whereas theoretical foundation and behavior change techniques were suggested to be potential positive determinants of effective interventions, the impact of social context remains unclear. None of the reviews included just-in-time adaptive interventions. Conclusion Findings of this umbrella review support the use of e/mHealth to enhance physical activity and healthy eating and reduce sedentary behavior. The general lack of precise reporting and comparison of confounding variables in reviews and original research studies as well as the limited number of reviews for each health behavior constrains the generalization and interpretation of results. Further research is needed on study-level to investigate effects of versatile determinants of e/mHealth efficiency, using a theoretical foundation and additionally explore the impact of social contexts and more sophisticated approaches like just-in-time adaptive interventions. Trial registration The protocol for this umbrella review was a priori registered with PROSPERO: CRD42020147902.

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“…regular/last week/month PA recall via questionnaire or measured PA during a de ned time via accelerometry) [59]. Furthermore, the earliest study included in the reviews was published in 1997 and the complexity and capacity of sensors evolved rapidly since that time [60], allowing for more precise measurements and the combination of PA data with physiological parameters like heartrate or blood sugar [61]. This potential in uence of different sensors on intervention effectiveness however, has not been considered in the reviews.…”

Section: Effectiveness Of E/mhealth Interventionsmentioning

confidence: 99%

Key facets to build up eHealth and mHealth interventions to enhance physical activity, sedentary behavior and nutrition in healthy subjects – An umbrella review

Fiedler

Eckert

Wunsch

et al. 2020

Preprint

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Background: Electronic (eHealth) and mobile (mHealth) health interventions can provide a large coverage, and are promising tools to change health behavior (i.e. physical activity, sedentary behavior and healthy eating). However, the determinants of intervention effectiveness in primary prevention has not been explored yet. Therefore, the objectives of this umbrella review were to evaluate intervention effectiveness, to explore the impact of pre-defined determinants of effectiveness (i.e. theoretical foundations, behavior change techniques, social contexts or just-in-time adaptive interventions), and to provide recommendations for future research and practice in the field of primary prevention delivered via e/mHealth technology.Methods: PubMed, Scopus, Web of Science and the Cochrane Library were searched for systematic reviews and meta-analyses (reviews) published between January 1990 and May 2020. Reviews reporting on e/mHealth behavior change interventions in physical activity, sedentary behavior and/or healthy eating for healthy subjects (i.e. subjects without physical or physiological morbidities which would influence the realization of behaviors targeted by the respective interventions) were included if they also investigated respective theoretical foundations, behavior change techniques, social contexts or just-in-time adaptive interventions. Included studies were ranked concerning their methodological quality and qualitatively synthesized.Results: The systematic search reveled eleven systematic reviews and meta-analyses of moderate quality. The majority of original research studies within the reviews found e/mHealth interventions to be effective, but the results showed a high heterogeneity concerning assessment methods and outcomes, making them difficult to compare. Whereas theoretical foundation and behavior change techniques were suggested to be potential positive determinants of effective interventions, the impact of social context remains unclear. None of the reviews included just-in-time adaptive interventions.Conclusion: Findings of this umbrella review support the use of e/mHealth to enhance physical activity and healthy eating and reduce sedentary behavior. The general lack of precise reporting and comparison of confounding variables in reviews and original research studies as well as the limited number of reviews for each health behavior constrains the generalization and interpretation of results. Further research is needed on study-level to investigate effects of versatile determinants of e/mHealth efficiency, using a theoretical foundation and additionally explore the impact of social contexts and more sophisticated approaches like just-in-time adaptive interventions.Trial registration: The protocol for this umbrella review was a priori registered with PROSPERO: CRD42020147902.

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Assessing physical behavior through accelerometry – State of the science, best practices and future directions

Cited by 60 publications

References 116 publications

The Tridirectional Relationship among Physical Activity, Stress, and Academic Performance in University Students: A Systematic Review and Meta-Analysis

The Tridirectional Relationship among Physical Activity, Stress, and Academic Performance in University Students: A Systematic Review and Meta-Analysis

Key facets to build up eHealth and mHealth interventions to enhance physical activity, sedentary behavior and nutrition in healthy subjects – an umbrella review

Key facets to build up eHealth and mHealth interventions to enhance physical activity, sedentary behavior and nutrition in healthy subjects – An umbrella review

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