Which patients benefit from physical activity on prescription (PAP)? A prospective observational analysis of factors that predict increased physical activity
Abstract Background There is robust evidence that regular physical activity (PA) has positive health effects. However, the best PA methods and the most important correlates for promoting PA remain unclear. Physical activity on prescription (PAP) aims to increase the patient’s motivation for and leve...
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doaj-25eafee5602b46a39077342af8ac3c722020-11-25T02:12:52ZengBMCBMC Public Health1471-24582019-05-0119111310.1186/s12889-019-6830-1Which patients benefit from physical activity on prescription (PAP)? A prospective observational analysis of factors that predict increased physical activityStefan Lundqvist0Mats Börjesson1Maria E. H. Larsson2Åsa Cider3Lars Hagberg4Department of Health and Rehabilitation, Unit of Physiotherapy, Institute of Neuroscience and Physiology, Sahlgrenska Academy, University of GothenburgDepartment of Food and Nutrition and Sport Science, Faculty of Education, University of GothenburgDepartment of Health and Rehabilitation, Unit of Physiotherapy, Institute of Neuroscience and Physiology, Sahlgrenska Academy, University of GothenburgDepartment of Health and Rehabilitation, Unit of Physiotherapy, Institute of Neuroscience and Physiology, Sahlgrenska Academy, University of GothenburgUniversity Health Care Research Center, Faculty of Medicine and Health, Örebro UniversityAbstract Background There is robust evidence that regular physical activity (PA) has positive health effects. However, the best PA methods and the most important correlates for promoting PA remain unclear. Physical activity on prescription (PAP) aims to increase the patient’s motivation for and level of PA. This study investigated possible predictive baseline correlates associated with changes in the PA level over a 6-month period of PAP treatment in order to identify the primary care patients most likely to benefit from a PAP intervention. Methods The study included 444 patients with metabolic risk factors who were aged 27 to 85 years and physically inactive. The patients received PAP treatment that included individual counseling plus an individually-tailored PA recommendation with a written prescription and individualised structured follow-up for 6 months. Eight baseline correlates of PA were analysed against the PA level at the 6-month follow-up in a predictor analysis. Results Five baseline correlates predicted the PA level at the 6-month follow-up: self-efficacy expectations for changing PA; the patient’s preparedness and confidence regarding readiness to change PA; a BMI < 30; and a positive valued physical health. The proportion of patients increasing the PA level and achieving a PA level that was in accordance with public health recommendations was higher with a positive valued baseline correlate. The odds of achieving the recommended PA level increased substantially when 2 to 4 predictive correlates were present. PA levels increased to a greater extent among patients with low PA at baseline than patients with high PA at baseline, especially in combination with 2 to 4 positively-valued correlates (87–95% vs. 62–75%). Conclusions This study identified potential predictive correlates of an increased PA level after a 6-month PAP intervention. This contributes to our understanding of PAP and could help individualise PAP support. The proportion of patients with the lowest PA level at baseline increased their PA level in a higher extent (84%) and thus may benefit the most from PAP. These results have clinical implications for behavioural change in those patients having the greatest health gains by increasing their PA level. Trial registration ClinicalTrials.gov; NCT03586011. Retrospectively registered on July 17, 2018.http://link.springer.com/article/10.1186/s12889-019-6830-1Physical activityMetabolic syndromePhysical activity on prescriptionHealth behaviourCorrelates of physical activityPredictive factor |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Stefan Lundqvist Mats Börjesson Maria E. H. Larsson Åsa Cider Lars Hagberg |
spellingShingle |
Stefan Lundqvist Mats Börjesson Maria E. H. Larsson Åsa Cider Lars Hagberg Which patients benefit from physical activity on prescription (PAP)? A prospective observational analysis of factors that predict increased physical activity BMC Public Health Physical activity Metabolic syndrome Physical activity on prescription Health behaviour Correlates of physical activity Predictive factor |
author_facet |
Stefan Lundqvist Mats Börjesson Maria E. H. Larsson Åsa Cider Lars Hagberg |
author_sort |
Stefan Lundqvist |
title |
Which patients benefit from physical activity on prescription (PAP)? A prospective observational analysis of factors that predict increased physical activity |
title_short |
Which patients benefit from physical activity on prescription (PAP)? A prospective observational analysis of factors that predict increased physical activity |
title_full |
Which patients benefit from physical activity on prescription (PAP)? A prospective observational analysis of factors that predict increased physical activity |
title_fullStr |
Which patients benefit from physical activity on prescription (PAP)? A prospective observational analysis of factors that predict increased physical activity |
title_full_unstemmed |
Which patients benefit from physical activity on prescription (PAP)? A prospective observational analysis of factors that predict increased physical activity |
title_sort |
which patients benefit from physical activity on prescription (pap)? a prospective observational analysis of factors that predict increased physical activity |
publisher |
BMC |
series |
BMC Public Health |
issn |
1471-2458 |
publishDate |
2019-05-01 |
description |
Abstract Background There is robust evidence that regular physical activity (PA) has positive health effects. However, the best PA methods and the most important correlates for promoting PA remain unclear. Physical activity on prescription (PAP) aims to increase the patient’s motivation for and level of PA. This study investigated possible predictive baseline correlates associated with changes in the PA level over a 6-month period of PAP treatment in order to identify the primary care patients most likely to benefit from a PAP intervention. Methods The study included 444 patients with metabolic risk factors who were aged 27 to 85 years and physically inactive. The patients received PAP treatment that included individual counseling plus an individually-tailored PA recommendation with a written prescription and individualised structured follow-up for 6 months. Eight baseline correlates of PA were analysed against the PA level at the 6-month follow-up in a predictor analysis. Results Five baseline correlates predicted the PA level at the 6-month follow-up: self-efficacy expectations for changing PA; the patient’s preparedness and confidence regarding readiness to change PA; a BMI < 30; and a positive valued physical health. The proportion of patients increasing the PA level and achieving a PA level that was in accordance with public health recommendations was higher with a positive valued baseline correlate. The odds of achieving the recommended PA level increased substantially when 2 to 4 predictive correlates were present. PA levels increased to a greater extent among patients with low PA at baseline than patients with high PA at baseline, especially in combination with 2 to 4 positively-valued correlates (87–95% vs. 62–75%). Conclusions This study identified potential predictive correlates of an increased PA level after a 6-month PAP intervention. This contributes to our understanding of PAP and could help individualise PAP support. The proportion of patients with the lowest PA level at baseline increased their PA level in a higher extent (84%) and thus may benefit the most from PAP. These results have clinical implications for behavioural change in those patients having the greatest health gains by increasing their PA level. Trial registration ClinicalTrials.gov; NCT03586011. Retrospectively registered on July 17, 2018. |
topic |
Physical activity Metabolic syndrome Physical activity on prescription Health behaviour Correlates of physical activity Predictive factor |
url |
http://link.springer.com/article/10.1186/s12889-019-6830-1 |
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