DOI of the published article 10.1093/pubmed/fdy206
Identification of dropout predictors to a community-based physical activity programme that uses motivational interviewing
DOI:
https://doi.org/10.31236/osf.io/yn6phKeywords:
exercise, primary care, public healthAbstract
Background: Participant dropout reduces intervention effectiveness. Predicting dropout has been investigated for Exercise Referral Schemes, but not physical activity (PA) interventions with Motivational Interviewing (MI). Methods: Data from attendees (n=619) to a community-based PA programme utilising MI techniques were analysed using a chi-squared test to determine dropout and attendance group differences. Binary logistic regression investigated the likelihood of dropout before 12-weeks. Results: 44.7% of participants dropped out, with statistical (P<0.05) differences between groups for age, PA, and disability. Regression for each variable showed participants aged 61-70 years (OR=0.28, CI=0.09 to 0.79; P=0.018), >70 years (OR=0.30, CI=0.09 to 0.90; P=0.036), and high PA (OR=0.40, CI=0.20 to 0.75; P=0.006) reduced dropout likelihood. Endocrine system disorders (OR=4.24, CI=1.19 to 19.43; P=0.036) and musculoskeletal disorders (OR=3.14, CI=1.84 to 5.45; P<0.001) increased dropout likelihood. Significant variables were combined in a single regression model. Dropout significantly reduced for 61-70 year olds (OR=0.31, CI=0.10 to 0.90; P=0.035), and high PA (OR=0.39, CI=0.19 to 0.76; P=0.008). Musculoskeletal disorders increased dropout (OR=2.67, CI=1.53 to 4.75; P<0.001). Conclusions: Age, PA, and disability type significantly influence dropout at 12-weeks. These are the first results specific to MI based programmes indicating the inclusion of MI and highlighting the need for further research.
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Copyright (c) 2018 Matthew Wade, Nicola Brown, Bernadette Dancy, Steven Mann, Conor Gissane, Anne Majumdar
This work is licensed under a Creative Commons Attribution 4.0 International License.