The Feasibility of a Text-Messaging Intervention Promoting Physical Activity in Shift Workers: A Process Evaluation.
Malebogo MonnaatsieStuart J H BiddleTracy L Kolbe-AlexanderPublished in: International journal of environmental research and public health (2023)
Workplace health promotion programs (WHPPs) can improve shift workers' physical activity. The purpose of this paper is to present the process evaluation of a text messaging health promotion intervention for mining shift workers during a 24-day shift cycle. Data collected from intervention participants with a logbook ( n = 25) throughout the intervention, exit interviews ( n = 7) and online surveys ( n = 17) examined the WHPP using the RE-AIM (Reach, Efficacy, Adoption, Implementation and Maintenance) framework. The program reached 66% of workers across three departments, with 15% of participants dropping out. The program showed the potential to be adopted if the recruitment strategies are improved to reach more employees, especially when involving work managers for recruitment. A few changes were made to the program, and participant adherence was high. Facilitators to adopt and implement the health promotion program included the use of text messaging to improve physical activity, feedback on behaviour, and providing incentives. Work-related fatigue was reported as a barrier to implementing the program. Participants reported that they would recommend the program to other workers and use the Mi fitness band to continue monitoring and improving their health behaviour. This study showed that shift workers were optimistic about health promotion. Allowing for long-term evaluation and involving the company management to determine scale-up should be considered for future programs.
Keyphrases
- health promotion
- quality improvement
- physical activity
- smoking cessation
- randomized controlled trial
- healthcare
- body mass index
- public health
- primary care
- electronic health record
- machine learning
- skeletal muscle
- risk assessment
- body composition
- big data
- health information
- insulin resistance
- drug induced
- data analysis