Physical Activity in Adults with Schizophrenia and Bipolar Disorder: A Large Cross-Sectional Survey Exploring Patterns, Preferences, Barriers, and Motivating Factors.
Garry Alan TewLaura BaileyRebecca J BeekenCindy CooperRobert J CopelandSamantha GascoynePaul HeronAndrew John HillEllen C LeePanagiotis SpanakisBrendon StubbsGemma D Traviss-TurnerLauren WalkerStephen WaltersSimon GilbodyEmily J PeckhamPublished in: International journal of environmental research and public health (2023)
Adults with severe mental ill health may have specific attitudes toward physical activity. To inform intervention development, we conducted a survey to assess the physical activity patterns, preferences, barriers, and motivations of adults with severe mental ill health living in the community. Data were summarised using descriptive statistics, and logistic regressions were used to explore relationships between physical activity status and participant characteristics. Five-hundred and twenty-nine participants (58% male, mean age 49.3 years) completed the survey. Large numbers were insufficiently active and excessively sedentary. Self-reported levels of physical activity below that recommended in national guidelines were associated with professional inactivity, consumption of fewer than five portions of fruit and vegetables per day, older age, and poor mental health. Participants indicated a preference for low-intensity activities and physical activity that they can do on their own, at their own time and pace, and close to home. The most commonly endorsed source of support was social support from family and friends. Common motivations included improving mental health, physical fitness, and energy levels. However, poor mental and physical health and being too tired were also common barriers. These findings can inform the development of physical activity interventions for this group of people.
Keyphrases
- physical activity
- mental health
- bipolar disorder
- healthcare
- body mass index
- social support
- public health
- sleep quality
- mental illness
- depressive symptoms
- randomized controlled trial
- early onset
- health information
- major depressive disorder
- machine learning
- middle aged
- heavy metals
- risk assessment
- deep learning
- health risk assessment