Identifying Barriers and Motivators to Exercise for Middle-Aged Adults at UBC
Bibliographic record
Abstract
Chronic diseases are one of the leading causes of death worldwide (Deering et al., 2009), and many are preventable by addressing and mitigating risk factors, such as tobacco use, raised blood pressure, unhealthy diet, and physical activity (Government of Canada, 2015). However, less than 20% of adults in Canada meet the recommended amount of physical activity (Statistics Canada, 2019), suggesting a need for increased exercise programming in order to improve the health of adults. UBC has several initiatives and programs to address this prevalent issue, such as Bodyworks, an evidence-based organization that strives to enhance wellbeing and fitness (Faculty of Education School of Kinesiology, n.d.). However, this organization has largely focused on programming for older adults, with limited engagement from community members aged 40 to 60 (Bundon, 2021). Therefore, this study aimed to engage with UBC community members 40 to 60 years of age with at least one risk factor for chronic disease, to learn about their experiences, behaviours, and perceptions of physical activity, in order to develop recommendations for future programming to be offered by BodyWorks. This study employed a mixed-methods approach by conducting a survey comprised of Likert-type, multiple-choice, and open-ended questions pertaining to demographics, motivators and barriers to exercise participation, awareness and perception of BodyWorks, and preferred exercise type and delivery. Over the course of three weeks, researchers collected data from 44 participants between the ages of 41 and 60. The results indicate that the population’s most prevalent barriers to participation are: a lack of time and a range of health concerns, such as fear of injury and limited physical abilities. However, participants also reported positive associations with exercise, enjoying exercise as a means to manage stress, increase energy levels, and socialize. The results also suggest that BodyWorks has a mixed reputation among the sample. Some participants feel their programs and equipment are outdated and only worthwhile for seniors, while other participants had never heard of the organization, or attended any of their classes. Furthermore, participants were asked to provide examples of fitness programs they would enjoy or participate in. The most common suggestions included condition-specific programs (where participants have similar needs and goals), classes set to music (such as dance fitness, Zumba, or yoga programs), and tiered, beginner programs (where participants can gain confidence using gym equipment and are provided the opportunity to progress to more advanced classes). Based on these findings, 5 recommendations are suggested to BodyWorks in order to best engage with this population. 1) Partner with other UBC organizations. 2) Develop a website separate from the UBC School of Kinesiology. 3) Use social media to advertise programs and educate the public. 4) Update facility and equipment for enhanced functionality and enjoyment. 5) Develop new programming in line with participant suggestions. Disclaimer: “UBC SEEDS provides students with the opportunity to share the findings of their studies, as well as their opinions, conclusions and recommendations with the UBC community. The reader should bear in mind that this is a student project/report and is not an official document of UBC. Furthermore readers should bear in mind that these reports may not reflect the current status of activities at UBC. We urge you to contact the research persons mentioned in a report or the SEEDS Coordinator about the current status of the subject matter of a project/report.”
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".