Using a qualitative approach, the dimensions of subjective well-being of active older adults were outlined and ways identified through which they might be influenced by participation in physical activities. One-to-one and group interviews were used to collect the data. Using cross-case analysis, 17 main themes were identified. The following main dimensions emerged: developmental, material, physical, mental, and social well-being. The findings indicated that physical activity influences all dimensions of the subjective well-being of older adults, with the exception of material well-being. Physical activity appears to contribute to the mental health of older adults through maintenance of a busy and active life, mental alertness, positive attitude toward life and avoidance of stress, negative function, and isolation. The complexity of subjective well-being and the multiple roles of physical activity stress the need to extend qualitative research to sedentary older adults and the institutionalized elderly to explore the relationship between well-being and physical activity in later life.
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Physical Activity and Dimensions of Subjective Well-Being in Older Adults
Aphrodite Stathi, Kenneth R. Fox, and James McKenna
Exploring Recall of Physical Activity in Young People Using Qualitative Interviewing
James McKenna, Lucy Jane Foster, and Angela Page
Recall of physical activity is a known problem affecting all forms of self-report. Participants age 8–16 years contributed to 16 focus groups and 24 interviews based on cognitive interviewing (n = 8) and think-aloud (n = 8) and general probing (n = 8) techniques. When unassisted, participants readily described physical activity mode but gave vague descriptions of daily activities. In contrast, the close detail of frequency, intensity, and duration of these activities was only more fully developed through prompting. Talk-based methods can provide considerable insight into developing more reliable and valid physical activity self-reports.
The Transition of Medical Students Through Residency: Effects on Physical Activity and Other Lifestyle-Related Behaviors
Alba Pardo, Anna Mitjans, Lucía Baranda, Manel Salamero, James McKenna, Antoni Arteman, and Mariona Violán
Background:
Little is known about lifestyle choices and preventive healthcare-seeking behaviors during the transition from medical school graduation to residency training, a period characterized by increased rates of stress and lack of free time due to demanding working conditions. All of these issues are likely to affect physical activity (PA) level. This study explored the evolution of PA and other lifestyle behaviors during this transition.
Methods:
A cross-sectional study and a cohort study were conducted with medical students (2010) and physicians before and after the first year of residency (2013 and 2014). A self-administered questionnaire assessed PA, health and lifestyle behaviors.
Results:
From a sample of 420 medical students and 478 residents, 74% comply with current PA guidelines. PA decreased by 16% during residency. Low levels of PA were found among (i) females and in respondents who reported (ii) poor self-perceived health and (iii) unhealthy body weight (P < .05). Low PA level was also significantly associated with poor mental health in first-year residents.
Conclusions:
The transition has a negative effect on physicians’ PA level that may affect physicians’ own health and patient care. Medical programs should encourage residents to engage in PA to assure physicians’ personal and mental health.
Physical Activity and Sedentary Behavior Clustering: Segmentation to Optimize Active Lifestyles
Stephen Zwolinsky, James McKenna, Andy Pringle, Paul Widdop, Claire Griffiths, Michelle Mellis, Zoe Rutherford, and Peter Collins
Background:
Increasingly the health impacts of physical inactivity are being distinguished from those of sedentary behavior. Nevertheless, deleterious health prognoses occur when these behaviors combine, making it a Public Health priority to establish the numbers and salient identifying factors of people who live with this injurious combination.
Methods:
Using an observational between-subjects design, a nonprobability sample of 22,836 participants provided data on total daily activity. A 2-step hierarchical cluster analysis identified the optimal number of clusters and the subset of distinguishing variables. Univariate analyses assessed significant cluster differences.
Results:
High levels of sitting clustered with low physical activity. The Ambulatory & Active cluster (n = 6254) sat for 2.5 to 5 h·d−1 and were highly active. They were significantly younger, included a greater proportion of males and reported low Indices of Multiple Deprivation compared with other clusters. Conversely, the Sedentary & Low Active cluster (n = 6286) achieved ≤60 MET·min·wk−1 of physical activity and sat for ≥8 h·d−1. They were the oldest cluster, housed the largest proportion of females and reported moderate Indices of Multiple Deprivation.
Conclusions:
Public Health systems may benefit from developing policy and interventions that do more to limit sedentary behavior and encourage light intensity activity in its place.
