Assessing flow in physical activity: The Flow State Scale-2 and Dispositional Flow Scale-2

The Flow State Scale-2 (FSS-2) and Dispositional Flow Scale-2 (DFS-2) are presented as two self-report instruments designed to assess flow experiences in physical activity. Item modifications were made to the original versions of these scales in order to improve the measurement of some of the flow dimensions. Confirmatory factor analyses of an item identification and a cross-validation sample demonstrated a good fit of the new scales. There was support for both a 9-first-order factor model and a higher order model with a global flow factor. The item identification sample yielded mean item loadings on the first-order factor of .78 for the FSS-2 and .77 for the DFS-2. Reliability estimates ranged from .80 to .90 for the FSS-2, and .81 to .90 for the DFS-2. In the cross-validation sample, mean item loadings on the first-order factor were .80 for the FSS-2, and .73 for the DFS-2. Reliability estimates ranged between .80 to .92 for the FSS-2 and .78 to .86 for the DFS-2. The scales are presented as ways of assessing flow experienced within a particular event (FSS-2) or the frequency of flow experiences in chosen physical activity in general (DFS-2).

A six-year longitudinal study of the relationship of physical activity to bone mineral accrual in growing children: The University of Saskatchewan bone mineral accrual study

To investigate the influence of physical activity on bone mineral accrual during the adolescent years, we analyzed 6 years of data from 53 girls and 60 boys. Physical activity, dietary intakes, and anthropometry were measured every 6 months and dual-energy X-ray absorptiometry scans of the total body (TB), lumbar spine (LS), and proximal femur (Hologic 2000, array mode) were collected annually. Distance and velocity curves for height and bone mineral content (BMC) were fitted for each child at several skeletal sites using a cubic spline procedure, from which ages at peak height velocity (PHV) and peak BMC velocity (PBMCV) were identified. A mean age- and gender-specific standardized activity (Z) score was calculated for each subject based on multiple yearly activity assessments collected up until age of PHV. This score was used to identify active (top quartile), average (middle 2 quartiles), or inactive (bottom quartile) groups. Two-way analysis of covariance, with height and weight at PHV controlled for, demonstrated significant physical activity and gender main effects (but no interaction) for PBMCV, for BMC accrued for 2 years around peak velocity, and for BMC at 1 year post-PBMCV for the TB and femoral neck and for physical activity but not gender at the LS (all p < 0.05). Controlling for maturational and size differences between groups, we noted a 9% and 17% greater TB BMC for active boys and girls, respectively, over their inactive peers 1 year after the age of PBMCV. We also estimated that, on average, 26% of adult TB bone mineral was accrued during the 2 years around PBMCV.

Social-cognitive and perceived environment influences associated with physical activity in older Australians

Background, Regular physical activity in older adults can facilitate healthy aging, improve functional capacity, and prevent disease. However, factors associated with physical inactivity in older populations are poorly understood. This study attempts to identify social-cognitive and perceived environmental influences associated with physical activity participation in older populations. Methods. In a randomly selected sample of 449 Australian adults age 60 and older, we assessed self-reported physical activity and a range of social-cognitive and perceived environmental factors. Respondents were classified as sufficiently active and inactive based on energy expenditure estimates (kcal/week) derived from self-reported physical activity. Two logistic regression models, with and without self-efficacy included, were conducted to identify modifiable independent predictors of physical activity. Results. Significantly more males than females were physically active. Physical activity participation was related to age with a greater proportion of those age 65-69 being active than those age 60-64 or 70 or older. High self-efficacy, regular participation of friends and family, finding footpaths safe for walking, and access to local facilities were significantly associated with being active. Conclusion. Identifying predictors of physical activity in older populations, particularly social support, facility access, and neighbourhood safety, can inform the development of policy and intervention strategies to promote the health of older people. (C) 2000 American Health Foundation and Academic Press.

Occupation, hours worked, and leisure-time physical activity

Background. International research indicates that blue-collar employees typically exhibit lower rates of leisure-time physical activity. While lack of time and work demands are commonly reported barriers to activity, the extent to which time-at-work mediates the relationship between occupation and leisure-time physical activity is unclear. This study investigated the association between occupation, time spent in paid employment, and participation in leisure-time physical activity. Methods. This was a secondary analysis of cross-sectional data from the 1995 Australian Health Survey, focusing on employed persons ages 18-64 years (n = 24,454), Occupation was coded as per the Australian Standard Classification of Occupations and collapsed into three categories (professional, white-collar, blue-collar). Hours worked was categorized into eight levels, ranging from 1-14 to more than 50 h per week. Participation in leisure-time physical activity was categorized as either insufficient or sufficient for health, consistent with recommended levels of energy expenditure (1600 METS-min/fortnight). The relationship between occupation, hours worked, and leisure-time physical activity was examined using logistic regression. Analyses were conducted separately for male and female, and the results are presented as a series of models that successively adjust for a range of potential covariates: age, living arrangement, smoking status, body mass index, and self-reported health. Results. Individuals in blue-collar occupations were approximately 50% more likely to be classified as insufficiently active. This occupational variability in leisure-time physical activity was not explained by hours worked. There was a suggested relationship between hours worked and leisure-time physical activity; however, this differed between men and women, and was difficult to interpret. Conclusions. Occupational variability in leisure-time physical activity cannot be explained by hours worked. Therefore, reports that work constitutes a barrier to participation should be explored further. Identification of the factors contributing to occupational variability in leisure-time physical activity will add to our understanding of why population subgroups differ in their health risk profiles, and assist in the development of health promotion strategies to reduce rates of sedentariness and health inequalities. (C) 2000 American Health Foundation and Academic Press.

Promoting physical activity among middle-aged and older adults in health care settings

Physical inactivity continues to be a significant public health issue for middle-aged and older adults. This review focuses on physical activity interventions targeting older adults in health care settings. The literature in this area is limited and the results to date disappointing. Much remains to be done to develop effective interventions targeting older adults, especially those from underserved groups. Attention also needs to be paid to maintenance of initial treatment gains and to linking primary-care-based physical activity interventions to community-based resources. Recognition in the social and behavioral sciences of the importance of social-environmental influences on health and health behaviors mandates both a multidisciplinary and a multilevel intervention approach to the problem of physical inactivity.

No association between the deficit syndrome in psychosis and summer birth in the Southern Hemisphere

Recent studies have shown that individuals with schizophrenia who are born in summer have an increased odds of have deficit syndrome versus nondeficit syndrome. This study extends this work to examiningthis issue in patients from the Southern Hemisphere. Data which included OPCRITrSCAN items and demographic information was obtained for Australian-born cases from the Australian National Mental Health Survey. Followingpreviously published methods, cases were assigned to the deficit group Žns153.or non-deficit groupŽns228.. A logistic regression analysis was used to ascertain whether beingborn in summer ŽDecember, January, February.in the Southern Hemisphere altered the odds of havingdeficit syndrome. There was no association between summer birth and odds of havingdeficit versus non-deficit schizophrenia ŽOdds Ratios0.75, 95% CI 0.49–1.16.. Based on our previous work showingthat the size of the winterrspringbirth excess in schizophrenia is reduced in the Southern Hemisphere, we speculate that factors that influence the association between summer birth and non-deficit syndrome may also vary across geography andror latitude. The Stanley Foundation supported this project.