Heart rate telemetry is frequently used to estimate daily activity in children and to validate other methods. This study compared the accuracy of heart rate monitoring, pedometry, triaxial accelerometry, and uniaxial accelerometry for estimating oxygen consumption during typical children's activities. Thirty Welsh children (mean age 9.2 +/- 0.8 yr) walked (4 and 6 km/h) and ran (8 and 10 km/h) on a treadmill, played catch, played hopscotch, and sat and crayoned. Heart rate, body accelerations in three axes, pedometry counts, and oxygen uptake were measured continuously during each 4-min activity. Oxygen uptake was expressed as a ratio of body mass raised to the power of 0.75 [scaled oxygen uptake (sVO2)]. All measures correlated significantly (P < 0.001) with sVO2. A multiple-regression equation that included triaxial accelerometry counts and heart rate predicted sVO2 better than any measure alone (R2 = 0.85, standard error of the estimate = 9.7 ml.kg-0.75.min-1). The best of the single measures was triaxial accelerometry (R2 = 0.83, standard error of the estimate = 10.3 ml.kg-0.75.min-1). It is concluded that a triaxial accelerometer provides the best assessment of activity. Pedometry offers potential for large population studies.

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Objectives. The aim of this study was to further develop and refine the Exercise Motivations Inventory (EMI), a measure of individuals' reasons for exercising.Design. Confirmatory factor analytic procedures using LISREL were employed to test the hypothesized 14-factor structure of the revised instrument (the EMI-2) and the invariance of the factor structure across gender.Methods. Four hundred and twenty-five civil servants completed the revised instrument. Analyses were conducted in three phases. Phase 1 involved detailed examination of the fit of the 14-factors separately in order to detect and eliminate poor indicators. In Phase 2 each factor was paired with every other factor in order to detect and eliminate ambiguous items. In Phase 3 factors were grouped with conceptually related factors into five submodels and the fit and factorial invariance across gender of these submodels was tested.Results. Item elimination at Phases 1 and 2 led to the development of a set of internally consistent factors with strong indicators and good discriminant validity. Phase 3 gave further evidence for the convergent and discriminant validity of the items and factors and strong support for the invariance of the factor structure across gender.Conclusions. The EMI-2 is a factorially valid means of assessing a broad range of exercise participation motives in adult males and females, applicable to both exercisers and non-exercisers.

The aim was to better understand the role of motives in exercise participation. It was hypothesised that motives influence exercise participation by influencing behavioural regulation, and that motives are themselves influenced by personality traits. Data were from a cross-sectional questionnaire survey of 252 office workers, mean age 40 years. Analysis was by structural equation modelling. According to the final model, appearance/weight motive increased external regulation, thereby reducing participation, and also increased introjected regulation. Health/fitness motive increased identified regulation, thereby increasing participation. Social engagement motive increased intrinsic regulation. Neuroticism increased appearance/weight motive, openness increased health/fitness motive, and conscientiousness, without affecting motives, reduced external and introjected regulation. It is inferred that exercise promotion programmes, without denigrating appearance/weight motive, should encourage other motives more conducive to autonomous motivation.

The relationships between children's activity, aerobic fitness, and fatness are unclear. Indirect estimates of activity, e.g., heart rate (HR) and recall, may mask any associations. The purpose of this study was to assess these relationships by using the Tritrac-R3D, a pedometer, and heart rate. Thirty-four children, ages 8-10 yr, participated in the study. The Tritrac and pedometer were worn for up to 6 days. HR was measured for 1 day. Activity measured by Tritrac or pedometer correlated positively to fitness in the whole group (Tritrac, r = 0.66; pedometer, r = 0.59; P < 0.01) and in boys and girls separately (P < 0.05) and correlated negatively to fatness in the whole group (r = -0.42, P < 0.05). In contrast, HR did not correlate significantly to fitness, and HR of >139 beats/min correlated positively to fatness in girls (r = 0.64, P < 0.05). This suggests that HR is misleading as a measure of activity. This study supports a positive relationship between activity and fitness and suggests a negative relationship between fatness and activity.

The aim was to examine how exercise motives differ across stages of change. British government employees completed questionnaires measuring exercise motives and exercise stage of change at baseline (N = 425) and at 3-month follow-up (247 of the original sample). Discriminant analysis was used to determine whether exercise motives (and age and gender) could collectively discriminate between baseline stages of change; and whether exercise motives could discriminate between those who stayed inactive, stayed active, became active or became inactive over the 3 months. Taken as a whole, and with some qualifications, the results suggest that extrinsic (specifically bodily) motives dominate during the early stages of exercise adoption, but that intrinsic (specifically enjoyment) motives are important for progression to and maintenance of actual activity. This is consistent with Deci and Ryan's (1985) self- determination theory. The implications for exercise promotion are discussed.

The aim was to test a three‐level model of motivation, derived from self‐determination theory. According to the model, dispositional motives (represented by life goals) influence participatory motives (exercise participation motives), which influence regulatory motives (exercise behavioural regulations), which influence behaviour (exercise participation). The participants were 251 young adults. They completed the Aspirations Index, Exercise Motivations Inventory version 2, Behavioural Regulation in Exercise Questionnaire version 2, and a quantity‐frequency measure of exercise participation. The model was tested using partial least squares latent variable modelling. Exercise participation was positively predicted by identified and intrinsic but not predicted by external or introjected behavioural regulations. Behavioural regulations were predicted by participation motives: intrinsic regulation by affiliation and challenge motives; identified regulation by health/fitness and stress management motives; introjected regulation by appearance/weight motive; external regulation by social recognition and appearance/weight motives; all positively. Participation motives were themselves predicted by corresponding life goals. The findings support the three‐level model of motivation. Health promotion programmes need to take account of individuals' participatory motives and underlying dispositional motives.

Understanding the progression of physical activity behaviour from childhood to adulthood requires a valid, reliable and practical method of assessing activity levels which is appropriate for use in large groups. The measurement of physical activity in large scale research projects requires a method which is low in cost, agreeable to the study volunteer and accurate. Self-report can be used to determine adult activity patterns, but children lack the cognitive ability to recall details about their activity patterns. Heart rate telemetry has been used to estimate daily activity in children as a sole criterion and to validate commercial accelerometers. However, heart rate is an indirect estimate of physical activity which makes assumptions based on the linear relationship between heart rate and oxygen uptake. It is sensitive to emotional stress and body position, and takes longer to reach resting levels after physical exertion compared with oxygen uptake. It also lags behind movement, particularly as children's physical activity is spasmodic or intermittent in nature. One alternative is the pedometer. Many early studies reported that the pedometer is inaccurate and unreliable in measuring distance or counting steps. While reasonably accurate at mid range speeds, the accuracy of the pedometer decreases in very slow walking or very fast walking or running. However, more recent studies have examined the efficacy of using pedometers to assess daily or weekly activity patterns as a whole, and these have produced more promising results. In this regard, the pedometer has a number of advantages. It is very cheap, objective and does not interfere with daily activities and is therefore appropriate for use in population studies. Commercial accelerometers with a time-sampling mechanism offer further potential and could be used to provide a picture of the pattern of children's activity. As it has been observed that prolonged activity periods are not typically associated with childhood behaviour patterns, the use of a threshold value for 'aerobic' training stimulus is not appropriate as a cut-off value for physical activity. Instead, there is evidence to suggest that the total activity data measured by pedometers over limited periods of time may be more appropriate to assess how active children are.