David K. Ingledew

A graded conceptualisation of self-determination in the regulation of exercise behaviour: Development of a measure using confirmatory factor analytic procedures

Summary--The aim of this research was to test the continuum of behavioural regulation, as outlined by Deci and Ryan (1990), in the exercise domain. A Behavioural Regulation in Exercise Questionnaire (BREQ) was developed to measure external, introjected, identified, intrinsic and amotivated forms of regulation for exercise behaviour. 298 sports centre attendees completed the questionnaire. Confirmatory factor analysis supported the existence of this gradient of autonomy in exercise behaviour regulation but high levels of skewness in the amotivation items indicated that amotivated regulation was not relevant for this sample. A four factor model with amotivation eliminated demonstrated acceptable discriminant validity and internal consistency. A second study confirmed the factor structure and internal consistency of the measure. Multisample analysis established factorial invariance across gender. Subscale intercorrelations approximated a simplex pattern, characteristic of an underlying continuum. The BREQ may allow finer analysis of the motivational forces at play in exercise adoption and maintenance situations.

Measurement of physical activity in children with particular reference to the use of heart rate and pedometry.

SummaryUnderstanding 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.

The effect of type of physical activity measure on the relationship between body fatness and habitual physical activity in children: a meta-analysis

Background: The relationship between activity levels and body fat in children is unclear, despite a large number of studies. The issue is clouded by the wide variety of methods used to assess childrens activity levels. It is important to assess whether the type of activity measure influences the fatness-activity relationship. This is a first step to uncovering the role of modifying variables such as gender, age, maturity, etc. Primary objective: This study uses meta-analytic procedures to synthesize the results of such studies and to assess whether the type of activity measure used has an effect on the strength of the relationship observed. Methods and procedures: Fifty studies were located that satisfied the inclusion criteria. Seventy-eight per cent of the studies showed a negative relationship, 18% no relationship and 4% a positive relationship between physical activity and body fatness. Data were analysed using the meta-analytic procedures described by Rosenthal (Meta-analytic Procedures for Social Research, Sage, 1991). Main outcomes and results: The mean effect size indicated a small to moderate, inverse relationship (r =-0.16). Mean effect sizes differed significantly (F(3,5,2) 8.04, p < 0.001) according to the activity measure used: questionnaire, r =-0.14; motion counters, r =-0.18; observation, r =-0.39; heart rate (HR), r = 0.00. Observation measures elicited a significantly stronger relationship with body fat than did questionnaire or heart rate measures (p < 0.05). However, there was no significant difference between the effect sizes elicited by observation and motion counters. Correlational analyses revealed no effect of age group or gender on the strength of the relationship between fatness and activity. Conclusions: This meta-analysis suggests there is a small to moderate relationship between body fat and activity in children. It is important to note, however, that the size of the relationship depends on the activity measure used. It is therefore recommended that direct measures of movement, such as observation or motion counter methods, are used to assess the relationship of activity levels with health.BACKGROUNDnThe relationship between activity levels and body fat in children is unclear, despite a large number of studies. The issue is clouded by the wide variety of methods used to assess childrens activity levels. It is important to assess whether the type of activity measure influences the fatness-activity relationship. This is a first step to uncovering the role of modifying variables such as gender, age, maturity, etc.nnnPRIMARY OBJECTIVEnThis study uses meta-analytic procedures to synthesize the results of such studies and to assess whether the type of activity measure used has an effect on the strength of the relationship observed.nnnMETHODS AND PROCEDURESnFifty studies were located that satisfied the inclusion criteria. Seventy-eight per cent of the studies showed a negative relationship, 18% no relationship and 4% a positive relationship between physical activity and body fatness. Data were analysed using the meta-analytic procedures described by Rosenthal (Meta-analytic Procedures for Social Research, Sage, 1991).nnnMAIN OUTCOMES AND RESULTSnThe mean effect size indicated a small to moderate, inverse relationship (r = -0.16). Mean effect sizes differed significantly (F(3,52) = 8.04, p < 0.001) according to the activity measure used: questionnaire, r = -0.14; motion counters, r = -0.18; observation, r = -0.39; heart rate (HR), r = 0.00. Observation measures elicited a significantly stronger relationship with body fat than did questionnaire or heart rate measures (p < 0.05). However, there was no significant difference between the effect sizes elicited by observation and motion counters. Correlational analyses revealed no effect of age group or gender on the strength of the relationship between fatness and activity.nnnCONCLUSIONSnThis meta-analysis suggests there is a small to moderate relationship between body fat and activity in children. It is important to note, however, that the size of the relationship depends on the activity measure used. It is therefore recommended that direct measures of movement, such as observation or motion counter methods, are used to assess the relationship of activity levels with health.

Social support dimensions and components of performance in tennis

The aim of this study was to explore the relationships between dimensions of social support and components of performance in tennis. A post-match performance measure was completed by 144 British tournament tennis players. Principal components analysis yielded eight components, labelled Execution of (Flexible) Plan, Loss of Composure, Feeling Flat, Positive Tension, Worry, Flow, Effective Tactics and Double Faults. Before the match, 46 players had also completed the Interpersonal Support Evaluation List. Stepwise regression analyses revealed significant effects of the Belonging and Appraisal dimensions of the Interpersonal Support Evaluation List on five of the performance components. The correlations between total support and four of these performance components were also significant. Logistic regression analyses revealed no significant effects of the dimensions of the Interpersonal Support Evaluation List or Total Support upon winning versus losing. Effects of social support upon performance were therefore only apparent when attention was focused on the components of performance.

Examination of the Validity of the Social Support Survey Using Confirmatory Factor Analysis

Abstract The Social Support Survey (SSS), validated by Richman, Rosenfeld, and Hardy (1993), is a multidimensional self-report measure of social support tested with student athletes. The SSS contains eight dimensions of support. For each dimension of support the same four questions are posed. The SSS could, therefore, be scored in two ways: (a) to derive a score for the support dimensions; (b) to derive a score for the questions posed across all eight support dimensions. Confirmatory factor analyses of the SSS on 416 university athletes revealed poor fits to models for both the eight support dimensions and the four questions across all eight dimensions. This problem was clarified by using a multitrait-multimethod model, which led to improved model fit but revealed that most of the SSS items were two-dimensional. Caution should, therefore, be exercised in using the SSS as a measure of multidimensional social support.