Using the affective priming paradigm to explore the attitudes underlying walking behaviour

Objectives. Walking is poorly represented in memory, making it difficult to measure using self-report and even harder to predict. To circumvent this, we used the affective priming paradigm (Fazio, Sanbonmatsu, Powell, & Kardes, 1986) to assess implicit attitudes towards walking. Methods. Royal Air Force trainee aircraftsmen (N ¼ 188) wore pedometers for 1 week prior to completing the affective priming paradigm, questionnaire and interview. The affective priming paradigm involved a computer-based response latency task containing physical activity words as primes followed by adjectives as targets to be evaluated. Targets were drawn from two bipolar dichotomies, good–bad (the original Fazio et al. items) and happy–sad (mood). Results. Priming for mood items was related to levels of physical activity with high frequency participants priming for the positive (happy) pole and low frequency participants priming for the negative (sad). Both groups primed for the negative element of the Fazio (good–bad) dichotomy. Regarding walking and running, there was no differentiation on the basis of participation level. Instead, facilitated responses to happy targets contrasted with inhibited responses to sad targets for both types of locomotion. There was weak evidence that intentions to run were associated with priming of positive target items, irrespective of category. Conclusions. The relationship between implicit attitudes and behaviour is complex. Whereas implicit attitudes were related to overall exercise participation, they were not related to the specific activity of walking, despite the behaviour being mainly under automatic control.</p

The theory of planned behaviour predicts self-reports of walking, but does not predict step count

Objectives This paper compares multiple measures of walking in two studies, and the second study compares how well Theory of Planned Behaviour (TPB) constructs perform in predicting these different measures. Methods In Study 1, 41 participants wore a New Lifestyles NL-2000 pedometer for 1 week. Subsequently, participants completed a questionnaire containing measures of the TPB constructs and two self-report measures of walking, followed by two interview measures of walking. For Study 2, 200 RAF trainee aircraftsmen wore pedometers for 2 weeks. At the end of each week, participants completed the questionnaire and interview measures of walking. Results Both studies found no significant association between questionnaire measures of walking and pedometer measures. In Study 1, the interview measures produced significant, large correlations with the pedometer measure, but these relationships were markedly weaker in the second study. TPB variables were found to explain 22% of variance in intention to walk in Study 1 and 45% of the variance in Study 2. In Study 2, prediction of subsequent measures of behaviour was found to be weak, except when using a single-item measure of walking. Conclusions Recall of walking is poor, and accurate measurement by self-report is problematic. Although the TPB predicts intentions to walk well, it does not predict actual amount of walking, as assessed by pedometer. Possible reasons for these findings include the unique nature of walking as an activity primarily used to facilitate higher order goals. The use of single-item measures may exaggerate the effectiveness of the TPB model for walking, and possibly other forms of physical activity.</p

Accessibility of salient beliefs about the outcomes of physical activity

Objectives. Attitudes may influence behaviour through both deliberative and automatic processes. To investigate the automatic influences of attitudes, this study explores the accessibility of modally salient beliefs about physical activity outcomes using response latency measures. Design. Response latencies for modally salient beliefs for physically activity outcomes were compared with latencies for non-salient, hygiene outcomes. Possible relationships between self-report and response latency was assessed between- and within-subjects. Method. Regularly active participants (N=148) completed a computer-based response latency task in which they indicated whether an outcome, for example more fit, was a likely or unlikely consequence of six different physical activities, for example go running. Self-reports of the likelihood of these outcomes, their importance, intentions to participate in the physical activities and frequency of participation were obtained. Results. As expected, the physical activity outcomes were more accessible than control outcomes. In addition, the outcome strong heart was less accessible than the outcomes more fit and have fun. There was only weak evidence, however, of any relationship between self-reports and the accessibility of the physical activity outcomes. Conclusion. Response latency data may represent a source of between-subject variation that differs from self-report. Discussion focuses on the possible origins of such a discrepancy

The theory of planned behaviour predicts self-reports of walking, but does not predict step count

Objectives This paper compares multiple measures of walking in two studies, and the second study compares how well Theory of Planned Behaviour (TPB) constructs perform in predicting these different measures. Methods In Study 1, 41 participants wore a New Lifestyles NL-2000 pedometer for 1 week. Subsequently, participants completed a questionnaire containing measures of the TPB constructs and two self-report measures of walking, followed by two interview measures of walking. For Study 2, 200 RAF trainee aircraftsmen wore pedometers for 2 weeks. At the end of each week, participants completed the questionnaire and interview measures of walking. Results Both studies found no significant association between questionnaire measures of walking and pedometer measures. In Study 1, the interview measures produced significant, large correlations with the pedometer measure, but these relationships were markedly weaker in the second study. TPB variables were found to explain 22% of variance in intention to walk in Study 1 and 45% of the variance in Study 2. In Study 2, prediction of subsequent measures of behaviour was found to be weak, except when using a single-item measure of walking. Conclusions Recall of walking is poor, and accurate measurement by self-report is problematic. Although the TPB predicts intentions to walk well, it does not predict actual amount of walking, as assessed by pedometer. Possible reasons for these findings include the unique nature of walking as an activity primarily used to facilitate higher order goals. The use of single-item measures may exaggerate the effectiveness of the TPB model for walking, and possibly other forms of physical activity