It's how you say it – The extended Theory of Planned Behaviour explains active transport use in cardiac patients depending on the type of self-report in a hypothesis-generating study. (October 2022) - Batool, Tooba; Ross, Veerle; Brijs, Kris; Neven, An; Smeets, Christophe J.P.; Scherrenberg, Martijn; Dendale, Paul; Vanrompay, Yves; Janssens, Davy; Wets, Geert
Highlights: Different behavioural measures were explained differently by Theory of planned behaviour (TPB) and habit strength. TPB explains the implicit measures of active transport use of CHD patients, poorly. Habit strength is a predictor in two types of behaviour measurement methods. Self-reported measures should be assessed in degree of representing the actual behaviour. Higher intention resulted in a lower behavioural frequency: intention-behaviour gap. Abstract: Physical activity (PA) plays an essential part in the secondary prevention of persons with coronary heart disease (CHD). A substantial amount of PA can be gained through increasing the use of active transport modes (walking or cycling for at least 10 min/day) in CHD patients' daily routine, benefiting the mortality and morbidity rate as well as the environment. The current study aims to investigate the utility of the Theory of Planned Behaviour (TPB) framework extended with habit strength, in understanding the behavioural intention and the behaviour of using active transport modes during the daily travel routine of CHD patients. A cross-sectional survey was conducted from 131 CHD patients. The behaviour was measured using three self-report methods; 1) scale measure, the walking or cycling frequency, 2) direct ATS (Active Travel Score, PA calculated by the directly reported aggregated time spent per day for walking or cycling for travel purposes), and 3) indirect ATS (PA calculated by combining the duration spent on trips by walking and cycling from the self-reported one-day travel diary). Additionally, the participants completed surveys on the direct measures of TPB constructs and habit strength. The results indicated that the TPB constructs explained a 38% variance in the intention to use active transport modes of CHD patients, by which the variance increased to 59% with the addition of habit strength. On the contrary, different behavioural measures were explained differently by TPB and habit strength. The scale measure of behaviour was best predicted (up to 21%) by TPB and habit strength. However, the direct and indirect measures of behaviour were poorly explained (up to 3% and 10% only, respectively). Habit strength moderated the relationship between behaviour (scale measure) and behavioural intention. Surprisingly, higher behavioural intention resulted in a lower behavioural frequency when the habit strength to be active is low. This suggests a limited control over the behaviour thus indicating the intention-behaviour gap. The current study findings highlight the inconsistent predictive utility of TPB across different types of behavioural self-report measures, targeted at the use of active transport modes in CHD patients. However, considering this study as hypothesis-generating, further research is necessary to replicate and extend these findings.