Designing solutions for complex behaviour change processes can be greatly aided by integrating insights from the behavioural sciences into design practice. However, this integration is hampered by the relative inaccessibility of behavioral scientific knowledge. Working in a multidisciplinary of design researchers and behavioural scientists may bridge the gap between the two fields. This paper shares our experiences in working as such a multidisciplinary group on a large project, amongst others consisting of the design of interventions for workplace safety. Our cooperation was fruitful, both for design researchers – being able to better structure the messiness of the design process –, behavioural scientists – gaining in ecological validity of their methods –, and commissioners – increased trust in potential outcomes of the design process. However, difficulties preventing synergy also transpired.
MULTIFILE
This workshop provides participants with the opportunity to familiarise themselves with the Behavioural Lenses Toolkit. This toolkit supports designers in using theory from the behavioural sciences to inform their work. The workshop consists of an introduction to the toolkit and a couple of hands-on exercises in which we will demonstrate and try out the toolkit in establishing use (r) contexts in behavioural design projects. Furthermore, we will try out a new prototype tool that supports making an evidence-based transition from user insights to behavioural change strategies.
OBJECTIVE: To investigate the level of agreement of the behavioural mapping method with an accelerometer to measure physical activity of hospitalized patients. DESIGN: A prospective single-centre observational study. SETTING: A university medical centre in the Netherlands. SUBJECTS: Patients admitted to the hospital. MAIN MEASURES: Physical activity of participants was measured for one day from 9 AM to 4 PM with the behavioural mapping method and an accelerometer simultaneously. The level of agreement between the percentages spent lying, sitting and moving from both measures was evaluated using the Bland-Altman method and by calculating Intraclass Correlation Coefficients. RESULTS: In total, 30 patients were included. Mean (±SD) age was 63.0 (16.8) years and the majority of patients were men (n = 18). The mean percentage of time (SD) spent lying was 47.2 (23.3) and 49.7 (29.8); sitting 42.6 (20.5) and 40.0 (26.2); and active 10.2 (6.1) and 10.3 (8.3) according to the accelerometer and observations, respectively. The Intraclass Correlation Coefficient and mean difference (SD) between the two measures were 0.852 and -2.56 (19.33) for lying; 0.836 and 2.60 (17.72) for sitting; and 0.782 and -0.065 (6.23) for moving. The mean difference between the two measures is small (⩽2.6%) for all three physical activity levels. On patient level, the variation between both measures is large with differences above and below the mean of ⩾20% being common. CONCLUSION: The overall level of agreement between the behavioural mapping method and an accelerometer to identify the physical activity levels 'lying', 'sitting' and 'moving' of hospitalized patients is reasonable.
