There is growing evidence for the effectiveness of choice architecture or ‘nudge’ interventions to change a range of behaviours including the consumption of alcohol, tobacco and food. Public acceptability is key to implementing these and other interventions. However, few studies have assessed public acceptability of these interventions, including the extent to which acceptability varies with the type of intervention, the target behaviour and with evidence of intervention effectiveness. These were assessed in an online study using a between-participants full factorial design with three factors: Policy (availability vs size vs labelling vs tax) x Behaviour (alcohol consumption vs tobacco use vs high-calorie snack food consumption) x Evidence communication (no message vs assertion of policy effectiveness vs assertion and quantification of policy effectiveness [e.g., a 10% change in behaviour]). Participants ( N = 7058) were randomly allocated to one of the 36 groups. The primary outcome was acceptability of the policy. Acceptability differed across policy, behaviour and evidence communication (all p s < .001). Labelling was the most acceptable policy (supported by 78%) and Availability the least (47%). Tobacco use was the most acceptable behaviour to be targeted by policies (73%) compared with policies targeting Alcohol (55%) and Food (54%). Relative to the control group (60%), asserting evidence of effectiveness increased acceptability (63%); adding a quantification to this assertion did not significantly increase this further (65%). Public acceptability for nudges and taxes to improve population health varies with the behaviour targeted and the type of intervention but is generally favourable. Communicating that these policies are effective can increase support by a small but significant amount, suggesting that highlighting effectiveness could contribute to mobilising public demand for policies. While uncertainty remains about the strength of public support needed, this may help overcome political inertia and enable action on behaviours that damage population and planetary health.

No abstract

Low public support for government interventions in health, environment and other policy domains can be a barrier to implementation. Communicating evidence of policy effectiveness has been used to influence attitudes towards policies, with mixed results. This review provides the first systematic synthesis of such studies. Eligible studies were randomized controlled experiments that included an intervention group that provided evidence of a policy's effectiveness or ineffectiveness at achieving a salient outcome, and measured policy support. From 6498 abstracts examined, there were 45 effect sizes from 36 eligible studies. In total, 35 ( N = 30 858) communicated evidence of effectiveness, and 10 ( N = 5078) communicated evidence of ineffectiveness. Random effects meta-analysis revealed that communicating evidence of a policy's effectiveness increased support for the policy (SMD = 0.11, 95% CI [0.07, 0.15], p < 0.0001), equivalent to support increasing from 50% to 54% (95% CI [53%, 56%]). Communicating evidence of ineffectiveness decreased policy support (SMD = −0.14, 95% CI [−0.22, −0.06], p < 0.001), equivalent to support decreasing from 50% to 44% (95% CI [41%, 47%]). These findings suggest that public support for policies in a range of domains is sensitive to evidence of their effectiveness, as well as their ineffectiveness.

Background Overconsumption of energy from food is a major contributor to the high rates of overweight and obesity in many populations. There is growing evidence that interventions that target the food environment may be effective at reducing energy intake. The current study aimed to estimate the effect of decreasing the proportion of higher energy (kcal) foods, with and without reducing portion size, on energy purchased in worksite cafeterias. Methods and findings This stepped-wedge randomised controlled trial (RCT) evaluated 2 interventions: (i) availability: replacing higher energy products with lower energy products; and (ii) size: reducing the portion size of higher energy products. A total of 19 cafeterias were randomised to the order in which they introduced the 2 interventions. Availability was implemented first and maintained. Size was added to the availability intervention. Intervention categories included main meals, sides, cold drinks, snacks, and desserts. The study setting was worksite cafeterias located in distribution centres for a major United Kingdom supermarket and lasted for 25 weeks (May to November 2019). These cafeterias were used by 20,327 employees, mainly (96%) in manual occupations. The primary outcome was total energy (kcal) purchased from intervention categories per day. The secondary outcomes were energy (kcal) purchased from nonintervention categories per day, total energy purchased per day, and revenue. Regression models showed an overall reduction in energy purchased from intervention categories of −4.8% (95% CI −7.0% to −2.7%), p < 0.001 during the availability intervention period and a reduction of −11.5% (95% CI −13.7% to −9.3%), p < 0.001 during the availability plus size intervention period, relative to the baseline. There was a reduction in energy purchased of −6.6% (95% CI −7.9% to −5.4%), p < 0.001 during the availability plus size period, relative to availability alone. Study limitations include using energy purchased as the primary outcome (and not energy consumed) and the availability only of transaction-level sales data per site (and not individual-level data). Conclusions Decreasing the proportion of higher energy foods in cafeterias reduced the energy purchased. Decreasing portion sizes reduced this further. These interventions, particularly in combination, may be effective as part of broader strategies to reduce overconsumption of energy from food in out-of-home settings. Trial registration ISRCTN registry ISRCTN87225572.

No abstract

The findings have implications for interventions designed to promote changes in health behaviour, as well as theoretical frameworks for understanding self-regulation.

Public support for numerous obesity policies is low, which is one barrier to their implementation. One reason for this low support is the tendency to ascribe obesity to failings of willpower as opposed to the environment. Correlational evidence supports this position. However, the experimental evidence is mixed. In two experimental studies, participants were randomised to receive no message, messages about the environment’s influence on obesity (Study 1 & 2), or messages about the environment’s influence on human behaviour (Study 1). We investigated whether communicating these messages changed support for obesity policies and beliefs about the causes of obesity. Participants were recruited from nationally representative samples in Great Britain (Study 1 & 2) and the USA (Study 2) (total n = 4391). Study 2 was designed to replicate existing research. Neither study found evidence that communicating the messages increased support for obesity policies or strengthened beliefs about the environment’s role in obesity. Study 2, therefore, did not replicate two earlier experimental studies. Instead, the studies reported here suggest that people’s beliefs about the causes of obesity are resistant to change in response to evidence and are, therefore, not a promising avenue to increase support for obesity policies.

Objective: Research on Open Science practices in Health Psychology is lacking. This meta-research study aimed to identify research question priorities and obtain consensus on the Top 5 prioritised research questions for Open Science in Health Psychology. Methods and measures: An international Delphi consensus study was conducted. Twenty-three experts in Open Science and Health Psychology within the European Health Psychology Society (EHPS) suggested research question priorities to create a 'long-list' of items (Phase 1). Forty-three EHPS members rated the importance of these items, ranked their top five and suggested their own additional items (Phase 2). Twenty-four EHPS members received feedback on Phase 2 responses and then re-rated and re-ranked their top five research questions (Phase 3). Results:The top five ranked research question priorities were: 1. 'To what extent are Open Science behaviours currently practised in Health Psychology?' , 2. 'How can we maximise the usefulness of Open Data and Open Code resources?' , 3. 'How can Open Data be increased within Health Psychology?' , 4. 'What interventions are effective for increasing the adoption of Open Science in Health Psychology?' and 5. 'How can we increase free Open Access publishing in Health Psychology?' . Conclusion: Funding and resources should prioritise the research questions identified here.