Impact on wine sales of removing the largest serving size by the glass: An A-B-A reversal trial in 21 pubs, bars, and restaurants in England.

BACKGROUND: Interventions that alter aspects of the physical environments in which unhealthy behaviours occur have the potential to change behaviour at scale, i.e., across populations, and thereby decrease the risk of several diseases. One set of such interventions involves reducing serving sizes, which could reduce alcohol consumption. The effect of modifying the available range of serving sizes of wine in a real-world setting is unknown. We aimed to assess the impact on the volume of wine sold of removing the largest serving size by the glass from the options available in licensed premises. METHODS AND FINDINGS: The study was conducted between September 2021 and May 2022 in 21 licensed premises in England that sold wine by the glass in serving sizes greater than 125 ml (i.e., 175 ml or 250 ml) and used an electronic point of sale till system. It used an A-B-A reversal design, set over 3 four-weekly periods. "A" represented the nonintervention periods during which standard serving sizes were served and "B" the intervention period when the largest serving size for a glass of wine was removed from the existing range in each establishment: 250 ml (18 premises) or 175 ml (3 premises). The primary outcome was the daily volume of wine sold, extracted from sales data. Twenty-one premises completed the study, 20 of which did so per protocol and were included in the primary analysis. After adjusting for prespecified covariates, the intervention resulted in -420·8 millilitres (ml) (95% confidence intervals (CIs) -681·4 to -160·2 p = 0·002) or -7·6% (95% CI -12·3%, -2·9%) less wine being sold per day. There was no evidence that sales of beer and cider or total daily revenues changed but the study was not powered to detect differences in these outcomes. The main study limitation is that we were unable to assess the sales of other alcoholic drinks apart from wine, beer, and cider, estimated to comprise approximately 30% of alcoholic drinks sold in participating premises. CONCLUSIONS: Removing the largest serving size of wine by the glass from those available reduced the volume of wine sold. This promising intervention for decreasing alcohol consumption across populations merits consideration as part of alcohol licensing regulations. TRIAL REGISTRATION: ISRCTN https://doi.org/10.1186/ISRCTN33169631; OSF https://osf.io/xkgdb.

Impact on alcohol selection and online purchasing of changing the proportion of available non-alcoholic versus alcoholic drinks: A randomised controlled trial.

BACKGROUND: Increasing the availability of non-alcoholic options is a promising population-level intervention to reduce alcohol consumption, currently unassessed in naturalistic settings. This study in an online retail context aimed to estimate the impact of increasing the proportion of non-alcoholic (relative to alcoholic) drinks, on selection and purchasing of alcohol. METHODS AND RESULTS: Adults (n = 737) residing in England and Wales who regularly purchased alcohol online were recruited between March and July 2021. Participants were randomly assigned to one of 3 groups: "25% non-alcoholic/75% alcoholic"; "50% non-alcoholic/50% alcoholic"; and "75% non-alcoholic/25% alcoholic," then selected drinks in a simulated online supermarket, before purchasing them in an actual online supermarket. The primary outcome was the number of alcohol units selected (with intention to purchase); secondary outcomes included actual purchasing. A total of 607 participants (60% female, mean age = 38 years [range: 18 to 76]) completed the study and were included in the primary analysis. In the first part of a hurdle model, a greater proportion of participants in the "75% non-alcoholic" group did not select any alcohol (13.1%) compared to the "25% non-alcoholic" group (3.4%; 95% confidence interval [CI] -2.09, -0.63; p < 0.001). There was no evidence of a difference between the "75% non-alcoholic" and the "50% non-alcoholic" (7.2%) groups (95% CI 0.10, 1.34; p = 0.022) or between the "50% non-alcoholic" and the "25% non-alcoholic" groups (95% CI -1.44, 0.17; p = 0.121). In the second part of a hurdle model in participants (559/607) selecting any drinks containing alcohol, the "75% non-alcoholic" group selected fewer alcohol units compared to the "50% non-alcoholic" (95% CI -0.44, -0.14; p < 0.001) and "25% non-alcoholic" (95% CI -0.54, -0.24; p < 0.001) groups, with no evidence of a difference between the "50% non-alcoholic" and "25% non-alcoholic" groups (95% CI -0.24, 0.05; p = 0.178). Overall, across all participants, 17.46 units (95% CI 15.24, 19.68) were selected in the "75% non-alcoholic" group; 25.51 units (95% CI 22.60, 28.43) in the "50% non-alcoholic" group; and 29.40 units (95% CI 26.39, 32.42) in the "25% non-alcoholic" group. This corresponds to 8.1 fewer units (a 32% reduction) in the "75% non-alcoholic" compared to the "50% non-alcoholic" group, and 11.9 fewer alcohol units (41% reduction) compared to the "25% non-alcoholic" group; 3.9 fewer units (13% reduction) were selected in the "50% non-alcoholic" group than in the "25% non-alcoholic" group. For all other outcomes, alcohol selection and purchasing were consistently lowest in the "75% non-alcoholic" group. Study limitations include the setting not being entirely naturalistic due to using a simulated online supermarket as well as an actual online supermarket, and that there was substantial dropout between selection and purchasing. CONCLUSIONS: This study provides evidence that substantially increasing the proportion of non-alcoholic drinks-from 25% to 50% or 75%-meaningfully reduces alcohol selection and purchasing. Further studies are warranted to assess whether these effects are realised in a range of real-world settings. TRIAL REGISTRATION: ISRCTN: 11004483; OSF: https://osf.io/qfupw.

Impact on sales of adding a smaller serving size of beer and cider in licensed premises: an A-B-A reversal design.

BACKGROUND: Smaller serving sizes of alcoholic drinks could reduce alcohol consumption across populations thereby lowering the risk of many diseases. The effect of modifying the available range of serving sizes of beer and cider in a real-world setting has yet to be studied. The current study assessed the impact on beer and cider sales of adding a serving size of draught beer and cider (2/3 pint) that was between the current smallest (1/2 pint) and largest (1 pint) standard serving sizes. METHODS: Twenty-two licensed premises in England consented to taking part in the study. The study used an ABA reversal design, set over three 4-weekly periods, with A representing the non-intervention periods, during which standard serving sizes were served and B the intervention period when a 2/3 pint serving size of draught beer and cider was added to the existing range, along with smaller 1/2 pint and larger 1 pint serving sizes. The primary outcome was the daily volume of beer and cider sold, extracted from sales data. RESULTS: Fourteen premises started the study, of which thirteen completed it. Twelve of those did so per protocol and were included in the primary analysis. After adjusting for pre-specified covariates, the intervention did not have a significant effect on the volume of beer and cider sold per day (3.14 ml; 95%CIs -2.29 to 8.58; p = 0.257). CONCLUSIONS: In licensed premises, there was no evidence that adding a smaller serving size for draught beer and cider (2/3 pint) when the smallest (1/2 pint) and largest (1 pint) sizes were still available, affected the volume of beer and cider sold. Studies are warranted to assess the impact of removing the largest serving size. TRIAL REGISTRATION: ISRCTN: https://doi.org/10.1186/ISRCTN33169631 (08/09/2021), OSF: https://osf.io/xkgdb/ (08/09/2021).

Visualising health risks with medical imaging for changing recipients' health behaviours and risk factors: Systematic review with meta-analysis.

BACKGROUND: There is ongoing clinical and research interest in determining whether providing personalised risk information could motivate risk-reducing health behaviours. We aimed to assess the impact on behaviours and risk factors of feeding back to individuals' images of their bodies generated via medical imaging technologies in assessing their current disease status or risk. METHODS AND FINDINGS: A systematic review with meta-analysis was conducted using Cochrane methods. MEDLINE, Embase, PsycINFO, CINAHL, and the Cochrane Central Register of Controlled Trials (CENTRAL) were searched up to July 28, 2021, with backward and forward citation searches up to July 29, 2021. Eligible studies were randomised controlled trials including adults who underwent medical imaging procedures assessing current health status or risk of disease, for which personal risk may be reduced by modifying behaviour. Trials included an intervention group that received the imaging procedure plus feedback of visualised results and assessed subsequent risk-reducing health behaviour. We examined 12,620 abstracts and included 21 studies, involving 9,248 randomised participants. Studies reported on 10 risk-reducing behaviours, with most data for smoking (8 studies; n = 4,308), medication use (6 studies; n = 4,539), and physical activity (4 studies; n = 1,877). Meta-analysis revealed beneficial effects of feedback of visualised medical imaging results on reduced smoking (risk ratio 1.11, 95% confidence interval [CI] 1.01 to 1.23, p = 0.04), healthier diet (standardised mean difference [SMD] 0.30, 95% CI 0.11 to 0.50, p = 0.003), increased physical activity (SMD 0.11, 95% CI 0.003 to 0.21, p = 0.04), and increased oral hygiene behaviours (SMD 0.35, 95% CI 0.13 to 0.57, p = 0.002). In addition, single studies reported increased skin self-examination and increased foot care. For other behavioural outcomes (medication use, sun protection, tanning booth use, and blood glucose testing) estimates favoured the intervention but were not statistically significant. Regarding secondary risk factor outcomes, there was clear evidence for reduced systolic blood pressure, waist circumference, and improved oral health, and some indication of reduced Framingham risk score. There was no evidence of any adverse effects, including anxiety, depression, or stress, although these were rarely assessed. A key limitation is that there were some concerns about risk of bias for all studies, with evidence for most outcomes being of low certainty. In particular, valid and precise measures of behaviour were rarely used, and there were few instances of preregistered protocols and analysis plans, increasing the likelihood of selective outcome reporting. CONCLUSIONS: In this study, we observed that feedback of medical images to individuals has the potential to motivate risk-reducing behaviours and reduce risk factors. Should this promise be corroborated through further adequately powered trials that better mitigate against risk of bias, such interventions could usefully capitalise upon the widespread and growing use of medical imaging technologies in healthcare.

Evaluation of physical activity calorie equivalent (PACE) labels' impact on energy purchased in cafeterias: A stepped-wedge randomised controlled trial.

BACKGROUND: A recent meta-analysis suggested that using physical activity calorie equivalent (PACE) labels results in people selecting and consuming less energy. However, the meta-analysis included only 1 study in a naturalistic setting, conducted in 4 convenience stores. We therefore aimed to estimate the effect of PACE labels on energy purchased in worksite cafeterias in the context of a randomised study design. METHODS AND FINDINGS: A stepped-wedge randomised controlled trial (RCT) was conducted to investigate the effect of PACE labels (which include kcal content and minutes of walking required to expend the energy content of the labelled food) on energy purchased. The setting was 10 worksite cafeterias in England, which were randomised to the order in which they introduced PACE labels on selected food and drinks following a baseline period. There were approximately 19,000 workers employed at the sites, 72% male, with an average age of 40. The study ran for 12 weeks (06 April 2021 to 28 June 2021) with over 250,000 transactions recorded on electronic tills. The primary outcome was total energy (kcal) purchased from intervention items per day. The secondary outcomes were: energy purchased from non-intervention items per day, total energy purchased per day, and revenue. Regression models showed no evidence of an overall effect on energy purchased from intervention items, -1,934 kcals per site per day (95% CI -5,131 to 1,262), p = 0.236, during the intervention relative to baseline, equivalent to -5 kcals per transaction (95% CI -14 to 4). There was also no evidence for an effect on energy purchased from non-intervention items, -5 kcals per site per day (95% CI -513 to 504), p = 0.986, equivalent to 0 kcals per transaction (95% CI -1 to 1), and no clear evidence for total energy purchased -2,899 kcals per site (95% CI -5,810 to 11), p = 0.051, equivalent to -8 kcals per transaction (95% CI -16 to 0). Study limitations include using energy purchased and not energy consumed as the primary outcome and access only to transaction-level sales, rather than individual-level data. CONCLUSION: Overall, the evidence was consistent with PACE labels not changing energy purchased in worksite cafeterias. There was considerable variation in effects between cafeterias, suggesting important unmeasured moderators. TRIAL REGISTRATION: The study was prospectively registered on ISRCTN (date: 30.03.21; ISRCTN31315776).

Is altering the availability of healthier vs. less-healthy options effective across socioeconomic groups? A mega-analysis.

BACKGROUND: Availability interventions have been hypothesised to make limited demands on conscious processes and, as a result, to be less likely to generate health inequalities than cognitively-oriented interventions. Here we synthesise existing evidence to examine whether the impact of altering the availability of healthier vs. less-healthy options differs by socioeconomic position. METHODS: Individual-level data (21,360 observations from 7,375 participants) from six studies (conducted online (n = 4) and in laboratories (n = 2)) were pooled for mega-analysis. Multilevel logistic regressions analysed the impact of altering the availability of healthier options on selection of a healthier (rather than a less-healthy) option by socioeconomic position, assessed by (a) education and (b) income. RESULTS: Participants had over threefold higher odds of selecting a healthier option when the available range was predominantly healthier compared to selections when the range offered was predominantly less-healthy (odds ratio (OR): 3.8; 95%CIs: 3.5, 4.1). Less educated participants were less likely to select healthier options in each availability condition (ORs: 0.75-0.85; all p < 0.005), but there was no evidence of differences in healthier option selection by income. Compared to selections when the range offered was predominantly less-healthy, when predominantly healthier options were available there was a 31% increase in selecting healthier options for the most educated group vs 27% for the least educated. This modest degree of increased responsiveness in the most educated group appeared only to occur when healthier options were predominant. There was no evidence of any differential response to the intervention by income. CONCLUSION: Increasing the proportion of healthier options available increases the selection of healthier options across socioeconomic positions. Availability interventions may have a slightly larger beneficial effect on those with the highest levels of education in settings when healthier options predominate.

Explaining the effect on food selection of altering availability: two experimental studies on the role of relative preferences.

BACKGROUND: Increasing the availability of healthier or plant-based foods increases their selection. The current studies aimed to examine the extent to which relative preferences account for food selections following availability interventions. In particular, (a) whether increasing the availability of lower-energy options increases the likelihood that individuals' highest-ranked option is lower-energy, and (b) the extent to which selections reflect individuals' highest-ranked option from the available range. METHODS: UK adults (Study 1: n = 1976; Study 2: n = 1078) took part in within-subjects online studies. In both studies, the order of preference between food options was established by participants choosing the option that they would prefer "to eat right now" from every possible pairing within a pool of eight options. Then, participants were shown either predominantly higher-energy options (three higher- and one lower-energy) or predominantly lower-energy options (vice versa), presented in a random order. RESULTS: When predominantly lower-energy options were presented, the odds of the highest-ranked option being a lower-energy option increased ten-fold (Study 1: odds ratio: 10.1; 95%CI: 8.9,11.4; Study 2: odds ratio: 10.4; 95%CI: 7.4,14.7), compared to when predominantly higher-energy options were available. In both studies, around 90% of selections reflected the highest-ranked option in the range offered in the studied availability conditions (range 88-92%). CONCLUSIONS: These studies suggest that increased availability of lower-energy options increases the likelihood of an individual's highest-ranked option being lower-energy, and that the highest-ranked option has the greatest likelihood of selection. As such, preferences may be a key contributor to the effects of altering availability on food selections. TRIAL REGISTRATION: ISRCTN ( http://www.isrctn.com/ISRCTN27598623 ; 3/12/19 [Study 1]; http://www.isrctn.com/ISRCTN61010183 ; 20/4/20 [Study 2]).

Effect of health warning labels on motivation towards energy-dense snack foods: Two experimental studies.

Health warning labels (HWLs) show promise in reducing motivation towards energy-dense snack foods. Understanding the underlying mechanisms could optimise their effectiveness. In two experimental studies in general population samples (Study 1 n = 90; Study 2 n = 1382), we compared the effects of HWLs and irrelevant aversive labels (IALs) on implicit (approach) motivation towards unhealthy snacks, using an approach-avoidance task (Study 1), and a manikin task (Study 2). We also assessed explicit motivation towards unhealthy snacks using food selection tasks. We examined whether labelling effects on motivation arose from the creation of outcome-dependent associations between the food and its health consequences or from simple, non-specific aversive associations. Both label types reduced motivation towards snack foods but only when the label was physically present. HWLs and IALs showed similar effects on implicit motivation, although HWLs reduced explicit motivation more than IALs. Thus, aversive HWLs appear to act both through low level associative mechanisms affecting implicit motivation, and by additionally emphasizing explicit causal links to health outcomes thereby affecting explicitly motivated choice behaviours.

Impact of decreasing the proportion of higher energy foods and reducing portion sizes on food purchased in worksite cafeterias: A stepped-wedge randomised controlled trial.

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.

Beyond choice architecture: advancing the science of changing behaviour at scale.

Addressing the global threats to population and planetary health requires changing many behaviours at scale. This demands consideration not only of the effect size of an intervention but also its reach - the proportion of the population exposed to the intervention.We propose that a relatively under-researched and generally poorly specified set of interventions involving changes to physical micro-environments - often referred to as Choice Architecture - has the potential to make a significant contribution to meeting this urgent challenge.Realising the potential of Choice Architecture interventions requires integration of basic - i.e. laboratory-based - and applied - i.e. field-based - research, generating interventions that can be delivered at scale alongside advancing theory. We illustrate this with examples to highlight the complementarity of laboratory and field studies informed by and in turn updating the results of evidence synthesis. The examples comprise two sets of interventions - changing the relative availability of products and changing their size - to reduce consumption of meat, energy from food and alcohol across populations.

Cigarette pack size and consumption: an adaptive randomised controlled trial.

BACKGROUND: Observational evidence suggests that cigarette pack size - the number of cigarettes in a single pack - is associated with consumption but experimental evidence of a causal relationship is lacking. The tobacco industry is introducing increasingly large packs, in the absence of maximum cigarette pack size regulation. In Australia, the minimum pack size is 20 but packs of up to 50 cigarettes are available. We aimed to estimate the impact on smoking of reducing cigarette pack sizes from ≥25 to 20 cigarettes per pack. METHOD: A two-stage adaptive parallel group RCT in which Australian smokers who usually purchase packs containing ≥25 cigarettes were randomised to use only packs containing either 20 (intervention) or their usual packs (control) for four weeks. The primary outcome, the average number of cigarettes smoked per day, was measured through collecting all finished cigarette packs, labelled with the number of cigarettes participants smoked. An interim sample size re-estimation was used to evaluate the possibility of detecting a meaningful difference in the primary outcome. RESULTS: The interim analysis, conducted when 124 participants had been randomised, suggested 1122 additional participants needed to be randomised for sufficient power to detect a meaningful effect. This exceeded pre-specified criteria for feasible recruitment, and data collection was terminated accordingly. Analysis of complete data (n = 79) indicated that the mean cigarettes smoked per day was 15.9 (SD = 8.5) in the intervention arm and 16.8 (SD = 6.7) among controls (difference - 0.9: 95%CI = - 4.3, 2.6). CONCLUSION: It remains unclear whether reducing cigarette pack sizes from ≥25 to 20 cigarettes reduces cigarette consumption. Importantly, the results of this study provide no evidence that capping cigarette pack sizes would be ineffective at reducing smoking. The limitations identified in this study can inform a more efficient RCT, which is urgently required to address the dearth of experimental evidence on the impact of large cigarette pack sizes on smoking. TRIAL REGISTRATION: https://doi.org/10.1186/ISRCTN34202533.

Effects of pairing health warning labels with energy-dense snack foods on food choice and attitudes: Online experimental study.

BACKGROUND: There is limited evidence concerning the potential effectiveness of health warning labels (HWLs) using images and text to depict possible negative health consequences of consumption, for reducing selection of energy-dense snack foods. Furthermore, the underlying mechanisms have received little attention; particularly effects on implicit attitudes, which previous work has shown may mediate the effect of aversive images on food choice. AIM: To assess the impact of pairing image- and text-based HWLs with energy-dense snack foods on a) the selection of, and b) implicit and explicit attitudes towards, those foods. METHODS: Online experimental study with a representative UK sample (n = 1185), using a 2(Image/No Image) x 2(Text/No Text) factorial between-subjects design. Participants were randomised to one of four study arms, viewing snack food images paired with either: image-only HWLs, text-only HWLs, image-and-text HWLs, or no HWLs (control). HWLs concerned various negative health consequences of excess energy intake, such as heart disease and type 2 diabetes. The primary outcome was hypothetical food choice (energy-dense snack foods versus fruit), assessed post-intervention. Secondary outcomes were implicit and explicit attitudes. RESULTS: Neither food choice nor explicit attitudes were changed significantly by any type of HWL. Implicit attitudes towards energy-dense snack foods were more negative after exposure to text-only or image-and-text HWLs. Both implicit and explicit attitudes predicted unique variance in food choice. CONCLUSIONS: This study suggests that short-term repeated exposure to HWLs paired with energy-dense snack foods may not consistently alter food choices, but can change implicit attitudes associated with food choices. Further laboratory and field studies are needed to more definitively assess the impact of HWLs on food selection and consumption in applied contexts and over time, as well as delineate underlying mechanisms.

Impact of altering the available food options on selection: Potential mediation by social norms.

Increasing the availability of lower-energy foods increases their selection. The current studies examine the extent to which this effect could be mediated by social norms - assessed by perceived popularity of foods - which may be implied by their relative availability. Study 1 (Online): 2340 UK adults estimated the perceived popularity of products. Participants were randomised to see photos of cafeteria shelves varying in the availability of lower-energy options (1/4 lower-energy; 1/2 lower-energy; 3/4 lower-energy) and fullness of shelves (fuller; emptier). Study 2 (Laboratory): 139 English adults were asked to select a snack. Participants were randomised to select from trays varying in the availability of the lower-energy option (1/3 lower-energy; 2/3 lower-energy) and fullness of tray (fuller; emptier). In Study 1, evidence for an interaction was found, such that when shelves were fuller, a higher proportion of lower-energy options led to greater perceived popularity of lower-energy products (1/4 lower-energy: 40.9% (95%CIs: 40.1,41.8); 3/4 lower-energy: 47.2% (46.3,48.0)), whereas when shelves were emptier, a higher proportion of lower-energy options led to lower perceived popularity (1/4 lower-energy: 48.4% (47.5,49.2); 3/4 lower-energy: 39.2% (38.3,40.0)). In Study 2, when the tray was fuller, participants were more likely - albeit non-significantly - to select a lower-energy snack when 2/3 of the available snacks were lower-energy (35.7% (18.5,52.9)) than when 1/3 were lower-energy (15.4% (4.2,26.5)). For emptier trays, lower-energy selections decreased as the relative availability of lower-energy snacks increased (1/3 lower-energy snacks: 36.0% (17.9,54.1); 2/3 lower-energy snacks: 27.8% (13.9,41.7)). These studies provide novel evidence that social norms may mediate the impact of availability on food selection. In addition, they suggest that the effect of availability may be moderated by display layout through its impact on perceived product popularity.

Altering the availability of products within physical micro-environments: a conceptual framework.

Altering the availability of products (e.g. food, alcohol or tobacco products) is one potential intervention to change behaviours to help reduce preventable premature deaths worldwide. However, research on these interventions lacks consistent conceptualisation, hindering clear reporting and cumulative synthesis. This paper proposes a conceptual framework - categorising intervention types and summarising constituent components - with which interventions can be reliably described and evidence synthesised. Three principal distinctions are proposed: interventions altering: (i) Absolute Availability (changing the overall number of options, while keeping the proportions comprised by any subsets of options constant); (ii) Relative Availability (changing the proportion comprised by a subset of options, yet keeping the overall number of options constant); (iii) Absolute and Relative Availability (changing both the overall number of options and the proportions comprised by subsets of options). These are subdivided into those targeting (a) a product or (b) a category of products. Mechanisms that might underlie each of these intervention types are discussed, and implications for future research highlighted. The proposed framework aims to facilitate study of a set of interventions that could contribute significantly to healthier behaviour across populations.

The impact on selection of non-alcoholic vs alcoholic drink availability: an online experiment.

BACKGROUND: Increasing the availability of healthier food increases its selection and consumption. However, there is an absence of evidence related to alcohol. This study aimed to estimate the impact of increasing the absolute and relative availability of non-alcoholic compared to alcoholic drinks on selection. We also assessed whether effects were modified by cognitive resource. METHODS: UK adult weekly alcohol consumers (n = 808) were recruited to an online experiment with a hypothetical drink selection task. Participants were randomly assigned to one of eight conditions, in a 4 (availability) × 2 (cognitive resource) factorial design. The four availability conditions were: i. Reference 1 (two non-alcoholic, two alcoholic drinks); ii. Reference 2 (four non-alcoholic, four alcoholic drinks); iii. Increased non-alcoholic drinks (six non-alcoholic, two alcoholic drinks); iv. Increased alcoholic drinks (two non-alcoholic, six alcoholic drinks). The two cognitive resource conditions were: a. Low (high time pressure); b. High (low time pressure). Logistic regression was used to assess selection of a non-alcoholic drink. RESULTS: 49% of participants selected a non-alcoholic drink in the Increased non-alcoholic drinks condition, compared to 36% in Reference 1, 39% in Reference 2, and 26% in the Increased alcoholic drinks condition. Non-alcoholic drink selection was similar between Reference 1 and 2 when the total number of drinks increased (absolute availability) but the proportion of non-alcoholic compared to alcoholic drinks (relative availability) was unchanged (OR = 1.15, 95% CI 0.77, 1.73). In contrast, the odds of selecting a non-alcoholic drink were 71% higher when both absolute and relative availability of non-alcoholic compared to alcoholic drinks was increased from Reference 1 to the Increased non-alcoholic drinks condition (OR: 1.71, 95% CI 1.15, 2.54), and 48% higher when increased from Reference 2 to the Increased non-alcoholic drinks condition (OR: 1.48, 95% CI 0.99, 2.19). There was no evidence of an effect of cognitive resource. CONCLUSIONS: Greater availability of non-alcoholic drinks, compared to alcoholic drinks, increased their online selection, an effect that may be larger when changing their relative availability, i.e., increasing the proportion of non-alcoholic drinks. Naturalistic studies are needed to determine the impact of availability interventions on reducing alcohol purchasing and consumption.

Image-and-text health warning labels on alcohol and food: potential effectiveness and acceptability.

BACKGROUND: Health warning labels (HWLs) using images and text to depict the negative health consequences of tobacco consumption are effective and acceptable for changing smoking-related outcomes. There is currently limited evidence concerning their potential use for reducing consumption of alcoholic drinks and energy-dense foods. The aim of this research was to describe the potential effectiveness and acceptability of image-and-text (also known as pictorial or graphic) HWLs applied to: i. alcoholic drinks and ii. energy-dense snack foods. METHODS: Two online studies were conducted using between-subjects designs with general population samples. Participants rated one of 21 image-and-text HWLs on alcoholic drinks (n = 5528), or one of 18 image-and-text HWLs on energy-dense snacks (n = 4618). HWLs comprised a graphic image with explanatory text, depicting, respectively, seven diseases linked to excess alcohol consumption, and six diseases linked to excess energy intake. Diseases included heart disease and various cancers. Outcomes were negative emotional arousal, desire to consume the labelled product, and acceptability of the label. Free-text comments relating to HWLs were content analysed. RESULTS: For both alcoholic drinks and energy-dense snacks, HWLs depicting bowel cancer generated the highest levels of negative emotional arousal and lowest desire to consume the product, but were the least acceptable. Acceptability was generally low for HWLs applied to alcohol, with 3 of 21 rated as acceptable, and was generally high for snacks, with 13 of 18 rated as acceptable. The majority of free-text comments expressed negative reactions to HWLs on alcohol or energy-dense snacks. CONCLUSIONS: Image-and-text health warning labels depicting bowel cancer showed greatest potential for reducing selection and consumption of alcoholic drinks and energy-dense snacks, although they were the least acceptable. Laboratory and field studies are needed to assess their impact on selection and consumption.

The impact of 'on-pack' pictorial health warning labels and calorie information labels on drink choice: A laboratory experiment.

Sugar-sweetened beverages (SSBs) are one of the largest added sugar sources to diets in the UK and USA. Health warning labels reduce hypothetical selection of SSBs in online studies but uncertainty surrounds their impact on selection of drinks for consumption. Calorie information labels are also promising but their impact on SSB selection is unclear. This laboratory study assessed the impact on SSB selection of 'on-pack' labels placed directly on physical products: i.a pictorial health warning label depicting an adverse health consequence of excess sugar consumption; and ii.calorie information labels. Potential moderation of any effects by socio-economic position (SEP) was also examined. Participants - 401 adults, resident in England, approximately half of whom were of lower SEP and half of higher SEP, were asked to select a drink from a range of two non-SSBs and four SSBs (subsequent to completing a separate study assessing the effects of food availability on snack selection). The drinks included 'on-pack' labels according to randomisation: Group 1: pictorial health warning label on SSBs; Group 2: calorie information label on all drinks; Group 3: no additional label. The primary outcome was the proportion of participants selecting an SSB. Compared to not having additional labels (39%), neither the pictorial health warning label (40%) nor calorie information labels (43%) affected the proportion of participants selecting an SSB. Lower SEP participants (45%) were more likely to select an SSB compared to those of higher SEP (35%), but SEP did not moderate the impact of labels on drink selection. In conclusion, pictorial health warning labels may be less effective in reducing SSB selection in lab-based compared with online settings, or depending on label design and placement. Findings suggest that effects might be absent when choosing from real products with actual 'on-pack' labels, positioned in a 'realistic' manner. Field studies are needed to further assess the impact of 'on-pack' SSB warning labels in real-world settings to rule out the possible contribution of study design factors.

Impact of health warning labels on snack selection: An online experimental study.

Excessive consumption of energy-dense food increases the risk of obesity, which in turn increases the risk of non-communicable diseases, including heart disease, type 2 diabetes and most non-smoking-related cancers. Health warning labels (HWLs) that communicate the adverse health consequences of excess energy consumption could reduce intake of energy-dense foods. The aim of the current study was to estimate the impact on selection of energy-dense snacks of (a) image-and-text HWLs (b) text-only HWLs and (c) calorie information. In a between-subjects, 3 (HWL: image-and-text, text-only, no label) x 2 (calorie information: present, absent), factorial experimental design, participants (N = 4134) were randomised to view a selection of energy-dense and non-energy-dense snacks with one of five label types or no label. The primary outcome was the proportion of participants selecting an energy-dense snack in a hypothetical vending machine task. The proportion of participants selecting an energy-dense snack was reduced in all label groups, relative to the no label group (no label: 59%; calories only: 54%; text-only HWL: 48%; text-only HWL with calories: 44%; image-and-text HWL: 37%; image-and-text HWL with calories: 38%). Compared to the no label group, participants were least likely to select an energy-dense snack in the image-and-text HWL group (OR = 0.46, 95%CI = 0.40, 0.54, p < 0.001). Health warning labels - particularly those including an image and text - have the potential to reduce selection of energy-dense snacks in an online setting. Their impact on selection and consumption in real-world settings awaits testing.

Plate size and food consumption: a pre-registered experimental study in a general population sample.

BACKGROUND: There is considerable uncertainty regarding the impact of tableware size on food consumption. Most existing studies have used small and unrepresentative samples and have not followed recommended procedures for randomised controlled trials, leading to increased risk of bias. In the first pre-registered study to date, we examined the impact on consumption of using larger versus smaller plates for self-served food. We also assessed impact on the underlying meal micro-structure, such as number of servings and eating rate, which has not previously been studied. METHODS: The setting was a purpose-built naturalistic eating behaviour laboratory. A general population sample of 134 adult participants (aged 18-61 years) was randomly allocated to one of two groups varying in the size of plate used for self-serving lunch: large or small. The primary outcome was amount of food energy (kcal) consumed during a meal. Additionally, we assessed impact on meal micro-structure, and examined potential modifying effects of executive function, socio-economic position, and sensitivity to perceptual cues. RESULTS: There was no clear evidence of a difference in consumption between the two groups: Cohen's d = 0.07 (95% CI [- 0.27, 0.41]), with participants in the large plate group consuming on average 19.2 (95% CI [- 76.5, 115.0]) more calories (3%) compared to the small plate group (large: mean (SD) = 644.1 (265.0) kcal, versus small: 624.9 (292.3) kcal). The difference between the groups was not modified by individual characteristics. There was no evidence of impact on meal micro-structure, with the exception of more food being left on the plate when larger plates were used. CONCLUSIONS: This study suggests that previous meta-analyses of a low-quality body of evidence may have considerably overestimated the effects of plate size on consumption. However, the possibility of a clinically significant effect - in either direction - cannot be excluded. Well-conducted trials of tableware size in real-world field settings are now needed to determine whether changing the size of tableware has potential to contribute to efforts to reduce consumption at population-level. TRIAL REGISTRATION: The study protocol ( https://osf.io/e3dfh/ ) and data analysis plan ( https://osf.io/sh5u7/ ) were pre-registered on the Open Science Framework.

Interventions to increase adherence to medications for tobacco dependence.

BACKGROUND: Pharmacological treatments for tobacco dependence, such as nicotine replacement therapy (NRT), have been shown to be safe and effective interventions for smoking cessation. Higher levels of adherence to these medications increase the likelihood of sustained smoking cessation, but many smokers use them at a lower dose and for less time than is optimal. It is important to determine the effectiveness of interventions designed specifically to increase medication adherence. Such interventions may address motivation to use medication, such as influencing beliefs about the value of taking medications, or provide support to overcome problems with maintaining adherence. OBJECTIVES: To assess the effectiveness of interventions aiming to increase adherence to medications for smoking cessation on medication adherence and smoking abstinence compared with a control group typically receiving standard care. SEARCH METHODS: We searched the Cochrane Tobacco Addiction Group Specialized Register, and clinical trial registries (ClinicalTrials.gov and the WHO International Clinical Trials Registry Platform) to the 3 September 2018. We also conducted forward and backward citation searches. SELECTION CRITERIA: Randomised, cluster-randomised or quasi-randomised studies in which adults using active pharmacological treatment for smoking cessation were allocated to an intervention arm where there was a principal focus on increasing adherence to medications for tobacco dependence, or a control arm providing standard care. Dependent on setting, standard care may have comprised minimal support or varying degrees of behavioural support. Included studies used a measure that allowed assessment of the degree of medication adherence. DATA COLLECTION AND ANALYSIS: Two authors independently screened studies for eligibility, extracted data for included studies and assessed risk of bias. For continuous outcome measures, we calculated effect sizes as standardised mean differences (SMDs). For dichotomous outcome measures, we calculated effect sizes as risk ratios (RRs). In meta-analyses for adherence outcomes, we combined dichotomous and continuous data using the generic inverse variance method and reported pooled effect sizes as SMDs; for abstinence outcomes, we reported and pooled dichotomous outcomes. We obtained pooled effect sizes with 95% confidence intervals (CIs) using random-effects models. We conducted subgroup analyses to assess whether the primary focus of the adherence treatment ('practicalities' versus 'perceptions' versus both), the delivery approach (participant versus clinician-centred) or the medication type were associated with effectiveness. MAIN RESULTS: We identified two new studies, giving a total of 10 studies, involving 3655 participants. The medication adherence interventions studied were all provided in addition to standard behavioural support.They typically provided further information on the rationale for, and emphasised the importance of, adherence to medication or supported the development of strategies to overcome problems with maintaining adherence (or both). Seven studies targeted adherence to NRT, two to bupropion and one to varenicline. Most studies were judged to be at high or unclear risk of bias, with four of these studies judged at high risk of attrition or detection bias. Only one study was judged to be at low risk of bias.Meta-analysis of all 10 included studies (12 comparisons) provided moderate-certainty evidence that adherence interventions led to small improvements in adherence (i.e. the mean amount of medication consumed; SMD 0.10, 95% CI 0.03 to 0.18; I² = 6%; n = 3655), limited by risk of bias. Subgroup analyses for the primary outcome identified no significant subgroup effects, with effect sizes for subgroups imprecisely estimated. However, there was a very weak indication that interventions focused on the 'practicalities' of adhering to treatment (i.e. capabilities, resources, levels of support or skills) may be effective (SMD 0.21, 95% CI 0.03 to 0.38; I² = 39%; n = 1752), whereas interventions focused on treatment 'perceptions' (i.e. beliefs, cognitions, concerns and preferences; SMD 0.10, 95% CI -0.03 to 0.24; I² = 0%; n = 839) or on both (SMD 0.04, 95% CI -0.08 to 0.16; I² = 0%; n = 1064), may not be effective. Participant-centred interventions may be effective (SMD 0.12, 95% CI 0.02 to 0.23; I² = 20%; n = 2791), whereas those that are clinician-centred may not (SMD 0.09, 95% CI -0.05 to 0.23; I² = 0%; n = 864).Five studies assessed short-term smoking abstinence (five comparisons), while an overlapping set of five studies (seven comparisons) assessed long-term smoking abstinence of six months or more. Meta-analyses resulted in low-certainty evidence that adherence interventions may slightly increase short-term smoking cessation rates (RR 1.08, 95% CI 0.96 to 1.21; I² = 0%; n = 1795) and long-term smoking cessation rates (RR 1.16, 95% CI 0.96 to 1.40; I² = 48%; n = 3593). In both cases, the evidence was limited by risk of bias and imprecision, with CIs encompassing minimal harm as well as moderate benefit, and a high likelihood that further evidence will change the estimate of the effect. There was no evidence that interventions to increase adherence to medication led to any adverse events. Studies did not report on factors plausibly associated with increases in adherence, such as self-efficacy, understanding of and attitudes toward treatment, and motivation and intentions to quit. AUTHORS' CONCLUSIONS: In people who are stopping smoking and receiving behavioural support, there is moderate-certainty evidence that enhanced behavioural support focusing on adherence to smoking cessation medications can modestly improve adherence. There is only low-certainty evidence that this may slightly improve the likelihood of cessation in the shorter or longer-term. Interventions to increase adherence can aim to address the practicalities of taking medication, change perceptions about medication, such as reasons to take it or concerns about doing so, or both. However, there is currently insufficient evidence to confirm which approach is more effective. There is no evidence on whether such interventions are effective for people who are stopping smoking without standard behavioural support.