Applying machine-learning to rapidly analyze large qualitative text datasets to inform the COVID-19 pandemic response: comparing human and machine-assisted topic analysis techniques.

Introduction: Machine-assisted topic analysis (MATA) uses artificial intelligence methods to help qualitative researchers analyze large datasets. This is useful for researchers to rapidly update healthcare interventions during changing healthcare contexts, such as a pandemic. We examined the potential to support healthcare interventions by comparing MATA with "human-only" thematic analysis techniques on the same dataset (1,472 user responses from a COVID-19 behavioral intervention). Methods: In MATA, an unsupervised topic-modeling approach identified latent topics in the text, from which researchers identified broad themes. In human-only codebook analysis, researchers developed an initial codebook based on previous research that was applied to the dataset by the team, who met regularly to discuss and refine the codes. Formal triangulation using a "convergence coding matrix" compared findings between methods, categorizing them as "agreement", "complementary", "dissonant", or "silent". Results: Human analysis took much longer than MATA (147.5 vs. 40 h). Both methods identified key themes about what users found helpful and unhelpful. Formal triangulation showed both sets of findings were highly similar. The formal triangulation showed high similarity between the findings. All MATA codes were classified as in agreement or complementary to the human themes. When findings differed slightly, this was due to human researcher interpretations or nuance from human-only analysis. Discussion: Results produced by MATA were similar to human-only thematic analysis, with substantial time savings. For simple analyses that do not require an in-depth or subtle understanding of the data, MATA is a useful tool that can support qualitative researchers to interpret and analyze large datasets quickly. This approach can support intervention development and implementation, such as enabling rapid optimization during public health emergencies.

An approach for embedding behavioural science in antimicrobial resistance One Health research.

Antimicrobial Resistance (AMR) is a global health emergency that threatens modern medicine and incurs great cost to human health. The World Health Organization as part of a quadripartite joint initiative with the Food and Agriculture Organization of the United Nations, World Organisation for Animal Health, and United Nations Environment Programme, has recently published a One Health Priority Research Agenda for AMR. In this article we present a multidisciplinary approach, proposed by behavioural science experts, One Health experts and AMR experts to support the implementation of the Priority Research Agenda. We review, using specific examples of complex interventions designed to tackle AMR in which behavioural science has been embedded, five main steps: Define - what behaviours are a priority in each context; Diagnose - What are the barriers and enablers to the behaviours prioritised? Design - what interventions exist and what new or enhanced interventions could work to tackle the barriers identified? and, Implement and Evaluate the intervention(s). The approach presented will be useful for funders and researchers who wish to incorporate methods, frameworks and insights from the behavioural sciences into research plans, proposals and protocols in relation to a multisectoral One Health agenda and produce findings that are more relevant to policymakers.

Can uptake of childhood influenza immunisation through schools and GP practices be increased through behaviourally-informed invitation letters and reminders: two pragmatic randomized controlled trials.

BACKGROUND: The UK is rolling out a national childhood influenza immunisation programme for children, delivered through primary care and schools. Behaviourally-informed letters and reminders have been successful at increasing uptake of other public health interventions. Therefore, we investigated the effects of a behaviourally-informed letter on uptake of the vaccine at GP practices, and of a letter and a reminder (SMS/ email) on uptake at schools. METHODS AND RESULTS: Study 1 was a cluster-randomised parallel trial of 21,786 two- and three-year olds in 250 GP practices, conducted during flu season (September to January inclusive) 2016/7. The intervention was a centrally-sent behaviourally-informed invitation letter, control was usual care. The proportion of two- and three-year olds in each practice who received a vaccination by 31st January 2017 was 23.4% in the control group compared to 37.1% in the intervention group (OR = 1.93; 95% CI = 1.82, 2.05, p <  0.001). Study 2 was a 2 (behavioural letter vs standard letter) × 2 (reminder vs no reminder) factorial trial of 1108 primary schools which included 3010 school years 1-3. Letters were sent to parents from providers, and reminders sent to parents from the schools. In the standard-letter-no-reminder arm, an average of 61.6% of eligible children in each school year were vaccinated, compared to 61.9% in the behavioural-letter-no-reminder arm, 63.5% in the standard-letter-plus-reminder arm, and 62.9% in the behavioural-letter-plus reminder condition, F(3, 2990) = 2.68, p = 0.046. In a multi-level model, with demographic variables as fixed effects, the proportion of eligible students in the school year who were vaccinated increased with the reminder, ß = 0.086 (0.041), p <  0.036, but there was no effect of the letter nor any interaction effect. CONCLUSION: Sending a behaviourally informed invitation letter can increase uptake of childhood influenza vaccines at the GP surgery compared to usual practice. A reminder SMS or email can increase uptake of the influenza vaccine in schools, but the effect size was minimal. TRIAL REGISTRATION: Study 1: Trial registration: ClinicalTrials.gov Identifier: NCT02921633. Study 2: Trial registration: ClinicalTrials.gov Identifier: NCT02883972.

Encouraging healthier grocery purchases online: A randomised controlled trial and lessons learned.

Online supermarket platforms present an opportunity for encouraging healthier consumer purchases. A parallel, double-blind randomised controlled trial tested whether promoting healthier products (e.g. lower fat and lower calorie) on the Sainsbury's online supermarket platform would increase purchases of those products. Participants were Nectar loyalty membership scheme cardholders who shopped online with Sainsbury's between 20th September and 10th October 2017. Intervention arm customers saw advertisement banners and recipe ingredient lists containing healthier versions of the products presented in control arm banners and ingredient lists. The primary outcome measure was purchases of healthier products. Additional outcome measures were banner clicks, purchases of standard products, overall purchases and energy (kcal) purchased. Sample sizes were small due to customers navigating the website differently than expected. The intervention encouraged purchases of some promoted healthier products (spaghetti [B = 2.10, p < 0.001], spaghetti sauce [B = 2.06, p < 0.001], spaghetti cheese [B = 2.45, p = 0.001], sour cream [B = 2.52, p < 0.001], fajita wraps [B = 2.10, p < 0.001], fajita cheese [B = 1.19, p < 0.001], bakery aisle products (B = 3.05, p = 0.003) and cola aisle products [B = 0.97, p < 0.002]) but not others (spaghetti mince, or products in the yogurt and ice cream aisles). There was little evidence of effects on banner clicks and energy purchased. Small sample sizes may affect the robustness of these findings. We discuss the benefits of collaborating to share expertise and implement a trial in a live commercial environment, alongside key learnings for future collaborative research in similar contexts.

Using text and charts to provide social norm feedback to general practices with high overall and high broad-spectrum antibiotic prescribing: a series of national randomised controlled trials.

BACKGROUND: Sending a social norms feedback letter to general practitioners who are high prescribers of antibiotics has been shown to reduce antibiotic prescribing. The 2017-9 Quality Premium for primary care in England sets a target for broad-spectrum prescribing, which should be at or below 10% of total antibiotic prescribing. We tested a social norm feedback letter that targeted broad-spectrum prescribing and the addition of a chart to a text-only letter that targeted overall prescribing. METHODS: We conducted three 2-armed randomised controlled trials, on different groups of practices: Trial A compared a broad-spectrum message and chart to the standard-practice overall prescribing letter (practices whose percentage of broad-spectrum prescribing was above 10% and who had relatively high overall prescribing). Trial C compared a broad-spectrum message and a chart to a no-letter control (practices whose percentage of broad-spectrum prescribing was above 10% and who had relatively moderate overall prescribing). Trial B compared an overall-prescribing message with a chart to the standard practice overall letter (practices whose percentage of broad-spectrum prescribing was below 10% but who had relatively high overall prescribing). Letters were posted to general practitioners, timed to be received on 1 November 2018. The primary outcomes were practices' percentage of broad-spectrum prescribing (trials A and C) and overall antibiotic prescribing (trial B) each month from November 2018 to April 2019 (all weighted by the number and characteristics of patients registered in the practice). RESULTS: We randomly assigned 1909 practices; 58 closed or merged during the trial, leaving 1851 practices: 385 in trial A, 674 in trial C, and 792 in trial B. AR(1) models showed that there were no statistically significant differences in our primary outcome measures: trial A ß = - .199, p = .13; trial C ß = .006, p = .95; trial B ß = - .0021, p = .81. In all three trials, there were statistically significant time trends, showing that overall antibiotic prescribing and total broad-spectrum prescribing were decreasing. CONCLUSION: Our broad-spectrum feedback letters had no effect on broad-spectrum prescribing; adding a bar chart to a text-only letter had no effect on overall antibiotic prescribing. Broad-spectrum and overall prescribing were both decreasing over time. TRIAL REGISTRATION: ClinicalTrials.gov NCT03862794. March 5, 2019.

Comparing antibiotic prescribing between clinicians in UK primary care: an analysis in a cohort study of eight different measures of antibiotic prescribing.

BACKGROUND: There is a need to reduce antimicrobial uses in humans. Previous studies have found variations in antibiotic (AB) prescribing between practices in primary care. This study assessed variability of AB prescribing between clinicians. METHODS: Clinical Practice Research Datalink, which collects electronic health records in primary care, was used to select anonymised clinicians providing 500+ consultations during 2012-2017. Eight measures of AB prescribing were assessed, such as overall and incidental AB prescribing, repeat AB courses and extent of risk-based prescribing. Poisson regression models with random effect for clinicians were fitted. RESULTS: 6111 clinicians from 466 general practices were included. Considerable variability between individual clinicians was found for most AB measures. For example, the rate of AB prescribing varied between 77.4 and 350.3 per 1000 consultations; percentage of repeat AB courses within 30 days ranged from 13.1% to 34.3%; predicted patient risk of hospital admission for infection-related complications in those prescribed AB ranged from 0.03% to 0.32% (5th and 95th percentiles). The adjusted relative rate between clinicians in rates of AB prescribing was 5.23. Weak correlation coefficients (<0.5) were found between most AB measures. There was considerable variability in case mix seen by clinicians. The largest potential impact to reduce AB prescribing could be around encouraging risk-based prescribing and addressing repeat issues of ABs. Reduction of repeat AB courses to prescribing habit of median clinician would save 21 813 AB prescriptions per 1000 clinicians per year. CONCLUSIONS: The wide variation seen in all measures of AB prescribing and weak correlation between them suggests that a single AB measure, such as prescribing rate, is not sufficient to underpin the optimisation of AB prescribing.

Location, location, location: a discrete choice experiment to inform COVID-19 vaccination programme delivery in the UK.

BACKGROUND: Large-scale vaccination is fundamental to combatting COVID-19. In March 2021, the UK's vaccination programme had delivered vaccines to large proportions of older and more vulnerable population groups; however, there was concern that uptake would be lower among young people. This research was designed to elicit the preferences of 18-29-year-olds regarding key delivery characteristics and assess the influence of these on intentions to get vaccinated, to inform planning for this cohort. METHODS: From 25 March to 2 April 2021, an online sample of 2012 UK adults aged 18-29 years participated in a Discrete Choice Experiment. Participants made six choices, each involving two SMS invitations to book a vaccination appointment and an opt-out. Invitations had four attributes (1 × 5 levels, 3 × 3 levels): delivery mode, appointment timing, proximity, and sender. These were systematically varied according to a d-optimal design. Responses were analysed using a mixed logit model. RESULTS: The main effects logit model revealed a large alternative-specific constant (ß = 1.385, SE = 0.067, p < 0.001), indicating a strong preference for 'opting in' to appointment invitations. Pharmacies were dispreferred to the local vaccination centre (ß = - 0.256, SE = 0.072, p < 0.001), appointments in locations that were 30-45 min travel time from one's premises were dispreferred to locations that were less than 15 min away (ß = - 0.408, SE = 0.054, p < 0.001), and, compared to invitations from the NHS, SMSs forwarded by 'a friend' were dispreferred (ß = - 0.615, SE = 0.056, p < 0.001) but invitations from the General Practitioner were preferred (ß = 0.105, SE = 0.048, p = 0.028). CONCLUSIONS: The results indicated that the existing configuration of the UK's vaccination programme was well-placed to deliver vaccines to 18-29-year-olds; however, some adjustments might enhance acceptance. Local pharmacies were not preferred; long travel times were a disincentive but close proximity (0-15 min from one's premises) was not necessary; and either the 'NHS' or 'Your GP' would serve as adequate invitation sources. This research informed COVID-19 policy in the UK, and contributes to a wider body of Discrete Choice Experiment evidence on citizens' preferences, requirements and predicted behaviours regarding COVID-19.

A Systematic Review of Nudge Interventions to Optimize Medication Prescribing.

Background: The benefits of medication optimization are largely uncontroversial but difficult to achieve. Behavior change interventions aiming to optimize prescriber medication-related decisions, which do not forbid any option and that do not significantly change financial incentives, offer a promising way forward. These interventions are often referred to as nudges. Objective: The current systematic literature review characterizes published studies describing nudge interventions to optimize medication prescribing by the behavioral determinants they intend to influence and the techniques they apply. Methods: Four databases were searched (MEDLINE, Embase, PsychINFO, and CINAHL) to identify studies with nudge-type interventions aiming to optimize prescribing decisions. To describe the behavioral determinants that interventionists aimed to influence, data were extracted according to the Theoretical Domains Framework (TDF). To describe intervention techniques applied, data were extracted according to the Behavior Change Techniques (BCT) Taxonomy version 1 and MINDSPACE. Next, the recommended TDF-BCT mappings were used to appraise whether each intervention applied a sufficient array of techniques to influence all identified behavioral determinants. Results: The current review located 15 studies comprised of 20 interventions. Of the 20 interventions, 16 interventions (80%) were effective. The behavior change techniques most often applied involved prompts (n = 13). The MINDSPACE contextual influencer most often applied involved defaults (n = 10). According to the recommended TDF-BCT mappings, only two interventions applied a sufficient array of behavior change techniques to address the behavioral determinants the interventionists aimed to influence. Conclusion: The fact that so many interventions successfully changed prescriber behavior encourages the development of future behavior change interventions to optimize prescribing without mandates or financial incentives. The current review encourages interventionists to understand the behavioral determinants they are trying to affect, before the selection and application of techniques to change prescribing behaviors. Systematic Review Registration: [https://www.crd.york.ac.uk/prospero/], identifier [CRD42020168006].

Interventions to change purchasing behaviour in supermarkets: a systematic review and intervention content analysis.

This systematic review and intervention content analysis used behavioural science frameworks to characterise content and function of interventions targeting supermarket shoppers' purchasing behaviour, and explore if coherence between content and function was linked to intervention effectiveness. Study eligibility: in-store interventions (physical supermarkets) with control conditions, targeting objectively measured food and/or non-alcoholic drink purchases, published in English (no date restrictions). Eleven electronic databases were searched; reference lists of systematic reviews were hand-searched. Methodological quality was assessed using the GATE checklist. A content analysis was performed to characterise intervention content and function, and theoretical coherence between these, using the Behaviour Change Wheel, Behaviour Change Techniques Taxonomy, and Typology of Interventions in Proximal Physical Micro-Environments (TIPPME). Forty-six articles (49 interventions) met inclusion criteria; 26 articles (32 interventions) were included in the content analysis. Twenty behaviour change techniques (BCTs), and four TIPPME intervention types were identified; three BCTs ('Prompts/cues', 'Material incentive', and 'Material reward') were more common in effective interventions. Nineteen interventions solely employed theoretically appropriate BCTs. Theoretical coherence between BCTs and intervention functions was more common in effective interventions. Effective interventions included price promotions and/or in-store merchandising. Future research should explore the effect of specific BCTs using factorial study designs. PROSPERO Registration: CRD42017071065.

Perceived risk factors for severe Covid-19 symptoms and their association with health behaviours: Findings from the HEBECO study.

Risk perceptions are important influences on health behaviours. We used descriptive statistics and multivariable logistic regression models to assess cross-sectionally risk perceptions for severe Covid-19 symptoms and their health behaviour correlates among 2206 UK adults from the HEBECO study. The great majority (89-99%) classified age 70+, having comorbidities, being a key worker, overweight, and from an ethnic minority as increasing the risk. People were less sure about alcohol drinking, vaping, and nicotine replacement therapy use (17.4-29.5% responding 'don't know'). Relative to those who did not, those who engaged in the following behaviours had higher odds of classifying these behaviours as (i) decreasing the risk: smoking cigarettes (adjusted odds ratios, aORs, 95% CI = 2.26, 1.39-3.37), and using e-cigarettes (aORs = 5.80, 3.25-10.34); (ii) having no impact: smoking cigarettes (1.98; 1.42-2.76), using e-cigarettes (aORs = 2.63, 1.96-3.50), drinking alcohol (aORs = 1.75, 1.31-2.33); and lower odds of classifying these as increasing the risk: smoking cigarettes (aORs: 0.43, 0.32-0.56), using e-cigarettes (aORs = 0.25, 0.18-0.35). Similarly, eating more fruit and vegetables was associated with classifying unhealthy diet as 'increasing risk' (aOR = 1.37, 1.12-1.69), and exercising more with classifying regular physical activity as 'decreasing risk' (aOR = 2.42, 1.75-3.34). Risk perceptions for severe Covid-19 among UK adults were lower for their own health behaviours, evidencing optimism bias. These risk perceptions may form barriers to changing people's own unhealthy behaviours, make them less responsive to interventions that refer to the risk of Covid-19 as a motivating factor, and exacerbate inequalities in health behaviours and outcomes.

Optimizing Making Every Contact Count (MECC) interventions: A strategic behavioral analysis.

OBJECTIVE: This Strategic Behavioral Analysis aimed to: identify barriers and facilitators to health care professionals' implementation of Making Every Contact Count (MECC); code behavioral components of nationally delivered interventions to improve MECC implementation; assess the extent to which these components are theoretically congruent with identified theoretical domains representing barriers and facilitators. Comparing national interventions that aim to support implementation of behavior change related activity to the barriers and facilitators for the target behavior enables identification of opportunities being missed in practice; thereby, facilitating intervention optimization. METHOD: A mixed-method study involving: a systematic review to identify barriers and facilitators to implementing MECC classified using the COM-B model and Theoretical Domains Framework (TDF); a content analysis of national interventions to improve MECC implementation in England using the Behavior Change Wheel (BCW) and Behavior Change Techniques Taxonomy (BCTTv1); linking intervention content to barriers identified in the systematic review. RESULTS: Across 27 studies, the most frequently reported barriers related to eight TDF domains: Environmental Context and Resources, Beliefs About Capabilities, Knowledge, Beliefs About Consequences, Intentions, Skills, Social Professional Role and Identity, and Emotions. National interventions aimed at supporting MECC implementation included on average 5.1 BCW intervention functions (Education, Modeling, Persuasion, and Training were used in all interventions) and 8.7 BCTs. Only 21% of BCTs potentially relevant to key domains were used across interventions. The majority of BCTs linked to seven of the eight most important domains were not used in any existing interventions. CONCLUSIONS: Intervention developers should seize missed opportunities by incorporating more theoretically relevant BCTs to target barriers to implementing MECC. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

Perceptions of Factors Influencing Engagement With Health and Well-being Apps in the United Kingdom: Qualitative Interview Study.

BACKGROUND: Digital health devices, such as health and well-being smartphone apps, could offer an accessible and cost-effective way to deliver health and well-being interventions. A key component of the effectiveness of health and well-being apps is user engagement. However, engagement with health and well-being apps is typically poor. Previous studies have identified a list of factors that could influence engagement; however, most of these studies were conducted on a particular population or for an app targeting a particular behavior. An understanding of the factors that influence engagement with a wide range of health and well-being apps can inform the design and the development of more engaging apps in general. OBJECTIVE: The aim of this study is to explore user experiences of and reasons for engaging and not engaging with a wide range of health and well-being apps. METHODS: A sample of adults in the United Kingdom (N=17) interested in using a health or well-being app participated in a semistructured interview to explore experiences of engaging and not engaging with these apps. Participants were recruited via social media platforms. Data were analyzed with the framework approach, informed by the Capability, Opportunity, Motivation-Behaviour (COM-B) model and the Theoretical Domains Framework, which are 2 widely used frameworks that incorporate a comprehensive set of behavioral influences. RESULTS: Factors that influence the capability of participants included available user guidance, statistical and health information, reduced cognitive load, well-designed reminders, self-monitoring features, features that help establish a routine, features that offer a safety net, and stepping-stone app characteristics. Tailoring, peer support, and embedded professional support were identified as important factors that enhance user opportunities for engagement with health and well-being apps. Feedback, rewards, encouragement, goal setting, action planning, self-confidence, and commitment were judged to be the motivation factors that affect engagement with health and well-being apps. CONCLUSIONS: Multiple factors were identified across all components of the COM-B model that may be valuable for the development of more engaging health and well-being apps. Engagement appears to be influenced primarily by features that provide user guidance, promote minimal cognitive load, support self-monitoring (capability), provide embedded social support (opportunity), and provide goal setting with action planning (motivation). This research provides recommendations for policy makers, industry, health care providers, and app developers for increasing effective engagement.

Effectiveness of digital interventions to improve household and community infection prevention and control behaviours and to reduce incidence of respiratory and/or gastro-intestinal infections: a rapid systematic review.

BACKGROUND: Digital interventions have potential to efficiently support improved hygiene practices to reduce transmission of COVID-19. OBJECTIVE: To evaluate the evidence for digital interventions to improve hygiene practices within the community. METHODS: We reviewed articles published between 01 January 2000 and 26 May 2019 that presented a controlled trial of a digital intervention to improve hygiene behaviours in the community. We searched MEDLINE, Embase, PsycINFO, Cochrane Controlled Register of Trials (CENTRAL), China National Knowledge Infrastructure and grey literature. Trials in hospitals were excluded, as were trials aiming at prevention of sexually transmitted infections; only target diseases with transmission mechanisms similar to COVID-19 (e.g. respiratory and gastrointestinal infections) were included. Trials had to evaluate a uniquely digital component of an intervention. Study designs were limited to randomised controlled trials, controlled before-and-after trials, and interrupted time series analyses. Outcomes could be either incidence of infections or change in hygiene behaviours. The Risk of Bias 2 tool was used to assess study quality. RESULTS: We found seven studies that met the inclusion criteria. Six studies reported successfully improving self-reported hygiene behaviour or health outcomes, but only one of these six trials, Germ Defence, confirmed improvements using objective measures (reduced consultations and antibiotic prescriptions). Settings included kindergartens, workplaces, and service station restrooms. Modes of delivery were diverse: WeChat, website, text messages, audio messages to mobiles, electronic billboards, and electronic personal care records. Four interventions targeted parents of young children with educational materials. Two targeted the general population; these also used behaviour change techniques or theory to inform the intervention. Only one trial had low risk of bias, Germ Defence; the most common concerns were lack of information about the randomisation, possible bias in reporting of behavioural outcomes, and lack of an analysis plan and possible selective reporting of results. CONCLUSION: There was only one trial that was judged to be at low risk of bias, Germ Defence, which reduced incidence and severity of illness, as confirmed by objective measures. Further evaluation is required to determine the effectiveness of the other interventions reviewed. TRIAL REGISTRATION: PROSPERO CRD42020189919 .

Increasing uptake of NHS Health Checks: a randomised controlled trial using GP computer prompts.

BACKGROUND: Public Health England wants to increase the uptake of the NHS Health Check (NHSHC), a cardiovascular disease prevention programme. Most invitations are sent by letter, but opportunistic invitations may be issued and verbal invitations have a higher rate of uptake. Prompting staff to issue opportunistic invitations might increase uptake. AIM: To assess the effect on uptake of automated prompts to clinical staff to invite patients to NHSHC, delivered via primary care computer systems. DESIGN AND SETTING: Pseudo-randomised controlled trial of patients eligible for the NHSHC attending GP practices in Southwark, London. METHOD: Eligible patients were allocated into one of two conditions, (a) Prompt and (b) No Prompt, to clinical staff. The primary outcome was attendance at an NHSHC. RESULTS: Fifteen of 43 (34.88%) practices in Southwark were recruited; 7564 patients were eligible for an NHSHC, 3778 (49.95%) in the control and 3786 (50.05%) in the intervention. Attendance in the intervention arm was 454 (12.09%) compared with 280 (7.41%) in the control group, a total increase of 4.58% (OR = 2.28; 95% CI = 1.46 to 3.55; P<0.001). Regressions found an interaction between intervention and sex (OR = 0.65; 95% CI = 0.44 to 0.86, P = 0.004), with the intervention primarily effective on males. Comparing the probabilities of attendance for each age category across intervention and control suggests that the intervention was primarily effective for younger patients. CONCLUSION: Prompts on computer systems in general practice were effective at improving the uptake of the NHSHC, especially for males and younger patients.

Adapting Behavioral Interventions for a Changing Public Health Context: A Worked Example of Implementing a Digital Intervention During a Global Pandemic Using Rapid Optimisation Methods.

Background: A rigorous approach is needed to inform rapid adaptation and optimisation of behavioral interventions in evolving public health contexts, such as the Covid-19 pandemic. This helps ensure that interventions are relevant, persuasive, and feasible while remaining evidence-based. This paper provides a set of iterative methods to rapidly adapt and optimize an intervention during implementation. These methods are demonstrated through the example of optimizing an effective online handwashing intervention called Germ Defense. Methods: Three revised versions of the intervention were rapidly optimized and launched within short timeframes of 1-2 months. Optimisations were informed by: regular stakeholder engagement; emerging scientific evidence, and changing government guidance; rapid qualitative research (telephone think-aloud interviews and open-text surveys), and analyses of usage data. All feedback was rapidly collated, using the Table of Changes method from the Person-Based Approach to prioritize potential optimisations in terms of their likely impact on behavior change. Written feedback from stakeholders on each new iteration of the intervention also informed specific optimisations of the content. Results: Working closely with clinical stakeholders ensured that the intervention was clinically accurate, for example, confirming that information about transmission and exposure was consistent with evidence. Patient and Public Involvement (PPI) contributors identified important clarifications to intervention content, such as whether Covid-19 can be transmitted via air as well as surfaces, and ensured that information about difficult behaviors (such as self-isolation) was supportive and feasible. Iterative updates were made in line with emerging evidence, including changes to the information about face-coverings and opening windows. Qualitative research provided insights into barriers to engaging with the intervention and target behaviors, with open-text surveys providing a useful supplement to detailed think-aloud interviews. Usage data helped identify common points of disengagement, which guided decisions about optimisations. The Table of Changes was modified to facilitate rapid collation and prioritization of multiple sources of feedback to inform optimisations. Engagement with PPI informed the optimisation process. Conclusions: Rapid optimisation methods of this kind may in future be used to help improve the speed and efficiency of adaptation, optimization, and implementation of interventions, in line with calls for more rapid, pragmatic health research methods.

Effectiveness of Digital Interventions for Reducing Behavioral Risks of Cardiovascular Disease in Nonclinical Adult Populations: Systematic Review of Reviews.

BACKGROUND: Digital health interventions are increasingly being used as a supplement or replacement for face-to-face services as a part of predictive prevention. They may be offered to those who are at high risk of cardiovascular disease and need to improve their diet, increase physical activity, stop smoking, or reduce alcohol consumption. Despite the popularity of these interventions, there is no overall summary and comparison of the effectiveness of different modes of delivery of a digital intervention to inform policy. OBJECTIVE: This review aims to summarize the effectiveness of digital interventions in improving behavioral and health outcomes related to physical activity, smoking, alcohol consumption, or diet in nonclinical adult populations and to identify the effectiveness of different modes of delivery of digital interventions. METHODS: We reviewed articles published in the English language between January 1, 2009, and February 25, 2019, that presented a systematic review with a narrative synthesis or meta-analysis of any study design examining digital intervention effectiveness; data related to adults (≥18 years) in high-income countries; and data on behavioral or health outcomes related to diet, physical activity, smoking, or alcohol, alone or in any combination. Any time frame or comparator was considered eligible. We searched MEDLINE, Embase, PsycINFO, Cochrane Reviews, and gray literature. The AMSTAR-2 tool was used to assess review confidence ratings. RESULTS: We found 92 reviews from the academic literature (47 with meta-analyses) and 2 gray literature items (1 with a meta-analysis). Digital interventions were typically more effective than no intervention, but the effect sizes were small. Evidence on the effectiveness of digital interventions compared with face-to-face interventions was mixed. Most trials reported that intent-to-treat analysis and attrition rates were often high. Studies with long follow-up periods were scarce. However, we found that digital interventions may be effective for up to 6 months after the end of the intervention but that the effects dissipated by 12 months. There were small positive effects of digital interventions on smoking cessation and alcohol reduction; possible effectiveness in combined diet and physical activity interventions; no effectiveness for interventions targeting physical activity alone, except for when interventions were delivered by mobile phone, which had medium-sized effects; and no effectiveness observed for interventions targeting diet alone. Mobile interventions were particularly effective. Internet-based interventions were generally effective. CONCLUSIONS: Digital interventions have small positive effects on smoking, alcohol consumption, and in interventions that target a combination of diet and physical activity. Small effects may have been due to the low efficacy of treatment or due to nonadherence. In addition, our ability to make inferences from the literature we reviewed was limited as those interventions were heterogeneous, many reviews had critically low AMSTAR-2 ratings, analysis was typically intent-to-treat, and follow-up times were relatively short. TRIAL REGISTRATION: PROSPERO International Prospective Register of Systematic Reviews CRD42019126074; https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=126074.

Influences on the Uptake of Health and Well-being Apps and Curated App Portals: Think-Aloud and Interview Study.

BACKGROUND: Health and well-being smartphone apps can provide a cost-effective solution to addressing unhealthy behaviors. The selection of these apps tends to occur in commercial app stores, where thousands of health apps are available. Their uptake is often influenced by popularity indicators. However, these indicators are not necessarily associated with app effectiveness or evidence-based content. Alternative routes to app selection are increasingly available, such as via curated app portals, but little is known about people's experiences of them. OBJECTIVE: The aim of this study is to explore how people select health apps on the internet and their views on curated app portals. METHODS: A total of 18 UK-based adults were recruited through social media and asked during an in-person meeting to verbalize their thoughts while searching for a health or well-being app on the internet on a platform of their choice. The search was then repeated on 2 curated health app portals: the National Health Service Apps Library and the Public Health England One You App portal. This was followed by semistructured interviews. Data were analyzed using framework analysis, informed by the Capability, Opportunity, Motivation-Behavior model and the Theoretical Domains Framework. RESULTS: Searching for health and well-being apps on the internet was described as a minefield. App uptake appeared to be influenced by participants' capabilities such as app literacy skills and health and app awareness, and opportunities including the availability of apps, app esthetics, the price of an app, and social influences. Motivation factors that seemed to affect the uptake were perceived competence, time efficiency, perceived utility and accuracy of an app, transparency about data protection, commitment and social identity, and a wide range of emotions. Social influences and the perceived utility of an app were highlighted as particularly important. Participants were not previously aware of curated portals but found the concept appealing. Curated health app portals appeared to engender trust and alleviate data protection concerns. Although apps listed on these were perceived as more trustworthy, their presentation was considered disappointing. This disappointment seemed to stem from the functionality of the portals, lack of user guidance, and lack of tailored content to an individual's needs. CONCLUSIONS: The uptake of health and well-being apps appears to be primarily affected by social influences and the perceived utility of an app. App uptake via curated health app portals perceived as credible may mitigate concerns related to data protection and accuracy, but their implementation must better meet user needs and expectations.

Improving Our Understanding and Practice of Antibiotic Prescribing: A Study on the Use of Social Norms Feedback Letters in Primary Care.

In the UK, 81% of all antibiotics are prescribed in primary care. Previous research has shown that a letter from the Chief Medical Officer (CMO) giving social norms feedback to General Practitioners (GPs) whose practices are high prescribers of antibiotics can decrease antibiotic prescribing. The aim of this study was to understand the best way for engaging with GPs to deliver feedback on prescribing behaviour that could be replicated at scale; and explore GP information requirements that would be needed to support prescribing behaviour change. Two workshops were devised utilising a participatory approach. Discussion points were noted and agreed with each group of participants. Minutes of the workshops and observation notes were taken. Data were analysed thematically. Four key themes emerged through the data analysis: (1) Our day-to-day reality, (2) GPs are competitive, (3) Face-to-face support, and (4) Empowerment and engagement. Our findings suggest there is potential for using behavioural science in the form of social norms as part of a range of engagement strategies in reducing antibiotic prescribing within primary care. This should include tailored and localised data with peer-to-peer comparisons.

A randomised experiment of health, cost and social norm message frames to encourage acceptance of swaps in a simulation online supermarket.

Offering lower-energy food swaps to customers of online supermarkets could help to decrease energy (kcal) purchased and consumed. However, acceptance rates of such food swaps tend to be low. This study aimed to see whether framing lower-energy food swaps in terms of cost savings or social norms could improve likelihood of acceptance relative to framing swaps in terms of health benefits. Participants (n = 900) were asked to shop from a 12-item shopping list in a simulation online supermarket. When a target high-energy food was identified in the shopping basket at check-out, one or two lower-energy foods would be suggested as an alternative (a "swap"). Participants were randomised to only see messages emphasising health benefits (fewer calories), cost benefits (lower price) or social norms (others preferred this product). Data were analysed for 713 participants after exclusions. Participants were offered a mean of 3.17 swaps (SD = 1.50), and 12.91% of swaps were accepted (health = 14.31%, cost = 11.49%, social norms = 13.18%). Swap acceptance was not influenced by the specific swap frame used (all p > .170). Age was significantly and positively associated with swap acceptance (b = 0.02, SE = 0.00, p < .001), but was also associated with smaller decreases in energy change (b = 0.46, SE = .19, p = .014). Overall, offering swaps reduced both energy (kcal) per product (b = -9.69, SE = 4.07, p = .017) and energy (kcal) per shopping basket (t712 = 11.09, p < .001) from pre- to post-intervention. Offering lower-energy food swaps could be a successful strategy for reducing energy purchased by customers of online supermarkets. Future research should explore alternative solutions for increasing acceptance rates of such swaps.

Infection Control Behavior at Home During the COVID-19 Pandemic: Observational Study of a Web-Based Behavioral Intervention (Germ Defence).

BACKGROUND: To control the COVID-19 pandemic, people should adopt protective behaviors at home (self-isolation, social distancing, putting shopping and packages aside, wearing face coverings, cleaning and disinfecting, and handwashing). There is currently limited support to help individuals conduct these behaviors. OBJECTIVE: This study aims to report current household infection control behaviors in the United Kingdom and examine how they might be improved. METHODS: This was a pragmatic cross-sectional observational study of anonymous participant data from Germ Defence between May 6-24, 2020. Germ Defence is an open-access fully automated website providing behavioral advice for infection control within households. A total of 28,285 users sought advice from four website pathways based on household status (advice to protect themselves generally, to protect others if the user was showing symptoms, to protect themselves if household members were showing symptoms, and to protect a household member who is at high risk). Users reported current infection control behaviors within the home and intentions to change these behaviors. RESULTS: Current behaviors varied across all infection control measures but were between sometimes (face covering: mean 1.61, SD 1.19; social distancing: mean 2.40, SD 1.22; isolating: mean 2.78, SD 1.29; putting packages and shopping aside: mean 2.75, SD 1.55) and quite often (cleaning and disinfecting: mean 3.17, SD 1.18), except for handwashing (very often: mean 4.00, SD 1.03). Behaviors were similar regardless of the website pathway used. After using Germ Defence, users recorded intentions to improve infection control behavior across all website pathways and for all behaviors (overall average infection control score mean difference 0.30, 95% CI 0.29-0.31). CONCLUSIONS: Self-reported infection control behaviors other than handwashing are lower than is optimal for infection prevention, although handwashing is much higher. Advice using behavior change techniques in Germ Defence led to intentions to improve these behaviors. Promoting Germ Defence within national and local public health and primary care guidance could reduce COVID-19 transmission.