Providing telemedicine services to persons living with HIV in an urban community: a demonstration project.

Although HIV incidence and mortality rates have declined over the past 20 years, HIV health disparities continue to persist among patients living in urban communities. Barriers to proficient health outcomes for persons with HIV (PWH) in urban communities include lack of access to care, resulting from limited transportation or clinic availability. While healthcare systems in rural communities provide telemedicine (TM) services to PWH to eliminate transportation and accessibility barriers, few examples exist regarding TM use for PWH in urban communities. This project's goal was to increase the provision of healthcare services in an urban setting to PWH, using TM. As guided by "Integration of Healthcare Delivery Service" theories and key principles, we created an integration framework comprised of several simultaneous, overlapping activities to include: (1) capacity building (2) clinical standardization (3) community and patient engagement and (4) evaluation performance and measurements. This paper describes major activities involved with developing, implementing and evaluating a TM program for PWH. We discuss results, challenges, and lessons learned from integrating this program into our existing healthcare system.

Behavioural Sciences Contribution to Suppressing Transmission of Covid-19 in the UK: A Systematic Literature Review.

BACKGROUND: Governments have relied on their citizens to adhere to a variety of transmission-reducing behaviours (TRBs) to suppress the Covid-19 pandemic. Understanding the psychological and sociodemographic predictors of adherence to TRBs will be heavily influenced by the particular theories used by researchers. This review aims to identify the theories and theoretical constructs used to understand adherence to TRBs during the pandemic within the UK social and legislative context. METHODS: A systematic review identified studies to understand TRBs of adults in the UK during the pandemic. Identified theoretical constructs were coded to the Theoretical Domains Framework. Data are presented as a narrative summary. RESULTS: Thirty-five studies (n = 211,209) investigated 123 TRBs, applied 13 theoretical frameworks and reported 50 sociodemographic characteristics and 129 psychological constructs. Most studies used social cognition theories to understand TRBs and employed cross-sectional designs. Risk of sampling bias was high. Relationships between constructs and TRBs varied, but in general, beliefs about the disease (e.g. severity and risk perception) and about TRBs (e.g. behavioural norms) influenced behavioural intentions and self-reported adherence. More studies than not found that older people and females were more adherent. CONCLUSIONS: Behavioural scientists in the UK generated a significant and varied body of work to understand TRBs during the pandemic. However, more use of theories that do not rely on deliberative processes to effect behaviour change and study designs better able to support causal inferences should be used in future to inform public health policy and practice. PROSPERO REGISTRATION: CRD42021282699.

Habits and Reflective Processes in COVID-19 Transmission-reducing Behaviors: Examining Theoretical Predictions in a Representative Sample of the Population of Scotland.

BACKGROUND: Based on theory, COVID-19 transmission-reducing behaviors (TRBs) should become habitual because of their frequent performance. Habits have been hypothesized to develop through reflective processes and, to act in conjunction with them. PURPOSE: We investigated the existence, development, and consequences of TRB habits, for physical distancing, handwashing, and wearing face coverings. METHODS: A representative sample of the Scottish population (N = 1,003) was interviewed by a commercial polling company in August-October 2020 and half were re-interviewed later. Measures included adherence, habit, personal routine tendency, reflective processes, and action control for three TRBs. Data were analyzed using general linear modeling, regression, and mediation analyses. RESULTS: Handwashing was most habitual; only face covering became more habitual over time. Routine tendencies predicted TRB habits, and adherence to handwashing and physical distancing. Those reporting greater habits reported better adherence, for physical distancing and handwashing, and this remained true after controlling for previous adherence. Reflective and habit processes independently predicted adherence for physical distancing and handwashing; only reflective processes were independently predictive for face covering. The relationship between planning and forgetting and adherence was partly direct, and partly mediated by habit. CONCLUSIONS: The results confirm hypotheses from habit theory including the role of repetition and of personal routine tendency in developing habits. They are consistent with dual processing theory in finding that both reflective and habit processes predict adherence to TRBs. Action planning partly mediated the relation between reflective processes and adherence. The COVID-19 pandemic has enabled the testing and confirmation of several theoretical hypotheses about habit processes in the enactment of TRBs.

During the COVID-19 pandemic we were all asked to adopt protective behaviors, for example, keeping distance from people, wearing face masks, and handwashing. When people do the same thing repeatedly in the same situation, that behavior is likely to become a habit. As habits are generally easier to perform and maintain than planned behaviors, understanding whether the protective behaviors we adopted during COVID-19 became habitual will help us understand how best to support people to adopt infection protective behaviors in future. In this study we examined whether protective behaviors became habitual over time during the pandemic. We found that handwashing was the most habitual behavior. This is likely because hand washing was a behavior that people already regularly performed pre-pandemic. Wearing face masks was the only behavior to become more habitual over time. People with stronger habits were more likely to perform the recommendations about handwashing and physical distancing. When you want people to perform a new protective behavior this can be accomplished by making a plan to do it. Following through on these plans will eventually form habits. Habitually performed behaviors that prevent COVID-19 might also help prevent other infections and could therefore improve population health.

Effect of In-Person Delivered Behavioural Interventions in People with Multimorbidity: Systematic Review and Meta-analysis.

BACKGROUND: To investigate the effect of in-person delivered behavioural interventions in people with multimorbidity and which behaviour change techniques (BCTs), targeting lifestyle behaviours, are associated with better outcomes. METHODS: Systematic review of randomised controlled trials. We searched MEDLINE, EMBASE, CENTRAL, and CINAHL and screened reference list of reviews including people with multimorbidity, registries, and citation tracking of included studies. Meta-analyses using random-effects model to assess the effect of behavioural interventions and meta-regression analyses and effectiveness ratios to investigate the impact of mediators on effect estimates. Cochrane 'Risk of Bias Tool' 2.0 and the GRADE assessment to evaluate the overall quality of evidence. RESULTS: Fourteen studies involving 1,378 people. Behavioural interventions had little to no effect on physical activity (standardised mean difference 0.38, 95% CI -0.12-0.87) and the effect on weight loss was uncertain (BMI mean difference -0.17, 95% CI -1.1-0.83) at the end-treatment follow-up. Small improvements were seen in health-related quality of life (SMD 0.29, 95% CI 0.17-0.42) and physical function (SMD 0.42, 95% CI 0.12-0.73), and moderate improvements were seen for depression symptoms (SMD -0.70, 95% CI -0.97-0.42). Studies using the BCTs 'action planning' and 'social support (practical)' reported greater physical activity and weight loss. CONCLUSIONS: Behavioural interventions targeting lifestyle behaviours may improve health-related quality of life and physical function, and reduce depression, whereas little to no effect was achieved on physical activity and weight loss in people with multimorbidity. However, the evidence for physical activity and weight loss were of low quality and the end-treatment benefits diminished over time.

Development of transmission-reducing behaviour adherence measure (TRAM) for monitoring and predicting transmission-reducing behaviours during the pandemic.

There is a need for a measure to monitor adherence to transmission-reducing behaviours (TRBs) during pandemics. An adherence measure can monitor current TRBs, assess change over time and, potentially, predict later behaviours. The TRB adherence measure (scale consisting of seven items) includes questions based on government behavioural directives in Scotland that were common internationally, i.e., physical distancing, face covering and hand hygiene. Data were collected weekly for 6 weeks at the beginning of the pandemic, including a later follow-up repeated measure of some participants, in 20-minute structured telephone surveys with a nationally representative random sample of adults in Scotland. A total of 2969 people completed the adherence items and were highly adherent. Confirmatory factor analysis supported a unidimensional scale (CFI = .95; TLI = .93; RMSEA = .08; SRMR = .08), although internal consistency was low (Cronbach's alpha = .49). The adherence score significantly predicted adherence to a validity test item (ΔR2 = .114, F(1,2964) = 379.76, p < .001). It also predicted adherence to TRBs later over and above personal habitual styles (Creature of Habit Scale: COHS). The adherence score has been developed for routine monitoring of adherence to TRBs during the COVID-19 pandemic. It can be used to predict future similar behaviours and adherence to other behaviours, although it may be necessary to explore adherence to the specific behaviours occasionally. Adherent behaviour for one TRB is likely to be associated with adherence to government directives to other TRBs. Importantly, these TRBs are likely to be crucial in reducing COVID-19 case numbers, as well as protecting against other infectious diseases including influenza and the common cold.

Achieving integrated self-directed Cancer aftercare (ASICA) for melanoma: how a digital intervention to support total skin self-examination was used by people treated for cutaneous melanoma.

BACKGROUND: Melanoma incidence has quadrupled since 1970 and melanoma is now the second most common cancer in individuals under 50. Targeted immunotherapies for melanoma now potentially enable long-term remission even in advanced melanoma, but these melanoma survivors require ongoing surveillance, with implications for NHS resources and significant social and psychological consequences for patients. Total skin self-examination (TSSE) can detect recurrence earlier and improve clinical outcomes but is underperformed in the UK. To support survivors, the Achieving Self-directed Integrated Cancer Aftercare (ASICA) intervention was developed to prompt and improve TSSE performance, with subsequent reporting of concerns and submission of skin photos to a Dermatology Nurse Practitioner (DNP). ASICA was delivered as a randomized pilot trial. METHODS: This paper reports on process evaluation. Data on participants' demographics and the concerns they reported during the trial were tabulated and displayed using Microsoft Excel and SPSS. We explored which participants used ASICA, and how frequently, to report any skin concerns. We also determined how the interactions had worked in terms of quality of skin photographs submitted, clinical assessments made by the DNP, and the assessments and decisions made for each concern. Finally, we explored significant events occurring during the trial. Data on participants' demographics and the concerns they reported during the trial were tabulated and displayed using SPSS. A semi-structured interview was undertaken with the DNP to gain perspective on the range of concerns presented and how they were resolved. RESULTS: Of 121 recruited melanoma patients receiving ASICA for 12 months, 69 participants submitted a total of 123 reports detailing 189 separate skin-related concerns and including 188 skin photographs. Where participants fully complied with follow-up by the DNP, concerns were usually resolved remotely, but 19 (10.1%) were seen at a secondary care clinic and 14 (7.4%) referred to their GP. 49 (25.9%) of concerns were not completely resolved due to partial non-compliance with DNP follow-up. CONCLUSION: Melanoma patients randomized to the ASICA intervention were able to report skin-related concerns that could be resolved remotely through interaction with a DNP. Feasibility issues highlighted by ASICA will support further development and optimization of this digital tool. TRIAL REGISTRATION: Clinical Trials.gov , NCT03328247 . Registered on 1 November 2017.

What Competences Are Required to Deliver Person-Person Behaviour Change Interventions: Development of a Health Behaviour Change Competency Framework.

BACKGROUND: The competence of the person delivering person-to-person behaviour change interventions may influence the effectiveness of the intervention. However, we lack a framework for describing the range of competences involved. The objective of the current work was to develop a competency framework for health behaviour change interventions. METHOD: A preliminary framework was developed by two judges rating the relevance of items in the competency framework for cognitive behaviour therapies; adding relevant items from reviews and other competency frameworks; and obtaining feedback from potential users on a draft framework. The Health Behaviour Change Competency Framework (HBCCF) was used to analyse the competency content of smoking cessation manuals. RESULTS: Judges identified 194 competency items as relevant, which were organised into two domains: foundation (12 competency topics comprising 56 competencies) and behaviour change (12 topics, 54 competencies); several of the 54 and 56 competencies were composed of sub-competencies (84 subcompetencies in total). Smoking cessation manuals included 14 competency topics from the foundation and behaviour change competency domains. CONCLUSION: The HBCCF provides a structured method for assessing and reporting competency to deliver behaviour change interventions. It can be applied to assess a practitioner's competency and training needs and to identify the competencies needed for a particular intervention. To date, it has been used in self-assessments and in developing training programmes. We propose the HBCCF as a practical tool for researchers, employers, and those who design and provide training. We envisage the HBCFF maturing and adapting as evidence that identifies the essential elements required for the effective delivery of behaviour change interventions emerges.

Sociodemographic and Psychological Risk Factors for Anxiety and Depression: Findings from the Covid-19 Health and Adherence Research in Scotland on Mental Health (CHARIS-MH) Cross-sectional Survey.

BACKGROUND: Investigations about mental health report prevalence rates with fewer studies investigating psychological and social factors influencing mental health during the Covid-19 pandemic. STUDY AIMS: (1) identify sociodemographic groups of the adult population at risk of anxiety and depression and (2) determine if the following social and psychological risk factors for poor mental health moderated these direct sociodemographic effects: loneliness, social support, threat perception, illness representations. METHODS: Cross-sectional nationally representative telephone survey in Scotland in June 2020. If available, validated instruments were used, for example, Patient Health Questionnaire (PHQ-4) to measure anxiety and depression. Simple linear regressions followed by examination of moderation effect. RESULTS: A total of 1006 participants; median age 53 years, 61.4% female, from all levels of area deprivation (i.e., 3.8% in the most deprived decile and 15.6% in the most affluent decile). Analyses show associations of anxiety and depression with sociodemographic (age, gender, deprivation), social (social support, loneliness) and psychological factors (perceived threat and illness representations). Mental health was poorer in younger adults, women and people living in the most deprived areas. Age effects were exacerbated by loneliness and illness representations, gender effects by loneliness and illness representations and deprivation effects by loneliness, social support, illness representations and perceived threat. In each case, the moderating variables amplified the detrimental effects of the sociodemographic factors. CONCLUSIONS: These findings confirm the results of pre-Covid-19 pandemic studies about associations between sociodemographics and mental health. Loneliness, lack of social support and thoughts about Covid-19 exacerbated these effects and offer pointers for pre-emptive action.

Healthy snacks in hospitals: Testing the potential effects of changes in availability.

BACKGROUND: Hospitals offer snacks for sale to patients, staff and visitors. AIM: As food choice is heavily influenced by the options available, the present study (a) audited snack availability and purchase in NHS hospital sites across a large UK city; and (b) tested the potential effects of changes to this availability in an online choice experiment. METHODS: In Study 1 (audit), single-serve snacks (n=376) available in 76 hospital food retail units were audited. Purchasing data were obtained from six food retail units over four weeks (27,989 sales). In Study 2 (online experiment), participants (n=159) chose snacks from pictured ranges containing 25% (minority), 50% (equivalent) or 75% (majority) healthy options. RESULTS: Available single-serve snacks varied markedly in calorie (18-641 kcals), fat (0-39 g), sugar (0.1-76 g) and salt (0-2.9 g). Only 30% of available snacks were healthy options and only 25% of the most commonly purchased snacks were healthy options. In Study 2, snack choice was significantly associated with the availability of healthy options in the choice array (X2 (2)= 59.71, p<.01). More participants made healthy choices when product ranges contained 75% healthy options compared to 50% (p<.01) and 50% healthy options compared with 25% (p<.01). CONCLUSIONS: Healthy snacks are readily available in NHS sites but there is a greater relative variety of unhealthy snack products. Many consumers continue to purchase unhealthy items. Further increasing the availability and variety of healthy options may support consumers to make healthier choices.

Do Combinations of Behavior Change Techniques That Occur Frequently in Interventions Reflect Underlying Theory?

BACKGROUND: Behavioral interventions typically include multiple behavior change techniques (BCTs). The theory informing the selection of BCTs for an intervention may be stated explicitly or remain unreported, thus impeding the identification of links between theory and behavior change outcomes. PURPOSE: This study aimed to identify groups of BCTs commonly occurring together in behavior change interventions and examine whether behavior change theories underlying these groups could be identified. METHODS: The study involved three phases: (a) a factor analysis to identify groups of co-occurring BCTs from 277 behavior change intervention reports; (b) examining expert consensus (n = 25) about links between BCT groups and behavioral theories; (c) a comparison of the expert-linked theories with theories explicitly mentioned by authors of the 277 intervention reports. RESULTS: Five groups of co-occurring BCTs (range: 3-13 BCTs per group) were identified through factor analysis. Experts agreed on five links (≥80% of experts), comprising three BCT groups and five behavior change theories. Four of the five BCT group-theory links agreed by experts were also stated by study authors in intervention reports using similar groups of BCTs. CONCLUSIONS: It is possible to identify groups of BCTs frequently used together in interventions. Experts made shared inferences about behavior change theory underlying these BCT groups, suggesting that it may be possible to propose a theoretical basis for interventions where authors do not explicitly put forward a theory. These results advance our understanding of theory use in multicomponent interventions and build the evidence base for further understanding theory-based intervention development and evaluation.

Why does work cause fatigue? A real-time investigation of fatigue, and determinants of fatigue in nurses working 12-hour shifts.

BACKGROUND: One of the striking regularities of human behavior is that a prolonged physical, cognitive, or emotional activity leads to feelings of fatigue. Fatigue could be due to (1) depletion of a finite resource of physical and/or psychological energy or (2) changes in motivation, attention, and goal-directed effort (e.g. motivational control theory). PURPOSE: To contrast predictions from these two views in a real-time study of subjective fatigue in nurses while working. METHODS: One hundred nurses provided 1,453 assessments over two 12-hr shifts. Nurses rated fatigue, demand, control, and reward every 90 min. Physical energy expenditure was measured objectively using Actiheart. Hypotheses were tested using multilevel models to predict fatigue from (a) the accumulated values of physical energy expended, demand, control, and reward over the shift and (b) from distributed lag models of the same variables over the previous 90 min. RESULTS: Virtually all participants showed increasing fatigue over the work period. This increase was slightly greater when working overnight. Fatigue was not dependent on physical energy expended nor perceived work demands. However, it was related to perceived control over work and perceived reward associated with work. CONCLUSIONS: Findings provide little support for a resource depletion model; however, the finding that control and reward both predicted fatigue is consistent with a motivational account of fatigue.

Links Between Behavior Change Techniques and Mechanisms of Action: An Expert Consensus Study.

BACKGROUND: Understanding the mechanisms through which behavior change techniques (BCTs) can modify behavior is important for the development and evaluation of effective behavioral interventions. To advance the field, we require a shared knowledge of the mechanisms of action (MoAs) through which BCTs may operate when influencing behavior. PURPOSE: To elicit expert consensus on links between BCTs and MoAs. METHODS: In a modified Nominal Group Technique study, 105 international behavior change experts rated, discussed, and rerated links between 61 frequently used BCTs and 26 MoAs. The criterion for consensus was that at least 80 per cent of experts reached agreement about a link. Heat maps were used to present the data relating to all possible links. RESULTS: Of 1,586 possible links (61 BCTs × 26 MoAs), 51 of 61 (83.6 per cent) BCTs had a definite link to one or more MoAs (mean [SD] = 1.44 [0.96], range = 1-4), and 20 of 26 (76.9 per cent) MoAs had a definite link to one or more BCTs (mean [SD] = 3.27 [2.91], range = 9). Ninety (5.7 per cent) were identified as "definite" links, 464 (29.2 per cent) as "definitely not" links, and 1,032 (65.1 per cent) as "possible" or "unsure" links. No "definite" links were identified for 10 BCTs (e.g., "Action Planning" and "Behavioural Substitution") and for six MoAs (e.g., "Needs" and "Optimism"). CONCLUSIONS: The matrix of links between BCTs and MoAs provides a basis for those developing and synthesizing behavioral interventions. These links also provide a framework for specifying empirical tests in future studies.

Behavior Change Techniques and Their Mechanisms of Action: A Synthesis of Links Described in Published Intervention Literature.

BACKGROUND: Despite advances in behavioral science, there is no widely shared understanding of the "mechanisms of action" (MoAs) through which individual behavior change techniques (BCTs) have their effects. Cumulative progress in the development, evaluation, and synthesis of behavioral interventions could be improved by identifying the MoAs through which BCTs are believed to bring about change. PURPOSE: This study aimed to identify the links between BCTs and MoAs described by authors of a corpus of published literature. METHODS: Hypothesized links between BCTs and MoAs were extracted by two coders from 277 behavior change intervention articles. Binomial tests were conducted to provide an indication of the relative frequency of each link. RESULTS: Of 77 BCTs coded, 70 were linked to at least one MoA. Of 26 MoAs, all but one were linked to at least one BCT. We identified 2,636 BCT-MoA links in total (mean number of links per article = 9.56, SD = 13.80). The most frequently linked MoAs were "Beliefs about Capabilities" and "Intention." Binomial test results identified up to five MoAs linked to each of the BCTs (M = 1.71, range: 1-5) and up to eight BCTs for each of the MoAs (M = 3.63, range: 1-8). CONCLUSIONS: The BCT-MoA links described by intervention authors and identified in this extensive review present intervention developers and reviewers with a first level of systematically collated evidence. These findings provide a resource for the development of theory-based interventions, and for theoretical understanding of intervention evaluations. The extent to which these links are empirically supported requires systematic investigation.

Enhancing Behavior Change Technique Coding Methods: Identifying Behavioral Targets and Delivery Styles in Smoking Cessation Trials.

BACKGROUND: The behavior change technique (BCT) taxonomy v1 is often used in systematic reviews for identifying active components of interventions. Its utility could be enhanced by linking BCTs to specific target behaviors and qualifying BCT delivery style. PURPOSE: To determine whether behavioral targets and delivery styles of BCTs can be coded reliably and to determine the utility of coding these characteristics. METHODS: As part of a large systematic review of 142 smoking cessation trials, two researchers independently coded publicly and privately held intervention and comparator group materials, specifying the behavioral target (quitting, abstinence, medication adherence, or treatment engagement) and delivery style (tailored vs. not tailored; active participation vs. passive receipt) of each BCT. RESULTS: Researchers coded 3,843 BCTs, which were reliably attributed to behavioral targets (AC1 = 0.92, PABAK = 0.91). Tailoring (AC1 = 0.80, PABAK = 0.74) and participation (AC1 = 0.71, PABAK = 0.64) were also coded reliably. There was considerable variability between groups in quitting and abstinence BCTs (ranges: 0-41; 0-18) and in tailoring and participation (ranges: 0-20; 0-32), but less variability for medication adherence and treatment engagement (ranges: 0-6; 0-7). CONCLUSIONS: Behavioral targets and delivery styles of BCTs can be reliably identified and occur with sufficient frequency in smoking cessation trials for inclusion in quantitative syntheses (e.g., meta-regression analyses). Systematic reviewers could consider adopting these methods to evaluate the impact of intervention components targeting different behaviors, as well as the benefits of different BCT delivery styles.

From Theory-Inspired to Theory-Based Interventions: A Protocol for Developing and Testing a Methodology for Linking Behaviour Change Techniques to Theoretical Mechanisms of Action.

Background: Understanding links between behaviour change techniques (BCTs) and mechanisms of action (the processes through which they affect behaviour) helps inform the systematic development of behaviour change interventions. Purpose: This research aims to develop and test a methodology for linking BCTs to their mechanisms of action. Methods: Study 1 (published explicit links): Hypothesised links between 93 BCTs (from the 93-item BCT taxonomy, BCTTv1) and mechanisms of action will be identified from published interventions and their frequency, explicitness and precision documented. Study 2 (expert-agreed explicit links): Behaviour change experts will identify links between 61 BCTs and 26 mechanisms of action in a formal consensus study. Study 3 (integrated matrix of explicit links): Agreement between studies 1 and 2 will be evaluated and a new group of experts will discuss discrepancies. An integrated matrix of BCT-mechanism of action links, annotated to indicate strength of evidence, will be generated. Study 4 (published implicit links): To determine whether groups of co-occurring BCTs can be linked to theories, we will identify groups of BCTs that are used together from the study 1 literature. A consensus exercise will be used to rate strength of links between groups of BCT and theories. Conclusions: A formal methodology for linking BCTs to their hypothesised mechanisms of action can contribute to the development and evaluation of behaviour change interventions. This research is a step towards developing a behaviour change 'ontology', specifying relations between BCTs, mechanisms of action, modes of delivery, populations, settings and types of behaviour.

Pharmacist services for non-hospitalised patients.

BACKGROUND: This review focuses on non-dispensing services from pharmacists, i.e. pharmacists in community, primary or ambulatory-care settings, to non-hospitalised patients, and is an update of a previously-published Cochrane Review. OBJECTIVES: To examine the effect of pharmacists' non-dispensing services on non-hospitalised patient outcomes. SEARCH METHODS: We searched CENTRAL, MEDLINE, Embase, two other databases and two trial registers in March 2015, together with reference checking and contact with study authors to identify additional studies. We included non-English language publications. We ran top-up searches in January 2018 and have added potentially eligible studies to 'Studies awaiting classification'. SELECTION CRITERIA: Randomised trials of pharmacist services compared with the delivery of usual care or equivalent/similar services with the same objective delivered by other health professionals. DATA COLLECTION AND ANALYSIS: We used standard methodological procedures of Cochrane and the Effective Practice and Organisation of Care Group. Two review authors independently checked studies for inclusion, extracted data and assessed risks of bias. We evaluated the overall certainty of evidence using GRADE. MAIN RESULTS: We included 116 trials comprising 111 trials (39,729 participants) comparing pharmacist interventions with usual care and five trials (2122 participants) comparing pharmacist services with services from other healthcare professionals. Of the 116 trials, 76 were included in meta-analyses. The 40 remaining trials were not included in the meta-analyses because they each reported unique outcome measures which could not be combined. Most trials targeted chronic conditions and were conducted in a range of settings, mostly community pharmacies and hospital outpatient clinics, and were mainly but not exclusively conducted in high-income countries. Most trials had a low risk of reporting bias and about 25%-30% were at high risk of bias for performance, detection, and attrition. Selection bias was unclear for about half of the included studies.Compared with usual care, we are uncertain whether pharmacist services reduce the percentage of patients outside the glycated haemoglobin target range (5 trials, N = 558, odds ratio (OR) 0.29, 95% confidence interval (CI) 0.04 to 2.22; very low-certainty evidence). Pharmacist services may reduce the percentage of patients whose blood pressure is outside the target range (18 trials, N = 4107, OR 0.40, 95% CI 0.29 to 0.55; low-certainty evidence) and probably lead to little or no difference in hospital attendance or admissions (14 trials, N = 3631, OR 0.85, 95% CI 0.65 to 1.11; moderate-certainty evidence). Pharmacist services may make little or no difference to adverse drug effects (3 trials, N = 590, OR 1.65, 95% CI 0.84 to 3.24) and may slightly improve physical functioning (7 trials, N = 1329, mean difference (MD) 5.84, 95% CI 1.21 to 10.48; low-certainty evidence). Pharmacist services may make little or no difference to mortality (9 trials, N = 1980, OR 0.79, 95% CI 0.56 to 1.12, low-certaintly evidence).Of the five studies that compared services delivered by pharmacists with other health professionals, no studies evaluated the impact of the intervention on the percentage of patients outside blood pressure or glycated haemoglobin target range, hospital attendance and admission, adverse drug effects, or physical functioning. AUTHORS' CONCLUSIONS: The results demonstrate that pharmacist services have varying effects on patient outcomes compared with usual care. We found no studies comparing services delivered by pharmacists with other healthcare professionals that evaluated the impact of the intervention on the six main outcome measures. The results need to be interpreted cautiously because there was major heterogeneity in study populations, types of interventions delivered and reported outcomes.There was considerable heterogeneity within many of the meta-analyses, as well as considerable variation in the risks of bias.

Interventions to Promote Healthy Eating, Physical Activity and Smoking in Low-Income Groups: a Systematic Review with Meta-Analysis of Behavior Change Techniques and Delivery/Context.

PURPOSE: Healthy eating, physical activity and smoking interventions for low-income groups may have small, positive effects. Identifying effective intervention components could guide intervention development. This study investigated which content and delivery components of interventions were associated with increased healthy behavior in randomised controlled trials (RCTs) for low-income adults. METHOD: Data from a review showing intervention effects in 35 RCTs containing 45 interventions with 17,000 participants were analysed to assess associations with behavior change techniques (BCTs) and delivery/context components from the template for intervention description and replication (TIDieR) checklist. The associations of 46 BCTs and 14 delivery/context components with behavior change (measures of healthy eating, physical activity and smoking cessation) were examined using random effects subgroup meta-analyses. Synergistic effects of components were examined using classification and regression trees (meta-CART) analyses based on both fixed and random effects assumptions. RESULTS: For healthy eating, self-monitoring, delivery through personal contact, and targeting multiple behaviors were associated with increased effectiveness. Providing feedback, information about emotional consequences, or using prompts and cues were associated with reduced effectiveness. In synergistic analyses, interventions were most effective without feedback, or with self-monitoring excluding feedback. More effective physical activity interventions included behavioral practice/rehearsal or instruction, focussed solely on physical activity or took place in home/community settings. Information about antecedents was associated with reduced effectiveness. In synergistic analyses, interventions were most effective in home/community settings with instruction. No associations were identified for smoking. CONCLUSION: This study identified BCTs and delivery/context components, individually and synergistically, linked to increased and reduced effectiveness of healthy eating and physical activity interventions. The identified components should be subject to further experimental study to help inform the development effective behavior change interventions for low-income groups to reduce health inequalities.

How behavioural science can contribute to health partnerships: the case of The Change Exchange.

BACKGROUND: Health partnerships often use health professional training to change practice with the aim of improving quality of care. Interventions to change practice can learn from behavioural science and focus not only on improving the competence and capability of health professionals but also their opportunity and motivation to make changes in practice. We describe a project that used behavioural scientist volunteers to enable health partnerships to understand and use the theories, techniques and assessments of behavioural science. CASE STUDIES: This paper outlines how The Change Exchange, a collective of volunteer behavioural scientists, worked with health partnerships to strengthen their projects by translating behavioural science in situ. We describe three case studies in which behavioural scientists, embedded in health partnerships in Uganda, Sierra Leone and Mozambique, explored the behaviour change techniques used by educators, supported knowledge and skill development in behaviour change, monitored the impact of projects on psychological determinants of behaviour and made recommendations for future project developments. DISCUSSION: Challenges in the work included having time and space for behavioural science in already very busy health partnership schedules and the difficulties in using certain methods in other cultures. Future work could explore other modes of translation and further develop methods to make them more culturally applicable. CONCLUSION: Behavioural scientists could translate behavioural science which was understood and used by the health partnerships to strengthen their project work.

What Is Behavioural Medicine? Commentary on Definition Proposed by Dekker, Stauder and Penedo.

PURPOSE: Dekker et al. (2016) propose an updated definition of behavioural medicine. METHOD: In this commentary, we discuss how the field and the disciplines involved have changed over time before suggesting small amendments to the proposed definition. RESULTS: We suggest that the range of medicine which might be considered 'behavioural' is increasing to encompass virtually all medical practice. In addition, the role of behaviour and the potential for behaviour change as a means of improving health have become increasingly important. A defining characteristic of behavioural medicine is the involvement of multiple disciplines, working together or in parallel and, as the extent of the field expands, more disciplines are likely to be involved. CONCLUSION: We therefore propose that the definition should represent the full width of the research, practice and disciplines involved in behavioural medicine.

Reducing patient delay in Acute Coronary Syndrome (RAPiD): research protocol for a web-based randomized controlled trial examining the effect of a behaviour change intervention.

AIMS: To evaluate the efficacy of a behaviour change technique-based intervention and compare two possible modes of delivery (text + visual and text-only) with usual care. BACKGROUND: Patient delay prevents many people from achieving optimal benefit of time-dependent treatments for acute coronary syndrome. Reducing delay would reduce mortality and morbidity, but interventions to change behaviour have had mixed results. Systematic inclusion of behaviour change techniques or a visual mode of delivery might improve the efficacy of interventions. DESIGN: A three-arm web-based, parallel randomized controlled trial of a theory-based intervention. METHODS: The intervention comprises 12 behaviour change techniques systematically identified following systematic review and a consensus exercise undertaken with behaviour change experts. We aim to recruit n = 177 participants who have experienced acute coronary syndrome in the previous 6 months from a National Health Service Hospital. Consenting participants will be randomly allocated in equal numbers to one of three study groups: i) usual care, ii) usual care plus text-only behaviour change technique-based intervention or iii) usual care plus text + visual behaviour change technique-based intervention. The primary outcome will be the change in intention to phone an ambulance immediately with symptoms of acute coronary syndrome ≥15-minute duration, assessed using two randomized series of eight scenarios representing varied symptoms before and after delivery of the interventions or control condition (usual care). Funding granted January 2014. DISCUSSION: Positive results changing intentions would lead to a randomized controlled trial of the behaviour change intervention in clinical practice, assessing patient delay in the event of actual symptoms. TRIAL REGISTRATION: Registered at ClinicalTrials.gov: NCT02820103.