Factors influencing uptake of protective behaviours by healthcare workers in England during the COVID-19 pandemic: A theory-based mixed-methods study.

BACKGROUND: Hospital infection control policies protect patients and healthcare workers (HCWs) and limit the spread of pathogens, but adherence to COVID-19 guidance varies. We examined hospital HCWs' enactment of social distancing and use of personal protective equipment (PPE) during the COVID-19 pandemic, factors influencing these behaviours, and acceptability and feasibility of strategies to increase social distancing. METHODS: An online, cross-sectional survey (n = 86) and semi-structured interviews (n = 22) with HCWs in two English hospitals during the first wave of the COVID-19 pandemic (May-December 2020). The Capability, Opportunity, Motivation (COM-B) model of behaviour change underpinned survey and topic guide questions. Spearman Rho correlations examined associations between COM-B domains and behaviours. Interviews were analysed using inductive and deductive thematic analysis. Potential strategies to improve social distancing were selected using the Behaviour Change Wheel and discussed in a stakeholder workshop (n = 8 participants). RESULTS: Social distancing enactment was low, with 85% of participants reporting very frequently or always being in close contact with others in communal areas. PPE use was high (88% very frequently or always using PPE in typical working day). Social distancing was associated with Physical Opportunity (e.g., size of physical space), Psychological Capability (e.g., clarity of guidance), and Social Opportunity (e.g., support from managers). Use of PPE was associated with Psychological Capability (e.g., training), Physical Opportunity (e.g., availability), Social Opportunity (e.g., impact on interactions with patients), and Reflective Motivation (e.g., beliefs that PPE is effective). Local champions and team competition were viewed as feasible strategies to improve social distancing. CONCLUSIONS: It is valuable to understand and compare the drivers of individual protective behaviours; when faced with the same level of perceived threat, PPE use was high whereas social distancing was rarely enacted. Identified influences represent targets for intervention strategies in response to future infectious disease outbreaks.

Exploration of the individual, social and environmental factors influencing dietary behaviour in shift workers with type 2 diabetes working in UK healthcare-The Shift-Diabetes Study: A qualitative study using the theoretical domains framework.

AIM: To identify factors influencing dietary behaviour in shift workers with type 2 diabetes (T2D) working in UK healthcare settings. METHODS: Semi-structured qualitative interviews based on the theoretical domains framework (TDF) were conducted with a convenience sample (n = 15) of shift workers (32-59 years) diagnosed with T2D who worked night shifts as part of a mixed shift schedule. The TDF was applied to analyse transcripts using a combined deductive framework and inductive thematic analysis approach. Identified influences were mapped to the behaviour change technique taxonomy to identify potential strategies to change dietary behaviour in this context. RESULTS: Key barriers to healthy dietary behaviours were access and cost of food available during night work (TDF domain: Environment Context and Resources). Factors identified as both enablers and barriers included: availability of staff facilities and time to take a break, (Environment Context and Resources), the physical impact of night work (Beliefs About Consequences), eating in response to stress or tiredness (Emotion), advance planning of meals/food and taking own food to work (Behavioural Regulation). Potential techniques to address these influences and improve dietary behaviour in this context include: meal planning templates, self-monitoring and biofeedback, and increasing accessibility and availability of healthier food choices during night shifts. CONCLUSIONS: The dietary behaviour of shift workers with T2D is influenced by interacting individual, socio-cultural and environmental factors. Intervention should focus on environmental restructuring and strategies that enable monitoring and meal planning.

Feasibility study of hospital antimicrobial stewardship analytics using electronic health records.

BACKGROUND: Hospital antimicrobial stewardship (AMS) programmes are multidisciplinary initiatives to optimize antimicrobial use. Most hospitals depend on time-consuming manual audits to monitor clinicians' prescribing. But much of the information needed could be sourced from electronic health records (EHRs). OBJECTIVES: To develop an informatics methodology to analyse characteristics of hospital AMS practice using routine electronic prescribing and laboratory records. METHODS: Feasibility study using electronic prescribing, laboratory and clinical coding records from adult patients admitted to six specialities at Queen Elizabeth Hospital, Birmingham, UK (September 2017-August 2018). The study involved: (i) a review of AMS standards of care; (ii) their translation into concepts measurable from commonly available EHRs; and (iii) a pilot application in an EHR cohort study (n = 61679 admissions). RESULTS: We developed data modelling methods to characterize antimicrobial use (antimicrobial therapy episode linkage methods, therapy table, therapy changes). Prescriptions were linked into antimicrobial therapy episodes (mean 2.4 prescriptions/episode; mean length of therapy 5.8 days), enabling several actionable findings. For example, 22% of therapy episodes for low-severity community-acquired pneumonia were congruent with prescribing guidelines, with a tendency to use broader-spectrum antibiotics. Analysis of therapy changes revealed IV to oral therapy switching was delayed by an average 3.6 days (95% CI: 3.4-3.7). Microbial cultures were performed prior to treatment initiation in just 22% of antibacterial prescriptions. The proposed methods enabled fine-grained monitoring of AMS practice down to specialities, wards and individual clinical teams by case mix, enabling more meaningful peer comparison. CONCLUSIONS: It is feasible to use hospital EHRs to construct rapid, meaningful measures of prescribing quality with potential to support quality improvement interventions (audit/feedback to prescribers), engagement with front-line clinicians on optimizing prescribing, and AMS impact evaluation studies.

Interventions to improve appropriate antibiotic prescribing in long-term care facilities: a systematic review.

BACKGROUND: Overuse of antibiotics has contributed to antimicrobial resistance; a growing public health threat. In long-term care facilities, levels of inappropriate prescribing are as high as 75%. Numerous interventions targeting long-term care facilities' antimicrobial stewardship have been reported with varying, and largely unexplained, effects. Therefore, this review aimed to apply behavioural science frameworks to specify the component behaviour change techniques of stewardship interventions in long-term care facilities and identify those components associated with improved outcomes. METHOD: A systematic review (CRD42018103803) was conducted through electronic database searches. Two behavioural science frameworks, the Behaviour Change Wheel and Behaviour Change Technique Taxonomy were used to classify intervention descriptions into intervention types and component behaviour change techniques used. Study design and outcome heterogeneity prevented meta-analysis and meta-regression. Interventions were categorised as 'very promising' (all outcomes statistically significant), 'quite promising' (some outcomes statistically significant), or 'not promising' (no outcomes statistically significant). 'Promise ratios' (PR) were calculated for identified intervention types and behaviour change techniques by dividing the number of (very or quite) promising interventions featuring the intervention type or behaviour change technique by the number of interventions featuring the intervention type or behaviour change technique that were not promising. Promising intervention types and behaviour change techniques were defined as those with a PR ≥ 2. RESULTS: Twenty studies (of19 interventions) were included. Seven interventions (37%) were 'very promising', eight 'quite promising' (42%) and four 'not promising' (21%). Most promising intervention types were 'persuasion' (n = 12; promise ratio (PR) = 5.0), 'enablement' (n = 16; PR = 4.33) and 'education' (n = 19; PR = 3.75). Most promising behaviour change techniques were 'feedback on behaviour' (n = 9; PR = 8.0) and 'restructuring the social environment' (e.g. staff role changes; n = 8; PR = 7.0). CONCLUSION: Systematic identification of the active ingredients of antimicrobial stewardship in long-term care facilities was facilitated through the application of behavioural science frameworks. Incorporating environmental restructuring and performance feedback may be promising intervention strategies for antimicrobial stewardship interventions within long-term care facilities.

Antibiotic prescribing in UK care homes 2016-2017: retrospective cohort study of linked data.

BACKGROUND: Older people living in care homes are particularly susceptible to infections and antibiotics are therefore used frequently for this population. However, there is limited information on antibiotic prescribing in this setting. This study aimed to investigate the frequency, patterns and risk factors for antibiotic prescribing in a large chain of UK care homes. METHODS: Retrospective cohort study of administrative data from a large chain of UK care homes (resident and care home-level) linked to individual-level pharmacy data. Residents aged 65 years or older between 1 January 2016 and 31 December 2017 were included. Antibiotics were classified by type and as new or repeated prescriptions. Rates of antibiotic prescribing were calculated and modelled using multilevel negative binomial regression. RESULTS: 13,487 residents of 135 homes were included. The median age was 85; 63% residents were female. 28,689 antibiotic prescriptions were dispensed, the majority were penicillins (11,327, 39%), sulfonamides and trimethoprim (5818, 20%), or other antibacterials (4665, 16%). 8433 (30%) were repeat prescriptions. The crude rate of antibiotic prescriptions was 2.68 per resident year (95% confidence interval (CI) 2.64-2.71). Increased antibiotic prescribing was associated with residents requiring more medical assistance (adjusted incidence rate ratio for nursing opposed to residential care 1.21, 95% CI 1.13-1.30). Prescribing rates varied widely by care home but there were no significant associations with the care home-level characteristics available in routine data. CONCLUSIONS: Rates of antibiotic prescribing in care homes are high and there is substantial variation between homes. Further research is needed to understand the drivers of this variation to enable development of effective stewardship approaches that target the influences of prescribing.

An interdisciplinary mixed-methods approach to developing antimicrobial stewardship interventions: Protocol for the Preserving Antibiotics through Safe Stewardship (PASS) Research Programme.

Behaviour change is key to combating antimicrobial resistance. Antimicrobial stewardship (AMS) programmes promote and monitor judicious antibiotic use, but there is little consideration of behavioural and social influences when designing interventions.  We outline a programme of research which aims to co-design AMS interventions across healthcare settings, by integrating data-science, evidence- synthesis, behavioural-science and user-centred design. The project includes three work-packages (WP): WP1 (Identifying patterns of prescribing):  analysis of electronic health-records to identify prescribing patterns in care-homes, primary-care, and secondary-care. An online survey will investigate consulting/antibiotic-seeking behaviours in members of the public. WP2 (Barriers and enablers to prescribing in practice): Semi-structured interviews and observations of practice to identify barriers/enablers to prescribing, influences on antibiotic-seeking behaviour and the social/contextual factors underpinning prescribing. Systematic reviews of AMS interventions to identify the components of existing interventions associated with effectiveness. Design workshops to identify constraints influencing the form of the intervention. Interviews conducted with healthcare-professionals in community pharmacies, care-homes, primary-, and secondary-care and with members of the public. Topic guides and analysis based on the Theoretical Domains Framework.  Observations conducted in care-homes, primary and secondary-care with analysis drawing on grounded theory.  Systematic reviews of interventions in each setting will be conducted, and interventions described using the Behaviour Change Technique taxonomy v1. Design workshops in care-homes, primary-, and secondary care. WP3 (Co-production of interventions and dissemination). Findings will be integrated to identify opportunities for interventions, and assess whether existing interventions target influences on antibiotic use. Stakeholder panels will be assembled to co-design and refine interventions in each setting, applying the Affordability, Practicability, Effectiveness, Acceptability, Side-effects and Equity (APEASE) criteria to prioritise candidate interventions.  Outputs will inform development of new AMS interventions and/or optimisation of existing interventions.  We will also develop web-resources for stakeholders providing analyses of antibiotic prescribing patterns, prescribing behaviours, and evidence reviews.

Improving medication adherence in stroke survivors: the intervention development process.

BACKGROUND: Medications targeting stroke risk factors have shown good efficacy, yet adherence is suboptimal. A lack of underlying theory may contribute to the ineffectiveness of eliciting or sustaining behaviour change in many existing interventions targeting medication adherence in stroke. Intervention effectiveness and implementation could be enhanced by consideration of evidence base and theory to drive development. The purpose of this study is to identify appropriate components for a theory-driven and evidence-based medication adherence intervention for stroke survivors. METHODS: The Behaviour Change Wheel (BCW), a guide to intervention development, informed our systematic process of intervention development. Our earlier systematic review had identified important determinants of medication adherence that were mapped into the Theoretical Domains Framework (TDF), with Knowledge, Beliefs about consequences and Emotions found to be more influential. Utilising the BCW facilitated selection of intervention options and behaviour change techniques (BCTs); the active ingredients within an intervention. To further refine BCT selection, APEASE criteria were employed, allowing evaluation of potential BCTs within context: The National Health Service (NHS), United Kingdom (UK). RESULTS: Five intervention functions (Education, Persuasion, Training, Environmental Restructuring and Enablement) and five policy categories (Communication/marketing, Guidelines, Regulation, Environmental/social planning and Service provision) were identified as potential intervention options, underpinned by our systematic review findings. Application of APEASE criteria led to an initial pool of 21 BCTs being reduced to 11 (e.g. Habit Formation, Information about Health Consequences and Action Planning) identified as potential intervention components that would both be feasible and directly target the underlying determinants of stroke survivors' medication adherence. CONCLUSIONS: Careful consideration of underlying evidence and theory to drive intervention design, facilitated by the BCW, enabled identification of appropriate intervention components. BCTs including Habit Formation, Information about Health Consequences and Self-monitoring of Behaviour were considered potentially effective and appropriate to deliver within the NHS. Having reduced the pool of potential intervention components to a manageable number, it will now be possible to explore the perceived acceptability of selected BCTs in interviews with stroke survivors and healthcare professionals. This approach to intervention development should be generalisable to other chronic conditions and areas of behaviour change (e.g. exercise adherence).

Clinical prediction models for mortality and functional outcome following ischemic stroke: A systematic review and meta-analysis.

OBJECTIVE: We aim to identify and critically appraise clinical prediction models of mortality and function following ischaemic stroke. METHODS: Electronic databases, reference lists, citations were searched from inception to September 2015. Studies were selected for inclusion, according to pre-specified criteria and critically appraised by independent, blinded reviewers. The discrimination of the prediction models was measured by the area under the curve receiver operating characteristic curve or c-statistic in random effects meta-analysis. Heterogeneity was measured using I2. Appropriate appraisal tools and reporting guidelines were used in this review. RESULTS: 31395 references were screened, of which 109 articles were included in the review. These articles described 66 different predictive risk models. Appraisal identified poor methodological quality and a high risk of bias for most models. However, all models precede the development of reporting guidelines for prediction modelling studies. Generalisability of models could be improved, less than half of the included models have been externally validated(n = 27/66). 152 predictors of mortality and 192 predictors and functional outcome were identified. No studies assessing ability to improve patient outcome (model impact studies) were identified. CONCLUSIONS: Further external validation and model impact studies to confirm the utility of existing models in supporting decision-making is required. Existing models have much potential. Those wishing to predict stroke outcome are advised to build on previous work, to update and adapt validated models to their specific contexts opposed to designing new ones.

Psychological Determinants of Medication Adherence in Stroke Survivors: a Systematic Review of Observational Studies.

BACKGROUND: Medications targeting stroke risk factors have shown good efficacy, yet adherence is suboptimal. To improve adherence, its determinants must be understood. To date, no systematic review has mapped identified determinants into the Theoretical Domains Framework (TDF) in order to establish a more complete understanding of medication adherence. PURPOSE: The aim of this study was to identify psychological determinants that most influence stroke survivors' medication adherence. METHODS: In line with the prospectively registered protocol (PROSPERO CRD42015016222), five electronic databases were searched (1953-2015). Hand searches of included full text references were undertaken. Two reviewers conducted screening, data extraction and quality assessment. Determinants were mapped into the TDF. RESULTS: Of 32,825 articles, 12 fulfilled selection criteria (N = 43,984 stroke survivors). Tested determinants mapped into 8/14 TDF domains. Studies were too heterogeneous for meta-analysis. Three TDF domains appeared most influential. Negative emotions ('Emotions' domain) such as anxiety and concerns about medications ('Beliefs about Consequences' domain) were associated with reduced adherence. Increased adherence was associated with better knowledge of medications ('Knowledge' domain) and stronger beliefs about medication necessity ('Beliefs about Consequences' domain). Study quality varied, often lacking information on sample size calculations. CONCLUSIONS: This review provides foundations for evidence-based intervention design by establishing psychological determinants most influential in stroke survivors' medication adherence. Six TDF domains do not appear to have been tested, possibly representing gaps in research design. Future research should standardise and clearly report determinant and medication adherence measurement to facilitate meta-analysis. The range of determinants explored should be broadened to enable more complete understanding of stroke survivors' medication adherence.

Predictors of anxiety after stroke: a systematic review of observational studies.

BACKGROUND: Anxiety disorders or symptoms are relatively common after stroke. A better understanding of the predictors of anxiety in stroke patients may improve the management of these disorders. The current review was conducted to determine the predictors of anxiety after stroke. METHODS: Relevant articles concerning population, hospital, or rehabilitation-based studies were identified by searching 10 electronic databases up to May 2014. Methodological quality appraisal, including the validity of prognostic models and data extraction were conducted by 3 reviewers. RESULTS: A total of 18 studies were identified. Data from 3 population-based studies including 8130 patients, 8 hospital-based studies including 1199 patients, and 7 rehabilitation-based studies including 1103 patients were evaluated. Prestroke depression, stroke severity, early anxiety, and dementia or cognitive impairment after stroke were the main predictors of poststroke anxiety. Older age, physical disability or impairment, and use of antidepressant drugs were not associated with the presence of anxiety. Limitations of studies included wide variation in screening tools and cutoff scores, variability in the time frame of screening for anxiety, use of extensive exclusion criteria, and questionable statistical internal and external validity of the models. CONCLUSIONS: Lack of methodological and statistical rigor affects the validity of proposed models to predict anxiety after stroke. Future research should focus on testing proposed models on both internal and external samples to ultimately inform future clinical practice.