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Background: Clinicians' behaviours require deliberate decision-making in complex contexts and may involve both impulsive (automatic) and reflective (motivational and volitional) processes. Purpose: The purpose of this study was to test a dual process model applied to clinician behaviours in their management of type 2 diabetes. Methods: The design used six nested prospective correlational studies. Questionnaires were sent to general practitioners and nurses in 99 UK primary care practices, measuring reflective (intention, action planning and coping planning) and impulsive (automaticity) predictors for six guideline-recommended behaviours: blood pressure prescribing ( N = 335), prescribing for glycemic control ( N = 288), providing diabetes-related education ( N = 346), providing weight advice ( N = 417), providing self-management advice ( N = 332) and examining the feet ( N = 218). Results: Respondent retention was high. A dual process model was supported for prescribing behaviours, weight advice, and examining the feet. A sequential reflective process was supported for blood pressure prescribing, self-management and weight advice, and diabetes-related education. Conclusions: Reflective and impulsive processes predict behaviour. Quality improvement interventions should consider both reflective and impulsive approaches to behaviour change. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Purpose: The aim of this paper is to assess the frequency of identification as well as the inter-coder and test-retest reliability of identification of behavior change techniques (BCTs) in written intervention descriptions.Methods: Forty trained coders applied the "Behavior Change Technique Taxonomy version 1" (BCTTv1) to 40 intervention descriptions published in protocols and repeated this 1 month later.Results: Eighty of 93 defined BCTs were identified by at least one trained coder, and 22 BCTs were identified in 16 (40 %) or more of 40 descriptions. Good inter-coder reliability was observed across 80 BCTs identified in the protocols: 66 (80 %) achieved mean prevalence and bias-adjusted kappa (PABAK) scores of 0.70 or greater, and 59 (74 %) achieved mean scores of 0.80 or greater. There was good within-coder agreement between baseline and 1 month, demonstrating good test-retest reliability.Conclusions: BCTTv1 can be used by trained coders to identify BCTs in intervention descriptions reliably. However, some frequently occurring BCT definitions require further clarification. [ABSTRACT FROM AUTHOR]

Background: CONSORT guidelines call for precise reporting of behavior change interventions: we need rigorous methods of characterizing active content of interventions with precision and specificity. Objectives: The objective of this study is to develop an extensive, consensually agreed hierarchically structured taxonomy of techniques [behavior change techniques (BCTs)] used in behavior change interventions. Methods: In a Delphi-type exercise, 14 experts rated labels and definitions of 124 BCTs from six published classification systems. Another 18 experts grouped BCTs according to similarity of active ingredients in an open-sort task. Inter-rater agreement amongst six researchers coding 85 intervention descriptions by BCTs was assessed. Results: This resulted in 93 BCTs clustered into 16 groups. Of the 26 BCTs occurring at least five times, 23 had adjusted kappas of 0.60 or above. Conclusions: 'BCT taxonomy v1,' an extensive taxonomy of 93 consensually agreed, distinct BCTs, offers a step change as a method for specifying interventions, but we anticipate further development and evaluation based on international, interdisciplinary consensus. [ABSTRACT FROM AUTHOR]

Background: Theories of action control emphasise the importance of planning, but plans are not universally beneficial. Purpose: The present study investigates whether the effectiveness of plans depends upon the skill of the planner. Methods: Study 1 prospectively predicted changes in unhealthy snacking behaviour over 1 week from intentions, action planning and performance on a standardised cognitive test of planning skill ( n = 72). Study 2 experimentally randomised skilled and poor planners to receive (or not) a planning intervention before completing an online food diary ( n = 144) Results: Spontaneously generated action plans about snacking explained significantly more variance in subsequent snacking if produced by a skilled rather than a poor planner. The planning intervention (implementation intention) significantly improved goal attainment but only in poor planners. Conclusions: Plans are only as good as the people who make them. Poor planners' plans do not help achieve goals. Planning interventions can compensate for a lack of planning skill. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Background: Stress in health care professionals may reflect both the work and appraisal of work and impacts on the individuals, their patients, colleagues and managers.Purpose: The purpose of the present study is to examine physiological and psychological effects of stressors (tasks) and theory-based perceptions of work stressors within and between nurses in real time.Methods: During two work shifts, 100 nurses rated experienced stress, affect, fatigue, theory-based measures of work stress and nursing tasks on electronic diaries every 90 min, whereas heart rate and activity were measured continuously.Results: Heart rate was associated with both demand and effort. Experienced stress was related to demand, control, effort and reward. Effort and reward interacted as predicted (but only within people). Results were unchanged when allowance was made for work tasks.Conclusions: Real-time appraisals were more important than actual tasks in predicting both psychological and physiological correlates of stress. At times when effort was high, perceived reward reduced stress. [ABSTRACT FROM AUTHOR]

Background: Adherence to preventive medication is often poor, and current interventions have had limited success. Purpose: This study was conducted to pilot a randomised controlled trial aimed at increasing adherence to preventive medication in stroke survivors using a brief, personalised intervention. Methods: Sixty-two stroke survivors were randomly allocated to either a two-session intervention aimed at increasing adherence via (a) introducing a plan linked to environmental cues (implementation intentions) to help establish a better medication-taking routine (habit) and (b) eliciting and modifying any mistaken patient beliefs regarding medication/stroke or a control group. Primary outcome was adherence to antihypertensive medication measured objectively over 3 months using an electronic pill bottle. Results: Fifty-eight people used the pill bottle and were analysed as allocated; 54 completed treatment. The intervention resulted in 10 % more doses taken on schedule (intervention, 97 %; control, 87 %; 95 % CI for difference (0.2, 16.2); p = 0.048). Conclusions: A simple, brief intervention increased medication adherence in stroke survivors, over and above any effect of increased patient contact or mere measurement. ( http://controlled-trials.com , number ISRCTN38274953.) [ABSTRACT FROM AUTHOR]

Objective: The purpose of this study is to identify factors which predict adherence in stroke survivors. Design: This is a longitudinal study where 180 stroke survivors were assessed 1 year after their first ischaemic stroke. The relationship between adherence and illness and medication beliefs was tested at baseline (time 1) and again 5-6 weeks later (time 2). Main Outcome Measures: The main outcome measures used in this study are Medication Adherence Report Scale and urinary salicylate levels. Results: Four variables predicted time 1 poor adherence: (1) younger age, (2) increased specific concerns about medications, (3) reduced cognitive functioning and (4) low perceived benefit of medication. Three out of these four variables were again predictive of time 2 adherence and accounted for 24% of the variance: (1) younger age, (2) increased specific concerns about medications and (3) low perceived benefit of medication. The urinary salicylate assay failed to differentiate between patients taking and not taking aspirin. Conclusion: Interventions to improve adherence should target patients' beliefs about their medication. [ABSTRACT FROM AUTHOR]