Trends in behaviour change techniques for implementing and de-Implementing healthcare practices using audit and feedback

Trends in behaviour change techniques for implementing and de-Implementing healthcare practices using audit and feedback | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Trends in behaviour change techniques for implementing and de-Implementing healthcare practices using audit and feedback Hamish Duncan, Andrea Patey, Jacob Crawshaw, Justin Presseau, and 4 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7519867/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 5 You are reading this latest preprint version Abstract Background Audit and feedback (A&F) is a widely used quality improvement strategy to modify healthcare professionals’ practice. However, there is considerable variation in how A&F is applied and in its effectiveness. Investigating this variation, in terms of differences in the behaviour change techniques (BCTs) interventions employ, and why it occurs may provide insights for optimising intervention design. This study, therefore, explored associations between which BCT are used in A&F interventions, behaviour change direction (implementation vs. de-implementation), and target behaviour type. Methods An exploratory secondary analysis was conducted on data from 261 randomized trials of A&F interventions, originally extracted as part of a Cochrane systematic review. Regression analyses investigated whether different BCTs were used for implementation versus de-implementation. These analyses were repeated in subgroups of different behaviour types (e.g., prescribing, testing/examinations). Parallel analyses aggregated data at the study level to assess the robustness of findings. Results Analyses on the whole sample demonstrated that the same BCTs were used to implement and de-implement target behaviours in A&F interventions. Subgroup analyses identified potential associations between specific BCTs and implementation direction within certain behaviour types: social comparison with implementation of treatment decisions/actions; education (unspecified) with implementation of testing/examinations; social support (unspecified) with implementation of prescribing; and feedback on outcome of behaviour with de-implementation of treatment decisions/actions. However, these associations were not consistently replicated across the main and parallel analyses, and may reflect prevailing design practices or methodological artefacts rather than genuine differences in BCT selection. Conclusions This study demonstrated that, overall, A&F interventions utilise similar BCTs regardless of whether behaviours are being implemented or de-implemented. However, exploratory subgroup analyses suggest that tailoring interventions through selectively using certain BCTs for either implementation or de-implementation, depending on the type of behaviour being acted on, may warrant further investigation. Future research should test these hypotheses using theory-informed intervention designs and robust methods, to determine whether current patterns of BCT use reflect true differences in intervention effectiveness. Audit and Feedback Implementation De-Implementation Healthcare Professionals Quality Improvement Intervention Design Behaviour Change Figures Figure 1 Figure 2 Contributions to the literature This study is the first to use inferential statistics to examine whether audit and feedback (A&F) interventions contain different behaviour change techniques (BCTs) for different types of behaviour and implementation versus de-implementation in healthcare. Conducting this analysis at a granular level and supplementing it with exploratory subgroup analyses, this study aimed to identify any such differences. Findings demonstrate that the same BCTs are used for implementation and de-implementation, suggesting practice does not reflect the view that distinct BCTs are required for each. This work highlights potential limitations in A&F design and calls for future research testing whether aligning BCTs with behaviour change direction improves effectiveness. Introduction Audit and feedback (A&F) is a type of behaviour change intervention in which a summary of a healthcare professional’s (HCP) clinical performance is produced over a specified period and compared to a standard (e.g., clinical guidelines) to promote behaviour change [ 1 – 4 ]. It is used in many healthcare organisations internationally to change HCPs’ behaviours, thereby, promoting evidence-based practices and discouraging those that are ineffective [ 5 , 6 ]. This process ensures that clinical performance is aligned with best practice, which is vital for improving the health outcomes of patients [ 7 – 9 ]. Extensive research has examined the effectiveness and underlying mechanisms of A&F in healthcare [ 1 , 2 ]. Meta-analyses consistently indicate that, on average, A&F results in small to moderate improvements in desired clinical practices within healthcare settings [ 10 – 12 ]. However, this effect is highly variable [ 10 – 12 ]. Many different contextual factors may contribute to this variability, such as the environment in which the intervention is operating [ 13 ] and the intervention’s target population [ 14 ]. Furthermore, there is evidence that features of the interventions, such as their content, may also contribute to differences in effectiveness [ 1 , 2 , 12 , 13 ]. Recent research has highlighted significant variability in the content of A&F interventions [ 1 , 2 , 15 , 16 ], particularly the behaviour change techniques (BCTs) they employ. BCTs are “observable, replicable and irreducible components of an intervention that are designed to alter or redirect causal processes regulating behaviour” [ 17 , p.82]. They are the active components of behavioural interventions, and so it is possible that the variation in which BCTs are used accounts for the variability in intervention effectiveness. Given this potential to influence intervention outcomes, investigating why different BCTs are used across A&F interventions may provide insights into current design practices and generate hypotheses for future research. The variability in which BCTs are used is often attributed to the fact that many interventions are developed without a clear grounding in behaviour change theory [ 18 – 20 ]. Consequently, A&F interventions may depend on suboptimal strategies for influencing behaviour, with design and implementation decisions driven by practical considerations, intuition, or other undocumented decision-making processes. However, it has also been suggested that certain characteristics of the behaviours targeted by A&F interventions may impact which BCTs they use. Two examples are the intended direction of behaviour change and the type of healthcare behaviour being acted on [ 21 , 22 ]. The intended direction of behaviour change refers to whether an intervention aims to implement a target behaviour, adopting a new practice or increasing its frequency of occurrence, or de-implement it, stopping a harmful or outdated practice or decreasing its frequency of occurrence [ 23 ]. This distinction between implementation and de-implementation is relatively new [ 21 ]. As a result, there is an ongoing debate over whether different BCTs are required for implementation versus de-implementation. If different behavioural strategies are needed, A&F designers may consider whether the target behaviour is being implemented or de-implemented when identifying which BCTs to include in their intervention [ 21 , 22 ]. Additionally, related target behaviours, such as those supporting mental health, may have common behavioural determinants [ 24 ] meaning that the same BCTs may be effective when acting on similar target behaviours [ 25 ]. Thus, A&F designers may select BCTs according to the type of target behaviour being targeted. Investigating whether these factors are considered in A&F design is important for understanding the current practice and guiding future improvements. A recent review [ 21 ] tested these premises across a sample of different types of behavioural interventions in healthcare, including but not specific to A&F. It found that different BCTs were used depending on the direction of behaviour change and the type of target behaviour [ 21 ]. However, there was no investigation using inferential statistics to determine whether this finding applies specifically to A&F interventions. Furthermore, the study relied on an overarching assumption, describing each intervention based on its general goal of either implementing or de-implementing one type of target behaviour. This description simplifies analysis but may not accurately reflect most A&F interventions, which often act on multiple different types of target behaviours simultaneously [ 1 ], with some being implemented and others de-implemented. Our study sought to investigate the extent to which A&F intervention content differs between implementation and de-implementation and whether this content is based on the specific type of behaviour being targeted. This may guide future studies on the effectiveness of current practices, and help determine whether A&F interventions should be adapted based on whether they aim to promote or reduce certain behaviours within healthcare. To address this, the current study refines previous methodologies to examine whether: 1) A&F interventions utilise different BCTs depending on if they are implementing or de-implementing their target behaviours; 2) the type of target behaviour influences this relationship. Method Design The current study is an exploratory secondary analysis of the recent Cochrane review of audit and feedback [ 1 , 2 ] It utilises a dataset of BCTs used in A&F interventions, produced as part the review. Additional data was also extracted from the original sample for the purposes of this study. This included whether each behaviour was targeted to be implemented or de-implemented and a more granular description of the type of target behaviour. Sample The original dataset included 287 A&F studies, published before 2020, which had been selected for an analysis of BCTs in A&F as part of an update of the Cochrane systematic review of A&F interventions [ 1 , 2 ]. The full list of the included studies as well as the search strategy and eligibility criteria are reported elsewhere [ 12 , 26 ]. The dataset includes only interventions that were part of randomised control trials or cluster randomised control trials that used A&F as either a standalone or cointervention to change HCPs’ practices [ 1 , 2 ]. Of the 287 studies in the dataset, 261 were included in the analyses. We extracted data relating to the target behaviours of the studies, the content of the interventions, and the aims of the studies. 26 studies from the original dataset had incomplete data with regards to these variables. As a result, these studies were excluded from the analyses, leaving 261 in the final sample. Measures Intervention content The original dataset describes intervention content in terms of BCTs. The behaviour change technique taxonomy version 1 (BCTTv1) [ 17 ] was used to categorise intervention content. The BCTTv1 includes 93 different BCTs, which have been used widely and successfully to identify the key active components of different interventions [ 17 , 27 ]. In addition to the BCTTV1, an A&F codebook - specifically developed to code A&F intervention content - included 2 additional BCTs, education (unspecified) and feedback (unspecified). Each intervention was coded for the presence or absence of the 95 BCTs. Types of target behaviour Target behaviours were identified in the original systematic review by the outcome variables used in the source studies to measure intervention success [ 1 , 2 ]. In cases where there were multiple measures of a single behaviour, judgement was used to ensure that a single target behaviour was not included in the dataset multiple times. The target behaviours were grouped into eight different categories in the original dataset: prescribing, testing/examination, treatment decision/action, counselling, immunization, referrals, diagnosis, and screening. The original categories are potentially broad and may not reflect the way that intervention designers think about target behaviours. As such, the three largest categories of target behaviours (prescribing, testing/examination, and treatment decision/action) were segmented into more granular categories by the research team. Prescribing was further divided into the following subcategories: prophylaxis, immediate treatment, monitoring, and support. These were selected because they reflect a difference in the immediacy of the action being taken (proactive, immediate, longstanding) which is a distinction that has previously been made in the literature [ 28 ]. The final subcategory, support, was created as several target behaviours related more to the encouragement of adherence to medication than to prescription in its truest sense. The testing/examinations category was divided into the subcategories: examinations, imaging, and laboratory tests. These three subcategories reflect distinctions that were included in many of the papers [e.g. 29–32] and refer to different categories of techniques commonly used for testing/examination. Finally, treatment decision/action was separated into the categories: medication decisions, surgical decisions, and other. The first two subcategories reflect two large observed groups within the dataset. However, due to the high variability in the treatment decisions/actions category, it was necessary to include an additional category of ‘other’ to describe a large portion of this subgroup. A description of each behavioural category, subcategory, and examples can be found in Table 1 . All target behaviours that fell into the three higher-order categories were recategorized into subcategories based on the description of the outcome variable used to measure the target behaviour. Table 1 Description and examples of the categories and subcategories or target behaviours used within the study. Behaviour subcategory Description Example and source Prescribing Prophylaxis A prescribing behaviour completed to prevent a disease or future negative outcome Rates of prophylactic use of oxytocin (Althabe et al., 2008) [ 33 ] Immediate treatment A prescribing behaviour completed to have an immediate effect on a patient Proportion of patient encounters with antibiotic prescribed (Awad et al., 2006) [ 34 ] Monitoring A prescribing behaviour taken to maintain the quality of longer-term prescriptions Amiodarone for > = 6 months without a thyroid function test in the past 6 months (Avery et al., 2012) [ 35 ] Support A behaviour taken to support the patient to adhere to an ongoing treatment Methotrexate without instructions to take weekly (Avery et al., 2012) [ 35 ] Testing/examination Examination A behaviour related to physically examining a patient Average proportion of paediatric admissions with documentation of weight (Ayieko et al., 2011) [ 36 ] Imaging A behaviour related to the use of imaging to examine a patient % Transthoracic echocardiography ordered that are rarely appropriate (Bhatia et al., 2017) [ 37 ] Laboratory tests A behaviour related to the use of laboratory tests for diagnostic information about a patient Proportion of angina patients with cholesterol checked (Baker et al., 2003) [ 38 ] Treatment decision/action Medication decisions Behavioural decisions or actions relating to the prescription of medication % Patients with sepsis receiving antibiotic therapy within 1 hour (Bloos et al., 2017) [ 39 ] Surgical decisions Behavioural decisions or actions relating to the performance of surgical procedures % Patients with planned caesarean delivery (Chaillet et al., 2015) [ 40 ] Other Treatment decisions/actions that do not fit into the above categories Proportion of patients with Do Not Resuscitate orders in place at time of death (Curtis et al., 2011) [ 41 ] Counselling The provision of advice or training to a patient Proportion of Asthmatic patients advised to avoid passive smoking (Baker et al., 2003) [ 37 ] Diagnosis A clinical diagnosis is made given certain criteria are met or relevant information is available Proportion of asthma diagnoses based on 1 of 3 criteria (Baker et al., 2003) [ 38 ] Immunization Behaviours directly related to the administration of immunizations Mean vaccination rate for influenza at each centre (Bond et al., 2011) [ 42 ] Referral Behaviours related to or the act of providing a patient with a referral to see another specialist Proportion of patients with a dietician visit in the last 60 months (Dijkstra et al., 2005) [ 43 ] Screening The act of pre-emptively assessing patients for otherwise unindicated conditions Proportion of patients at or above target for HbA1c measurement in previous 12 months (Ornstein, 2004) [ 44 ] Table 1 . Description and examples of the categories and subcategories or target behaviours used within the study [Table 1 here, page 31] Categorisation of target behaviours as implemented or de-implemented The original dataset lacked information on whether target behaviours were being implemented or de-implemented, so additional data abstraction was completed. A binary classification proved too simplistic, as some entries combined multiple separable behaviours. When these behaviours were affected in the same direction (e.g., “proportion of patients prescribed and administered any psychotropic”), classification was straightforward. However, if some behaviours were implemented while others were de-implemented, as in the meeting of guidelines that call for some behaviours to be completed more and others to be halted (e.g., “improving MRSA infection control audit score”), a single label was inaccurate. These were classified as mixed and excluded from the analyses. Data analysis Research aim 1: Logistic regression on the whole sample The primary research question explored whether different BCTs are used to implement a target behaviour versus de-implement it. To investigate this, a logistic regression was fitted to the data with the presence or absence of each BCT as binary predictor variables and whether a target behaviour was intended to be implemented as the outcome variable. For this analysis, individual datapoints represent each target behaviours in each intervention, avoiding the simplifying assumption that all target behaviours in an intervention are either being implemented or de-implemented. However, as it was possible that multiple target behaviours were present in the same study, a random effect of study was included within the model. Due to the high number of potential BCTs, only the most frequent BCTs, i.e. those found to be used across 100 target behaviours, were included in the model. The variance inflation factor (VIF) for each predictor was checked and any variables with a VIF above five were removed [ 45 ]. Research Aim 2: Subgroup logistic regression The above analysis was then repeated in subgroups, each containing one type of target behaviour, to investigate whether different techniques are used for implementation and de-implementation depending on the type of target behaviour. The categories in the original dataset were analysed first, followed by the subcategories that were generated in this study. Parallel Analyses The analyses described above use random effects to account for multiple target behaviours within the same study. However, this approach may obscure small but meaningful relationships [ 46 ]. Due to this potential, parallel analyses were conducted that did not rely on random effects, providing an alternative approach to identify smaller effects and replicate the findings of the first analysis. The data were condensed to the intervention level and the proportion of behaviours targeted for implementation within each study was used as the dependent variable. For example, an intervention that aims to implement 4 target behaviours and de-implement 1 had a value of .8. A linear regression was then performed with the same BCT predictors as in Analysis 1, but without random effects. This regression was also repeated within each behaviour category from the original dataset. Results Coding of target behaviours There was a total of 942 target behaviours within the dataset. The intended direction of behaviour change of 749 behaviours was categorised using the stated aims and title of the paper. The remaining 193 were categorised via full-text screening. After this process, all target behaviours were classified as either to be ‘implemented’, ‘de-implemented’, or a mix. Most of the target behaviours in the dataset were being implemented (n = 732), a much smaller number were being de-implemented (n = 179), and fewer still were mixed (n = 31). The descriptive statistics for the sample can be found in Table 2 . Table 2 Descriptive statistics of the sample resulting from the categorisations made in this study Target behaviours Implemented target behaviours Studies implementing at least one target behaviour De-implemented target behaviours Studies de-implementing at least one target behaviour Prescribing 189 89 115 51 Testing/Examination 216 75 41 24 Treatment Decision/Action 96 48 18 12 Counselling 96 46 2 2 Diagnosis 68 41 1 1 Immunization 45 26 0 0 Referral 13 10 2 1 Screening 9 2 0 0 Whole sample 732 196 179 88 Table 2 . Descriptive statistics of the sample resulting from the categorisations made in this study [Table 2 here, page 32] Research aim 1: Logistic regression on the whole sample The first analysis examined whether the presence of different BCTs predicted if a target behaviour was intended to be implemented or de-implemented. The dataset for this analysis included 911 target behaviours, each coded as either implemented (n = 732) or de-implemented (n = 179). Sixteen BCTs met the inclusion threshold of being used in at least 100 target behaviours and were retained as binary predictor variables. These BCTs can be seen in Fig. 1 ., alongside the proportion of target behaviours to which each BCT was applied. The VIFs for all sixteen predictors were below five; therefore, no BCTs were excluded from the final model [ 45 ]. The model included a random effect for ‘study’ to account for clustering of target behaviours within the same intervention. Figure 1 . presents the proportion of implemented and de-implemented target behaviours to which each BCT was applied. The fitted model indicated that none of the 16 BCTs were significantly associated with the log-odds of a target behaviour being implemented versus de-implemented (Table 3 ). The model’s very low marginal R 2 (marginal R 2 = .006) indicated that the presences of these 16 BCTs explained very little of the overall variance. In contrast, the variable ‘study’ explained a large amount of the variance, indicating that whether a target behaviour was implemented or de-implemented was largely influenced by the study in which the behaviour was reported. Table 3 Outputs from the models fitted as part of the logistic regression analyses. Whole sample Prescribing Testing/Examinations Treatment decision/action Predictors Log-Odds SE p Log-Odds SE p Log-Odds SE p Log-Odds SE p (Intercept) 10.54 3.33 0.002 36.02 81.99 0.660 50.10 13421773.52 1.00 -0.69 2.22 0.756 Goal setting 0.45 1.56 0.776 -2.16 2.35 0.359 8.93 149.73 0.952 1.48 1.46 0.31 Problem solving 0.17 0.17 0.901 0.37 2.06 0.856 - - - 0.46 0.86 0.592 Action planning -0.04 1.94 0.983 0.99 3.59 0.783 -44.9 223.53 0.841 21.25 16960.24 0.999 Discrepancy between current behaviour and goal 0.68 1.28 0.596 1.07 2.05 0.603 -15.22 152.96 0.921 -0.76 0.89 0.397 Feedback on behaviour -2.39 3.25 0.461 -29.13 190.15 0.878 -34.17 53918.1 0.999 2.04 1.93 0.291 Feedback on outcome of behaviour 0.74 1.48 0.619 2.52 2.63 0.337 34.42 173.19 0.842 - - - Social support (unspecified) -0.82 1.7 0.629 -14.2 3.41 < .001 -22.92 173.83 0.895 -2.55 1.56 0.103 Social support (practical) 1.11 1.5 0.457 2.16 2.41 0.37 -7.22 171.6 0.966 -1.28 1.07 0.233 Instruction on how to perform the behaviour -0.25 1.16 0.831 0.67 1.91 0.726 9.23 135.3 0.946 0.02 0.84 0.983 Education 0.41 1.25 0.744 0.32 1.68 0.849 31.81 1616.19 0.984 -0.24 0.92 0.794 Information about health consequences -0.94 1.31 0.472 -1.72 2.21 0.437 -42.08 191.3 0.826 21.13 9180.79 0.998 Social comparison 0.25 1.12 0.827 -0.76 1.65 0.646 19.74 132.44 0.882 2.49 1 0.013 Prompts/Cues 0.82 1.31 0.531 -0.01 2.18 0.995 - - - 1.88 1.18 0.11 Credible source 0.19 1.17 0.873 0.32 1.71 0.852 20.04 136.03 0.883 -1.11 0.92 0.226 Restructuring the social environment 0.07 1.49 0.961 0.56 2.11 0.792 50.16 3893859.38 1 -1.12 0.87 0.202 Adding objects to the environment 1.26 1.83 0.493 0.65 2.46 0.79 57.29 958621.72 1 - - - Random Effects Study 281.19 203.3 20573.97 0 Marginal R 2 0.006 0.126 0.064 0.964 Conditional R 2 0.989 0.986 1 0.964 Figure 1 . The proportion of implemented and de-implemented target behaviours to which each BCT was applied. [Figure 1 here, page 36] Research Aim 2: Subgroup logistic regression Given the high ratio of implemented to de-implemented target behaviours and the predominance of target behaviours in the largest three categories, subgroup analyses were only conducted for prescribing, testing/examination, and treatment decision/action categories. The full regression outputs from the models are presented in Table 3 . and Fig. 2 . shows the proportion of implemented or de-implemented target behaviours to which each BCT was applied within each behaviour category. In the testing/examinations category, two BCTs, “problem solving” and “prompts/cues” had to be excluded as predictors because their VIFs were greater than five. The remaining fourteen predictors were all non-significant. In the prescribing category, all the predictors had VIFs less than five, so the full model could be assessed. The presence of one BCT, “social support (unspecified)”, significantly increased the log-odds that a target behaviour was being de-implemented ( β = -14.20 log-odds, SE = 3.41, p < .001). The other fifteen predictors were all non-significant. Finally, in the treatment decision/action category, two BCTs, “feedback on outcome of behaviour” and “adding objects to the environment”, had to be removed from the model due to high VIFs. Among the remaining fourteen predictors, only the BCT “social comparison” was a significant predictor associated with implementing target behaviours ( β = 2.49 log-odds, SE = 1.00, p = .013). Figure 2 . The proportion of implemented and de-implemented behaviours, by type, to which each BCT was applied. [Figure 2 here, pages 36 and 37] The subcategories immediate treatment and laboratory testing were the only two subcategories of adequate size for analysis. When the model was fitted to the laboratory testing data the 16 BCTs were too multicollinear for any analysis to be completed. The model was successfully fitted to the immediate treatment data. All predictors were included in the model due to low VIFs. None of the BCTs were significantly associated with either implementation or de-implementation. However, the BCT "feedback on outcome(s) of behaviour” was marginally nonsignificant and associated with implementation ( β = 5.43 log-odds, SE = 1.94, p = .053). Table 3 . Outputs from the models fitted as part of the logistic regression analyses. [Table 3 here, pages 33 and 34] Parallel analyses Whole sample linear regression To assess the robustness of findings from the random-effects models, a parallel set of analyses was conducted with data aggregated at the study level. The dependent variable was the proportion of target behaviours within each study that were aimed at implementation. These data were then analysed using a linear regression with the presence of the same sixteen BCTs as in the previous analyses used as predictor variables. The output from this model can be seen in Table 4 . Consistent with the previous analyses conducted on the whole dataset, no BCTs were found to be significantly associated with a change in the proportion of target behaviours being implemented in an A&F intervention. Table 4 Outputs from the models fitted as part of the linear regression analyses. Whole sample Prescribing Testing/Examinations Treatment decision/action Predictors Proportion SE p Proportion SE p Proportion SE p Proportion SE p (Intercept) 0.81 0.14 < .001 0.97 0.31 0.002 0.58 0.22 0.013 0.96 0.24 < .001 Goal setting 0.01 0.08 0.902 -0.05 0.12 0.66 0.08 0.12 0.469 0.04 0.14 0.802 Problem solving 0.07 0.07 0.298 0.03 0.1 0.759 -0.13 0.11 0.231 0.08 0.1 0.419 Action planning -0.02 0.1 0.84 0.06 0.15 0.686 -0.08 0.13 0.596 0.22 0.24 0.364 Discrepancy between current behaviour and goal 0.05 0.06 0.418 0.08 0.1 0.425 -0.03 0.1 0.786 -0.11 0.12 0.364 Feedback on behaviour -0.21 0.13 0.101 -0.4 0.29 0.171 -0.08 0.2 0.701 -0.08 0.2 0.681 Feedback on outcome of behaviour 0.07 0.07 0.352 0.18 0.11 0.093 0.14 0.12 0.241 -0.31 0.12 0.014 Social support (unspecified) -0.05 0.09 0.559 -0.22 0.14 0.123 0.04 0.13 0.749 -0.19 0.17 0.259 Social support (practical) 0.09 0.07 0.167 0.15 0.1 0.745 0.07 0.11 0.525 -0.06 0.11 0.603 Instruction on how to perform the behaviour -0.04 0.06 0.52 0.04 0.1 0.695 0 0.1 0.986 0.07 0.11 0.535 Education 0.02 0.06 0.735 0.06 0.09 0.523 0.24 0.11 0.029 -0.18 0.12 0.136 Information about health consequences -0.06 0.07 0.35 -0.13 0.1 0.192 -0.09 0.12 0.456 0.16 0.12 0.194 Social comparison 0.02 0.06 0.728 -0.07 0.09 0.391 0.12 0.09 0.171 0.18 0.11 0.095 Prompts/Cues 0.08 0.06 0.223 0.03 0.1 0.745 0.02 0.1 0.872 -0.03 0.12 0.839 Credible source 0.02 0.06 0.668 0.02 0.09 0.835 0.06 0.1 0.56 -0.17 0.1 0.096 Restructuring the social environment 0.05 0.07 0.441 0.03 0.11 0.8 0.21 0.12 0.097 -0.17 0.12 0.14 Adding objects to the environment 0.14 0.08 0.077 0.07 0.12 0.576 0.25 0.13 0.066 0.09 0.13 0.465 Subgroup linear regression As was the case with previous subgroup analyses, only the three largest categories of target behaviours contained an adequate number of behaviours to be analysed. The full outputs from the models can be seen in Table 4 . None of the predictors in any of the three linear regressions were multicollinear. In the prescribing subgroup, no BCTs were significant predictors of the proportion of prescribing behaviours being implemented in an intervention. In the testing/examination subcategory, the BCT “education (unspecified)” was significantly linked to an increase in the proportion of testing/examination behaviours being implemented in an intervention ( β = 0.24, SE = 0.11, p = .03). Finally, in the treatment decision/action subcategory, only the BCT “feedback on outcome(s) of behaviour” was significantly associated with a decrease in the proportion of implemented behaviours ( β = -0.31, SE = 0.12, p = .01). Interestingly, this is the reverse of the effect found in other subcategories. Table 4 . Outputs from the models fitted as part of the linear regression analyses. [Table 4 here, pages 34 and 35] Discussion The first aim of this study was to investigate whether the same BCTs are used within A&F interventions in healthcare when implementing versus de-implementing target behaviours. When examining the whole sample of A&F interventions, our analyses demonstrated that the sixteen most commonly used BCTs are all as frequently employed for implementing target behaviours as they are for de-implementing them. None of the predictors were significantly associated with the direction of behaviour change in the main logistic regression, a finding that aligns with previous research on behavioural interventions more broadly [ 21 ], with the exceptions of “feedback on behaviour”, which was found to be associated with implementation, and “restructuring the social environment”, which was associated with de-implementation. These minor discrepancies may be attributable to methodological differences (e.g., inclusion criteria, analytic approach) or to the present study’s focus solely on A&F interventions. Overall, the results of this study are consistent with the notion that, in current practice, the same BCTs are applied regardless of the intended direction of behaviour change. The second aim was to examine whether this pattern of results differed for specific categories of target behaviours. The subgroup analyses revealed that four BCTs were significantly associated with either implementation or de-implementation in particular behaviour types: “social comparison” (implementation of treatment decisions/actions), “social support (unspecified)” (de-implementation of prescribing), “education (unspecified)” (implementation of testing/examination), and “feedback on outcome of behaviour” (de-implementation of treatment decisions/actions). However, these associations were not consistent between the main and parallel analyses, and in some cases, such as “feedback on outcome of behaviour” in treatment decision/action, the direction of association reversed when analyses were aggregated to the study level. This reversal may indicate that the relationship between this BCT and implementation status is context-dependent or influenced by the unit of analysis, with aggregation potentially obscuring patterns visible in individual behaviour-level data. Several explanations could account for these subgroup-specific patterns. For example, the BCT “social comparison” involves presenting an individual’s or a team’s performance relative to others [ 17 ] and it is often used within healthcare to improve care for patients through comparison, presenting clinicians or teams with data showing how their performance compares with that of peers, colleagues, or benchmark standards [ 1 , 2 , 47 ]. While previous literature has suggested that it is used as frequently for implementation as de-implementation [ 21 ], our study revealed that it was being used to implement more than de-implement treatment decisions/actions. However, this effect was only significant in the main regression and was approaching significance in the parallel analysis. This BCT’s association with implementation of treatment decisions/actions - but not with other behaviour types - could reflect contextual differences in how social comparisons are perceived, or the nature of decisions being de-implemented within this category, which may render such comparisons less suitable. Alternatively, the observed effect may be attributable to the lower proportion of de-implemented target behaviours employing “social comparison”, as shown in Fig. 2 . The BCT “feedback on outcome of behaviour” also showed an interesting pattern of usage across our subgroup analyses. “Feedback on outcome of behaviour” provides information on the consequences of behaviour and might be more persuasive for de-implementation when the outcomes are extreme or negative (e.g., patient harm), but more challenging to apply persuasively for implementation, particularly in prescribing where benefits (such as reduced antimicrobial resistance) may be less tangible in the short term [e.g. 48–50]. However, testing this was beyond the scope of this study. Similarly, the identification of “Education (unspecified)” as associated with implementation of testing/examination behaviours may relate to its role in introducing new knowledge or procedures [ 1 , 2 ], while “social support (unspecified), often used for enablement, may lower barriers to adopting new prescribing practices [ 17 ]. [ 17 ]. Enablement is an important component of the implementation of a new behaviour, which may explain why “social support (unspecified)” has been linked to implementation. However, further investigation of this BCT's role in A&F interventions in healthcare would be useful. Overall, these findings indicate that, currently, A&F practice rarely employs different BCTs according to the intended direction of behaviour change. Nevertheless, the observed associations suggest that practitioners may tailor the BCTs used in A&F interventions to particular behaviour types and change directions. It remains unclear whether these patterns reflect genuine differences in effectiveness or are artefacts of prevailing intervention design practices. Future research should experimentally evaluate the impact of aligning BCT choice with both behaviour type and change direction, employing theory-informed designs and preregistered analytic plans to minimise the risk of artefactual findings. Strengths and limitations A key strength of this study is its use of a large, systematically coded dataset of target behaviours from A&F interventions in healthcare, enabling detailed analyses at the level of individual behaviours. This granularity allowed us to avoid the simplifying assumption that all behaviours within an intervention share the same change direction and to model behaviour-level predictors while accounting for study-level clustering. The use of both random-effects logistic regression and parallel analyses using linear regressions provided a more robust assessment of observed associations. However, several limitations should be acknowledged. First, the granularity of our approach may also serve as a limitation, as we had to include random effects in our analyses. These random effects were large and explained the vast majority of variance in our dependent variables. These large random effects may have obscured some small but otherwise real effects. This is in part borne out by the identification of some significant associations and several associations approaching significance in the linear regressions. Our analyses were also limited by only including BCTs which were used 100 or more times. While this threshold was important to ensure sufficient statistical power and to mitigate risks of multi-collinearity, it also meant that only the most frequently used BCTs were considered. There is no theoretical rationale to suggest that these BCTs should be more suited for implementation or de-implementation than others within the taxonomy. Furthermore, it is plausible that frequently used BCTs are incorporated almost by default into A&F interventions, whereas those that are less commonly included may be used more intentionally with greater consideration of intervention characteristics such as the intended direction of behaviour change. It is also important to note that the exploratory nature of the subgroup analyses, combined with the number of statistical tests conducted, increases the risk of Type I error. No correction for multiple comparisons was applied, as the primary objective was to identify potential associations, even if these were accompanied by lower confidence. Consequently, the findings - particularly those from subgroup analyses - should be interpreted as preliminary. Moreover, although the inclusion of random effects addressed clustering, differences between the behaviour-level and study-level analyses (as in the reversal observed for “feedback on outcome of behaviour”) highlight that results may be sensitive to the unit of analysis. Finally, the study was not designed to determine whether particular BCTs are used more successfully for implementing versus de-implementing target behaviours. Implications for future research and practice This study offers strong evidence that, in most cases, the same BCTs are used for implementing and de-implementing target behaviours regardless of their types. This is an important finding with potential implications for both theory and practice. If certain BCTs would be more suitable for implementing target behaviours than de-implementing [ 21 , 22 , 24 , 25 ], then current practices could be improved by tailoring intervention strategies accordingly. Understanding which BCTs work best in each context could enhance the effectiveness of behaviour change interventions. Conversely, if BCTs are equally suitable for implementing and de-implementing, as reflected in current practice, then this finding has theoretical significance. It would suggest that BCTs operate through mechanisms that are broadly applicable across both processes, challenging assumptions that different strategies are needed for implementation versus de-implementation. The current study did not test which of these two hypotheses is accurate, so future research should aim to investigate this premise. This finding highlights the need for further investigation to determine whether these BCTs are being used because they enhance intervention effectiveness or if their usage is simply an artefact of current practices. Understanding this distinction could help enhance the application of more effective BCTs in A&F interventions. Additionally, another future aim would be to investigate whether the same combinations of BCTs are being used for implementing and de-implementing across behaviour types as opposed to singular BCTs. As such, future research should focus on these areas to refine theoretical understanding and improve practical application. For practice, implementers of A&F interventions should consider whether the BCTs selected are appropriate for both the clinical behaviour targeted and the intended direction of change. Although this study does not establish causal effects, it provides a preliminary “menu” of potentially relevant BCTs for different contexts, which can be refined through stakeholder engagement and empirical testing. Conclusion The present findings suggest that current A&F practice does not typically tailor BCT selection to the intended direction of behaviour change. However, exploratory subgroup analyses indicate that certain BCTs, such as “social comparison,” “feedback on outcome of behaviour,” “education (unspecified),” and “social support (unspecified)”, may be differentially associated with implementation or de-implementation within specific behaviour types. While these associations require confirmation in randomised controlled studies, they raise the possibility that more targeted selection of BCTs could enhance intervention effectiveness. These findings highlight the need for further investigation to determine whether these BCTs are being used because they enhance intervention effectiveness or if their usage is simply an artefact of current practices. Understanding this distinction could help enhance the application of more effective BCTs in A&F interventions. Abbreviations A&F Audit and Feedback BCT(s) Behaviour Change Technique(s) HCP(s) Health Care Professional(s) BCTTV1 Behaviour Change Technique Taxonomy Version 1 VIF Variance Inflation Factor Declarations Ethics approval and consent to participate: Not applicable Consent for publication: Not applicable Funding: Not applicable Authors’ contributions: HD led the analysis and wrote the first draft of this manuscript, under the supervision of VA. AP, JMG, JC, JP, NI, and FL provided suggestions for the design of this work and supported the interpretation of the data. All authors reviewed and commented on the final draft of this manuscript. Acknowledgements: Not applicable Availability of data and materials: The syntax and analysis document is available on OSF (https://osf.io/dsp8t/) while access to the dataset of the current study can be provided from the corresponding author on reasonable request. Competing interests: The authors declare that they have no competing interests. References Ivers N, Yogasingam S, Lacroix M, Brown KA, Antony J, Soobiah C, Simeoni M, Willis TA, Crawshaw J, Antonopoulou V, Meyer C. Audit and feedback: effects on professional practice. Cochrane Database Syst Reviews. 2025(3). Crawshaw J, Meyer C, Antonopoulou V, Antony J, Grimshaw JM, Ivers N, Konnyu K, Lacroix M, Presseau J, Simeoni M, Yogasingam S. Identifying behaviour change techniques in 287 randomized controlled trials of audit and feedback interventions targeting practice change among healthcare professionals. Implement Sci. 2023;18(1):63. Sykes M, Rosenberg-Yunger ZR, Quigley M, Gupta L, Thomas O, Robinson L, Caulfield K, Ivers N, Alderson S. Exploring the content and delivery of feedback facilitation co-interventions: a systematic review. Implement Sci. 2024;19(1):37. Badejo O, Saleeb M, Hall A, Furlong B, Logan GS, Gao Z, Barrett B, Alcock L, Aubrey-Bassler K. Audit and feedback to change diagnostic image ordering practices: A systematic review and meta-analysis. PLoS ONE. 2024;19(6):e0300001. Ivers NM, Sales A, Colquhoun H, Michie S, Foy R, Francis JJ, Grimshaw JM. No more ‘business as usual’with audit and feedback interventions: towards an agenda for a reinvigorated intervention. Implement Sci. 2014;9:1–8. Jamtvedt G, Flottorp S, Ivers N. Audit and feedback as a quality strategy. Improving Healthc Qual Europe 2019 Oct 17:265. Hepner KA, Rowe M, Rost K, Hickey SC, Sherbourne CD, Ford DE, Meredith LS, Rubenstein LV. The effect of adherence to practice guidelines on depression outcomes. Ann Intern Med. 2007;147(5):320–9. Donnellan C, Sweetman S, Shelley E. Health professionals’ adherence to stroke clinical guidelines: a review of the literature. Health Policy. 2013;111(3):245–63. Chiew KL, Chong S, Duggan KJ, Kaadan N, Vinod SK. Assessing guideline adherence and patient outcomes in cervical cancer. Asia-Pac J Clin Oncol. 2017;13(5):e373–80. O'Brien MA, Oxman AD, Davis D, Haynes RB, Freemantle N, Harvey E. Audit and feedback versus alternative strategies: effects on professional practice and health care outcomes. Cochrane Database Syst Rev. 1998;1998(1). Jamtvedt G, Young JM, Kristoffersen DT, O'Brien MA, Oxman AD. Audit and feedback: effects on professional practice and health care outcomes. Cochrane database Syst reviews. 2006(2). Ivers N, Jamtvedt G, Flottorp S, Young JM, Odgaard-Jensen J, French SD, O'Brien MA, Johansen M, Grimshaw J, Oxman AD. Audit and feedback: effects on professional practice and healthcare outcomes. Cochrane database Syst reviews. 2012(6). Foy R, Eccles MP, Jamtvedt G, Young J, Grimshaw JM, Baker R. What do we know about how to do audit and feedback? Pitfalls in applying evidence from a systematic review. BMC Health Serv Res. 2005;5:1–7. Strömmer S, Lawrence W, Shaw S, Simao SC, Jenner S, Barrett M, Vogel C, Hardy-Johnson P, Farrell D, Woods-Townsend K, Baird J. Behaviour change interventions: getting in touch with individual differences, values and emotions. J Dev Origins Health Disease. 2020;11(6):589–98. Improved Clinical Effectiveness through Behavioural Research Group (ICEBeRG) martin. eccles@ ncl.ac.uk. Designing theoretically-informed implementation interventions. Implement Sci. 2006;1(1):4. Colquhoun H, Michie S, Sales A, Ivers N, Grimshaw JM, Carroll K, Chalifoux M, Eva K, Brehaut J. Reporting and design elements of audit and feedback interventions: a secondary review. BMJ Qual Saf. 2017;26(1):54–60. Michie S, Richardson M, Johnston M, Abraham C, Francis J, Hardeman W, Eccles MP, Cane J, Wood CE. The behavior change technique taxonomy (v1) of 93 hierarchically clustered techniques: building an international consensus for the reporting of behavior change interventions. Ann Behav Med. 2013;46(1):81–95. Davies P, Walker AE, Grimshaw JM. A systematic review of the use of theory in the design of guideline dissemination and implementation strategies and interpretation of the results of rigorous evaluations. Implement Sci. 2010;5:1–6. Colquhoun HL, Brehaut JC, Sales A, Ivers N, Grimshaw J, Michie S, Carroll K, Chalifoux M, Eva KW. A systematic review of the use of theory in randomized controlled trials of audit and feedback. Implement Sci. 2013;8:1–8. Davis R, Campbell R, Hildon Z, Hobbs L, Michie S. Theories of behaviour and behaviour change across the social and behavioural sciences: a scoping review. Health Psychol Rev. 2015;9(3):323–44. Patey AM, Grimshaw JM, Francis JJ. Changing behaviour, ‘more or less’: do implementation and de-implementation interventions include different behaviour change techniques? Implement Sci. 2021;16:1–7. Patey AM, Hurt CS, Grimshaw JM, Francis JJ. Changing behaviour ‘more or less’—do theories of behaviour inform strategies for implementation and de-implementation? A critical interpretive synthesis. Implement Sci. 2018;13:1–3. Prusaczyk B, Swindle T, Curran G. Defining and conceptualizing outcomes for de-implementation: key distinctions from implementation outcomes. Implement Sci Commun. 2020;1:1–0. Gifford EV, Tavakoli S, Weingardt KR, Finney JW, Pierson HM, Rosen CS, Hagedorn HJ, Cook JM, Curran GM. How do components of evidence-based psychological treatment cluster in practice? a survey and cluster analysis. J Subst Abuse Treat. 2012;42(1):45–55. Olsson TM, von Thiele Schwarz U, Hasson H, Vira EG, Sundell K, Adapted. Adopted, and Novel Interventions: A Whole-Population Meta-Analytic Replication of Intervention Effects. Research on social work practice. Dec. 2023;6:10497315231218646. Ivers N, Antony J, Konnyu K, O’Connor D, Presseau J, Grimshaw JM. Audit and feedback: effects on professional practice [protocol for a Cochrane review update]. Zenodo. 2022. Presseau J, Ivers NM, Newham JJ, Knittle K, Danko KJ, Grimshaw JM. Using a behaviour change techniques taxonomy to identify active ingredients within trials of implementation interventions for diabetes care. Implement Sci. 2015;10:1–0. Patey AM, Fontaine G, Francis JJ, McCleary N, Presseau J, Grimshaw JM. Healthcare professional behaviour: health impact, prevalence of evidence-based behaviours, correlates and interventions. Psychol Health. 2023;38(6):766–94. Everett GD, deBlois CS, Chang PF. Effect of cost education, cost audits, and faculty chart review on the use of laboratory services. Arch Intern Med. 1983;143(5):942–4. Gullion DS, Tschann JM, Adamson ET, Coates TJ. Management of hypertension in private practice: a randomized controlled trial in continuing medical education. J Continuing Educ Health Professions. 1988;8(4):239–55. Gascon Canovas JJ, Saturno Hernández PJ, Anton Botella JJ. Effectiveness of internal quality assurance programmes in improving clinical practice and reducing costs. J Eval Clin Pract. 2009;15(5):813–9. Cheater FM, Baker R, Reddish S, Spiers N, Wailoo A, Gillies C, Robertson N, Cawood C. Cluster randomized controlled trial of the effectiveness of audit and feedback and educational outreach on improving nursing practice and patient outcomes. Med Care. 2006;44(6):542–51. Althabe F, Buekens P, Bergel E, Belizán JM, Campbell MK, Moss N, Hartwell T, Wright LL. A behavioral intervention to improve obstetrical care. N Engl J Med. 2008;358(18):1929–40. Awad AI, Eltayeb IB, Baraka OZ. Changing antibiotics prescribing practices in health centers of Khartoum State. Sudan Eur J Clin Pharmacol. 2006;62:135–42. Avery AJ, Rodgers S, Cantrill JA, Armstrong S, Cresswell K, Eden M, Elliott RA, Howard R, Kendrick D, Morris CJ, Prescott RJ. A pharmacist-led information technology intervention for medication errors (PINCER): a multicentre, cluster randomised, controlled trial and cost-effectiveness analysis. Lancet. 2012;379(9823):1310–9. Ayieko P, Ntoburi S, Wagai J, Opondo C, Opiyo N, Migiro S, Wamae A, Mogoa W, Were F, Wasunna A, Fegan G. A multifaceted intervention to implement guidelines and improve admission paediatric care in Kenyan district hospitals: a cluster randomised trial. PLoS Med. 2011;8(4):e1001018. Bhatia RS, Ivers NM, Yin XC, Myers D, Nesbitt GC, Edwards J, Yared K, Wadhera RK, Wu JC, Kithcart AP, Wong BM. Improving the appropriate use of transthoracic echocardiography: the Echo WISELY Trial. J Am Coll Cardiol. 2017;70(9):1135–44. Baker R, Fraser RC, Stone M, Lambert P, Stevenson K, Shiels C. Randomised controlled trial of the impact of guidelines, prioritized review criteria and feedback on implementation of recommendations for angina and asthma. Br J Gen Pract. 2003;53(489):284–91. Bloos F, Rueddel H, Thomas-Rueddel D, Schwarzkopf D, Pausch C, Harbarth S, Schreiber T, Gründling M, Marshall J, Simon P, Levy MM. Effect of a multifaceted educational intervention for anti-infectious measures on sepsis mortality: a cluster randomized trial. Intensive Care Med. 2017;43:1602–12. Chaillet N, Dumont A, Abrahamowicz M, Pasquier JC, Audibert F, Monnier P, Abenhaim HA, Dubé E, Dugas M, Burne R, Fraser WD. A cluster-randomized trial to reduce cesarean delivery rates in Quebec. N Engl J Med. 2015;372(18):1710–21. Curtis JR, Nielsen EL, Treece PD, Downey L, Dotolo D, Shannon SE, Back AL, Rubenfeld GD, Engelberg RA. Effect of a quality-improvement intervention on end-of-life care in the intensive care unit: a randomized trial. Am J Respir Crit Care Med. 2011;183(3):348–55. Bond TC, Patel PR, Krisher J, Sauls L, Deane J, Strott K, McClellan W. A group-randomized evaluation of a quality improvement intervention to improve influenza vaccination rates in dialysis centers. Am J Kidney Dis. 2011;57(2):283–90. Dijkstra RF, Braspenning JC, Huijsmans Z, Akkermans RP, Van Ballegooie E, Ten Have P, Casparie T, Grol RP. Introduction of diabetes passports involving both patients and professionals to improve hospital outpatient diabetes care. Diabetes Res Clin Pract. 2005;68(2):126–34. Ornstein S, Jenkins RG, Nietert PJ, Feifer C, Roylance LF, Nemeth L, Corley S, Dickerson L, Bradford WD, Litvin C. A multimethod quality improvement intervention to improve preventive cardiovascular care: a cluster randomized trial. Ann Intern Med. 2004;141(7):523–32. Meyer C, Goffe L, Antonopoulou V, Graham F, Tang MY, Lecouturier J, Grimani A, Chadwick P, Sniehotta FF. Using the precaution adoption process model to understand decision-making about the COVID-19 booster vaccine in England. Vaccine. 2023;41(15):2466–75. Kain MP, Bolker BM, McCoy MW. A practical guide and power analysis for GLMMs: detecting among treatment variation in random effects. PeerJ. 2015;3:e1226. Hallsworth M, Chadborn T, Sallis A, Sanders M, Berry D, Greaves F, Clements L, Davies SC. Provision of social norm feedback to high prescribers of antibiotics in general practice: a pragmatic national randomised controlled trial. Lancet. 2016;387(10029):1743–52. Gjelstad S, Høye S, Straand J, Brekke M, Dalen I, Lindbæk M. Improving antibiotic prescribing in acute respiratory tract infections: cluster randomised trial from Norwegian general practice (prescription peer academic detailing (Rx-PAD) study). BMJ. 2013;347. Hallsworth M, Chadborn T, Sallis A, Sanders M, Berry D, Greaves F, Clements L, Davies SC. Provision of social norm feedback to high prescribers of antibiotics in general practice: a pragmatic national randomised controlled trial. Lancet. 2016;387(10029):1743–52. Molloy E, Borrell-Carrio F, Epstein R. The impact of emotions in feedback. In Feedback in higher and professional education 2012 Dec 12 (pp. 50–71). Routledge. Cite Share Download PDF Status: Under Review Version 1 posted Editorial decision: Major revision 08 Feb, 2026 Reviewers agreed at journal 15 Oct, 2025 Reviewers invited by journal 29 Sep, 2025 Editor assigned by journal 04 Sep, 2025 First submitted to journal 02 Sep, 2025 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. 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2","display":"","copyAsset":false,"role":"figure","size":27331,"visible":true,"origin":"","legend":"\u003cp\u003eThe proportion of implemented and de-implemented behaviours, by type, to which each BCT was applied.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003e\u003cstrong\u003eNote\u003c/strong\u003e\u003c/em\u003e. The BCTs in this graph are depicted by their numerical labels. For a translation of these numbers see Figure 1.\u003c/p\u003e","description":"","filename":"floatimage2.png","url":"https://assets-eu.researchsquare.com/files/rs-7519867/v1/c90af8517ba41d2b3f3d27c6.png"},{"id":93267218,"identity":"4c94b06e-8c21-4aae-97e2-c014f34c2068","added_by":"auto","created_at":"2025-10-10 20:33:59","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1549198,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7519867/v1/9c007a61-a2ee-4801-a6d4-0b9d50e92d3e.pdf"}],"financialInterests":"","formattedTitle":"Trends in behaviour change techniques for implementing and de-Implementing healthcare practices using audit and feedback","fulltext":[{"header":"Contributions to the literature","content":"\u003cul\u003e\n \u003cli\u003eThis study is the first to use inferential statistics to examine whether audit and feedback (A\u0026amp;F) interventions contain different behaviour change techniques (BCTs) for different types of behaviour and implementation versus de-implementation in healthcare.\u003c/li\u003e\n \u003cli\u003eConducting this analysis at a granular level and supplementing it with exploratory subgroup analyses, this study aimed to identify any such differences.\u0026nbsp;\u003c/li\u003e\n \u003cli\u003eFindings demonstrate that the same BCTs are used for implementation and de-implementation, suggesting practice does not reflect the view that distinct BCTs are required for each.\u003c/li\u003e\n \u003cli\u003eThis work highlights potential limitations in A\u0026amp;F design and calls for future research testing whether aligning BCTs with behaviour change direction improves effectiveness.\u003c/li\u003e\n\u003c/ul\u003e\n\u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e"},{"header":"Introduction","content":"\u003cp\u003eAudit and feedback (A\u0026amp;F) is a type of behaviour change intervention in which a summary of a healthcare professional\u0026rsquo;s (HCP) clinical performance is produced over a specified period and compared to a standard (e.g., clinical guidelines) to promote behaviour change [\u003cspan additionalcitationids=\"CR2 CR3\" citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. It is used in many healthcare organisations internationally to change HCPs\u0026rsquo; behaviours, thereby, promoting evidence-based practices and discouraging those that are ineffective [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. This process ensures that clinical performance is aligned with best practice, which is vital for improving the health outcomes of patients [\u003cspan additionalcitationids=\"CR8\" citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eExtensive research has examined the effectiveness and underlying mechanisms of A\u0026amp;F in healthcare [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. Meta-analyses consistently indicate that, on average, A\u0026amp;F results in small to moderate improvements in desired clinical practices within healthcare settings [\u003cspan additionalcitationids=\"CR11\" citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. However, this effect is highly variable [\u003cspan additionalcitationids=\"CR11\" citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. Many different contextual factors may contribute to this variability, such as the environment in which the intervention is operating [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e] and the intervention\u0026rsquo;s target population [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. Furthermore, there is evidence that features of the interventions, such as their content, may also contribute to differences in effectiveness [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e, \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eRecent research has highlighted significant variability in the content of A\u0026amp;F interventions [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e], particularly the behaviour change techniques (BCTs) they employ. BCTs are \u0026ldquo;observable, replicable and irreducible components of an intervention that are designed to alter or redirect causal processes regulating behaviour\u0026rdquo; [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e, p.82]. They are the active components of behavioural interventions, and so it is possible that the variation in which BCTs are used accounts for the variability in intervention effectiveness. Given this potential to influence intervention outcomes, investigating why different BCTs are used across A\u0026amp;F interventions may provide insights into current design practices and generate hypotheses for future research.\u003c/p\u003e\u003cp\u003eThe variability in which BCTs are used is often attributed to the fact that many interventions are developed without a clear grounding in behaviour change theory [\u003cspan additionalcitationids=\"CR19\" citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]. Consequently, A\u0026amp;F interventions may depend on suboptimal strategies for influencing behaviour, with design and implementation decisions driven by practical considerations, intuition, or other undocumented decision-making processes. However, it has also been suggested that certain characteristics of the behaviours targeted by A\u0026amp;F interventions may impact which BCTs they use. Two examples are the intended direction of behaviour change and the type of healthcare behaviour being acted on [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e, \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eThe intended direction of behaviour change refers to whether an intervention aims to implement a target behaviour, adopting a new practice or increasing its frequency of occurrence, or de-implement it, stopping a harmful or outdated practice or decreasing its frequency of occurrence [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]. This distinction between implementation and de-implementation is relatively new [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]. As a result, there is an ongoing debate over whether different BCTs are required for implementation versus de-implementation. If different behavioural strategies are needed, A\u0026amp;F designers may consider whether the target behaviour is being implemented or de-implemented when identifying which BCTs to include in their intervention [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e, \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eAdditionally, related target behaviours, such as those supporting mental health, may have common behavioural determinants [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e] meaning that the same BCTs may be effective when acting on similar target behaviours [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]. Thus, A\u0026amp;F designers may select BCTs according to the type of target behaviour being targeted. Investigating whether these factors are considered in A\u0026amp;F design is important for understanding the current practice and guiding future improvements.\u003c/p\u003e\u003cp\u003eA recent review [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e] tested these premises across a sample of different types of behavioural interventions in healthcare, including but not specific to A\u0026amp;F. It found that different BCTs were used depending on the direction of behaviour change and the type of target behaviour [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]. However, there was no investigation using inferential statistics to determine whether this finding applies specifically to A\u0026amp;F interventions. Furthermore, the study relied on an overarching assumption, describing each intervention based on its general goal of either implementing or de-implementing one type of target behaviour. This description simplifies analysis but may not accurately reflect most A\u0026amp;F interventions, which often act on multiple different types of target behaviours simultaneously [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e], with some being implemented and others de-implemented.\u003c/p\u003e\u003cp\u003eOur study sought to investigate the extent to which A\u0026amp;F intervention content differs between implementation and de-implementation and whether this content is based on the specific type of behaviour being targeted. This may guide future studies on the effectiveness of current practices, and help determine whether A\u0026amp;F interventions should be adapted based on whether they aim to promote or reduce certain behaviours within healthcare. To address this, the current study refines previous methodologies to examine whether: 1) A\u0026amp;F interventions utilise different BCTs depending on if they are implementing or de-implementing their target behaviours; 2) the type of target behaviour influences this relationship.\u003c/p\u003e"},{"header":"Method","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\u003ch2\u003eDesign\u003c/h2\u003e\u003cp\u003eThe current study is an exploratory secondary analysis of the recent Cochrane review of audit and feedback [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e] It utilises a dataset of BCTs used in A\u0026amp;F interventions, produced as part the review. Additional data was also extracted from the original sample for the purposes of this study. This included whether each behaviour was targeted to be implemented or de-implemented and a more granular description of the type of target behaviour.\u003c/p\u003e\u003c/div\u003e\n\u003ch3\u003eSample\u003c/h3\u003e\n\u003cp\u003eThe original dataset included 287 A\u0026amp;F studies, published before 2020, which had been selected for an analysis of BCTs in A\u0026amp;F as part of an update of the Cochrane systematic review of A\u0026amp;F interventions [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. The full list of the included studies as well as the search strategy and eligibility criteria are reported elsewhere [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e, \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]. The dataset includes only interventions that were part of randomised control trials or cluster randomised control trials that used A\u0026amp;F as either a standalone or cointervention to change HCPs\u0026rsquo; practices [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eOf the 287 studies in the dataset, 261 were included in the analyses. We extracted data relating to the target behaviours of the studies, the content of the interventions, and the aims of the studies. 26 studies from the original dataset had incomplete data with regards to these variables. As a result, these studies were excluded from the analyses, leaving 261 in the final sample.\u003c/p\u003e\n\u003ch3\u003eMeasures\u003c/h3\u003e\n\u003cdiv id=\"Sec6\" class=\"Section2\"\u003e\u003ch2\u003eIntervention content\u003c/h2\u003e\u003cp\u003eThe original dataset describes intervention content in terms of BCTs. The behaviour change technique taxonomy version 1 (BCTTv1) [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e] was used to categorise intervention content. The BCTTv1 includes 93 different BCTs, which have been used widely and successfully to identify the key active components of different interventions [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e, \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]. In addition to the BCTTV1, an A\u0026amp;F codebook - specifically developed to code A\u0026amp;F intervention content - included 2 additional BCTs, education (unspecified) and feedback (unspecified). Each intervention was coded for the presence or absence of the 95 BCTs.\u003c/p\u003e\u003c/div\u003e\n\u003ch3\u003eTypes of target behaviour\u003c/h3\u003e\n\u003cp\u003eTarget behaviours were identified in the original systematic review by the outcome variables used in the source studies to measure intervention success [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. In cases where there were multiple measures of a single behaviour, judgement was used to ensure that a single target behaviour was not included in the dataset multiple times. The target behaviours were grouped into eight different categories in the original dataset: prescribing, testing/examination, treatment decision/action, counselling, immunization, referrals, diagnosis, and screening.\u003c/p\u003e\u003cp\u003eThe original categories are potentially broad and may not reflect the way that intervention designers think about target behaviours. As such, the three largest categories of target behaviours (prescribing, testing/examination, and treatment decision/action) were segmented into more granular categories by the research team. Prescribing was further divided into the following subcategories: prophylaxis, immediate treatment, monitoring, and support. These were selected because they reflect a difference in the immediacy of the action being taken (proactive, immediate, longstanding) which is a distinction that has previously been made in the literature [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]. The final subcategory, support, was created as several target behaviours related more to the encouragement of adherence to medication than to prescription in its truest sense. The testing/examinations category was divided into the subcategories: examinations, imaging, and laboratory tests. These three subcategories reflect distinctions that were included in many of the papers [e.g. 29\u0026ndash;32] and refer to different categories of techniques commonly used for testing/examination. Finally, treatment decision/action was separated into the categories: medication decisions, surgical decisions, and other. The first two subcategories reflect two large observed groups within the dataset. However, due to the high variability in the treatment decisions/actions category, it was necessary to include an additional category of \u0026lsquo;other\u0026rsquo; to describe a large portion of this subgroup. A description of each behavioural category, subcategory, and examples can be found in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. All target behaviours that fell into the three higher-order categories were recategorized into subcategories based on the description of the outcome variable used to measure the target behaviour.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eDescription and examples of the categories and subcategories or target behaviours used within the study.\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"3\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eBehaviour subcategory\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eDescription\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eExample and source\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePrescribing\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003eProphylaxis\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eA prescribing behaviour completed to prevent a disease or future negative outcome\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eRates of prophylactic use of oxytocin (Althabe et al., 2008) [\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e]\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003eImmediate treatment\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eA prescribing behaviour completed to have an immediate effect on a patient\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eProportion of patient encounters with antibiotic prescribed (Awad et al., 2006) [\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e]\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003eMonitoring\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eA prescribing behaviour taken to maintain the quality of longer-term prescriptions\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eAmiodarone for \u0026gt;\u0026thinsp;=\u0026thinsp;6 months without a thyroid function test in the past 6 months (Avery et al., 2012) [\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e]\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003eSupport\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eA behaviour taken to support the patient to adhere to an ongoing treatment\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eMethotrexate without instructions to take weekly (Avery et al., 2012) [\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e]\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eTesting/examination\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003eExamination\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eA behaviour related to physically examining a patient\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eAverage proportion of paediatric admissions with documentation of weight (Ayieko et al., 2011) [\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e]\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003eImaging\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eA behaviour related to the use of imaging to examine a patient\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e% Transthoracic echocardiography ordered that are rarely appropriate (Bhatia et al., 2017) [\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e]\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003eLaboratory tests\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eA behaviour related to the use of laboratory tests for diagnostic information about a patient\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eProportion of angina patients with cholesterol checked (Baker et al., 2003) [\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e]\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eTreatment decision/action\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003eMedication decisions\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eBehavioural decisions or actions relating to the prescription of medication\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e% Patients with sepsis receiving antibiotic therapy within 1 hour (Bloos et al., 2017) [\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e]\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003eSurgical decisions\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eBehavioural decisions or actions relating to the performance of surgical procedures\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e% Patients with planned caesarean delivery (Chaillet et al., 2015) [\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e]\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003eOther\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eTreatment decisions/actions that do not fit into the above categories\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eProportion of patients with Do Not Resuscitate orders in place at time of death (Curtis et al., 2011) [\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e]\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eCounselling\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eThe provision of advice or training to a patient\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eProportion of Asthmatic patients advised to avoid passive smoking (Baker et al., 2003) [\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e]\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eDiagnosis\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eA clinical diagnosis is made given certain criteria are met or relevant information is available\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eProportion of asthma diagnoses based on 1 of 3 criteria (Baker et al., 2003) [\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e]\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eImmunization\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eBehaviours directly related to the administration of immunizations\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eMean vaccination rate for influenza at each centre (Bond et al., 2011) [\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e]\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eReferral\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eBehaviours related to or the act of providing a patient with a referral to see another specialist\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eProportion of patients with a dietician visit in the last 60 months (Dijkstra et al., 2005) [\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e]\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eScreening\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eThe act of pre-emptively assessing patients for otherwise unindicated conditions\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eProportion of patients at or above target for HbA1c measurement in previous 12 months (Ornstein, 2004) [\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e]\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. Description and examples of the categories and subcategories or target behaviours used within the study\u003c/p\u003e\u003cp\u003e[Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e here, page 31]\u003c/p\u003e\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e\u003ch2\u003eCategorisation of target behaviours as implemented or de-implemented\u003c/h2\u003e\u003cp\u003eThe original dataset lacked information on whether target behaviours were being implemented or de-implemented, so additional data abstraction was completed. A binary classification proved too simplistic, as some entries combined multiple separable behaviours. When these behaviours were affected in the same direction (e.g., \u0026ldquo;proportion of patients prescribed and administered any psychotropic\u0026rdquo;), classification was straightforward. However, if some behaviours were implemented while others were de-implemented, as in the meeting of guidelines that call for some behaviours to be completed more and others to be halted (e.g., \u0026ldquo;improving MRSA infection control audit score\u0026rdquo;), a single label was inaccurate. These were classified as mixed and excluded from the analyses.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec9\" class=\"Section2\"\u003e\u003ch2\u003eData analysis\u003c/h2\u003e\u003cdiv id=\"Sec10\" class=\"Section3\"\u003e\u003ch2\u003eResearch aim 1: Logistic regression on the whole sample\u003c/h2\u003e\u003cp\u003eThe primary research question explored whether different BCTs are used to implement a target behaviour versus de-implement it. To investigate this, a logistic regression was fitted to the data with the presence or absence of each BCT as binary predictor variables and whether a target behaviour was intended to be implemented as the outcome variable. For this analysis, individual datapoints represent each target behaviours in each intervention, avoiding the simplifying assumption that all target behaviours in an intervention are either being implemented or de-implemented. However, as it was possible that multiple target behaviours were present in the same study, a random effect of study was included within the model.\u003c/p\u003e\u003cp\u003eDue to the high number of potential BCTs, only the most frequent BCTs, i.e. those found to be used across 100 target behaviours, were included in the model. The variance inflation factor (VIF) for each predictor was checked and any variables with a VIF above five were removed [\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e].\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e\u003ch2\u003eResearch Aim 2: Subgroup logistic regression\u003c/h2\u003e\u003cp\u003eThe above analysis was then repeated in subgroups, each containing one type of target behaviour, to investigate whether different techniques are used for implementation and de-implementation depending on the type of target behaviour. The categories in the original dataset were analysed first, followed by the subcategories that were generated in this study.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec12\" class=\"Section2\"\u003e\u003ch2\u003eParallel Analyses\u003c/h2\u003e\u003cp\u003eThe analyses described above use random effects to account for multiple target behaviours within the same study. However, this approach may obscure small but meaningful relationships [\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e]. Due to this potential, parallel analyses were conducted that did not rely on random effects, providing an alternative approach to identify smaller effects and replicate the findings of the first analysis. The data were condensed to the intervention level and the proportion of behaviours targeted for implementation within each study was used as the dependent variable. For example, an intervention that aims to implement 4 target behaviours and de-implement 1 had a value of .8. A linear regression was then performed with the same BCT predictors as in Analysis 1, but without random effects. This regression was also repeated within each behaviour category from the original dataset.\u003c/p\u003e\u003c/div\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec14\" class=\"Section2\"\u003e\u003ch2\u003eCoding of target behaviours\u003c/h2\u003e\u003cp\u003eThere was a total of 942 target behaviours within the dataset. The intended direction of behaviour change of 749 behaviours was categorised using the stated aims and title of the paper. The remaining 193 were categorised via full-text screening. After this process, all target behaviours were classified as either to be \u0026lsquo;implemented\u0026rsquo;, \u0026lsquo;de-implemented\u0026rsquo;, or a mix. Most of the target behaviours in the dataset were being implemented (n\u0026thinsp;=\u0026thinsp;732), a much smaller number were being de-implemented (n\u0026thinsp;=\u0026thinsp;179), and fewer still were mixed (n\u0026thinsp;=\u0026thinsp;31). The descriptive statistics for the sample can be found in Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eDescriptive statistics of the sample resulting from the categorisations made in this study\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"9\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTarget behaviours\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e\u003cp\u003eImplemented target behaviours\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e\u003cp\u003eStudies implementing at least one target behaviour\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c7\"\u003e\u003cp\u003eDe-implemented target behaviours\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colspan=\"2\" nameend=\"c9\" namest=\"c8\"\u003e\u003cp\u003eStudies de-implementing at least one target behaviour\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u003cp\u003ePrescribing\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e189\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u003cp\u003e89\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"3\" nameend=\"c8\" namest=\"c6\"\u003e\u003cp\u003e115\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e51\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u003cp\u003eTesting/Examination\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e216\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u003cp\u003e75\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"3\" nameend=\"c8\" namest=\"c6\"\u003e\u003cp\u003e41\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e24\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u003cp\u003eTreatment Decision/Action\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e96\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u003cp\u003e48\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"3\" nameend=\"c8\" namest=\"c6\"\u003e\u003cp\u003e18\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e12\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u003cp\u003eCounselling\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e96\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u003cp\u003e46\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"3\" nameend=\"c8\" namest=\"c6\"\u003e\u003cp\u003e2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e2\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u003cp\u003eDiagnosis\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e68\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u003cp\u003e41\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"3\" nameend=\"c8\" namest=\"c6\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u003cp\u003eImmunization\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e45\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u003cp\u003e26\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"3\" nameend=\"c8\" namest=\"c6\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u003cp\u003eReferral\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e13\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u003cp\u003e10\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"3\" nameend=\"c8\" namest=\"c6\"\u003e\u003cp\u003e2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u003cp\u003eScreening\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u003cp\u003e2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"3\" nameend=\"c8\" namest=\"c6\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u003cp\u003eWhole sample\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e732\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u003cp\u003e196\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"3\" nameend=\"c8\" namest=\"c6\"\u003e\u003cp\u003e179\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e88\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e. Descriptive statistics of the sample resulting from the categorisations made in this study\u003c/p\u003e\u003cp\u003e[Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e here, page 32]\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec15\" class=\"Section2\"\u003e\u003ch2\u003eResearch aim 1: Logistic regression on the whole sample\u003c/h2\u003e\u003cp\u003eThe first analysis examined whether the presence of different BCTs predicted if a target behaviour was intended to be implemented or de-implemented. The dataset for this analysis included 911 target behaviours, each coded as either implemented (n\u0026thinsp;=\u0026thinsp;732) or de-implemented (n\u0026thinsp;=\u0026thinsp;179). Sixteen BCTs met the inclusion threshold of being used in at least 100 target behaviours and were retained as binary predictor variables. These BCTs can be seen in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e., alongside the proportion of target behaviours to which each BCT was applied. The VIFs for all sixteen predictors were below five; therefore, no BCTs were excluded from the final model [\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e].\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eThe model included a random effect for \u0026lsquo;study\u0026rsquo; to account for clustering of target behaviours within the same intervention. Figure\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. presents the proportion of implemented and de-implemented target behaviours to which each BCT was applied.\u003c/p\u003e\u003cp\u003eThe fitted model indicated that none of the 16 BCTs were significantly associated with the log-odds of a target behaviour being implemented versus de-implemented (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). The model\u0026rsquo;s very low marginal R\u003csup\u003e2\u003c/sup\u003e (marginal R\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;.006) indicated that the presences of these 16 BCTs explained very little of the overall variance. In contrast, the variable \u0026lsquo;study\u0026rsquo; explained a large amount of the variance, indicating that whether a target behaviour was implemented or de-implemented was largely influenced by the study in which the behaviour was reported.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eOutputs from the models fitted as part of the logistic regression analyses.\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"13\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c11\" colnum=\"11\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c12\" colnum=\"12\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c13\" colnum=\"13\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e\u003cp\u003eWhole sample\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colspan=\"3\" nameend=\"c7\" namest=\"c5\"\u003e\u003cp\u003ePrescribing\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colspan=\"3\" nameend=\"c10\" namest=\"c8\"\u003e\u003cp\u003eTesting/Examinations\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colspan=\"3\" nameend=\"c13\" namest=\"c11\"\u003e\u003cp\u003eTreatment decision/action\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePredictors\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eLog-Odds\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eSE\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u003cem\u003ep\u003c/em\u003e\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eLog-Odds\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003eSE\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c7\"\u003e\u003cp\u003e\u003cem\u003ep\u003c/em\u003e\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c8\"\u003e\u003cp\u003eLog-Odds\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c9\"\u003e\u003cp\u003eSE\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c10\"\u003e\u003cp\u003e\u003cem\u003ep\u003c/em\u003e\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c11\"\u003e\u003cp\u003eLog-Odds\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c12\"\u003e\u003cp\u003eSE\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c13\"\u003e\u003cp\u003e\u003cem\u003ep\u003c/em\u003e\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e(Intercept)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e10.54\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e3.33\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.002\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e36.02\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e81.99\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.660\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e50.10\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e13421773.52\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e1.00\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u003cp\u003e-0.69\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u003cp\u003e2.22\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c13\"\u003e\u003cp\u003e0.756\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eGoal setting\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.45\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1.56\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.776\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e-2.16\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e2.35\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.359\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e8.93\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e149.73\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e0.952\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u003cp\u003e1.48\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u003cp\u003e1.46\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c13\"\u003e\u003cp\u003e0.31\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eProblem solving\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.17\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.17\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.901\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.37\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e2.06\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.856\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u003cp\u003e0.46\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u003cp\u003e0.86\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c13\"\u003e\u003cp\u003e0.592\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAction planning\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e-0.04\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1.94\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.983\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.99\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e3.59\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.783\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e-44.9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e223.53\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e0.841\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u003cp\u003e21.25\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u003cp\u003e16960.24\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c13\"\u003e\u003cp\u003e0.999\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eDiscrepancy between current behaviour and goal\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.68\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1.28\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.596\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1.07\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e2.05\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.603\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e-15.22\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e152.96\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e0.921\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u003cp\u003e-0.76\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u003cp\u003e0.89\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c13\"\u003e\u003cp\u003e0.397\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eFeedback on behaviour\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e-2.39\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e3.25\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.461\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e-29.13\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e190.15\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.878\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e-34.17\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e53918.1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e0.999\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u003cp\u003e2.04\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u003cp\u003e1.93\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c13\"\u003e\u003cp\u003e0.291\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eFeedback on outcome of behaviour\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.74\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1.48\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.619\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e2.52\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e2.63\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.337\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e34.42\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e173.19\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e0.842\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c13\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSocial support (unspecified)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e-0.82\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1.7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.629\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e-14.2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e3.41\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;.001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e-22.92\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e173.83\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e0.895\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u003cp\u003e-2.55\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u003cp\u003e1.56\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c13\"\u003e\u003cp\u003e0.103\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSocial support (practical)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1.11\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1.5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.457\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e2.16\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e2.41\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.37\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e-7.22\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e171.6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e0.966\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u003cp\u003e-1.28\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u003cp\u003e1.07\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c13\"\u003e\u003cp\u003e0.233\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eInstruction on how to perform the behaviour\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e-0.25\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1.16\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.831\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.67\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e1.91\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.726\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e9.23\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e135.3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e0.946\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u003cp\u003e0.02\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u003cp\u003e0.84\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c13\"\u003e\u003cp\u003e0.983\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eEducation\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.41\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1.25\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.744\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.32\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e1.68\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.849\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e31.81\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e1616.19\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e0.984\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u003cp\u003e-0.24\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u003cp\u003e0.92\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c13\"\u003e\u003cp\u003e0.794\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eInformation about health consequences\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e-0.94\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1.31\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.472\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e-1.72\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e2.21\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.437\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e-42.08\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e191.3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e0.826\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u003cp\u003e21.13\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u003cp\u003e9180.79\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c13\"\u003e\u003cp\u003e0.998\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSocial comparison\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.25\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1.12\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.827\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e-0.76\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e1.65\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.646\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e19.74\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e132.44\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e0.882\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u003cp\u003e2.49\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c13\"\u003e\u003cp\u003e0.013\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePrompts/Cues\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.82\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1.31\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.531\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e-0.01\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e2.18\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.995\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u003cp\u003e1.88\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u003cp\u003e1.18\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c13\"\u003e\u003cp\u003e0.11\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCredible source\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.19\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1.17\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.873\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.32\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e1.71\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.852\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e20.04\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e136.03\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e0.883\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u003cp\u003e-1.11\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u003cp\u003e0.92\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c13\"\u003e\u003cp\u003e0.226\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eRestructuring the social environment\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.07\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1.49\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.961\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.56\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e2.11\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.792\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e50.16\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e3893859.38\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u003cp\u003e-1.12\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u003cp\u003e0.87\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c13\"\u003e\u003cp\u003e0.202\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAdding objects to the environment\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1.26\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1.83\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.493\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.65\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e2.46\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.79\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e57.29\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e958621.72\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c13\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eRandom Effects\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eStudy\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e281.19\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e203.3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e20573.97\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMarginal R\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.006\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.126\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e0.064\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u003cp\u003e0.964\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eConditional R\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.989\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.986\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u003cp\u003e0.964\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eFigure \u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. The proportion of implemented and de-implemented target behaviours to which each BCT was applied.\u003c/p\u003e\u003cp\u003e[Figure \u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e here, page 36]\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec16\" class=\"Section2\"\u003e\u003ch2\u003eResearch Aim 2: Subgroup logistic regression\u003c/h2\u003e\u003cp\u003eGiven the high ratio of implemented to de-implemented target behaviours and the predominance of target behaviours in the largest three categories, subgroup analyses were only conducted for prescribing, testing/examination, and treatment decision/action categories. The full regression outputs from the models are presented in Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e. and Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e. shows the proportion of implemented or de-implemented target behaviours to which each BCT was applied within each behaviour category.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eIn the testing/examinations category, two BCTs, \u0026ldquo;problem solving\u0026rdquo; and \u0026ldquo;prompts/cues\u0026rdquo; had to be excluded as predictors because their VIFs were greater than five. The remaining fourteen predictors were all non-significant.\u003c/p\u003e\u003cp\u003eIn the prescribing category, all the predictors had VIFs less than five, so the full model could be assessed. The presence of one BCT, \u0026ldquo;social support (unspecified)\u0026rdquo;, significantly increased the log-odds that a target behaviour was being de-implemented (\u003cem\u003eβ\u003c/em\u003e = -14.20 log-odds, SE\u0026thinsp;=\u0026thinsp;3.41, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;.001). The other fifteen predictors were all non-significant.\u003c/p\u003e\u003cp\u003eFinally, in the treatment decision/action category, two BCTs, \u0026ldquo;feedback on outcome of behaviour\u0026rdquo; and \u0026ldquo;adding objects to the environment\u0026rdquo;, had to be removed from the model due to high VIFs. Among the remaining fourteen predictors, only the BCT \u0026ldquo;social comparison\u0026rdquo; was a significant predictor associated with implementing target behaviours (\u003cem\u003eβ\u003c/em\u003e\u0026thinsp;=\u0026thinsp;2.49 log-odds, SE\u0026thinsp;=\u0026thinsp;1.00, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;.013).\u003c/p\u003e\u003cp\u003eFigure \u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e. The proportion of implemented and de-implemented behaviours, by type, to which each BCT was applied.\u003c/p\u003e\u003cp\u003e[Figure \u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e here, pages 36 and 37]\u003c/p\u003e\u003cp\u003eThe subcategories immediate treatment and laboratory testing were the only two subcategories of adequate size for analysis. When the model was fitted to the laboratory testing data the 16 BCTs were too multicollinear for any analysis to be completed. The model was successfully fitted to the immediate treatment data. All predictors were included in the model due to low VIFs. None of the BCTs were significantly associated with either implementation or de-implementation. However, the BCT \"feedback on outcome(s) of behaviour\u0026rdquo; was marginally nonsignificant and associated with implementation (\u003cem\u003eβ\u003c/em\u003e\u0026thinsp;=\u0026thinsp;5.43 log-odds, SE\u0026thinsp;=\u0026thinsp;1.94, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;.053).\u003c/p\u003e\u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e. Outputs from the models fitted as part of the logistic regression analyses.\u003c/p\u003e\u003cp\u003e[Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e here, pages 33 and 34]\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec17\" class=\"Section2\"\u003e\u003ch2\u003eParallel analyses\u003c/h2\u003e\u003cdiv id=\"Sec18\" class=\"Section3\"\u003e\u003ch2\u003eWhole sample linear regression\u003c/h2\u003e\u003cp\u003eTo assess the robustness of findings from the random-effects models, a parallel set of analyses was conducted with data aggregated at the study level. The dependent variable was the proportion of target behaviours within each study that were aimed at implementation. These data were then analysed using a linear regression with the presence of the same sixteen BCTs as in the previous analyses used as predictor variables. The output from this model can be seen in Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e. Consistent with the previous analyses conducted on the whole dataset, no BCTs were found to be significantly associated with a change in the proportion of target behaviours being implemented in an A\u0026amp;F intervention.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eOutputs from the models fitted as part of the linear regression analyses.\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"13\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c11\" colnum=\"11\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c12\" colnum=\"12\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c13\" colnum=\"13\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e\u003cp\u003eWhole sample\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colspan=\"3\" nameend=\"c7\" namest=\"c5\"\u003e\u003cp\u003ePrescribing\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colspan=\"3\" nameend=\"c10\" namest=\"c8\"\u003e\u003cp\u003eTesting/Examinations\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colspan=\"3\" nameend=\"c13\" namest=\"c11\"\u003e\u003cp\u003eTreatment decision/action\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePredictors\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eProportion\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eSE\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u003cem\u003ep\u003c/em\u003e\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eProportion\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003eSE\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c7\"\u003e\u003cp\u003e\u003cem\u003ep\u003c/em\u003e\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c8\"\u003e\u003cp\u003eProportion\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c9\"\u003e\u003cp\u003eSE\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c10\"\u003e\u003cp\u003e\u003cem\u003ep\u003c/em\u003e\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c11\"\u003e\u003cp\u003eProportion\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c12\"\u003e\u003cp\u003eSE\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c13\"\u003e\u003cp\u003e\u003cem\u003ep\u003c/em\u003e\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e(Intercept)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.81\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.14\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;.001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.97\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.31\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.002\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e0.58\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e0.22\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e0.013\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u003cp\u003e0.96\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u003cp\u003e0.24\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c13\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eGoal setting\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.01\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.08\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.902\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e-0.05\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.12\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.66\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e0.08\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e0.12\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e0.469\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u003cp\u003e0.04\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u003cp\u003e0.14\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c13\"\u003e\u003cp\u003e0.802\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eProblem solving\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.07\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.07\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.298\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.03\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.759\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e-0.13\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e0.11\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e0.231\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u003cp\u003e0.08\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u003cp\u003e0.1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c13\"\u003e\u003cp\u003e0.419\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAction planning\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e-0.02\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.84\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.06\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.15\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.686\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e-0.08\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e0.13\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e0.596\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u003cp\u003e0.22\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u003cp\u003e0.24\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c13\"\u003e\u003cp\u003e0.364\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eDiscrepancy between current behaviour and goal\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.05\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.06\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.418\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.08\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.425\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e-0.03\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e0.1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e0.786\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u003cp\u003e-0.11\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u003cp\u003e0.12\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c13\"\u003e\u003cp\u003e0.364\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eFeedback on behaviour\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e-0.21\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.13\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.101\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e-0.4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.29\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.171\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e-0.08\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e0.2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e0.701\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u003cp\u003e-0.08\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u003cp\u003e0.2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c13\"\u003e\u003cp\u003e0.681\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eFeedback on outcome of behaviour\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.07\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.07\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.352\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.18\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.11\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.093\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e0.14\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e0.12\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e0.241\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u003cp\u003e-0.31\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u003cp\u003e0.12\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c13\"\u003e\u003cp\u003e0.014\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSocial support (unspecified)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e-0.05\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.09\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.559\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e-0.22\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.14\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.123\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e0.04\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e0.13\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e0.749\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u003cp\u003e-0.19\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u003cp\u003e0.17\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c13\"\u003e\u003cp\u003e0.259\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSocial support (practical)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.09\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.07\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.167\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.15\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.745\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e0.07\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e0.11\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e0.525\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u003cp\u003e-0.06\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u003cp\u003e0.11\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c13\"\u003e\u003cp\u003e0.603\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eInstruction on how to perform the behaviour\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e-0.04\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.06\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.52\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.04\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.695\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e0.1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e0.986\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u003cp\u003e0.07\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u003cp\u003e0.11\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c13\"\u003e\u003cp\u003e0.535\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eEducation\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.02\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.06\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.735\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.06\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.09\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.523\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e0.24\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e0.11\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e0.029\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u003cp\u003e-0.18\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u003cp\u003e0.12\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c13\"\u003e\u003cp\u003e0.136\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eInformation about health consequences\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e-0.06\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.07\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.35\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e-0.13\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.192\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e-0.09\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e0.12\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e0.456\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u003cp\u003e0.16\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u003cp\u003e0.12\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c13\"\u003e\u003cp\u003e0.194\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSocial comparison\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.02\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.06\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.728\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e-0.07\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.09\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.391\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e0.12\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e0.09\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e0.171\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u003cp\u003e0.18\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u003cp\u003e0.11\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c13\"\u003e\u003cp\u003e0.095\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePrompts/Cues\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.08\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.06\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.223\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.03\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.745\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e0.02\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e0.1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e0.872\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u003cp\u003e-0.03\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u003cp\u003e0.12\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c13\"\u003e\u003cp\u003e0.839\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCredible source\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.02\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.06\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.668\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.02\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.09\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.835\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e0.06\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e0.1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e0.56\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u003cp\u003e-0.17\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u003cp\u003e0.1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c13\"\u003e\u003cp\u003e0.096\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eRestructuring the social environment\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.05\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.07\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.441\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.03\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.11\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e0.21\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e0.12\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e0.097\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u003cp\u003e-0.17\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u003cp\u003e0.12\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c13\"\u003e\u003cp\u003e0.14\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAdding objects to the environment\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.14\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.08\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.077\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.07\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.12\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.576\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e0.25\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e0.13\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e0.066\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u003cp\u003e0.09\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u003cp\u003e0.13\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c13\"\u003e\u003cp\u003e0.465\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv id=\"Sec19\" class=\"Section2\"\u003e\u003ch2\u003eSubgroup linear regression\u003c/h2\u003e\u003cp\u003eAs was the case with previous subgroup analyses, only the three largest categories of target behaviours contained an adequate number of behaviours to be analysed. The full outputs from the models can be seen in Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e. None of the predictors in any of the three linear regressions were multicollinear. In the prescribing subgroup, no BCTs were significant predictors of the proportion of prescribing behaviours being implemented in an intervention. In the testing/examination subcategory, the BCT \u0026ldquo;education (unspecified)\u0026rdquo; was significantly linked to an increase in the proportion of testing/examination behaviours being implemented in an intervention (\u003cem\u003eβ\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.24, SE\u0026thinsp;=\u0026thinsp;0.11, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;.03). Finally, in the treatment decision/action subcategory, only the BCT \u0026ldquo;feedback on outcome(s) of behaviour\u0026rdquo; was significantly associated with a \u003cem\u003edecrease\u003c/em\u003e in the proportion of implemented behaviours (\u003cem\u003eβ\u003c/em\u003e = -0.31, SE\u0026thinsp;=\u0026thinsp;0.12, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;.01). Interestingly, this is the reverse of the effect found in other subcategories.\u003c/p\u003e\u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e. Outputs from the models fitted as part of the linear regression analyses.\u003c/p\u003e\u003cp\u003e[Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e here, pages 34 and 35]\u003c/p\u003e\u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eThe first aim of this study was to investigate whether the same BCTs are used within A\u0026amp;F interventions in healthcare when implementing versus de-implementing target behaviours. When examining the whole sample of A\u0026amp;F interventions, our analyses demonstrated that the sixteen most commonly used BCTs are all as frequently employed for implementing target behaviours as they are for de-implementing them. None of the predictors were significantly associated with the direction of behaviour change in the main logistic regression, a finding that aligns with previous research on behavioural interventions more broadly [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e], with the exceptions of \u0026ldquo;feedback on behaviour\u0026rdquo;, which was found to be associated with implementation, and \u0026ldquo;restructuring the social environment\u0026rdquo;, which was associated with de-implementation. These minor discrepancies may be attributable to methodological differences (e.g., inclusion criteria, analytic approach) or to the present study\u0026rsquo;s focus solely on A\u0026amp;F interventions. Overall, the results of this study are consistent with the notion that, in current practice, the same BCTs are applied regardless of the intended direction of behaviour change.\u003c/p\u003e\u003cp\u003eThe second aim was to examine whether this pattern of results differed for specific categories of target behaviours. The subgroup analyses revealed that four BCTs were significantly associated with either implementation or de-implementation in particular behaviour types: \u0026ldquo;social comparison\u0026rdquo; (implementation of treatment decisions/actions), \u0026ldquo;social support (unspecified)\u0026rdquo; (de-implementation of prescribing), \u0026ldquo;education (unspecified)\u0026rdquo; (implementation of testing/examination), and \u0026ldquo;feedback on outcome of behaviour\u0026rdquo; (de-implementation of treatment decisions/actions). However, these associations were not consistent between the main and parallel analyses, and in some cases, such as \u0026ldquo;feedback on outcome of behaviour\u0026rdquo; in treatment decision/action, the direction of association reversed when analyses were aggregated to the study level. This reversal may indicate that the relationship between this BCT and implementation status is context-dependent or influenced by the unit of analysis, with aggregation potentially obscuring patterns visible in individual behaviour-level data.\u003c/p\u003e\u003cp\u003eSeveral explanations could account for these subgroup-specific patterns. For example, the BCT \u0026ldquo;social comparison\u0026rdquo; involves presenting an individual\u0026rsquo;s or a team\u0026rsquo;s performance relative to others [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e] and it is often used within healthcare to improve care for patients through comparison, presenting clinicians or teams with data showing how their performance compares with that of peers, colleagues, or benchmark standards [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e]. While previous literature has suggested that it is used as frequently for implementation as de-implementation [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e], our study revealed that it was being used to implement more than de-implement treatment decisions/actions. However, this effect was only significant in the main regression and was approaching significance in the parallel analysis. This BCT\u0026rsquo;s association with implementation of treatment decisions/actions - but not with other behaviour types - could reflect contextual differences in how social comparisons are perceived, or the nature of decisions being de-implemented within this category, which may render such comparisons less suitable. Alternatively, the observed effect may be attributable to the lower proportion of de-implemented target behaviours employing \u0026ldquo;social comparison\u0026rdquo;, as shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e.\u003c/p\u003e\u003cp\u003eThe BCT \u0026ldquo;feedback on outcome of behaviour\u0026rdquo; also showed an interesting pattern of usage across our subgroup analyses. \u0026ldquo;Feedback on outcome of behaviour\u0026rdquo; provides information on the consequences of behaviour and might be more persuasive for de-implementation when the outcomes are extreme or negative (e.g., patient harm), but more challenging to apply persuasively for implementation, particularly in prescribing where benefits (such as reduced antimicrobial resistance) may be less tangible in the short term [e.g. 48\u0026ndash;50]. However, testing this was beyond the scope of this study.\u003c/p\u003e\u003cp\u003eSimilarly, the identification of \u0026ldquo;Education (unspecified)\u0026rdquo; as associated with implementation of testing/examination behaviours may relate to its role in introducing new knowledge or procedures [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e], while \u0026ldquo;social support (unspecified), often used for enablement, may lower barriers to adopting new prescribing practices [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]. [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]. Enablement is an important component of the implementation of a new behaviour, which may explain why \u0026ldquo;social support (unspecified)\u0026rdquo; has been linked to implementation. However, further investigation of this BCT's role in A\u0026amp;F interventions in healthcare would be useful.\u003c/p\u003e\u003cp\u003eOverall, these findings indicate that, currently, A\u0026amp;F practice rarely employs different BCTs according to the intended direction of behaviour change. Nevertheless, the observed associations suggest that practitioners may tailor the BCTs used in A\u0026amp;F interventions to particular behaviour types and change directions. It remains unclear whether these patterns reflect genuine differences in effectiveness or are artefacts of prevailing intervention design practices. Future research should experimentally evaluate the impact of aligning BCT choice with both behaviour type and change direction, employing theory-informed designs and preregistered analytic plans to minimise the risk of artefactual findings.\u003c/p\u003e\u003cdiv id=\"Sec21\" class=\"Section2\"\u003e\u003ch2\u003eStrengths and limitations\u003c/h2\u003e\u003cp\u003eA key strength of this study is its use of a large, systematically coded dataset of target behaviours from A\u0026amp;F interventions in healthcare, enabling detailed analyses at the level of individual behaviours. This granularity allowed us to avoid the simplifying assumption that all behaviours within an intervention share the same change direction and to model behaviour-level predictors while accounting for study-level clustering. The use of both random-effects logistic regression and parallel analyses using linear regressions provided a more robust assessment of observed associations.\u003c/p\u003e\u003cp\u003eHowever, several limitations should be acknowledged. First, the granularity of our approach may also serve as a limitation, as we had to include random effects in our analyses. These random effects were large and explained the vast majority of variance in our dependent variables. These large random effects may have obscured some small but otherwise real effects. This is in part borne out by the identification of some significant associations and several associations approaching significance in the linear regressions.\u003c/p\u003e\u003cp\u003eOur analyses were also limited by only including BCTs which were used 100 or more times. While this threshold was important to ensure sufficient statistical power and to mitigate risks of multi-collinearity, it also meant that only the most frequently used BCTs were considered. There is no theoretical rationale to suggest that these BCTs should be more suited for implementation or de-implementation than others within the taxonomy. Furthermore, it is plausible that frequently used BCTs are incorporated almost by default into A\u0026amp;F interventions, whereas those that are less commonly included may be used more intentionally with greater consideration of intervention characteristics such as the intended direction of behaviour change.\u003c/p\u003e\u003cp\u003eIt is also important to note that the exploratory nature of the subgroup analyses, combined with the number of statistical tests conducted, increases the risk of Type I error. No correction for multiple comparisons was applied, as the primary objective was to identify potential associations, even if these were accompanied by lower confidence. Consequently, the findings - particularly those from subgroup analyses - should be interpreted as preliminary. Moreover, although the inclusion of random effects addressed clustering, differences between the behaviour-level and study-level analyses (as in the reversal observed for \u0026ldquo;feedback on outcome of behaviour\u0026rdquo;) highlight that results may be sensitive to the unit of analysis. Finally, the study was not designed to determine whether particular BCTs are used more successfully for implementing versus de-implementing target behaviours.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec22\" class=\"Section2\"\u003e\u003ch2\u003eImplications for future research and practice\u003c/h2\u003e\u003cp\u003eThis study offers strong evidence that, in most cases, the same BCTs are used for implementing and de-implementing target behaviours regardless of their types. This is an important finding with potential implications for both theory and practice. If certain BCTs would be more suitable for implementing target behaviours than de-implementing [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e, \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e, \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e, \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e], then current practices could be improved by tailoring intervention strategies accordingly. Understanding which BCTs work best in each context could enhance the effectiveness of behaviour change interventions. Conversely, if BCTs are equally suitable for implementing and de-implementing, as reflected in current practice, then this finding has theoretical significance. It would suggest that BCTs operate through mechanisms that are broadly applicable across both processes, challenging assumptions that different strategies are needed for implementation versus de-implementation. The current study did not test which of these two hypotheses is accurate, so future research should aim to investigate this premise. This finding highlights the need for further investigation to determine whether these BCTs are being used because they enhance intervention effectiveness or if their usage is simply an artefact of current practices. Understanding this distinction could help enhance the application of more effective BCTs in A\u0026amp;F interventions.\u003c/p\u003e\u003cp\u003eAdditionally, another future aim would be to investigate whether the same combinations of BCTs are being used for implementing and de-implementing across behaviour types as opposed to singular BCTs. As such, future research should focus on these areas to refine theoretical understanding and improve practical application.\u003c/p\u003e\u003cp\u003eFor practice, implementers of A\u0026amp;F interventions should consider whether the BCTs selected are appropriate for both the clinical behaviour targeted and the intended direction of change. Although this study does not establish causal effects, it provides a preliminary \u0026ldquo;menu\u0026rdquo; of potentially relevant BCTs for different contexts, which can be refined through stakeholder engagement and empirical testing.\u003c/p\u003e\u003c/div\u003e"},{"header":"Conclusion","content":"\u003cp\u003eThe present findings suggest that current A\u0026amp;F practice does not typically tailor BCT selection to the intended direction of behaviour change. However, exploratory subgroup analyses indicate that certain BCTs, such as \u0026ldquo;social comparison,\u0026rdquo; \u0026ldquo;feedback on outcome of behaviour,\u0026rdquo; \u0026ldquo;education (unspecified),\u0026rdquo; and \u0026ldquo;social support (unspecified)\u0026rdquo;, may be differentially associated with implementation or de-implementation within specific behaviour types. While these associations require confirmation in randomised controlled studies, they raise the possibility that more targeted selection of BCTs could enhance intervention effectiveness. These findings highlight the need for further investigation to determine whether these BCTs are being used because they enhance intervention effectiveness or if their usage is simply an artefact of current practices. Understanding this distinction could help enhance the application of more effective BCTs in A\u0026amp;F interventions.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cdiv class=\"DefinitionList\"\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eA\u0026amp;F\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eAudit and Feedback\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eBCT(s)\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eBehaviour Change Technique(s)\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eHCP(s)\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eHealth Care Professional(s)\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eBCTTV1\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eBehaviour Change Technique Taxonomy Version 1\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eVIF\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eVariance Inflation Factor\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003c/div\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable\u003c/p\u003e\n\u003ch2\u003eFunding:\u003c/h2\u003e\n\u003cp\u003eNot applicable\u003c/p\u003e\n\u003ch2\u003eAuthors\u0026rsquo; contributions:\u003c/h2\u003e\n\u003cp\u003eHD led the analysis and wrote the first draft of this manuscript, under the supervision of VA. AP, JMG, JC, JP, NI, and FL provided suggestions for the design of this work and supported the interpretation of the data. All authors reviewed and commented on the final draft of this manuscript.\u003c/p\u003e\n\u003ch2\u003eAcknowledgements:\u003c/h2\u003e\n\u003cp\u003eNot applicable\u003c/p\u003e\n\u003ch2\u003eAvailability of data and materials:\u003c/h2\u003e\n\u003cp\u003eThe syntax and analysis document is available on OSF (https://osf.io/dsp8t/) while access to the dataset of the current study can be provided from the corresponding author on reasonable request.\u003c/p\u003e\n\u003cp\u003eCompeting interests: The authors declare that they have no competing interests.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eIvers N, Yogasingam S, Lacroix M, Brown KA, Antony J, Soobiah C, Simeoni M, Willis TA, Crawshaw J, Antonopoulou V, Meyer C. Audit and feedback: effects on professional practice. Cochrane Database Syst Reviews. 2025(3).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eCrawshaw J, Meyer C, Antonopoulou V, Antony J, Grimshaw JM, Ivers N, Konnyu K, Lacroix M, Presseau J, Simeoni M, Yogasingam S. Identifying behaviour change techniques in 287 randomized controlled trials of audit and feedback interventions targeting practice change among healthcare professionals. Implement Sci. 2023;18(1):63.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eSykes M, Rosenberg-Yunger ZR, Quigley M, Gupta L, Thomas O, Robinson L, Caulfield K, Ivers N, Alderson S. Exploring the content and delivery of feedback facilitation co-interventions: a systematic review. Implement Sci. 2024;19(1):37.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eBadejo O, Saleeb M, Hall A, Furlong B, Logan GS, Gao Z, Barrett B, Alcock L, Aubrey-Bassler K. Audit and feedback to change diagnostic image ordering practices: A systematic review and meta-analysis. PLoS ONE. 2024;19(6):e0300001.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eIvers NM, Sales A, Colquhoun H, Michie S, Foy R, Francis JJ, Grimshaw JM. No more \u0026lsquo;business as usual\u0026rsquo;with audit and feedback interventions: towards an agenda for a reinvigorated intervention. Implement Sci. 2014;9:1\u0026ndash;8.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eJamtvedt G, Flottorp S, Ivers N. Audit and feedback as a quality strategy. Improving Healthc Qual Europe 2019 Oct 17:265.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eHepner KA, Rowe M, Rost K, Hickey SC, Sherbourne CD, Ford DE, Meredith LS, Rubenstein LV. The effect of adherence to practice guidelines on depression outcomes. Ann Intern Med. 2007;147(5):320\u0026ndash;9.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eDonnellan C, Sweetman S, Shelley E. Health professionals\u0026rsquo; adherence to stroke clinical guidelines: a review of the literature. Health Policy. 2013;111(3):245\u0026ndash;63.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eChiew KL, Chong S, Duggan KJ, Kaadan N, Vinod SK. Assessing guideline adherence and patient outcomes in cervical cancer. Asia-Pac J Clin Oncol. 2017;13(5):e373\u0026ndash;80.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eO'Brien MA, Oxman AD, Davis D, Haynes RB, Freemantle N, Harvey E. Audit and feedback versus alternative strategies: effects on professional practice and health care outcomes. Cochrane Database Syst Rev. 1998;1998(1).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eJamtvedt G, Young JM, Kristoffersen DT, O'Brien MA, Oxman AD. Audit and feedback: effects on professional practice and health care outcomes. Cochrane database Syst reviews. 2006(2).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eIvers N, Jamtvedt G, Flottorp S, Young JM, Odgaard-Jensen J, French SD, O'Brien MA, Johansen M, Grimshaw J, Oxman AD. Audit and feedback: effects on professional practice and healthcare outcomes. Cochrane database Syst reviews. 2012(6).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eFoy R, Eccles MP, Jamtvedt G, Young J, Grimshaw JM, Baker R. What do we know about how to do audit and feedback? Pitfalls in applying evidence from a systematic review. BMC Health Serv Res. 2005;5:1\u0026ndash;7.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eStr\u0026ouml;mmer S, Lawrence W, Shaw S, Simao SC, Jenner S, Barrett M, Vogel C, Hardy-Johnson P, Farrell D, Woods-Townsend K, Baird J. Behaviour change interventions: getting in touch with individual differences, values and emotions. J Dev Origins Health Disease. 2020;11(6):589\u0026ndash;98.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eImproved Clinical Effectiveness through Behavioural Research Group (ICEBeRG) martin. eccles@ ncl.ac.uk. Designing theoretically-informed implementation interventions. Implement Sci. 2006;1(1):4.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eColquhoun H, Michie S, Sales A, Ivers N, Grimshaw JM, Carroll K, Chalifoux M, Eva K, Brehaut J. Reporting and design elements of audit and feedback interventions: a secondary review. BMJ Qual Saf. 2017;26(1):54\u0026ndash;60.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eMichie S, Richardson M, Johnston M, Abraham C, Francis J, Hardeman W, Eccles MP, Cane J, Wood CE. The behavior change technique taxonomy (v1) of 93 hierarchically clustered techniques: building an international consensus for the reporting of behavior change interventions. Ann Behav Med. 2013;46(1):81\u0026ndash;95.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eDavies P, Walker AE, Grimshaw JM. A systematic review of the use of theory in the design of guideline dissemination and implementation strategies and interpretation of the results of rigorous evaluations. Implement Sci. 2010;5:1\u0026ndash;6.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eColquhoun HL, Brehaut JC, Sales A, Ivers N, Grimshaw J, Michie S, Carroll K, Chalifoux M, Eva KW. A systematic review of the use of theory in randomized controlled trials of audit and feedback. Implement Sci. 2013;8:1\u0026ndash;8.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eDavis R, Campbell R, Hildon Z, Hobbs L, Michie S. Theories of behaviour and behaviour change across the social and behavioural sciences: a scoping review. Health Psychol Rev. 2015;9(3):323\u0026ndash;44.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003ePatey AM, Grimshaw JM, Francis JJ. Changing behaviour, \u0026lsquo;more or less\u0026rsquo;: do implementation and de-implementation interventions include different behaviour change techniques? Implement Sci. 2021;16:1\u0026ndash;7.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003ePatey AM, Hurt CS, Grimshaw JM, Francis JJ. Changing behaviour \u0026lsquo;more or less\u0026rsquo;\u0026mdash;do theories of behaviour inform strategies for implementation and de-implementation? A critical interpretive synthesis. Implement Sci. 2018;13:1\u0026ndash;3.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003ePrusaczyk B, Swindle T, Curran G. Defining and conceptualizing outcomes for de-implementation: key distinctions from implementation outcomes. Implement Sci Commun. 2020;1:1\u0026ndash;0.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eGifford EV, Tavakoli S, Weingardt KR, Finney JW, Pierson HM, Rosen CS, Hagedorn HJ, Cook JM, Curran GM. How do components of evidence-based psychological treatment cluster in practice? a survey and cluster analysis. J Subst Abuse Treat. 2012;42(1):45\u0026ndash;55.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eOlsson TM, von Thiele Schwarz U, Hasson H, Vira EG, Sundell K, Adapted. Adopted, and Novel Interventions: A Whole-Population Meta-Analytic Replication of Intervention Effects. Research on social work practice. Dec. 2023;6:10497315231218646.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eIvers N, Antony J, Konnyu K, O\u0026rsquo;Connor D, Presseau J, Grimshaw JM. Audit and feedback: effects on professional practice [protocol for a Cochrane review update]. Zenodo. 2022.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003ePresseau J, Ivers NM, Newham JJ, Knittle K, Danko KJ, Grimshaw JM. Using a behaviour change techniques taxonomy to identify active ingredients within trials of implementation interventions for diabetes care. Implement Sci. 2015;10:1\u0026ndash;0.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003ePatey AM, Fontaine G, Francis JJ, McCleary N, Presseau J, Grimshaw JM. Healthcare professional behaviour: health impact, prevalence of evidence-based behaviours, correlates and interventions. Psychol Health. 2023;38(6):766\u0026ndash;94.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eEverett GD, deBlois CS, Chang PF. Effect of cost education, cost audits, and faculty chart review on the use of laboratory services. Arch Intern Med. 1983;143(5):942\u0026ndash;4.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eGullion DS, Tschann JM, Adamson ET, Coates TJ. Management of hypertension in private practice: a randomized controlled trial in continuing medical education. J Continuing Educ Health Professions. 1988;8(4):239\u0026ndash;55.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eGascon Canovas JJ, Saturno Hern\u0026aacute;ndez PJ, Anton Botella JJ. Effectiveness of internal quality assurance programmes in improving clinical practice and reducing costs. J Eval Clin Pract. 2009;15(5):813\u0026ndash;9.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eCheater FM, Baker R, Reddish S, Spiers N, Wailoo A, Gillies C, Robertson N, Cawood C. Cluster randomized controlled trial of the effectiveness of audit and feedback and educational outreach on improving nursing practice and patient outcomes. Med Care. 2006;44(6):542\u0026ndash;51.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eAlthabe F, Buekens P, Bergel E, Beliz\u0026aacute;n JM, Campbell MK, Moss N, Hartwell T, Wright LL. A behavioral intervention to improve obstetrical care. N Engl J Med. 2008;358(18):1929\u0026ndash;40.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eAwad AI, Eltayeb IB, Baraka OZ. Changing antibiotics prescribing practices in health centers of Khartoum State. Sudan Eur J Clin Pharmacol. 2006;62:135\u0026ndash;42.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eAvery AJ, Rodgers S, Cantrill JA, Armstrong S, Cresswell K, Eden M, Elliott RA, Howard R, Kendrick D, Morris CJ, Prescott RJ. A pharmacist-led information technology intervention for medication errors (PINCER): a multicentre, cluster randomised, controlled trial and cost-effectiveness analysis. Lancet. 2012;379(9823):1310\u0026ndash;9.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eAyieko P, Ntoburi S, Wagai J, Opondo C, Opiyo N, Migiro S, Wamae A, Mogoa W, Were F, Wasunna A, Fegan G. A multifaceted intervention to implement guidelines and improve admission paediatric care in Kenyan district hospitals: a cluster randomised trial. PLoS Med. 2011;8(4):e1001018.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eBhatia RS, Ivers NM, Yin XC, Myers D, Nesbitt GC, Edwards J, Yared K, Wadhera RK, Wu JC, Kithcart AP, Wong BM. Improving the appropriate use of transthoracic echocardiography: the Echo WISELY Trial. J Am Coll Cardiol. 2017;70(9):1135\u0026ndash;44.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eBaker R, Fraser RC, Stone M, Lambert P, Stevenson K, Shiels C. Randomised controlled trial of the impact of guidelines, prioritized review criteria and feedback on implementation of recommendations for angina and asthma. Br J Gen Pract. 2003;53(489):284\u0026ndash;91.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eBloos F, Rueddel H, Thomas-Rueddel D, Schwarzkopf D, Pausch C, Harbarth S, Schreiber T, Gr\u0026uuml;ndling M, Marshall J, Simon P, Levy MM. Effect of a multifaceted educational intervention for anti-infectious measures on sepsis mortality: a cluster randomized trial. Intensive Care Med. 2017;43:1602\u0026ndash;12.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eChaillet N, Dumont A, Abrahamowicz M, Pasquier JC, Audibert F, Monnier P, Abenhaim HA, Dub\u0026eacute; E, Dugas M, Burne R, Fraser WD. A cluster-randomized trial to reduce cesarean delivery rates in Quebec. N Engl J Med. 2015;372(18):1710\u0026ndash;21.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eCurtis JR, Nielsen EL, Treece PD, Downey L, Dotolo D, Shannon SE, Back AL, Rubenfeld GD, Engelberg RA. Effect of a quality-improvement intervention on end-of-life care in the intensive care unit: a randomized trial. Am J Respir Crit Care Med. 2011;183(3):348\u0026ndash;55.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eBond TC, Patel PR, Krisher J, Sauls L, Deane J, Strott K, McClellan W. A group-randomized evaluation of a quality improvement intervention to improve influenza vaccination rates in dialysis centers. Am J Kidney Dis. 2011;57(2):283\u0026ndash;90.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eDijkstra RF, Braspenning JC, Huijsmans Z, Akkermans RP, Van Ballegooie E, Ten Have P, Casparie T, Grol RP. Introduction of diabetes passports involving both patients and professionals to improve hospital outpatient diabetes care. Diabetes Res Clin Pract. 2005;68(2):126\u0026ndash;34.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eOrnstein S, Jenkins RG, Nietert PJ, Feifer C, Roylance LF, Nemeth L, Corley S, Dickerson L, Bradford WD, Litvin C. A multimethod quality improvement intervention to improve preventive cardiovascular care: a cluster randomized trial. Ann Intern Med. 2004;141(7):523\u0026ndash;32.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eMeyer C, Goffe L, Antonopoulou V, Graham F, Tang MY, Lecouturier J, Grimani A, Chadwick P, Sniehotta FF. Using the precaution adoption process model to understand decision-making about the COVID-19 booster vaccine in England. Vaccine. 2023;41(15):2466\u0026ndash;75.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eKain MP, Bolker BM, McCoy MW. A practical guide and power analysis for GLMMs: detecting among treatment variation in random effects. PeerJ. 2015;3:e1226.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eHallsworth M, Chadborn T, Sallis A, Sanders M, Berry D, Greaves F, Clements L, Davies SC. Provision of social norm feedback to high prescribers of antibiotics in general practice: a pragmatic national randomised controlled trial. Lancet. 2016;387(10029):1743\u0026ndash;52.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eGjelstad S, H\u0026oslash;ye S, Straand J, Brekke M, Dalen I, Lindb\u0026aelig;k M. Improving antibiotic prescribing in acute respiratory tract infections: cluster randomised trial from Norwegian general practice (prescription peer academic detailing (Rx-PAD) study). BMJ. 2013;347.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eHallsworth M, Chadborn T, Sallis A, Sanders M, Berry D, Greaves F, Clements L, Davies SC. Provision of social norm feedback to high prescribers of antibiotics in general practice: a pragmatic national randomised controlled trial. Lancet. 2016;387(10029):1743\u0026ndash;52.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eMolloy E, Borrell-Carrio F, Epstein R. The impact of emotions in feedback. In Feedback in higher and professional education 2012 Dec 12 (pp. 50\u0026ndash;71). Routledge.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"implementation-science-communications","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"iscm","sideBox":"Learn more about [Implementation Science Communications](https://implementationsciencecomms.biomedcentral.com)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/ISCM/default.aspx","title":"Implementation Science Communications","twitterHandle":"@ImplementSci","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Audit and Feedback, Implementation, De-Implementation, Healthcare Professionals, Quality Improvement, Intervention Design, Behaviour Change","lastPublishedDoi":"10.21203/rs.3.rs-7519867/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7519867/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e\u003cp\u003eAudit and feedback (A\u0026amp;F) is a widely used quality improvement strategy to modify healthcare professionals\u0026rsquo; practice. However, there is considerable variation in how A\u0026amp;F is applied and in its effectiveness. Investigating this variation, in terms of differences in the behaviour change techniques (BCTs) interventions employ, and why it occurs may provide insights for optimising intervention design. This study, therefore, explored associations between which BCT are used in A\u0026amp;F interventions, behaviour change direction (implementation vs. de-implementation), and target behaviour type.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e\u003cp\u003eAn exploratory secondary analysis was conducted on data from 261 randomized trials of A\u0026amp;F interventions, originally extracted as part of a Cochrane systematic review. Regression analyses investigated whether different BCTs were used for implementation versus de-implementation. These analyses were repeated in subgroups of different behaviour types (e.g., prescribing, testing/examinations). Parallel analyses aggregated data at the study level to assess the robustness of findings.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e\u003cp\u003eAnalyses on the whole sample demonstrated that the same BCTs were used to implement and de-implement target behaviours in A\u0026amp;F interventions. Subgroup analyses identified potential associations between specific BCTs and implementation direction within certain behaviour types: social comparison with implementation of treatment decisions/actions; education (unspecified) with implementation of testing/examinations; social support (unspecified) with implementation of prescribing; and feedback on outcome of behaviour with de-implementation of treatment decisions/actions. However, these associations were not consistently replicated across the main and parallel analyses, and may reflect prevailing design practices or methodological artefacts rather than genuine differences in BCT selection.\u003c/p\u003e\u003ch2\u003eConclusions\u003c/h2\u003e\u003cp\u003eThis study demonstrated that, overall, A\u0026amp;F interventions utilise similar BCTs regardless of whether behaviours are being implemented or de-implemented. However, exploratory subgroup analyses suggest that tailoring interventions through selectively using certain BCTs for either implementation or de-implementation, depending on the type of behaviour being acted on, may warrant further investigation. Future research should test these hypotheses using theory-informed intervention designs and robust methods, to determine whether current patterns of BCT use reflect true differences in intervention effectiveness.\u003c/p\u003e","manuscriptTitle":"Trends in behaviour change techniques for implementing and de-Implementing healthcare practices using audit and feedback","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-10-10 20:17:53","doi":"10.21203/rs.3.rs-7519867/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Major revision","date":"2026-02-08T12:49:29+00:00","index":"","fulltext":""},{"type":"reviewerAgreed","content":"","date":"2025-10-15T16:18:56+00:00","index":0,"fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-09-29T05:24:43+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-09-05T01:05:32+00:00","index":"","fulltext":""},{"type":"submitted","content":"Implementation Science Communications","date":"2025-09-02T12:44:05+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"implementation-science-communications","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"iscm","sideBox":"Learn more about [Implementation Science Communications](https://implementationsciencecomms.biomedcentral.com)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/ISCM/default.aspx","title":"Implementation Science Communications","twitterHandle":"@ImplementSci","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"31ce9269-395b-4f0b-8a3c-96f9df981124","owner":[],"postedDate":"October 10th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2026-05-22T11:19:37+00:00","versionOfRecord":[],"versionCreatedAt":"2025-10-10 20:17:53","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7519867","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7519867","identity":"rs-7519867","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}