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Background There is growing evidence that context mediates the effects of implementation interventions intended to increase healthcare professionals’ use of research evidence in clinical practice. However, conceptual clarity about what comprises context is elusive. The purpose of this study was to advance conceptual clarity on context by developing the Implementation in Context Framework, a meta-framework of the context domains, attributes and features that can facilitate or hinder healthcare professionals’ use of research evidence and the effectiveness of implementation interventions in clinical practice. Methods We conducted a meta-synthesis of data from three interrelated studies: (1) a concept analysis of published literature on context (n = 70 studies), (2) a secondary analysis of healthcare professional interviews (n = 145) examining context across 11 unique studies and (3) a descriptive qualitative study comprised of interviews with heath system stakeholders (n = 39) in four countries to elicit their tacit knowledge on the attributes and features of context. A rigorous protocol was followed for the meta-synthesis, resulting in development of the Implementation in Context Framework. Following this meta-synthesis, the framework was further refined through feedback from experts in context and implementation science. Results In the Implementation in Context Framework, context is conceptualized in three levels: micro (individual), meso (organizational), and macro (external). The three levels are composed of six contextual domains: (1) actors (micro), (2) organizational climate and structures (meso), (3) organizational social behaviour (meso), (4) organizational response to change (meso), (5) organizational processes (meso) and (6) external influences (macro). These six domains contain 22 core attributes of context and 108 features that illustrate these attributes. Conclusions The Implementation in Context Framework is the only meta-framework of context available t

Background There is growing evidence that context mediates the effects of implementation interventions intended to increase healthcare professionals’ use of research evidence in clinical practice. However, conceptual clarity about what comprises context is elusive. The purpose of this study was to advance conceptual clarity on context by developing the Implementation in Context Framework, a meta-framework of the context domains, attributes and features that can facilitate or hinder healthcare professionals’ use of research evidence and the effectiveness of implementation interventions in clinical practice. Methods We conducted a meta-synthesis of data from three interrelated studies: (1) a concept analysis of published literature on context (n = 70 studies), (2) a secondary analysis of healthcare professional interviews (n = 145) examining context across 11 unique studies and (3) a descriptive qualitative study comprised of interviews with heath system stakeholders (n = 39) in four countries to elicit their tacit knowledge on the attributes and features of context. A rigorous protocol was followed for the meta-synthesis, resulting in development of the Implementation in Context Framework. Following this meta-synthesis, the framework was further refined through feedback from experts in context and implementation science. Results In the Implementation in Context Framework, context is conceptualized in three levels: micro (individual), meso (organizational), and macro (external). The three levels are composed of six contextual domains: (1) actors (micro), (2) organizational climate and structures (meso), (3) organizational social behaviour (meso), (4) organizational response to change (meso), (5) organizational processes (meso) and (6) external influences (macro). These six domains contain 22 core attributes of context and 108 features that illustrate these attributes. Conclusions The Implementation in Context Framework is the only meta-framework of context available t

Background There is growing evidence that context mediates the effects of implementation interventions intended to increase healthcare professionals’ use of research evidence in clinical practice. However, conceptual clarity about what comprises context is elusive. The purpose of this study was to advance conceptual clarity on context by developing the Implementation in Context Framework, a meta-framework of the context domains, attributes and features that can facilitate or hinder healthcare professionals’ use of research evidence and the effectiveness of implementation interventions in clinical practice. Methods We conducted a meta-synthesis of data from three interrelated studies: (1) a concept analysis of published literature on context (n = 70 studies), (2) a secondary analysis of healthcare professional interviews (n = 145) examining context across 11 unique studies and (3) a descriptive qualitative study comprised of interviews with heath system stakeholders (n = 39) in four countries to elicit their tacit knowledge on the attributes and features of context. A rigorous protocol was followed for the meta-synthesis, resulting in development of the Implementation in Context Framework. Following this meta-synthesis, the framework was further refined through feedback from experts in context and implementation science. Results In the Implementation in Context Framework, context is conceptualized in three levels: micro (individual), meso (organizational), and macro (external). The three levels are composed of six contextual domains: (1) actors (micro), (2) organizational climate and structures (meso), (3) organizational social behaviour (meso), (4) organizational response to change (meso), (5) organizational processes (meso) and (6) external influences (macro). These six domains contain 22 core attributes of context and 108 features that illustrate these attributes. Conclusions The Implementation in Context Framework is the only meta-framework of context available t

Background Decision coaching is non -directive support delivered by a healthcare provider to help patients prepare to actively participate in making a hea[th decision. 'Healthcare providers' are considered to be aEl people who are engaged in actions whose primary intent is to protect and improve health (e.g. nurses, doctors, pharmacists, social workers, health support vvorkers such as peer health workers). Little is known about the effectiveness of decision coaching. Objectives To determine the effects of decision coaching (I) for people facing healthcare decisions for themselves or a family member (P) compared to (C) usual care or evidence -based intervention only, on outcomes (0) related to preparation for decision making, decisional needs and potential adverse effects. Search methods We searched the Cochrane Library (Wiley), Cochrane Central Register of Controlled Trials (CENTRAL), MEDLINE (Ovid), Embase (Ovid), PsycINFO (Ovid), CI NAHL (Ebsco), Nursing and Allied Health Source (ProQuest), and Web of Science from database inception to June 2021. Selection criteria We included randomised controlled trials (RCTs) where the intervention was provided to adults or children preparing to make a treatment or screening healthcare decision for themselves or a family member. Decision coaching was defined as: a) delivered individually by a healthcare provider who istrained or using a protocol; and b) providing non -directive support and preparing an adult or child to participate in a healthcare decision. Comparisons included usual care or an alternate intervention. There were no language restrictions. Data collection and analysis Two authors independently screened citations, assessed risk of bias, and extracted data on characteristics of the intervention(s) and outcomes. Any disagreements were resolved by discussion to reach consensus. We used the standardised mean difference (SMD) with 95% confidence intervals (CI) as the measures of treatment effect and, where possible, sy

Background Decision coaching is non -directive support delivered by a healthcare provider to help patients prepare to actively participate in making a hea[th decision. 'Healthcare providers' are considered to be aEl people who are engaged in actions whose primary intent is to protect and improve health (e.g. nurses, doctors, pharmacists, social workers, health support vvorkers such as peer health workers). Little is known about the effectiveness of decision coaching. Objectives To determine the effects of decision coaching (I) for people facing healthcare decisions for themselves or a family member (P) compared to (C) usual care or evidence -based intervention only, on outcomes (0) related to preparation for decision making, decisional needs and potential adverse effects. Search methods We searched the Cochrane Library (Wiley), Cochrane Central Register of Controlled Trials (CENTRAL), MEDLINE (Ovid), Embase (Ovid), PsycINFO (Ovid), CI NAHL (Ebsco), Nursing and Allied Health Source (ProQuest), and Web of Science from database inception to June 2021. Selection criteria We included randomised controlled trials (RCTs) where the intervention was provided to adults or children preparing to make a treatment or screening healthcare decision for themselves or a family member. Decision coaching was defined as: a) delivered individually by a healthcare provider who istrained or using a protocol; and b) providing non -directive support and preparing an adult or child to participate in a healthcare decision. Comparisons included usual care or an alternate intervention. There were no language restrictions. Data collection and analysis Two authors independently screened citations, assessed risk of bias, and extracted data on characteristics of the intervention(s) and outcomes. Any disagreements were resolved by discussion to reach consensus. We used the standardised mean difference (SMD) with 95% confidence intervals (CI) as the measures of treatment effect and, where possible, sy

BackgroundUndernutrition contributes to five million deaths of children under five each year. Furthermore, throughout the life cycle, undernutrition contributes to increased risk of infection, poor cognitive functioning, chronic disease, and mortality. It is thus important for decision-makers to have evidence about the effectiveness of nutrition interventions for young children.ObjectivesPrimary objective1. To assess the effectiveness of supplementary feeding interventions, alone or with co-intervention, for improving the physical and psychosocial health of disadvantaged children aged three months to five years.Secondary objectives1. To assess the potential of such programmes to reduce socio-economic inequalities in undernutrition.2. To evaluate implementation and to understand how this may impact on outcomes.3. To determine whether there are any adverse effects of supplementary feeding.Search methodsWe searched CENTRAL, Ovid MEDLINE, PsycINFO, and seven other databases for all available years up to January 2014. We also searched ClinicalTrials.gov and several sources of grey literature. In addition, we searched the reference lists of relevant articles and reviews, and asked experts in the area about ongoing and unpublished trials.Selection criteriaRandomised controlled trials (RCTs), cluster-RCTs, controlled clinical trials (CCTs), controlled before-and-after studies (CBAs), and interrupted time series (ITS) that provided supplementary food (with or without co-intervention) to children aged three months to five years, from all countries. Adjunctive treatments, such as nutrition education, were allowed. Controls had to be untreated.Data collection and analysisTwo or more review authors independently reviewed searches, selected studies for inclusion or exclusion, extracted data, and assessed risk of bias. We conducted meta-analyses for continuous data using the mean difference (MD) or the standardised mean difference (SMD) with a 95% confidence interval (CI), correct

Objective. The Effective Consumer Scale (EC-17) comprises 17 items measuring the main skills and behaviors people need to effectively manage their healthcare. We tested the responsiveness of the EC-17. Methods. Participants, in 2 waves of a 6-week Arthritis Self-Management Program (ASMP) from Arthritis Ireland, received a questionnaire at the first and last week of the weekly ASMP. The questionnaire included the EC-17 and 10 other measures for arthritis. Deficits, mean change, and standard deviations were calculated at baseline and Week 6. The EC-17 scores were compared to the Arthritis Self-Efficacy (ASE) and Patient Activation Measure (PAM) scales. Results were presented at OMERACT 9. Results. There is some overlap between the EC-17 and the ASE and PAM; however, most items of greatest deficit in the EC-17 are not covered by those scales. In 327 participants representing both intervention waves (2006 and 2007), the EC-17 was more efficient than the ASE but less efficient than the PAM for detecting improvements after the ASMP, and was moderately correlated with the PAM. Conclusion. The EC-17 appears to measure different skills and attributes than the ASE and PAM. Discussions with participants at OMERACT 9 agreed that it is worthwhile to measure the skills and attributes of an effective consumer, and supported the development of an intervention (such as proposed online decision aids) that would include education in the categories in the EC-17.