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Background:The multi-disciplinarity of long-term care for people with intellectual disabilities makes organisations seek stability and predictability, complicating implementing innovations. Interventions to implement a method for reducing restrictive measures were analysed through the lens of Normalisation Process Theory to understand the social mechanisms at play.Methods:Process notes, collected during a trial in which a method to reduce restrictive measures was implemented, were analysed guided by implementation interventions defined by Cochrane Effective Practice and Organisation of Care Review Group. These interventions were mapped to social mechanisms of Normalisation Process Theory.Results:Implementation interventions were widely used in which clients’ perspectives were expressed (client-related-interventions), and consensus processes were held with care professionals. These interventions initiated NPT’s social mechanisms’ Coherence, Cognitive Participation and Collective Action.Conclusions:The emphasis on consensus and clients’ perspectives when methodically reducing restrictive measures reflects some unique implementation challenges in long-term intellectual disability care.

Background Postpartum haemorrhage (PPH) is the leading cause of global maternal deaths, accounting for 30–50% of maternal deaths in sub-Saharan Africa. Most PPH-related deaths are preventable with timely detection and initiation of care, which may be facilitated by using a clinical care bundle. We explore influences on current PPH detection and management and on the future implementation of a new PPH bundle (E-MOTIVE) in low-resource, high-burden settings. Methods Semi-structured qualitative interviews based on the Theoretical Domains Framework were conducted with 45 healthcare providers across nine hospitals in Nigeria, Kenya and South Africa, to identify barriers and enablers to current PPH detection and management and future implementation of a new PPH care bundle. Data were analysed using thematic and framework analysis. The Behaviour Change Wheel was used to identify potential interventions to address identified barriers and enablers. Results Influences on current PPH detection and management fell under 12 domains: Environmental Context and Resources (drug and staff shortages), Skills (limited in-service training), Knowledge (variable understanding of the recommended practice), Behaviour Regulation (limited quality improvement culture), Beliefs about Consequences (drawbacks from inaccurate detection), Emotion (stress from the unpredictability of PPH), Social Influence (teamwork), Memory, Attention and Decision-making (limited guideline use), Social/Professional Role and Identity (role clarity), Beliefs about Capabilities (confidence in managing PPH), Reinforcement (disciplinary procedures) and Goals (PPH as a priority). Influences on bundle uptake included: Beliefs about Consequences (perceived benefits of new blood loss measurement tool), Environmental Context and Resources (high cost of drugs and new tools), Memory, Attention and Decision-making (concerns about whether bundle fits current practice), Knowledge (not understanding ‘bundled’ approach), Social Influence (acceptance by women and staff) and Intention (limited acceptance of ‘bundled' approach over existing practice). These influences were consistent across countries. Proposed interventions included: Education, Training, Modelling (core and new skills), Enablement (monitoring uptake), Persuasion (leadership role) and Environmental Restructuring (PPH emergency trolley/kit). Conclusions A wide range of individual, socio-cultural and environmental barriers and enablers to improving PPH detection and management exist in these settings. We identified a range of interventions that could improve PPH care and the implementation of new care bundles in this context. Trial registration ClinicalTrials.gov: NCT04341662

Background There is little information about the functions and behavior change techniques (BCTs) needed to implement shared decision making (SDM) in clinical practice. To guide future implementation initiatives, we sought to develop a BCT taxonomy for SDM implementation interventions. Methods This study is a secondary analysis of a 2018 Cochrane review on interventions for increasing the use of shared decision making by healthcare professionals. We examined all 87 studies included in the review. We extracted relevant information on each study intervention into a spreadsheet. Coders had undergone a training workshop on intervention functions and online training on BCT Taxonomy version 1 (BCTTv1). We performed functions and BCTs coding trials, and identified coding rules. We used Michie’s guide for designing behavior change interventions to code the functions and BCTs used in the interventions. Coders met to compare coding and discrepancies were discussed until consensus was reached. Data was analyzed using simple descriptive statistics. Results Overall, 7 functions, 24 combinations of functions and 32 BCTs were used in the 87 SDM implementation interventions. The mean of functions per intervention was 2.5 and the mean of BCTs per intervention was 3.7. The functions Coercion and Restriction were not found. The most common function was Education (73 studies). Three combinations of functions were most common (e.g: Education + Persuasion, used in 10 studies). The functions associated with more effective SDM implementation interventions were Modeling and Training. The most effective combination of functions was Education + Training + Modeling + Enablement. The most commonly used BCT was Instruction on how to perform the behavior (43 studies). BCTs associated with more effective SDM implementation interventions were: Instruction on how to perform the behavior, Demonstration of the behavior, Feedback on behavior, Pharmacological support, Material reward, and Biofeedback. Twenty-five BCTs were associated with less effective SDM implementation interventions. Four new BCTs were identified: General information to support the behavior, Tailoring, Exercises to conceptually prepare for the behavior, and Experience sharing and learning. Conclusions We established a BCT taxonomy specific to the field of SDM to guide future SDM implementation interventions. Four new BCTs should be added to BCTTv1.

Background Mental health services aim to provide recovery-focused care and facilitate coproduced care planning. In practice, mental health providers can find supporting individualized coproduced care with service users difficult while balancing administrative and performance demands. To help meet this aim and using principles of coproduction, an innovative mobile digital care pathway tool (CPT) was developed to be used on a tablet computer and piloted in the West of England. Objective The aim of this study was to examine mental health care providers’ views of and experiences with the CPT during the pilot implementation phase and identify factors influencing its implementation. Methods A total of 20 in-depth telephone interviews were conducted with providers participating in the pilot and managers in the host organization. Interviews were audio recorded, transcribed, anonymized, and thematically analyzed guided by the Consolidated Framework for Implementation Research. Results The tool was thought to facilitate coproduced recovery-focused care planning, a policy and organizational as well as professional priority. Internet connectivity issues, system interoperability, and access to service users’ health records affected use of the tool during mobile working. The organization’s resources, such as information technology (IT) infrastructure and staff time and IT culture, influenced implementation. Participants’ levels of use of the tool were dependent on knowledge of the tool and self-efficacy; perceived service-user needs and characteristics; and perceptions of impact on the therapeutic relationship. Training and preparation time influenced participants’ confidence in using the tool. Conclusions Findings highlight the importance of congruence between staff, organization, and external policy priorities and digital technologies in aiding intervention engagement, and the need for ongoing training and support of those intended to use the technology during and after the end of implementation interventions.