Explore the vast range of titles available.

Background Globally, many children fail to meet the World Health Organization’s physical activity and sedentary behaviour guidelines. Schools are an ideal setting to intervene, yet despite many interventions in this setting, success when delivered under real-world conditions or at scale is limited. This systematic review aims to i) identify which implementation models are used in school-based physical activity effectiveness, dissemination, and/or implementation trials, and ii) identify factors associated with the adoption, implementation and sustainability of school-based physical activity interventions in real-world settings. Methods The review followed PRISMA guidelines and included a systematic search of seven databases from January 1st, 2000 to July 31st, 2018: MEDLINE, EMBASE, CINAHL, SPORTDiscus, PsycINFO, CENTRAL, and ERIC. A forward citation search of included studies using Google Scholar was performed on the 21st of January 2019 including articles published until the end of 2018. Study inclusion criteria: (i) a primary outcome to increase physical activity and/or decrease sedentary behaviour among school-aged children and/or adolescents; (ii) intervention delivery within school settings, (iii) use of implementation models to plan or interpret study results; and (iv) interventions delivered under real-world conditions. Exclusion criteria: (i) efficacy trials; (ii) studies applying or testing school-based physical activity policies, and; (iii) studies targeting special schools or pre-school and/or kindergarten aged children. Results 27 papers comprising 17 unique interventions were included. Fourteen implementation models (e.g., RE-AIM, Rogers’ Diffusion of Innovations, Precede Proceed model), were applied across 27 papers. Implementation models were mostly used to interpret results ( n  = 9), for planning evaluation and interpreting results ( n  = 8), for planning evaluation ( n  = 6), for intervention design ( n  = 4), or for a combination of designing the intervention and interpreting results ( n  = 3). We identified 269 factors related to barriers ( n  = 93) and facilitators ( n  = 176) for the adoption ( n  = 7 studies), implementation ( n  = 14 studies) and sustainability ( n  = 7 studies) of interventions. Conclusions Implementation model use was predominately centered on the interpretation of results and analyses, with few examples of use across all study phases as a planning tool and to understand results. This lack of implementation models applied may explain the limited success of interventions when delivered under real-world conditions or at scale. Trial registration PROSPERO ( CRD42018099836 ).

Background Theories provide a synthesizing architecture for implementation science. The underuse, superficial use, and misuse of theories pose a substantial scientific challenge for implementation science and may relate to challenges in selecting from the many theories in the field. Implementation scientists may benefit from guidance for selecting a theory for a specific study or project. Understanding how implementation scientists select theories will help inform efforts to develop such guidance. Our objective was to identify which theories implementation scientists use, how they use theories, and the criteria used to select theories. Methods We identified initial lists of uses and criteria for selecting implementation theories based on seminal articles and an iterative consensus process. We incorporated these lists into a self-administered survey for completion by self-identified implementation scientists. We recruited potential respondents at the 8th Annual Conference on the Science of Dissemination and Implementation in Health and via several international email lists. We used frequencies and percentages to report results. Results Two hundred twenty-three implementation scientists from 12 countries responded to the survey. They reported using more than 100 different theories spanning several disciplines. Respondents reported using theories primarily to identify implementation determinants, inform data collection, enhance conceptual clarity, and guide implementation planning. Of the 19 criteria presented in the survey, the criteria used by the most respondents to select theory included analytic level (58%), logical consistency/plausibility (56%), empirical support (53%), and description of a change process (54%). The criteria used by the fewest respondents included fecundity (10%), uniqueness (12%), and falsifiability (15%). Conclusions Implementation scientists use a large number of criteria to select theories, but there is little consensus on which are most important. Our results suggest that the selection of implementation theories is often haphazard or driven by convenience or prior exposure. Variation in approaches to selecting theory warn against prescriptive guidance for theory selection. Instead, implementation scientists may benefit from considering the criteria that we propose in this paper and using them to justify their theory selection. Future research should seek to refine the criteria for theory selection to promote more consistent and appropriate use of theory in implementation science.

Background Theories, models, and frameworks (TMF) are foundational for generalizing implementation efforts and research findings. However, TMF and the criteria used to select them are not often described in published articles, perhaps due in part to the challenge of selecting from among the many TMF that exist in the field. The objective of this international study was to develop a user-friendly tool to help scientists and practitioners select appropriate TMF to guide their implementation projects. Methods Implementation scientists across the USA, the UK, and Canada identified and rated conceptually distinct categories of criteria in a concept mapping exercise. We then used the concept mapping results to develop a tool to help users select appropriate TMF for their projects. We assessed the tool’s usefulness through expert consensus and cognitive and semi-structured interviews with implementation scientists. Results Thirty-seven implementation scientists (19 researchers and 18 practitioners) identified four criteria domains: usability, testability, applicability, and familiarity. We then developed a prototype of the tool that included a list of 25 criteria organized by domain, definitions of the criteria, and a case example illustrating an application of the tool. Results of cognitive and semi-structured interviews highlighted the need for the tool to (1) be as succinct as possible; (2) have separate versions to meet the unique needs of researchers versus practitioners; (3) include easily understood terms; (4) include an introduction that clearly describes the tool’s purpose and benefits; (5) provide space for noting project information, comparing and scoring TMF, and accommodating contributions from multiple team members; and (6) include more case examples illustrating its application. Interview participants agreed that the tool (1) offered them a way to select from among candidate TMF, (2) helped them be explicit about the criteria that they used to select a TMF, and (3) enabled them to compare, select from among, and/or consider the usefulness of combining multiple TMF. These revisions resulted in the Theory Comparison and Selection Tool (T-CaST), a paper and web-enabled tool that includes 16 specific criteria that can be used to consider and justify the selection of TMF for a given project. Criteria are organized within four categories: applicability, usability, testability, and acceptability. Conclusions T-CaST is a user-friendly tool to help scientists and practitioners select appropriate TMF to guide implementation projects. Additionally, T-CaST has the potential to promote transparent reporting of criteria used to select TMF within and beyond the field of implementation science.

Background Over 60 implementation frameworks exist. Using multiple frameworks may help researchers to address multiple study purposes, levels, and degrees of theoretical heritage and operationalizability; however, using multiple frameworks may result in unnecessary complexity and redundancy if doing so does not address study needs. The Consolidated Framework for Implementation Research (CFIR) and the Theoretical Domains Framework (TDF) are both well-operationalized, multi-level implementation determinant frameworks derived from theory. As such, the rationale for using the frameworks in combination (i.e., CFIR + TDF) is unclear. The objective of this systematic review was to elucidate the rationale for using CFIR + TDF by (1) describing studies that have used CFIR + TDF, (2) how they used CFIR + TDF, and (2) their stated rationale for using CFIR + TDF. Methods We undertook a systematic review to identify studies that mentioned both the CFIR and the TDF, were written in English, were peer-reviewed, and reported either a protocol or results of an empirical study in MEDLINE/PubMed, PsycInfo, Web of Science, or Google Scholar. We then abstracted data into a matrix and analyzed it qualitatively, identifying salient themes. Findings We identified five protocols and seven completed studies that used CFIR + TDF. CFIR + TDF was applied to studies in several countries, to a range of healthcare interventions, and at multiple intervention phases; used many designs, methods, and units of analysis; and assessed a variety of outcomes. Three studies indicated that using CFIR + TDF addressed multiple study purposes. Six studies indicated that using CFIR + TDF addressed multiple conceptual levels. Four studies did not explicitly state their rationale for using CFIR + TDF. Conclusions Differences in the purposes that authors of the CFIR (e.g., comprehensive set of implementation determinants) and the TDF (e.g., intervention development) propose help to justify the use of CFIR + TDF. Given that the CFIR and the TDF are both multi-level frameworks, the rationale that using CFIR + TDF is needed to address multiple conceptual levels may reflect potentially misleading conventional wisdom. On the other hand, using CFIR + TDF may more fully define the multi-level nature of implementation. To avoid concerns about unnecessary complexity and redundancy, scholars who use CFIR + TDF and combinations of other frameworks should specify how the frameworks contribute to their study. Trial registration PROSPERO CRD42015027615

Background Evidence on how to implement new interventions into complex healthcare environments is often poorly reported and indexed, reducing its potential to inform initiatives to improve healthcare services. Using the implementation of a digital intervention within routine National Health Service (NHS) practice, we provide an example of how to develop a theoretically based implementation plan and how to report it transparently. In doing so we also highlight some of the challenges to implementation in routine healthcare. Methods The implemented intervention was HeLP-Diabetes, a digital self-management programme for people with Type 2 Diabetes, which was effective in improving diabetes control. The target setting for the implementation was an inner city London Clinical Commissioning Group in the NHS comprised of 34 general practices. HeLP-Diabetes was designed to be offered to patients as part of routine diabetes care across England. Evidence synthesis, engagement of local stakeholders, a theory of implementation (Normalization Process Theory), feedback, qualitative interviews and usage data were used to develop an implementation plan. Results A new implementation plan was developed to implement HeLP-Diabetes within routine practice. Individual component strategies were selected and developed informed by Normalization Process Theory. These strategies included: engagement of local opinion leaders, provision of educational materials, educational visits, educational meetings, audit and feedback and reminders. Additional strategies were introduced iteratively to address barriers that arose during the implementation. Barriers largely related to difficulties in allocating resources to implement the intervention within routine care. Conclusion This paper provides a worked example of implementing a digital health intervention. The learning from this work can inform others undertaking the work of planning and executing implementation activities in routine healthcare. Of particular importance is: the selection of appropriate theory to guide the implementation process and selection of strategies; ensuring that enough attention is paid to planning implementation; and a flexible approach that allows response to emerging barriers.

There is a vigorous debate about the capacity of conservation biology, as a scientific discipline, to effectively contribute to actions that preserve and restore biodiversity. Various factors may be responsible for the current great divide that exists between conservation research and action. Part of the problem may be a lack of involvement by conservation scientists in actually conducting or helping implement concrete conservation actions, yet scientists' involvement can be decisive for successful implementation, as illustrated here by the rapid recovery of an endangered hoopoe population in the Swiss Alps after researchers decided to implement the corrective measures they were proposing themselves. We argue that a conceptual paradigm shift should take place in the academic conservation discipline toward more commitment on the part of researchers to turn conservation science into conservation action. Practical implementation should be regarded as an integrated part of scientific conservation activity, as it actually constitutes the ultimate assessment of the effectiveness of the recommended conservation guidelines, and should be rewarded as such.

The theory of full implementation has been criticized for using integer/modulo games which admit no equilibrium (Jackson (1992)). To address the critique, we revisit the classical Nash implementation problem due to Maskin (1977, 1999) but allow for the use of lotteries and monetary transfers as in Abreu and Matsushima (1992, 1994). We unify the two well-established but somewhat orthogonal approaches in full implementation theory. We show that Maskin monotonicity is a necessary and sufficient condition for (exact) mixed-strategy Nash implementation by a finite mechanism. In contrast to previous papers, our approach possesses the following features: finite mechanisms (with no integer or modulo game) are used; mixed strategies are handled explicitly; neither undesirable outcomes nor transfers occur in equilibrium; the size of transfers can be made arbitrarily small; and our mechanism is robust to information perturbations.

Background Many international health policies recognise the World Health Organization’s (2008) vision that communities should be involved in shaping primary healthcare services. However, researchers continue to debate definitions, models, and operational challenges to community participation. Furthermore, there has been no use of implementation theory to study how community participation is introduced and embedded in primary healthcare in order to generate insights and transferrable lessons for making this so. Using Normalisation Process Theory (NPT) as a conceptual framework, this qualitative study was designed to explore the levers and barriers to the implementation of community participation in primary healthcare as a routine way of working. Methods We conducted two qualitative studies based on a national Initiative designed to support community participation in primary care in Ireland. We had a combined multi-stakeholder purposeful sample ( n  = 72), utilising documentary evidence (study 1), semi-structured interviews (studies 1 and 2) and focus groups (study 2). Data generation and analysis were informed by Participatory Learning and Action (PLA) Research Methodology and NPT. Results For many stakeholders, community participation in primary healthcare was a new way of working. Stakeholders did not always have a clear, shared understanding of the aims, objectives and benefits of this way of working and getting involved in a specific project sometimes provided this clarity. Drivers/champions, and strong working partnerships, were considered integral to its initiation and implementation. Participants emphasised the benefits of funding, organisational support, training and networking to enact relevant activities. Health-promoting activities and healthcare consultation/information events were generally successful, but community representation on interdisciplinary Primary Care Teams proved more challenging. Overall, participants were broadly positive about the impacts of community participation, but were concerned about the scope to sustain the work without the ‘protected’ space and resources that the national Initiative afforded. Conclusions Despite the success of specific activities undertaken as part of a community process in Irish primary healthcare, the likelihood of this becoming a routine way of working in Ireland is low. Analysing the learning from this process using NPT provides theoretically informed recommendations that are transferrable to other settings and can be used to prospectively design and formatively evaluate community participation processes.

I define Weak Implementation under incomplete information. A social choice set is weakly implementable if the set of equilibrium outcomes of some mechanism is a non-empty subset of the social choice set. Weak implementation is a more natural objective than either full or partial implementation in many cases. I show that there are social choice sets where every subset can be weakly implemented, yet the set cannot be fully implemented. I give a complete characterization of the weakly implementable social choice sets under a weak restriction on preferences. As a corollary, I show that in independent private values environments the set of interim efficient social choice functions is weakly implementable whenever it is partially implementable.

Background The clinical effectiveness of Enhanced Recovery After Surgery (ERAS) protocols in reducing length of stay and postoperative complications is well established. Yet, the uptake of these protocols remains variable in many healthcare settings. Methods We used the Generative Co‐Design Framework for Healthcare Innovation to design and deliver strategies to implement ERAS protocols at one Australian tertiary hospital. Co‐design groups included surgeons, anaesthetists, perioperative and surgical nurses, and health consumers with previous surgery experience. Two workshops with co‐designers were held over 4 months. Textual data derived through workshop artefacts and discussions were analysed inductively. Then, subcategories representing implementation strategies were deductively mapped to the level they primarily target, individual, team and organisation. Finally, using a consensus‐building approach, the top two implementation strategies were ranked across each group. Results In total, 36 practitioners across perioperative, ward, surgery and anaesthetics and 4 consumers participated in the co‐design sessions. Through the analysis, 16 implementation strategies were identified, and half of these were aimed at the organisational level. Strategies ranked in the top two commons across all groups of practitioners included reviewing clinical pathways and processes. Consumers believed receiving patient education about ERAS, including its risks and benefits, was essential. Conclusion Our findings underscore the intricate nature of coordinating diverse stakeholders in co‐design processes. Despite the challenges this may present, it provides valuable insights and promotes consensus‐driven solutions, ultimately strengthening the implementation of ERAS initiatives. Patient or Public Contribution Consumers were involved in the co‐design process and were co‐researchers.