Background. CONSORT guidelines call for precise reporting of behavior change interventions: we need rigorous methods of characterizing active content of

It is increasingly acknowledged that ‘acceptability’ should be considered when designing, evaluating and implementing healthcare interventions. However, the published literature offers little guidance on how to define or assess acceptability. The purpose of this study was to develop a multi-construct theoretical framework of acceptability of healthcare interventions that can be applied to assess prospective (i.e. anticipated) and retrospective (i.e. experienced) acceptability from the perspective of intervention delivers and recipients. Two methods were used to select the component constructs of acceptability. 1) An overview of reviews was conducted to identify systematic reviews that claim to define, theorise or measure acceptability of healthcare interventions. 2) Principles of inductive and deductive reasoning were applied to theorise the concept of acceptability and develop a theoretical framework. Steps included (1) defining acceptability; (2) describing its properties and scope and (3) identifying component constructs and empirical indicators. From the 43 reviews included in the overview, none explicitly theorised or defined acceptability. Measures used to assess acceptability focused on behaviour (e.g. dropout rates) (23 reviews), affect (i.e. feelings) (5 reviews), cognition (i.e. perceptions) (7 reviews) or a combination of these (8 reviews). From the methods described above we propose a definition: Acceptability is a multi-faceted construct that reflects the extent to which people delivering or receiving a healthcare intervention consider it to be appropriate, based on anticipated or experienced cognitive and emotional responses to the intervention. The theoretical framework of acceptability (TFA) consists of seven component constructs: affective attitude, burden, perceived effectiveness, ethicality, intervention coherence, opportunity costs, and self-efficacy. Despite frequent claims that healthcare interventions have assessed acceptability, it is evident that acceptability research could be more robust. The proposed definition of acceptability and the TFA can inform assessment tools and evaluations of the acceptability of new or existing interventions.

In interview studies, sample size is often justified by interviewing participants until reaching ‘data saturation’. However, there is no agreed method of establishing this. We propose principles for deciding saturation in theory-based interview studies (where conceptual categories are pre-established by existing theory). First, specify a minimum sample size for initial analysis (initial analysis sample). Second, specify how many more interviews will be conducted without new ideas emerging (stopping criterion). We demonstrate these principles in two studies, based on the theory of planned behaviour, designed to identify three belief categories (Behavioural, Normative and Control), using an initial analysis sample of 10 and stopping criterion of 3. Study 1 (retrospective analysis of existing data) identified 84 shared beliefs of 14 general medical practitioners about managing patients with sore throat without prescribing antibiotics. The criterion for saturation was achieved for Normative beliefs but not for other beliefs or studywise saturation. In Study 2 (prospective analysis), 17 relatives of people with Paget's disease of the bone reported 44 shared beliefs about taking genetic testing. Studywise data saturation was achieved at interview 17. We propose specification of these principles for reporting data saturation in theory-based interview studies. The principles may be adaptable for other types of studies.

There is little systematic operational guidance about how best to develop complex interventions to reduce the gap between practice and evidence. This article is one in a Series of articles documenting the development and use of the Theoretical Domains Framework (TDF) to advance the science of implementation research.

Background: Implementation research may play an important role in reducing research waste by identifying strategies that support translation of evidence into practice. Implementation of healthcare interventions is influenced by multiple factors including the organisational context, implementation strategies and features of the intervention as perceived by people delivering and receiving the intervention. Recently, concepts relating to perceived features of interventions have been gaining traction in published literature, namely, acceptability, fidelity, feasibility, scalability and sustainability. These concepts may influence uptake of healthcare interventions, yet there seems to be little consensus about their nature and impact. The aim of this paper is to develop a testable conceptual framework of implementability of healthcare interventions that includes these five concepts. Methods: A multifaceted approach was used to develop and refine a conceptual framework of implementability of healthcare interventions. An overview of reviews identified reviews published between January 2000 and March 2021 that focused on at least one of the five concepts in relation to a healthcare intervention. These findings informed the development of a preliminary framework of implementability of healthcare interventions which was presented to a panel of experts. A nominal group process was used to critique, refine and agree on a final framework. Results: A total of 252 publications were included in the overview of reviews. Of these, 32% were found to be feasible, 4% reported sustainable changes in practice and 9% were scaled up to other populations and/or settings. The expert panel proposed that scalability and sustainability of a healthcare intervention are dependent on its acceptability, fidelity and feasibility. Furthermore, acceptability, fidelity and feasibility require re-evaluation over time and as the intervention is developed and then implemented in different settings or with different populations. The final agreed framework of implementability provides the basis for a chronological, iterative approach to planning for wide-scale, long-term implementation of healthcare interventions. Conclusions: We recommend that researchers consider the factors acceptability, fidelity and feasibility (proposed to influence sustainability and scalability) during the preliminary phases of intervention development, evaluation and implementation, and iteratively check these factors in different settings and over time.