PurposeUnderstanding the effectiveness of complex, face‐to‐face health behaviour change interventions requires high‐quality measures to assess fidelity of delivery and engagement. This systematic review aimed to (1) identify the types of measures used to monitor fidelity of delivery of, and engagement with, complex, face‐to‐face health behaviour change interventions and (2) describe the reporting of psychometric and implementation qualities.MethodsElectronic databases were searched, systematic reviews and reference lists were hand‐searched, and 21 experts were contacted to identify articles. Studies that quantitatively measured fidelity of delivery of, and/or engagement with, a complex, face‐to‐face health behaviour change intervention for adults were included. Data on interventions, measures, and psychometric and implementation qualities were extracted and synthesized using narrative analysis.ResultsSixty‐six studies were included: 24 measured both fidelity of delivery and engagement, 20 measured fidelity of delivery, and 22 measured engagement. Measures of fidelity of delivery included observation (n = 17; 38.6%), self‐report (n = 15; 34%), quantitatively rated qualitative interviews (n = 1; 2.3%), or multiple measures (n = 11; 25%). Measures of engagement included self‐report (n = 18; 39.1%), intervention records (n = 11; 24%), or multiple measures (n = 17; 37%). Fifty‐one studies (77%) reported at least one psychometric or implementation quality; 49 studies (74.2%) reported at least one psychometric quality, and 17 studies (25.8%) reported at least one implementation quality.ConclusionFewer than half of the reviewed studies measured both fidelity of delivery of, and engagement with complex, face‐to‐face health behaviour change interventions. More studies reported psychometric qualities than implementation qualities. Interpretation of intervention outcomes from fidelity of delivery and engagement measurements may be limited due to a lack of reporting of psychometric and implementation qualities. Statement of contribution What is already known on this subject? Evidence of fidelity and engagement is needed to understand effectiveness of complex interventionsEvidence of fidelity and engagement are rarely reportedHigh‐quality measures are needed to measure fidelity and engagement What does this study add? Evidence that indicators of quality of measures are reported in some studiesEvidence that psychometric qualities are reported more frequently than implementation qualitiesA recommendation for intervention evaluations to report indicators of quality of fidelity and engagement measures

Background and aimsPeople with mental illnesses and substance abuse disorders are important targets for smoking cessation interventions. Mental health professionals (MHPs) are ideally placed to deliver interventions, but their attitudes may prevent this. This systematic review therefore aimed to identify and estimate quantitatively MHPs attitudes towards smoking and main barriers for providing smoking cessation support and to explore these attitudes in‐depth through qualitative synthesis.MethodsThe online databases AMED, EMBASE, Medline, PsychINFO, HMIC and CINAHL were searched in March 2015 using terms relating to three concepts: ‘attitudes’, ‘mental health professionals’ and ‘smoking cessation’. Quantitative or qualitative studies of any type were included. Proportions of MHPs' attitudes towards smoking and smoking cessation were pooled across studies using random effects meta‐analysis. Qualitative findings were evaluated using thematic synthesis.ResultsThirty‐eight studies including 16 369 participants were eligible for inclusion. Pooled proportions revealed that 42.2% [95% confidence interval (CI) = 35.7–48.8] of MHPs reported perceived barriers to smoking cessation interventions, 40.5% (95% CI = 30.4–51.0) negative attitudes towards smoking cessation and 45.0% (95% CI = 31.9–58.4) permissive attitudes towards smoking. The most commonly held beliefs were that patients are not interested in quitting (51.4%, 95% CI = 33.4–69.2) and that quitting smoking is too much for patients to take on (38%, 95% CI = 16.4–62.6). Qualitative findings were consistent with quantitative results, revealing a culture of smoking as ‘the norm’ and a perception of cigarettes as a useful tool for patients and staff.ConclusionsA significant proportion of mental health professionals hold attitudes and misconceptions that may undermine the delivery of smoking cessation interventions; many report a lack of time, training and confidence as main barriers to addressing smoking in their patients.

Time series analyses are statistical methods used to assess trends in repeated measurements taken at regular intervals and their associations with other trends or events, taking account of the temporal structure of such data. Addiction research often involves assessing associations between trends in target variables (e.g. population cigarette smoking prevalence) and predictor variables (e.g. average price of a cigarette), known as a multiple time series design, or interventions or events (e.g. introduction of an indoor smoking ban), known as an interrupted time series design. There are many analytical tools available, each with its own strengths and limitations. This paper provides addiction researchers with an overview of many of the methods available (GLM, GLMM, GLS, GAMM, ARIMA, ARIMAX, VAR, SVAR, VECM) and guidance on when and how they should be used, sample size det ermination, reporting and interpretation. The aim is to provide increased clarity for researchers proposing to undertake these analyses concerning what is likely to be acceptable for publication in journals such as Addiction. Given the large number of choices that need to be made when setting up time series models, the guidance emphasizes the importance of pre‐registering hypotheses and analysis plans before the analyses are undertaken.

Objectives. To understand whether interventions are effective, we need to know whether the interventions are delivered as planned (with fidelity) and engaged with. To measure fidelity and engagement effectively, high-quality measures are needed. We outline a five-step method which can be used to develop quality measures of fidelity and engagement for complex health interventions. We provide examples from a fidelity study conducted within an evaluation of an intervention aimed to increase independence in dementia.Methods. We propose five steps that can be systematically used to develop fidelity checklists for researchers, providers, and participants to measure fidelity and engagement. These steps include the following: (1) reviewing previous measures, (2) analysing intervention components and developing a framework outlining the content of the intervention, (3) developing fidelity checklists and coding guidelines, (4) obtaining feedback about the content and wording of checklists and guidelines, and (5) piloting and refining checklists and coding guidelines to assess and improve reliability.Results. Three fidelity checklists that can be used reliably were developed to measure fidelity of and engagement with, the Promoting Independence in Dementia (PRIDE) intervention. As these measures were designed to be used by researchers, providers, and participants, we developed two versions of the checklists: one for participants and one for researchers and providers.Conclusions. The five steps that we propose can be used to develop psychometrically robust and implementable measures of fidelity and engagement for complex health interventions that can be used by different target audiences. By considering quality when developing measures, we can be more confident in the interpretation of intervention outcomes drawn from fidelity and engagement studies.

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