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Background In individually randomised trials we might expect interventions delivered in groups or by care providers to result in clustering of outcomes for participants treated in the same group or by the same care provider. In partially nested randomised controlled trials (pnRCTs) this clustering only occurs in one trial arm, commonly the intervention arm. It is important to measure and account for between-cluster variability in trial design and analysis. We compare analysis approaches for pnRCTs with continuous outcomes, investigating the impact on statistical inference of cluster sizes, coding of the non-clustered arm, intracluster correlation coefficient (ICCs), and differential variance between intervention and control arm, and provide recommendations for analysis. Methods We performed a simulation study assessing the performance of six analysis approaches for a two-arm pnRCT with a continuous outcome. These include: linear regression model; fully clustered mixed-effects model with singleton clusters in control arm; fully clustered mixed-effects model with one large cluster in control arm; fully clustered mixed-effects model with pseudo clusters in control arm; partially nested homoscedastic mixed effects model, and partially nested heteroscedastic mixed effects model. We varied the cluster size, number of clusters, ICC, and individual variance between the two trial arms. Results All models provided unbiased intervention effect estimates. In the partially nested mixed-effects models, methods for classifying the non-clustered control arm had negligible impact. Failure to account for even small ICCs resulted in inflated Type I error rates and over-coverage of confidence intervals. Fully clustered mixed effects models provided poor control of the Type I error rates and biased ICC estimates. The heteroscedastic partially nested mixed-effects model maintained relatively good control of Type I error rates, unbiased ICC estimation, and did not noticeably reduce power even with homoscedastic individual variances across arms. Conclusions In general, we recommend the use of a heteroscedastic partially nested mixed-effects model, which models the clustering in only one arm, for continuous outcomes similar to those generated under the scenarios of our simulations study. However, with few clusters (3–6), small cluster sizes (5–10), and small ICC (≤0.05) this model underestimates Type I error rates and there is no optimal model.

Evidence for parenting programs to improve wellbeing in children under three is inconclusive. We investigated the fidelity, impact, and cost-effectiveness of two parenting programs delivered within a longitudinal proportionate delivery model ('E-SEE Steps'). Eligible parents with a child ≤ 8 weeks were recruited into a parallel two-arm, assessor blinded, randomized controlled, community-based, trial with embedded economic and process evaluations. Post-baseline randomization applied a 5:1 (intervention-to-control) ratio, stratified by primary (child social-emotional wellbeing (ASQ:SE-2)) and key secondary (maternal depression (PHQ-9)) outcome scores, sex, and site. All intervention parents received the Incredible Years® Baby Book (IY-B), and were offered the targeted Infant (IY-I)/Toddler (IY-T) program if eligible, based on ASQ:SE-2/PHQ-9 scores. Control families received usual services. Fidelity data were analysed descriptively. Primary analysis applied intention to treat. Effectiveness analysis fitted a marginal model to outcome scores. Cost-effectiveness analysis involved Incremental Cost-Effectiveness Ratios (ICERs). The target sample (N = 606) was not achieved; 341 mothers were randomized (285:56), 322 (94%) were retained to study end. Of those eligible for the IY-I (n = 101), and IY-T (n = 101) programs, 51 and 21 respectively, attended. Eight (of 14) groups met the 80% self-reported fidelity criteria. No significant differences between arms were found for adjusted mean difference scores; ASQ:SE-2 (3.02, 95% CI: -0.03, 6.08, p = 0.052), PHQ-9 (-0.61; 95% CI: -1.34, 0.12, p = 0.1). E-SEE Steps had higher costs, but improved mothers' Health-related Quality of Life (0.031 Quality Adjusted Life Year (QALY) gain), ICER of £20,062 per QALY compared to control. Serious adverse events (n = 86) were unrelated to the intervention. E-SEE Steps was not effective, but was borderline cost-effective. The model was delivered with varying fidelity, with lower-than-expected IY-T uptake. Changes to delivery systems and the individual programs may be needed prior to future evaluation. International Standard Randomized Controlled Trial Number: ISRCTN11079129.

Manuscripts should include all the experimental and statistical details that are needed to replicate the experiments and analyses reported in them.Manuscripts should include all the experimental and statistical details that are needed to replicate the experiments and analyses reported in them.

Background Adaptive designs are increasingly being used in clinical trials within diverse clinical areas. They can offer advantages over traditional non-adaptive approaches, including improved efficiency and patient benefit. The level of improvement observed in practice depends to a large degree on conducting interim analyses (at which adaptations can be made to the trial based on collected data) rapidly and to a high standard. Methods The ROBust INterims for adaptive designs (ROBIN) project aimed to identify best practice for conducting high-quality and rapid interim analyses. This was done through evidence synthesis of published work, qualitative research with trial stakeholders working at public sector clinical trials units, engagement with patients and the public, and a meeting of trial stakeholders to discuss findings and agree recommendations. Results This paper provides recommendations for teams that conduct adaptive trials about how to ensure interim analyses are done rapidly and to a high standard. We break down recommendations by stage of the trial. We also identify a lack of methodology on how best to involve patients in adaptive trials and related decision-making. A limitation of our recommendations is that the research was mostly focused on UK academic settings, although we believe much of the recommendations are relevant in other countries and to industry-sponsored trials. Conclusions When following the recommendations outlined in this paper, the process of planning and executing interim analyses will be smoother; in turn, this will lead to more benefits from using adaptive designs.

Background/objectives: Maternal adiposity is a known risk factor for adverse pregnancy outcomes, yet routine antenatal care primarily relies on body mass index (BMI), which has limitations. This study aimed to explore the acceptability of incorporating a broader range of adiposity measurements into early pregnancy antenatal care, assessing pregnant women’s perceptions to inform implementation strategies. Methods: A qualitative study using semi-structured interviews was conducted with 14 pregnant women purposively sampled to capture variation in BMI, age, and parity. Interviews occurred approximately 4–5 months post-measurement experience. The Theoretical Framework of Acceptability (TFA) guided thematic analysis of transcribed data, with independent coding to ensure rigour. Results: Participants generally viewed the current reliance on BMI as outdated and expressed neutral to positive attitudes toward the use of more detailed adiposity measurements. Most reported little emotional discomfort with the process. However, some reflected likelihood of more body self-consciousness had it been their first pregnancy. Time involved in measurements was not seen as burdensome, however waiting between procedures was a minor inconvenience. Self-assessing body shape was described as difficult. Women emphasised the importance of choice, autonomy, and informed consent, especially in relation to partner involvement, the gender of the anthropometrist, and the nature of the procedures. Clear, advance communication and supportive explanations during appointments were seen as essential to ensuring a positive experience. Conclusions: Expanding adiposity assessments in early pregnancy is acceptable to women if implemented ethically, prioritising consent, privacy, emotional safety, and effective communication. Integration into routine care requires staff training and pre-appointment guidance.

Many studies in the biomedical research literature report analyses that fail to recognise important data dependencies from multilevel or complex experimental designs. Statistical inferences resulting from such analyses are unlikely to be valid and are often potentially highly misleading. Failure to recognise this as a problem is often referred to in the statistical literature as a unit of analysis (UoA) issue. Here, by analysing two example datasets in a simulation study, we demonstrate the impact of UoA issues on study efficiency and estimation bias, and highlight where errors in analysis can occur. We also provide code (written in R) as a resource to help researchers undertake their own statistical analyses.

Objectives We systematically reviewed how investigators argued for and justified the validity of their instrumental variables (IV) in clinical studies of dementia and neurodegenerative disease. Methods We included studies using IV analysis with observational data to investigate causal effects in clinical research studies of dementia and neurodegenerative disease. We reported the subject‐matter argumentation, falsification test, and study design strategies used to satisfy the three assumptions of a valid IV: relevance, exclusion restriction, and exchangeability. Results Justification for the relevance assumption was performed in all 12 included studies, exclusion restriction in seven studies, and exchangeability in nine studies. Two subject‐matter argumentation strategies emerged from seven studies on the relevance of their IV. All studies except one provided quantitative evidence for the strength of the association between the IV and exposure variable. Four argumentation strategies emerged for exclusion restriction from six studies. Four falsification tests were performed across three studies. Three argumentation strategies emerged for exchangeability across four studies. Nine falsification tests were performed across nine studies. Two notable study design strategies were reported. Conclusion Our results reinforce IV analysis as a feasible option for clinical researchers in dementia and neurodegenerative disease by clarifying known strategies used to validate an IV.

Background In the UK, around 93,000 (0.8%) children and young people (CYP) are experiencing specific phobias that have a substantial impact on daily life. The current gold-standard treatment—multi-session cognitive behavioural therapy (CBT) – is effective at reducing specific phobia severity; however, CBT is time consuming, requires specialist CBT therapists, and is often at great cost and limited availability. A briefer variant of CBT called one session treatment (OST) has been found to offer similar clinical effectiveness for specific phobia as multi-session CBT. The aim of this study was to assess the cost-effectiveness of OST compared to multi-session CBT for CYP with specific phobias through the Alleviating Specific Phobias Experienced by Children Trial (ASPECT), a two-arm, pragmatic, multi-centre, non-inferiority randomised controlled trial. Methods CYP aged seven to 16 years with specific phobias were recruited nationally via Health and Social Care pathways, remotely randomised to the intervention group (OST) or the control group (CBT-based therapies) and analysed ( n  = 267). Resource use based on NHS and personal social services perspective and quality adjusted life years (QALYs) measured by EQ-5D-Y were collected at baseline and at six-month follow-up. Incremental cost-effectiveness ratio (ICER) was calculated, and non-parametric bootstrapping was conducted to capture the uncertainty around the ICER estimates. The results were presented on a cost-effectiveness acceptability curve (CEAC). A set of sensitivity analyses (including taking a societal perspective) were conducted to assess the robustness of the primary findings. Results After adjustment and bootstrapping, on average CYP in the OST group incurred less costs (incremental cost was -£302.96 (95% CI -£598.86 to -£28.61)) and maintained similar improvement in QALYs (QALYs gained 0.002 (95% CI − 0.004 to 0.008)). The CEAC shows that the probability of OST being cost-effective was over 95% across all the WTP thresholds. Results of a set of sensitivity analyses were consistent with the primary outcomes. Conclusion Compared to CBT, OST produced a reduction in costs and maintained similar improvement in QALYs. Results from both primary and sensitivity analyses suggested that OST was highly likely to be cost saving. Trial registration ISRCTN19883421 (30/11/2016).

IntroductionObservational studies represent an alternative to estimate real-world causal effects in the absence of available randomised controlled trials (RCTs). Target trial emulation is a framework for the application of RCT design principles to emulate a hypothetical open-label RCT (the hypothetical target trial) using existing observational data as the primary data source as opposed to the prospective recruitment and measurement of randomised units. The aim of this systematic review is to investigate the practices of studies applying the target trial emulation framework to evaluate the effectiveness of interventions.Methods and analysisWe will systematically search in Medline (via Ovid), Embase (via Ovid, entries from medRxiv are included), PsycINFO (via Ovid), SCOPUS, Web of Science, Cochrane Library, the ISRCTN registry and ClinicalTrials.gov for all study reports and protocols which used the trial emulation framework (without time restriction). We will extract information concerning study design, data source, analysis, results, interpretation and dissemination. Two reviewers will perform study selection, data extraction and quality assessment. Disagreements between reviewers will be resolved by a third reviewer. A narrative approach will be used to synthesise and report qualitative and quantitative data. Reporting of the review will be informed by Preferred Reporting Items for Systematic Review and Meta-Analysis guidance (PRISMA).Ethics and disseminationEthical approval is not required as it is a protocol for a systematic review. Findings will be disseminated through peer-reviewed publications and conference presentations.

Background In proportionate or adaptive interventions, the dose or intensity can be adjusted based on individual need at predefined decision stages during the delivery of the intervention. The development of such interventions may require an evaluation of the effectiveness of the individual stages in addition to the whole intervention. However, evaluating individual stages of an intervention has various challenges, particularly the statistical design and analysis. This review aimed to identify the use of trials of proportionate interventions and how they are being designed and analysed in current practice. Methods We searched MEDLINE, Web of Science and PsycINFO for articles published between 2010 and 2015 inclusive. We considered trials of proportionate interventions in all fields of research. For each trial, its aims, design and analysis were extracted. The data synthesis was conducted using summary statistics and a narrative format. Results Our review identified 44 proportionate intervention trials, comprising 28 trial results, 13 protocols and three secondary analyses. These were mostly described as stepped care ( n =37) and mainly focussed on mental health research ( n =30). The other studies were aimed at finding an optimal adaptive treatment strategy ( n =7) in a variety of therapeutic areas. Further terminology used included adaptive intervention, staged intervention, sequentially multiple assignment trial or a two-phase design. The median number of decision stages in the interventions was two and only one study explicitly evaluated the effect of the individual stages. Conclusions Trials of proportionate staged interventions are being used predominantly within the mental health field. However, few studies consider the different stages of the interventions, either at the design or the analysis phase, and how they may interact with one another. There is a need for further guidance on the design, analyses and reporting across trials of proportionate interventions. Trial registration Prospero, CRD42016033781. Registered on 2 February 2016.