Evidence map›Paper›PMID 41578192›Full record

SynthesisBMC medical research methodology2026

Non-adherence in randomised controlled trials: empirical comparison of treatment policy and efficacy estimands using individual participant data.

Mohammod B A Mostazir, Joshua E J Buckman, Nicola Wiles, Glyn Lewis, Steve Pilling, Rob Saunders, David Kessler, Chris Salisbury, Gareth Ambler, Zachary D Cohen and 6 more

Abstract readComparative StudyMeta-Analysis
In one paragraph

Synthesis in BMC medical research methodology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

16 authors.

Mohammod B A MostazirFaculty of Health and Life Sciences, School of Psychology, Mood Disorder Centre, University of Exeter, Exeter, EX4 4QG, UK. m.mostazir@exeter.ac.uk.ORCID http://orcid.org/0000-0002-8657-515X
Joshua E J BuckmanCentre for Outcomes Research and Effectiveness (CORE), Research Department of Clinical, Educational & Health Psychology, University College London, London, WC1E 7HB, UK.
Nicola WilesBristol Medical School, Centre for Academic Mental Health, Population Health Sciences, University of Bristol, Canynge Hall, 39 Whatley Road, Bristol, BS8 2PS, UK.
Glyn LewisCentre for Outcomes Research and Effectiveness (CORE), Research Department of Clinical, Educational & Health Psychology, University College London, London, WC1E 7HB, UK.
Steve PillingCentre for Outcomes Research and Effectiveness (CORE), Research Department of Clinical, Educational & Health Psychology, University College London, London, WC1E 7HB, UK.
Rob SaundersCentre for Outcomes Research and Effectiveness (CORE), Research Department of Clinical, Educational & Health Psychology, University College London, London, WC1E 7HB, UK.
David KesslerBristol Medical School, Centre for Academic Mental Health, Population Health Sciences, University of Bristol, Canynge Hall, 39 Whatley Road, Bristol, BS8 2PS, UK.
Chris SalisburyCentre for Academic Primary Care, Bristol Medical School, Population Health Sciences, University of Bristol, Canynge Hall, 39 Whatley Road, Bristol, BS8 2PS, UK.
Gareth AmblerDepartment of Statistical Science, University College London, Gower Street, London, WC1E 6BT, UK.
Zachary D CohenDepartment of Psychology, University of Arizona, Tucson, United States of America.
Steven D HollonDepartment of Psychology, Vanderbilt University, Nashville, TN, 37023, United States.
Simon GilbodyHull York Medical School and Department of Health Sciences, University of York, York, United Kingdom.
Tony KendrickPrimary Care Research Centre, Population Sciences & Medical Education, University of Southampton, Aldermoor Health Centre, Primary Care, Southampton, SO16 5ST, United Kingdom.
Edward Robert WatkinsFaculty of Health and Life Sciences, School of Psychology, Mood Disorder Centre, University of Exeter, Exeter, EX4 4QG, UK.
William Edward HenleyDepartment of Health and Community Sciences, Medical School, University of Exeter, University of Exeter, Exeter, EX1 2LU, UK.
Rod S TaylorMRC/CSO Social and Public Health Sciences Unit & Robertson Centre for Biostatistics, Institute of Health and Well Being, University of Glasgow, Glasgow, G2 3AX, UK.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundNon-adherence to interventions is common in randomized controlled trials (RCTs), complicating the interpretation of treatment effects. The intention-to-treat (ITT) principle estimates the treatment effect of assignment to intervention but does not reflect efficacy among those who adhere. Per-protocol (PP) analyses attempt to address this but introduce selection bias by violating randomisation. The complier average causal effect (CACE) provides an efficacy estimand among compliers while preserving randomisation. This study aimed to provide an empirical comparison of ITT, PP, and CACE approaches using individual participant data (IPD) from trials of depression interventions in primary care.

methodsWe analysed IPD from the Depression in General Practice (Dep-GP) collaboration, comprising seven eligible RCTs with 3,467 participants. Trials reported continuous (depression symptom scores) or binary (treatment response) outcomes. Adherence was defined within the intervention group. We conducted a two-stage IPD meta-analysis to estimate treatment effects under ITT, PP, and CACE. Results were expressed as differences in standardised mean difference (ΔSMD) for continuous outcomes and as ratios of odds ratios (ROR) for binary outcomes. One-stage mixed-effects models were performed as secondary analyses.

resultsFor binary outcomes, both PP and CACE analyses produced larger effects than ITT (ROR for PP vs ITT: 1.09; 95% CI, 1.05–1.14; P < .001; CACE vs ITT: 1.19; 95% CI, 1.00–1.42; P < .05). For continuous outcomes, CACE yielded a larger effect than ITT (ΔSMD = 0.10; 95% CI, 0.01–0.20; P < .05), while PP did not differ from ITT (ΔSMD = 0.03; 95% CI, –0.01 to 0.08; P = .167). Sensitivity analysis, excluding the TREAD trial, yielded larger effect by the PP method (ΔSMD = 0.05; 95% CI, 0.01–0.09; P < .05). DISCUSSION: Our findings demonstrate that CACE provides a causal efficacy estimand that diverges from the treatment policy effect estimated by ITT, while PP yields similar but potentially biased results. This highlights the importance of distinguishing between estimands in the presence of non-adherence and illustrates empirically how they differ in practice.

conclusionsCurrent RCT reporting recommendations should be updated to require routine reporting of CACE alongside ITT, together with adherence information, to provide a more complete and transparent account of treatment effects.

Indexed as

DepressionPatient ComplianceRandomized Controlled Trials as TopicHumansIntention to Treat AnalysisPrimary Health CareSecondary Data AnalysisTreatment OutcomeComplier average causal effect (CACE)EstimandsIndividual patient data (IPD) meta-analysisIntention-to-treatNon-adherencePer-protocol (PP)Randomised controlled trials (RCTs)

Identifiers

PMID41578192
PMCPMC12914939

What OpenQuestion holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.