Skip to main content

Complex Intervention Trials

  • Living reference work entry
  • First Online:
Principles and Practice of Clinical Trials

Abstract

Clinical trial methodology was developed for pharmaceutical drug development and evaluation. In recent years, trials have expanded to an increasingly diverse range of interventions.

The term complex intervention describes treatments that are multicomponent and include clustering due to specific components, such as the healthcare provider, which cannot be separated from the package of treatment and influence treatment outcomes. This chapter provides an overview of the main considerations in the design and analysis of complex interventions trials.

Initial development of complex interventions is a multidisciplinary endeavor and requires rigorous qualitative and quantitative methods. Understanding both the intervention components and how they interact is crucial for successful development and evaluation of the intervention.

Published guidance on methods for feasibility, piloting, or early phase trials of complex interventions is scarce. However, there are well-established methods for phase III trials of multicomponent interventions that involve clustering. The most commonly used methods, including individually randomized trials with random effects for clusters, cluster randomized trials, and stepped-wedge cluster randomized trials, are described. Analysis focuses on generalized linear (mixed) models; methods for sample size estimation that accommodate the extra variance related to clustering are also provided for a range of designs in this setting.

With careful attention to the correlation structure induced by the chosen design, results can be analyzed in standard statistical software, although small numbers of clusters, and/or small within-cluster sizes, can cause convergence problems.

Statistical analysis results of complex interventions trials, including those relating to components of the intervention, need to be considered alongside economic, qualitative, and behavioral research to ensure that complex interventions can be successfully implemented into routine practice.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Institutional subscriptions

References

  • Austin PC (2010) Estimating multilevel logistic regression models when the number of clusters is low: a comparison of different statistical software procedures. Int J Biostat 6

    Google Scholar 

  • Blencowe NS, Brown JM, Cook JA, Metcalfe C, Morton DG, Nicholl J, Sharples LD, Treweek S, Blazeby JM, Members of the, M. R. C. H. F. T. M. R. N. W (2015) Interventions in randomised controlled trials in surgery: issues to consider during trial design. Trials 16:392

    Article  Google Scholar 

  • Blencowe NS, Mills N, Cook JA, Donovan JL, Rogers CA, Whiting P, Blazeby JM (2016) Standardizing and monitoring the delivery of surgical interventions in randomized clinical trials. Br J Surg 103:1377–1384

    Article  Google Scholar 

  • Boutron I, Altman DG, Moher D, Schulz KF, Ravaud P, Group, C. N (2017) CONSORT Statement for randomized trials of nonpharmacologic treatments: a 2017 update and a CONSORT extension for nonpharmacologic trial abstracts. Ann Intern Med 167:40–47

    Article  Google Scholar 

  • Brown CA, Lilford RJ (2006) The stepped wedge trial design: a systematic review. BMC Med Res Methodol 6:54

    Article  Google Scholar 

  • Browne WJ, Goldstein H, Rasbash J (2001) Multiple membership multiple classification (MMMC) models. Stat Model 1:103–124

    Article  Google Scholar 

  • Campbell MK, Piaggio G, Elbourne DR, Altman DG, Group, C (2012) Consort 2010 statement: extension to cluster randomised trials. BMJ 345:e5661

    Article  Google Scholar 

  • Cisse MBM, Sangare D, Oxborough RM, Dicko A, Dengela D, Sadou A, Mihigo J, George K, Norris L, Fornadel C (2017) A village level cluster-randomized entomological evaluation of combination long-lasting insecticidal nets containing pyrethroid plus PBO synergist in Southern Mali. Malar J 16:477

    Article  Google Scholar 

  • Collins LM, Murphy SA, Strecher V (2007) The multiphase optimization strategy (MOST) and the sequential multiple assignment randomized trial (SMART): new methods for more potent eHealth interventions. Am J Prev Med 32:S112–S118

    Article  Google Scholar 

  • Cook JA, Ramsay CR, Fayers P (2004) Statistical evaluation of learning curve effects in surgical trials. Clin Trials 1:421–427

    Article  Google Scholar 

  • Dickens C, Katon W, Blakemore A, Khara A, Tomenson B, Woodcock A, Fryer A, Guthrie E (2014) Complex interventions that reduce urgent care use in COPD: a systematic review with meta-regression. Respir Med 108:426–437

    Article  Google Scholar 

  • Donner A, Birkett N, Buck C (1981) Randomization by cluster. Sample size requirements and analysis. Am J Epidemiol 114:19

    Google Scholar 

  • Drummond MF, Sculpher MJ, Claxton K, Stoddart GL, Torrance GW (2015) Methods for the economic evaluation of health care programmes, 4th edn. University Press, Oxford

    Google Scholar 

  • Eldridge S, Kerry S (2012) A practical guide to cluster randomised trials in health services research. Wiley, Chichester

    Book  Google Scholar 

  • Eldridge SM, Ashby D, Kerry S (2006) Sample size for cluster randomized trials: effect of coefficient of variation of cluster size and analysis method. Int J Epidemiol 35:1292–1300

    Article  Google Scholar 

  • Emery JD, Gray V, Walter FM, Cheetham S, Croager EJ, Slevin T, Saunders C, Threlfall T, Auret K, Nowak AK, Geelhoed E, Bulsara M, Holman CDJ (2017) The Improving Rural Cancer Outcomes Trial: a cluster-randomised controlled trial of a complex intervention to reduce time to diagnosis in rural cancer patients in Western Australia. Br J Cancer 117:1459–1469

    Article  Google Scholar 

  • Erasmus V, Huis A, Oenema A, Van Empelen P, Boog MC, Van Beeck EH, Polinder S, Steyerberg EW, Richardus JH, Vos MC, Van Beeck EF (2011) The ACCOMPLISH study. A cluster randomised trial on the cost-effectiveness of a multicomponent intervention to improve hand hygiene compliance and reduce healthcare associated infections. BMC Public Health 11:721

    Article  Google Scholar 

  • Fuller C, Michie S, Savage J, Mcateer J, Besser S, Charlett A, Hayward A, Cookson BD, Cooper BS, Duckworth G, Jeanes A, Roberts J, Teare L, Stone S (2012) The Feedback Intervention Trial (FIT)-improving hand-hygiene compliance in UK healthcare workers: a stepped wedge cluster randomised controlled trial. PLoS One 7:e41617

    Article  Google Scholar 

  • Goldstein H, Rasbash J (1996) Improved approximations for multilevel models with binary responses. J R Stat Soc Ser A-Stat Soc 159:505–513

    Article  MathSciNet  MATH  Google Scholar 

  • Hemming K, Taljaard M (2016) Sample size calculations for stepped wedge and cluster randomised trials: a unified approach. J Clin Epidemiol 69:137–146

    Article  Google Scholar 

  • Hemming K, Taljaard M, Forbes A (2018) Modeling clustering and treatment effect heterogeneity in parallel and stepped-wedge cluster randomized trials. Stat Med 37:883–898

    Article  MathSciNet  Google Scholar 

  • Hoffmann TC, Glasziou PP, Boutron I, Milne R, Perera R, Moher D, Altman DG, Barbour V, Macdonald H, Johnston M, Lamb SE, Dixon-Woods M, Mcculloch P, Wyatt JC, Chan AW, Michie S (2014) Better reporting of interventions: template for intervention description and replication (TIDieR) checklist and guide. BMJ 348:g1687

    Article  Google Scholar 

  • Jordan S, Gabe-Walters ME, Watkins A, Humphreys I, Newson L, Snelgrove S, Dennis MS (2015) Nurse-led medicines’ monitoring for patients with dementia in care homes: a pragmatic cohort stepped wedge cluster randomised trial. PLoS One 10:e0140203

    Article  Google Scholar 

  • Kahan BC, Morris TP (2013) Assessing potential sources of clustering in individually randomised trials. BMC Med Res Methodol 13:58

    Article  Google Scholar 

  • Loudon K, Zwarenstein M, Sullivan F, Donnan P, Treweek S (2013) Making clinical trials more relevant: improving and validating the PRECIS tool for matching trial design decisions to trial purpose. Trials 14:115

    Article  Google Scholar 

  • Mars T, Ellard D, Carnes D, Homer K, Underwood M, Taylor SJ (2013) Fidelity in complex behaviour change interventions: a standardised approach to evaluate intervention integrity. BMJ Open 3:e003555

    Article  Google Scholar 

  • Mcculloch P, Altman DG, Campbell WB, Flum DR, Glasziou P, Marshall JC, Nicholl J, Balliol C, Aronson JK, Barkun JS, Blazeby JM, Boutron IC, Campbell WB, Clavien PA, Cook JA, Ergina PL, Feldman LS, Flum DR, Maddern GJ, Nicholl J, Reeves BC, Seiler CM, Strasberg SM, Meakins JL, Ashby D, Black N, Bunker J, Burton M, Campbell M, Chalkidou K, Chalmers I, De Leval M, Deeks J, Ergina PL, Grant A, Gray M, Greenhalgh R, Jenicek M, Kehoe S, Lilford R, Littlejohns P, Loke Y, Madhock R, Mcpherson K, Meakins J, Rothwell P, Summerskill B, Taggart D, Tekkis P, Thompson M, Treasure T, Trohler U, Vandenbroucke J (2009) No surgical innovation without evaluation: the IDEAL recommendations. Lancet 374:1105–1112

    Article  Google Scholar 

  • Medical_Research_Council (2000) A framework for the development and evaluation of RCTs for complex interventions to improve health

    Google Scholar 

  • Medical_Research_Council (2008) Developing and evaluating complex interventions: new guidance

    Google Scholar 

  • Moher D, Hopewell S, Schulz KF, Montori V, Gotzsche PC, Devereaux PJ, Elbourne D, Egger M, Altman DG, Consolidated Standards of Reporting Trials, G (2010) CONSORT 2010 explanation and elaboration: updated guidelines for reporting parallel group randomised trials. J Clin Epidemiol 63:e1–e37

    Article  Google Scholar 

  • Mohler R, Kopke S, Meyer G (2015) Criteria for Reporting the Development and Evaluation of Complex Interventions in healthcare: revised guideline (CReDECI 2). Trials 16:204

    Article  Google Scholar 

  • Mohr DC, Carmody T, Erickson L, Jin L, Leader J (2011) Telephone-administered cognitive behavioral therapy for veterans served by community-based outpatient clinics. J Consult Clin Psychol 79:261–265

    Article  Google Scholar 

  • Papachristofi O, Jenkins D, Sharples LD (2016a) Assessment of learning curves in complex surgical interventions: a consecutive case-series study. Trials 17:266

    Article  Google Scholar 

  • Papachristofi O, Klein A, Sharples L (2016b) Evaluation of the effects of multiple providers in complex surgical interventions. Stat Med 35:5222–5246

    Article  MathSciNet  Google Scholar 

  • Perez MC, Minoyan N, Ridde V, Sylvestre MP, Johri M (2018) Comparison of registered and published intervention fidelity assessment in cluster randomised trials of public health interventions in low- and middle-income countries: systematic review. Trials 19:410

    Article  Google Scholar 

  • Pocock SJ (1983) Clinical trials: a practical approach. Wiley, Chichester

    Google Scholar 

  • Rabe-Hesketh S and Skrondal A (2012) Mulilevel and longitudinal modelling using Stata. Stata Press, Texas

    Google Scholar 

  • Richards DA, Hallberg IR (2015) Complex interventions in health. Routledge, Oxford

    Book  Google Scholar 

  • Richardson E, Redden DT (2014) Moving towards multiple site outcomes in spinal cord injury pain clinical trials: an issue of clustered observations in trial design and analysis. J Spinal Cord Med 37:278–287

    Article  Google Scholar 

  • Roberts C, Walwyn R (2013) Design and analysis of non-pharmacological treatment trials with multiple therapists per patient. Stat Med 32:81–98

    Article  MathSciNet  Google Scholar 

  • Sharples L, Everett C, Singh J, Mills C, Spyt T, Abu-Omar Y, Fynn S, Thorpe B, Stoneman V, Goddard H, Fox-Rushby J, Nashef S (2018) Amaze: a double-blind, multicentre randomised controlled trial to investigate the clinical effectiveness and cost-effectiveness of adding an ablation device-based maze procedure as an adjunct to routine cardiac surgery for patients with pre-existing atrial fibrillation. Health Technol Assess 22:1–132

    Article  Google Scholar 

  • Surr CA, Walwyn RE, Lilley-Kelly A, Cicero R, Meads D, Ballard C, Burton K, Chenoweth L, Corbett A, Creese B, Downs M, Farrin AJ, Fossey J, Garrod L, Graham EH, Griffiths A, Holloway I, Jones S, Malik B, Siddiqi N, Robinson L, Stokes G, Wallace D (2016) Evaluating the effectiveness and cost-effectiveness of Dementia Care Mapping to enable person-centred care for people with dementia and their carers (DCM-EPIC) in care homes: study protocol for a randomised controlled trial. Trials 17:300

    Article  Google Scholar 

  • Turner RM, White IR, Croudace T, Group, P. I. P. S (2007) Analysis of cluster randomized cross-over trial data: a comparison of methods. Stat Med 26:274–289

    Article  MathSciNet  Google Scholar 

  • Ukoumunne OC, Thompson SG (2001) Analysis of cluster randomized trials with repeated cross-sectional binary measurements. Stat Med 20:417–433

    Article  Google Scholar 

  • Walwyn R, Roberts C (2010) Therapist variation within randomised trials of psychotherapy: implications for precision, internal and external validity. Stat Methods Med Res 19:291–315

    Article  MathSciNet  Google Scholar 

  • Walwyn R, Roberts C (2017) Meta-analysis of standardised mean differences from randomised trials with treatment-related clustering associated with care providers. Stat Med 36:1043–1067

    Article  MathSciNet  Google Scholar 

  • Wilson DT, Walwyn RE, Brown J, Farrin AJ, Brown SR (2016) Statistical challenges in assessing potential efficacy of complex interventions in pilot or feasibility studies. Stat Methods Med Res 25:997–1009

    Article  MathSciNet  Google Scholar 

  • Woertman W, De Hoop E, Moerbeek M, Zuidema SU, Gerritsen DL, Teerenstra S (2013) Stepped wedge designs could reduce the required sample size in cluster randomized trials. J Clin Epidemiol 66:752–758

    Article  Google Scholar 

  • Yuen WW, Wong WC, Tang CS, Holroyd E, Tiwari AF, Fong DY, Chin WY (2013) Evaluating the effectiveness of personal resilience and enrichment programme (PREP) for HIV prevention among female sex workers: a randomised controlled trial. BMC Public Health 13:683

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Linda Sharples .

Editor information

Editors and Affiliations

Section Editor information

Rights and permissions

Reprints and permissions

Copyright information

© 2020 Springer Nature Switzerland AG

About this entry

Check for updates. Verify currency and authenticity via CrossMark

Cite this entry

Sharples, L., Papachristofi, O. (2020). Complex Intervention Trials. In: Piantadosi, S., Meinert, C. (eds) Principles and Practice of Clinical Trials. Springer, Cham. https://doi.org/10.1007/978-3-319-52677-5_245-1

Download citation

  • DOI: https://doi.org/10.1007/978-3-319-52677-5_245-1

  • Received:

  • Accepted:

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-52677-5

  • Online ISBN: 978-3-319-52677-5

  • eBook Packages: Springer Reference MathematicsReference Module Computer Science and Engineering

Publish with us

Policies and ethics