Strengthening causal inference from randomised controlled trials of complex interventions

Researchers conducting randomised controlled trials (RCTs) of complex interventions face design and analytical challenges that are not fully addressed in existing guidelines. Further guidance is needed to help ensure that these trials of complex interventions are conducted to the highest scientific...

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Autores principales: Leroy, Jef L., Frongillo, Edward A., Kase, B.E., Alonso, Silvia, Chen, M., Dohoo, I., Huybregts, Lieven, Kadiyala, S., Saville, N.M.
Formato: Journal Article
Lenguaje:Inglés
Publicado: BMJ 2022
Materias:
Acceso en línea:https://hdl.handle.net/10568/119825
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author Leroy, Jef L.
Frongillo, Edward A.
Kase, B.E.
Alonso, Silvia
Chen, M.
Dohoo, I.
Huybregts, Lieven
Kadiyala, S.
Saville, N.M.
author_browse Alonso, Silvia
Chen, M.
Dohoo, I.
Frongillo, Edward A.
Huybregts, Lieven
Kadiyala, S.
Kase, B.E.
Leroy, Jef L.
Saville, N.M.
author_facet Leroy, Jef L.
Frongillo, Edward A.
Kase, B.E.
Alonso, Silvia
Chen, M.
Dohoo, I.
Huybregts, Lieven
Kadiyala, S.
Saville, N.M.
author_sort Leroy, Jef L.
collection Repository of Agricultural Research Outputs (CGSpace)
description Researchers conducting randomised controlled trials (RCTs) of complex interventions face design and analytical challenges that are not fully addressed in existing guidelines. Further guidance is needed to help ensure that these trials of complex interventions are conducted to the highest scientific standards while maximising the evidence that can be extracted from each trial. The key challenge is how to manage the multiplicity of outcomes required for the trial while minimising false positive and false negative findings. To address this challenge, we formulate three principles to conduct RCTs: (1) outcomes chosen should be driven by the intent and programme theory of the intervention and should thus be linked to testable hypotheses; (2) outcomes should be adequately powered and (3) researchers must be explicit and fully transparent about all outcomes and hypotheses before the trial is started and when the results are reported. Multiplicity in trials of complex interventions should be managed through careful planning and interpretation rather than through post hoc analytical adjustment. For trials of complex interventions, the distinction between primary and secondary outcomes as defined in current guidelines does not adequately protect against false positive and negative findings. Primary outcomes should be defined as outcomes that are relevant based on the intervention intent and programme theory, declared (ie, registered), and adequately powered. The possibility of confirmatory causal inference is limited to these outcomes. All other outcomes (either undeclared and/or inadequately powered) are secondary and inference relative to these outcomes will be exploratory.
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spelling CGSpace1198252025-10-26T12:51:48Z Strengthening causal inference from randomised controlled trials of complex interventions Leroy, Jef L. Frongillo, Edward A. Kase, B.E. Alonso, Silvia Chen, M. Dohoo, I. Huybregts, Lieven Kadiyala, S. Saville, N.M. research trial methods surveys randomized controlled trials assessment survey design Researchers conducting randomised controlled trials (RCTs) of complex interventions face design and analytical challenges that are not fully addressed in existing guidelines. Further guidance is needed to help ensure that these trials of complex interventions are conducted to the highest scientific standards while maximising the evidence that can be extracted from each trial. The key challenge is how to manage the multiplicity of outcomes required for the trial while minimising false positive and false negative findings. To address this challenge, we formulate three principles to conduct RCTs: (1) outcomes chosen should be driven by the intent and programme theory of the intervention and should thus be linked to testable hypotheses; (2) outcomes should be adequately powered and (3) researchers must be explicit and fully transparent about all outcomes and hypotheses before the trial is started and when the results are reported. Multiplicity in trials of complex interventions should be managed through careful planning and interpretation rather than through post hoc analytical adjustment. For trials of complex interventions, the distinction between primary and secondary outcomes as defined in current guidelines does not adequately protect against false positive and negative findings. Primary outcomes should be defined as outcomes that are relevant based on the intervention intent and programme theory, declared (ie, registered), and adequately powered. The possibility of confirmatory causal inference is limited to these outcomes. All other outcomes (either undeclared and/or inadequately powered) are secondary and inference relative to these outcomes will be exploratory. 2022-06 2022-06-15T07:40:53Z 2022-06-15T07:40:53Z Journal Article https://hdl.handle.net/10568/119825 en Open Access BMJ Leroy, J.L., Frongillo, E.A., Kase, B.E., Alonso, S., Chen, M., Dohoo, I., Huybregts, L., Kadiyala, S. and Saville, N.M. 2022. Strengthening causal inference from randomised controlled trials of complex interventions. BMJ Global Health 7(6): e008597.
spellingShingle research
trial methods
surveys
randomized controlled trials
assessment
survey design
Leroy, Jef L.
Frongillo, Edward A.
Kase, B.E.
Alonso, Silvia
Chen, M.
Dohoo, I.
Huybregts, Lieven
Kadiyala, S.
Saville, N.M.
Strengthening causal inference from randomised controlled trials of complex interventions
title Strengthening causal inference from randomised controlled trials of complex interventions
title_full Strengthening causal inference from randomised controlled trials of complex interventions
title_fullStr Strengthening causal inference from randomised controlled trials of complex interventions
title_full_unstemmed Strengthening causal inference from randomised controlled trials of complex interventions
title_short Strengthening causal inference from randomised controlled trials of complex interventions
title_sort strengthening causal inference from randomised controlled trials of complex interventions
topic research
trial methods
surveys
randomized controlled trials
assessment
survey design
url https://hdl.handle.net/10568/119825
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