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Exploratory randomized controlled trial evaluating the impact of a waiting list control design
Open accessAbstract
BACKGROUND: Employing waiting list control designs in psychological and behavioral intervention research may artificially inflate intervention effect estimates. This exploratory randomized controlled trial tested this proposition in a study employing a brief intervention for problem drinkers, one domain of research in which waiting list control designs are used. METHODS: All participants (N = 185) were provided with brief personalized feedback intervention materials after being randomly allocated either to be told that they were in the intervention condition and that this was the intervention or to be told that they were in the waiting list control condition and that they would receive access to the intervention in four weeks with this information provided in the meantime. RESULTS: A total of 157 participants (85%) were followed-up after 4 weeks. Between-group differences were found in one of four outcomes (proportion within safe drinking guidelines). An interaction was identified between experimental manipulation and stage of change at study entry such that participant change was arrested among those more ready to change and told they were on the waiting list. CONCLUSIONS: Trials with waiting list control conditions may overestimate treatment effects, though the extent of any such bias appears likely to vary between study populations. Arguably they should only be used where this threat to valid inference has been carefully assessed.
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“The literature reports growing concerns over the use of waitlist style control groups in psychotherapy research, as the outcomes of the interventions may be over-estimated with this type of control.64”
From Workplace interventions to improve well-being and reduce burnout for nurses, physicians and allied healthcare professionals: a systematic review. (2023) · cites this paper as [64]
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“Intervention outcomes should also be interpreted with caution because of the potential for overestimation of effect sizes when a waitlist comparison group is used in behavior change research [106].”
From Evaluation of an App-Delivered Psychological Flexibility Skill Training Intervention for Medical Student Burnout and Well-being: Randomized Controlled Trial (2023) · cites this paper as [106]
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“previous research suggests that waitlist participants’ expectations of receiving support at a later time could hinder the self-driven behavior change that they might otherwise have made during the same period [106].”
From Evaluation of an App-Delivered Psychological Flexibility Skill Training Intervention for Medical Student Burnout and Well-being: Randomized Controlled Trial (2023) · cites this paper as [106]
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“it has been noted that such designs may overestimate intervention effects [84].”
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“Athough many studies trialing novel treatments utilize a waitlist or placebo control group, these can artificially inflate the efficacy of the experimental group (Baskin et al., 2003; Cunningham et al., 2013).”
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Background6-Week student wellness program improves psychological wellbeing of students
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BackgroundCare ally-assisted massage for Veterans with chronic neck pain: TOMCATT results
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“Finally, it is important to note that the waiting-list control condition may overestimate treatment effects, although the extent of any such bias is likely to vary among study populations (Cunningham et al., 2013).”
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“These differences also affect collaboration among various social service providers, including healthcare, schools, and communities [33, 34, 35].”
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“We chose an active control group (instead of a waiting-list group) to avoid overestimation of treatment effects [21].”
MethodVelalagan, R., Wu, W. T., John, J. R., Lin, P., & Eapen, V. (2026) · BMC Psychiatry · doi:10.1186/s12888-026-08579-9
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“As such, we used a waitlist-controlled design, which is inherently less rigorous than an RCT and research suggests that behavioral health interventions using this approach may inflate intervention effect (Cunningham et al., 2013).”
Botchway-Commey, E. N., Burton, C., Pace, C. C., Ehrenreich, J. T., Kennedy, S. M., Williams, J. S., Poulakis, Z., DPsychClin, A. M., Anderson, V. A., & Crowe, L. M. (2025) · BMC Psychology · doi:10.1186/s40359-025-03052-w
“Although the waitlist control group method is said to sometimes cause people to stall in their personal efforts to change behaviour [59] and overestimate treat-ment effects, our short waitlist period (i.e., 8 weeks) and regular contact with this group during the waitlist period are expected to…”
Asriati, R., & Oriza, I. I. D. (2025) · Konselor · doi:10.24036/02025142127-0-86
“A wait-list control means that participants who want help will still receive the intervention later, while allowing researchers to analyze the results from the main intervention group (Cunningham et al., 2013).”
Curtis, K., Clarke, H. A., Mina, D. S., Bechsgaard, G., Weinrib, A., Jones, J. S., Au, D., & Katz, J. D. (2025) · OBM Integrative and Complementary Medicine · doi:10.21926/obm.icm.2503041
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“48 Second, the characteristics of the study population and facility may have introduced bias.”
Lauckner, C., Adatorwovor, R., Taylor, E. W., Sesenu, F., Tanner, T., Whitmire, A., Marconi, V. C., Kershaw, T., & Hansen, N. B. (2025) · Addiction Science & Clinical Practice · doi:10.1186/s13722-025-00631-5
“While waitlist-control groups have noted disadvantages, such as inflated effect sizes [36, 37], they are common in alcohol reduction interventions [38–40] and in this case represented an approach that balanced scientific rigor with equity and principles of beneficence.”
Laing, J., McKinnon, A. I., Creswell, C., Ehlers, A., & Wild, J. (2025) · Trials · doi:10.1186/s13063-025-09341-4
“Some research suggests that participants assigned to wait conditions avoid attempting behaviour change on their own and, as such, demonstrate limited improvement [73].”
Bendtsen, M., Åsberg, K., & McCambridge, J. (2022) · Figshare · doi:10.6084/m9.figshare.19777956
Self-citationJensen, M., Hüttenrauch, E., Schmidt, J., Andersson, G., Chavanon, M.-L., & Weise, C. (2020) · Figshare · doi:10.6084/m9.figshare.12257978
Jensen, M., Hüttenrauch, E., Schmidt, J., Andersson, G., Chavanon, M.-L., & Weise, C. (2020) · Figshare · doi:10.6084/m9.figshare.12257963
Kristensen, M. B., Wessel, I., Beck, A. M., Dieperink, K. B., Mikkelsen, T. B., Møller, J.-J. K., & Zwisler, A.-D. (2020) · Figshare · doi:10.6084/m9.figshare.11999325
Craig, S. L., Eaton, A. D., Leung, V. W. Y., Iacono, G., Pang, N., Dillon, F. R., Austin, A., Pascoe, R. V., & Dobinson, C. (2021) · Figshare · doi:10.6084/m9.figshare.14746329
Jensen, M., Hüttenrauch, E., Schmidt, J., Andersson, G., Chavanon, M.-L., & Weise, C. (2020) · Figshare · doi:10.6084/m9.figshare.12257987
Kristensen, M. B., Wessel, I., Beck, A. M., Dieperink, K. B., Mikkelsen, T. B., Møller, J.-J. K., & Zwisler, A.-D. (2020) · Figshare · doi:10.6084/m9.figshare.11999340
Bendtsen, M., Åsberg, K., & McCambridge, J. (2022) · Figshare · doi:10.6084/m9.figshare.19777953
Self-citationJensen, M., Hüttenrauch, E., Schmidt, J., Andersson, G., Chavanon, M.-L., & Weise, C. (2020) · Figshare · doi:10.6084/m9.figshare.12257969
Schormann, A. L. A., Pillny, M., Haß, K., & Lincoln, T. M. (2023) · Figshare · doi:10.6084/m9.figshare.22735638
Collier, E. S., Blomqvist, J., Crawford, J., McCambridge, J., & Bendtsen, M. (2023) · Figshare · doi:10.6084/m9.figshare.24454950
Self-citationBendtsen, M., Åsberg, K., & McCambridge, J. (2022) · Figshare · doi:10.6084/m9.figshare.19777950
Self-citationJensen, M., Hüttenrauch, E., Schmidt, J., Andersson, G., Chavanon, M.-L., & Weise, C. (2020) · Figshare · doi:10.6084/m9.figshare.12257993
Bendtsen, M., Åsberg, K., & McCambridge, J. (2022) · Figshare · doi:10.6084/m9.figshare.19777959
Self-citationKristensen, M. B., Wessel, I., Beck, A. M., Dieperink, K. B., Mikkelsen, T. B., Møller, J.-J. K., & Zwisler, A.-D. (2020) · Figshare · doi:10.6084/m9.figshare.11999352
Jensen, M., Hüttenrauch, E., Schmidt, J., Andersson, G., Chavanon, M.-L., & Weise, C. (2020) · Figshare · doi:10.6084/m9.figshare.12257984
Bendtsen, M., Åsberg, K., & McCambridge, J. (2022) · Figshare · doi:10.6084/m9.figshare.19777944
Self-citationMoghaddam, N., Dawson, D. L., Nikos, E., Turton, J. C., Hawton, A., Law, G. R., Roche, B., Rowan, E., Burge, R., Frost, A. C., et al. (2022) · Figshare · doi:10.6084/m9.figshare.20887251
Kristensen, M. B., Wessel, I., Beck, A. M., Dieperink, K. B., Mikkelsen, T. B., Møller, J.-J. K., & Zwisler, A.-D. (2020) · Figshare · doi:10.6084/m9.figshare.11999331
Metadata
- Authors
- Cunningham, J. A., Kypri, K., & McCambridge, J.
- Affiliations
- Australian National University (AU)
- University of Newcastle Australia (AU)
- London School of Hygiene & Tropical Medicine (GB)
- Corresponding author
- Cunningham, John A
- Venue
- BMC Medical Research Methodology
- Published
- 2013-12
- Volume
- 13
- Issue
- 1
- Pages
- 150-150
- ISSN
- 1471-2288 (ISSN-L)
- PMC
- PMC4029562
- OpenAlex
- W2132268984
- Cited by
- 321
- References
- 40
- Citations by year
- 2026: 18 · 2025: 29 · 2024: 35 · 2023: 41 · 2022: 42 · 2021: 37 · 2020: 33 · 2019: 28 · 2018: 15 · 2017: 17 · 2016: 11 · 2015: 5 · 2014: 10
- FWCI
- 7.62
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- Locations
- BMC Medical Research Methodology (publishedVersion, cc-by)
- Europe PMC (PubMed Central) (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- LSHTM Research Online (London School of Hygiene and Tropical Medicine) (acceptedVersion)
- Figshare (submittedVersion, cc-by)
- ANU Open Research (Australian National University) (submittedVersion, cc-by)
- NOVA (University of Newcastle Australia) (submittedVersion)
- Funders
- Wellcome Trust (WT086516MA)
- Medical Research Council
- Topics
- Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods in Clinical Trials
- Health Sciences › Medicine › Epidemiology › Substance Abuse Treatment and Outcomes
- Social Sciences › Decision Sciences › Statistics, Probability and Uncertainty › Meta-analysis and systematic reviews
- Keywords
- overestimation of treatment effects, brief intervention, problem drinking, personalized feedback, stages of change, alcohol consumption, drinking guidelines
- MeSH terms
- Adult, Alcohol Drinking, Behavior Therapy, Female, Humans, Male, Middle Aged, Research Design, Waiting Lists, Bias, Alcohol-Related Disorders
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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