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Protocol for a bandit-based response adaptive trial to evaluate the effectiveness of brief self-guided digital interventions for reducing psychological distress in university students: The Vibe Up Study.

Huckvale, K.; Hoon, L.; Stech, E.; Newby, J.; Zheng, W.-Y.; Han, J.; Vasa, R.; Gupta, S.; Barnett, S.; Senadeera, M.; Cameron, S.; Kurniawan, S.; Agarwal, A.; Kupper, J. F.; Asbury, J.; Willie, D.; Grant, A.; Cutler, H.; Parkinson, B.; Ahumada-Canale, A.; Beames, J.; Logothetis, R.; Bautista, M.; Rosenberg, J.; Shvetcov, A.; Quinn, T.; Mackinnon, A.; Rana, S.; Tran, T.; Rosenbaum, S.; Mouzakis, K.; Werner-Seidler, A.; Whitton, A.; Venkatesh, S.; Christensen, H.

2022-12-06 psychiatry and clinical psychology
10.1101/2022.12.05.22283129 medRxiv
Show abstract

IntroductionMeta-analytic evidence confirms a range of interventions, including mindfulness, physical activity and sleep hygiene, can reduce psychological distress in university students. However, it is unclear which intervention is most effective. Artificial intelligence (AI) driven adaptive trials may be an efficient method to determine what works best and for whom. The primary purpose of the study is to rank the effectiveness of mindfulness, physical activity, sleep hygiene and an active control on reducing distress, using a multi-arm contextual bandit-based AI-adaptive trial method. Furthermore, the study will explore which interventions have the largest effect for students with different levels of baseline distress severity. Methods and analysisThe Vibe Up study is a pragmatically-oriented, decentralised AI-adaptive group sequential randomised controlled trial (RCT) comparing the effectiveness of one of three brief, two week digital self-guided interventions (mindfulness, physical activity, or sleep hygiene) or active control (ecological momentary assessment) in reducing self-reported psychological distress in Australian university students. The adaptive trial methodology involves up to 12 sequential mini-trials that allow for the optimisation of allocation ratios. The primary outcome is change in psychological distress (DASS-21 total score) from pre-intervention to post-intervention. Secondary outcomes include change in depression, anxiety, and stress (measured by DASS-21 subscales) from pre-intervention to post-intervention. Planned contrasts will compare the four groups (i.e., the three intervention and control) using self-reported psychological distress at pre-specified time points for interim analyses. The study aims to determine the best performing intervention, as well as ranking of other interventions. Ethics and disseminationEthical approval was sought and obtained from the UNSW Sydney Human Research Ethics Committee (HREC A, HC200466). A trial protocol adhering to the requirements of the Guideline for Good Clinical Practice [1] was prepared for and approved by the Sponsor, UNSW Sydney (Protocol number: HC200466_CTP). Registration detailsThe trial is registered with the Australian New Zealand Clinical Trials Registry (AC-TRN12621001223820). STRENGTHS AND LIMITATIONS OF THIS STUDYO_ST_ABSStrengthsC_ST_ABSO_LIThe study addresses an important clinical question using novel, advanced methods C_LIO_LIThe trial uses short-duration interventions designed to improve coping responses to transient stressors, which addresses the most common needs of university students C_LIO_LIA value of information analysis is included to compare the value of the new trial methods with traditionalapproaches C_LIO_LIDigital phenotyping is used to explore smartphone sensor information with clinical outcomes C_LI WeaknessesO_LIMore than 12 mini-trials might be required to determine the ranking for the interventions C_LIO_LIThe interventions may prove to be of the same level of effectiveness for each level of severity C_LIO_LIInterventions other than those examined in this study, such as CBT, may be more effective and remain untested C_LIO_LIThe methodology assumes that the three digital interventions are configured to deliver similar doses and/or have approximate fidelity with standard methods C_LI

Published in BMJ Open (predicted rank #1) · training set

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