Thrive at Work Wellbeing Premium - Evaluation of a Cluster Randomised Controlled Trial

Last registered on October 17, 2018

Pre-Trial

Trial Information

General Information

Title
Thrive at Work Wellbeing Premium - Evaluation of a Cluster Randomised Controlled Trial
RCT ID
AEARCTR-0003420
Initial registration date
October 15, 2018

Initial registration date is when the trial was registered.

It corresponds to when the registration was submitted to the Registry to be reviewed for publication.

First published
October 16, 2018, 12:30 AM EDT

First published corresponds to when the trial was first made public on the Registry after being reviewed.

Last updated
October 17, 2018, 8:08 AM EDT

Last updated is the most recent time when changes to the trial's registration were published.

Locations

Primary Investigator

Affiliation
University of Warwick

Other Primary Investigator(s)

PI Affiliation
West Midlands Combined Authority
PI Affiliation
Rand Europe

Additional Trial Information

Status
On going
Start date
2018-07-15
End date
2020-02-28
Secondary IDs
Abstract
Good employee health and wellbeing is of key importance to employers and the economy. For example in the workplace, 6.5m employees reported musculoskeletal problems in 2008 and this is predicted to rise to 7m employees by 2030. Similarly the impact of mental ill health in the West Midlands is significant; overall mental ill health costs the West Midlands an estimated £12.5bn annually, equivalent to £3,100 per population head, per year. As a setting for health promotion, workplaces enable access to large groups of people to promote health and wellbeing. The increase in the last decade of schemes aimed at changing the health related behaviour of the public has been accompanied by evidence that even small incentives can positively influence choices. The aim is to evaluate the effectiveness of a cluster randomised controlled trial offering wellbeing monetary incentives to small-medium enterprises in the West Midlands. This is to establish whether small-medium enterprises will improve their health and wellbeing offer and achieve higher employee awareness and participation in the offer in response to a monetary wellbeing incentive.
External Link(s)

Registration Citation

Citation
Lilford, Richard, Sean Russell and Alex Sutherland. 2018. "Thrive at Work Wellbeing Premium - Evaluation of a Cluster Randomised Controlled Trial." AEA RCT Registry. October 17. https://doi.org/10.1257/rct.3420-2.0
Former Citation
Lilford, Richard, Sean Russell and Alex Sutherland. 2018. "Thrive at Work Wellbeing Premium - Evaluation of a Cluster Randomised Controlled Trial." AEA RCT Registry. October 17. https://www.socialscienceregistry.org/trials/3420/history/35817
Sponsors & Partners

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Experimental Details

Interventions

Intervention(s)
A workplace health and wellbeing initiative (Thrive at Work) with or without a monetary incentive:
Intervention 1: 100% of the monetary incentive + Thrive at Work
Intervention 2: 50% of the monetary incentive + Thrive at Work
Control 1: Thrive at work
Control 2: Thrive at work (no baseline measures)
Intervention Start Date
2018-12-02
Intervention End Date
2019-12-02

Primary Outcomes

Primary Outcomes (end points)
Does your organisation take positive action on health and wellbeing?
Primary Outcomes (explanation)
Whether SMEs will improve their health and wellbeing offer in response to a monetary wellbeing incentive

Secondary Outcomes

Secondary Outcomes (end points)
Employee wellbeing. Employer and employee:
• Awareness of information provision
• Likelihood of taking part in workplace initiatives
• Improvement efforts
• Provision of activity / services
• Utilisation of activity/services
Employer:
• Policies
• Regulations
Secondary Outcomes (explanation)
A) Recruitment evaluation
B) Issues we propose to explore (derived from a logic model):
1. Were the fiscal incentive, Thrive at Work Commitment and network meetings implemented with a high level of fidelity?
2. How effective have communications about the intervention been (from West Midlands Combined Authority to employer and from employer to employee)?
4. What health and wellbeing offer was made by the employer before and since their participation in the trial?
5. Have employees intentions or behaviour changed towards the health and wellbeing offer?
6. To what extent (if at all) and how have the initial grant (and prospect of further payment) triggered commitment and activity on the part of the employer?
7. To what extent and how has the Thrive at Work Commitment and toolkit been effective in facilitating behaviour change among employers and employees?
8. How, if at all, have the network meetings helped employers enhance their health and wellbeing offer?

Experimental Design

Experimental Design
Randomised, staggered, parallel, cluster design
Experimental Design Details
Randomised, staggered, parallel, cluster design with two intervention and two control groups, one of which omits baseline and mid-point observations
Randomization Method
Constrained randomisation done in office by a computer
Randomization Unit
Cluster of small-medium enterprises
Was the treatment clustered?
Yes

Experiment Characteristics

Sample size: planned number of clusters
132
Sample size: planned number of observations
132 small-medium enterprises with a total of 1320 employees and 132 employers
Sample size (or number of clusters) by treatment arms
33 clusters per arm for the 4 arm study
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
Power calculations are conducted on the basis of observing ‘statistically significant’ differences between study arms, however ‘statistical significance’ is not a statistic used in Bayesian analyses, nor we argue is it the appropriate statistic for determining the effectiveness of the intervention. Instead, we conduct an ‘assurance’ analysis, to determine what the probability of estimating an effect size to within a given degree of certainty is once we have observed the data and updated the model. This has a more natural interpretation and allows us to take into account our prior uncertainty over the effect size. Given that the assurance calculations are mathematically intractable, we simulate trial data to conduct our evaluation of the design. We conduct a simulation with no individual or cluster-level covariates and a trial start staggered over three time periods. The West Midlands Combined Authority will recruit 132 workplaces to be randomised equally between the different arms of the trial (33 per trial arm). Based on the demographics of SMEs in the West Midlands, we anticipate a mean size of 35 employees per small-medium enterprise, so approximately 4,620 employees would be eligible to be sampled. A minimum of 10 employees per small-medium enterprise (at a range of different levels) will be randomly selected from each small-medium enterprise for interview, employees will be resampled for each subsequent assessment. For the purposes of the design evaluation and generation of simulation data we consider informative priors, akin to a prior belief about effect size in Frequentist power calculations, as distinct to the analysis priors for the analysis stage and model estimation. The treatment effects for the 50% and 100% incentive arms are considered likely to fall in the ranges (in terms of percentage point increases) of [0, 20] and [0, 30] for the simulation, which translated into approximate odds ratio intervals of [1.00, 2.33] and [1.00, 3.50] respectively. We therefore conduct our simulation with distributions on the log scale of N(0.44, 0.222) and N(0.83, 0.322). The baseline was assumed to be between 0% and 50% and we used a simulation distribution of N(-1.1,0.52). We also assumed the ICC would lie between 0.02 and 0.05 uniformly. Finally, we simulated the measurement effect to be, as an odds ratio, between 0.9 and 1.1, thus using a N(0,0.12) distribution. Based on the design of the trial, we determined the probability that there would be at least a 95% posterior probability that each treatment effect (as an odds ratio) would be >1 and that the absolute difference between the treatment effects would be >0. The respective probabilities for the 50% and 100% treatment conditions were 85% and 94%, and the probability for the difference was >99%.
IRB

Institutional Review Boards (IRBs)

IRB Name
Biomedical & Scientific Research Ethics Committee (BSREC) of Faculties of Medicine and Science
IRB Approval Date
2018-09-13
IRB Approval Number
REGO-2018-2230

Post-Trial

Post Trial Information

Study Withdrawal

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Intervention

Is the intervention completed?
No
Data Collection Complete
Data Publication

Data Publication

Is public data available?
No

Program Files

Program Files
Reports, Papers & Other Materials

Relevant Paper(s)

Reports & Other Materials