Menu Back to Poster-Presentations-Details

P116: Testing a Nutritional Intervention on Sleep Quality Outcomes: Insights Into Design and Operational Challenges

Poster Presenter

Mun Teng Low

Clinical Project Manager
Nestle
Singapore

Objectives

Describe the design and execution challenges of a study assessing the impact of a nutritional intervention on sleep quality.

Method

This is a randomized double-blind cross-over trial design, with 2 weeks per intervention (control and active). The trial was completed in Dec22 with total 42 completers. Key trial assessments includes actigraphy (research and commercial sensors), continuous glucose monitoring, ePRO, cognitive tasks

Results

Performing a study to improve sleep quality requires the inclusion of “poor sleepers”. Recruitment of those subjects is complex and challenging since perceived sleep and objective sleep doesn’t always match. 300 subjects were pre-screened, only 43 fulfilled the sleep quality criteria and successfully randomized. To aid recruitment the team implemented strategies in waves from May22, which includes posting of digital ads, videos, posters on Google and social media. The recruitment completed in Aug22. The decentralized approach to assess subjects’ sleep quality at their home (not in lab) has brought trial execution closer to reality while bringing challenges. The trial subjects are required to follow a customized diet plan. Initial plan was to enroll subjects from university dormitories to ease central meal supply. However, as the recruitment expanded to nation-wide, it was hard for team to secure hot meal provider who can commit to small orders, strict preparation, and delivery schedule. The recruitment was conducted in batches to meet the minimum order requirement. More recruitment time, resource, and cost (>40% increase) were spent to ensure continued supplies from provider. To ensure subject centricity, digitalization was enabled to allow remote and continuous data collection and management. Though onsite visits were reduced, but more resources were spent to monitor the quality and clean the collected data. More discrepancies were noticed for complex assessments like cognitive tasks which were usually completed in the lab. Dedicated resource was assigned to monitor the compliance status and send daily reminders to subjects. With all effort, the study was completed earlier with low dropout (<5%) and sufficient completers with high compliance rate. The data collected from research and commercial grade sensors were compared, and it was interesting to see that the commercial sensors are complementary and non-inferior with the research sensors.

Conclusion

Conduct of clinical trial in real life is subject to more variability and uncontrolled environment, which could challenge the data quality and consistency. This is clearly observed for our sleep trial as the quality of sleep is greatly impacted by environment (light, temperature etc.), and sleep habits varies among individuals. While exerting full control over the subjects in real-life over 3 months is not possible, it is important for us to adopt the risk management mindset and assess what should and can be controlled. Keep up with the mitigations put in place for risks that are beyond control, and yet be responsive and adaptive to unforeseen challenges. The lessons learnt from this study allow us to rethink what could have been done differently to eliminate or reduce the impact of these operational challenges. For instance, if the trial requires frequent measurements, complex trial assessments and customized diet, it might be worth considering having the subjects stayed in the lab and only be provided with 1 intervention. This may require double of subjects’ numbers to be enrolled, but subjects’ interest and commitment might increase if the trial duration shorten from 3 months (screening + cross over + wash out) to 3 weeks (screening + single intervention). For the customized meal plan, instead of providing hot meals which are subject to strict delivery and food safety guidelines, the team could work with nutritionist and supplier to batch produce the frozen meals with the required nutritional composition. The use of wearables promotes conduct of decentralized trial. However, the challenge with data quality, compliance and consistency also increased with remote collection. The use of commercial sensors also provided interesting exploratory data and confidence to implement for clinical trial use. With the experience gained, new studies can be planned with the use of the commercial sensors for its better wearability compared to research sensors.