Use of Personalized Recommendations, Through Genetic and Lifestyle Data, to Improve Healthcare Staff Wellbeing

Overview

With the NHS under increasing pressure and strain, the health and wellbeing of staff is an important area to prioritize, to help reduce staff stress levels and increase retention of staff. This study will look to explore how efficacious personalised insights and recommendations are, based on genetic and lifestyle information, at improving the health and wellbeing of NHS employees. It will also explore how sustainable these recommendations are for long-term change. Recruitment of NHS staff as participants will take place across multiple NHS trusts including Bradford Teaching Hospital NHS Trust and Sandwell and West Birmingham NHS Trust. Following consent to partake in the trial, participants will be asked to complete a pre-trial questionnaire which will explore health and wellbeing interests and motivations, perceptions of genetic testing, and a baseline measure of mental and physical wellbeing using a standardised and validated questionnaire (5-item World Health Organisation Well-being Index (WHO-5)). This, and all further questionnaires, will be completed online. Participants will undertake a DNA test provided by FitnessGenes, free of charge. This test will require participants to provide a saliva sample via a spit test. This sample will then be analysed at an ISO-accredited laboratory and results provided back to the participant within 2-3 weeks. While awaiting the results, participants will have access to lifestyle traits calculated using questionnaire data collected when creating a FitnessGenes account. Once their genetic data is added to a participant's FitnessGenes accounts, they will be asked to spend two weeks exploring this information. A questionnaire will then be completed to reassess participant's wellbeing measures and any changes in their perceptions of DNA testing. At this stage, some semi-structured interviews may be conducted, to those who consent to this, to gain further insight. A 3-month follow up will be completed to assess whether the platform has had any long-lasting impacts on participants' health and wellbeing.

This will be a 6-week long study to explore the impact of FitnessGenes' platform, with a follow-up after 3 months. NHS staff from multiple NHS trusts will be recruited to partake in the study. Following consent to partake in the trial, participants will be asked to complete a pre-trial questionnaire which will explore health and wellbeing interests and motivations, alongside taking a baseline measure of mental and physical wellbeing using the 5-item World Health Organization Well-being Index (WHO-5) which has been clinically validated. This, and all further questionnaires, will be completed online. Participants will undertake a DNA test provided by FitnessGenes, free of charge. This test will require participants to provide a saliva sample via a spit test. This sample will then be analysed at an ISO-accredited laboratory and results provided back to the participant within 2-3 weeks. Test result data is stored in an encrypted format and saliva samples are anonymized using unique barcodes printed on the collection tubes, which do not contain any Personal Information. User identity data (email, name, address, contact info etc.) is kept in a separate database to user personal data (demographic, biometric, lifestyle, genetic etc.). This means all personal data is already kept in an anonymised form. Once their genetic data is added to a participant's FitnessGenes account, they will be asked to spend a week exploring this upgraded information. A feedback questionnaire will be completed, 3 weeks after they have received their results, to assess participant's experiences of the platform and their results. At this stage, some semi-structured interviews may be conducted, to those who consent to this, to gain further insight. A 3-month follow up, after the baseline measures were taken, will be completed to assess whether the platform has had any long-lasting impacts on participants' health and wellbeing. This follow up will be completed via a short online questionnaire. The primary aim of the study is to assess changes in subjects' well-being, as evaluated by the 5-item World Health Organisation Well-being Index (WHO-5). The investigators will adopt a repeated measures analysis, collecting raw WHO-5 scores from the same subjects at three discrete time points: baseline (i.e. before genetic analysis), 3 weeks after receiving genetic results and at 3 months after baseline. The investigators will also assess the internal consistency of the WHO-5 by performing a Cronbach's alpha test at the three time points. To assess changes in well-being, raw WHO-5 scores (ranging from 0 to 25) will be multiplied by 4 and transformed into final scores of 0 - 100 for each subject. Descriptive statistics (mean and standard deviation) will be calculated for the 5 individual items of the WHO-5 and the final WHO-5 scores (0-100). The main dependent variable to be evaluated will be the final WHO-5 Score (ranging from 0-100). The investigators will use repeated measures analysis to assess changes in mean final WHO-5 score across the three different time points. Briefly, the investigators will assess the distributions of the WHO-5 scores and perform basic tests of normality (including Q-Q plot and performing a Shapiro-Wilkes test) and sphericity/equal variances (Mauchly's test). Depending on the distributions of this data, the investigators will select the appropriate statistical test to assess changes in mean final WHO-5 score. Assuming normality and sphericity of data and no outliers, the investigators will perform a repeated measures (within-subjects) ANOVA to assess whether the mean final WHO-5 score is statistically significantly different across the three time points. Post-hoc tests will include paired T-tests to make pairwise comparisons in mean final WHO-5 score between the time points, with P-values adjusted using the Bonferroni multiple testing correction method. Depending on the demographic make-up of the subjects, the investigators may include other moderator variables (e.g. gender) to assess for interactions with time point. If the assumptions behind these parametric tests are violated, a non-parametric alternative (e.g. Friedmans test) will be used to assess changes in mean WHO-5 score. All statistical analysis will be performed using R. Repeated measures analysis will be used to evaluate the secondary outcomes related to user experience and perceptions of genetic testing.