Statistical analysis
pre-lockdown
Descriptive statistics were used to summarise participant demographic details (age, gender, job title, employment type, length of time working at the contact centre, any health problems reported) for all participants and also stratified by contact centre. Categorical variables were summarised using number (%) and continuous variables using mean, median, standard deviation, minimum, maximum, and interquartile range. In addition, descriptive statistics of continuous participant outcomes were also produced and split by data collection time point. For the binary outcome of “meeting physical activity guidelines” according to the Scot-PASQ, frequencies and percentages were calculated.Box and dot plots were used to present graphical representations of the data using ggplot 2 in R software [The major changes to the study design resulting from the impact of the COVID-19 pandemic meant that we could not fully adhere to the statistical analysis plan [Three of the centres recruited during the pre-lockdown period provided information on rates of staff turnover between the pre- and post-lockdown periods (over a 10–12 month period). Proportions of participants leaving the company or moving jobs within the same company were computed with exact 95% confidence intervals. Similarly, for the post-lockdown period, the number of participants involved in the post-lockdown data collection who left the company or moved jobs over the 3 months follow-up period were calculated.Most statistical analyses were performed using SPSS software version 24 [