Trends, variations and prediction of staff sickness absence rates among NHS ambulance services in England: a time series study

Objectives Our aim was to measure ambulance sickness absence rates over time, comparing ambulance services and investigate the predictability of rates for future forecasting.

Setting All English ambulance services, UK.

Design We used a time series design analysing published monthly National Health Service staff sickness rates by gender, age, job role and region, comparing the 10 regional ambulance services in England between 2009 and 2018. Autoregressive Integrated Moving Average (ARIMA) and Seasonal ARIMA (SARIMA) models were developed using Stata V.14.2 and trends displayed graphically.

Participants Individual participant data were not available. The total number of full-time equivalent (FTE) days lost due to sickness absence (including non-working days) and total number of days available for work for each staff group and level were available. In line with The Data Protection Act, if the organisation had less than 330 FTE days available during the study period it was censored for analysis.

Results A total of 1117 months of sickness absence rate data for all English ambulance services were included in the analysis. We found considerable variation in annual sickness absence rates between ambulance services and over the 10-year duration of the study in England. Across all the ambulance services the median days available were 1 336 888 with IQR of 548 796 and 73 346 median days lost due to sickness absence, with IQR of 30 551 days. Among clinical staff sickness absence varied seasonally with peaks in winter and falls over summer. The winter increases in sickness absence were largely predictable using seasonally adjusted (SARIMA) time series models.

Conclusion Sickness rates for clinical staff were found to vary considerably over time and by ambulance trust. Statistical models had sufficient predictive capability to help forecast sickness absence, enabling services to plan human resources more effectively at times of increased demand.

University of Lincoln, College of Social Science Research

Zahid B Asghar, University of Lincoln, School of Health and Social Care

Paresh Wankhade, Edge Hill University, Business School

Fiona Bell, Yorkshire Ambulance Service NHS Trust

Kristy Sanderson, University of East Anglia, School of Health Science

Kelly Hird, Yorkshire Ambulance Service NHS Trust

Viet-Hai Phung, University of Lincoln, School of Health and Social Care

Aloysius Niroshan Siriwardena, University of Lincoln, School of Health and Social Care

Having options alters the attractiveness of familiar versus novel faces: Sex differences and similarities

Although online dating allows us to access a wider pool of romantic partners, choice could induce an ‘assessment mindset’, orienting us toward ‘optimal’ or alternative partners and undermining our willingness to commit or remain committed to someone. Contextual changes in judgements of facial attractiveness can shed light on this issue. We directly test this proposal by activating a context where participants imagine choosing between items in picture slideshows (dates or equally attractive desserts), observing its effects on attraction to i) faces on second viewing and ii) novel versus familiar identities. Single women, relative to single men, were less attracted to the same face on second viewing (Experiments 2 and 4), with this sex difference only observed after imagining not ‘matching’ with any romantic dates in our slideshow (i.e., low choice, Experiment 4). No equivalent sex differences were observed in the absence of experimental choice slideshows (Experiment 3), and these effects (Experiment 2) were not moderated by slideshow content (romantic dates or desserts) or choice set size (five versus fifteen items). Following slideshows, novel faces were more attractive than familiar faces (Experiment 1), with this effect stronger in men than in women (Experiment 2), and stronger across both sexes after imagining ‘matching’ with desired romantic dates (i.e., high choice, Experiment 4). Our findings suggest that familiarity does not necessarily ‘breed liking’ when we have the autonomy to choose, revealing lower-order socio-cognitive mechanisms that could underpin online interactions, such as when browsing profiles and deciding how to allocate effort to different users.

University of Lincoln, College of Social Science Research

Jordan R Sculley, Abertay University, School of Applied Sciences

Kay Ritchie, University of Lincoln, School of Psychology