Patrick Olivier

Bing Zhai, Stuart Nicholson, Kyle Montague et al.

Sleep deprivation is a public health issue. Awareness of sleep deprivation has not been widely investigated in workplace-based wellness programmes. This study adopted a three-stage design process with nine participants from a local manufacturing company to help raise awareness of sleep deprivation. The common causes of sleep deprivation were identified through the deployment of technology probes and participant interviews. The study contributes smart Internet of things(IoT) workplace-based design concepts for activity tracking that may aid sleep and explore ways of sharing personal sleep data within the workplace. Through the use of co-design methods, the study also highlights prominent privacy concerns relating to use of personal data from different stakeholders' perspectives, including the unexpected use of sleep data by organisations for fatigue risk management and the evaluation of employee performance. The Actigrahy and sleep diary data can be accessed online through https://github.com/famousgrouse/pervasivehealth/

Dinislam Abdulgalimov, Reuben Kirkham, James Nicholson et al.

Employee voice and workplace democracy have a positive impact on employee wellbeing and the performance of organizations. In this paper, we conducted interviews with employees to identify facilitators and inhibitors for the voice within the workplace and a corresponding set of appropriate qualities: Civility, Validity, Safety and Egalitarianism. We then operationalised these qualities as a set of design goals - Assured Anonymity, Constructive Moderation, Adequate Slowness and Controlled Access - in the design and development of a secure anonymous employee voice system. Our novel take on the Enterprise Social Network aims to foster good citizenship whilst also promoting frank yet constructive discussion. We reflect on a two-week deployment of our system, the diverse range of candid discussions that emerged around important workplace issues and the potential for change within the host organization. We conclude by reflecting on the ways in which our approach shaped the discourse and supported the creation of a trusted environment for employee voice.

Timur Osadchiy, Ivan Poliakov, Patrick Olivier et al.

Recall assistance methods are among the key aspects that improve the accuracy of online dietary assessment surveys. These methods still mainly rely on experience of trained interviewers with nutritional background, but data driven approaches could improve cost-efficiency and scalability of automated dietary assessment. We evaluated the effectiveness of a recommender algorithm developed for an online dietary assessment system called Intake24, that automates the multiple-pass 24-hour recall method. The recommender builds a model of eating behavior from recalls collected in past surveys. Based on foods they have already selected, the model is used to remind respondents of associated foods that they may have omitted to report. The performance of prompts generated by the model was compared to that of prompts hand-coded by nutritionists in two dietary studies. The results of our studies demonstrate that the recommender system is able to capture a higher number of foods omitted by respondents of online dietary surveys than prompts hand-coded by nutritionists. However, the considerably lower precision of generated prompts indicates an opportunity for further improvement of the system.