Improving the acceptability of workplace mental well-being platforms through ethical design and use

越来越多的工作场所正在将注意力转向数字化解决方案，如福祉自助技术，旨在供员工用来管理自己的福祉(Jones等人，2021年；Torous等人，2020)。这发生在混合和远程工作方式因新冠肺炎疫情而变得越来越普遍的时候。生产力和幸福感被认为是齐头并进的，这使得在工作场所分享心理健康数据成为一个高度敏感的话题。一些数字心理健康平台重塑了工作场所组织支持员工的方式，通常是通过决策者的仪表盘，这可以为领导力沟通开辟新的渠道(Truong&McLachlan，2022)。然而，随着人们越来越关注无限制的工人监控(Ajuwa，Crawford&Schultz，2017)以及“数据监控”技术导致的员工关系紧张(例如，Ball，2014)，如何设计和使用这些平台以真正实现其预期目的仍然存在问题。具有讽刺意味的是，有理由相信，不正确地推广和使用这些平台可能会对员工的心理健康产生负面影响。下面的博士论文从潜在的最终用户开始，探讨关键利益相关者对这些平台的看法，并试图了解它们可能如何影响组织内个人的实际福祉。采用定性和定量相结合的方法，这个博士主要使用来自人机界面的低保真原型方法，并结合半结构化面试。还将收集调查数据，以提高早期调查结果对各种工作环境和角色的代表性。本博士学位结束时，将为雇主和福利平台开发人员提供一套建议，以促进这些技术更好地被接受，并重点关注用户对其个人数据的控制感。

Increasingly, workplaces are shifting their attention towards digitalised solutions, such as wellbeing self-help technologies, that are intended for use by employees to manage their own wellbeing (Jones et al., 2021; Torous et al., 2020). This comes at a time when hybrid and remote working practices are becoming more common as a result of the Covid-19 pandemic. Productivity and well-being are seen to go hand in hand, making the sharing of mental well-being data in the workplace a highly sensitive topic. Some digital mental well-being platforms reinvent the way in which workplace organisations can support their employees, often through decision-maker dashboards, which can open up new channels for leadership communication (Truong & McLachlan, 2022). However, with growing concerns of limitless worker surveillance (Ajunwa, Crawford & Schultz, 2017) and strains on employee relations as a result of 'dataveillance' techniques (e.g., Ball, 2014), questions remain as to how these platforms can be designed and used to truly fulfil their intended purpose. There is reason to believe that incorrect promotion and use of these platforms may, ironically, have negative implications for employees' mental well-being. The following PhD explores key stakeholder perspectives towards these platforms, starting with prospective end-users, and seeks to understand how they may affect the actual well-being of individuals within an organisation. Adopting a combination of qualitative and quantitative approaches, this PhD predominantly employs low-fidelity prototyping methods from HCI in combination with semi-structured interviews. Survey data will also be captured to improve the representativeness of earlier findings to a variety of work settings and roles. A set of recommendations for employers and wellbeing platform developers will be produced at the end of this PhD to foster greater acceptability of these technologies, with a strong focus on users' feelings of control over their personal data.