With the rapid growth of workplace wellbeing interventions, determining their effectiveness is not only good science but also good practice. Wellbeing research continues to evolve; thus, it is likely that there will be advances in measurement. With the growing list of wellbeing measures (e.g., see [
1,
2]), identifying and selecting the most appropriate instruments for effectiveness evaluations in the workplace have never been so important. Whilst a wide variety of wellbeing measures exist in the literature, it is not always clear what they are measuring, nor which measures best meet study objectives. For example, a recent systematic review of longitudinal studies that investigated workers’ wellbeing constructs found the majority of the 40 identified studies focussed on illbeing, or the “negative side” of employee wellbeing (e.g., burnout [
3]). This systematic review protocol, and subsequent systematic review, will provide a unique opportunity to provide future rigorous updates as the work wellbeing science grows. The study will improve clarity for researchers and clinicians in the appropriate instrument selection in the measurement of workers’ (or employees’) wellbeing.
The construct of workers’ wellbeing is described as rich and multifaceted, with key features scaffolding individual, team and organisational levels, inclusive of factors that transcend work (the role), workers (the individuals and teams), and workplaces (organisations) [
4]. The factors associated with wellbeing differ for different occupational groups [
5]. For professionals, the greatest amount of variance in job satisfaction is due to the five factors of work-life balance, satisfaction with education, being engaged, and experiencing meaning, purpose and autonomy [
5]. For labourers, these factors were work-life balance, being absorbed, experiencing meaning and purpose, feeling respected, and having self-esteem [
5]. For nurses, these factors included workplace characteristics, the ability to cope with changing demands and feedback loops [
6]. The largely Western theoretical models and definitions of work wellbeing are also varied [
7‐
9]. Key factors are thought to include subjective wellbeing, including job satisfaction, attitudes and affect; eudiamonic wellbeing including engagement, meaning, growth, intrinsic motivation and calling; and social wellbeing such as quality connections and satisfaction with co-workers [
10]. Laine and Rinne [
11] add to these factors in their ‘discursive’ definition which encompasses healthy living/working, work/family roles, leadership/management styles, human relations/social factors, work-related factors, working life uncertainties, and personality/individual factors. Work-related quality of life (WRQoL) adds further factors, including general wellbeing, home-work interface, job and career satisfaction, control at work, working conditions, and stress at work [
12]. Given the breadth of these factors, and the disparity in theoretical models and definitions of what workers’ wellbeing is, selecting instruments for the measurement of workers’ wellbeing is challenging. The most appropriate instrument to measure the construct may require a selection of unidimensional (sub) scales, similar to the measurement of wellbeing [
13] and WRQoL [
12]. It is expected that two different instruments that are intended to measure the same construct of “workers’ wellbeing” should correlate. Thus, we will test the a priori hypothesis: instruments intending to assess the same construct of “workers’ wellbeing” will be strongly positively correlated. For this review, the aim is to evaluate the measurement properties of instruments that measure the broader construct of workers’ wellbeing (e.g., the Workplace Well-being Index [
14,
15]). Any identifiable sub-scales within the instruments will be individually reported. Specifically, the objectives are to (1) systematically identify studies that measure workers’ wellbeing, (2) critically appraise the methodological quality of the studies, (3) critically appraise the workers’ wellbeing instrument properties and, (4) recommend the most appropriate instruments to measure workers’ wellbeing.