Flourishing at Work - Factors effecting employee wellbeing. A project to benchmark employee wellbeing over time.
Creators: name: Salhi, Louisa
name: Facey-Campbell, Nicole
name: Mainstone-Cotton, Lily
Publisher: name: Open Science Framework
Year: 2022
Subjects: subject: Clinical Psychology
subject: Industrial and Organizational Psychology
subject: Counseling
subject: Social and Behavioral Sciences
subject: Psychology
subject: FOS: Psychology
subject: burnout
subject: discrimination
subject: employee mental health
subject: flourishing
subject: stressful life events
subject: WHO5

description: Background and rationale: Highlighted in the ‘thriving at work’ (2017) report, we know that 80% of employees have or will have concerns about their mental health in their career. This is staggeringly high, with 20% of these needing to take additional action to gain support. These figures are from resources pre-2017; since the Covid-19 pandemic started in March 2020 we know that mental health needs in general have been exacerbated by the pandemic itself, associated lockdowns, and rapid changes to workplaces (Pierce et al., 2020). This decline in general mental health will inevitably have negative consequences on employees, and their employers. Importantly on a company level, employees experiencing mental health problems are seen to take a higher level of sickness absences. Sickness absence due to mental health issues has risen by 5% in the 10 years prior to the ‘thriving at work’ (2017) report, with employees with mental health issues being three times more likely to take long-term sickness leave. There are widespread negative effects of this on the company with absenteeism and presenteeism adding strain to other employees, affecting workplace culture and morale, there are economic consequences and increased staff turnover. Prior literature shows that for employees taking sickness absence due to mental health needs, workplace counselling reduces this type of sickness absences by 20% - 60% over a one-year period (Rost et al., 2004, Van der Klink et al., 2003, Blaze- Temple and Howat 1997). There are a wide array of wellbeing measures and they map onto different constructs. Broadly speaking well-being is related to ‘the quality and state of a person's life’ however there is no consensus on outcome measures for measuring wellbeing (Linton, 2016). Therefore, providing a battery of wellbeing measures will enable a holistic view of employee wellbeing, provide a method of benchmarking to track changes over time. Project Aims: This project aims to benchmark employee wellbeing data points - utilising standardised outcome measures of mental health and wellbeing. Additionally the collection of demographic data will enable the segmentation of employees by gender, ethnicity and other critical demographic. The demographic characteristics provide insight into if certain individuals are at higher risk or have higher mental health needs. We will also collect data on what mental health support employees currently have access to, what they would like access too and what they have used previously. Finally we will collect some data points on workplace mental health culture, as well as personal contributors to wellbeing, such as physical illness, discrimination and experiencing Adverse Childhood experience (ACEs) and stressful life events. The overarching aim is to provide a battery of surveys that can benchmark employee wellbeing over time. In the first year we will be using a snowballing and opportunity sampling technique, with a focus on exploring the effects of discrimination of employee wellbeing. The overarching project explores key factors affecting employee wellbeing, these are broken into separate research questions: How do experiences of discrimination affect wellbeing in employees? How has workplace changes over the COVID-19 pandemic impacted the mental health of employees? Workplace culture and mental health effects (support, access and preferences). Does this change based on sector and seniority level? How do personal factors, such as stressful life events, affect the wellbeing of employees? Research Hypothesis How do experiences of discrimination affect wellbeing in employees? The study asks the question: How do experiences of discrimination affect wellbeing in employees? H1: We expect that people who have experienced discrimination will have significantly lower wellbeing than those who have not experienced discrimination; discriminated groups will have significantly higher scores on a) GAD-7, b) Workplace Burnout and c) WSAS, and significantly lower scores on d) WHO-5 and e) Flourishing. H2: We predict that there will be a significant relationship between seeking mental health support following experiences of discrimination and scores on wellbeing measures a) GAD-7, b) Copenhagen Workplace Burnout Inventory, c) WHO-5 and d) Flourishing. H3: We predict that workplace outcomes (presenteeism, absenteeism, intention to stay at work, work engagement, WSAS) will differ significantly for discriminated vs non-discriminated groups. H4: Types of mental health support accessed and found useful may differ depending on if individuals have experienced discriminated or not. H5: There may be differences in the most important features of support for discriminated versus non-discriminated groups. Covid-19 and the changes to workplaces How has workplace changes over the COVID-19 pandemic impacted the mental health of employees? H1: We predict that if their workplace pattern suits their preferences and workplace covid-19 support scores are high (positive experience of workplaces changes during covid) there will be a positive relationship with mental health outcomes in 2022 (when we control for recent stressful life events). Mental health outcomes are personal burnout, workplace burnout, GAD-7, WHO-5, and flourishing score. H2: We predict that if their workplace pattern suits their preferences and workplace covid-19 support scores are high (positive experience of workplaces changes during covid) there will be a positive relationship with workplace outcomes in 2022 (when we control for recent stressful life events). Workplace outcomes are lower presenteeism, lower absenteeism, work engagement and an intention to stay at their current workplace. This relationship is expected to be mediated by access to mental health support, and workplace mental health culture which will be exploitively investigated depending on the planned analysis findings from the hypothesis above. Workplace culture and mental health effects (support, access and preferences). How does support and workplace culture mediate mental health outcomes? Does this change based on sector and seniority level? H1: We expect (Workplace mental health culture score, work burnout, personal burnout, WHO-5, Flourishing and GAD-7) to predict workplace outcomes (presenteeism, absenteeism, intention to stay at work, engagement, WSAS). H2: We will further explore if the relationship is affected by whether or not they have accessed mental health support. H3: We tentatively expect that workplace setting factors, such as income/ workplace sector /seniority will affect scores on mental health measures (WHO-5, Flourishing, Personal Burnout, Workplace Burnout, GAD-7). H4: How does workplace mental health culture score, workplace preferences and whether or not their preferences were consulted, the impact of work on mental health, and the number of negative contributors to mental health selected, predict scores of Workplace Engagement, WSAS, Work Burnout, WHO-5, Flourishing and GAD-7? How is this influenced by the types of support at work? How do personal factors, such as stressful life events, affect the wellbeing of employees? -&gt; Stressful Life Events We are interested in looking at the influence of having experienced stressful life events, number of stressful life events, of having experienced stressful life events under 18 and number of stressful life events under 18, on workplace outcomes such as workplace burnout, WHO-5 scores, Flourishing scores and GAD-7 scores. Also, how the relationship is influenced by support following the events. H1: We expect that experiencing recent stressful life events (in the last year) will have a significant effect on wellbeing, workplace engagement and work burnout. We also expect that the number of stressful life events experienced in the past year will have a significant effect on wellbeing and work outcomes. H2: We expect that having stressful life events under 18 will significantly affect workplace burnout scores. We also expect that the number of stressful life events under 18 will have a significant effect on work burnout. H3: We expect that salary, employment status and workplace engagement will also be significantly affected by experiencing stressful life events under 18 and the number of stressful life events under 18 experienced. How do the mental health measures (WHO-5, Flourishing, Personal Burnout, Workplace Burnout, GAD-7) correlate with each other? We predict: H1: A positive correlation between scores on Work Engagement and scores on Flourishing A positive correlation between scores on WHO-5 Index and Work Engagement H2: A negative correlation between Personal and Workplace Burnout and Work Engagement H3: A negative correlation between scores of GAD-7 and Work Engagement H4: A positive correlation (if any) between Flourishing and WHO-5 Index H5: A negative correlation between Flourishing and Work and Personal Burnout H6: A negative correlation between Flourishing and Anxiety H7: A negative correlation between scores of WHO-5 Index and Burnout H8: A negative correlation between scores on WHO-5 Index and GAD-7. H9: A negative correlation between scores on workplace engagement and wsas impairment scale. H10: A negative correlation between who-5 index and wsas H11: A negative correlation between flourish and wsas H12: A positive correlation between Personal burnout and wsas H13: A positive correlation between Workplace burnout and wsas Method Design This pre-registration describes a series of projects, all of which fall under the same umbrella of employee wellbeing. We initially will be examining employee wellbeing and our key hypothesis across one fixed time period. After this we plan to continue data collection and re-visit the data at later intervals, primarily annually thereafter. The design of this study is a cross-sectional survey. The reason this design was chosen was because it is important to the study to have a diverse sample, with people from a variety of age, gender and ethnic groups, sexual orientations, and abilities, to understand better the experiences of employees across the UK and their mental wellbeing. After the first cross-sectional survey study we aim to continue data collection to enable year-on-year comparisons. Data analysis will be conducted at intervals (by-annually or annually), lending itself to a cross-section analysis. Collecting data in this way will enable a higher response rate and utilise the snowballing method, collecting data from more organisations than if we conducted a cross-sectional survey at one fixed time period. This will be important to enable enough data to benchmark UK organisations, for example, by sector. Something that one year of data may not enable. Participants We will use opportunity sampling through participatory networks, organisations and companies. Respondents within those organisations will distribute the survey further to more people and more participants will take part through snowballing. The rest of the participants will be sourced by QuestionPro Panel and paid to take part in the survey. Inclusion Criteria Participants need to fit the criteria of: 1) being over the age of 18 2) a UK employee 3) fluent in English Exclusion Criteria To exclude participants, any one of the following criteria would be sufficient: Failed attention check question Not a UK employee Not over the age of 18 Planned Sample Size (Power Analysis) Correlational Analysis An a priori power analysis was conducted using G-POWER (Faul et al., 2007) to determine the sample size needed to conduct a correlational analysis. The power analysis for a two-tailed correlational analysis determined a sufficient sample size of 84, using an alpha of 0.05, power of 0.8 and medium effect size (r=0.3). The power analysis for a two-tailed correlational analysis determined a sufficient sample size of 782, using an alpha of 0.05, power of 0.8 and small effect size (r=0.1). One-way ANOVA An a priori power analysis was conducted using G-POWER (Faul et al., 2007) to determine the sample size needed to conduct a one-way ANOVA. The sample size needed to conduct a one-way ANOVA is 128, with two groups, an alpha of 0.05, power of 0.8 and a medium effect size (F=0.25). The sample size needed to conduct a one-way ANOVA is 788, with two groups, an alpha of 0.05, power of 0.8 and a small effect size (F=0.1). 2-way ANOVA An a priori power analysis was conducted using G-POWER (Faul et al., 2007) to determine the sample size needed to conduct a two-way ANOVA. The sample size needed to conduct a two-way ANOVA is 128, with four groups, an alpha of 0.05, power of 0.8 and a medium effect size (F=0.25). The sample size needed to conduct a two-way ANOVA is 787, with four groups , an alpha of 0.05, power of 0.8 and a small effect size (F=0.1). Linear regression An a priori power analysis was conducted using G-POWER (Faul et al., 2007) to determine the sample size needed to conduct a linear regression. The sample size needed to conduct a linear regression is 98, with six predictors, an alpha of 0.05, power of 0.8 and a medium effect size (F squared =0.15). The sample size needed to conduct a linear regression is 688, with six predictors, an alpha of 0.05, power of 0.8 and a medium effect size (F squared =0.02). Data Extractions As this project will be ongoing and utilises snowballing opportunities sampling different data extracts will occur once we have enough sample size for the relevant described research questions. We will aim to attain a sample size to detect small effect sizes, however a pragmatic approach is needed when collecting data in this way and we will aim to a sample size between the small and medium effect sizes. If required sensitivity analysis will be conducted after the analysis is done. Materials Participants will be given a link to a survey to complete online through QuestionPro. The survey includes questions we created, demographic questions and some standardised scales . The standardised scales used measure concepts such as burnout, overall mental wellbeing, anxiety, flourishing, impairment, work engagement and workplace and personal burnout. Demographics We will ask the participants a variety of demographic question such as age, gender, ethnicity and sexual orientation. We will also ask questions specifically about their work, such as their employee status e.g. working full-time, seniority level e.g. staff, the sector they work for e.g. Accounting, the number of employees at the company they work for, e.g. 1 to 50, and their annual income. Certain contracts have specific questions which were added specifically for them i.e. which school do you work for? and what type of role do you work in?. Mental health standardised scales Impairment. The scale used to measure impairment will be the Work and Social Adjustment Scale (WSAS). The WSAS scale asks how a problem affects their ability to work, home management, social leisure activities, private leisure activities and close relationships. The degree of impairment is rated on a 9-point Likert scale from not at all to very severely (Mundt et al., 2002). Flourishing. The scale we will use to measure flourishing is from (Diener et al., 2010). It includes 8 statements rated on a Likert scale from 1-7, strongly disagree to strongly agree. Scoring of the scale involves adding up the score for each statement. Scores range from 8 to 56, 56 represents a person with many psychological resources and strengths. Personal and Workplace Burnout. We will use the Copenhagen Burnout Inventory, specifically the personal and workplace burnout scales since not all the employees assessed in this survey will necessarily work with clients (Kristensen et al., 2005). The personal burnout scale is made up of 6 items and the workplace burnout scale is made up of 7 items. Each item is rated from 0 – 100, 0 – never/almost never, 25- seldom, 50 –sometimes, 75 – often, 100 – always. The total score is calculated by adding each rating together and then calculating a mean. Respondents with a score over 50 are considered to have burnout, specifically scores between 50-74 are considered ‘moderate’ , scores of 74-99 are considered high and a score of 100 is considered severe burnout (British Orthapedic Association, 2021; Creedy et al., 2017) Anxiety. We will use the Generalised Anxiety Disorder (GAD) assessment to measure anxiety (Spitzer et al., 2006). The GAD-7 has 7 items. The scale is time bound; respondents are asked to respond by considering their feelings “over the last two weeks”. Respondents rate each item as: Not at all (0), Several days (1), More than half the days (2), Nearly every day (3). The total score is calculated by adding all the ratings. Total scores of 5 indicate mild anxiety, total scores of 10 indicate moderate anxiety and total scores of 15 indicate severe anxiety. Mental Wellbeing. We will use the World Health Organisation Five Wellbeing Index (WHO-5) to measure current mental wellbeing (WHO, 1998). It has a timeframe of the “last two weeks” like the GAD-7. Respondents rate statements from 0 to 5. 0 = at no time, 1 = some of the time, 2 = less than half of the time, 3 = more than half of the time, 4 = most of the time, 5 = all the time. Scores are calculated by adding up the ratings and multiplying by 4 to give a score ranging from 0 – worst quality of life, to 100 representing the best quality of life. Personal Factors Discrimination. We measure subjective perception of discrimination. We first ask participants if they have ever experienced discrimination based on a protected characteristic. Then we ask agreement/disagreement with several statements about discrimination such as “I have experienced discrimination in workplace setting.” All statements were rated from strongly disagree (0) to strongly agree (5). Overall “Discrimination score” was recorded. We finally ask them if they sought mental health support after any of their experiences of discrimination. Physical health We asked questions about employee physical health such as “Do you have a long-term physical illness or disability that has lasted longer than 12 months?” The response options were yes, no or prefer not to say. Stressful Life Events. We ask participants about their experiences of stressful life events. We first ask them if they have experienced any stressful life events and give them examples “For example, suffering from a serious illness or injury, being a victim of abuse, death of close family members or friends, financial crises.” If they respond “yes” to this, participants are then asked “How many stressful life events have you experienced” then if they have experienced any of the events in the past year, and if they have experienced any of the events under 18, if they say yes to experiencing stressful life events under 18, they are asked how many stressful life events they experienced under the age of 18. The final stressful life event question asks if they sought mental health support following any of the events. Financial stress. Participants are asked “Are you under pressure or stressed about your financial situation? Workplace mental health culture questions Work engagement. The scale we used to measure work engagement on the Ultra Short Utrecht Work Engagement 3-item Scale (UWES-3). The UWES-3 scale includes 3 items, each testing a different dimension of work engagement – vigour, dedication, and absorption. The 3-item version was used for its shorter test time but the internal consistency is still similar to that of the longer UWES-9 scale (Schaufeli et al., 2019). Participants rated items on a 5-point Likert scale from 1 = not at all like me to 5 = very much like me, other studies have also used this rating for the UWES scales (Eskreis-Winkler et al., 2014). The total score for this scale is out of 18. Absenteeism We are particularly interested in finding out the number of days taken off in relation to mental health, we will ask participants “How many days have you taken off due to mental health in the past year?” Presenteeism We will ask participants “when you are unwell, how often do you work? For example, working with a cold/flu, a migraine, fatigue or a stomach bug”, participants can respond with options from “never” to “always”. Then we will ask “since the covid-19 pandemic started, do you think you have worked more often whilst unwell?” How does their workplace affect their wellbeing? We will ask participants “How does your work affect your mental health/wellbeing?”. Participants can respond with “in a positive way”, “neither positively/negatively” or “in a negative way”. Those who say “in a negative way”, are shown the question, “What aspects of your workplace negatively affect your wellbeing?” and are given a list of options such as “long working hours or lack of breaks” to select from. Mental health culture at workplace. We have a matrix of questions about mental health culture in their workplace, participants will be asked to rate statements such as “I would approach someone at work for support if I was struggling with mental health” from agree to disagree. Mental health support access through work. We will show participants a list of possible mental health services such as “anonymous digital mental health support e.g. Qwell/Kooth”, participants are asked to select the mental health services they believe their company provides, then which of them are most useful and finally which of them you have used. They are then asked “Is there something else you would like your employer to offer in terms of mental health support?” which is a free text question and “What is most important to you when it comes to accessing mental health support?” , where they can select “free access”, “anonymity” etc. Employee Retention Participants will then be asked “Do you intend to stay working at your current workplace?” and can respond with “I plan to stay for the foreseeable future” or “I plan to start looking for another job, and will leave when I find one” etc. Workplace pattern Participants will be asked “In the last month, which of the following options best describes your workplace pattern?” with answer options such as “working in the office three days or more a week”. They will then be asked “would you prefer a different workplace pattern?” , if they answer “no” to the question. They are then asked “what type of workplace pattern would you prefer?” with the same options such as “In the last month, which of the following options best describes your workplace pattern?” Covid-19 workplace questions Following the workplace pattern questions, participants will be asked “Due to the covid-19 pandemic, did your workplace pattern change? For example from office-based to home working, from fixed hours to flexible hours, from full time to part-time.” Those who say “no” to this question, are shown a matrix of questions - asking about how changes to your workplace due to Covid-19 restrictions affect wellbeing, participants rate statements such as “Did this impact your mental health?” from “A lot” to “Not at all”. After these questions, participants are asked to read statements about how they feel about their current workplace in relation to the pandemic, rated from “Not Applicable” to “Agree”. Survey feedback At the end of the survey participants are asked for their feedback on the questionnaire, “How easy was it to complete?” and “Did you feel comfortable answering the questions?” Ethics This project was submitted to the University of Kent for ethics approval on January 24th, 2022. It was approved on 2nd February 2022 . The ethics application number is: 202216437986057576. Informed consent will be collected prior to beginning the survey and those who do not give consent were not included in the analysis. At the end of the survey, participants will be debriefed in writing, they will be given scores for the standardised scales and encouraged to seek support should they need it and signposted to a list of resources to support mental wellbeing and information about experiences of discrimination. One risk we have monitored is anonymity, individual participants will not be identified from their data in this report. Information such as location, IP address, and other identifiable information will not be collected in this survey. General trends in participant data will be included in reports for employers however identifiable information will not be included. Individual categories will only be discussed if there are more than 10 participants in that category. Procedure The survey takes approximately 8-15 minutes to complete (depending on logic follow-up questions and free-text responses). Participants will be first shown an information sheet with contact information in case of any questions and then informed consent will be collected, by asking participants to agree to the statements. If the participant does not agree with the statement, then they will be shown the terminated message. Participants will be first asked demographic questions, then standardised measures, questions on discrimination, and stressful life events questions and finally, questions on workplace culture and mental health support. The last questions of the survey are employee feedback questions. At the end of the survey, the participants will be shown scores on different standardised scales and explanations of the meaning of the scores. They will then be signposted to resources and given the opportunity to contact the ethics board and the research team again. Planned Analyses Exploration into the relationship between experiencing discrimination (at work and/or home) on wellbeing. Investigations into the effect and preferences for wellbeing support. Data analysis will be conducted in R (R Core Team (2020)) and/or JAMOVI(“The Jamovi Project,” 2021). A correlation analysis will be conducted to look at the correlation between scores on the different measures of mental health (WHO-5, GAD-7, Workplace Burnout and Personal Burnout, Work Engagement, WSAS, Mental Health Culture). ANOVAs will also be carried out to look at the relationship between experiencing discrimination and scores on measures of mental health (WHO-5, GAD-7, Workplace Burnout and Personal Burnout). Correlational analysis will be conducted using the discrimination scales e.g. My experiences of discrimination negatively affected my wellbeing at the time, and scores on the mental health measures e.g. GAD-7 scores. The proportion of people who said they accessed each different type of support will be compared between the discriminated group and the non-discriminated group. The proportion of respondents who chose each type of support as useful will be compared between the discriminated group and non-discriminated group. If appropriate Chi-Squared analysis will be used. An exploratory correlational analysis of workplace culture scores, mental health culture score, workplace engagement and discrimination scales. Two-way ANOVA comparing discrimination at work versus outside of work on scores on workplace engagement, workplace burnout , WHO-5 and GAD-7. Exploration into the effects of Covid on employee wellbeing, perceptions of workplace mental health culture and employee preferences to remain or resign. A cross-sectional exploration after the UK Covid-19 lockdowns (2020-2021) have been lifted. Data analysis will be conducted in R (R Core Team (2020)) and/or JAMOVI(“The Jamovi Project,” 2021). A one-way ANOVA will be used to analyse the differences between groups who have their workplace pattern preference is met or not, on mental health outcomes (WHO-5, GAD-7, Workplace Burnout and Personal Burnout, Work Engagement, WSAS, Mental Health Culture scores). Correlations will be conducted to examine if there is a relationship between the workplace covid impact scores on mental health outcomes (WHO-5, GAD-7, Workplace Burnout and Personal Burnout, Work Engagement, WSAS). If a relationship is seen, a linear regression analysis will be carried out to assess the impact of the workplace covid scores on mental health outcomes (WHO-5, GAD-7, Workplace Burnout and Personal Burnout, Work Engagement, WSAS) Explorative analysis, if relevant after the planned analysis findings, will look into the mediating impact of accessing support. Workplace culture and mental health effects (support, access and preferences) Data analysis will be conducted in R (R Core Team (2020)) and/or JAMOVI(“The Jamovi Project,” 2021). Correlation analysis will be used for each predictor (Workplace mental health culture score, work burnout, personal burnout, WHO-5, Flourishing and GAD-7) and outcome (presenteeism, absenteeism, intention to stay at work, engagement, WSAS). If the results are significant, then a multiple linear regression will be used. Explorative analysis, if relevant after the planned analysis findings, will look into the mediating impact of accessing support and will also be considered along with other variables. Stressful life events Data analysis will be conducted in R (R Core Team (2020)) and/or JAMOVI(“The Jamovi Project,” 2021). One-way ANOVAs will be conducted examining mental helath outcomes (WHO-5, GAD-7, Workplace Burnout and Personal Burnout, Work Engagement, WSAS, Mental Health Culture scores) for people who have experienced a stressful life event in the past year and those who have not experienced a stressful life event in the past year, will be compared. Explorative analysis will examine the effect of covid workplace impact scores on mental helath outcomes (Workplace mental health culture score, work burnout, personal burnout, WHO-5, Flourishing and GAD-7) given that this was a recent global life stressor. Correlation analysis will be conducted to look at the relationship between the number of stressful life events and scores on the mental helath outcomes (WHO-5, GAD-7, Workplace Burnout and Personal Burnout, Work Engagement, WSAS, Mental Health Culture scores). If correlations are seen, linear regression will be used to look at a predictive relationship between the number of stressful life events and scores on the different mental helath outcomes. One-way ANOVAs will be conducted examining mental health outcomes (WHO-5, GAD-7, Workplace Burnout and Personal Burnout, Work Engagement, WSAS, Mental Health Culture scores) for people who have had stressful life events and those who have not, will be compared. Correlation analysis will be conducted to look at the relationship between the number of stressful life events and scores on the different mental health measures (WHO-5, GAD-7, Workplace Burnout and Personal Burnout, Work Engagement, WSAS, Mental Health Culture scores). 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