DATA ANALYSIS AND REPORT. Melissa Lehmann Work Solutions. Abstract

Transcription

1 PO Box A Beckett Melbourne VIC 8006 t f DATA ANALYSIS AND REPORT Melissa Lehmann Work Solutions Abstract The role of work and work-life balance in contributing to stress was investigated as part of ABC TV s Stress Buster program. Visitors to the Stress Buster website were invited to participate in a survey which measured: a) respondents level of psychological distress; b) stress levels; c) the degree to which they felt work contributed to this stress; d) the value they placed on key areas of life; and e) the energy they spent in these areas. Overall, 5,692 participants completed the survey between March 16 th and April 29 th, Findings indicated that participants who had experienced high levels of stress over the last four weeks were more likely to report elevated levels of psychological distress according to the K10 symptom scale, with 24% of all respondents having a three out of four chance of meeting the criteria for depression and anxiety (Andrews & Slade, 2001). The total amount of energy exerted across key life areas (e.g., work, personal health, recreation), age and the amount of balance in one s life were also found, along with stress levels, to predict psychological distress scores. Further, work was considered to impact on stress levels, with both work and the amount of energy spent undertaking recreational activities significantly predicting such stress, whereby participants were more likely to experience stress when less time was spent on recreation. Overall, results suggest that while work does contribute to stress, it may not necessarily directly result in people experiencing psychological distress rather it is the amount of energy people get to spend in all of the important areas in their life, and, to some extent, their age, along with whether they simply experience stress that determines such distress. Introduction The meaning of the word stress varies across individuals: for some it reflects a physical state of arousal (e.g., increased heart rate, agitation, nausea), for others stress is more psychological (e.g., racing thoughts, loss of concentration) or emotional (e.g., irritability, teariness) in nature. Although there are many definitions of stress, it is generally accepted that a person is stressed when he or she perceives that the demands made upon that person exceed the resources (e.g., time, money, emotional, physical or cognitive capacity) available to address or reduce those demands (e.g., Lazarus & Folkman, 1984; Nesse et al., 2007). Although people can momentarily feel stressed in response to a specific situation and event without long term consequences 1, chronically high stress levels can lead to more significant mental health symptoms such as depression and anxiety (e.g., Holahan et al., 1999; Wang & Patten; 2001). Given 1 Although it is noted that even such instances can give rise to mental health symptoms or disorders such Post Traumatic Stress Disorder (PTSD). WSA Letterhead

2 initial data from the Work Outcomes Research and Cost-Benefits (WORC) study conducted at the University of Queensland by Professor Harvey Whiteford and colleagues suggests that each year, 6.7 percent of Australian full-time employees will suffer from clinical depression, it is useful to explore the relationship between Australian perceptions of stress, work, and psychological distress. It is noted, however, that while research suggests that feeling overwhelmed by work can contribute to levels of stress (Cotton & Hart, 2002), the relationship between work and stress is complex, with stress being significantly influenced by other factors such as organisational climate and morale (Cotton & Hart, 2003). While Cotton and Hart s (2002; 2003) research suggests a minimal relationship between negative work experiences and stress, colloquially, Australians do tend to frame their experiences of stress within the context of work-life balance, that is, they are more likely to say they are feeling stressed when work demands impact on their capacity to enjoy multiple aspects of life such as spending time with family and friends, and other recreational pursuits. As contemporary acceptance commitment theory (ACT; Bond & Hayes, 2002; Hayes & Smith, 2005) also proposes that the degree to which people pursue individually valued life goals (versus socially promoted goals) influences psychological wellbeing, exploring the relationship between stress, psychological distress and the capacity to balance our energy between necessary versus valued pursuits is also appropriate. Method As part of ABC TV s Stress Buster program, a four-part series exploring factors influencing wellbeing in specific workplaces (which aired during April, 2008), visitors to the website were invited to complete The Stress Survey. Overall, 5,692 individuals participated in the survey, approximately two thirds of which were female (N= 3,728) and one third male (N = 1,942). Participants were asked to answer a number of questions, and were provided feedback about their responses. In addition to basic demographic questions (i.e., age, gender, and location), participants were asked to complete a work-life balance questionnaire and several questions pertaining to stress levels. To measure participants tendency to pursue valued life goals, a work-life balance questionnaire was developed based on Hayes and Smith (2005) ranking activity. Participants were first required to rate on a scale of 1-10 how much they valued particular areas or domains of their life, whereby 1 indicated that a domain was of minimal value and 10 indicated that the domain was of significant value. The domains comprised: a) work/career; b) personal health; c) intimate relationships; d) family and friends; and e) recreation. Once completed, participants were then asked to rate on a scale of 1-10 how much energy they spent on each of these domains, whereby 1 indicated that they spent little energy on that domain, and 10 indicated that they spent a lot of energy on that domain. Participants were provided with their difference scores (i.e., the difference between the value attached to, and energy spent on, a particular domain) and then ask to list one to three goals or intentions that they would like to undertake to address this lack of balance. Participants were also asked to complete two single item statements: 1) Over the last 4 weeks, I have felt stress.., with response options ranging from 1 : not at all, to 7 : a great deal; and 2) do you think work is contributing to your stress?, with response options ranging from 1 : not at all, to 7 : a great deal. The ten items comprising the Kessler Psychological Distress Scale (K10) were then completed, and scores provided back to the participant along with recommendations to seek medical review if the scores were within the medium or high range (according to the tables provided Clinical Research Unit for Anxiety and Depression - CRUfAD; Andrews & Slade, 2001). 2

3 Results The results were analysed using SPSS version 16. Means and standard deviations for the variables were obtained and are presented in Table 1. A reliability co-efficient was computed for the K10 scale: the internal reliability of the scale was very high (α = 0.92). Demographics The average age of participants was 42 years, with almost ten percent of participants being aged between 18 to 25 years of age, almost 50 percent being aged between 26 and 45 years of age and 40 percent being aged between 46 and 65 years of age: three percent indicated that they were younger than 18 years of age and 2 percent indicated that they were older than 65 years of age. Overall, 66% of the participants resided in the city versus regional Australia. Twenty six percent of participants resided in New South Wales (NSW), twenty percent in both Victoria and Queensland, with the remaining thirty four percent of participants coming from the other states. Work-Life Balance Question All participants completed the Work-Life Balance items (N=5692). Table 2 presents the means and standard deviations for each of the life domains in terms of both value and actual that is, how valued participants considered each domain on a scale of 1-10, where 10 indicated very important, and how much energy they spent in this domain on a scale of 1-10, where 10 indicated a lot of energy. Overall, participants tended to value Family and Friends more highly (M = 8.57; SD = 1.56) than other domains. Participants next valued Personal Health (M = 8.37; SD = 1.80), with Work and Career and Recreation valued as the lowest (M= 6.99, SD = 2.08; M= 6.96, SD = 2.06, respectively). By contrast, participants reported that they spent more energy in the Work and Career domain (M = 7.63, SD= 2.50) than in other domains. They spent relatively the least amount of energy in Recreation (M = 4.63; SD = 2.49). To analyse the difference between value and actual domains in the Work-Life Balance items, two methods were used. The first method involved the calculation of the difference scores between value and actual that is the discrepancy between how important a domain was to the participant and how much energy was spent in this domain, whereby a negative value indicated that more energy was spent in a domain than it was valued and a positive value indicated less energy was spent in a domain than it was valued. The second method involved the calculation of the Euclidean distance between all items this method was used to assess the overall distance or balance between the ratings across the domains, whereby a low score indicates a greater amount of balance (or less discrepancy) between the value and energy ratings. This computation was also squared to return the value to a positive score with less variance. The means and standard deviations for the difference scores, the Euclidean balance value and the square root of this balance are presented in Table 2. Finally the two values were computed to reflect the overall value (M = 38.41, SD= 6.15) given to the five life domains and the overall energy (M = 28.76, SD= 7.00) spent on these domains. Overall, participants reported that they spent more energy in the domain of Work and Career than its perceived importance, and spent less energy in the other domains that their respective importance levels. The most amount of difference was observed in the area of Personal Health where there were, on average, 3 scores different between the value and actual energy spent in this domain (the 3

4 maximum score possible was 9). Paired t-tests revealed that all differences were significant (work/career: t(5961) = , p<0.001; personal health: t(5691) = 95.11, p<0.001; intimate relationships: t(5691) = 82.21, p<0.001; family/friends: t(5691) = 78.67, p<0.001; recreation: t(5691) = 75.58, p<0.001). Stress Items Participants tended to rate themselves at above the mid-point in terms of how stressed they had been over the last four weeks (M = 5.37, SD = 1.48), where a rating of 7 indicated high stress levels were experienced. Almost 75% of participants rated themselves as 5 or above on this item (28% indicated the maximum score of 7 ). They also rated themselves slightly above the mid-point in terms of whether they felt work contributed to this reported stress level (M = 4.97, SD = 1.90), where a rating of 7 indicated work contributed a lot to stress: almost 65% of participants gave a rating of 5 or more (28% indicated the maximum score of 7 ). Finally, participants on average indicated psychological distress levels in the medium range on the K10 scale (M = 22.73, SD = 7.69). It is noted that, using the CRUfAD (2003) scoring ranges, 15.6% of respondents reported scores that fell within the nil or minimal stress range, 60.4% fell in the medium range and 24% fell within the high range of psychological distress, with 0.4% of respondents indicating psychological distress levels in the upper limit (scores between 45 and 50, whereby the minimum score is 10 and maximum score is 50). Table 1 Means, standard deviations and percentages for demographic variables: gender, age and location Variable Mean SD N Percentage Gender 5670 Male % Female % Age Under % (1.7% were excluded: age< 16) % % % % % 65+ 2% Reside 5692 City 66.1% Country Region 33.4% State 5692 NSW 26.4% VIC 20.8% QLD 20.3% WA 15.5% SA 7.5% ACT 4.8% TAS 3.7% NT 1.0% Note: N = No of participants who responded to the question. 4

5 Table 2 Means and standard deviations for stress and work/life balance items Variable Mean SD N Percentage Valued 5692 domain Work and Career Personal Health Intimate Relationships Family and Friends Recreation Actual domain 5692 Work and Career Personal Health Intimate Relationships Family and Friends Recreation Difference Scores Diff Work and Career Diff Personal Health Diff Intimate Relationships Diff Family and Friends Diff Recreation Balance Balance sqrt Value total Actual total weeks Stress Workstress K Scores % Scores % Scores % (Scores 45-50) (0.4%) Note: N = No of participants who responded to the question; Valued and Actual Domain: min = 1 & max = 10; Diff scores: min = -10 & max = 10; Balance : min = -20 & max+ 405; Balance sqrt : min = 0, max = 20.12; Value: min = 5 & max = 50; Actual: min = 5 & max = 50; 4 week Stress: min = 1 & max = 7; Workstress: min = 1 & max = 7; K10 scale: min = 10 & max =100. 5

6 Predictors of Psychological Distress (K10) To test whether the level of psychological distress (as measured by the K10 scale) could be predicted by perceived stress and other relevant variables, a standard multiple regression was calculated with the K10 score as the dependent variable and significantly correlated stress and demographic variables as the independent variables. Table 3 presents the regression statistics. The results indicated that the degree to which, over the last 4 weeks, participants experienced stress, the total amount of energy they exerted and the degree to which they experienced balance across the five life domains, and their age significantly predicted their scores on the psychological distress scale (K10): F(4, 5653) = , p<0.001, R² = 0.43, whereby older participants, those who reported greater balance and more overall energy exerted across the five life domains were likely to experience less distress than their counterparts. Thus, 43% of the variance observed in the K10 scale could be accounted for by these four variables, with the vast majority of this variance contributed by the single stress item (i.e., how r 2 much participants experienced stress over the last 4 weeks): S = Table 3 Regression statistics for variables predicting scores of psychological distress (K10) Variables K10 (DV) 4weeks stress total energy age balance B β r 2 S (unique) 4weeks 0.61* 2.89* stress total -0.32* -0.20* -0.07* energy age -0.16* -0.06* * balance 0.28* 0.24* -0.49* -0.03* -0.21* Intercept = M SD R² =0.43ª Adjusted R² =0.43 R = 0.66* Note: * = p<0.001 ªUnique variability =.33; shared variability =

7 Predictors of Stress Levels To test whether work had contributed to stress levels over the last four weeks, these variables were correlated and found to be significantly related (r = 0.51, p<0.001). To test whether the level of stress experienced over the last 4 weeks by participants could be predicted by other relevant variables as well as work, a standard multiple regression was calculated with the 4weeks stress variable as the dependent variable. Table 4 presents the regression statistics. The results suggested that the degree to which participants experienced stress over the last four weeks was significantly predicted by the workstress item and the amount of energy they spent on recreational activities: F(2, 5683) = , p<0.001, R² = 0.30, whereby people who spent less time on recreational activities and felt that work impacted on their stress levels, were more likely to be stressed. Thus, 30% of the variance observed in participants stress levels could be accounted for by both work and recreational activities r 2 undertaken, with work contributing to two thirds of this variance in stress levels: S Table 4 Regression statistics for variables predicting stress levels 4weeks Stress (DV) workstress recreational activity B β r 2 S (unique) workstress 0.51* 0.36* recreational -0.31* -0.21* -0.13* activity Intercept = 4.17 M SD Note: * = p<0.001 ªUnique variability =.23; shared variability = 0.07 R² =0.30ª Adjusted R² =0.30 R = 0.55* Discussion Overall, the results from the ABC TV Stress Buster survey suggest that when Australians experience stress for a period of time they are also more likely to experience significant psychological distress, with a strong chance of meeting the criteria for anxiety or depression. The degree to which they are able to experience balance across key life domains, the amount of energy they put into these domains, and their age also contributes to their psychological distress. Additionally, the results indicated that Australians reporting high stress levels were more likely to consider that work contributed to this stress compared to those reporting lower stress levels. Individuals who spent less time pursuing recreational activities than their national counterparts were also more likely to experience high stress levels. Further, findings revealed that while individuals valued family and friends greater than other aspects of their life, including work/career, personal health, intimate relationships and recreation, they spent more energy on their work and career than any of these other domains. Indeed, the energy spent on each life domain significantly differed from the way individuals valued these domains: participants tended to spend more time on their work and career and less time on the other areas of their life than their 7

8 perceived value. In particular, while participants tended to value personal health very highly, they reported only spending a moderate amount of energy pursuing this goal. It was this overall lack of balance or, colloquially speaking, lack of work-life balance, that contributed to their higher levels of psychological distress. The notion of work-life balance is a difficult one to define; it could be said that such balance can only be evaluated post hoc for example, was there enough time in the day, week or month for me to undertake, complete or enjoy all the things I value in my life?. Recent literature in the area of happiness and contentment, such as ACT theory (e.g., Bond & Hayes, 2002; Hayes & Smith, 2005), proposes that pursuing personally valued rather than socially promoted life-goals contributes considerably to psychological wellbeing. In the current research, this approach was employed to measure the balance Australians experienced between the energy they exerted in a particular area of their life and the value they placed on that area. The results, and the observed relationship between balance and psychological distress, provides some support for this proposition: the less overall discrepancy between the value an individual placed on a particular life domain and the actual energy spent undertaking activities in this area, the less likely that individual was to experience psychological distress. The relationship between having minimal recreational time and higher stress levels also supports the well-communicated principle that having time to pursue pleasurable activities contributes to positive wellbeing. In addition to stress levels and work-life balance, participants age and whether they spent less energy rather than more across the range of life domains were also related to higher psychological distress. The age-related finding supports Australian research which shows that the highest prevalence for depression is amongst people who are in their early to mid 20 s (for women) or in their mid-to-late 30 s (for men) versus older aged individuals. However, the relationship between less energy spent and psychological distress appears counter-intuitive, that is, one might have hypothesised that having to do a lot rather than a little would result in such distress. Alternatively, the finding suggests that participants who were able to report having spent energy across a range of life domains were less likely to feel distressed because they had the time (from work) to do so. Finally, it was noted that almost a quarter of Australians (i.e., one in four) who responded to the survey were found to experience psychological distress levels in the high range with a three in four chance of meeting the criteria for depression or anxiety (Andrews & Slade, 2001). This data is somewhat higher than current epidemiological estimates, which suggest that almost one in ten employed Australians (i.e., 6.7 FTE) will experience clinical depression each year (WORC: Whiteford et al., 2005), and one in five Australian adults will experience a mental illness sometime during their life (Beyond Blue, 2008). These higher figures may simply, however, be an artefact of the internet-based sample: that is, people experiencing distress may have been attracted to the ABC TV Stress Buster website and survey as a way of increasing their knowledge about their experience 2. This may have resulted in a sample biased towards reporting higher levels of both stress and psychological distress than would otherwise have been observed in a more random sample. Overall, the findings from the ABC TV Stress Buster survey provided an interesting snapshot of Australian s perceived stress, psychological distress and the impact that work and Australians capacity to attend to the things in their life that matter has on these experiences. Additionally, the large internetbased participant sample is testament to Australians interest in the topic of stress, their desire to receive feedback about their own stress levels, as well as the capacity of the media to promote and research issues around psychological wellbeing. 2 It is noted that other mental health websites report significant hit rates and completion of mental health surveys or checklists; for example, Beyond Blue s website experienced 280,000 hits between the 7 th and the 16 th of May,

9 References Andrews, G., & Slade, T. (2001). Interpreting scores on the Kessler Psychological Distress Scale. Australian and New Zealand Journal of Public Health 2001, 25 (6), [Online] See: [Accessed: 5/2/2008] beyondblue Research Book : Targeted research in depression, anxiety and related disorders, [Online] Available at: [Accessed: 15/5/2008] Bond, F.W. & Hayes, S.C. (2002). Acceptance and Commitment Therapy at work. In F.W. Bond & W. Dryden (Eds.), Handbook of brief cognitive behaviour therapy. Chichester: John Wiley & Sons. Cotton, P., & Hart P.M. (2003). Occupational wellbeing and performance: A review of organisational health research. Australian Psychologist, 38(2), Cotton, P., & Hart P.M. (2002). The management of work demands in Victorian Schools. Melbourne: Department of Education, Employment and Training. Hayes, Steven C.; Spencer Smith (2005). Get Out of Your Mind and Into Your Life: The New Acceptance and Commitment Therapy. New Harbinger Publications Holahan, C. J., Moos, R. H., Holahan, C. K., & Cronkite, R. C. (1999). Resource loss, resource gain, and depressive symptoms: A 10-year model. Journal of Personality & Social Psychology, 77(3), Hilton, M. Assessing the financial return on investment of good management strategies and the WORC Project [Online] Available at: [Accessed: 15/5/2008] K10 Symptom Scale. Clinical Research Unit for Anxiety and Depression. A WHO Collaborating Center. School of Psychiatry, University of NSW, [Online] Available at: [Accessed: 5/2/2008] Lazarus, R.S., & Folkman, S. (1984). Stress, appraisal and coping. New York: Springer. Nesse, R.M., Bhatnagar, S., & Young, E.A. (2007). Evolutionary Origins and Functions of the Stress Response. Encyclopedia of Stress, Second Edition, 1, pp Wang, J. L. & Patten, S. B. (2001). Perceived work stress and major depression in the Canadian employed population, years old. Journal of Occupational Health Psychology, 6(4), Whiteford, H.A., Sheridan. J., Cleary, C.M., & Hilton, M.F. (2005).The work outcomes research costbenefit (WORC) project: the return on investment for facilitating help seeking behaviour. Australian and New Zealand Journal of Psychiatry, 39 (Suppl.2), A37 9