13 October 2016 Zelenski, J. M., Murphy, S. A., & Jenkins, D. A. (2008). The happy-productive worker thesis revisited. Journal of Happiness Studies, 9(4), 521-537. Introduction Zelinski, et al (2008) look at over 70 years of research realizing that little has been revealed regarding whether happier workers are more productive. Utilizing a longitudinal literature review and experience sampling methods, they examine this relationship amongst Directors in the public and private sectors and attempt to reconcile the long history of mixed findings of this happy productive worker thesis. Review of the Literature The authors review literature dating from the 1930s (two sources only), but the vast majority of their sources are from the 1990s to 2000s with two additional from the middle 1980s and one index of job satisfaction dating from the 1950s. While the authors review a rather expansive selection of literature, there are no definitive or conclusive results from this review of the literature. The authors admit that the findings in the research are inconsistent, possibly due to inconsistent measurement (Zelinsky, et al, p. 522, 2008), yet they do not question the motives of the research and who funded the research, whether universities or corporate, and they do not indicate what the measurements were and how they were measured. The authors indicate that in these studies happiness has been mostly operationalized as job satisfaction, though they admit that job satisfaction may not be an effective proxy for happiness. Throughout the discussion, the authors’ language indicates a possible link between the operationalized terms of happiness and productivity and a corporate or industrial link. In other words, the literature analysis that they have conducted here imply that the studies were meant to determine what indicates a happy productive worker, not what a happy productive person might look like. This strikes me as a study in the service of industry and corporations. Research Question and Hypotheses It is also narrow overall that the researchers insisted on a sampling of Directors, rather than overall, employees; given that Directors more than likely receive a higher salary than wage employees, and while a higher salary doesn’t necessarily equate to a happier worker, it certainly is a factor for its consideration. Their rationale for the Happy/Productive Worker Hypothesis relies upon “Theory Y” (Zelinsky, et al, p. 522, 2008), which suggests that happier people are more productive as they cite several studies that support this, with one outlier pair of researchers, Weiss and Cropanzano ((Zelinsky, et al, p. 523, 2008) who argue that the relationship between productivity and happiness would be stronger if the focus was on more than just job satisfaction. However, they offer no studies that specifically cite research with lower income communities and within communities of color where productivity equates to a job that pays the bills when there are no other opportunities than the present one. In this case, productivity does not necessarily equate to happiness but survival. There is no mention of the ethnic make-up of the study’s participants anywhere in the research. The present study rejects the vague association between happiness and productivity because the relationship remains unclear. To address these discrepancies, the authors utilized multiple happiness indicators assessed as both states and traits that cover both cognitive and emotional approaches. They used one happiness measure, Job Satisfaction, to cover the approach used in past studies. The authors added Life Satisfaction to provide the broadest measure to test the happy productive worker hypothesis to encompass factors that contribute but may not necessarily be related to work. Study Design and Data Collection The present study relies upon three hypotheses, positive affect will be the strongest predictor of productivity, an independent measure that allows participants to consider work life quality as they wish (to allow for participants’ ability to measure productivity better themselves rather than more standard measures), and day-to-day variations in life satisfaction beyond the job site will influence trait-level productivity and overall satisfaction will not influence variations of short-term productivity. To measure the happiness indicators, they utilized the PANAS questionnaire (Zelinsky, et al, p. 525, 2008) that includes two dimensions of “high arousal” of pleasant and unpleasant emotions to assess trait emotions where participants rated similar sets of emotional adjectives that are associated with productivity. Additionally, the authors used an experience sampling method (ESM) that allowed participants to grade their happiness and productivity every two weeks. While quantitative measures are sometimes necessary to quantify measurements of productivity and happiness, I question the results as truly accurate, except on an extremely superficial level. What is missing is nuanced qualitative assessment of the participants’ happiness within working conditions and life conditions. In most cases, I would find quantitative studies flawed without utilizing a mixed methods approach and this study is no different. Population and Sample Participants were 75 Directors who typically reported to a junior Vice President that were drawn from a larger pool of 143 respondents in a larger study that were employed in the private sector and the Canadian Federal Government. No participants were drawn from a pool of hourly wage earners, and that fact, while sometimes necessary for a study limited in scope, designed to obtain results that can be measured, also limits the results from being reflected upon a larger population. That is also true here. Also limiting is the fact that almost half were men (Zelinsky, et al, p. 527, 2008). Participants were also noted as being either married (or in a common-law relationship), and had children. The assumption, according to the study is that the men were cisgendered men in heterosexual relationships. Nowhere is any other sexual orientation mentioned. The authors analyzed participants who completed ESM questionnaires at least five times and measured these against day-to-day reports of happiness and productivity. While the ESM diary was a written record of happiness or unhappiness, participants were asked to regulate their descriptions to six positive emotions and nine negative emotions. Emotions from this scale were averaged to obtain a single figure for positive effect and one for negative effect. Throughout, unfortunately, there was no room for nuances in mood beyond this scale. The PANAS scale was measured in the same way. Study Findings and Data Analysis The ESM phase of the study, among individual participants, participants reported being somewhat satisfied with their jobs and their lives as a whole. The authors reported a very low level of negative affect and a somewhat low level of positive affect, though they indicate that the variance was significant which seems insignificant to this author, and still, the motivation of the participants, if they were under the impression that the study might not be anonymous and would possibly be reported should be questioned. Between-subject correlations and within-subject correlations were not all statistically significant but all were positive. Again, this author questions the wisdom of selecting a sample amongst directors without including another group of wage employees to measure against this sample. Additionally, job satisfaction and life satisfaction demonstrated slightly weaker but significant correlations with productivity. This was expected according to the study authors but not the negative effect that was not significantly associated with productivity who concluded that it was not surprising that happy Directors tended to be more productive than unhappy Directors. When the authors performed a regression analysis of between-subject’s happiness and unhappiness factors, happiness explained 17% of the variance in productivity, but positive effect was the only significant predictor in this equation. Given that the results here are not entirely earth-shattering, it is possible that the authors became so immersed in the numbers and the analysis that they ignored the nuanced satisfaction and dissatisfaction of the participants, insisting that the results fit into what they were either hoping to find or forgetting the fact that there were human subjects at all, becoming completely lost in the analysis of the numbers in their study. In short, the results were not surprising and were found to correlate with the original hypothesis that happier people were more productive when it was conceptualized as the frequent experience of positive emotions. While the authors insisted upon using statistical analysis, two that have been used in previous studies, why did they hope to achieve results all that different from those previous studies? Summary and Discussion The authors looked at over 70 years of happy-productive worker studies that date from the 1930s, but significantly are drawn from the mid 1980s to the 2000s. They paid special attention to three components: the state-trait distinction, alternative conceptualizations of happiness (life factors), and causal direction. These were explored utilizing an ESM, multiple happiness indicators, and a prospective design, attempting to codify research testing that has varied within many of the previous studies. What varied here, beyond the generally expected happy-productive thesis, was that the extent of that support depended upon what “happiness” means to the participants. As expected, positive effect correlated with productivity generally and across methodological contexts (prospective, between-subjects, and within-subject), but the negative effect revealed no relationship. The authors believe that their multiple method approach allows them to argue against some alternative explanations, such as happy moods encouraging socialization and less productivity, but the results indicate positive affect resulted in fairly immediate payoff in productivity. Again, this author is compelled to ask what the ethnic makeup of the participants’ sample. According to the data supplied, other factors were not included that would necessarily skew the results to anything but a happy productive worker where a Director, a person of color would be unhappy and productive because their survival and success in work and personal life depended on it. Nowhere does the data or hypothesis account for this, and grated it should be another group that is also studied, perhaps with a distinct hypothesis. This population is ignored and isn’t even considered. While the emphasis of the authors is on productivity and essentially how to increase it, happiness is generally accorded the means to obtain that productivity, rather than the general life satisfaction or life happiness of the whole person fulfilling their life’s aspirations. This is another flawed element that the authors failed to take into account, perhaps because they were primarily focused on the results of a happy productive worker rather than the individuals behind the participants. References Zelenski, J. M., Murphy, S. A., & Jenkins, D. A. (2008). The happy-productive worker thesis revisited. Journal of Happiness Studies, 9(4), 521-537.