Issues in Interdisciplinarity 2020-21/Evidence in Measuring Workplace Happiness

Introduction
Modern perspectives on happiness tend towards defining "purpose" in one's life. The Japanese, for example, qualify happiness through their idea of Ikigai, "that which makes one's life worth living", focusing on four main areas of life. (Note that "well-being" differs from happiness, which forms a part of overall well-being). This Wikibook chapter will explore the use of evidence in measuring workplace happiness, as well as the tensions arising between different disciplinary perspectives.

Economics


Economists place value on quantitative data, using surveys, self-assessment scales and measurement tools such as the Day Reconstructing Method and Bhutan's Gross National Happiness Index. Tensions can arise with other disciplines as economists focus selectively on empirical data, which lacks subjective context, treating happiness purely as a calculation.

Previously unavailable, big datasets now provide empirical evidence that higher income correlates with higher happiness. This is true cross-nationally, enabling "reassessment" of the Easterlin Paradox, the idea that money doesn't buy happiness, and that more money to a poor person means more than it does a rich person. Company bosses use this evidence and implement pay increases tapered to benefit lower-incomes more than higher. The hope here is that happiness is "endogenous": engendering productivity and conscientiousness (Pinker, 2018), partially fulfilling a need to feel valued to feel happier. The evidence also refutes the earlier idea that $75,000 is the optimal happiness and income level above which happiness growth slows.

Psychology


Modern Positive Psychologists established the Happiness Formula of H = C + V + S: C being conditions of your life; V being Volunteering that you do and daily choices you make; and S being your biological set point. Meditation, under the “eightfold noble path” (Haidt, 2006) helps with the V because it reduces attachment and cultivates acceptance. Happiness has been defined as “the form of pleasant moods and emotions, well‐being, and positive attitudes” (Fisher, 2010), and being happy at work has been shown to be an important factor in workplace advancement. Fisher established the key variables in measuring workplace happiness as job satisfaction, engagement and organisational loyalty, all of which can be measured both subjectively and empirically across a timeframe, concerning a unitary or collective subject.

Cognitive Behavioural Therapy works to rationalise and not catastrophise behaviours, asking questions like "what's the worst that could happen?" and "has it ever happened?" to change behaviours through changing thought patterns. This has been evidenced through Randomised Control Trials (RCTs) and implemented in workplace settings to reduce stress amongst employees. A major method of evidence retrieval in psychology is self-reporting, consisting of single or multi-faceted questionnaires given to respondents through RCTs or on case-by-case bases, for example the Job Descriptive Index, or the Utrecht Work Enthusiasm Scale.

Psychology raises both intra- and inter-disciplinary tensions. Within psychology, twin studies have shown that genetic factors account for 35-50% of our happiness levels. This disproved early Freudian theory, favouring quantitative genetic data over subjective and qualitative analysis methods, raising tensions between psychologists as quantitative data continues to be held in increasingly high regard. Psychology emphasises reasons for behaviour rather than outcomes, with data typically being more subjective. However, evidence used in happiness economics is largely quantitative: mathematical models predict behaviour with happiness as the desired outcome. These types of data are seen in stark contrast to one another, ultimately leading to disharmony, perpetuating interdisciplinary tension further.

Neuroscience
Neuroscientific studies have been conducted into workplace happiness, demonstrating the interactions of neurotransmitters and the impact these have on happiness levels.

Recent research by neuroeconomist Paul Zak found that an increased level of the hormone and neurotransmitter oxytocin leads to an increased level of trust, efficiency and workplace productivity, in turn resulting in higher levels of happiness. This was proven with empirical evidence, as blood samples were used to quantify oxytocin levels in social interactions.

The evidence shows dopamine, a neurotransmitter, is a strong contributor to workplace happiness. Higher levels of dopamine in the brain have been correlated with higher levels of workplace motivation and happiness. Lower levels of motivation are linked to psychiatric disorders like depression and increased risk of Alzheimer's and other neurological disorders. The evidence used to quantify dopamine levels is empirical, using Positron Emission Tomography (PET scanning) to map, analyse and quantify neurotransmitter levels in different parts of the brain.

Tensions also exist between psychology and neuroscience. Psychology was historically the more sociological discipline, with neuroscience relying on biological principles. Neuroscience is based on the concept of 'eliminative reductionism', meaning many neuroscientists believe that neural analysis could replace psychological analysis. Psychologists label humans as complex systems, and believe that brain function can't simply be reduced to neural functions, but rather is influenced by a whole range of biological, social and cultural factors. Here lies an obvious tension, due to two opposing fundamental principals (reductionism vs holism), and the consequent effect on research methodology and formation of evidence.

Anthropology


Cultural, societal and geographical constructs of happiness hold the same communalities, what the Japanese call 'Ikigai', the Danish 'Hygge', for example. Humans are happier when they are fit, healthy, loved, safe, comfortable and socially connected (not lonely), which are critical considerations for workplace happiness. These factors can be measured by anthropologists through qualitative data, helping to understand the role of meaning and value in happiness, which are variables often excluded when just focusing on quantitative measures.

Smaller societies feel happier if they have cultural autonomy within an advancing, modern world. Many young, single, white, males have experienced high levels of unhappiness during lockdown and look forward to going to work for interpersonal contact, upon which mental health is dependent. Happiness differs between the generations: happiness at twenty is different to that at forty and at sixty as vested interests evolve and sociocentric orientations are challenged by globalisation. Anthropology has been a cultural critique of disciplines and what's best for humans and what's best for the State.

Anthropology almost keeps a restraining hand on quantitative happiness measurements. Sustainable emotional well-being of employees is a crucial contributing factor to workplace happiness; its positive effects can lead to increased productivity, resilience and engagement. Economic measures alone cannot quantify happiness, so applying an anthropological perspective could provide an overview of what makes humans happy, combining all the interdisciplinary evidence available and applying those conditions to the workplace. While the sciences, including economics, value empirical evidence, anthropology values qualitative ethnographic evidence. These differences can be overcome by combining cross-cultural statistics, which offer more nuanced understandings of local differences.

Conclusion
Disciplines approach the epistemology and ontology of evidence in different ways, creating incongruity in what constitutes evidence and how evidence is defined, leading to interdisciplinary tensions.

These contrasting beliefs pose challenges when it comes to measuring workplace happiness. While individual disciplines can provide unique perspectives, the search for clearer common ground continues. Taking a more comprehensive approach to measuring happiness, combining the subjective nature of qualitative data with quantitative data would be the ideal interdisciplinary solution. Evidence needs to be integrated holistically, but perspectivism between the disciplines slows the process of collaboration.