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Measuring Happiness Levels in Mumbai: Methodology

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Published: 23rd Mar 2018 in Health

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Happiness has been defined either as a broad notion of how one feels about their life in general or as an emotional or affective state. Depending on the way researchers define the concept, there have been variable attempts at measurement. With decades of research, we have a better understanding of how to measure the happiness of others. A combination of quantitative and qualitative methods appears to be most productive. (Helm, 2000)

This chapter illustrates the methodology followed, tools used and ethical guidelines followed during the study.

The following are the research objectives of the study.


  • To determine the level of happiness among the residents of Mumbai
  • To assess the mental healthcare facilities in the city
  • To find out If there is any correlation between mental health and happiness among the residents of Mumbai

On the basis of these research objectives, the following methodology was formulated.

  1. Quantitative measurement of happiness

Over the past two decades there have been an increasing number of quantitative studies of happiness and well-being. In particular, there have been ongoing debates on whether happiness can be measured, whether it should be measured, how it should be measured and what are the factors affecting it (Ballas & Tranmer, 2012).Psychologists and sociologists have used subjective questions regarding individuals’ happiness for over three decades. Cantril (1965) developed a question for life satisfaction. Similar question modules include the Likert (1932)-scale and the Visual Analog Scale (VAS). See also Bradburn (1969). The answer to these subjective questions has been indiscriminately termed ‘happiness’, ‘general satisfaction’ and ‘subjective well-being’. In the GSOEP the satisfaction question is:

Please answer by using the following scale in which 0 means totally unhappy, and 10 means totally happy.

How happy are you at present with your life as a whole?

Here, we call the response to this question the General Satisfaction (GS) level of the respondent. In this case, there are 11 numerical categories, but the question has also been posed with 7 or 5 categories or with verbal labels, such as ‘very happy/happy/so-so/somewhat unhappy/very unhappy’. The end result is invariably an ordered categorical evaluation of the quality of life of the individual.(Ferrer-i-Carbonell & Frijters, 2004).The survey context, such as question order, introductory text and the survey source, can influence respondents’ understanding of individual questions within a survey, as well as the information that they draw on in order to answer those questions.

In quantitative measurement, we measure the overall subjective well begin by quantifying certain constructs and concepts given below.

  1. Measurement of subjective well being

Eudemonic questions like show happy are you with your life and how satisfied are you with your life have been asked to be rated on a cantril ladder.

Subjective wellbeing is a broad category of phenomena that includes people’s emotional responses, domain satisfactions and global judgements of life satisfaction. Each of the specific constructs need to be understood in their own right ,yet the components often correlate substantially suggesting the need for the higher order factor.(Diener, Suh, Lucas, & Smith, 2013). Quality of life is a broad term covering those aspects of overall well-being that are not captured only by material conditions(OECD Guidelines on Measuring Subjective Well-being, 2013). 12 different constructs were identified and worked upon to generate questions. The constructs namely are: education, employment, family, gender, health/lifestyle, personality/self-efficacy, relationships, work-life balance, communal living & housing/income.

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Employment status – employment status is known to have a large influence on subjective Well-being, with unemployment in particular associated with a strong negative impact on measures of life satisfaction.(OECD Guidelines on Measuring Subjective Well-being, 2013). Hence 9 questions have been formulated on employment.

Both physical and mental health are correlated with measures of subjective well-being (Dolan, Peasgood and White, 2008), and there is evidence that changes in disability status cause changes in life satisfaction (Lucas, 2007). Although health status is complex to measure in household surveys, there is a large pool of well-developed measures available, such as the health state descriptions from the World Health Survey (WHO, 2012), or more specialised question modules, such as the GHQ-12 for mental health (Goldberg et al., 1978).

Environmental quality is inherently a geographic phenomenon, and integrating datasets on environmental quality with household level data on life satisfaction is costly. Nonetheless, there is some evidence that noise pollution (Weinhold, 2008) and air pollution (Dolan, Peasgood and White, 2008) have a significant negative impact on life satisfaction(OECD Guidelines on Measuring Subjective Well-being, 2013). Hence by merging both, 14 questions have been formulated beneath the heading Health/Lifestyle.

There is significant evidence that aspects of work/life balance impact on subjective well-being, in particular commuting (Frey and Stutzer, 2008; Kahneman and Kruger, 2006), and time spent caring for others(OECD Guidelines on Measuring Subjective Well-being, 2013). To gauge its effect, 4 questions have been formulated on it.

Education and skills have obvious interest both as variables for cross-classification and because there is good evidence that education is associated with subjective well-being at a bivariate level(OECD Guidelines on Measuring Subjective Well-being, 2013). To understand the effect and views of the respondent on education, 7 questions have been formulated.

Generalised trust in others as well as more domain specific measures of neighbourhood and workplace trust are crucial factors when accounting for variation in subjective well-being(OECD Guidelines on Measuring Subjective Well-being, 2013).Social contact is one of the most important drivers of subjective well-being, as it has a large impact both on life evaluations and on affect(OECD Guidelines on Measuring Subjective Well-being, 2013). 5 questions have been formulated under communal living.

One of the most consistent and robust findings in the field of subjective well-being (SWB) is that the components of SWB are moderately related to personality. Like personality traits, SWB is consistent across situations and is stable across the life span, even after the occurrence of intervening life events(Diener & Lucas, 1999). 7 questions have been formulated on personality.

Subjective sexual well-being refers to the perceived quality of an individual’s sexuality, sexual life, and sexual relationships. We focus primarily on evaluations of sexuality in terms of satisfaction judgments, which have been central for studying the concept of overall wellbeing(Laumann et al., 2006). Some of these questions have been asked under relationships (4).

The relationship and effect of familial relations, housing and income has also been captured by asking 8 questions on it.

  1. Satisfaction with life scale

The Satisfaction with Life Scale (SWLS) was originally developed by Diener, Emmons, Larsen and Griffin (1985), and was intended as a brief assessment of an individual’s general sense of satisfaction with their life as a whole. Although the SWLS includes only five items, it has demonstrated good psychometric characteristics.(Pavot & Diener, 2008)

The Satisfaction with Life Scale (SWLS; Diener, Emmons, Larsen, & Griffin, 1985) is a widely used measure of life satisfaction. The SWLS consists of five items which are rated on a seven-point Likert-type response scale? Scores on the SWLS vary from 5 to 35 and can be compared with the scores of an international norm group (see Pavot & Diener, 2008). According to Pavot and Diener (2008), various studies confirmed the internal consistency of the SWLS (with alpha coefficients varying from .79 to .89) – (Rothmann, 2013)

The authors began the development of the SWLS by generating a pool of 48 items intended to reflect life satisfaction and well-being. From this original pool of items, factor analysis was used to identify 10 items with high loadings (0.60 or above) on a common factor interpreted as global evaluations of a person’s life. After the elimination of redundancies, this group of items was then further reduced to five items, with minimal effect on the alpha reliability of the scale. A 7-point Likert style response scale (ranging from 1¼strongly disagree to 7¼strongly agree) was utilized in order to afford respondents an array of response options. The five items are all keyed in a positive direction, so the five responses can simply be added to arrive at a total score for the scale. The possible range of scores is therefore 5 to 35, with a score of 20 representing the neutral point on the scale. Scores between 5 and 9 indicate that the respondent is extremely dissatisfied with life, whereas scores ranging between 31 and 35 indicate that the respondent is extremely satisfied with life. Scores between 21 and 25

represent slightly satisfied, and scores from 15 to 19 are interpreted as falling in the slightly dissatisfied range(Pavot & Diener, 2008).

Quality of life has become a primary concern in the evaluation of both the quality and outcome of health care (Moons, Budts, & De Geest, 2006). In a review of different conceptual approaches of quality of life, Moons et al. (2006) found life satisfaction to be the most adequate and appropriate conceptualization, as it successfully addresses all of the conceptual problems they examined with regard to health-related quality of life.(Pavot & Diener, 2008).

  1. In most ways my life is close to my ideal

1. Strongly disagree.

2. Disagree.

3. Slightly agree.

4. Neither agrees nor disagrees.

5. Slightly agree.

6. Agree.

7. Strongly agree.

  1. The conditions of my life are excellent

1. Strongly disagree.

2. Disagree.

3. Slightly agree.

4. Neither agrees nor disagrees.

5. Slightly agree.

6. Agree.

7. Strongly agree.

  1. I am satisfied with my life.

1. Strongly disagree.

2. Disagree.

3. Slightly agree.

4. Neither agrees nor disagrees.

5. Slightly agree.

6. Agree.

7. Strongly agree.

  1. So far I have gotten the important things I want in life.

1. Strongly disagree.

2. Disagree.

3. Slightly agree.

4. Neither agrees nor disagrees.

5. Slightly agree.

6. Agree.

7. Strongly agree.

  1. If I could live my life over, I would change almost nothing.

1. Strongly disagree.

2. Disagree.

3. Slightly agree.

4. Neither agrees nor disagrees.

5. Slightly agree.

6. Agree.

7. Strongly agree.

  1. Rating scale

There are multiple scales, questionnaires and inventories of happiness. The following tools are mere examples: the Oxford Happiness Inventory, the Depression-Happiness Scale and the Memorial University of Newfoundland Scale Of Happiness. These scales and other contain multiple items, most frequently from 10-130 items. A plethora of studies on happiness have used single item self-rating scales with different options , mainly the Likert scale which offers 5 or 7 choice point.(Abdel-Khalek, 2006). Much quantitative research within psychology relies upon the use of numerical scales and in the main Likert scales have emerged as the dominant measurement tool(Ogden & Lo, 2012).

Although providing respondents with a rating scale may seem straightforward, there are many ways in which response formats can vary.

There may be differences in the response formats that may be optimal for evaluative, eudemonic and affective measures. Evaluative and eudemonic measures are similar to attitude measures in that it may be preferable for the response format to contain information about both the direction of feeling (positive/neutral/negative or agree/disagree), as well as its intensity (strong-weak). In the case of affect measures, it is often desirable to measure positive and negative affective states separately. Thus, rather than asking about the direction (positive-neutral-negative) of affect, respondents are often given a single adjective (e.g. happy) and asked to describe either the intensity or the frequency with which they felt that way within a given time period. This may in turn have implications for the optimal number of response options, as well as response scale labelling and anchoring.

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There is, however, considerable debate around the optimal number of response categories – and a very wide range of opinions is available in the literature (Weng, 2004, for a brief summary). This number will depend on respondents’ information-processing capacities and preferences, survey mode, scale labelling, and, to some extent, presentational concerns and questionnaire length. Increasing the number of response categories beyond the optimal length could result in loss of information, increased error and decreased reliability, because the individual scale points will mean less to respondents. The increased response burden associated with longer scales may also lead respondents to become less motivated to optimise and more likely to satisfice in their answers, thus also increasing the risk of response biases and error

Bradburn et al. (2004) argue that, due to the burden on memory and attention, five categories is the maximum number that a respondent can process in a verbal interview setting (telephone or face-to-face) without visual prompts. Furthermore, when the response categories are qualitatively different from one another (rather than being imagined on a sliding scale), these authors suggest that four categories should be the upper maximum. On the other hand, Alwin and Krosnick (1991) indicate that respondents may prefer to have response options denoting weak, moderate and strong negative and positive evaluations (i.e. a 7-point scale) in part because these are the categories that people often use to describe attitudes and opinions in everyday life.

For evaluative measures with numerical response scales, longer scales (up to around 11 scale points) often appear to perform better. Using a multi-trait-multi-method design, Alwin found that across all 17 domains of life satisfaction measured, the 11-point scales had higher reliabilities than the 7-point scales. In 14 out of 17 cases, the 11-point scales also had higher validity coefficients; and in 12 of 17 cases, 11-point scales had lower invalidity coefficients, indicating they were affected less, rather than more, by method variance

– I.e. systematic response biases or styles. This overall finding is supported by Saris et al. (1998) who used a similar multi-trait-multi-method analysis to compare 100-point, 4 or 5-point and 10-point satisfaction measures, and found that the 10-point scale demonstrated the best reliability.

For affect measures, one might be interested in measuring either the intensity of feeling or the frequency with which that feeling occurred. Measures of recently-experienced affect are less like attitude measures, in that one is effectively asking respondents to remember a specific experience or to sum experiences over a specific time period.

The method adopted for this study due to paucity of time and level of research expected from us at master’s level is using a 7 point scale for affect measures and using cantril ladder for eudemonic measures. The 7 point scale ranged from strongly disagrees to strongly agree.

  1. Background characteristics

Questions on the respondent’s background characteristics were collected in the beginning of the questionnaire. Information such as the following was collected.

  • Age
  • Gender
  • Marital status
  • Religion
  • Education
  • Work status
  • Family income
  • Number of years residing in Mumbai
  • Native state
  • Number of family members
  • Number of earning members in family
  • No of rooms in house
  • Ownership of house
  1. Qualitative measurement of happiness

One open ended question was asked in the beginning of the questionnaire i.e. what does happiness means to you? The aim was to explore what people equate happiness with and how does it affect their overall living. The use of qualitative assessment methods, such as open- ended questions, provides information about the participants’ perceptions, views and beliefs in their own terms, in contrast to using outside researchers’ definitions and categories, which is typical of quantitative inquiries (Denzin and Lincoln 2000). Qualitative data show an additional crucial feature: it is possible to convert them into quantitative scales for purposes of statistical analyses(Fave, Brdar, Freire, Vella-Brodrick, & Wissing, 2010).

The entire questionnaire was formulated in the following way

Background characteristics


Open ended question on happiness


Eudemonic question on happiness and satisfaction


Questions on different constructs merged with the GHQ -12


Satisfaction with life scale


  1. Data collection & sampling

Some surveys with the household as the unit of measure rely on a single respondent (such as the head of household) to provide responses for the household as a whole. This cannot be used for measures of subjective well-being, since the cognitive process of evaluating and responding with respect to one’s own subjective well-being is very different to that of providing an estimate of another householder’s state of mind. Responses to questions on subjective wellbeing are inherently personal, and consequently the unit of measure for subjective well-being must be the individual. While this will typically not be an issue for surveys where the individual is the primary unit of analysis(OECD Guidelines on Measuring Subjective Well-being, 2013).

The two modes most commonly used to collect information on subjective well-being are Computer-Assisted Telephone Interviewing (CATI), conducted by an interview over the telephone, and Computer-Assisted Personal Interviewing (CAPI), where the interviewer is personally present when recording the data.(OECD Guidelines on Measuring Subjective Well-being, 2013)

Due to paucity of time, the mode was data collection was paper and pen method. The respondents were allowed to take the questionnaire home for a day and could be collected later based on their discretion.

The sampling universe was people who had lived in Mumbai for more than 5 years and was targeted at literate working population. The sampling method chose was convenience sampling and the sample size is 200.

  1. Confidentiality and ethics

Initially the respondents were informed about the purpose of the study and the collector’s identity and her affiliation to the institute. The confidentiality of the participants was not disclosed at any point during the course of the research. Furthermore, the respondents were assured that their responses would be used for academic purposes only.


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