Correspondence author. Email: tiruchelvi_y@annauniv.edu
This study examines the factor structure of the Hindi version of the Oxford Happiness Questionnaire (OHQ) (
Este estudio examina la estructura factorial de la versión hindu del Cuestionario Oxford de Felicidad (OHQ) (
Traditionally, psychologists have paid greater attention to the concept of ‘unhappiness’ which has many forms like depression, anxiety, stress, and burnout. This has led to an imbalance between the number of studies on depression and studies on positive emotions. However, recent research on positive psychology has thrown light on the concept of happiness and studies on happiness are on the rise (
Though there are controversies on the objective and subjective measurement of happiness as well as on the distortions that could happen when subjects are asked to rate their happiness (
However, few questions have raised doubts on the factor structure of OHQ. First, the study on 172 undergraduate students has resulted in a seven-factor structure for the OHI and an eight-factor structure for OHQ (
As OHQ is the widely used questionnaire in positive psychology research, the issue is whether the OHQ can be used as a uni-dimensional or as a multi-dimensional measure. The standard uni-dimensional approach for the quality of life measures would fail mostly as unidimensionality is the strict requirement (
It is possible that happiness takes different forms across cultures. Culture influences the feelings and emotions of a person, and in turn, these emotional experiences may influence her/his level of happiness and perception of happiness. In the West, happiness is conceptualized as more related to intrapersonal or internal evaluation whereas in China happiness is more related to interpersonal or external evaluation (
Furthermore, the predictors of life satisfaction differ between individualist and collectivist societies (
India is an interesting case for studies on happiness as it is a unique country with cultural traditions unlike anywhere else in the world (
Because of the growth of IT sector, the work patterns of Indian workforce have changed. This has led to increased stress and depression levels among Indian professionals. According to the estimates of PPC worldwide, more than 62% of health concern in India in the year 2012 was due to work stress. In a study by
Few studies have tried to understand the factor structure of OHI, but no study has made use of OHQ. The results of the studies on OHI are not conclusive on the final structure.
Study 1 aims to understand the factor structure of OHQ using exploratory factor analysis.
There are two main ways of determining the sample size either by roughly estimating the absolute sample size or by using the item ratios. This study has used the latter approach. For exploratory factor analysis, the minimum subject to item ratio suggested is 5:1 (
1000 Indian university students pursuing their undergraduate education participated in the study. Of these, 130 responses had missing data which were rejected for analysis. Hence, for analysis, only 870 datasets were taken. The mean age of respondents is 21.53 years with a standard deviation of 0.69. Out of the 870 respondents, 599 were males, and 271 were females.
The questionnaire used for this study is the OHQ (
The reliability of the questionnaire is checked using chronbach’s alpha. The chronbach’s alpha is 0.82, which shows that the internal reliability of the tool for this data set is acceptable.
The initial principal component factor analysis has resulted in a six-factor solution with 63.97% of variance explained. For better interpretation of the factor structure, oblimin rotation is
adopted as the factors are related.
The
factor loadings
less than
0.4 have been suppressed.
Items
Factor 1
Factor 2
Factor 3
Factor 4
Factor 5
Factor 6
OHI Q1
0.41
OHI Q2
0.73
OHI Q3
0.57
OHI Q4
0.48
OHI Q5
0.82
OHI Q6
0.59
OHI Q7
0.55
OHI Q8
OHI Q9
0.70
OHI Q10
0.47
OHI Q11
0.48
OHI Q12
0.74
OHI Q13
0.49
OHI Q14
0.79
OHI Q15
0.71
OHI Q16
0.46
OHI Q17
0.49
OHI Q18
0.58
OHI Q19
0.53
OHI Q20
0.71
OHI Q21
0.73
OHI Q22
0.63
OHI Q23
0.56
OHI Q24
0.50
OHI Q25
0.69
OHI Q26
0.69
OHI Q27
0.80
OHI Q28
0.75
OHI Q29
0.83
Items with factor loadings above 0.4 are only considered for this study as suggested by
Items are
numbered as same
as in
OHQ
Factor
Items
Cronbach’s Alpha
1. Positive Mindset
7,
18, 20, 21, 25
0.83
2. Joy
11,
15, 16, 22
0.86
3. Life Satisfaction
3,
9, 10, 12, 24, 27, 28, 29
0.91
4. Confidence
1, 5,
6
0.81
5. Self Esteem
13,
14, 19, 23
0.86
6. Social Interest
2,
4, 17, 26
0.87
It is unclear whether all these factors converge into the domain of happiness. Hence, a principal component factor analysis is attempted. Such an analysis is useful to extract the uni-dimensional model by restricting the extraction to a single factor. Surprisingly, the single factor could explain only 26.32% of the variance. Thus, the uni-dimensional model could account for only half the variance explained by the six-factor model.
The factor structure generated using EFA in study 1 is tested using Confirmatory Factor
Analysis (CFA) in study 2. Apart from the six-factor model, the other reported models of OHI viz seven-factor structure of
800 Indian university students pursuing their undergraduate education participated in the study. The mean age of respondents is 21.62 years with a standard deviation of 0.81. Out of the 800 respondents, 430 were males, and 370 were females. Of the 800 responses, 145 had missing data which were rejected for analysis. Hence, for analyses, only 655 datasets were taken.
The factor structure extracted from EFA is tested for the fit using Confirmatory Factor Analysis (CFA). CFA allows a researcher to test the relationship between the observed variable and their underlying latent constructs. AMOS 7.0 is used to do CFA. As Maximum likelihood estimation is the default method in AMOS, the pre-requisite for applying the maximum likelihood estimation needs to be checked.
CFA is done to analyze the uni-dimensional, six-factor model (as extracted from EFA) and the other reported models of OHI.
Structure of OHQ
TLI
CFI
RMSEA
χ2 /df
Uni-Dimensional
0.64
0.68
0.10
6.97
Six Factor
Model (extracted
by EFA)
0.91
0.93
0.05
3.64
Three Factor Model
(
0.73
0.78
0.09
6.76
Seven Factor Model
(
0.84
0.86
0.06
4.34
Five Factor Model
(
0.86
0.88
0.06
5.06
The six-factor model yielded fit indices of TLI, (0.91), CFI (0.92), and RMSEA (0.05), falling within the acceptable limits. Hence, the six-factor model extracted using EFA in study 1 shows a good fit. The uni-dimensional model does not show good fit as the indices of TLI (0.61), CFI (0.68), and RMSEA (0.10) are wider than the acceptable limits. Similarly, the other models tested also do not show good fit.
Both the exploratory and the confirmatory factor analysis could not support the uni- dimensional model of OHQ. It could be argued that the wider facets that are included in the construction of OHQ have resulted in the non-convergence of the items into a single domain. As happiness has been looked from the dimensions of negative and positive emotions, well-being, joy and cheerfulness, OHQ has reported a multi-dimensional model rather than a unidimensional model.
The results of the exploratory factor analysis of OHQ have resulted in a six-factor structure. While tested via CFA, the six-factor model reported a good fit and the uni-dimensional model as proposed by
The factor structure of OHQ in India has some common factors and many differences when compared to the Euro-American studies.
This study reports that feeling healthier is related to satisfaction with life. This result is in congruence with the results of
Feeling a sense of purpose of life and mentally alert and having great energy are related to self- concepts. Hence, a person’s self-concept is more related to cognition and action-oriented in the West, which is called an independent self or Euro-American self-ways (
A striking difference noted in this study is that the item ‘having a good influence over events’ is related to a positive outlook in the West (
Hence, OHQ is a combination of many psychological characteristics. Any model of happiness could not explain many of these factors, for example, self-esteem and self-efficacy. It has already been reported that the item content of OHQ failed to differentiate subjective well-being from its antecedents and precedents (
Even though reliabilities are satisfactory for all the six factors, the number of negative items in the tool is quite lesser when compared to the positive items. This unequal ratio of positive and negative items hints at the psychometrically unsatisfactory nature of the tool. Hence, reversal of some of the items should be generated, and further factor structure can be analyzed. Though the six factors generated could be explainable, the existence of the superordinate general factor ‘happiness’ should be looked into. Hence, a hierarchical model can be tested.
The study has not attempted to establish the existence of the happiness domain. It is advised for the researchers to explore the factor structure of the tool and use it for further analysis. A valid measurement tool with well-structured subscales is of great help in research to understand the concept in a better way. Since happiness is an abstract construct, it has to be handled with utmost care while measuring the construct and its sub components. Until the subcomponents and the construct are generalized with repetitive studies, work on the area of happiness with OHQ will remain vague. The validation of OHQ across different samples is still open.
Research article.