Exploring indicators for happiness and its effect to people's emotion using LEIQ(TM) (original) (raw)
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LEIQ™ As An Emotion and Importance Model for QoL: Fundamentals and Case Studies
Jurnal Komunikasi: Malaysian Journal of Communication, 2019
Past literature has increasingly highlighted the importance of understanding people's emotional responses towards the characteristics of everything that has points of interactions with the people. Ever since it was introduced, research relating the emotional responses to the economic power of industrial products, hospitality services, as well as employees' or peoples' productivity has been expanding. This paper presents a model called Lokman's Emotion and Importance Quadrant (LEIQ)™, which was built based on axes of emotion vs. importance, to investigate emotion and the importance of the influential factors of the emotion. The paper presents two case studies; i) Employee's Happiness, ii) Student's Well-being, with the implementation of LEIQ™ to showcase the process to discover the indicators that affect people's emotion, and its importance to the people in the effort to provide information to the leaders or management advocates for their strategic decision-making in ensuring well-being and Quality of Life (QoL). Both case studies have enabled the research to understand factors that affect Employee's Happiness and Student's Well-being, and how it is important to them. The effective use of this model could facilitate decision makers in an organisation, community, society, and even a nation at large to gain knowledge and devise correct strategies to boost people's well-being, promoting more positive emotion, and ultimately upsurge productivity and QoL of the people.
Emotions in everyday life: probability of occurrence, risk factors, appraisal and reaction patterns
Social Science Information, 2004
In a quasi-representative survey, 1242 respondents were asked to describe a situation or event that had elicited an emotion on the previous day. They were also asked to report on the respective appraisal and reaction patterns as well as to verbally label the experience. In addition, they completed a rating list on the relative frequency of experiencing each of 14 emotions and a medical symptom list. The data are interpreted in terms of the odds of experiencing a particular type of emotion in everyday life, mediated by “risk factors” such as culture, socio-demographic background, personality, health, and situational context. Further results concern typical appraisals and reactions for different emotions and relationships between everyday emotions and subjective well-being (life satisfaction and subjective health).
Proposing a New Score to Measure Personal happiness by Identifying the Contributing Factors
Measurement, 2019
Different assessment tools and questionnaires have been developed to measure happiness. The Oxford Happiness Questionnaire (OHQ), that has 29 items, has been used widely to estimate personal happiness. The OHQ is used to quantify personal happiness based on an equal effectiveness assumption for all 29 items. Although the OHQ has been used by several studies, very few studies assess the contribution of the individual OHQ items in explaining personal happiness. The current study attempts to fill this gap by assessing the contribution of the individual OHQ items in explaining personal happiness as a latent variable. Structural Equation Modeling (SEM) is used to assess the relationship of the individual OHQ items in explaining personal happiness in Skudai, Johor, Malaysia. The significant OHQ items that are extracted from SEM results, are used to develop a new personal happiness measurement score. The SEM factor loading values are used to weight the extracted items. All usual clustering methods are used in this study and the most suitable one based on the higher silhouette value is chosen to cluster the proposed personal happiness index. Finally, the relationships between socio demographic factors and the proposed personal happiness index clusters are tested by Gamm and Pearson Chi-Square tests. The SEM results show that 16 out of the 29 OHQ items have poor associations with personal happiness and can be excluded from the model. Most of the non-significant items (items with low level of association) are negatively worded items and the majority of the significant items are related to personal attitudes. The proposed personal happiness index can help to save time and avoid confusion.
The Happiness Indicator (www.happinessindicator.nl) is an online tool designed to make people more aware of their own happiness. Participants periodically record how happy they feel on the present day and how happy they have felt over the past month, using the Happiness Comparer. They also have the option of indicating in the Happiness Diary how happy they felt during the various activities of the previous day. Participants receive feedback in the form of a comparison with their earlier scores and with the average scores of similar participants. The theory behind the website is that a keener awareness of one's own happiness helps users find an optimal lifestyle and consequently promotes happiness among participants.
in the retail industry. Secondary data is collected from various research journals, articles, books and with the help of the internet. For descriptive statistics mean and standard deviation and z test were used.
A Real Data-Driven Analytical Model to Predict Happiness
2021
Original Research Article Purpose: Philosophers and many modern-day researchers are convinced by the fact that the pursuit of happiness is the ultimate goal for humankind. Aristotle believed that the utmost goal of human life was eudaimonia (interpreted as “happiness,” “human flourishing,” or “a good life.”). Recently, many economists and physiologists have been doing applied research in the areas of subjective well-being (SWB) or happiness and trying to understand how it improves the quality of life of individual beings. Thus, searching for a data-driven analytical model is crucial to predict SWB and enhance the quality of life. Methods: Our present study utilizes the world happiness database obtained from the GallupWorld Poll on the happiness of 156 countries. However, our study focuses on using only the data of fiftyfour developed countries, based on the human development index (HDI). We have developed a non-linear analytical model that predicts the average happiness score based ...
Journal of Social Change, 2017
The Happiness Index is a comprehensive survey instrument that assesses happiness, well-being, and aspects of sustainability and resilience. The Happiness Alliance developed the Happiness Index to provide a survey instrument to community organizers, researchers, and others seeking to use a subjective well-being index and data. It is the only instrument of its kind freely available worldwide and translated into over ten languages. This instrument can be used to measure satisfaction with life and the conditions of life. It can also be used to define income inequality, trust in government, sense of community and other aspects of well-being within specific demographics of a population. This manuscript documents the development the Happiness Index between 2011 and 2015, and includes suggestions for implementation.
Happiness Index Measurement: Application of Kansei Engineering and Positive Psychology
This paper discusses how to measure happiness from subjective worker's emotion in one's work environment. It is one of the most important and fundamental problems for positive psychology to measure happiness. In positive psychology study, many of scientific and experimental methods have been proposed as happiness testing or questionnaires. The methods are however depending on specific fields, test groups, and purposes of the measurement. The main issue of this paper is to illustrate the objective method by using factor analysis from subjective data of given basic questionnaires. The method is testing by actual data from a case study of workers' happiness. The robustness is confirmed from the testing data by multidimensional analysis.
The analysis and measurement of happiness as a sense of well-being
Social Indicators Research, 1984
General happiness is philosophically construed as a sense of well-being which in turn has been defined either as a complete and lasting satisfaction with life-as-awhole or as a preponderance of positive over negative feelings. A factor analysis of thirteen well-being scales shows that these two definitions coalesce into a single general well-being factor which is distinguishable only from an independent stress/worries factor. Further evidence shows that familiar scales of neuroticism, depression and trait anxiety measure the same well-being dimension if only in the negative half-range. So does a list of somatic complaints. Various two-factor models of well-being that treat positive and negative affect as independent processes, or that distinguish between affecrive and cognitive components, are challenged on the grounds that they depend on the properties of Bradburn's affect scales which are found to be highly dependent on methodological parameters. Attention is drawn here to the role of test method effects and curvilinearities as factors influencing inter-scale correhtions and structural models. It is concluded that well-being is a robust, primary dimension of human experience and that happiness research is alive and well in psychology.
This paper documents the development and research results of the SHAQ questionnaire; which was developed primarily from ideas in my book, You Can Choose To Be Happy: “Rise Above” Anxiety, Anger, and Depression. It assumes a cognitive systems model of human personality and behavior and emphasizes the importance of cognitions (values, beliefs, knowledge, thoughts, skills, etc.) for influencing both emotions and behavior. Happiness and success (personal, relationship, academic, career, etc.) are a function of cognitive, environmental/conditional, and hereditary/genetic factors. Of is these three classes of factors controlling our happiness and success, we can currently exert control primarily over two—cognitive and environmental. In the book I called these two internal and external routes to happiness. However, even our control over our environment stems ultimately from our cognitions that give us the knowledge, skills, and motivation to affect our environment (including our social environment). SHAQ consists of 81 scales and subscales to reflect the complexity of key cognitive factors influencing happiness and success. SHAQ‘s main scales were reliable according to Cronbach alpha tests. More than 3446 users completed much of SHAQ according to their personal choices. All completed additional outcome scales and items. Overall happiness, depression, anxiety, anger, health, relationship outcomes, highest personal income, academic achievement, and other factors were measured by outcome scales. The SHAQ scales had moderate to high positive correlations with almost all outcome measures. SHAQ‘s subscales had surprisingly high multiple correlations with the emotional outcomes; with Overall Happiness, R = .865, R Square = .749; with Low Depression, R = .730, R Square = .533; with Low Anxiety R = .675, R Square = .426; with Low Anger-Aggression, R = .701, R Square = .491(N = 1123 for all analyses). For the 224 subjects who completed all 70 subscales including the academic scales, R = .897, R Square = .805 for Overall Happiness. I devised the Happiness Quotient (HQ) to get an overall predictor of happiness. The HQ score is determined by a linear combination of the 56 SHAQ subscale scores. HQ has a mean equal to 100 and a SD equal 10 (similar to IQ). Results for other outcomes included for the Relationship Outcomes scale, R = .693, R Square = .467; for the Health Outcomes scale, R = .816, R Square = .666; for Highest Income, R = .486, R Square = .236; and for Educational Attainment, R = .458, R Square = .210. Behavioral measures used as outcomes also yielded good results. For example, for a Major Depression Checklist, R = .596, R Square = .356; Amount of Therapy for Depression, R = .452, R Square = .204; and Amount of Medication for Depression, R = .409, R Square = .167. The results support SHAQ‘s reliability, validity, and utility. The results also support the main ideas in the book and the proposition that a host of key cognitions are the most important determinants of happiness and other emotions. They also show how these positive happiness and success-producing factors tend to correlate with each other and may support the development of each other. The implication is that when people begin a self-development program, they can use SHAQ to get a profile of the factors they need to improve in order to increase their happiness (and decrease depression, anxiety, and anger) and increase life success. The results also suggest that starting almost anywhere can begin a positive change process that will improve other factors as well.