Access the full text.
Sign up today, get DeepDyve free for 14 days.
F. Faul, E. Erdfelder, A. Buchner, Albert-Georg Lang (2009)
Statistical power analyses using G*Power 3.1: Tests for correlation and regression analysesBehavior Research Methods, 41
C. Chandramouli (1932)
The Census of IndiaNature, 130
Harpreet Singh (2016)
Increasing rural to urban migration in India: A challenge or an opportunityInternational journal of applied research, 2
D. Myers, E. Diener (1995)
Who Is Happy?Psychological Science, 6
J. Smyth, Matthew Zawadzki, Vanessa Juth, C. Sciamanna (2017)
Global life satisfaction predicts ambulatory affect, stress, and cortisol in daily life in working adultsJournal of Behavioral Medicine, 40
S. Oishi (2021)
Income and Subjective Well-Being: Review, Synthesis, and Future Research
Hugo Vásquez-Vera, L. Palència, Ingrid Magna, Carlos Mena, Jaime Neira, C. Borrell (2017)
The threat of home eviction and its effects on health through the equity lens: A systematic review.Social science & medicine, 175
Sugata Bag, S. Seth (2017)
Does It Matter How We Assess Standard of Living? Evidence from Indian Slums Comparing Monetary and Multidimensional ApproachesSocial Indicators Research, 140
K. Brown, T. Kasser, R. Ryan, P. Linley, K. Orzech (2009)
When what one has is enough: Mindfulness, financial desire discrepancy, and subjective well-beingJournal of Research in Personality, 43
M. Larsen (2002)
The Psychology of Survey ResponseJournal of the American Statistical Association, 97
M. Lange (2020)
Multidimensional poverty in Kolkata’s slums: towards data driven decision making in a medium-sized NGOThe Journal of Poverty and Social Justice
Roshan James, A. Sabry (2012)
Information effects
Jean Ki, S. Faye, B. Faye (2005)
Multidimensional Poverty in Senegal: A Non-Monetary Basic Needs ApproachPartnership for Economic Policy Working Paper Series
H. Blanton, J. Crocker, Dale Miller (2000)
The effects of in-group versus out-group social comparison on self-esteem in the context of a negative stereotype.Journal of Experimental Social Psychology, 36
C. Leach, Heather Smith (2006)
By whose standard? The affective implications of ethnic minorities' comparisons to ethnic minority and majority referents.European journal of social psychology, 36 5
(2020)
Poverty & Equity Brief India
D Boswell (1975)
10.2307/2801228Man, 10
L. Camfield, G. Crivello, M. Woodhead (2008)
Wellbeing Research in Developing Countries: Reviewing the Role of Qualitative MethodsSocial Indicators Research, 90
H. Cantril (1965)
The pattern of human concerns
J. Marshall (1981)
This is psychology?Nature, 290
L. Asselin (2009)
Analysis of Multidimensional Poverty
C. Kabiru, S. Mojola, D. Béguy, C. Okigbo (2013)
Growing up at the 'margins': Concerns, aspirations, and expectations of young people living in Nairobi's slums.Journal of research on adolescence : the official journal of the Society for Research on Adolescence, 23 1
Prashanth Ak (2010)
Toward an Economy of Well-BeingScience, 329
Ryan Howell, C. Howell (2008)
The relation of economic status to subjective well-being in developing countries: a meta-analysis.Psychological bulletin, 134 4
P. Blaauw, Anmar Pretorius, Kotie Viljoen, Rinie Schenck (2020)
Adaptive Expectations and Subjective Well-being of Landfill Waste Pickers in South Africa’s Free State ProvinceUrban Forum, 31
E. Bárcena-Martín, F. García-Pardo (2019)
Multidimensional PovertyEncyclopedia of the UN Sustainable Development Goals
J. Chodosh, R. Wight (2011)
Mechanisms Linking Social Ties and Support to Physical and Mental Health
Amit Thorat, Reeve Vanneman, S. Desai, A. Dubey (2017)
Escaping and Falling into Poverty in India Today.World development, 93
C. Ratnam, V. Chandra (1996)
Sources of diversity and the challenge before human resource management in IndiaInternational Journal of Manpower, 17
(2015)
Number and Percentage of Population Below Poverty Line
J. Orley, W. Kuyken (1994)
The Development of the World Health Organization Quality of Life Assessment Instrument (the WHOQOL)
Cassondra Batz-Barbarich, L. Tay, Lauren Kuykendall, Ho Cheung (2018)
A Meta-Analysis of Gender Differences in Subjective Well-Being: Estimating Effect Sizes and Associations With Gender InequalityPsychological Science, 29
J. Neve, E. Diener, L. Tay, C. Xuereb (2013)
The Objective Benefits of Subjective Well-BeingSustainability at Work eJournal
G. Khilnani, P. Tiwari (2018)
Air pollution in India and related adverse respiratory health effects: past, present, and future directionsCurrent Opinion in Pulmonary Medicine, 24
(2019)
KoBoToolbox
E. Diener, L. Tay (2013)
A Scientific Review of the Remarkable Benefits of Happiness for Successful and Healthy Living
Publisher's Note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations
Svenja Flechtner (2014)
Aspiration Traps: When Poverty Stifles Hope
I. Eibl-Eibesfeldt
Social Behavior
PA Thoits (2011)
10.1177/0022146510395592Journal of Health and Social Behavior
Anna Maccagnan, Sam Wren-Lewis, Helen Brown, T. Taylor (2019)
Wellbeing and Society: Towards Quantification of the Co-benefits of WellbeingSocial Indicators Research, 141
Laura Nolan, David Bloom, R. Subbaraman (2017)
Legal Status and Deprivation in India's Urban Slums: An Analysis of Two Decades of National Sample Survey DataPolitical Economy - Development: International Development Efforts & Strategies eJournal
C. Freytag (2016)
All Our Kin Strategies For Survival In A Black Community
William III, Brian Gillespie (2019)
Effect SizeSAGE Research Methods Foundations
J. Tan, Michael Kraus, Nichelle Carpenter, N. Adler (2020)
The association between objective and subjective socioeconomic status and subjective well-being: A meta-analytic review.Psychological bulletin, 146 11
J. Knight, Lina Song, R. Gunatilaka (2009)
Subjective Well-being and its Determinants in Rural ChinaChina Economic Review, 20
CS Carver (2001)
10.1017/CBO9781139174794Cambridge University Press
(2020)
Satisfaction with LifeEncyclopedia of Evolutionary Psychological Science
Tineke Jonge, R. Veenhoven, L. Arends (2013)
Homogenizing Responses to Different Survey Questions on the Same Topic: Proposal of a Scale Homogenization Method Using a Reference DistributionSocial Indicators Research, 117
(2021)
GDP (currentUS$) -India
R Tourangeau (2000)
10.1017/CBO9780511819322Cambridge University Press
D. Dunn (2017)
Positive Psychology : Established and Emerging Issues
S. Alkire, J. Foster (2010)
Counting and Multidimensional Poverty Measurement
E. Diener, R. Biswas-Diener (2002)
Will Money Increase Subjective Well-Being?Social Indicators Research, 57
(2003)
Urbanisation and urban governance : Search for a perspective beyond neo - liberalism
T. Mussweiler, Shira Gabriel, G. Bodenhausen (2000)
Shifting social identities as a strategy for deflecting threatening social comparisons.Journal of personality and social psychology, 79 3
A. Khaptsova, S. Schwartz (2016)
Life Satisfaction and Value Congruence: Moderators and Extension to Constructed Socio-Demographic Groups in a Russian National SampleSocial Psychology, 47
C. Carver, M. Scheier (1998)
On the Self-Regulation of Behavior
Shannon Suldo, E. Huebner (2004)
Does life satisfaction moderate the effects of stressful life events on psychopathological behavior during adolescenceSchool Psychology Quarterly, 19
A. Furlong, A. Biggart, F. Cartmel (1996)
Neighbourhoods, Opportunity Structures and Occupational AspirationsSociology, 30
K. Edin, L. Lein (1997)
Work, welfare, and single mothers' economic survival strategiesAmerican Sociological Review, 62
Alice Isen (1993)
Positive affect and decision making.
K. Whitaker, D. Moss (1976)
Titration of human placental alkaline phosphatase with radioactive orthophosphate.Clinica chimica acta; international journal of clinical chemistry, 71 2
S. Lyubomirsky, L. King, E. Diener (2005)
The Benefits of Frequent Positive Affect: Does Happiness Lead to Success?
S Alkire (2014)
10.1016/j.worlddev.2014.01.026World Development
F. Munger (2003)
Laboring Below the Line: The New Ethnography of Poverty, Low-Wage Work, and Survival in the Global EconomyContemporary Sociology, 32
D. Schkade, Daniel Kahneman (1998)
Does Living in California Make People Happy? A Focusing Illusion in Judgments of Life SatisfactionPsychological Science, 9
Harald Strotmann, J. Volkert (2018)
Multidimensional Poverty Index and HappinessJournal of Happiness Studies, 19
(2018)
Widening gaps
Ruut Veenhoven (2008)
Healthy happiness: effects of happiness on physical health and the consequences for preventive health careJournal of Happiness Studies, 9
R. Waldinger, C. Der-Martirosian (2003)
Creating Networks for Survival and Mobility: Social Capital Among African-American and Latin-American Low-Income Mothers
Bernhard Christoph (2010)
The Relation Between Life Satisfaction and the Material Situation: A Re-Evaluation Using Alternative MeasuresSocial Indicators Research, 98
E. Diener, M. Seligman (2004)
Beyond MoneyPsychological Science in the Public Interest, 5
Anni Mäkinen, P. Hájek (2010)
Psychology of happiness
J. Moskowitz, Dikla Shmueli-Blumberg, M. Acree, S. Folkman (2012)
Positive Affect in the Midst of Distress: Implications for Role Functioning.Journal of community & applied social psychology, 22 6
C. Whelan, R. Layte, B. Maître (2004)
Understanding the mismatch between income poverty and deprivation: A dynamic comparative analysisEuropean Sociological Review, 20
P. Mateu, Enrique Vásquez, Javier Zúñiga, Franklin Ibáñez (2020)
Happiness and poverty in the very poor Peru: measurement improvements and a consistent relationshipQuality & Quantity, 54
Ritu Sharma, N. Khurana, Anna Bagrij (2019)
Satisfaction of Life of Slum Dwellers Pre- and Post- Rehabilitation in IndiaScholedge International Journal of Multidisciplinary & Allied Studies ISSN 2394-336X
S. Alkire, María Santos (2013)
Measuring Acute Poverty in the Developing World: Robustness and Scope of the Multidimensional Poverty IndexDevelopment Economics: Macroeconomic Issues in Developing Economies eJournal
AC Michalos (1985)
10.1007/BF00333288Social Indicators Research
R. Veenhoven (2004)
Happiness in Hardship
(2015)
How Does Subjective Well - being Vary Around the World by Gender and Age ?
B. Ray (2017)
Quality of life in selected slums of Kolkata: a step forward in the era of pseudo-urbanisationLocal Environment, 22
(2017)
Subjective well - being : Payoffs of being happy and ways to promote happiness
R. Biswas-Diener, E. Diener (2001)
Making the Best of a Bad Situation: Satisfaction in the Slums of CalcuttaSocial Indicators Research, 55
E. Stewart, Eric Stewart, R. Simons (2007)
The Effect of Neighborhood Context on the College Aspirations of African American AdolescentsAmerican Educational Research Journal, 44
Melissa Kearney, P. Levine (2020)
Role Models, Mentors, and Media InfluencesThe Future of Children, 30
Keith Cox (2011)
Happiness and Unhappiness in the Developing World: Life Satisfaction Among Sex Workers, Dump-Dwellers, Urban Poor, and Rural Peasants in NicaraguaJournal of Happiness Studies, 13
B. Fredrickson (2004)
The broaden-and-build theory of positive emotions.Philosophical transactions of the Royal Society of London. Series B, Biological sciences, 359 1449
(2007)
Informal support networks and the maintenance of low - wage jobs
Siddhi Sundar, Adil Qureshi, P. Galiatsatos (2016)
A Positive Psychology Intervention in a Hindu Community: The Pilot Study of the Hero Lab CurriculumJournal of Religion and Health, 55
S. Ghosal, A. Mani, Sandip Mitra (2013)
Sex Workers, Stigma and Self-Belief: Evidence from a Psychological Training Program in India
A. Michalos (1985)
Multiple discrepancies theory (MDT)Social Indicators Research, 16
(2020)
Cities and happiness: a global
L. Festinger (1954)
A Theory of Social Comparison ProcessesHuman Relations, 7
T. Robinson, A. Gorb, Robert Page (2016)
Sustainable Development GoalsWorld Social Report
Psychol Stud (July–September 2022) 67(3):281–293 https://doi.org/10.1007/s12646-022-00657-8 RESEARCH IN PROGRESS Life Satisfaction among the Poorest of the Poor: A Study in Urban Slum Communities in India 1,2 1,3 Esther Sulkers Jasmijn Loos Received: 15 July 2021 / Accepted: 10 March 2022 / Published online: 4 May 2022 The Author(s) 2022 Abstract This study investigates the level and predictors Abbreviations of life satisfaction in people living in slums in Kolkata, ES Effect size India. Participants of six slum settlements (n = 164; 91% GDP Gross domestic product female) were interviewed and data on age, gender, poverty MPI Multidimensional poverty index indicators and life satisfaction were collected. The results NGO Non-governmental organization showed that the level of global life satisfaction in this SDG Sustainable development goal sample of slum residents did not significantly differ from WHO World Health Organization that of a representative sample of another large Indian city. In terms of life-domain satisfaction, the slum residents were most satisfied with their social relationships and least satisfied with their financial situation. Global life satisfac- Introduction tion was predicted by age, income and non-monetary poverty indicators (deprivation in terms of health, educa- Over the past decades, life satisfaction has received an tion and living standards) (R 15.4%). The current study increasing amount of attention. Life satisfaction refers to supports previous findings showing that people living in the cognitive evaluation of the quality of one’s life as a slums tend to report higher levels of life satisfaction than whole (global life satisfaction), or of specific life domains one might expect given the deprivation of objective cir- (domain satisfaction) (Myers & Diener, 1995). Numerous cumstances of their lives. Furthermore, the results suggest studies have emphasized the links of life satisfaction with that factors other than objective poverty make life more, or several benefits such as health, longevity, social relation- less, satisfying. The findings are discussed in terms of ships, prosociality and productivity (de Neve et al., 2013; theory about psychological adaptation to poverty. Diener & Tay, 2012; Heintzelman & Tay, 2017; Lyubo- mirsky et al., 2005). Given its benefits, life satisfaction has Keywords Life satisfaction Poverty Urban slum become more and more relevant, both for individuals and India policymakers (Maccagnan et al., 2019). It is, therefore, not surprising that over the past decades there has been an extraordinary amount of effort put in the assessment of life satisfaction, both on the national and the individual level. Esther Sulkers and Jasmijn Loos shared first authorship. For instance, since 2005, the Gallup World Poll has col- & Esther Sulkers lected data on life satisfaction of large samples in more e.sulkers@umcg.nl than 160 countries in over 140 languages (Helliwell et al., 1 2019). This allows for between-country comparison on life Calcutta Rescue, Kolkata, West Bengal, India satisfaction as well as analysis of change in life satisfaction Department of Health Sciences, University Medical Centre within countries over time. Groningen, University of Groningen, Groningen, Netherlands Utrecht University, Utrecht, The Netherlands 123 282 Psychol Stud (July–September 2022) 67(3):281–293 The positive effects of life satisfaction highlight the percent—270 million people—of the total population in importance of improving our understanding of its ante- India is living below the poverty line (Reserve Bank of cedents and what can be done to improve it within society India, 2015), economic wealth is far out of sight for a for psychology, public health and policy makers in these significant number of people. fields. One of the most interesting questions with regard to Throughout the twentieth century distress and poverty in life satisfaction is the extent to which life satisfaction is the rural areas in India resulted in a huge influx of refugees influenced by external and material conditions versus per- and migrants into urban areas which has led cities to grow sonal factors (including the attitude towards these condi- rapidly since the 1950s (Singh, 2016). The rapid urban- tions). A more specific question is ‘‘What are the ization resulted in lack of space and acceptable housing conditions for a satisfied life: to what extent needs life to be which culminated in the emergence of slum settlements in trouble-free?’’. Available evidence shows that the average and outside the city (Ray, 2017). Although the living ratings of life satisfaction are lower in nations and people conditions in most slums are generally bad, there is sig- who are afflicted by serious hardship (e.g., war, violence nificant variation between slums for example with regard to personal adversity and loss) than in nations/people that are available facilities, identity groups (e.g., Hindu versus not. On the other hand, evidence obtained in various set- Muslim) and reported incomes (Lange, 2020). Another tings shows that people can be quite happy and can even source of variability between slums is legal status. More thrive in spite of difficult circumstances (Veenhoven, than half of all slums in India are not recognized by the 2005). These paradoxical findings make clear that there is government (Nolan et al., 2017). These slums, also known more to learn about life satisfaction, in particular in people as non-notified slums, are more deprived in access to basic confronted with serious hardship. services and living security than notified slums and people The current study has been carried out in India, which is living in these slums live under a constant threat of eviction extreme in terms of population density and wealth (Ray, 2017). This deprivation of living security may have inequality. Moreover, India is facing a large number of negative consequences. Evidence from a systematic review other social issues such as caste system, gender inequality, revealed that threat of eviction is related to lower mental child labor, illiteracy, poverty, religious conflicts, and and physical health such as depression, anxiety, psycho- more. It represents, therefore, a particularly interesting logical distress, suicide, elevated blood pressure and child setting for research on life satisfaction. This study focuses maltreatment (Vasquez-Vera et al., 2017). Even with sig- on life satisfaction of people living in a very low resource nificant variation in living security, facilities and ethical/ setting i.e., in urban slums in India where hardship is religious demographics, slums are often deprived with bounteous, which remains a vastly understudied group. respect to economic, social and living conditions (Ray, 2017) and most people would consider these places as Growth and Inequality in India unsuitable for living. When it comes to well-being, one might expect that a population of this enormous magnitude, India is one of the most culturally, linguistically, and living in these deprived circumstances, is less happy as genetically diverse countries in the world. It consists of 28 their more privileged, Indian counterparts. But are the poor states and 9 union territories, has 22 official languages and really as dissatisfied with life as one might expect them to over a thousand dialects, six major religions and over 4000 be? castes (Venkata Ratnam & Chandra, 1996). It is a country of opposites: on the one hand, India is known for its Poverty and Life Satisfaction in Urban Slum immense population and population growth, its pollution Settlements and poverty (Chandramouli, 2011; Khilnani & Tiwari, 2018; Thorat et al., 2017). On the other hand, however, it is The idea that material conditions (e.g., money) matter to a country of opportunities, where the economy and tech- happiness has inspired many scholars to explore the rela- nological development are thriving at enormous speed: tionship between income and life satisfaction (e.g., Tay India has the second biggest annual GDP growth in the et al., 2018). The results of these studies show that income world and the national GDP grew about 260 percent from contributes to life satisfaction. For instance, the World 2000 to 2019 (The World Bank, 2021). Regardless of the Happiness Report 2019 found that higher national incomes economic growth and newly achieved wealth in India, the are linked with higher life satisfaction of citizens, indi- wealth inequality in the country has increased rapidly since cating that on average, those living in richer countries are 1991. Where the wealth of Indian billionaires increased by happier than those living in poorer countries (Helliwell almost 10 times over the last decade, the poorest half of the et al., 2019). The results from within-nation studies show population saw their wealth rise by just 1 percent however that the positive correlation between income and (Himanshu, 2018). Taking into consideration that about 22 life satisfaction varies. The highest correlations between 123 Psychol Stud (July–September 2022) 67(3):281–293 283 income and life satisfaction were found in low-income The Current Research groups living in economically less developed countries. Yet, this relationship remains weak, which implies that The purpose of this study is to examine life satisfaction and income explains little of the variance in life satisfaction its predictors in the context of extreme poverty. The study is set in Kolkata which is one of the largest cities in India. (Howell & Howell, 2008). Despite the plethora of research on life satisfaction, few Out of a total population of about 4.5 million people (Government of India, 2011), almost a third of its inhabi- studies have focused on life satisfaction in people living in extreme poverty. Traditionally, poverty has been concep- tants lives in slums (Ray, 2017) showing the importance of carrying out research in this particular population. tualized as economic deprivation. Yet, since the 1980s, the definition of poverty has broadened from a monetary The current study aims to replicate the work of (Biswas- approach (measured by income only) to a multidimensional Diener & Diener, 2001) who performed a study on life approach which takes into account other factors related to satisfaction among the poorest inhabitants of Kolkata in basic needs such as housing, sanitation, and education. 2001. Their results showed that their sample, consisting of Previous studies (Bag & Seth, 2018; Ki et al., 2005) pavement dwellers, slum residents and sex workers, scored showed that a multidimensional assessment of poverty slightly negative on global life satisfaction. It is notewor- thy, however, that the level of global life satisfaction in more completely captures the phenomenon and it is now widely recognized that multidimensional poverty is a richer slum residents (which was significantly higher than in the other disadvantaged groups) almost matched the level of concept than the traditional unidimensional monetary approach (Asselin, 2009). The Multidimensional Poverty global life satisfaction in Indian students. Moreover, it was Index (MPI), constructed by (Alkire & Foster, 2011), is a found that the participants were satisfied with most of the methodology to measure poverty corresponding to the assessed life domains. These findings suggest that certain three dimensions: Health, Education and Standard of Liv- communities and cultures, although poor, may enjoy a ing (Table 1). It gathers different household-level infor- relatively high level of life satisfaction. mation with the use of ten indicators and captures whether Nearly 20 years have passed since then and during that time India has seen rapid changes. Economic growth has households suffer deprivation according to the dimensions. Most of the research on poverty and life satisfaction has combined with actions by government agencies and Non- Governmental Organizations (NGOs) to address the newly focused on the monetary approach solely, whereas the current research builds on this by including non-monetary revised target of the first Sustainable Development Goal (SDG): ‘‘to end poverty in all forms everywhere’’ (United indices of poverty. Table 1 Dimensions and indicators of the Multidimensional Poverty Index (MPI) Dimension Indicator Deprived if… Relative weight (%) Health Mortality Any child aged 5 or under has died in the family (in the last 5 years) 16.7 Nutrition The individual measured has an underweight (\ 18.5) or overweight (25 C) BMI 16.7 Education Years of No household member aged 15–45 has completed 8 years of schooling 16.7 schooling School Not all children aged 4–16 attend age-appropriate schools (classes 1–10) 16.7 attendance Standard of Electricity The household has no electricity 5.6 living Sanitation The household does not use at least ‘‘limited’’ standard sanitation facilities 5.6 Water The household does not have access to clean drinking water or clean water is [ 30 min walking 5.6 from home Housing The floor is made of dirt; the walls, roof or floor do not protect from rain, wind and sun 5.6 materials Cooking fuel The household cooks with dung, wood or charcoal 5.6 Assets The household does not own three or more of these assets: radio/speaker, TV, landline phone, basic 5.6 mobile phone, smartphone, bicycle, cycle van, computer/tablet*, motorbike*, car*, refrigerator* Based on Alkire & Santos, 2014 The starred items are counted as two as they represent a distinctly greater value 123 284 Psychol Stud (July–September 2022) 67(3):281–293 Nations, 2015). Yet, despite these efforts, the gap between and Sampling Method). Participation was voluntary and the rich and the poor has widened and still a substantial participants did not receive any financial compensation for proportion of the population lives below the poverty line their participation. The informed consent was read to (or (World Bank Group, 2020). After 20 years of change it by) all participants, dependent on whether the respondent might be time to investigate the life satisfaction of the was able to read and write. In case the respondent was extreme poor again. illiterate, the informed consent was explained verbally, and The current study focuses on the level and determinants a literate family member was asked to sign on behalf of the of life satisfaction of people living in slums in Kolkata. In participant, or a thumbprint was obtained from the line with the study by Biswas-Diener and Diener (2001) the respondent. assessment of global life satisfaction will be complemented with measures of life-domain satisfaction (e.g., income Slum Selection and Sampling Method satisfaction, health satisfaction). What is new is that the study does not solely focuses on monetary poverty as a A slum area is defined broadly in line with the 1997 Indian predictor of life satisfaction, but also takes the explanatory Compendium of Environment Statistics as groups of 25 or power of multidimensional aspects of poverty into account. more poor-quality dwellings (Kundu, 2003). The slums to Last, as 59% of the slums in India are non-notified (Nolan be sampled were all part of the operational area of Calcutta et al., 2017), the role of fear of eviction as a predictor of Rescue and were distributed across the city. Part of the global life satisfaction will be explored. slum settlements was unregistered and part was registered The specific aims of this study are: (legal). The slums varied in population size: based on the average household size and the number of households, the 1. To document the level of life satisfaction (global and estimated population numbers vary between 132 (Barana- domain-specific) of people living in urban slums in gar) and 1107 (Local Bustee). Following Kundu’s (Kundu, Kolkata, India. 2003) study on slums in Kolkata, a systematic sampling 2. To test whether there is a difference between the method was used. According to this method, an equal different domain satisfactions (social relationships, distribution of 15 percent of the households is considered physical environment, physical health, psychological as a minimum sample size. The current study aimed at health and financial situation) in people living in urban sampling/interviewing 20 percent of the slum or 30 slums in Kolkata, India. households, whichever was bigger. In order to get an equal 3. To compare the level of global life satisfaction of slum sample across the whole slum, the area was mapped and residents with global life satisfaction measured in a households were counted prior to data collection. Every representative sample from the general population of fifth household (20 percent) was asked to participate. Data another large Indian city (Delhi) as measured by the were collected during the day and the structured interviews Gallup Poll. lasted between 25 and 50 min. Interviews were conducted 4. To examine age, gender, poverty indicators (monetary, in the participant’s home with the researcher and a trans- multidimensional) and fear of eviction as predictors of lator, who was fluent in English, Bengali and Hindi. The global life satisfaction. data were recorded on smartphones in (KoBoToolBox, 2019), an online data collection system for challenging environments. Method Measures Participants and Procedure Life Satisfaction Participants Global life satisfaction was assessed using Cantril’s ladder The present study, conducted by Calcutta Rescue in 2019, (Cantril, 1965). Respondents were asked to evaluate their is part of a larger cross-sectional research project on pov- satisfaction with their lives as a whole using the Ladder erty in urban slums (Lange, 2020). Calcutta Rescue is a Scale; an illustration of a ladder which represents their life, medium-sized NGO that focuses on supporting the slum 1 being their worst possible life and 8 being their best communities in Kolkata which are most poorly served by possible life. Participants’ domain satisfaction was mea- the local and national government. Participants were eli- sured with 5 single items assessing participants’ satisfac- gible for this study if they were 18 years and older and tion with different life domains: social relationships, resided in one of the six different slum settlements in the physical environment, physical health, psychological urban area of Kolkata in India (see Sect. Slum Selection health and financial situation. The items were derived from 123 Psychol Stud (July–September 2022) 67(3):281–293 285 the WHO questionnaire on Quality of Life (WHOQoL The Greenhouse–Geisser adjustment was used to correct Group, 1994) (e.g., In general, how satisfied are you with for violation of assumption of sphericity, which is common your social relationships) using a 5-point Likert scale in ANOVA within-subject analyses. Effect sizes (ES) were format. The one-to-five rating was depicted on a piece of based on Cohen’s g (ES: 0.01 = small, 0.06 = medium, paper ranging from an extreme frown (1) to an extreme 0.16 or larger = large) (Draper, 2011). To address the third smile (5), similar to earlier research by Biswas-Diener and research aim we compared the sample mean with the mean Diener (Biswas-Diener & Diener, 2001). Higher scores life satisfaction score of a representative sample of the reflect higher levels of life satisfaction. general population in Delhi as measured by the Gallup Poll (De Neve & Krekel, 2020). We first homogenized the Predictors of Life Satisfaction responses for the Cantril’s ladder of our study (measured on a 1–8 response format) with those obtained by the Socio-Demographic Variables Socio-demographic vari- Gallup Poll (the Cantril’s ladder in the Gallup Poll uses a ables included age and gender (female = 0, male = 1). 0–10 response format) using the linear stretch method (de Jonge et al., 2014). The one sample t test was used to Poverty Poverty was measured in two ways: using both determine whether the Kolkata slum sample mean signifi- monetary (income) and non-monetary approaches (MPI). cantly differed from the Delhi general population mean. Effect sizes were based on Cohen’s d (ES: 0.2 = small, Income Monthly income per capita was calculated based 0.5 = medium, and 0.8 or larger = large; Draper, 2011). on the monthly household income divided by the number The fourth research aim was tested by applying hierarchi- cal multiple regression analysis (method enter) in which of household members. age and gender were entered in the first step, income per Multidimensional Poverty Table 1 illustrates the assess- capita in the second step and the MPI and living security in ment of multidimensional poverty based on the Multidi- the third step. Effect sizes were based on R (1% small, 9% mensional Poverty Index (Alkire & Santos, 2014; UNDP, medium, 25% large; Draper, 2011). Statistical significance 2020). The MPI identifies deprivations at the household (alpha) was assessed at the 0.05 level. and individual level across three dimensions and 10 indi- cators: Health (child mortality, nutrition), Education (years of schooling and school enrollment) and Standard of Liv- Results ing (water, sanitation, electricity, cooking fuel, floor, assets). As shown in the table each of the three dimensions Sample Characteristics is equally weighted (one third each), though the individual indicators receive different weights. Weights are thus The characteristics of the sample (N = 164) are described applied to each of the indicators, which are then summed in Table 2. As shown in the table, the sample was pre- up to a total MPI score. The total MPI score for each dominantly female (90.9%). Almost two-thirds of the person lies between 0 and 1. A higher score represents a sample were literate and from a Hindu background. The higher level of multidimensional deprivation. participants were long-term residents who had, themselves or their families, lived in the slum settlement for decades Fear of Eviction In addition to the above-mentioned (not shown in the table). Almost two-third of the house- MPI-indicators, information was gathered about whether holds was deprived in living security (64.6%). Most par- the participant experienced a fear of being evicted (0 = no, ticipants were able to meet daily needs. The results showed 1 = yes). that the participants were most deprived in terms of housing, assets and living security. Statistical Analysis The Level of Life Satisfaction in Kolkata Slum An a priori power analysis was conducted through G power Residents (Faul et al., 2009)(a = 0.05, power = 0.80, medium effect sizes) to calculate the required sample size. Descriptive The descriptive statistics for global and domain-specific statistics (medians, means, standard deviations, percent- life satisfaction (research aim 1) are presented in Table 3. ages) were used to describe the data and to address the first With regard to research aim 2, the results of the repeated research aim. Repeated measures analysis of variance measures ANOVA with a Greenhouse–Geisser correction (ANOVA) was used to test the significance of the mean demonstrated a significant difference between the mean differences between the five life domains (research aim 2). satisfaction levels across the different life domains (F(3.61, 580.69) = 21.83, p = 0.000, partial g = 0.12). 123 286 Psychol Stud (July–September 2022) 67(3):281–293 Table 2 Sample characteristics (n = 164) Median Range % (n) Demographics Age 32.50 18–85 Gender (% female) 90.9% (149) Educational level No education 36.0% (58) Lower primary (class 1–5) 25.5% (41) Upper primary (class 6–8) 19.3% (31) Secondary (class 9–10) 11.8% (19) Class 11–12 3.1% (5) Higher education 4.3% (7) Religion Hindu 63.4% (104) Muslim 36.0% (58) Other 0.6% (1) Household size 5 2–15 Monetary indicators of poverty Monthly income (in Rs) 7200 300 0–3000 76,100 15.2% (24) 3001–6000 30.4% (48) 6001–9000 17.7% (28) 9001 and above 36.7% (58) Monthly income per capita (in Rs) 1500 Ability to meet daily needs 25–25,367 Has difficulty in meeting daily needs 13.4% (22) Has just enough, no extra things 36.6% (60) Can easily meet daily needs 34.1% (56) Is able to save some money 15.9% (26) Non-monetary indicators of poverty Multidimensional poverty index (MPI) 22.30 0–72 Deprived in health: composite score 1 0–2 Nutrition 46.5% (74) Child mortality 5.5% (7) Deprived in education: composite score 0 0–2 Deprived of access to education adults 38.1% (59) Deprived of access to education children 4–16 13.1% (16) Deprived in standards of living: composite score 2 0–6 Deprived in water 20.1 (33) Deprived in clean sanitation 11.0 (18) Deprived in suitable housing materials 71.7 (114) Deprived in clean cooking fuel 36.2 (59) Deprived in electricity 22.7 (37) Deprived in assets 54.3 (88) Deprived in living security (fear of eviction) 64.6 (106) 123 Psychol Stud (July–September 2022) 67(3):281–293 287 Table 3 Descriptive statistics for life satisfaction measured in Kolkata’s slum population (M = 4.27, SD = 3.19) did not significantly differ from the average global Variable Mean (SD) Min–Max life satisfaction score of 4.01 of people living in Delhi (De Global life satisfaction 4.27 (3.19) 0–10 Neve & Krekel, 2020). The difference, 0.26, 95% CI [-0.24 Domain satisfaction to 0.75], t(160) = 1.02, p = 0.31, represented an effect size Satisfaction with financial situation 2.57 (1.16) 1–5 of d = 0.08. Satisfaction with living environment 2.90 (1.28) 1–5 Satisfaction with social relationships 3.60 (1.12) 1–5 Prediction of Life Satisfaction Satisfaction with physical health 3.18 (1.31) 1–5 Satisfaction with psychological health 3.16 (1.27) 1–5 Table 4 shows the relationships between (non)monetary indices of poverty, fear of eviction and global life satis- faction (controlled for age and gender) (research aim 4). The results of the bivariate analyses (presented in the A Bonferroni-adjusted post hoc analysis revealed that the second column of the table) revealed that lower age, higher participants reported significantly lower satisfaction in the income, lower levels of multidimensional deprivation (MPI financial domain than in the other life domains, whereas scores) and lower scores on fear of eviction were associ- their ratings of satisfaction in the social domain were sig- ated with higher levels of global life satisfaction. When nificantly higher than those of the other life domains (all entered in the multivariate model (presented in columns p \ 0.05). The satisfaction levels of the living environment 3–5 of the table) the association between fear of eviction domain and health domains (physical and psychological) and global life satisfaction was no longer significant. The did not significantly differ from each other (all p’s [ 0.05). MPI (reflecting the non-monetary approach to poverty) accounted for additional variance (above income). The full Life Satisfaction: Kolkata Slum Residents vs. model explained 15.4% of the variance (F(5, 150) = 5.46; the General Population p = 0.00) in global life satisfaction. Regarding research aim 3, the results of the one sample t test showed the mean global life satisfaction score Table 4 Hierarchical multiple regression analysis of factors contributing to life satisfaction Life satisfaction (global) Single predictor Multiple predictors Multiple predictors Multiple predictors Step 1 Step 2 Step 3 2 2 2 rp b p D R b p D R b p D R Demographics 4.4% 5.6% 5.4% Age - .21 .01 - .21 .01 - .19 .02 - .19 .01 Gender - .06 .48 - .06 .55 - .07 .35 - .11 .17 Monetary poverty Income per capita .24 \ .001 .24 \ .001 .22 \ .001 Non-monetary poverty MPI - .22 .01 - .17 .04 Deprived in health - .05 .61 Deprived in education - .16 .05 Deprived in SoL - .31 \ .001 Fear of eviction - .19 .02 - .11 .20 Standard of Living 123 288 Psychol Stud (July–September 2022) 67(3):281–293 residents and those with higher incomes and lower scores Discussion on the MPI reported higher levels of global life satisfac- This study investigated the level and predictors of life tion. Our findings regarding the relationship between age and global life satisfaction related to those reported by satisfaction of people living in slums in Kolkata, India. In line with previous research, it was found that slum resi- (Cox, 2012) who examined age as a predictor of life sat- isfaction in poor populations in Nicaragua and data from dents were less dissatisfied with their lives than one would have held given the dire living conditions of these people. the Gallup World Poll (Fortin et al., 2015). Our results are in line with previous work which emphasized the role of For the prediction of global life satisfaction, income (monetary poverty) was complemented with the Multidi- income in life satisfaction (Whitaker & Moss, 1976). Moreover, the income-life satisfaction relationship in this mensional Poverty Index (non-monetary poverty) and fear study was comparable to the average r effect size of 0.28 of eviction. The results showed that not only income but computed for low-income samples in developing countries also non-monetary indices such as education, living stan- in Howell and Howell’s (2008) meta-analysis. The current dards and fear of eviction are important correlates of life satisfaction of people living in slums. study also confirms the results of research reporting a negative relationship between the MPI and life satisfaction The level of global life satisfaction observed in this study was comparable to those measured in a representa- in people living in the poorest districts of Peru (Mateu et al., 2020) and India (Strotmann & Volkert, 2018). tive sample from Delhi, another large metropole in India. Although counterintuitive, our finding of a relatively high Overall, data from several studies suggest that slum residents in developing countries, such as India, are more level of life satisfaction in a marginalized group is not new. satisfied with their lives than one would expect based on For example, in a study among the poorest of the poor in their living conditions. This contradicts the common-sense South Africa, it was found that landfill waste pickers scored belief that poor people are unhappy by definition. Such higher on life satisfaction than the national average judgment is, however, an illustration of the ‘‘focusing (Blaauw et al., 2020). The same study found that there was illusion’’ (Schkade & Kahneman, 1998) which has received a significant group of waste pickers who were very satisfied with their lives. Our findings also resemble those reported a lot of attention in the literature on life satisfaction. The ‘‘focusing illusion’’ takes place when individuals exag- by Biswas-Diener and Diener (2001) and Cox (2012) who found slightly positive global life satisfaction in urban slum gerate the importance of a single factor (e.g., living cir- cumstances or material wealth) on well-being. Going residents and dump dwellers in Kolkata, India and Mana- gua, Nicaragua, respectively. beyond the stereotype that poverty equates unhappiness may provide a different picture. Research suggests that With regard to domain satisfaction, the slum residents were fairly satisfied with three of the five life domains people living in poverty may consider different aspects of life important for their well-being than people from a more assessed in this study i.e., their social relationships and affluent background. For example, extremely poor Nicar- health (physical and psychological). They were least sat- isfied with their financial situation and physical environ- aguan garbage dump dwellers in the study by (Vasquez- Vera et al., 2017) reported that their happiness did not ment. Similar findings have been reported in previous studies addressing domain satisfaction in poor populations emerge from job status or income, but rather from mean- ingful interactions and relationships with others. (Biswas-Diener & Diener, 2001; Cox, 2012; Sharma et al., 2019). Various scholars have emphasized the importance Moreover, the explanatory power of objective poverty (as measured by income and the MPI) for life satisfaction of social ties for well-being (Diener & Seligman, 2004), especially in poor populations (Boswell & Stack, 1975; was limited. This is in line with a vast array of research ´ showing that objective life conditions do explain only a Domınguez & Watkins, 2003; Henly, 2007). Social con- minor part of inter-individual differences in life satisfaction nectedness has been associated with access to various (Argyle, 2013; Diener & Biswas-Diener, 2002). How forms of social support and cognitive processes associated hardship is perceived on the other hand, may be of much with subjective well-being such as life satisfaction, enhanced self-esteem, self-worth, purpose and meaning in bigger importance for the appraisal of one’s life (Veen- hoven, 2005). Poverty is a subjective feeling, which means life (Thoits, 2011). Social ties may serve as a private safety net, a poor family can fall back on in times of need (Edin & that people defined as poor by objective standards do not necessarily have to feel poor. Indeed, results from a recent Lein, 1997). In terms of prediction, higher levels of life satisfaction meta-analysis (Tan et al., 2020) indicate that life satisfac- tion has a stronger link to subjective socio-economic status were related to age, income and deprivation. Due to shared variance with the MPI, fear of eviction did not explain than objectively measured income or education. Our findings could be interpreted in the light of the unique variance in life satisfaction. Specifically, younger human capacity to adapt to environmental demands. 123 Psychol Stud (July–September 2022) 67(3):281–293 289 Adaptability is a self-regulatory resource which allows beyond the scope of personal control (Blanton et al., 2000; individuals to adjust to good and bad phenomena by Leach & Smith, 2006; Mussweiler et al., 2000). Unfortu- altering their standards, thoughts, behaviors and emotions nately, such strategies may also lead to aspiration traps to the requirements of situations at hand. Adaptability can where people under-aspire in occupational and educational help prevent or mitigate the negative impact of challenge goals, thereby contributing to the intergenerational trans- and adversity on well-being (Carver & Scheier, 2001). mission of poverty (Flechtner, 2014). Following the multiple discrepancies theory (Michalos, This study is one of the few examining life satisfaction 1985), life satisfaction relates to the discrepancy between in people living in a very low resource setting such as an what one has and what one wants (desire discrepancy) and urban slum in India. Other strengths are the relatively large what relevant others have (social comparison discrepancy) sample size and the inclusion of non-monetary indicators (Brown et al., 2009). Perceived negative discrepancies of objective poverty as predictors of life satisfaction. The between one’s standards and one’s actual situation have a use of non-monetary poverty indices such as the MPI in life negative impact on life satisfaction. In the context of slums, satisfaction research is relatively new. This approach is in perceived discrepancies between what one has (slum line with new perspectives on measuring the material sit- dwelling) and what one wants (a decent house), or what uation (combining income with a direct measure such as a one has (no income) and what relevant others have (im- deprivation index) (Christoph, 2010). Our results (showing provement in daily wage) could be a source of dissatis- an incremental contribution by the MPI) suggest the added faction with life. Effects of perceived negative value of combining monetary- (income) and non-monetary discrepancies can be counterbalanced, however, by self- measures (the MPI) when analyzing the relationship regulatory discrepancy reducing processes such as choos- between the material situation and life satisfaction. ing a relevant reference group for social comparison and Nevertheless, some limitations merit attention. First of lowering aspirations (Carver & Scheier, 2001). all, this study only included objective measures of poverty. Regarding social comparison, it has been found that The addition of subjective measures of poverty (the indi- people have a natural tendency to compare themselves with vidual’s perception of his/her financial and material situa- others (Festinger, 1954), in particular with relevant refer- tion) could have offered a more complete picture of the ence groups such as people with a similar ethnicity, poverty-life satisfaction relationship. Secondly, the cross- background or occupation (Khaptsova & Schwartz, 2016). sectional design of this study failed to establish causality. In the case of low status or minority groups, several studies Thirdly, because the interviews were conducted in person found that exposure to a successful referent from a low- and in the participants’ homes, which gave the possibility status group is more pleasant and meaningful than expo- onlookers or family members meandering in earshot of the survey being asked, the research design could have been sure to a referent from a high-status group (Blanton et al., 2000; Leach & Smith, 2006; Mussweiler et al., 2000). This prone to social desirability bias (Tourangeau et al., 2000). highlights the value of identifying local champions (e.g., Finally, the fact that the sample was predominantly female former classmates who have excelled in school or sports) to was most likely caused by the fact that interviews were serve as role models for young people living in low conducted during the day when women were more typi- resource settings (Kearney & Levine, 2020). cally at home. This may limit the generalization of the Lowering aspirations is another discrepancy reducing results. However, a recent meta-analysis of 281 samples mechanism. This has been observed in deprived neigh- (Batz-Barbarich et al., 2018) did not show significant borhoods including two Kenyan urban slums (Kabiru et al., gender differences in life satisfaction. In addition, the study 2013) where the constraints of the environment had a of Biswas-Diener and Diener (2001) which was conducted leveling effect on young people’s occupational and edu- in a comparable sample in Kolkata showed no significant cational aspirations. Similar findings have been reported differences in life satisfaction between men and women. for youth in disadvantaged neighborhoods in the US and This gives us no reason to believe that the unequal sample Scotland (Furlong et al., 1996; Stewart et al., 2007). In the sizes in gender influence outcomes in life satisfaction in the case of Kolkata, it is possible that slum residents compare current study. themselves mostly to people within their community and The results of the present study highlight the need for set their aspirations and goals accordingly. Indeed, research further research. A mixed methods design adding qualita- has found that expectations of life and oneself are influ- tive approaches to the assessment of life satisfaction could enced by one’s relative position and social norms within illuminate a more holistic and contextual understanding of one’s community (Knight et al., 2009). Both social com- slum residents’ perceptions and experiences in daily life parison and lowering aspirations are self-protective strate- (Camfield et al., 2009). Secondly, in addition to measures gies that may help to ensure subjective well-being of objective poverty, further research should also include in situations in which the remediation of disadvantage is subjective indices of poverty as this accounts for a better 123 290 Psychol Stud (July–September 2022) 67(3):281–293 prediction of life satisfaction compared to objective pov- individual difference factors when measuring the impact of erty measures (Tan et al., 2020). Lastly, it would be poverty on life satisfaction. valuable to learn more in-depth about psychological pro- Acknowledgements The authors thank Mr. Jaydeep Chakraborty, cesses underlying life satisfaction of people living in slums Chief Executive Officer at Calcutta Rescue, the Calcutta Rescue such as social comparison and aspirations. Research Collaborative and volunteer researchers Eleo Tibbs (UK), In terms of clinical practice, practical assistance such as Maurice Lange (UK), and Ezra Spinner (NL) for their contributions to slum upgrading should be complemented with efforts to the foundation of this study. Debuprasad Chakraborty & Ananya Chatterjee (CR, India), and the interns (Madhubanti Talukdar, improve the life satisfaction of slum residents. Research Annesha Dasgupta, Amrita Mukherjee, Sagnik Pramanick, Varbi highlights the benefits of a positive mindset including a less Mridha) are thanked for all their help with data collection. pronounced stress response (Smyth et al., 2017), better role functioning (Moskowitz et al., 2012) and more efficient Author contributions Both authors (ES and JL) contributed equally to the realization of the study and the manuscript i.e., study con- decision making (Isen, 2000). This has been explained by ception, study design, data collection, data analysis, data interpreta- research showing that a positive mental state helps building tion and writing were performed by both authors. The draft coping resources by broadening the individual’s attention manuscript was critically revised. Both authors read and approved the and action repertoire (Fredrickson, 2004). Other research final manuscript. The authors agree to be accountable for all aspects of the work in ensuring that questions related to the accuracy or has shown that the presence of a positive mindset buffers integrity of any part of the work are appropriately investigated and against the negative psychological impact of adversity resolved. (Suldo & Huebner, 2004; Veenhoven, 2008). Psychological interventions aimed at improving the mental health of Funding There was no specific funding for this research project. people living in slums should thus not exclusively focus on the reduction in problems but also on the enhancement of Availability of data and material Open ICPSR, https://www. openicpsr.org/openicpsr/. https://doi.org/10.3886/E136141V1 positive mental states. The few studies that have examined the effect of individual and group-based positive psychol- Code availability IBM SPSS Statistics for Windows, version 26.0 ogy interventions in disadvantaged populations in devel- oping countries show promising results, including a large Declarations increase in life satisfaction, positive affect, positive Conflict of interest The authors declare that they have no conflicts of thoughts, generalized self-efficacy and reductions in self- interest. reported symptoms of depression and negative affect (Ghosal et al., 2013; Sundar et al., 2016). Efforts to Ethics approval The study was performed in accordance with the improve the life satisfaction of the slum residents may thus ethical standards laid down in the 1964 Declaration of Helsinki and its later amendments. be worthwhile to consider, as it may help them deal with the harsh reality of life. Consent to participate and consent for publication Written informed consent was obtained from the participants. The data were anonymized before analysis and publication. Conclusion Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, The common belief that poor people are unhappy by def- adaptation, distribution and reproduction in any medium or format, as inition is challenged by the results of this study on life long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate satisfaction in urban slums in India. The findings of the if changes were made. The images or other third party material in this study show that the slum residents in Kolkata scored article are included in the article’s Creative Commons licence, unless comparable to the general population in terms of global life indicated otherwise in a credit line to the material. If material is not satisfaction (evaluation of the quality of life as a whole) included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted and that they found satisfaction in other life domains than use, you will need to obtain permission directly from the copyright finances and their living environment. Moreover, in terms holder. To view a copy of this licence, visit of prediction, objective poverty indicators explained only a http://creativecommons.org/licenses/by/4.0/. minor part of the variance in life satisfaction. This suggests that it is not correct to determine a person’s life satisfaction on the basis of income and other socioeconomic variables References alone and that other factors such as the appraisal of one’s Alkire, S., & Foster, J. (2011). Counting and multidimensional life should be taken into account when examining life poverty measurement. Journal of Public Economics, 95(7–8), satisfaction. A suggestion for future studies is to include 476–487. https://doi.org/10.1016/j.jpubeco.2010.11.006 measures of subjective poverty and other personal 123 Psychol Stud (July–September 2022) 67(3):281–293 291 Alkire, S., & Santos, M. E. (2014). Measuring acute poverty in the de Neve, J., Diener, E., Tay, L., & Xuereb, C. (2013). The objective developing world: Robustness and scope of the multidimensional benefits of subjective well-being. CEP Discussion Paper No poverty index. World Development. https://doi.org/10.1016/ 1236, 1236, 1–35. http://eprints.lse.ac.uk/51669/1/dp1236.pdf j.worlddev.2014.01.026 de Neve, J.-E., & Krekel, C. (2020). Cities and happiness: a global Argyle, M. (2013). The psychology of happiness. Routledge. ranking and analysis. The World Hapiness Report 2020, https://www.cis.org.au/app/uploads/2015/04/images/stories/ pp. 46–65. https://worldhappiness.report/ policy-magazine/2002-autumn/2002-18-1-richard-tooth.pdf Diener, E., & Tay, L. (2012). A scientific review of the remarkable Asselin, L.-M. (2009). Analysis of Multidimensional Poverty (Vol. benefits of happiness for successful and healthy living. Happi- 7). Springer New York. https://doi.org/10.1007/978-1-4419- ness: Transforming the Development Landscape, 90–117. 0843-8 http://www.bhutanstudies.org.bt/publicationFiles/ Bag, S., & Seth, S. (2018). Does it matter how we assess standard of OccasionalPublications/Transforming Happiness/Chapter 6 A living? Evidence from Indian slums comparing monetary and Scientific Review.pdf multidimensional approaches. Social Indicators Research. Diener, E., & Biswas-Diener, R. (2002). Will money increase https://doi.org/10.1007/s11205-017-1786-y subjective well-being? Social Indicators Research, 57(2), Batz-Barbarich, C., Tay, L., Kuykendall, L., & Cheung, H. K. (2018). 119–169. A meta-analysis of gender differences in subjective well-being: Diener, E., & Seligman, M. E. P. (2004). Beyond money: Toward an Estimating effect sizes and associations with gender inequality. economy of well-being. Psychological Science in the Public Psychological Science, 29(9), 1491–1503. https://doi.org/ Interest, 5(1), 1–31. https://doi.org/10.1111/j.0963-7214.2004. 10.1177/0956797618774796 00501001.x Biswas-Diener, R., & Diener, E. (2001). Making the best of a bad Domı´nguez, S., & Watkins, C. (2003). Creating Networks for situation: Satisfaction in the slums of Calcutta. Social Indicators Survival and Mobility: Social Capital Among African-American Research, 55(3), 329–352. https://doi.org/10.1023/A:10109050 and Latin-American Low-Income Mothers. Social Problems, 29386 https://doi.org/10.1525/sp.2003.50.1.111 Blaauw, P., Pretorius, A., Viljoen, K., & Schenck, R. (2020). Draper, S. (2011). Effect size. https://www.psy.gla.ac.uk/*steve/ Adaptive expectations and subjective well-being of landfill waste best/effect.html pickers in South Africa’s free state province. Urban Forum. Edin, K., & Lein, L. (1997). Work, welfare, and single mothers’ https://doi.org/10.1007/s12132-019-09381-5 economic survival strategies. American Sociological Review, Blanton, H., Crocker, J., & Miller, D. T. (2000). The effects of in- 62(2), 253–266. https://doi.org/10.2307/2657303 group versus out-group social comparison on self-esteem in the Faul, F., Erdfelder, E., Buchner, A., & Lang, A.-G. (2009). Statistical context of a negative stereotype. Journal of Experimental Social power analyses using G*Power 3.1: Tests for correlation and Psychology. https://doi.org/10.1006/jesp.2000.1425 regression analyses. Behavior Research Methods. https://doi.org/ Boswell, D., & Stack, C. B. (1975). All our kin: strategies for survival 10.3758/BRM.41.4.1149 in a black community. Man, 10(1), 160. https://doi.org/ Festinger, L. (1954). A theory of social comparison processes. Human 10.2307/2801228 Relations. https://doi.org/10.1177/001872675400700202 Brown, K. W., Kasser, T., Ryan, R. M., Alex Linley, P., & Orzech, K. Flechtner, S. (2014). Aspiration traps: When poverty stifles hope. (2009). When what one has is enough: Mindfulness, financial Inequality in Focus, 2(4), 1–4. desire discrepancy, and subjective well-being. Journal of Fortin, N., Helliwell, J., & Wang, S. (2015). How Does Subjective Research in Personality. https://doi.org/10.1016/j.jrp.2009. Well-being Vary Around the World by Gender and Age? In 07.002 Helliwell JF, Layard R, & Sachs J (Eds.), World Happiness Camfield, L., Crivello, G., & Woodhead, M. (2009). Wellbeing Report 2015 (2015th ed., pp. 42–75). Earth Institute, Columbia research in developing countries: reviewing the role of qualita- University. https://www.academia.edu/download/46704794/ tive methods. Social Indicators Research. https://doi.org/ WHR15.pdf#page=44 10.1007/s11205-008-9310-z Fredrickson, B. L. (2004). The broaden–and–build theory of positive Cantril, H. (1965). The pattern of human concerns. The British emotions. Philosophical Transactions of the Royal Society of Journal of Sociology, 18, 212. London. Series B: Biological Sciences. https://doi.org/10.1098/ Carver, C. S., & Scheier, M. F. (2001). On the Self-Regulation of rstb.2004.1512 Behavior. Cambridge University Press. https://doi.org/10.1017/ Furlong, A., Biggart, A., & Cartmel, F. (1996). Neighbourhoods, CBO9781139174794 Opportunity Structures and Occupational Aspirations. Sociology, Chandramouli, C. (2011). Census of India 2011. Provisional Popu- https://doi.org/10.1177/0038038596030003008 lation Totals. New Delhi: Government of India. https://www. Ghosal, S., Mani, A., & Mitra, S. (2013). Sex Workers, Stigma and censusindia.gov.in/2011-prov-results/data_files/India/paper_cont Self-Belief: Evidence from a Psychological Training Program in entsetc.pdf India. https://www.isid.ac.in/*epu/acegd2014/papers/Sanchari Christoph, B. (2010). The relation between life satisfaction and the Roy.pdf material situation: A re-evaluation using alternative measures. Government of India. (2011). Census of India. Final Population Social Indicators Research, 98(3), 475–499. https://doi.org/ Tables. 10.1007/s11205-009-9552-4 Heintzelman, S. J., & Tay, L. (2017). Subjective well-being: Payoffs Cox, K. (2012). Happiness and unhappiness in the developing world: of being happy and ways to promote happiness. Positive life satisfaction among sex workers, dump-dwellers, urban poor, Psychology Established and Emerging Issues. https://doi.org/ and rural peasants in Nicaragua. Journal of Happiness Studies. 10.4324/9781315106304 https://doi.org/10.1007/s10902-011-9253-y Helliwell, J. F., Layard, R., & Sachs, J. D. (2019). World Happness de Jonge, T., Veenhoven, R., & Arends, L. (2014). Homogenizing Report. Oecd, March, 20. https://s3.amazonaws.com/happiness- responses to different survey questions on the same topic: report/2019/WHR19.pdf Proposal of a scale homogenization method using a reference Henly, J. R. (2007). Informal support networks and the maintenance distribution. Social Indicators Research, 117(1), 275–300. of low-wage jobs. In F. Munger (Ed.), Laboring Below The Line: https://doi.org/10.1007/s11205-013-0335-6 The New Ethnography of Poverty, Low-Wage Work, and Survival in the Global Economy (pp. 179–203). Russell Sage 123 292 Psychol Stud (July–September 2022) 67(3):281–293 Foundation. https://www.jstor.org/stable/https://doi.org/10.7758/ Myers, D. G., & Diener, E. (1995). Who is happy? Psychological 9781610444163 Science, 6(1), 10–19. https://doi.org/10.1111/j.1467-9280. Himanshu. (2018). Widening gaps, India Inequality Report 2018. 1995.tb00298.x https://www.oxfamindia.org/sites/default/files/WideningGaps_ Nolan, L. B., Bloom, D. E., & Subbaraman, R. (2017). Legal status IndiaInequalityReport2018.pdf and deprivation in India’s Urban Slums: An analysis of two Howell, R. T., & Howell, C. J. (2008). The relation of economic decades of national sample survey data. SSRN, 10639. status to subjective well-being in developing countries: A meta- https://www.econstor.eu/bitstream/10419/161262/1/dp10639.pdf analysis. Psychological Bulletin. https://doi.org/10.1037/0033- Ray, B. (2017). Quality of life in selected slums of Kolkata: a step 2909.134.4.536 forward in the era of pseudo-urbanisation. Local Environment. Isen, A. M. (2000). Positive Affect and Decision Making, Handbook https://doi.org/10.1080/13549839.2016.1205571 of emotions, M. Lewis & J. Haviland-Jones Ed, 417–435. Reserve Bank of India. (2015). Number and Percentage of Population https://psycnet.apa.org/record/1993-98937-013 Below Poverty Line. https://www.rbi.org.in/scripts/Publications Kabiru, C. W., Mojola, S. A., Beguy, D., & Okigbo, C. (2013). View.aspx?id=16603 Growing Up at the ‘‘Margins’’: Concerns, aspirations, and Schkade, D. A., & Kahneman, D. (1998). Does living in california expectations of young people living in Nairobi’s slums. Journal make people happy? A Focusing Illusion In Judgments Of Life of Research on Adolescence. https://doi.org/10.1111/j.1532- Satisfaction. Psychological Science, https://doi.org/10.1111/ 7795.2012.00797.x 1467-9280.00066 Kearney, M. S., & Levine, P. B. (2020). Role models, mentors, and Sharma, R., Khurana, N., & Bagrij, A. (2019). Satisfaction of life of media Influences. The Future of Children, 30(1), 83–106. slum dwellers pre- and post- rehabilitation in India. Scholedge Khaptsova, A., & Schwartz, S. H. (2016). Life satisfaction and value International Journal of Multidisciplinary & Allied Studies congruence. Social Psychology. https://doi.org/10.1027/1864- https://doi.org/10.19085/journal.sijmas051001 9335/a000268 Singh, H. (2016). Increasing rural to urban migration in India: A Khilnani, G. C., & Tiwari, P. (2018). Air pollution in India and related challenge or an opportunity. International Journal of Applied adverse respiratory health effects: Past, present, and future Research, 2(4), 447–450. directions. Current Opinion in Pulmonary Medicine, 24(2), Smyth, J. M., Zawadzki, M. J., Juth, V., & Sciamanna, C. N. (2017). 108–116. https://doi.org/10.1097/MCP.0000000000000463 Global life satisfaction predicts ambulatory affect, stress, and Ki, J. B., Faye, S., & Faye, B. (2005). Multidimensional poverty in cortisol in daily life in working adults. Journal of Behavioral Senegal: A non-monetary basic needs approach. SSRN Elec- Medicine. https://doi.org/10.1007/s10865-016-9790-2 tronic Journal. https://doi.org/10.2139/ssrn.3173246 Stewart, E. B., Stewart, E. A., & Simons, R. L. (2007). The effect of Knight, J., Song, L., & Gunatilaka, R. (2009). Subjective well-being neighborhood context on the college aspirations of African and its determinants in rural China. China Economic Review, American Adolescents. American Educational Research Jour- 20(4), 635–649. https://doi.org/10.1016/j.chieco.2008.09.003 nal. https://doi.org/10.3102/0002831207308637 KoBoToolBox. (2019). KoBoToolbox. https://www.kobotoolbox.org/ Strotmann, H., & Volkert, J. (2018). Multidimensional poverty index Kundu, A. (2003). Urbanisation and urban governance: Search for a and happiness. Journal of Happiness Studies. https://doi.org/ perspective beyond neo-liberalism. Economic and Political 10.1007/s10902-016-9807-0 Weekly, 38(29), 3079–3087. Suldo, S. M., & Huebner, E. S. (2004). Does life satisfaction moderate Lange, M. (2020). Multidimensional poverty in Kolkata’s slums: the effects of stressful life events on psychopathological Towards data driven decision making in a medium-sized NGO. behavior during adolescence? School Psychology Quarterly, Journal of Poverty and Social Justice. https://doi.org/10.1332/ 19(2), 93–105. https://doi.org/10.1521/scpq.19.2.93.33313 175982720x16034770581665 Sundar, S., Qureshi, A., & Galiatsatos, P. (2016). A Positive Leach, C. W., & Smith, H. J. (2006). By whose standard? The Psychology Intervention in a Hindu Community: The Pilot affective implications of ethnic minorities’ comparisons to Study of the Hero Lab Curriculum. Journal of Religion and ethnic minority and majority referents. European Journal of Health. https://doi.org/10.1007/s10943-016-0289-5 Social Psychology, 36(5). https://doi.org/10.1002/ejsp.315 Tan, J. J. X., Kraus, M. W., Carpenter, N. C., & Adler, N. E. (2020). Lyubomirsky, S., King, L., & Diener, E. (2005). The benefits of The association between objective and subjective socioeconomic frequent positive affect: Does happiness lead to success? status and subjective well-being: A meta-analytic review. Psychological Bulletin, 131(6), 803. Psychological Bulletin. https://doi.org/10.1037/bul0000258 Maccagnan, A., Wren-Lewis, S., Brown, H., & Taylor, T. (2019). Tay, L., Zyphur, M., & Batz, C. L. (2018). Income and subjective Wellbeing and society: Towards quantification of the co-benefits well-being: review, synthesis, and future research. Handbook of of wellbeing. Social Indicators Research, 141(1), 217–243. Well-Being, 1974, 1–12. https://doi.org/10.1007/s11205-017-1826-7 The World Bank. (2021). GDP (currentUS$) - India. https://data. ´ ´ ´ Mateu, P., Vasquez, E., Zun˜iga, J., & Iban˜ez, F. (2020). Happiness worldbank.org/indicator/NY.GDP.MKTP.CD?locations=IN and poverty in the very poor Peru: measurement improvements Thoits, P. A. (2011). Mechanisms linking social ties and support to and a consistent relationship. Quality & Quantity. https://doi.org/ physical and mental health. Journal of Health and Social 10.1007/s11135-020-00974-y Behavior. https://doi.org/10.1177/0022146510395592 Michalos, A. C. (1985). Multiple discrepancies theory (MDT). Social Thorat, A., Vanneman, R., Desai, S., & Dubey, A. (2017). Escaping Indicators Research. https://doi.org/10.1007/BF00333288 and falling into poverty in India today. World Development, 93, Moskowitz, J. T., Shmueli-Blumberg, D., Acree, M., & Folkman, S. 413–426. https://doi.org/10.1016/j.worlddev.2017.01.004 (2012). Positive affect in the midst of distress: implications for Tourangeau, R., Rips, L. J., & Rasinski, K. (2000). The psychology of role functioning. Journal of Community & Applied Social survey response. Cambridge University Press. https://doi.org/ Psychology. https://doi.org/10.1002/casp.1133 10.1017/CBO9780511819322 Mussweiler, T., Gabriel, S., & Bodenhausen, G. V. (2000). Shifting UNDP. (2020). The 2020 Global Multidimensional Poverty Index social identities as a strategy for deflecting threatening social (MPI) | Human Development Reports. Human Development comparisons. Journal of Personality and Social Psychology. Report. http://hdr.undp.org/en/2020-MPI%0Ahttp://hdr.undp. https://doi.org/10.1037/0022-3514.79.3.398 org/en/2018-MPI%0Ahttp://hdr.undp.org/en/2020-MPI 123 Psychol Stud (July–September 2022) 67(3):281–293 293 United Nations. (2015). Sustainable development goals. https://sdgs. comparative analysis. European Sociological Review, 20(4), un.org/ 287–302. https://doi.org/10.1093/esr/jch029 ´ ` Vasquez-Vera, H., Palencia, L., Magna, I., Mena, C., Neira, J., & Whitaker, K. B., & Moss, D. W. (1976). Titration of human placental Borrell, C. (2017). The threat of home eviction and its effects on alkaline phosphatase with radioactive orthophosphate. Clinica health through the equity lens: A systematic review. Social Chimica Acta, 71(2), 277–284. https://doi.org/10.1016/0009- Science & Medicine. https://doi.org/10.1016/j.socscimed.2017. 8981(76)90541-6 01.010 WHOQoL Group. (1994). The Development of the World Health Veenhoven, R. (2005). Happiness in hardship. In L. Bruni & P. Porta Organization Quality of Life Assessment Instrument (the (Eds.), Economics and happiness (pp. 243–266). Oxford: Oxford WHOQOL). In Quality of Life Assessment: International University Press. https://doi.org/10.1093/0199286280.003.0011 Perspectives (pp. 41–57). https://doi.org/10.1007/978-3-642- Veenhoven, R. (2008). Healthy happiness: effects of happiness on 79123-9_4 physical health and the consequences for preventive health care. World Bank Group. (2020). Poverty & Equity Brief India. Poverty & Journal of Happiness Studies. https://doi.org/10.1007/s10902- Equity Brief India. 006-9042-1 Venkata Ratnam, C. S., & Chandra, V. (1996). Sources of diversity Publisher’s Note Springer Nature remains neutral with regard to and the challenge before human resource management in India. jurisdictional claims in published maps and institutional affiliations. International Journal of Manpower, 17(4–5), 76–108. https://doi.org/10.1108/01437729610127631 Whelan, C. T., Layte, R., & Maıˆtre, B. (2004). Understanding the mismatch between income poverty and deprivation: A dynamic
Psychological Studies – Springer Journals
Published: Sep 1, 2022
Keywords: Life satisfaction; Poverty; Urban slum; India
You can share this free article with as many people as you like with the url below! We hope you enjoy this feature!
Read and print from thousands of top scholarly journals.
Already have an account? Log in
Bookmark this article. You can see your Bookmarks on your DeepDyve Library.
To save an article, log in first, or sign up for a DeepDyve account if you don’t already have one.
Copy and paste the desired citation format or use the link below to download a file formatted for EndNote
Access the full text.
Sign up today, get DeepDyve free for 14 days.
All DeepDyve websites use cookies to improve your online experience. They were placed on your computer when you launched this website. You can change your cookie settings through your browser.