E-Bulletin of the Human Development and Capability Association
Number 14, June 2009
Dear HDCA Member,
of operationalizing the capability approach continues to be a thorny
one for those who are trying to build an alternative economic approach
to wellbeing measurement. As is well-known the use of consumption or
income-related data remains widespread precisely because of its user-friendliness.
However, almost a decade of sustained research on developing capability
indicators is changing the landscape of official statistics. Across
the world and in different policy areas, such as health or poverty reduction,
one observes the emergence of surveys that are designed to collect data
on capabilities so that the capability approach can become as ‘user-friendly’
than the income approach in the evaluation of stats of affairs.
In this issue
of Maitreyee on ‘collecting capability data’, Paul Anand
discusses some methodological questions when collecting data on capabilities.
Paula Lorgelly examines how the capability approach can be used in health
policy in a developed country context. She sets out pathways to developing
a capability measure that can be used in public health evaluations.
Suman Seth concludes the ‘Insights’ section by describing how capability-related
data can be collected on the basis of existing surveys. He illustrates
this with the case of India.
‘In the Practice’
section reproduces two examples of surveys that have been used to collect
capability data. One is the survey on ‘missing dimensions’ by the
Oxford Poverty and Human Development Initiative that is being pioneered
in Chile. The other is the one that has been used in the capability-based
evaluation of health policy described by Paula Lorgelly in the ‘Insights’
As usual, if
you have any comments, or would like to make a contribution to forthcoming
issues of Maitreyee, do not hesitate to contact us. Our next
issue will be in October and cover the topic of culture and human rights.
and Arnab Acharya
and their Measurement
The Open University and
Research Centre, Oxford University
A key question for capabilities researchers is a simple one about whether capabilities can be measured. On the side of the sceptics, there are those who point out that data on individual capabilities is difficult to find. After all, where can we obtain objective enumerations of all the elements of an agent’s choice set given his or her resource endowments? And yet more positively, variables increasingly used in the assessment of economic progress like literacy rates, morbidity and even unemployment rates clearly do measure aspects of the capabilities and opportunities that individuals possess. So the extent to which the capabilities approach has inspired the development of the Human Development Index (HDI), and the degree to which HDI is now a central concept in policy debate around low income countries is a clear marker of success for those interested in the operationalisation of the capability approach.
However, this important achievement, which reflects the role of measurement and measurability for policy-making and evaluation, raises serious questions about whether a few simple capability indicators can be broadened out to develop measures of progress that have significance for all countries around the world. This at least has been the central question of our research. At the heart of the capability approach to welfare economics and human progress are a number of concepts that could potentially have significance for national and international systems of measurement. In particular, we might want to distinguish between functionings and capabilities and identify, and even ultimately prioritise, a range of different dimensions of welfare and poverty. And if we can generate or find such data, then there may be a whole new set of questions about how such data are best analysed.
For nearly a decade now, a range of institutions including The Open University, Oxford University and institutions around the world have been exploring these issues in an approach that has moved between the generation of our own primary data tailored to the measurement of capabilities and the search for variables in secondary panel data sets that provide reasonable indicators of capabilities in significant life domains. As a result, multi-dimensional data on capabilities are still relatively sparse but some indicators do exist. There are questions about access to services, the ability to make certain kinds of plans and decisions, the scope for socialising in one’s life and so on that clearly go beyond asking people how times a week they perform a certain action and that are used widely in the big household panel surveys around the world. Not only has our trawling of surveys unearthed such questions but we have been able to generate similar kinds of questions across a range of life domains and thereby develop new datasets that show how the extant indicators can be broadened out and analysed.
During the course of this work, there has been a tendency to use the term indicators (in preference to measures) partly because the variables developed relate to aspects of what a person can do but also because there is a clear affinity with the literature on social indicators. Based on this work, it seems that one way of classifying capability indicators is according to the following five-fold taxonomy:(i) Opportunity oriented indicators
(ii) Ability oriented indicators
(iii) Constraint oriented indicators
(iv) Functioning questions with reasons
(v) Functioning questions with universality assumptions
Questions that members of the public understand and can respond to may not exactly match the categories that seem to be clear cut from a theoretical perspective but we find questions that often seem to have a focus or orientation that is reflected in these categories. Some questions ask people about the opportunities in their environment whilst others seem to be more focussed on what the individual can him or herself do. Yet other questions seem to focus on what people cannot do – in which case the replies might be determined by a mix of features in the environment and a person’s own abilities.
categories illustrate what we might call direct capability indicators
but we should also recognise that questions about functionings can also
provide indirect evidence of a person’s capabilities. For example
it is not implausible to ask people about the safety of the area in
which they live and to infer that those living in unsafe areas are in
some way constrained to live there. Alternatively, one can ask about
functionings and follow up with questions about the reasons why people
do or do not engage in particular activities. These indirect capabilities
indicators have not been so important in our work to date though I believe
they could be exploited more fully.
The OCAP family of instruments1
Following early pilot work using the concept of scope, a team at the Open University developed questions drawing on all five indicator types above, that are taken from or look similar to those that can be found in household surveys (Anand et al 2009b). The main OCAP instrument) is suitable for use with adult populations comprises around 60 items. It is based on an attempt to closely translate Martha Nussbaum’s list, though for reasons that were primarily related to comprehensiveness rather than any particular view about the nature of ideal constitutions. If one looks at similar lists produced by researchers in many disciplines they often share common elements. However, the attraction for us was that Nussbaum’s list is relatively comprehensive and so dimensions that turn out not to be of interest can simply be ignored.
The OCAP instrument
was first delivered to a national sample of 1000 adults in the UK in
2005. Subsequently, it has been translated into Spanish for use with
a similar sample in Argentina, was subject to focus group dimension
reduction by a project in Glasgow and is currently being used in a clinical
trial related to mental health in Oxford (possibly the first clinical
trial in the world to use this approach explicitly!).
The development and use of capabilities measurement surveys creates an opportunity for data to be analysed by a variety of methods. In our published work to date, we have particularly focused on, (a) national overviews of individual capabilities, (b) the role of past current and future violence on experienced welfare and (c) identifying groups who are capability impoverished across a wide range of life domains.
The idea of doing a national survey of capabilities seemed a natural starting point for us and this is something that could easily be replicated in other countries using our survey instrument (see the articles cited for question wording and rationale). Thus far we have looked at this data in terms of age and gender differences and find that whilst the pattern of significant coefficients of capabilities indicators in happiness equations differs between men and women and in ways that are not altogether surprising, the signs associated with the coefficients are identical between the two groups. We have also examined in some detail the role of violence (past, current and expected) on experienced welfare and find significant evidence of a negative impact, little evidence that preferences adapt to the experience of violence, and some suggestion that fear of violence dominates past experiences in terms of its negative impact of welfare Anand et al (2009a). Finally, we have looked at poverty in the sense of low all round capability deprivation and find, in our UK sample that about 8% of the population fall into such a group and that about half have health problems. A second group comprising 10% of the population also has relatively low capabilities and consists mainly of women across the age range. These empirical insights do not obviously fall out from a more conventional approach suggesting that the capabilities approach if used in this way has the capacity to generate some potential novel empirical findings that may be of interest to policy-makers.
What this project has demonstrated is that there are ways of moving from theory to data design, survey collection and analysis that operationalise the capabilities approach in quite a literal manner. This is not the only way to go about operationalisation as work with latent class techniques by Krishakumar and colleagues nicely illustrates but it does suggest at least one potentially fruitful line of inquiry for both those interested in survey development as well as those keen to analyse some unique kinds of data. It would be particularly interesting to see the survey instruments replicated with new populations or adapted to novel topics.
Anand P., C. Santos and R. Smith (2009a), ‘The Measurement of Capabilities’, in K. Basu and R. Kanbur (eds), Arguments for a Better World, Oxford: Oxford University Press
G. Hunter, K. Dowding, F. Guala, M. van Hees (2009b), ‘The Development
of Capability Indicators’, Journal of Human Development and Capabilities,
The Capabilities Measurement Project Website
Developing a capability measure for use in public health evaluations
Dr Paula Lorgelly
There is a growing interest, within the field of health economics, in the application of Sen’s capability approach to the evaluation of health care programmes. This article describes the development of questionnaire to measure outcome within the capabilities framework, for use in the (economic) evaluation of complex social and public health interventions.
Economic evaluation – which seeks to identify whether a proposed change in service provision is a good use of scarce resources – involves comparing the additional costs associated with the change and the additional outcomes achieved by the change. Economic theory prescribes that such evaluations take a welfarist approach, that is, where outcomes are valued in monetary terms. However, due to difficulties in placing a monetary value on life and health, within the speciality of health economics, an extra-welfarist approach has developed, whereby health is valued for health’s sake and outcomes are commonly assessed using quality adjusted life years (QALYs). One issue of assessing health related quality of life (HRQoL) and QALYs within an evaluation of complex social and public health interventions is that the focus is too narrow – simply health. The capability approach has a much wider focus (that is a broader evaluative space) and as such would appear to be an appealing alternative.
There is, therefore, theoretical support for using the approach, but the application of the approach is limited by the fact that capability sets are not easily or directly observable. There are a limited number of empirical applications of the capability approach, in part because many secondary data sources measure an individual’s choices, their functionings, and not their capabilities per se. Anand et al (2005) responded to this lack of empirical research by utilising data from the British Household Panel Survey in an attempt to measure capability. Upon finding incompleteness, they developed further indicators. The result is a set of more than 60 indicators, which reflect Nussbaum’s list of ten capabilities. Anand et al (2009) found strong evidence of a link to wellbeing, but noted that further research was required, particularly in terms of tailoring samples to focus on specific issues. While their application is not the only approach to measuring capabilities, its survey design is practical for use in large research projects which involve self completing questionnaires or interviews, such as evaluations of social and public health interventions, and so offers the potential to provide a summary measure of wellbeing and capability.
Sixty plus indicators was, however, considered to be a rather arduous task for study participants completing a questionnaire which would also include other outcome measures and a range of demographic questions. Therefore, it was necessary to reduce and refine the instrument as proposed by Anand et al. This was conducted in three phases.
Phase One reviewed the literature on capability, questionnaire design and outcome measurement; this informed the initial design and layout of the questionnaire (see Appendix, version 1). Members of the public were recruited to attend five focus groups, during which they discussed the range of questions, style of elicitation, their understanding and the overall questionnaire design. The results of these focus groups, together with secondary analysis (factor analysis) of Anand et al.’s original data, then informed the first revision of the questionnaire (see Appendix, version 2). Questions were removed if: factor loadings suggested correlation with other questions; pairwise correlations were significant; and there were multiple questions measuring a specific capability; or questions measured functioning rather than capability. Questions were refined with respect to: ordering; merging; consistency in question wording and answer options (including reduction in answer options); understanding and interpretation of terminology. This revised version was piloted in a postal survey and via interviews with members of the general public.
Phase Two involved a thematic analysis of the interview data and a quantitative analysis of all completed questionnaires (factors analysis and correlation patterns) with the aim of identifying areas in which the questionnaire could be further reduced. Questions were removed if: correlations were found; they appeared not be a measure of capability (given qualitative analysis), this was complimented by the quantitative analysis (in terms of correlations and factor loadings); they were considered to be a capability in the developing country context, rather than specific to public health interventions. Questions were refined with respect to: ordering; understanding and interpretation of terminology. The questionnaire was then redesigned using the reduced set of questions (see Appendix, version 3) prior to further interviews and a postal survey. In essence Anand et al.’s original 60+ capabilities – nested within Nussbaum’s list of ten – were first reduced to 43 capabilities, and finally to 18 specific capabilities (version 3). The Appendix (on the last page) provides a graphical representation of this process. The first column presents Nussbaum’s list of central human capabilities (life; bodily health; bodily integrity; senses imagination and thought; emotions; practical reason; affiliation; other species; play; and control over one’s environment), while the second column presents the questions from Anand et al.’s original questionnaire, classified into each of Nussbaum’s ten capabilities. The questions used in the first revision of the questionnaire are presented in the third column (version 2), while the last column presents the final version of the questionnaire. Reading from left to right shows the process of item reduction and question refinement.
Phase Three involved analysing the data from version 3 of the questionnaire, and an attempt to generate an index of capability.
Data collection using the final version of the questionnaire began in October 2007 when the questionnaire was sent out to 1000 addresses within Glasgow City. 180 questionnaires were returned completed. This resulted in a response rate of 18.6%. In addition, during October and November 2007, 18 respondents completed the questionnaire in an interview setting; therefore a total sample of 198 was available for analysis.
Demographically, this sample was broadly representative of the Glasgow population, though with a higher proportion of white and female respondents than in the population as a whole. Notably the proportion of respondents living in each deprivation decile was very representative of the Glasgow population; this was achieved by a strategy of over-sampling in the most deprived areas.
Analysis of the questionnaire responses found that respondents had a range of capabilities, and that these capabilities appear to be sensitive to one’s gender, age, income and deprivation decile. An analysis of inequalities within individual capabilities and questions about capabilities found that males were better at predicting their life expectancy (‘life’ capability), whilst males also believed that they are more likely to be victims of assault (‘bodily integrity’). The elderly (older than 60) were more likely to report that their health limited their activities of daily life relative to younger respondents (‘bodily health’), while a higher proportion of younger respondents (those under 60) felt they were likely to experience discrimination outside of their place of employment compared to older respondents (‘affiliation’). Those living in more deprived areas were found to report greater limitations in their daily activities due to their health status (‘bodily health’), as well as feel less safe walking in their neighbourhood (‘bodily integrity’), report having fewer opportunities to socialise (‘emotions’ capability) and were less able to afford to own property than respondents in the more affluent areas of Glasgow City (‘control over one’s life’). Those in low income groups were also found to have worse health in terms of limiting daily activities (‘bodily health’), and to predict life expectancies well below that expected given their age and gender (‘life’ capability), compared to those in higher income groups. Respondents with low household incomes also reported limitations in terms of socialising with friends and family (‘emotions’) and owning property (‘control over one’s life’). They were also less likely to feel they could influence local decision making (‘control over one’s life’), more likely to report losing sleep over worry (‘emotions’) and rarely able to enjoy recreational activity (’play’ capability) relative to respondents with high household incomes.
An index of capability, estimated by assuming equal weight for each capability question, found that the average level of capability amongst respondents was 12.44, with a range of 3 to 17.75 (given a possible maximum of 18). This index was found to be highly correlated with a measure of health regularly used by health economists, the EQ5D, and wellbeing, as measured using a global quality of life scale. Some differences were apparent, implying that the questionnaire has the potential to be a valid measure of outcome for public health interventions.
Similar inequalities to those described above for specific capabilities were found to exist across groups with respect to the index as a whole. While no differences were found between males and females or across age groups, those respondents residing in the more deprived areas and those respondents with lower incomes were found to have less capability as measured by the index. A multivariate approach, however, found that income was a greater driver of inequalities in capability than was area-based deprivation.
The benefits of using the capability approach to evaluate public health interventions are numerous. It offers a much richer set of dimensions for evaluation, which given the nature of public health and social interventions, with their many and complex outcomes, makes the approach ideal for capturing all these outcomes, rather than focusing solely on health status. The equitable underpinnings of the approach are also appropriate for use with public health interventions which often involve reducing inequalities across groups (namely improving deprivation) as an overriding aim. In terms of the practical issues of measuring capabilities, it would appear that our reduced and refined questionnaire, provides one means of doing this. It appears to be responsive to different groups of individuals, and to measure something additional to health and wellbeing, although is still highly correlated with these measures.
Anand P, Hunter G and Smith R (2005) ‘Capabilities and well-being: evidence based on the Sen–Nussbaum approach to welfare’, Social Indicators Research, 79: 9-55.
Anand P, Hunter G, Carter I, Dowding K, Guala F and Van Hees M (2009) ‘The development of capability indicators’, Journal of Human Development and Capabilities,10: 125-152.
capability data on the basis of existing surveys: The case of India
Over the past few decades, the capability approach has been applied in many contexts. Several countries have directed the evaluation of welfare, poverty, and inequality on its basis. Proper application of the approach, however, has encountered mainly two serious challenges among others. The first is attributed to the choice of reasonable indicators for measuring poverty, the second to the collection of appropriate data. It is difficult to measure capabilities directly and thus the first challenge is often met by selecting dimensions and indicators that measure the following three categories – (i) functionings (‘doings’ and ‘beings’), (ii) access to basic services, and (iii) control over physical materials that enhance capabilities.
This brief article discusses how some existing surveys can be useful in the Indian context to collect data for the required dimensions and thus meeting the second challenge. There are two major surveys that are conducted in India covering all states. The first is the National Sample Survey (NSS) conducted by the National Sample Survey Organization, Department of Statistics, Government of India. The second is the National Family Health Survey (NFHS), which is collaboratively conducted by the International Institute for Population Sciences (IIPS), Mumbai, India; ORC Macro, Calverton, Maryland, USA; and the East-West Center, Honolulu, Hawaii, USA. The first survey is carried out every year but a major survey is conducted every five years. The second survey has been carried out in three rounds since 1992-93. The NSS is primarily a consumer expenditure survey and is suitable for poverty measures that are motivated by the basic needs approach. The NFHS, on the other hand, is more useful if one wishes to capture the dimensions of capabilities. The first two rounds of NFHS surveys, conducted in 1992-93 and 1998-99, respectively, interviewed only ever-married women. While the third round of NFHS, conducted in 2005-06, interviewed in addition never-married women and never-married and ever-married men. In this article, we especially elaborate the dataset of the third round of the survey.
The survey interviewed 124,385 women aged 15-49 and 74,369 men aged 15-54 from 109,041 households across all 28 states and Delhi. There are three different types of questionnaires – household, women, and men questionnaire. The questionnaires for men and women contain information on individual functionings such as the level of education and the health status among others. Besides, the household questionnaire collects information on access to basic services and access to physical materials. We provide a detail description of the dimensions and responses in the three categories as follows.
First, we report the responses that would enable us to capture the access to basic services. The following related questions are contained in the dataset.
Second, the following set of questions contained in the questionnaire take into account the access to physical materials.
A positive response to the set of questions asked above is helpful in terms of creating an opportunity for the members of any household to ‘be’ or ‘do’ what they have reason value. However, these responses are not sufficient to capture the set of capabilities they enjoy. For example, an ownership of a bicycle does not enable a young mother, who is not properly educated, to take appropriate care for her children. The NFHS questionnaire also asks the following set of questions that should capture the functionings of the members of the household.
It is well-known that being educated (Question 11) is an essential functioning that enhances capabilities in various dimensions of life. The survey asks about each family member’s level of education. Like education, being healthy is also an important functioning. There are various ways of measuring health status. Body mass index (BMI) may be a possible candidate. The survey asks information about height and weight (Question 12). This gives us information, at least, about one member of the household. This definitely is not one of the best proxies one can use for the entire household but we can at least capture the status in part. However, this indicator should perform reasonably well when we measure the health status of women and men respondents only. There are also other health related questions, such as anaemia level, if somebody believes it to be a more appropriate candidate.
The third question in this category is the type of occupation that the respondent and her partner are involved in. Occupation categories, such as unemployed and labourers, make a household incapable of enjoying many freedoms. The fourth question is concerned with whether the household members are capable of breathing in a clean, healthy, and unpolluted environment, as this prevents respiratory diseases and enables the members to live a prolonged and successful life. The next category asks about the labour status of the children in a household. For any country, one of the biggest assets is children. However, the lack of education and engagement in household chores constrain their set of opportunities to live a life they would value. The final question in this category is women’s empowerment. Women with freedom in a household are capable of making better decision. Women’s empowerment is difficult to measure directly. There are few existing questions, however, that might enable us to capture the status of women in the family. One of the questions asks if the woman in the household enjoys the freedom of going to certain places according to her will, and the other question asks if the woman has a final say on certain decisions. We expect that a positive response to these questions would, at least, in part reflect the empowerment of women within the household.
After we learned what the survey is capable of, we should also be careful about certain aspects as there are indeed certain limitations. The first is that the dataset does not contain any information regarding the income level of the household. However, income is a transitory concept and can be proxied by the ownership of other physical materials (Q. 7 - 10). The second limitation is that the sample survey collects information only from those households that contain either a woman in the age group of 15-45, or a man in the age group of 15-54, or both. However, the proportion of population living in a household without anyone in those age groups would be minimal.
Alkire, S. (2008), ‘Choosing Dimensions: The Capability Approach and Multi-dimensional Poverty’, in Kakwani and Silber (eds), The Many Dimensions of Poverty, New York: Palgrave
Alkire, S. and S. Seth (2008), ‘Multidimensional Poverty and BPL Measures in India: A Comparison of Methods’, OPHI Working Paper No. 15, www.ophi.org.uk
IIPS and ORG Macro International (2007), National Family Health Survey (NFHS-3), 2005-06: India, Volume 1, Mumbai: International Institute for Population Sciences
Nations Development Programme (2003), Indicators for Monitoring the
Millennium Development Goals: Definitions, Rationale, Concepts, and
Sources, New York: United Nations
In the Practice
Missing Dimensions of Poverty Data: First National Survey in Chile
and Human Development Initiative
OPHI began the first-ever large scale survey of the Missing Dimensions in Chile in November 2008. Working with the Centro de Microdatos of the University of Chile, it designed a nationally-representative survey which draws on 2,000 households interviewed in the 2006 round of Chile’s national household survey, the CASEN. The survey permits combining the new OPHI indicators with those that are collected conventionally.
The full household
survey is available in Spanish on the OPHI website at www.ophi.org.uk. This article reproduces some of the
questions that relate to three missing dimensions: empowerment, meaning
and ability to go out without shame. The OPHI website also contains
a generic survey for collecting data on other dimensions of human wellbeing
such as employment and security from which the questions below are extracted
(see the Maitreyee issue of October 2007 for the ‘missing dimensions’).4
Perceptions about decision-making (empowerment)
1. In general, how much control do you think you have over decisions which affect your daily activities (drop the kids at school, buy bread, cook, wash, etc.)?: a) Over all decisions; b) Over a great deal of decisions; c) Over some decisions; d) Over few decisions; e) Over none.
2. How much does your household spend on food during a normal week?
3. When decisions are taken regarding minor expenses such as food and other consumables, who does usually make these decisions?; a) Me; b) Me and my spouse or partner; c) Me and someone else (but not my spouse/partner); d) My spouse/partner; e) Other.
4. If you wished to take these decisions, would you able to? a) Yes; b) No.
5. Now, I am asking you to tell me whether you agree or disagree with the following statements, with 1 being ‘agree very much and 4 ‘disagree very much, with regard to how you take decisions about certain minor expenses of the household, such as food, soap and others: a) I have no choice for buying minor expenses for the household. I have no choice in doing things; b) I do the daily shopping according to what my spouse, someone else, society, social organizations, or my community ask me/oblige me to do; c) I do the daily shopping according to what is expected of me to gain social approval. If I don’t do it, I feel guilty; d) I do the daily shopping according to what I consider personally to be important.
6. Do you practice any religion?: a) Yes, which one?; b) No.
7. How important is religion in your life?: a) Very important; b) Quite important; c) Not much important; d) Not important at all.
8. Who takes decisions about whether to practice a religion or not and how to practice it?; a) Me; b) Me and my spouse or partner; c) me and someone else (who is not my spouse or partner); d) My spouse/partner; e) Someone else; f) The community/ social organization/ neighbourhood association.
9. If you wished to take these decisions, would you be able to?: a) Yes; b) No.
10. Now, I am asking you to tell me whether you agree or disagree with the following statements, with 1 being ‘agree very much and 4 ‘disagree very much, with regard to how you take decisions about religious practice: a) I have no decision power over to practice or no religion. I have no choice but to practice; b) I practice/don’t practice a religion because my spouse, someone else, society, social organizations, or my community ask me/oblige me to do so; c) I practice/don’t practice a religion depending on what is expected of me to gain social approval. If I don’t do it, I feel guilty; d) I practice/don’t practice a religion because I personally consider it to be important.
11. Would you like to change something in your life for the moment?: a) Yes; b) No; c) I don’t know.
12. Who seems to be contributing more about change in your own life?; a) Myself; b) My family; c) My community; d) the local government; e) the central government; f) Other; g) I don’t know.
13. Do you believe that you can change things in your community if you would like to?: a) Yes, very easily; b) Yes, easily; c) Yes, but with difficulty; d) Yes, but with much difficulty; e) No, not at all; f) Other; g) I don’t know.
14. Who takes usually the decisions whether you participate or not in a social organization?: a) Myself; b) Me and my spouse or partner; c) Me and someone else; d) My spouse/partner; e) Other; f) The community.
15. Now, I
am asking you to tell me whether you agree or disagree with the following
statements, with 1 being ‘agree very much and 4 ‘disagree very much,
with regard to how you take decisions about participating in a social
organization: a) I have no power of deciding whether to participate
or not; b) I participate because my spouse, someone else, society, social
organizations, or my community ask me/oblige me to do; c) I participate
because it is expected of me to gain social approval. If I don’t do
it, I feel guilty; d) I participate because I personally consider it
to be important.
Perception about values
1. (Meaning of life) Please take a few minutes to think about the things that make your life important. Which of these affirmations would you subscribe to?: a) My life has a clear sense and purpose; b) I have discovered a satisfactory sense of life; c) I have some clear idea that gives meaning to my life.
2. (Autonomy) Which of these affirmations would you subscribe to?: a) I feel that I am free to decide how to live my life; b) In general, I think that I can express freely my ideas and opinions; c) I feel that in each daily situation, I can be honest to myself.
3. (Competence) Which of these affirmations would you subscribe to?: a) The people I know say that I am able/skilled in what I am doing; b) Most of the time, I feel that I achieve the things I do; c) In general, I feel very able.
Which of these affirmations would you subscribe to?: a) I get on well
with the people I am in touch with; b) I consider that the people I
relate to are close; c) People around me are concerned about me.
1. Do you agree or disagree with the following statements?: a) I am ashamed of being poor; b) I would be ashamed if someone in my family was poor; c) Poor people should feel ashamed of themselves; d) The people who are not poor make poor people feel bad.
2. How do you think people in your community/city would answer the following questions: a) I would feel ashamed of being poor; b) I would feel ashamed if someone in my family was poor; c) Poor people should be ashamed of themselves; d) The people who are not poor make poor people feel bad.
3. For each of the following feelings, please give a number from 1 to 4 to reflect how often do you feel them (1: continually almost always; 2: frequently but not always; 3: sometimes; 4: rarely or never; 5: I don’t know). a) feeling ashamed; b) feeling ridicule; c) feeling oppressed; d) feeling humiliated; e) feeling stupid; f) feeling childish; g)feeling paralysed; h) feeling blushing; i) feeling laughed at; j) feeling that others are disgusted by me.
4. To what extent do you feel that people treat you with respect? (1: yes, always; 2: yes, frequently; 3: yes, occasionally; 4: no, never.
5. Who has treated you with discrimination?: health services, school/work, police/judicial system, social services, shops/restaurants, banks/insurance companies, government housing programme, close family, strangers in public places, others
6. Why have you been treated with discrimination (please indicate the main reason): ethnic, racial or cultural background, gender, sexual orientation, age, disability, religion, socio-economic group, education, others, I don’t know.
Survey used to assess capabilities in a context of public health in the UK