UKHLS consultation: Risky and Illicit Behaviour

Transcription

1 UKHLS consultation: Risky and Illicit Behaviour Steve Pudney Institute for Social and Economic Research

2 Outline of meeting UKHLS: an introductory overview The potential The constraints Measures of illicit behaviour An initial list of measures (in current use) Introduction to issues: general to detailed Floor discussion

3 UKHLS scientific leadership team Nick Buck (ISER, Essex) Principal investigator Randy Banks (ISER) Stephen Jenkins (ISER) Heather Laurie (ISER) Peter Lynn (ISER) Steve Pudney (ISER) Lucinda Platt (ISER) ethnicity strand Richard Berthoud (ISER) ethnicity strand Heidi Mirza (Institute of Education) ethnicity strand Dieter Wolke (Warwick) biomedical strand Scott Weich (Warwick) biomedical strand

4 UKHLS: background UKLHS is a longitudinal study based on a household panel design, i.e. sample based on all residents (adults and children) at addresses selected at wave one, following them at each wave, including movers and collecting data about new household members Similar in design to British Household Panel Survey (BHPS), which it will replace, and panels in other countries, e.g. SOEP, HILDA, PSID, SoFIE Target sample size of 40,000 households largest household panel study in world

5 UKHLS background (ii) A major investment, motivated by the success of longitudinal research in UK 1. ESRC secured funding from OSI to start UKHLS 2. Expert Panel (chair: Peter Elias) steered development of UKHLS up to appointment of PI team 3. 4 expert studies made recommendations on content and design presented at meeting in October November 2006 March 2007, commissioning of principal investigator team 5. From April 2007, PI team starts work with consultation and commission survey organisation 6. ESRC continues to seek co-funding

6 UKHLS key features Large sample size Household focus Full age range sample Innovative data collection methods Multi-purpose multi-topic design to meet a wide range of disciplinary and interdisciplinary research needs Ethnic minority research Biomedical research

7 (1) large sample size 40,000 households gives an opportunity to explore issues where other longitudinal surveys are too small Small subgroups, e.g. single-parent families, offender groups, etc. Smaller areas: analysis at regional and sub-regional levels, allowing examination of the effects of geographical variation Smaller time periods: large sample size allows highresolution analysis of events in time e.g. single-year birth cohorts

8 (2) household focus Data collected on all members of sampled households (unlike, e.g. OCJS or BCS) Important for research on e.g. Family circumstances as an influence on behaviour Effects of one family member s behaviour on others in the family Observing multiple generations and siblings allows examination of long-term transmission processes Opportunities to explore linkages outside the household

9 (3) full age range full age range at any point in time complements age-focused studies sampling elderly people (e.g. ELSA) or young people (e.g. LSYPE, birth cohort studies) Provide a unique look at behaviours and transitions in mid-life e.g. long-run implications of early risky or illicit behaviour Large sample size all cohorts can be analysed at a common point in time

10 (4) innovative data collection Continuous development in data collection methods benefiting from: experience from other longitudinal surveys introduction of new technologies This will involve e.g.: additional modes of interviewing collection of qualitative and visual data external record linkage An Innovation Panel to allow experimentation and methodological development

11 (5) broad interdisciplinary topic coverage Multi-purpose survey supporting a very wide range of research agenda cannot have the focus of more specialist surveys Strength arises from bringing together information on many life course domains Interdisciplinary aiming both to meet needs of traditional panel-use disciplines (economics, social policy and sociology) and support more interdisciplinary work within the social sciences (e.g. geography and economics); within the biomedical sciences (e.g. psychology and genetics); and between the two

12 (6) ethnic minority research Ethnicity strand includes: Boost sample for five key groups (Indian, Pakistani, Bangladeshi, Caribbean, Black African) Ethnic minority group members selected for main sample Questions focused on ethnicity issues Recognises the increasing prominence of research into ethnic differences for understanding the make-up of British society and issues of diversity and commonality

13 (7) biomedical research Collection of a wide range of biomarkers and health indicators to be supported Opportunity to assess exposure and antecedent factors of health status, understanding disease mechanisms (e.g. gene-environment interaction, gene-to-function links), household and socioeconomic effects and analysis of outcomes using direct assessments or data linkage. Opens up prospects for advances at the interface between social science and biomedical research Psychological underpinnings of problematic behaviour

14 UKHLS study design Randomly sample UK addresses: select as sample members all members of private households found At each wave, all sample members above a threshold age eligible for interview (threshold to be decided) Individuals followed as they move and form new households Other individuals who form households with sample members after wave 1 eligible for interview Following rules mean that the UKHLS will remain representative of the UK population as it changes, subject to weighting and except for new immigrants to the UK

15 UKHLS sample composition 1. A new equal probability main panel achieved sample of 28,000 29,000 households Fieldwork to commence in January A new boost ethnic minority sample, to provide 1,000 adult individuals in each of the five main ethnic minority groups 3. The BHPS sample of approximately 8,400 households Data collection as part of the UKHLS will start with wave 2 in October An Innovation Panel of 1500 households to enable methodological research Fieldwork to commence in January 2008

16 UKHLS design Some aspects remain to be finalised and depend partly on co-funding Expected features include: 12 month intervals between interviews Continuous fieldwork (implications for reference periods for retrospective questions) [Possible 24 month field period, with second wave overlapping with first] Face-to-face interview at wave 1; mixed mode at wave 2 Wave 1 individual interview not more than 40 minutes, wave 2 depends on budget, unlikely to exceed 40 minutes and may be shorter Some data collection directly from children aged less than 16 (unclear when to be implemented)

17 The UKHLS questionnaire Length constraints are likely to be particularly acute, given broad scope of UKHLS and wide range of demands move away from BHPS structure where most people are eligible to be asked all questions and most questions repeated each wave More use of questions asked regularly, but not every wave More use of questions asked only after key events or at particular ages More use of sub-samples, perhaps random sub-samples, where full sample unnecessary, or demographic subsamples

18 Structure of the UKHLS questionnaire Main sample Innovation panel Ethnic boost Current BHPS Annual Event triggered Regular periodic Other modules Special ethnic annual Special ethnic periodic Question development Time in minutes

19 BHPS and UKHLS At wave 2 of UKHLS (wave 19 of BHPS), the BHPS sample will become part of UKHLS Expected that BHPS will use new questionnaire from that point with limited modification to preserve some measurement continuity Development process recognised importance of comparability with BHPS likely to be significant use of BHPS questions But likely that a high proportion of BHPS questions will not be included or asked less often

20 Consultation 10 topic consultation groups June/July 2007: meeting for each group Summer 2007: Further interchanges, receipt of comments & memos Autumn 2007: convenors summarize conclusions; questionnaire design team will have access to all comments received January 2008: consultation conference Please see UKHLS website for further details!

21 Risky & illicit behaviour measures In the context of a survey that is general purpose & multi-topic longitudinal space constrained using measure(s) that are: short reliable valid

22 Potential R&IB measures: For example: 1. Smoking & (binge) drinking 2. Truancy & anti-social behaviour 3. Offending behaviour & victimisation 4. Illicit drug use 5. Problem gambling 6. Diet & physical (in)activity 7. Sexual behaviour 8. External impacts of R&I behaviour: Within the household Outside the household 9. Underlying behavioural characteristics, such as: Risk aversion Time discounting Cognitive ability Empathetic capacity R&IB measures could be used both as outcomes and predictors 22

23 R&IB measures: current practice 1. General population victimisation surveys (e.g. BCS) 2. Surveys of young people (e.g. LSYPE, Edinburgh YT&CS, School surveys of smoking, drinking & drug use, etc.) 3. Food consumption surveys (e.g. EFS) 4. Targeted surveys of special groups (e.g. of prison, arrestee & drug treatment client populations) 5. Health surveys (e.g. HSE) 6. Birth cohorts: limited coverage of lifetime drug prevalence, more on other health-related behaviour 7. BHPS has rather little: smoking, drinking, acquaintance with drug users, neighbourhood problems No survey currently contains all measures 23

24 General issues What is it feasible to ask about in a household context? How serious are the non-response and misreporting problems? How are sensitive issues best dealt with in the interview? Can we ask a family member about the impact on the family of other family members problem behaviour? What are the most important research questions to be addressed using R&IB measures, now and potentially in the future? Which of the measures cited should receive priority? Are there other important measures? How important is continuity of measurement relative to the existing BHPS, and comparability with other UK national surveys? To what extent is cross-national comparability an important consideration? 24

25 25 Definitional issues Optimal data collection frequency? e.g. sub-annual, annual, less frequent Reference period? e.g. activity ever, last year, last month, etc. How comprehensive a measure is really required? Detail of category of behaviour age of onset Frequency expenditure, etc. Which unit(s)? Each child? Each adult? Key persons?

26 Data collection issues 26 Which methods of data collection are workable? how to guarantee confidentiality in household survey context? e.g. postal self-completion versus computer-based selfcompletion (CASI or A-CASI); other non-traditional tools of data collection? automatic checks for unreliable responses? questions about worries over other family members behaviour? Linkage to external datasets? Health records Criminal records Education records

27 Discussion (1): Which research issues & which measures? 27 [AM] suggestion to prepare draft q naire to prompt bids for space, and to be a concrete thing to react against [AM] What possibility for screening questions that could lead to special modules of qns about e.g. problem gambling? Or even a special survey of a subsample of a problem group separately from the main UKHLS survey process, rather than an event-triggered part of UKHLS There already exists a 5 min screening Qn set Problem gambling starts / ends, not constant things, so importance of longitudinal / repeated measures Importance of social context for problem gambling Problem gambling co-morbid with alcohol use

28 28 Laundry list discussion (1): ctd. Alcohol misuse and interrelationships within families e.g. impact of parental behaviour on behaviour of adolescents. Longitudinal and HH contexts are important Distinguish between frequency and quantity. Experience asking these Qns in context of birth cohorts [Rob Frost, Acad of Med Sci] importance also of age of onset [Nico J] White collar crime and fraud tax declaration, embezzlement related to problem gambling issues, for example Importance of identifying tipping behaviours

29 29 Laundry list discussion (1): ctd. Stress and health, housing and poverty: relationships between these and problem behaviours NatCen single-interview 1999 study (soon to be repeated) of # gamblers at point in time currently best source of information about prevalence (c. 1.6% rate within a sample of 8000) The new legislation expanding gambling possibilities raises policy relevance of a PG module [Heather L] argued that Identification of PGers was the key issue, since could then would huge amount of detail about other aspects of their lives in subsequent interviews PG issues are very similar to all other problem behaviours

30 Discussion (2): Methods of data collection? Focussed studies on particular issues not ruled out; nonetheless we re cautious about implementing these are especially likely to have adverse impacts on response to the main UKHLS study What is feasible? What is valid and reliable? What Qns work? PG people can forward us sample questions or provide references please do! Can t ask about expenditure on the problem behaviour (e.g. drugs, PG, alcohol). Drug research asked about episodes Ask about PG stakes and winnings in each gambling episode over last week (?) rather than total spend What Qns to resp about someone else s behaviour and its effects New Zealand examples of this please send 30

31 31 Methods of data collection? ctd How will interviews be undertaken in the HH context? F2f + self-completion; individual resp and a HH respondent. Not a group interview. Interview context is important and will be recorded What about diaries (e.g. of time use, or expenditure)? On the medium and long-term agendas for consideration; whatever used, likely to be trialled and tested in Innovation Panel first Peer group and social network effects? How to collect the information, develop samples of networks and peers (and how to use the data)?

32 Methods of data collection? Ctd 32 Are there external record linkage possibilities in addition to those already mentioned? No

33 Discussion (3): Continuities & comparabilities 33 Virtually none? Drug use is it important to mimic e.g. BCS measures? [SP] Survey context (e.g. mode; other sorts of Qns asked) rather than precise wording likely to have greater impacts on responses