Young people's mental health in context: Comparing life in the city and small communities in Siberia

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Social Science & Medicine 65 (2007) 1180–1191 www.elsevier.com/locate/socscimed

Young people’s mental health in context: Comparing life in the city and small communities in Siberia$ Anthony Glendinninga,, Patrick Westb a

University of Aberdeen, Aberdeen, UK MRC Social and Public Health Sciences Unit, University of Glasgow, Scotland, UK

b

Available online 18 June 2007

Abstract The study compares young people’s mental health in the major Siberian city of Novosibirsk with small communities of the surrounding region, at the end of the statutory period of secondary education. Data are drawn from a school-based questionnaire survey of ninth graders and semi-structured interviews. In line with the findings of international comparative studies, general health profiles are not good by Western standards, but extending such findings, general health appears even poorer in small communities and is differentiated further by the rural household’s impoverished socio-economic circumstances. However, despite poorer general health among rural youth, the study finds the opposite for more specific profiles of mental health, which are worse among city youth. In this, distinctive social factors are associated with mental health differently in the large city and small communities of the region. In the relatively affluent city of Novosibirsk, selfworth and depression are differentiated by family background and engagement with the education system. By contrast, in small communities social capital associated with family support and kin-based networks become important resources instead. Positive mental health is bound up with the local cultural context, centred on the family household and ‘traditions’ of rural society. r 2007 Elsevier Ltd. All rights reserved. Keywords: Russia; Mental health; Rural; Urban; Socio-economic circumstances; Siberia; Young people

Introduction The present study examines the situations of young people in the Novosibirsk region of Siberia, who were born in the second half of the 1980s and who began school in the 1990s during a period of $

The study formed part of a larger project with Professor Yurii V. Popkov, Siberian Branch, Russian Academy of Sciences. It was supported by awards from the British Academy and the Economic and Social Research Council (R000220506/ R000223988). Corresponding author. E-mail addresses: [email protected], [email protected] (A. Glendinning). 0277-9536/$ - see front matter r 2007 Elsevier Ltd. All rights reserved. doi:10.1016/j.socscimed.2007.05.012

profound societal change and uncertainty in Russia. By the time the fieldwork was undertaken for the study, this cohort of young people were in the ninth grade (i.e. 14/15 years old) at a critical juncture in their education and contemplating their futures beyond secondary school. The dislocations of the 1990s—with the ‘reform’ of centralised state institutions, administrative structures, and state welfare and social support systems—have had a severe impact on people’s lives in Siberia (Humphrey, 2002). Change and uncertainty are seen to pose new ‘risks’ for youth in particular, with life chances and choices seen as increasingly tied to socio-economic status and locality (Zubok, 2005). In the study, the

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lives of young people in the major regional city of Novosibirsk are contrasted with those of young people in small towns and villages of the Novosibirsk region. The aim of the study is to examine young people’s life circumstances and the implications for mental health in context. The study asks:

   

Do health profiles in general differ between the city and small communities? Do mental health profiles in particular differ between the city and small communities Do socio-economic circumstances affect health in general, and mental health in particular, differently in the city and small communities? And allowing for socio-economic circumstances, do family, school, peers and the wider community context affect mental health differently in the city and small communities?

We know adolescent children’s general health profiles are worse in Russia. A comparative picture is provided by the 2001/2 WHO-HBSC crossnational study, which was undertaken in 35 countries and regions of Europe and North America (Currie et al., 2004). Russian school children were second or third from bottom of the international league tables of ‘poorer’ health: more than one-third of the nationwide sample of 15 year olds rated their general health as ‘less than good’ (Torsheim, Va¨limaa, & Danielson, 2004, p. 58). Material deprivation was also evident among Russian youth. Comparisons with other countries put family households in second last place (Boyce & Dallago, 2004, p. 21) and poorer general health was correlated with material deprivation (Holstein, Parry-London, Zambon, Currie, & Roberts, 2004, p. 167). Participants in the WHO-HBSC survey were also asked about more specific health complaints, including the extent to which they had experienced feeling ‘irritable’ ‘nervous’ or ‘low’ but extended profiles of mental well-being are not available. Nor did the study include consideration of urban–rural differences in young people’s health generally, or their mental health. Few studies have used standardised and validated measures of mental health problems with representative community samples of Russian children and adolescents. However, a study of some 450 school children has been undertaken in ten schools in the city of Novosibirsk, using internationally recognised measures (Goodman, Slobodskaya, & Knyazev,

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2005). A screening measure of psychopathology was used and a more detailed assessment was carried out with ‘screen-positive’ and some ‘screennegative’ children. The overall prevalence of ‘psychiatric disorder’ among 11–14 year-olds was 24 per cent, and one-half of that group was diagnosed as having an ‘emotional disorder’, that is about one-ineight 11–14 year olds in the city. Risk factors included the family environment and doing badly at school, but neither family type nor socio-economic circumstances were associated with children’s mental health. The present study is able to extend the picture of young people’s health in Russia, by comparing the lives of youth in small communities of Novosibirsk region with those of youth in the regional capital of Novosibirsk, and also by examining what the implications are for mental health in these different contexts. Given the frequent impoverished circumstances of families in the Russian countryside, the expectation is adolescent children’s mental health should be the cause for much concern there (Williams, Chuprov, & Zubok, 2003), especially among youth in rural society who are at the end of secondary education, when they must contemplate their futures beyond school. Data and methods The study was part of a larger collaborative project using a mixed-methods approach to research with youth in Siberia. The project began in 2001 with preparatory fieldwork with young people in the age range 15–21 years, and discussions with educators, youth workers and administrators in the Novosibirsk region. According to our discussions the consensus view was the term ‘youth’ could be applied broadly to those in the age range 15–29 years, although Russian ninth graders (14/15 year olds) in their final year of compulsory schooling were also referred to as children. Study settings Novosibirsk is Russia’s ‘third city’, with well over one million inhabitants, and it is a major economic, administrative and educational centre in Siberia. Similar numbers of people live in the surrounding region (Novosibirskaia oblast’) equally spread among ‘urban’ and ‘rural’ settlements. The study design reflects these population distributions between the city and countryside. In the city, schools in the centre, labour districts and outskirts, and in worse and better off areas, represented a range of state, specialist, elite, religious and private education.

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In the surrounding region, the sample was clustered within three administrative districts at increasing distances from the city, centred on Iskitim (approximately 50 km, 70,000 people), Chulym (approximately 150 km, 14,000 people) and Dovol’noe (approximately 250 km, 8000 people). The large town of Iskitim is close to the city, but with the collapse of the centralised economy, as elsewhere, it lost much of its manufacturing base and struggled through the severe social and economic disruptions of the 1990s. Some villages in the surrounding district of Iskitimsk now serve as dormitory settlements for the city, whereas others remain dependent on agricultural enterprises, such as dairy production. Chulym is a railway town on the Trans-Siberian Railroad (trans-sib). This small town is not well off but it has good communications and there remain light industry and services associated with the railway, and, for example, bakery, footwear, leather clothing and forestry enterprises. In Dovol’noe, transport and communications are poor and local employment is based on primary industries and services but townspeople still see their situations as better off than life in the surrounding villages. In the countryside, rural communities are not comprised of scattered homesteads and farms but more often reflect the former collective nature of socialist state agriculture (kolkhoz). Village households often rely on subsistence farming (Clarke, 2002). Data collection Following on from the project development work, a school-based survey was undertaken by means of a self-completion questionnaire with ninth graders in the academic year 2002/2003. Complementing this, semi-structured interviews were conducted with a sub-sample of survey participants in all of the study schools. Once permissions for access had been negotiated, the survey was administered to small groups of students by two young Russian members of the research team. Students were curious about the study and keen to be involved (with the exception of one group in one urban school). In the city students from 12 schools took part in the study (184 girls and 163 boys). In the large town of Iskitim two schools were selected (31 girls and 34 boys). Two schools were selected in the small town of Chulym (31 girls and 29 boys) and another two schools in the township of Dovol’noe (34 girls and 28 boys). In addition, the local school was selected in each of three villages at varying distances from the district centre of Iskitim (33 girls and 25 boys) and another

three village schools were selected from outside Chulym (28 girls and 28 boys). Finally, four village schools were selected from among the more remote rural communities outside Dovol’noe (32 girls and 32 boys). Between two and four survey participants per school also provided in-depth, interview accounts. No school staff were present during the survey sessions, or interviews. After follow-up of absentees and anonymous post-back, an overall survey response rate of 95 per cent was achieved. An OECD-sponsored survey in 2000, with robust design protocol and excellent response rate, found nationally the prevalence of frequent absences from school among Russian 15 year olds was 10 per cent (Adams & Wu, 2002). In our regional sample, 11 per cent of ninth graders reported being absent from school ‘without permission’ in the course of the previous year on a weekly basis or more often. In what follows, study participants from the two schools in the large town of Iskitim are not included in the analysis because our aim here is to contrast young people’s lives in small communities of the Novosibirsk region with the major regional centre. Sample socio-demographic characteristics: Characterisations of the family’s situation were based on young people’s self-reports, including household composition, parents’ education and economic activities and family circumstances. The fieldwork team also checked these details with survey participants on a confidential, one-to-one basis. The qualitative interviews were also used to confirm, and for participants to elaborate on, their situations. Given circumstances nationwide, detailed information necessary to produce a classification of occupations was not collected in the 2001 Russian Census. Therefore, family affluence and parents’ education are used in place of an occupational classification in the present study. The measure of family affluence (FAS) was the same as used in the 2001/2 WHO-HBSC survey (Boyce & Dallago, 2004, p. 15). As to parents’ education, cross-checks built into the project design established whether young people were certain when their parents had no qualifications or only a basic education; or else, when their parents had gone on to study for more qualifications at higher, further or special levels of education. However, they were less clear about differentiating further. Therefore, responses were collapsed into three broad categories, representing ‘no secondary’, ‘secondary’ and ‘advanced’ education. Next, the education levels of

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both parents were compared and the highest level used. In the case of lone parent households, the single parent’s education level was used. In effect our classification identifies households where parents are less well educated, namely: households where parents had little or no education, and households where parents only had experience of education at the compulsory school level, compared to those households where at least one parent had experience of ‘advanced’ education. As shown in Table 1, parents in small communities of the region were generally much less well qualified than those in the city. Young people said their parents had no experience of ‘advanced’ education in the majority of small community households compared to only a minority of city households. For the parents’ generation, the Soviet system had been committed to universal secondary education and reductions in the numbers receiving only a primary or incomplete high school education in rural areas was the most significant reform between the 1960s and 1980s (Sobkin, 2001). State support had also been guaranteed for free education up to the eleventh grade, rather than the current ninth grade. The percentage of households in small communities where young people said their parents did not hold at least a secondary education was 14 per cent compared to only two per cent in the city, which corresponded to estimates for households with same-age children taken from a Goskomstat micro-census in the region (Goncharova, 2004). In villages, 18 per cent of our sample represented

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households where parents held only a ‘basic’ education. In villages in the Chulymsk and Dovolensk districts, two out of three households were employed in agricultural production. Households in small communities were also less well off on the family affluence scale (FAS, see Table 1). Young people from households in small communities were much more likely to report material disadvantage compared to respondents in the city, or to the national figure from the WHOHBSC survey (54 per cent in the city, 78 per cent in small communities and 58 per cent nationally). The composition of the sample reflected the emergence of single parenthood in Russia (Klugman & Motivans, 2001), although as found in the WHOHBSC survey, three-quarters of our sample continued to live in a household with both of their parents (see Table 1). The proportion of lone-parent households was lower than in the WHO-HBSC survey (13 per cent compared to 17 per cent) but this was balanced by those young people who were not living with either of their parents, for example with grandparents instead (4 per cent compared to a figure of only 1 per cent in the nationwide survey). Thus, despite school-based methods of data collection, with the possible absence of ‘socially excluded’ youth from schools, the study can still be said to represent young people in poorer circumstances in the Novosibirsk region. Measures of mental health and self-rated general health: Our analysis of mental health focuses on feelings of self-worth and depression. The survey

Table 1 Household socio-economic status and circumstances in the city and small communities of the Novosibirsk region 14/15 year-olds, Siberia 2002 Column percentage (%) Parents’ highest education

Advanced Secondary No secondary

Family affluence (FAS)

Low 0–3 Mid 4–5 High 6–7

Family type

Complete Step-parent Lone-parent Others

Bases, N ¼ 100%

City

Small communities

Total

73 25 2 100 54 36 10 100 76 8 13 3 100 341

39 47 14 100 78 20 2 100 75 8 13 4 100 296

57 35 8 100 65 28 7 100 76 8 13 3 100 637

Notes: a2001/2 WHO-HBSC survey (Currie et al. 2004: Figs. 2.6 & 2.7). po0,01.

Russian Federationa – – – 58 35 7 100 75 7 17 1 100

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included measures of: general self-esteem (ten items, Rosenberg, 1965, a ¼ 0.67); depressive mood (six items, Kandel & Davies, 1982, a ¼ 0.69); psychological distress (twelve items, Goldberg & Williams, 1988, a ¼ 0.67); and subjective health complaints, such as irritability, anxiety, difficulties sleeping, headaches and abdominal pain (eight items, Haugland & Wold, 2001, a ¼ 0.80); and also a measure of self-rated health generally (‘How do you assess the state of your health in the course of the previous year?’ ‘Excellent’, ‘Good’, ‘Fair’ or ‘Poor’). The terms ‘less than good’ and ‘poorer’ are used in the text to refer to those participants who rated their general health as only ‘fair’ or ‘poor’. Data reduction of responses to the inventory of subjective health complaints showed these were made up of two factors, representing ‘somatic’ and ‘affective’ components (Principal Components Analysis PCA, Kaiser–Meyer–Olkin KMO ¼ 0.81). In the event there was a high correlation between scores on the depressed mood scale and the full subjective health complaints scale (r ¼ 0.66) and a further correlation between scores on the depressed mood and the psychological distress scales (r ¼ 0.50). Depressed mood was also correlated with general self-esteem scores, but only moderately (r ¼ –0.39). The depressive mood scale has been validated in identifying ‘severe’ cases of depression in adolescent populations (Kandel & Davies, 1982). In respect of the measure of self-rated health, follow-up interviews of survey respondents elsewhere about their responses to this question have shown people’s self-assessments are based primarily on the absence of ill health, modified by the severity, duration and restrictions posed by ill health, but also connected to their life situations, and for some, fitness and health behaviours (Manderbacka, 1998). In what follows, self-rated health is viewed as a global measure and it is used to compare the specific findings for mental health with young people’s health overall. Measures of family, school, peers and wider community life: Data reduction was used (PCA with oblique ‘oblimin’ rotation) first to identify components from each of four modules of questions (i.e., modules relating to family, school, peers and community life) and second to identify general factors that underlay young people’s experiences and views of their lives and situations. Details of young people’s responses to the four modules of survey questions and their analysis by locality are provided in a technical report (Pak, Glendinning, &

Popkov, 2003). Young people also spoke at length in the semi-structured interviews of their lives in their home communities, and with their families, peers and at school (Glendinning, Pak, & Popkov, 2004). In the final analysis, the more general social–psychological factors derived from data reduction echoed key themes in the qualitative interview accounts, and therefore, they were interpreted to represent young people’s evaluations of: family support and acceptance; conflict and control at home; engagement with school; peer support and social isolation; perceived constraints within the wider community; and lastly, future prospects for youth in their home areas. In more detail, characterisations of family life were derived from questions taken from a rural study in northern Scotland and mid Sweden (Glendinning, Kloep, & Hendry, 2000) and an urban study in the large, post-industrial city of Glasgow (West & Sweeting, 2004; Young, Sweeting, & West, 2000), and for comparative purposes, from the 2001/2 WHO-HBSC study (Currie, Samdal, Boyce, & Smith, 2001). In addition, the brief form of Parker’s ‘parental bonding instrument’ for adolescent research was included (Klimidis, Minas, & Alta, 1992; Parker, 1990). The questions on family life and relations were translated and piloted locally before inclusion. The final questionnaire contained some thirty questions in this area, for example including questions on feelings of support (e.g., ‘My parent/s understand my problems and concerns’), control (e.g., ‘My parent/s try to control everything I do’) and autonomy (e.g., ‘My parent/s like me to make my own decisions’). Generally, the module of sixteen questions concerning school life represented feelings of support and participation (e.g., ‘I am able to ask for assistance when I need’), motivation and inclusion (e.g., ‘I find the work at school interesting and useful’) and control and disaffection (e.g., ‘I get fed up being told what to do’). And the module of eighteen questions concerning peer relations represented feelings of support (e.g., ‘I have friends I can depend on’), conflict (e.g., ‘I often argue and fall out [with peers]’) and isolation (e.g., ‘I worry about being rejected [by peers]’). Characterisations of community life were developed by piloting questions used previously in northern Scotland and mid Sweden (Glendinning, Nuttall, Hendry, Kloep, & Wood, 2003). Young people were asked about a range of issues including questions about social relations and levels of trust

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locally, as well as questions about amenities, transport and infrastructure, and housing and employment in their home communities (Glendinning et al., 2004). Our analysis indicated responses to this module of questions about the wider community can be represented as evaluations of prospects for youth locally (e.g., ‘The future looks good for young people who stay on here’), quality of life (e.g., ‘This is a good place for young people like me to stay’), feelings of support (e.g., ‘There are people here I can rely on to talk to [outside of my family]’), feelings of constraint (e.g., ‘It’s hard to be yourself here’), feelings of insecurity (e.g., ‘It’s not safe to go out at night here’) and lack of amenities (e.g., ‘There’s nothing for young people to do here’).

Findings Family, school, peers and wider community life: Table 2 provides a breakdown of mean factor scores from the PCA for youth living in the city and small communities. Young people’s overall feelings of emotional support were found to vary little between contexts, and quality of family relations and peer support were generally high throughout the region. The family support factor included assessments of degree of encouragement, talking, listening and understanding, and of care, love and attention from parents. To illustrate with a single item, across the different study settings most ninth graders reported ‘getting on well’ with their parents (ranging from 82 per cent to 88 per cent). Urban–rural differences Table 2 Family, school, peers, community life in the city and small communities of the Novosibirsk region 14/15 year-olds, Siberia 2002 Mean standardised factor scores

City

Small communities

Family support and acceptance Family control and conflict School integration and commitment Peer support Community constraints and insecuritya Poor prospects for youth locally Bases, N

0.02 +0.07 0.14 0.02 +0.10 0.41 345

+0.02 –0.07 +0.16 +0.01 –0.09 +0.40 296

Notes: Factor scores derived from PCA of four modules of questions relating to family, school, peers and community life (KMO ¼ 0.71). a However, perceived constraints were less evident among village compared to small town youth. po0.01.

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were evident in school integration. Young people in small communities were highly positive about their schooling compared to city youth overall. However, the most marked differences between contexts lay in the divide in evaluations of the future prospects for those who stayed on in their home areas. In Novosibirsk these were relatively positive (representing some 60 per cent of city youth) while in small communities young people were mostly negative about prospects in their home areas (only 20 per cent of village youth expressed optimism about staying on locally). General health: Thirty nine per cent of the girls and 24 per cent of the boys in our sample rated their health as less than good. For either gender, these estimates are one-eighth less than the national figures of 44 per cent for 15 year old girls and 27 per cent for 15 year old boys from the WHO-HSBC survey, but that study asked, ‘Would you say your health is Excellent, Good, Fair or Poor?’ while the present study asked about health in general over ‘the previous year’. Gender differences in self-rated health are not specific to Russia, although the WHO-HSBC survey found such differences were larger than in most Western countries (Torsheim et al., 2004, p. 58). In our regional sample, young people in small communities were more likely to report poorer general health compared to those in Novosibirsk (36 per cent compared to 27 per cent in the city) but poorer general health was focused among lessadvantaged households in small communities. As shown in Table 3, lower levels of parental education, material deprivation and living in a lone-parent context were all associated with poorer general health in small communities only. Low socioeconomic status appears to explain the link between the family context and poorer health in general. In small communities 68 per cent of adolescent children from less educated, lone-parent family contexts rated their general health as less than good. The figure for materially deprived lone-parent households was correspondingly high. Thus, the study points to general health inequalities patterned by locality and tied to the household’s socio-economic status in small communities of the region. Mental health: We have seen young people living in small communities reported poorer general health overall compared to the city. However, the pattern was reversed for measures of self-worth and depression. Young people living in small communities were consistently more positive in their

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Table 3 Self-rated general health and household socio-economic status and circumstances in the city and small communities of the Novosibirsk region 14/15 year-olds, Siberia 2002 Prevalence of poorer health (%) Bases, N ¼ 100% Parents’ highest education

City

Advanced

Other households Family Affluence (FAS)

Deprived (Low FAS) Other households

Family type

Lone-parent Other households

Total

Small communitiesa

27%

26%

243 26%

115 42%**

91 29%

178 39%**

182 24%

225 24%

155 26% 43 27%

67 51%* 35 34%

294 27% 334

259 36%* 292

Notes: ‘Poorer’ means general health over the previous year rated as only ‘fair’ or ‘poor’. *po0.05; **po0.01. a Two-thirds of the children from less educated, lone-parent families reported poorer general health, and the prevalence was correspondingly high among materially deprived, lone-parent households.

evaluations of self-confidence and mental health (see, Table 4). Prevalence of ‘low’ self-worth stood at 12 per cent in small communities against 19 per cent in the city. The figure for ‘severe’ depression was 9 per cent compared to 14 per cent. As further confirmation, the estimate for psychiatric ‘caseness’ (i.e., with four or more symptoms of psychological distress on the 12-item General Health Questionnaire GHQ12, Goldberg & Williams, 1988) was 17 per cent in small communities compared to 28 per cent in the city. In their more detailed assessments of mental health, Goodman et al. (2005) estimated the prevalence of ‘psychiatric disorder’ as 24 per cent among 11–14 year olds in the city. By means of follow-up psychiatric interviews, they estimated the prevalence of ‘emotional disorder’ as one-half of that figure. Using less-exact methods, our estimate of ‘caseness’ is 28 per cent among an older age group of ninth graders in the city, and our estimate for ‘severe’ depression is 14 per cent.

Table 4 Mental health in the city and small communities of the Novosibirsk region 14/15 year-olds, Siberia 2002 Prevalence of poor mental well-being (%) I II III Bases, N

General self-esteem: ‘low’* Depressive mood: ‘severe’* Psychological distress: ‘psychiatric caseness’**

City

Small communities

19 15 28

12 9 17

336

290

I. Responded negatively to more than five questions from the 10item self-esteem scale. II. Respondents with a score of 23 or more out of 30 on the sixitem depressive mood scale. III. Reported four or more symptoms of psychological distress from the twelve-item GHQ scale. *po0.05; **po0.01.

Self-worth: To move the analysis on, we examine next the joint effects of socio-economic status (see, Table 1) and social–psychological factors (see, Table 2) on mental health in the city and small communities of the region. Table 5 reports the results of a regression analysis of the joint effects of gender, home circumstances, family, school, peers and community life on self-worth. The analysis identifies factors that are specific to small communities, and others specific to the city. Family support was correlated with higher self-esteem scores in small communities only. Girls were also less positive than boys in small communities only, and where it was felt, the constraining nature of community life was associated with lower self-esteem scores. By contrast, education stood out as a significant factor in the city only. Those who were positive about their schooling reported higher self-esteem scores. As to factors common to the city and small communities, efforts by parents to impose what are seen as ‘unreasonable’ or ‘inappropriate’ controls (e.g., ‘My parent/s treat me like a small child’) and conflicts about friends, appearance and schoolwork were associated with lower self-esteem scores in both contexts, but the negative effects on self-esteem were stronger among city youth. One factor accorded equal weight in the city and small communities was peer support, which was seen as important to self-worth. However, household circumstances appeared to play little role in youth self-worth, with the specific exception of parents’ education in the city. Those city youth who come from better educated backgrounds reported higher self-esteem scores.

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Table 5 Factors affecting self-worth in the city and small communities of the Novosibirsk region (identified from regression analysis using backward elimination) 14/15 year-olds, Siberia 2002 I. City (N ¼ 326, R2 ¼ 0.19) Included variables Parents’ education (advanced)

II. Small communities (N ¼ 284, R2 ¼ 0.16) b

Included variables Gender (female)

b 0.16**

Family support Family constraints

0.14 * –0.16**

Peer support Community constraintsa

0.27** –0.12*

Excluded variables Type of locality (village)

part’corr. 0.01

Parents’ education (advanced) Family affluence (FAS low) Family type (lone-parent)

0.02 –0.07 –0.04

0.14*

Family constraints School commitment Peer support

–0.27** 0.13** 0.29**

Excluded variables

part’corr.

Gender (female)

–0.05

Family affluence (FAS low) Family type (lone-parent) Family support

–0.03 –0.08 0.02

Community constraints Poor future prospects

–0.04 –0.08

School commitment Poor future prospects

0.03 –0.02

Dependent variable: 10-item self-report general self-esteem scale. Notes: In analysis II, type of locality is also included to allow for possible differences between small town and village youth, since in Russia small towns are classified administratively as ‘urban’.aFitting an additional interaction effect showed ‘constraints’ related to small town, not village youth. *po0.05, **po0.01.

Depression: Table 6 reports the results of a parallel regression analysis with depressed mood replacing self-worth as the dependent variable. Factors specific to small communities centred on family support, and peer support. Thus, a supportive family and peer group were associated with lower depressed mood scores in small communities only. By contrast, factors specific to the city centred on education and future prospects for youth. A positive orientation to school was associated with lower depressed mood scores among city youth, while pessimism about future prospects was associated with higher scores. Thus, it is only in the city that poor prospects locally and disaffection with education were associated with a sense of depression. As to factors common to the city and small communities, feelings of depression were associated with perceived constraints within the family and wider community in both contexts, for example feelings about the monitoring of behaviour (e.g., ‘Adults interfering in young people’s business’). Gender was a further common factor, and here the effect of gender was stronger in small communities. Boys in small communities were less likely to report

depression. Tests for effects of household circumstances on youth depression were inconclusive. Discussion Mental health in context: Our analysis of the responses of young people to our questionnaire point to distinctive social factors, which affect mental health differently in the city, and small communities of the Novosibirsk region. As far as we can tell from our study, these social factors do not single out loneparent families (nor absent fathers) nor do they implicate household material deprivation as direct causes of mental ill health, either in the large city or small communities of the region, contrary to expectations that family disruption and hardship lead to marked psychological difficulties of adjustment for Russian youth, and more so in rural society (Chuprov, Zubok, & Williams, 2001). What we do find is socially excluded youth in the major city of Novosibirsk experience the poorest mental health. Wallace and Kovatcheva (1998) place such processes of social exclusion in post-soviet societies in historical context. In our analysis, social exclusion relates to disaffection with education and a lack of family

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Table 6 Factors affecting depression in the city and small communities of the Novosibirsk region (identified from regression analysis using backward elimination) 14/15 year-olds, Siberia 2002 I. City (N ¼ 329, R2 ¼ 0.22)

II. Small communities (N ¼ 287, R2 ¼ 0.27)

Included variables Gender (female)

b 0.22**

Family constraints School commitment

0.28** –0.18**

Community constraints Poor future prospects

0.19** 0.15**

Excluded variables

Part’corr.

Parents’ education (advanced) Family affluence (FAS low) Family type (lone-parent) Family support

–0.05 0.03 0.01 –0.02

Peer support

–0.09

Included variables Gender (female) Family support Family constraints

b 0.36** –0.16** 0.18**

Peer support Community constraints

–0.13* 0.20**

Excluded variables Type of locality (village) Parents’ education (advanced) Family affluence (FAS low) Family type (lone-parent)

part’corr. –0.01 –0.09 0.10 0.01

School commitment

–0.02

Poor future prospects

0.10

Dependent variable: 6-item self-report depressive mood scale. Notes: In analysis II, type of locality is also included to allow for possible differences between small town and village youth, since in Russia small towns are classified administratively as ‘urban’. *po0.05, **po0.01

resources to engage with the reformed education system in the new Russia (Webber, 2000). Yet this only applies to a minority of youth despite ‘deprived’ households representing the majority of city families. When we asked them, only about 20 per cent of our respondents said they were less than satisfied with their lives in the city. Where it was most expected, in small communities adolescents’ mental health is undifferentiated by the rural family’s socio-economic status, including parents’ education levels. Adolescents’ mental health appears generally better there, not worse, compared to the city. Notwithstanding better mental health profiles in small communities, we find adolescents’ general health overall is poorer in small communities compared to the city, and in small communities poorer general health is associated with low socioeconomic status. There is no contradiction here with better mental health in the same small communities. Our findings illustrate the multi-dimensional nature of health, and that the social patterning of different components of health and ill health are context dependent (West & Sweeting, 2004). In the city mental health is patterned by education; in small communities poorer health overall, but not mental health specifically, is patterned by socio-economic disadvantage.

We know a great deal about young people’s situations and lives in small communities of the region from the qualitative interviews conducted by the Russian researcher Ol’ga Pak as part of our larger project (Glendinning et al., 2004). Young people in the city and small communities draw on different family resources in their hopes of securing a future, and paradoxically, despite impoverished family circumstances, this has positive implications for adolescent children’s mental health in rural society. As we have already mentioned, engagement with education acts to differentiate between city youth in how they feel about their situations and futures. Socially excluded youth feel badly about themselves, given the supposed opportunities the major regional centre of Novosibirsk has to offer. Drop out rates after ninth grade are lower in more prosperous regions of Russia, which further marginalises early leavers in the city. Sobkin (2001, p. 295) concludes the changes in education in the 1990s were concerned, above all, with ‘processes of social stratification’ and Webber (2000, p. 181) provides a sobering analysis of exclusion in urban contexts, and the situation for early leavers, including a report from one school in Novosibirsk. In small communities families adopt a joint response to widespread hardship and adversity

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(Glendinning et al., 2004) and because adolescent children are an integral part of the household, with roles and responsibilities, they seem mentally resilient. In her interviews Ol’ga Pak found gaining an ‘advanced’ education—by staying on at school, entering further education or preparatory higher education college—had reacquired importance for young people and their families, and she did not often find evidence of a ‘generational divide’ within rural households. It is important to realise that in rural communities most parents and their adolescent children share common values and aspirations, also shared by the peer group (odnoklassniki). The ‘traditional’ values of hard work (trud) and cooperation (collectiv) continue to frame young people’s lives there, and children respect their parents’ advice and guidance. Rural youth are also highly positive and respectful of their teachers and schools irrespective of the quality of provision, despite a seeming lack of ‘autonomy’ in relationships with teachers, which can be at odds with an imperative to assume adult status. Young people and their parents must work together to establish a future that might secure a ‘comfortable’ life, where social capital in this context means the resources associated with kin-based and informal social networks. The reciprocity and obligations of social relations in small communities should not be underestimated, and is important for positive selfworth and mental health. Comparisons with youth elsewhere: Our findings are reminiscent of Elder and Conger’s (2000) conclusions, which were based on extensive study of rural decline, adversity and resilience among families with adolescent children in small communities of the mid-western United States during the ‘great farm crisis’ of the 1980s. In quite another context, adolescents in small communities who came from families with a history of ‘ties to the land’, and especially those from families who continued to farm, drew on family social capital embedded in community ties in positive psychosocial adjustment, self-confidence, social relations and commitment to school, compared to their nonfarm counterparts. Farm children valued their productive roles and responsibilities and were more likely to seek the advice of parents and grandparents. One need only consider rural youths’ very different understandings of leisure (svobodnoe vremja or ‘free time’) in small communities of the Novosibirsk region compared to youth in the ‘modern’ city in order to appreciate the connection.

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Some factors appear common to mental health in the city and small communities, for example feelings that parents imposed ‘unreasonable’ and ‘inappropriate’ controls, with conflicts about appearance, friends and schoolwork. Allied to perceived constraints at home, feelings of constraint in the wider community were also associated with depression. The negative effects of parental intolerance and the perceived constraints of small community life on depression appear general to rural adolescents (Glendinning et al., 2003). Peers also appear central to feelings of self-worth irrespective of context, although in Russia peer groupings may assume different forms in small communities compared to the city neighbourhood (dvor) (Pilkington, 2004). Self-worth associated with the peer group seems protective of depression in small communities. As we have noted, the peer group is not of necessity antagonistic to the values of parents in rural society, because rural youth’s concern was to become adult (solidnye). In his comparative study of childhood in the US and USSR, Bronfenbrenner (1970) saw shared values as a widespread phenomenon among the previous generation in Russia, and as very different from the individualism and separate social worlds of the family and peers in the United States. In the wider project, unlike the city, we found little to support the idea of ‘individualisation’ in rural society (Furlong & Cartmel, 1997) or more specifically Russian concerns about the ‘westernisation’ of youth (Pilkington, Omel’chenko, Flynn, Bliudina, & Starkova, 2002). Pilkington (1996) has looked at issues of gender and generation in Russia but more in urban contexts. Given we did not find a marked ‘generational divide’ in rural society, we were not surprised to find our respondents expressed ‘traditional’ views on gender roles, especially rural males (80 per cent of boys and the majority of girls in small communities agreed with the statement, ‘a husband’s [man’s] job is to earn money; a wife’s [woman’s] job is to look after the home and family’). Most young women imagined they would have to leave their home communities because it would be impossible to stay. Horizons often focused on larger towns rather than the perceived risks associated with moving to the regional capital, and career choices were highly gendered. A subtext through Conger and Elder’s (2000) study in the US was that farming communities support boys. More overtly, Dalhstro¨m (1996) describes small communities in northern Norway

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as a ‘male periphery’ with an imperative for young women to leave. Glendinning et al. (2003) found in small communities of northern Scotland adolescent girls were less likely to want to stay than boys, although girls were more likely than boys to consider returning to settle down after a period away. At the end of compulsory schooling, girls who pictured themselves as staying on in the home area reported lower self-esteem but boys who wanted to stay on reported higher self-esteem compared to other youth locally. Nonetheless, it was girls who planned definitely to leave for good who were the most likely to report depression. There may be ironies in young men’s choices to stay on. In the south west of Ireland, young men who chose to stay often experienced poor mental health in the longer term (Nı´ Laoire 2000, 2001) and those young men who had succeeded locally attributed this to good business and management practices rather than a commitment to farming as a way of life, or family tradition (Nı´ Laoire, 2004). What we find in Siberia, which has not been examined in youth research before, is a larger gender divide in adolescent mental health in small communities compared to the city. Extensions to the study: Novosibirsk is one of Russia’s major administrative and economic centres and our study has not considered young people’s situations in other urban contexts where families and their children may experience much hardship (White, 2004). Iskitim serves as an example in our study (Popkov, 1998) but because we were only able to contact a total of 65 young people in Iskitim we do not have sufficient data accurately to represent the situations of youth in such a large town. Provisionally, the prevalence of psychological ill health among the group of respondents in Iskitim matches our estimates for the neighbouring city of Novosibirsk (14 per cent reporting ‘severe’ depression compared to 15 per cent in the city) but the overall prevalence of general ill health matches our estimates for small communities of the region instead (38 per cent of our sample in Iskitim reporting poorer general health compared to 36 per cent in small communities). In terms of health profiles, Iskitim and other larger towns may represent the worst of both worlds for Russian youth. There, in the absence of social capital associated with informal social support networks in small communities, it appears urban social exclusion operates adversely to affect mental health, while deprived socio-economic circumstances results

in more general ill health among adolescent children. Finally, unlike many other regions of Siberia, the Novosibirsk region, and our sample, is not ethnically diverse and ethnicity is a further factor in locating young people’s mental health in context in Siberia.

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