Does problem behaviour affect attrition from a cohort study on adolescent mental health?

Transcription

1 European Journal of Public Health, Vol. 21, No. 3, ß The Author Published by Oxford University Press on behalf of the European Public Health Association. All rights reserved. doi: /eurpub/ckq078 Advance Access published on 22 June Does problem behaviour affect attrition from a cohort study on adolescent mental health? Sari A. Fröjd 1, Riittakerttu Kaltiala-Heino 2,3, Mauri J. Marttunen 4,5,6 1 Tampere School of Public Health, University of Tampere, Tampere, Finland 2 Medical School, University of Tampere, Tampere, Finland 3 Psychiatric Treatment and Research Unit for Adolescent Intensive Care (EVA), Tampere University Hospital, Tampere, Finland 4 Department of Psychiatry, Kuopio University Hospital, University of Kuopio, Finland 5 Department of Mental Health and Alcohol Research, National Institute for Health, and Welfare, Helsinki, Finland 6 Department of Adolescent, Psychiatry Peijas Hospital, Helsinki University Hospital, Vantaa, Finland Correspondence: Sari A. Fröjd, Tampere School of Public Health, University of Tampere, Tampere, Finland, tel: , fax: , sari.frojd@uta.fi Received 4 September 2009, accepted 26 May 2010 Background: Most surveys are plagued by significant numbers of non-respondents. In psychiatric epidemiology, differences in levels of psychopathology are often assumed between respondents and non-respondents. However, studies on attrition are rare, especially in child and adolescent populations. The present study sought to estimate the association of depression, anti-social behaviour with attrition from a cohort study among adolescents. Methods: The adolescent mental health cohort study (AMHC) is a prospective follow-up study on prevalence and determinants of mental health problems and risk behaviour among Finnish adolescents at two study sites. Subjects of the final baseline sample (n = 3278) were reached for a 2-year follow-up. Differences in data collecting methods between the study sites yielded different response rates (78% vs. 51%). Chi-square statistics and logistic regression models were computed to estimate the effect of two types of problem behaviour on attrition. Results: Depression at baseline was associated with higher probability of attrition at follow-up. School performance was a stronger predictor of attrition than problem behaviour. The models predicted non-response in the study site with mainly school-based surveys but not in the study site with mainly postal surveys. Conclusion: Internalizing problem behaviour may be underrepresented in adolescent mental health surveys. School performance is strongly associated with attrition. Hence, special attention should be paid to designing questionnaires targeting adolescents. Keywords: attrition, adolescents, survey... Introduction ow response proportion has often been associated with high Lprobability of response bias; although high attrition may not automatically result in non-response bias in the data. 1 Studies targeting individuals with psychological problems may have special problems in data collection. Data collection among adolescents may suffer from multiple practical obstacles and excess attrition due to the turbulent period of life among the respondents. The response rates in surveys have been declining alarmingly in the recent years. 2 4 The well designed and resourced National Comorbidity survey replication in the beginning of the 21st century yielded a response rate of 71%, 5 and response rates considerably lower have been frequently reported in this century. 4 Due to person identifiable data collection, cohort studies may be especially vulnerable to high rates of non-response. Attrition may be associated with background variables, such as socio-economic status (SES) or age, which leads to problems in generalizability of the results. It may also be associated with the outcome variables, resulting in prevalence or incidence rates being over- or under-estimations. Psychiatric epidemiology may suffer from extra problems in data collection due to the delicate nature of information gathered about possibly stigmatizing social and health problems. Empiric support for this assumption is hard to find, however. There are two determinants constantly reported to affect attrition in studies concerning psychiatric epidemiology: sex and socio-economic background. Females and persons with higher SES seem to respond more frequently than males and persons with low SES. 6 8 Among adolescents, SES is a more complicated concept. Indicators of socio-economic situation, poor academic performance and parental educational level, have been associated with nonresponse Another problem possibly affecting participation in surveys on psychological symptoms is the effect of symptoms on performance. Depression may lower initiative and individuals with behavioural problems may consider researchers as authorities deserving nothing but resistance, for example. Non-response among individuals with severe symptoms causing disability will result in differences in levels of psychopathology between respondents and non-respondents. Lower response rates among individuals with psychopathology have been suggested in adults, 7,8,12 whereas in samples of children or adolescents the reports in general show no significant associations between responding and symptom levels. 3,13,14 Data assessing characteristics of non-respondents is hard to obtain. In longitudinal studies, selection typically occurs already in the first response wave when some of the subjects invited refuse to participate. Follow-up surveys among non-respondents are likely to suffer from additional response bias. One way of estimating the response bias in prospective

2 Adolescent problem behaviour and attrition 307 longitudinal surveys is to compare the characteristics of respondents in different response waves. In the present study, the first survey covered all ninth-grade pupils in the study location, and 97% of the original study population completed the baseline survey. We aimed at studying, whether internalizing (depression) or externalizing (antisocial behaviour) problem behaviour at baseline affect attrition in follow-up. Methods The study design was approved by the ethical committee of the Pirkanmaa Hospital District. Parents of the pupils in participating schools were informed of the study, but parental consent was not requested because the Finnish law allows independent decision on participation for adolescents aged 15 years. Written informed consent was obtained from the participants. Baseline data Ninth-grade students (aged years) of all the 37 Finnish-speaking secondary schools in Tampere and Vantaa were identified in the school registers and invited to complete a person-identifiable questionnaire during a school lesson supervised by a teacher, who was instructed not to interfere with the data collection. Students were provided with information of the study, its purpose and the duration of follow-up. The questionnaire comprised of structured questions about school performance, symptoms of different psychiatric disorders, frequency of different types of risk-taking behaviour, occurrence of life events, perceived social support and self-esteem. Questionnaires were returned in sealed envelopes collected by the research coordinator. For students absent from the school on the original survey day, a separate opportunity to participate was offered. For students not present on either occasion, the questionnaires and two reminders were sent by post. Pupils invited totalled 3809, of whom 3597 responded (response rate 94%). Even though pupils had the possibility to refuse from participation, non-responding (212 pupils) was almost exclusively associated with absence from school on the survey occasions. Six respondents were excluded because their responses were judged to be facetious. Respondents aged <15 years had to be excluded due to missing parental consent (n = 313). Thus, the final sample consisted of 1609 girls and 1669 boys. Follow-up data The subjects in the final baseline sample were reached for a 2-year follow-up (T2) when they were aged 17- to 18-years old. This is a time, when Finnish adolescents have completed basic education. Residential moves are common due to finding new study places. The variety of study places is large and there are no official records capable of identifying the study place of a specific individual. All adolescents are not in educational institutes. They may also be seeking employment or staying at home studying for entrance examinations, for example. Planning the data collection was, thus challenging. The actual collection proved even more challenging. Respondents of the final baseline sample were invited to complete a 16-page questionnaire with questions similar to baseline. Written information on the goals of the study and the link with the initial study was given alongside the questionnaire. Educational institutions in Tampere and neighbouring towns were contacted to try and find out the current study location of the adolescents in the final baseline sample. For the adolescents whose current study location was identified (n = 1250), a possibility to complete the questionnaire there was organized. A current address was identified from the national register and the questionnaire with three reminders was mailed for adolescents who were not studying or whose current study location was unknown, and to the adolescents who were not at school when the possibility to complete the questionnaire was offered. Vantaa is located near the capital city of Finland; hence the number of educational institutes near Vantaa was too high to enable all adolescents to be tracked down to their current study locations. Thus, current addresses were identified from the national register for all respondents in the final baseline sample (n = 1792) and the questionnaire with three reminders was mailed (in the third reminder we also offered a possibility to complete the questionnaire in the internet). Many educational institutions were also contacted but the problem was that there were only few individuals from our sample in each institution. Arranging an opportunity to fill in our questionnaire at school was, thus inconvenient for both institutions and students. Despite these problems, five institutions agreed to co-operate. There were 468 students belonging to our research cohort in these institutions and 200 of them responded. Finally, we also piloted an internet-based questionnaire, offering adolescents who had not yet responded, an opportunity to use this alternative response method. The differences in data collecting methods resulted in differences in response rate. The response rate in Tampere was 78% (1163/1483) and 51% (907/1795) in Vantaa, and the final sample totalled 2070 respondents. The proportion of adolescents responding at school was 79% in Tampere and 21% in Vantaa. Measures Attrition Information about responding/not responding to follow-up survey was added to baseline data. Problem behaviour Depression The Finnish modification of the 13-item Beck Depression Inventory was used to assess depression. R-BDI comprises 13 statements showing increasing intensity of depressive emotions and cognitions. Each item is scored 0 3 according to the severity of the symptom. Sum scores of the 13 items (range 0 39 scores) were dichotomized according to the cut-off point of 8 suggested in the literature into moderate to severe depression (yes/no) Anti-social behaviour Anti-social behaviour was assessed by the externalizing scale of the Youth self-report (YSR). The externalizing scale consists of 11 variables concerning delinquency and 18 variables concerning aggressive behaviour. Each variable was scored 0 2 according to the frequency of anti-social behaviour. Sum scores of the 29 items (range 0 58) were dichotomized using the sex-specific 90th percentile as cut-off into those within normal range vs. those within clinical range. 18,19 SES at baseline The educational levels of both mother and father were ascertained with asking the highest education that the mother/ father had completed. Educational level was dichotomized into low (comprehensive or vocational school) and high (secondary school/university degree).

3 308 European Journal of Public Health School performance at baseline GPA at baseline The adolescents were asked, what the GPA of their last school report was <6.5/ / / / / / / (theoretical range of GPA is ) GPA was then dichotomized into below 7.0 and 7.0 or higher. Statistical methods Crosstabulations with Chi-square (or Fishers exact tests, when appropriate) were made in order to explore the univariate associations of two types of problem behaviour at baseline with attrition from follow-up. Also the associations of confounders (sex, SES and school performance) were explored. Logistic regression models were computed for both problem behaviour outcomes separately to estimate the effect of confounders (sex, SES and school performance) on the association between problem behaviour and attrition. Classification tables were computed to estimate percentages non-respondents predicted correctly by the binary logistic regression models. Similar analyses were computed for the whole sample and, due to differences in data collection methods and response levels, stratified according to study site. All analyses were computed with the SPSS for Windows 16.0 statistical package. Results In univariate analyses, all baseline variables were associated with attrition from follow-up. Better SES and higher GPA were associated with less probable attrition. Adolescents with problem behaviour at baseline were less likely to respond at follow-up. The results were similar in both study sites except that depression was not associated with attrition in the study site with low response rate. The proportions of adolescents with problem behaviour not responding the baseline survey were higher in the study site with lower response rate. (table 1) When confounders were entered into logistic regression models, the association between depression and attrition was sustained in the Tampere only. GPA was the strongest predictor of attrition (table 2). The model for the whole sample predicted correctly 22% of the non-respondents. The models computed for samples stratified according to study site differed by their ability to predict non-response: The percentage predicted correctly was two in the Tampere sample and 70 in the Vantaa sample. When confounders were entered into logistic regression models, the association between anti-social behaviour and attrition failed to reach significance. GPA was the strongest predictor of attrition in the models for the whole sample and Tampere and sex was the strongest predictor in the model for Vantaa (table 2). The model for the whole sample predicted correctly 22% of the non-respondents. The models computed for samples stratified according to study site differed by their ability to predict non-response. The percentage predicted correctly was zero in the Tampere sample and 71 in the Vantaa sample. Discussion Depression was associated with attrition even when sex, SES and school performance were controlled for. The association differed according to study site, however. Depression was associated with attrition in Tampere, where the response rate was high and data collection was carried out mainly in educational institutions but not in Vantaa, where the response rate was low and data collection was carried out mainly by mail. Anti-social behaviour was not associated with attrition when sex, SES and school performance were controlled for. It is often assumed that the likelihood of non-response bias is increased when the response proportion is low. In the present study, the method of data collection differed between two study sites producing samples with different response rates. The proportion of adolescents with problem behaviour not responding the baseline survey was higher in the study site with lower response rate. Low response rate was observed when the primary means of data collection was mailed surveys. Surveys may not have been returned simply because of the extra effort needed to carry the envelope to a post-box. No extra effort was needed when responding in the educational institute. Table 1 Frequency of not responding according to sex, SES, family structure and problem behaviour in the whole sample and stratified by study site Whole sample Vantaa Tampere %(n) P %(n) P %(n) P Problem behaviour Depression Yes 42 (140) 49 (102) 32 (38) No 36 (1061) 50 (781) 21 (280) Anti-social behaviour Yes 45 (158) 58 (105) 31 (53) No 36 (1050) 49 (783) 20 (267) Sex <0.001 <0.001 <0.001 Male 46 (766) 63 (560) 26 (206) Female 28 (442) 36 (328) 16 (114) SES Paternal educational level < Comprehensive only 42 (228) 55 (181) 22 (47) Higher 34 (815) 46 (596) 20 (219) Maternal educational level < Comprehensive only 44 (195) 55 (155) 24 (40) Higher 34 (873) 47 (636) 20 (237) School performance GPA <0.001 <0.001 <0.001 < (356) 71 (241) 38 (115) 7.0 or higher 32 (831) 44 (630) 17 (201)

4 Adolescent problem behaviour and attrition 309 Table 2 Risk for attrition (OR with 95% CI) according to mental health problems when sex, SES and school performance are controlled for in the whole sample and stratified by study site Whole sample Vantaa Tampere OR (95% CI) OR (95% CI) OR (95% CI) Depression 1.4 ( ) 1.0 ( ) 1.8 ( ) Sex (male) 2.0 ( ) 2.7 ( ) 1.6 ( ) Paternal educational level low 1.3 ( ) 1.3 ( ) 1.1 ( ) Maternal educational level low 1.1 ( ) 1.0 ( ) 1.0 ( ) GPA below ( ) 2.8 ( ) 2.5 ( ) Anti-social behaviour 1.3 ( ) 1.5 ( ) 1.5 ( ) Sex (male) 2.0 ( ) 2.8 ( ) 1.5 ( ) Paternal educational level low 1.3 ( ) 1.3 ( ) 1.1 ( ) Maternal educational level low 1.1 ( ) 1.0 ( ) 1.0 ( ) GPA below ( ) 2.6 ( ) 2.5 ( ) Attrition from health-related surveys is often assumed to be associated with poor health. There are few studies focusing on determinants of attrition in mental health studies and even less conducted among children or adolescents. In the present study, depression at baseline was associated with attrition from follow-up 2 years later. Psychiatric disorders have been suggested to affect attrition in population surveys. 20,21 Some studies have reported opposite results, however. In a Finnish longitudinal study of adolescent depression, no association was found between depression and later attrition. 14 Depression at earlier waves was not associated with attrition in the Baltimore Epidemiologic Catchment Area Follow-up, either. 20 The association of externalizing behaviours with attrition has been scarcely studied but the findings considering problem behaviours such as excessive alcohol consumption in adolescents or adults in the general population 14,22 and aggressive and delinquent behaviour in pre-adolescents 23 suggest similar conclusions: externalizing behaviour per se may not be associated with attrition. The present study is in agreement with previous studies on mental health study attrition among children and adolescents 14 in that a low grade point average was associated with attrition. Grade point average was a stronger variable than parental educational levels in explaining attrition thus suggesting that it was not merely an artefact of social class. Cognitive ability has been suggested to be a more salient explanatory factor than social class when studying attrition from a longitudinal study 6 and also special education has been found to be predictive of attrition among young adults. 24 Our questionnaire was lengthy thus requiring concentration. Also, choosing an alternative best describing one s current situation may have required good cognitive skills. Our baseline survey covered all ninth-grade pupils in two study sites and 97% of the target population participated. Hence, the data may provide especially good information about the subjects dropping out from the follow-up. Both internalizing and externalizing problem behaviours have shown high tendency of stability and recurrence during adolescence. 25,26 Presence of problem behaviour in baseline is thus indicative of presence of problem behaviour at follow-up. Using baseline variables to predict attrition from follow-up 2 years later may thus be justified. Conclusion Internalizing problem behaviour may be underrepresented in respondents of mental health surveys among adolescents. Lengthy questionnaires may require good concentration and cognitive ability thus preventing respondents with low academic performance or mental disorders affecting the required abilities, from participating. When designing surveys among adolescents, special care should be taken to make the questionnaires easy to answer and appealing to the eye of an adolescent respondent. Funding Data colection was financially supported by the competitive research funding of the Pirkanmaa Hospital District, Yrjö Jahnson Foundation and the Finnish Cultural Foundation. Conflicts of interest: None declared. Key points Mental health problems may be underrepresented in adolescent survey respondents. Males and adolescents with low grades have lower probability to respond to mental health surveys. Lay-out of surveys may have an effect on responding. References 1 Stang A. Nonresponse research an underdeveloped field in epidemiology. Eur J Epidemiol 2003;18: Falah-Hassani K. Emergency contraception among Finnish adolescents: awareness, use and the effect of non-prescription status. BMC Public Health 2007: Gerrits MH, van den Oord EJ, Voogt R. An evaluation of nonresponse bias in peer, self, and teacher ratings of children s psychosocial adjustment. J Child Psychol Psychiatry 2001;42: Galea S, Tracy M. Participation rates in epidemiologic studies. 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