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Abstract

Objective: To assess the relationship between risk and protective factors and the continuity of psychological problems from age 7 to age 33.

Methods: Data on 5591 cohort members of the National Child Development Study were used to track continuity and discontinuity between internalizing and externalizing problems at age 7, as assessed by the Rutter ‘A’ Health and Behaviour Checklist, and psychological distress at age 33, as assessed by the Malaise Inventory, controlling for risk and protective groupings present at age 7.

Results: There was no association between malaise in adulthood and internalizing problems in childhood. However, people who had externalizing problems in childhood were nearly twice as likely as those without such problems to have high Malaise scores in adulthood. A grouping of risk factors (police/probation experience by family, agency referral for difficulties in school, social services involvement, domestic tension) did not predict malaise in adulthood. Also a grouping of protective factors (outings with mother, father reads to child, good creative skills, good numeric skills) predicted that women were less likely to have high Malaise scores in adult life.

Conclusions: Protective factors in childhood were strongly associated with lower Malaise scores in adulthood. Research on factors associated with discontinuity of psychological problems may prove fruitful.

Keywords

continuity and discontinuity emotional and behavioural problems National Child Development Study risk and protective factors

An impressive amount of evidence, particularly relating to antisocial disorders, demonstrates the continuity between behaviour problems in childhood and difficulties in later life [1–4]. In a recent review of the relevant evidence from epidemiological, community-based and clinical studies, Kovacs and Devlin [5] concluded that internalizing disorders in early life consistently predict internalizing problems in later life. Similarly, findings from studies on children with externalizing disorders paint a rather depressing picture of continuity from childhood into adult life [6, 7].

Although there is considerable ‘stability’ in disorders throughout childhood, there is also considerable evidence of ‘discontinuity’. Smith [8], for example, notes that although there is evidence from longitudinal studies of continuity between antisocial behaviour throughout childhood, results also show a substantial element of discontinuity. Campbell's [6] conclusion that half of three-year-olds with hard to manage behaviour go on to have later difficulties also means that half do not. But if effective interventions are to be developed we need to know more about both factors that protect children from disorders and factors that carry risks for disorders. Fombonne [9] suggests that one of the most important issues on the research agenda is the identification of protective mechanisms for those at risk that help build healthy developmental pathways into adult life. These moderators or protective factors can reside either in the individual or in the context [10]. Kazdin [11], Rutter [12] and Fombonne [9] all note that much less is known about protective factors than about risk factors. From the relatively few studies that explored these moderators or protective factors, it has been shown that factors such as high self-esteem, good coping skills, school achievement, involvement in extra-curricular activities, positive relationship with parents, peers and adults, and parents’ involvement with their child protect against adverse outcomes [13–17].

A lot more is known about the risk factors for psychological problems. There is considerable evidence, for instance, that social adversities, parental disagreements and punitive parenting styles are strongly related with externalizing disorders especially when these develop into antisocial behaviour [18–21]. Continuing childhood behaviour problems are associated with single parenting, family and maternal stress, and poor family relationships [21, 22]. Buchanan and Ten Brinke [23], using data from the National Child Development Study (NCDS) showed that severe socioeconomic disadvantage and care, rather than family structure, and family conflict were related to a high Malaise score in adulthood. Cheung and Buchanan [24] also using data from NCDS, found that cohort members, especially men, who had been in care were significantly more likely to have high Malaise scores in adult life than a comparative group who had experienced severe social disadvantage.

Building on this evidence, this study aims to test the hypothesis that groupings of risk and protective factors present at age 7 are associated with a tendency to psychological distress in adult life, as measured by a high Malaise score. NCDS with its detailed person, family and educational data gathered over 33 years offers an excellent opportunity to test this hypothesis.

Method

The National Child Development Study

This study uses data from 4 sweeps of NCDS. The NCDS is a longitudinal study of some 17 000 children born between 3 and 9 March 1958 in England, Scotland and Wales. The aim of the study is to improve understanding of the factors affecting human development over the lifespan. NCDS has its origins in the Perinatal Mortality Survey (PMS) which was sponsored by the National Birthday Trust and designed to examine social and obstetric factors associated with stillbirth and death in early infancy. Five follow-up studies have been carried out: in 1965 (age 7); in 1969 (age 11); in 1974 (age 16); in 1981 (age 23), and in 1991 (age 33). When the cohort members were aged 33, data were obtained from 11 363 respondents. For the first three follow-ups information was obtained from parents, teachers and the school health service and at age 16 from the cohort members as well. In 1981 information was obtained from the cohort and in 1991 from the cohort, their partners and a sample of their children.

The representative nature of the study has been maintained [25]. Refusals have been low. However, a major problem with NCDS is the possibility of bias in the responding sample. Analysis of non-response bias has indicated that there were high losses of participants in disadvantaged groups. It is possible that those who could not be traced may be more disadvantaged than those who have been traced. Despite these limitations, the National Child Development Study is one of the best datasets available to investigate long-term effects of parental background.

Eight hundred and sixty members were mentally disabled or had chronic illness or disability. These were not included in this analysis. This study uses information obtained from 6441 people for whom there were complete psychological data in both childhood (7, 11 and 16) and adulthood (33).

Measures

Development of the emotional and behavioural measures

All measures were based on the Rutter ‘A’ Health and Behaviour Checklist [26], which has been widely used to measure psychosocial wellbeing. Two subscales were derived from this checklist to identify children whose problems were internalized (‘neurotic’) or externalized (‘antisocial’). In 1974, when members were 16, the full Rutter ‘A’ (31 questions) was completed by the parent or primary care giver. At 7 and 11 a shortened version was used. Variants of the latter have been used by Chase-Lansdale et al. [27] and Elliott and Richards [28]. The eight items that were not available in the shortened version were: the child has temper tantrums in the past year, plays truant, steals, has eating difficulties, is restless, is fussy, often tells lies, and bullies other children. This shortened Rutter ‘A’ at 16 was compared with the full Rutter ‘A’ at 16. A 20% cut-off applied to both the shortened and the full Rutter ‘A’ largely identified the same individuals (χ² = 2841.45, df = 1, p < 0.001).

Factor analysis carried out on the items of the shortened Rutter ‘A’ at 16 to examine its dimensionality confirmed that two sets of behaviour grouped together [29]. The ‘internalizing’ subgroup was based on the total score for positive responses to: having headaches, stomach aches, sleep problems, worries, and being solitary, miserable and fearful. The ‘externalizing’ subgroup was based on the total score for positive responses to: being fidgety, destroying things, fighting, not being liked and being irritable, disobedient and unsettled. A third group appeared to relate to health problems. Note that the item ‘miserable’ loads on both externalizing and internalizing factors, which denotes high comorbidity between depressed mood and externalizing and internalizing problems. However, to keep the internalizing and externalizing groups separate this item is included in the internalizing scale only. Table 1 presents the results of a varimax rotated factor analysis. Factor loadings equal to or greater than 0.30 are underscored for clarification of the factor structure. There was a good correlation between the ‘internalizing’ measure from the short Rutter ‘A’ and the ‘neurotic’ measure from the full Rutter ‘A’, as was between the ‘externalizing’ measure from the short Rutter ‘A’ and the ‘conduct’ measure from the full Rutter ‘A’ (r = 0.80, p < 0.001, and r = 0.61, p < 0.001, respectively). Factor analysis of the Rutter ‘A’ scale at 7 also revealed two factors corresponding to the broad dimensions of externalizing and internalizing behaviour problems found in previous research [30].

Table 1.

Factor loadings for the shortened Rutter ‘A’ at age 16

In Rutter ‘A’ a cut-off score of 13 + is usually used to identify a significant level of maladjustment. Goodman, [31] in developing the Strengths and Difficulties Questionnaire, argues that a better strategy is a percentage cut-off. Although using a single cut-off has the advantage of simplicity and equivalence across studies, it also has disadvantages, the most important of which is that ‘caseness’ does not have a comparable meaning in different studies simply because those studies use the same cut-off. In this study a similar strategy was used. Children in the top 20% of the total score from the shortened Rutter ‘A’ at 7 were designated as showing some disorder (n = 1416). Children with an ‘internalizing’ score exceeding their ‘externalizing’ score were designated as having an ‘internalizing’ problem (n = 806), while those with a ‘externalizing’ score exceeding their ‘internalizing’ score were designated as having an ‘externalizing’ problem (n = 466). In an attempt to explore independently the effects of internalizing and externalizing problems on adult mental health, children who had equal internalizing and externalizing scores, the comorbid group (n = 144) were omitted from the analysis.

At 33 members were asked to complete the Malaise Inventory, a 24-item list of symptoms of depression, anxiety and psychosomatic illness [26] taken from the Cornell Medical Index. The Malaise Inventory has been used to identify those at risk of psychological distress [32–34]. A score of 8 + has been widely used to identify people with a ‘high level of emotional distress’ [35]. Because a score of 8 + on the Malaise Inventory has been found to be related to clinically significant psychiatric disorder [26, 32–37] we used this rather than the top quintile as a cutpoint on the Malaise instrument. The 24 symptoms are positive responses to: having backaches, feeling tired, feeling miserable and depressed, having headaches, worrying, having difficulty in falling asleep or staying asleep, waking unnecessarily early in the morning, worrying about health, getting into a violent rage, getting annoyed by people, having twitches, becoming scared for no reason, being scared to be alone, being easily upset, being frightened of going out alone, being jittery, suffering from indigestion, suffering from upset stomach, having poor appetite, being worn out by little things, experiencing racing heart, having bad pains in your eyes, being troubled by rheumatism, and having had a nervous breakdown. Although concerns have been expressed about the dimensionality of the Malaise Inventory [38], it is robust [39] and has good psychometric qualities [40]. Rodgers et al. [41] showed that the internal consistency of the full 24-item was acceptable (in NCDS the Cronbach's alpha of the scale at 33 was 0.80). Factor analysis identified a general, and a second psychological factor. Receiver operating characteristic (ROC) analysis indicated that validity held for men and women and for different socioeconomic groups, by reference to external criteria covering current or recent psychiatric morbidity and service use. It should be noted, however, that the Malaise Inventory cannot be used alone to diagnose depression but it is intended to be an indicator, and is thought to provide representation of symptoms associated with emotional disturbance [42]. Four hundred and fourteen people (6.4%) of the sample had a Malaise score of 8 + at 33, which compares well with the 7.6% of the NCDS sample reported earlier [43].

Independent measures used

This study used measures which have been identified [43, 44] as risk and protective factors. In accordance to Bronfenbrenner's [44] paradigm, these reflect factors from different ‘ecological’ domains, (i.e. within the person, and are related to family, school and the social environment). The demographic variables used were gender and parental socioeconomic status when the child was born. Parental mental health when the cohort member was 7, structure of the parental background (assessed as in [45]), experience of severe social disadvantage (measured as in [24]) and experience of care were also included in the analysis. The grouping of risk factors, present when the cohort members were aged 7 years, included the following variables: family involvement with the police/probation service, agency referral for difficulties at school, social services involvement and domestic tension. The grouping of protective factors, present when the cohort members were aged 7 years, included the following variables: outings with mother, father reads to child, and child's good numeric and creative skills. Both groupings were the sum of their individual four dichotomous components, and ranged from 0 to 4. Both risk and protective factors were selected following our earlier related research [23]. A description of the measures used in this study is shown in Table 2.

Table 2.

Independent measures used

Results

A logistic regression analysis was carried out to explore the influence of factors in childhood associated with a tendency to psychological distress in adult life. Gender was first entered – women were at a significantly higher risk of distress than men (χ² = 52.31, df = 1). When social class was added, the fit was further improved to (χ² = 60.68, df = 2). Adding parental mental ill health further increased the fit (χ² = 71.16, df = 3). Family structure, disadvantage and a care experience increased explanatory power (χ² = 100.26, df = 8). Finally, when internalizing and externalizing disorders and risk and protective groupings were added, the χ² was 125.81 (df = 12). The models described below show the results by gender (see Table 3).

Table 3.

Hierarchial logistic regression results showing the effect of childhood variables on the risk of high Malaise at age 33

As Table 3 shows, parental social class and parental ill mental health were significant predictors of men's self-reported malaise in adult life but not of women's. Social disadvantage, on the other hand, predicted malaise in women and an experience of care significantly predicted malaise in men, a finding consistent with previous research [24, 43]. Compared to children who grew up with their birth family, children who grew up with a single parent were significantly more likely to have a high Malaise score in adult life. Children with externalizing problems were twice as likely to have a high Malaise score in adulthood as children without externalizing problems. Finally, the protective grouping at age 7 was negatively associated with psychological distress in women but not in men (although, as shown by the comparability odds ratios for both sexes, this may reflect insufficient power due to a lower rate of high Malaise scores in men).

Discussion

Recently we showed that an experience of severe disadvantage of care and the presence of emotional and behavioural difficulties in childhood significantly predict emotional difficulties in adult life [43]. This study builds on those findings. When other factors were controlled for, externalizing (but not internalizing) problems at a very early age (7) they were significantly linked to high Malaise scores in adult life. There are several reasons why internalizing problems at 7 did not predict Malaise scores at 33. First, although studies suggest continuity of psychological problems [1, 7] there is also substantial evidence suggesting discontinuity [8]. Second, the Malaise Inventory cannot be used alone to diagnose depression but it is an indicator of depression. Finally, another reason might be that the questions on internalizing behaviour in the Rutter ‘A’ checklist represent less serious psychopathology than the ones on externalizing behaviour. Other research has also shown that apart from internalizing, externalizing problems in childhood are associated with psychological distress later in life [5], which suggests that the presence of one of these types of problems can create an increased risk for the occurrence of the other [5, 46].

This study also highlighted gender differences, and corroborated previous research [24, 43, 45]. For example, men (but not women) who had been in care were more than four times as likely to have high Malaise scores as men with no public care experience. This may be because of the poor prospects in adulthood among men who have been in care ‘due to lack of qualifications and job opportunities’ [24].

In this study, the grouping of risk factors present at 7 was not predictive of later depressive symptoms. The reason might be that the risk grouping used reflects a range of interacting personal, family, school and social difficulties and adversities at 7, which actually may be related to the presence of externalizing problems at 7. Therefore, when externalizing problems at 7 are included in the model, the strength of the association between these and a later high Malaise score is so great, that the effects of the risk grouping is not important. This does not mean that other risk factors will also be insignificant. However, the childhood risk factors used have been highlighted as significant predictors of adverse mental health outcomes [5, 6, 8, 9].

This study showed that groupings of protective factors present at 7 were associated with lower Malaise scores in adulthood. As with the risk factors, the protective variables used (good creative and numeric skills, outings with mother and father reads to child) were selected to reflect a range of protective factors both in the person, family and school. These factors also are not definitive and there may be others which are more important. Fombonne [9], for example, notes that high self-esteem, good coping, school achievement, and positive relationships with parents and adults outside the family all exert protective influences against depressive outcomes. Building on this evidence, we showed that parental involvement and teacher's recognition of a child's creative talents and skills protect against adverse psychological outcomes.

Clinical implications

This research identified factors in childhood that protect children from psychological distress in adult life. ‘Father reads to child’ and ‘outings with mother’ are indicative of ‘involved’ parents who spend time with their children and are interested in their education. The short-term benefits from this style of parenting have been demonstrated [16]. This study showed that this style of parenting is associated with long-term benefits as well. Clinicians may find it helpful to remind parents that quality time spent with children on enjoyable activities when they are young may have long-term benefits. Similarly, school achievement is strongly associated with positive outcomes [13]. The benefits of identifying a child's particular skills may be protective. As Robins and Rutter [47] noted, ‘if… benevolent environments can be intentionally created for youngsters who would not encounter them naturally and if protective traits and skills can be taught or cultivated, they constitute the basis for interventions particularly likely to succeed’ (p. xiv). Some children may need to be ‘set up’ to succeed.

Limitations

Caution is needed in interpreting these findings. First, there remain the limitations of any longitudinal study, in particular attrition, and of using dated data. Second, to compare assessments at two time-periods, only the members who had complete data on mental health at 4 time-points (7, 11 16 and 33) were included. Since we know that the losses to the NCDS were greatest among more disadvantaged children, this may underestimate the long-term impact of disadvantage. It could also be, as suggested by Cox et al. [48], that missing cases are likely to include a higher proportion of people with mental health problems. Third, many of the independent family or school-related variables were unstandardized. Fourth, the Rutter ‘A’ is a parent-report assessment while the Malaise Inventory is completed by the member. Ideally, mental health problems should be assessed from various sources. This was not possible. However, parental reports of the child's mental health are stable [49]. In contrast, it is possible that the Malaise Inventory, more focused on emotional symptoms, was rated up in women and down in men. Finally, associations do not indicate causes. But, longitudinal studies allow one to draw causal inferences more convincingly since the design permits time order and prediction of later outcomes permits analysis of within-individual changes and between individual variations [50].

Footnotes

Acknowledgements

We acknowledge the NHS Anglia and Oxford Executive for funding this study.

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Emotional and Behavioural Problems in Childhood and Distress in Adult Life: Risk and Protective Factors

Abstract

Keywords

Method

The National Child Development Study

Measures

Development of the emotional and behavioural measures

Independent measures used

Results

Discussion

Clinical implications

Limitations

Footnotes

Acknowledgements

References