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Childhood intelligence, self-esteem, early trait neuroticism and behaviour adjustment as predictors of locus of control in teenagers
Personality and Individual Differences 95 (2016) 178–182
Contents lists available at ScienceDirect
Personality and Individual Differences journal homepage: www.elsevier.com/locate/paid
Childhood intelligence, self-esteem, early trait neuroticism and behaviour adjustment as predictors of locus of control in teenagers Adrian Furnham a,b,⁎, &, Helen Cheng a,c a b c
Department of Psychology, University College London, London WC1E 6BT, UK BI: Norwegian Business School, Nydalsveien 37, 0484 Oslo, Norway ESRC Centre for Learning and Life Chances in Knowledge, Economies and Societies, UCL Institute of Education, University College London, London WC1H 0AL, UK
a r t i c l e
i n f o
Article history: Received 23 December 2015 Received in revised form 19 February 2016 Accepted 21 February 2016 Available online xxxx Keywords: Locus of control Intelligence Self-esteem Trait neuroticism Behavioural problems Longitudinal
a b s t r a c t This study explored a longitudinal data set of 3725 sixteen year olds examining parental social status (at birth), childhood intelligence, self-esteem, personality traits and behavioural problems (all measured at age 10) that influence teenage locus of control (measured at age 16). Correlational analysis showed that intelligence, measured by four tests at age 10, was the most powerful predictor of locus of control at aged 16, followed by self-esteem and then parental education and class, personality traits and behavioural problems. Structural equation modelling showed that childhood intelligence, self-esteem, trait neuroticism and behavioural problems were all independent predictors of locus of control at age 16, whilst parental social status predicted the outcome variable mainly through self-esteem. There were no gender differences in the outcome variable. Limitations, implications and suggestions for future research are considered. © 2016 Elsevier Ltd. All rights reserved.
1. Introduction There is a vast academic literature on the locus of control concept. Rotter (1966) defined locus of control (LOC) as followed: “When a reinforcement is perceived by the subject as not being entirely contingent upon his action, then, in our culture, it is typically perceived as the result of luck, chance, fate, as under the control of powerful others, or as unpredictable because of the great complexity of the forces surrounding him. When the event is interpreted in this way by an individual, we have labelled this a belief in external control. If the person perceives that the event is contingent upon his own behaviour or his own relatively permanent characteristics, we have termed this a belief in internal control” (p. 1). LOC is conceived of as a belief that a response will, or will not, influence the attainment of reinforcement. It is not an expectancy concerning a particular type of reinforcement, but a ‘problem-solving’ generalised expectancy, addressing the issue of whether behaviours are perceived as instrumental to goal attainment, regardless of the specific nature of the goal or reinforcer. Locus of control is seen to influence the particular goal expectancy in any given specific situation depending upon the novelty and the ambiguity of the setting, as well as the degree
⁎ Corresponding author at: Department of Psychology, University College London, London WC1E 6BT, UK. E-mail address: [email protected] (A. Furnham).
http://dx.doi.org/10.1016/j.paid.2016.02.054 0191-8869/© 2016 Elsevier Ltd. All rights reserved.
of reinforcement that the individual has directly experienced in that setting (Rotter, 1975). Rotter (1990) attempted to explain the ‘enormous and somewhat surprising popularity’ of the internal versus external control of reinforcement variable. He attributed the heuristic value of the variable to four factors: the variable was precisely defined; the variable construct was imbedded in a broader theory, namely social learning theory; the scale developed to measure this variable was derived from psychological (social learning) theory (providing the best assurance of construct validity); and the fact that the construct was widely disseminated in a research monograph. There has been criticism of the construct and an enormous increase in the measures developed to measure it. Indeed over 20 years ago Furnham and Steele (1993) noted eight conceptual and three methodological issues concerned with the literature but also a surprising number locus on control scales, some designed to measure specific beliefs (i.e., health LOC) or meant for certain groups (i.e., children's LOC). Some measures do not have the LOC concept but use more common concepts like self-confidence to deal effectively with different situations (Shrauger, 1995; Cheng & Furnham, 2002). There have also been attempts to provide a biological theory for LOC (Declerck, Boone, & De Brabander, 2006). There have been many studies to attempt to locate LOC in personality, specifically the Big Five, space. Results show small and inconsistent relationships (Wambach & Panackal, 1979). Perhaps the best known relationship is between neuroticism and LOC which prompted Judge, Erez,
A. Furnham, H. Cheng / Personality and Individual Differences 95 (2016) 178–182
Bono, and Thoresen (2003) to develop the now well-known Core SelfEvaluations Scale which sees low self-esteem, neuroticism and external locus of control as highly correlated features of self-evaluations. Indeed there are many early studies using different measures and populations showing that LOC is related to depression and anxiety (Abramowitz, 1969; Butterfield, 1964; Rapee, Craske, Brown, & Barlow, 1996; Watson, 1967; Zawawi & Hamaideh, 2009). Most studies have been cross-sectional and it has therefore been impossible to determine whether external locus of control leads to anxiety and depression or the other way around. This study is on LOC beliefs of adolescents. Various studies have looked at LOC as a mediator variable between early childhood experiences and later effects in adolescence like anxiety and depression (Culpin, Stapinski, Miles, Araya, & Joinson, 2015; Spokas & Heimberg, 2009). There have probably been more studies on the consequences rather than the causes of LOC (Carton, Norwicki, & Balster, 1996). Few studies have looked at the relationship between LOC and intelligence though in an early study Ollendick and Ollendick (1976) found intelligence and internal locus of control positively correlated as predicted. A review of the literature indicates that LOC is nearly always treated as the independent rather than the dependent variable. This fact is recognised in many recent papers: for instance, Ahlin (2014) noted, “…we know little about the contextual factors that influence the development of LOC” (p. 2995). Ahlin and Antunes (2015) noted, “…very little is known about the antecedents of an internal LOC orientation. Without an understanding of what factors contribute to the development of an internal LOC, it is not clear how to best encourage its formation” (p. 1803). Those studies that have looked at antecedents have mainly concentrated on parental styles (Carton et al., 1996). In this study we examined the effects of sociological and psychological variables on adolescent LOC. We predicted that parental social class and education are linked to their children's LOC in adolescence, specifically that poorer educated and lower social class parents, have children with more external LOC. This is because of the personal beliefs, experiences and socialisation practises by the parents of these children. There is a wealth of evidence to suggest that poorer households are more chaotic and with fewer educational facilities to encourage learning. In this study we also examined childhood intelligence and LOC. Previous studies have established findings on the links between family background and childhood intelligence (Deary et al., 2005; Tong, Baghurst, Vimpani, & McMichael, 2007). There are also studies which have demonstrated a positive relationship between childhood intelligence and LOC at the same age (Von Stumm, Gale, Batty, & Deary, 2009). Many studies on people from many age groups have demonstrated the relationship between IQ and LOC, it being argued that intelligence affords people a whole range of opportunities that increases their sense of personal control and mastery. In this study we also examine the relationship between self-esteem, personality traits, and behavioural problems (all measured at age 10) and LOC measured six years later. There is a considerable literature on the association between external LOC and depression which suggests that people get into a vicious circle, where fatalism leads to inactivity and negative affect which reinforces the external locus of control beliefs (Hill, 2011). 1.1. Hypotheses This study explored the effects of a set of childhood factors on teenage locus of control at 16 years using structural equation modelling and drawing on data collected from a large representative population sample in the UK. Its primary aim was to examine the relative power of individual difference factors measured before adolescence particularly intelligence, personality, parental social status indicators (parental
179
social class and education), and behavioural problems (maternal report) in predicting LOC at sixteen. It was hypothesised that: H1. Parental social status is a significant predictor of LOC at age 16 years; H2. Childhood intelligence (at aged 10) is a significant predictor of LOC at age 16 years; H3. Childhood self-esteem (at aged 10) is a significant predictor of LOC at age 16 years; H4. Childhood trait neuroticism (at aged 10) is a significant predictor of LOC at age 16 years; H5. Childhood behavioural problems (at aged 10) is a significant predictor of LOC at age 16 years; H6. Parental social status, childhood intelligence, self-esteem, trait neuroticism, and behavioural problems would be independent predictors of the outcome variable. 2. Method 2.1. Participants The study draws on a nationally representative cohort study: the 1970 British Cohort Study (BCS70). The study participants were recruited as part of a perinatal mortality survey. BCS70 comprises 16,571 individuals who were born in Great Britain in a week in April 1970 (Elliott & Shepherd, 2006). The following analysis is based on data collected at birth, age 10, and age 16. The analytic sample comprises 3725 cohort members (57% females), for whom complete data were collected at birth and the follow-ups at age 16. Analysis of response bias in the cohort data showed that the achieved adult samples did not differ from their target sample across a number of critical variables (social class, parental education and gender), despite a slight under-representation of the most disadvantaged groups (Plewis, Calderwood, Hawkes, & Nathan, 2004). 2.2. Measures 1. Family social background includes information on parental social class and parental education. Parental social class at birth was measured by the Registrar General's measure of social class (RGSC). RGSC is defined according to occupational status (Marsh, 1986). Where the father was absent, the social class (RGSC) of the mother's father was used. RGSC was coded on a 6-point scale: I professional; II managerial/technical; IIIN skilled non-manual; IIIM skilled manual; IV semiskilled; and V unskilled occupations (Leete & Fox, 1977). Scores were reversed. Parental education is measured by the age parents had left their full-time education. 2. Childhood intelligence was assessed at age 10 using a modified version of the British Ability Scales (BAS) which can serve as a measure for childhood IQ. The assessment involved the administration of four sub-scales: word definitions and word similarities which were used to measure verbal ability, and recall of digits and matrices which were used to measure non-verbal ability. The alpha for the four measures combined into a total scale was .92. 3. Personality traits at age 10, teachers were asked to use their knowledge of the study child to assess his/her disposition/temperament with two well-known personality dimensions: Extraversion (described as “An extravert, lively, likes company”) and Neuroticism (described as “An anxious child”). These were single item ratings. For each measure scores ranged from 1 (not at all) to 7 (a great deal). 4. Behavioural problems at age 10, the parent (mother) was asked to complete the items of the Rutter A scale (Rutter, Tizard, &
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A. Furnham, H. Cheng / Personality and Individual Differences 95 (2016) 178–182
3.2.1. Model fit The χ2 statistic is overly sensitive when sample sizes are large or the observed variables are non-normally distributed. The root mean square error of approximation (RMSEA) gives a measure of the discrepancy in fit per degrees of freedom (b.05 indicates a good fit). The final index of choices are the Comparative Fit Index (CFI) and the Tucker Lewis Index (or Non-normed Fit Index) where values above .95 indicate a very good fit, and values N .90 are interpreted as good (Bentler, 1990). Table 2 shows unstandardized estimate, standard error, and standardised estimate of each indicator of the latent variable and the predictors of LOC. Fig. 1 shows that childhood intelligence, childhood self-esteem, trait neuroticism, and behavioural problems were significant predictors of LOC at age 16, whilst parental social status influenced LOC mainly through self-esteem. The model showed a good fit. Chi-square was 236.7 (df = 44, p b .001), the CFI was .974, the TLI was .955, and the RMSEA was .034. The model explains 19% of the total variance of LOC at sixteen.
Whitmore, 1970) on an analogous scale which, using an automated marking system, yielded a score between 0 (does not apply) and 100 (certainly applies) for each item. 5. Self-esteem was measured at age 10. Cohort members completed a 12-item Self-esteem Scale (Yes/No) (Lawrence, 1973, 1978). The alpha was .73. 6. Locus of control was measured at age 16. Cohort members completed a 19-item Locus of Control Scale (Yes/No) (Gammage, 1975). The alpha was .72. 3. Results 3.1. Correlational analysis Table 1 shows the correlations of means and SDs of all variables in the study. LOC was significantly associated with parental social class, maternal and paternal education, childhood intelligence measures, childhood self-esteem, personality traits, and behavioural problems (p b .01 to p b .001). The strongest predictor of LOC was childhood intelligence. Gender was not significantly associated with LOC at sixteen.
4. Discussion 3.2. Structural equation modelling This study is among the first to explore the early factors that influence LOC in teenagers. The correlational data (see Table 1) showed that 16 year olds with an external LOC tended to come from homes with lower social class and less well-educated parents while the teenagers themselves were of lower intelligence, with lower self-esteem, higher neuroticism as rated by teachers, and manifesting more behavioural problems as rated by parents. By far the most powerful correlate was childhood intelligence which showed that intelligence measured at 10 years predicted LOC six years later. More intelligent children tended to have a more internal locus of control. There were also unusual results from the correlational matrix. It shows that there was no association between gender and LOC. Whilst
Structural equation modelling (SEM) was used to assess the links among family social status, childhood intelligence, childhood selfesteem and behavioural problems, and LOC at sixteen. The SEM model testing was carried out using the structural equation modelling programme IBM AMOS 22 (Arbuckle, 2013) using maximum likelihood estimation that can be based on incomplete data, known as the full information maximum likelihood (FIML) approach (Arbuckle, 1996). Fig. 1 show the standardised path coefficients of the structural equation model. The solid lines indicate that the corresponding path coefficients are statistically significant and dashed line indicates that the path coefficients is non-significant. Error variance for each observable variables are included in the model (not shown in the diagrams).
Table 1 Pearson correlations among gender, parental social status measures, childhood intelligence measures, childhood personality traits, self-esteem and behavioural problems, and locus of control at age 16 yrs. Variables
Mean SD
1
1.
Locus of control
–
2.
Gender
3.
Parental social class
4.
Paternal education
5.
Maternal education
6.
Word definition scores
7.
Word Similarities scores
8.
Digits recall scores
9.
Matrices scores
10.
Extraversion
11.
Neuroticism
12.
Behavioural problems
13.
Self-esteem
14.15 (3.25) .57 (.50) 3.44 (1 .22) 15.59 (1.21) 15.56 (1.09) 11.41 (4.99) 29.09 (4.03) 22.95 (4.16) 16.84 (5.12) 26.31 (12.03) 19.75 (11.99) 410.70 (198.0) 8.34 (2.65)
2
3
4
5
6
7
8
9
10
11
−.018
–
.168
−.019
–
.167
.003
.464
–
.154
−.018
.359
.470
–
.336
−.134
.309
.259
.268
–
.301
−.101
.268
.229
.229
.624
–
.185
.025
.111
.127
.107
.294
.274
–
.260
.034
.208
.195
.190
.425
.418
.262
–
.052
−.021
.053
.040
−.031
.081
.076
.068
.040
−.106
.018
−.078
.041
−.062
−.123
−.096
−.099
−.101
−.460
−.130
−.055
−.112
−.101
−.113
−.137
−.116
−.088
−.138
−.050
.094
.216
−.106
.124
.122
.121
.219
.172
.108
.165
.067
−.139
12
13
−.167
–
Note: Variables were scored such that a higher score indicated being female, a more professional occupation for the parent and higher age parents left school, higher verbal and non-verbal ability test scores in childhood, higher scores on childhood personality traits extraversion and neuroticism, higher scores on childhood self-esteem and behavioural problems, and higher scores on internal locus of control at teen.
A. Furnham, H. Cheng / Personality and Individual Differences 95 (2016) 178–182
181
Fig. 1. SEM model of early indicators associated with locus of control at age 16 (n = 3725).
the results have been inconsistent it is common to find a sex difference, usually with males having a more internal LOC. The SEM shows however the most important findings. It demonstrates first, the importance of intelligence, measured at age 10, in shaping LOC at sixteen. Presumably brighter children do better at school and have a great number options than less intelligent children. Intelligence is correlated with so many variables like psychological health, wellbeing and with lifestyle factors that mean intelligent children are greatly advantaged over less intelligent children (Deary, Whiteman, Starr, Whalley, & Fox, 2004). Indeed it has been shown to be a strong predictor of social mobility in adulthood (von Stumm et al., 2009). Second, the analysis showed that both parental class and intelligence were significantly associated with self-esteem at age 10 which Table 2 Measurement of the latent variables and SEM of locus of control at teen. Variables
Unstandardized estimate
Standard error
Standardised estimate
Parental social status RGSC Father's education Mather's education
1.000 1.144 .875
.044⁎⁎⁎ .035⁎⁎⁎
.635 .732 .622
Childhood intelligence Digits recall scores Matrices scores Word definition scores Word similarities scores
1.000 1.795 2.559 1.939
.095⁎⁎⁎ .123⁎⁎⁎ .093⁎⁎⁎
.379 .552 .809 .757
Predicting locus of control Parental social status Childhood intelligence Extraversion Neuroticism Behavioural problems Self-esteem
.157 .742 .003 −.020 −.021 .128
.097 .056⁎⁎⁎ .005 .005⁎ −.001⁎ .020⁎⁎⁎
.034 .360 −.013 −.040 −.041 .105
⁎ p b .05. ⁎⁎⁎ p b .001.
predicted LOC at age 16. This is possibly the beginning of a virtuous cycle: self-confident children are more likely to initiate a range of activities in social and educational settings where they discover their strengths and weaknesses. They learn that they can initiate and succeed in various activities which increases their self-efficacy. Parental social class at birth is significantly associated with both intelligence and selfesteem at age 10, both of which are directly linked to a more healthy internal LOC. The mechanisms underlying these associations are worth considering. It is possible that the association between parental social class and childhood intelligence is primarily genetic (Plomin & Spinath, 2004). Further, higher social class is associated with healthier parenting which is associated with self-esteem in the child. Third, results show that teachers' observations of pupils' trait neuroticism at age 10 modestly but significantly predicted LOC at age 16. Pupils observed as “anxious child” were more likely to have lower scores on internal locus of control at sixteen. Although anxiety and depression (two main components of neuroticism) were found to be associated with locus of control in previous studies (Abramowitz, 1969; Furnham, 2008; Watson, 1967), almost all those studies used selfreported personality measures, and participants were adults rather than children. The findings of the current study shows the validity of teachers' report on pupils' personality, albeit a single item rating. This method might be used in related studies when pupils are relatively young. Fourth, children's behavioural problems reported by parents at age 10 predicted LOC at age 16 as expected. More behavioural problems they were observed in childhood in school the lower scores they tend to achieve on self-reported internal LOC at sixteen. Interestingly less intelligent children from lower socio-economic status tended to exhibit more behavioural problems at age 10. Thus H2, H3, H4, H5 were supported, H1 was refuted and H6 were partially refuted, as parental social status was not a significant and independent predictor of LOC at sixteen. Like all studies this had limitations. First the LOC measure used a less well-used scale which made it less easy to compare with other studies,
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A. Furnham, H. Cheng / Personality and Individual Differences 95 (2016) 178–182
though there is no reason to assume there were any problems with its psychometric qualities. It would also be desirable to have a multidimensional LOC scale which measured separate facets of LOC like academic, physical, social LOC (Cheng & Furnham, 2002). Second, it would have been desirable to have more information on the parents, particularly their child-rearing style, but also their own personality and intelligence. Third, it would have been most interesting to know more about the personality of the respondents, measured at any age as well as their social relationships. Fourth, it would be desirable to have a more robust rating measure of personality than a single item rated by teachers. What are the implications of this study? Whilst it is less easy to change the intelligence level of a child it is possible to work on their self-esteem which was shown in this study to be an important predictor of their LOC some six years later. One question is which method to use to try to increase the self-esteem of children and whether there are any negative consequences of such attempts. Further, there is a significant debate and equivocal literature on whether self-esteem shapes educational and general life achievements or vice versa (Emler, 2001, 2003). There is considerable doubt that the simple “manipulation” of selfesteem would lead to a change in LOC which is sustained over time though it is possible a virtuous circle may be started which increases the association that increases over time. The literature suggests that both self-esteem and LOC are multidimensional thus targeting one facet of self-esteem may only have an impact on that facet of LOC. Equally it is possible that other variables not assessed in this study such as school type or parenting style have a more direct and immediate impact on LOC than variables mentioned in this study. There are some obvious future research suggestions arising from this study. The most obvious is to follow up the participants and see whether the LOC beliefs are stable over time and whether they have the same determinants in adulthood that they had in adolescence. Next, it would be most interesting to see what LOC scores measured at 16 predict behaviours in adulthood as LOC has been shown to be a correlate of a wide range of social behaviours (Rotter, 1990).
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Contents lists available at ScienceDirect
Personality and Individual Differences journal homepage: www.elsevier.com/locate/paid
Childhood intelligence, self-esteem, early trait neuroticism and behaviour adjustment as predictors of locus of control in teenagers Adrian Furnham a,b,⁎, &, Helen Cheng a,c a b c
Department of Psychology, University College London, London WC1E 6BT, UK BI: Norwegian Business School, Nydalsveien 37, 0484 Oslo, Norway ESRC Centre for Learning and Life Chances in Knowledge, Economies and Societies, UCL Institute of Education, University College London, London WC1H 0AL, UK
a r t i c l e
i n f o
Article history: Received 23 December 2015 Received in revised form 19 February 2016 Accepted 21 February 2016 Available online xxxx Keywords: Locus of control Intelligence Self-esteem Trait neuroticism Behavioural problems Longitudinal
a b s t r a c t This study explored a longitudinal data set of 3725 sixteen year olds examining parental social status (at birth), childhood intelligence, self-esteem, personality traits and behavioural problems (all measured at age 10) that influence teenage locus of control (measured at age 16). Correlational analysis showed that intelligence, measured by four tests at age 10, was the most powerful predictor of locus of control at aged 16, followed by self-esteem and then parental education and class, personality traits and behavioural problems. Structural equation modelling showed that childhood intelligence, self-esteem, trait neuroticism and behavioural problems were all independent predictors of locus of control at age 16, whilst parental social status predicted the outcome variable mainly through self-esteem. There were no gender differences in the outcome variable. Limitations, implications and suggestions for future research are considered. © 2016 Elsevier Ltd. All rights reserved.
1. Introduction There is a vast academic literature on the locus of control concept. Rotter (1966) defined locus of control (LOC) as followed: “When a reinforcement is perceived by the subject as not being entirely contingent upon his action, then, in our culture, it is typically perceived as the result of luck, chance, fate, as under the control of powerful others, or as unpredictable because of the great complexity of the forces surrounding him. When the event is interpreted in this way by an individual, we have labelled this a belief in external control. If the person perceives that the event is contingent upon his own behaviour or his own relatively permanent characteristics, we have termed this a belief in internal control” (p. 1). LOC is conceived of as a belief that a response will, or will not, influence the attainment of reinforcement. It is not an expectancy concerning a particular type of reinforcement, but a ‘problem-solving’ generalised expectancy, addressing the issue of whether behaviours are perceived as instrumental to goal attainment, regardless of the specific nature of the goal or reinforcer. Locus of control is seen to influence the particular goal expectancy in any given specific situation depending upon the novelty and the ambiguity of the setting, as well as the degree
⁎ Corresponding author at: Department of Psychology, University College London, London WC1E 6BT, UK. E-mail address: [email protected] (A. Furnham).
http://dx.doi.org/10.1016/j.paid.2016.02.054 0191-8869/© 2016 Elsevier Ltd. All rights reserved.
of reinforcement that the individual has directly experienced in that setting (Rotter, 1975). Rotter (1990) attempted to explain the ‘enormous and somewhat surprising popularity’ of the internal versus external control of reinforcement variable. He attributed the heuristic value of the variable to four factors: the variable was precisely defined; the variable construct was imbedded in a broader theory, namely social learning theory; the scale developed to measure this variable was derived from psychological (social learning) theory (providing the best assurance of construct validity); and the fact that the construct was widely disseminated in a research monograph. There has been criticism of the construct and an enormous increase in the measures developed to measure it. Indeed over 20 years ago Furnham and Steele (1993) noted eight conceptual and three methodological issues concerned with the literature but also a surprising number locus on control scales, some designed to measure specific beliefs (i.e., health LOC) or meant for certain groups (i.e., children's LOC). Some measures do not have the LOC concept but use more common concepts like self-confidence to deal effectively with different situations (Shrauger, 1995; Cheng & Furnham, 2002). There have also been attempts to provide a biological theory for LOC (Declerck, Boone, & De Brabander, 2006). There have been many studies to attempt to locate LOC in personality, specifically the Big Five, space. Results show small and inconsistent relationships (Wambach & Panackal, 1979). Perhaps the best known relationship is between neuroticism and LOC which prompted Judge, Erez,
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Bono, and Thoresen (2003) to develop the now well-known Core SelfEvaluations Scale which sees low self-esteem, neuroticism and external locus of control as highly correlated features of self-evaluations. Indeed there are many early studies using different measures and populations showing that LOC is related to depression and anxiety (Abramowitz, 1969; Butterfield, 1964; Rapee, Craske, Brown, & Barlow, 1996; Watson, 1967; Zawawi & Hamaideh, 2009). Most studies have been cross-sectional and it has therefore been impossible to determine whether external locus of control leads to anxiety and depression or the other way around. This study is on LOC beliefs of adolescents. Various studies have looked at LOC as a mediator variable between early childhood experiences and later effects in adolescence like anxiety and depression (Culpin, Stapinski, Miles, Araya, & Joinson, 2015; Spokas & Heimberg, 2009). There have probably been more studies on the consequences rather than the causes of LOC (Carton, Norwicki, & Balster, 1996). Few studies have looked at the relationship between LOC and intelligence though in an early study Ollendick and Ollendick (1976) found intelligence and internal locus of control positively correlated as predicted. A review of the literature indicates that LOC is nearly always treated as the independent rather than the dependent variable. This fact is recognised in many recent papers: for instance, Ahlin (2014) noted, “…we know little about the contextual factors that influence the development of LOC” (p. 2995). Ahlin and Antunes (2015) noted, “…very little is known about the antecedents of an internal LOC orientation. Without an understanding of what factors contribute to the development of an internal LOC, it is not clear how to best encourage its formation” (p. 1803). Those studies that have looked at antecedents have mainly concentrated on parental styles (Carton et al., 1996). In this study we examined the effects of sociological and psychological variables on adolescent LOC. We predicted that parental social class and education are linked to their children's LOC in adolescence, specifically that poorer educated and lower social class parents, have children with more external LOC. This is because of the personal beliefs, experiences and socialisation practises by the parents of these children. There is a wealth of evidence to suggest that poorer households are more chaotic and with fewer educational facilities to encourage learning. In this study we also examined childhood intelligence and LOC. Previous studies have established findings on the links between family background and childhood intelligence (Deary et al., 2005; Tong, Baghurst, Vimpani, & McMichael, 2007). There are also studies which have demonstrated a positive relationship between childhood intelligence and LOC at the same age (Von Stumm, Gale, Batty, & Deary, 2009). Many studies on people from many age groups have demonstrated the relationship between IQ and LOC, it being argued that intelligence affords people a whole range of opportunities that increases their sense of personal control and mastery. In this study we also examine the relationship between self-esteem, personality traits, and behavioural problems (all measured at age 10) and LOC measured six years later. There is a considerable literature on the association between external LOC and depression which suggests that people get into a vicious circle, where fatalism leads to inactivity and negative affect which reinforces the external locus of control beliefs (Hill, 2011). 1.1. Hypotheses This study explored the effects of a set of childhood factors on teenage locus of control at 16 years using structural equation modelling and drawing on data collected from a large representative population sample in the UK. Its primary aim was to examine the relative power of individual difference factors measured before adolescence particularly intelligence, personality, parental social status indicators (parental
179
social class and education), and behavioural problems (maternal report) in predicting LOC at sixteen. It was hypothesised that: H1. Parental social status is a significant predictor of LOC at age 16 years; H2. Childhood intelligence (at aged 10) is a significant predictor of LOC at age 16 years; H3. Childhood self-esteem (at aged 10) is a significant predictor of LOC at age 16 years; H4. Childhood trait neuroticism (at aged 10) is a significant predictor of LOC at age 16 years; H5. Childhood behavioural problems (at aged 10) is a significant predictor of LOC at age 16 years; H6. Parental social status, childhood intelligence, self-esteem, trait neuroticism, and behavioural problems would be independent predictors of the outcome variable. 2. Method 2.1. Participants The study draws on a nationally representative cohort study: the 1970 British Cohort Study (BCS70). The study participants were recruited as part of a perinatal mortality survey. BCS70 comprises 16,571 individuals who were born in Great Britain in a week in April 1970 (Elliott & Shepherd, 2006). The following analysis is based on data collected at birth, age 10, and age 16. The analytic sample comprises 3725 cohort members (57% females), for whom complete data were collected at birth and the follow-ups at age 16. Analysis of response bias in the cohort data showed that the achieved adult samples did not differ from their target sample across a number of critical variables (social class, parental education and gender), despite a slight under-representation of the most disadvantaged groups (Plewis, Calderwood, Hawkes, & Nathan, 2004). 2.2. Measures 1. Family social background includes information on parental social class and parental education. Parental social class at birth was measured by the Registrar General's measure of social class (RGSC). RGSC is defined according to occupational status (Marsh, 1986). Where the father was absent, the social class (RGSC) of the mother's father was used. RGSC was coded on a 6-point scale: I professional; II managerial/technical; IIIN skilled non-manual; IIIM skilled manual; IV semiskilled; and V unskilled occupations (Leete & Fox, 1977). Scores were reversed. Parental education is measured by the age parents had left their full-time education. 2. Childhood intelligence was assessed at age 10 using a modified version of the British Ability Scales (BAS) which can serve as a measure for childhood IQ. The assessment involved the administration of four sub-scales: word definitions and word similarities which were used to measure verbal ability, and recall of digits and matrices which were used to measure non-verbal ability. The alpha for the four measures combined into a total scale was .92. 3. Personality traits at age 10, teachers were asked to use their knowledge of the study child to assess his/her disposition/temperament with two well-known personality dimensions: Extraversion (described as “An extravert, lively, likes company”) and Neuroticism (described as “An anxious child”). These were single item ratings. For each measure scores ranged from 1 (not at all) to 7 (a great deal). 4. Behavioural problems at age 10, the parent (mother) was asked to complete the items of the Rutter A scale (Rutter, Tizard, &
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3.2.1. Model fit The χ2 statistic is overly sensitive when sample sizes are large or the observed variables are non-normally distributed. The root mean square error of approximation (RMSEA) gives a measure of the discrepancy in fit per degrees of freedom (b.05 indicates a good fit). The final index of choices are the Comparative Fit Index (CFI) and the Tucker Lewis Index (or Non-normed Fit Index) where values above .95 indicate a very good fit, and values N .90 are interpreted as good (Bentler, 1990). Table 2 shows unstandardized estimate, standard error, and standardised estimate of each indicator of the latent variable and the predictors of LOC. Fig. 1 shows that childhood intelligence, childhood self-esteem, trait neuroticism, and behavioural problems were significant predictors of LOC at age 16, whilst parental social status influenced LOC mainly through self-esteem. The model showed a good fit. Chi-square was 236.7 (df = 44, p b .001), the CFI was .974, the TLI was .955, and the RMSEA was .034. The model explains 19% of the total variance of LOC at sixteen.
Whitmore, 1970) on an analogous scale which, using an automated marking system, yielded a score between 0 (does not apply) and 100 (certainly applies) for each item. 5. Self-esteem was measured at age 10. Cohort members completed a 12-item Self-esteem Scale (Yes/No) (Lawrence, 1973, 1978). The alpha was .73. 6. Locus of control was measured at age 16. Cohort members completed a 19-item Locus of Control Scale (Yes/No) (Gammage, 1975). The alpha was .72. 3. Results 3.1. Correlational analysis Table 1 shows the correlations of means and SDs of all variables in the study. LOC was significantly associated with parental social class, maternal and paternal education, childhood intelligence measures, childhood self-esteem, personality traits, and behavioural problems (p b .01 to p b .001). The strongest predictor of LOC was childhood intelligence. Gender was not significantly associated with LOC at sixteen.
4. Discussion 3.2. Structural equation modelling This study is among the first to explore the early factors that influence LOC in teenagers. The correlational data (see Table 1) showed that 16 year olds with an external LOC tended to come from homes with lower social class and less well-educated parents while the teenagers themselves were of lower intelligence, with lower self-esteem, higher neuroticism as rated by teachers, and manifesting more behavioural problems as rated by parents. By far the most powerful correlate was childhood intelligence which showed that intelligence measured at 10 years predicted LOC six years later. More intelligent children tended to have a more internal locus of control. There were also unusual results from the correlational matrix. It shows that there was no association between gender and LOC. Whilst
Structural equation modelling (SEM) was used to assess the links among family social status, childhood intelligence, childhood selfesteem and behavioural problems, and LOC at sixteen. The SEM model testing was carried out using the structural equation modelling programme IBM AMOS 22 (Arbuckle, 2013) using maximum likelihood estimation that can be based on incomplete data, known as the full information maximum likelihood (FIML) approach (Arbuckle, 1996). Fig. 1 show the standardised path coefficients of the structural equation model. The solid lines indicate that the corresponding path coefficients are statistically significant and dashed line indicates that the path coefficients is non-significant. Error variance for each observable variables are included in the model (not shown in the diagrams).
Table 1 Pearson correlations among gender, parental social status measures, childhood intelligence measures, childhood personality traits, self-esteem and behavioural problems, and locus of control at age 16 yrs. Variables
Mean SD
1
1.
Locus of control
–
2.
Gender
3.
Parental social class
4.
Paternal education
5.
Maternal education
6.
Word definition scores
7.
Word Similarities scores
8.
Digits recall scores
9.
Matrices scores
10.
Extraversion
11.
Neuroticism
12.
Behavioural problems
13.
Self-esteem
14.15 (3.25) .57 (.50) 3.44 (1 .22) 15.59 (1.21) 15.56 (1.09) 11.41 (4.99) 29.09 (4.03) 22.95 (4.16) 16.84 (5.12) 26.31 (12.03) 19.75 (11.99) 410.70 (198.0) 8.34 (2.65)
2
3
4
5
6
7
8
9
10
11
−.018
–
.168
−.019
–
.167
.003
.464
–
.154
−.018
.359
.470
–
.336
−.134
.309
.259
.268
–
.301
−.101
.268
.229
.229
.624
–
.185
.025
.111
.127
.107
.294
.274
–
.260
.034
.208
.195
.190
.425
.418
.262
–
.052
−.021
.053
.040
−.031
.081
.076
.068
.040
−.106
.018
−.078
.041
−.062
−.123
−.096
−.099
−.101
−.460
−.130
−.055
−.112
−.101
−.113
−.137
−.116
−.088
−.138
−.050
.094
.216
−.106
.124
.122
.121
.219
.172
.108
.165
.067
−.139
12
13
−.167
–
Note: Variables were scored such that a higher score indicated being female, a more professional occupation for the parent and higher age parents left school, higher verbal and non-verbal ability test scores in childhood, higher scores on childhood personality traits extraversion and neuroticism, higher scores on childhood self-esteem and behavioural problems, and higher scores on internal locus of control at teen.
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Fig. 1. SEM model of early indicators associated with locus of control at age 16 (n = 3725).
the results have been inconsistent it is common to find a sex difference, usually with males having a more internal LOC. The SEM shows however the most important findings. It demonstrates first, the importance of intelligence, measured at age 10, in shaping LOC at sixteen. Presumably brighter children do better at school and have a great number options than less intelligent children. Intelligence is correlated with so many variables like psychological health, wellbeing and with lifestyle factors that mean intelligent children are greatly advantaged over less intelligent children (Deary, Whiteman, Starr, Whalley, & Fox, 2004). Indeed it has been shown to be a strong predictor of social mobility in adulthood (von Stumm et al., 2009). Second, the analysis showed that both parental class and intelligence were significantly associated with self-esteem at age 10 which Table 2 Measurement of the latent variables and SEM of locus of control at teen. Variables
Unstandardized estimate
Standard error
Standardised estimate
Parental social status RGSC Father's education Mather's education
1.000 1.144 .875
.044⁎⁎⁎ .035⁎⁎⁎
.635 .732 .622
Childhood intelligence Digits recall scores Matrices scores Word definition scores Word similarities scores
1.000 1.795 2.559 1.939
.095⁎⁎⁎ .123⁎⁎⁎ .093⁎⁎⁎
.379 .552 .809 .757
Predicting locus of control Parental social status Childhood intelligence Extraversion Neuroticism Behavioural problems Self-esteem
.157 .742 .003 −.020 −.021 .128
.097 .056⁎⁎⁎ .005 .005⁎ −.001⁎ .020⁎⁎⁎
.034 .360 −.013 −.040 −.041 .105
⁎ p b .05. ⁎⁎⁎ p b .001.
predicted LOC at age 16. This is possibly the beginning of a virtuous cycle: self-confident children are more likely to initiate a range of activities in social and educational settings where they discover their strengths and weaknesses. They learn that they can initiate and succeed in various activities which increases their self-efficacy. Parental social class at birth is significantly associated with both intelligence and selfesteem at age 10, both of which are directly linked to a more healthy internal LOC. The mechanisms underlying these associations are worth considering. It is possible that the association between parental social class and childhood intelligence is primarily genetic (Plomin & Spinath, 2004). Further, higher social class is associated with healthier parenting which is associated with self-esteem in the child. Third, results show that teachers' observations of pupils' trait neuroticism at age 10 modestly but significantly predicted LOC at age 16. Pupils observed as “anxious child” were more likely to have lower scores on internal locus of control at sixteen. Although anxiety and depression (two main components of neuroticism) were found to be associated with locus of control in previous studies (Abramowitz, 1969; Furnham, 2008; Watson, 1967), almost all those studies used selfreported personality measures, and participants were adults rather than children. The findings of the current study shows the validity of teachers' report on pupils' personality, albeit a single item rating. This method might be used in related studies when pupils are relatively young. Fourth, children's behavioural problems reported by parents at age 10 predicted LOC at age 16 as expected. More behavioural problems they were observed in childhood in school the lower scores they tend to achieve on self-reported internal LOC at sixteen. Interestingly less intelligent children from lower socio-economic status tended to exhibit more behavioural problems at age 10. Thus H2, H3, H4, H5 were supported, H1 was refuted and H6 were partially refuted, as parental social status was not a significant and independent predictor of LOC at sixteen. Like all studies this had limitations. First the LOC measure used a less well-used scale which made it less easy to compare with other studies,
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though there is no reason to assume there were any problems with its psychometric qualities. It would also be desirable to have a multidimensional LOC scale which measured separate facets of LOC like academic, physical, social LOC (Cheng & Furnham, 2002). Second, it would have been desirable to have more information on the parents, particularly their child-rearing style, but also their own personality and intelligence. Third, it would have been most interesting to know more about the personality of the respondents, measured at any age as well as their social relationships. Fourth, it would be desirable to have a more robust rating measure of personality than a single item rated by teachers. What are the implications of this study? Whilst it is less easy to change the intelligence level of a child it is possible to work on their self-esteem which was shown in this study to be an important predictor of their LOC some six years later. One question is which method to use to try to increase the self-esteem of children and whether there are any negative consequences of such attempts. Further, there is a significant debate and equivocal literature on whether self-esteem shapes educational and general life achievements or vice versa (Emler, 2001, 2003). There is considerable doubt that the simple “manipulation” of selfesteem would lead to a change in LOC which is sustained over time though it is possible a virtuous circle may be started which increases the association that increases over time. The literature suggests that both self-esteem and LOC are multidimensional thus targeting one facet of self-esteem may only have an impact on that facet of LOC. Equally it is possible that other variables not assessed in this study such as school type or parenting style have a more direct and immediate impact on LOC than variables mentioned in this study. There are some obvious future research suggestions arising from this study. The most obvious is to follow up the participants and see whether the LOC beliefs are stable over time and whether they have the same determinants in adulthood that they had in adolescence. Next, it would be most interesting to see what LOC scores measured at 16 predict behaviours in adulthood as LOC has been shown to be a correlate of a wide range of social behaviours (Rotter, 1990).
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