The current study aimed to explore health behaviour, quality of life and well-being in older children in relation to social background, parental academic socialisation and academic expectation stress, and the role of emerging constructs of self-compassion and psychological capital as potential protective factors. A survey was administered to a sample of 373 children (150 males and 223 females) aged between 11 and 15 years. Children were assessed on academic expectations stress, home and social background, parenting experience, psychological capital, self-compassion, health behaviour, well-being and quality of life. Academic expectation stress was inversely predictive of well-being and quality of life and through its impact on self-compassion and psychological capital, to health behaviour. Findings from this study would suggest that positive psychology interventions to build self-compassion and psychological capital may be efficacious in reducing the negative impact of academic expectation stress in children.
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Parents play a critical role in children’s psychological and behavioural development and perhaps crucially in terms of the expectations they have for them to achieve (Lara & Saracostti, 2019; Ma et al., 2016). Expectations to achieve can place demands on students that become a major cause of stress (Poots & Cassidy, 2020). While these demands come mainly from parental expectations for their children (Sangma et al., 2018), students can also place high demands on themselves and may also be influenced by demands from teachers (Bedewy & Gabriel, 2015). However, the origins of expectations to achieve are mainly rooted in the family for most children. Parental expectations have been investigated in terms of parental involvement in their children’s education and early evidence suggests that parents who are higher in socioeconomic status (SES) tend to have more involvement (Cripps & Zyromski, 2009). Parental involvement that is encouraging and supportive has generally been consistently related to higher achievement (Boonk et al., 2018; Ceballo et al., 2014; El Nokali et al., 2010; Vasquez et al., 2016), and to better mental well-being and positive health behaviours (Westerlund et al., 2015). This type of involvement includes practices such as meetings and communication with teachers, assisting children with homework, and volunteering to help with school activities (Cripps & Zyromski, 2009; Spera, 2005). Parental over involvement which is demanding and controlling often hinders students’ attainment and creates anxiety and increased stress for children (Schiffrin et al., 2014).
There is an established literature on the impact of expectations placed on children and their academic development but the literature lacks evidence on the impact of expectations on the health and well-being of children. The current study aimed to explore health behaviour, quality of life and well-being in older children in relation to social background, parental academic socialisation and academic expectation stress, and the role of emerging constructs of self-compassion and psychological capital as potential protective factors. These variables form the proposed model to be tested as shown in Fig. 1 which is explained more fully through the following review.
Fig. 1
Proposed relationships underpinning a path model
×
The health and well-being of school age children has become a major and growing concern (Fazel et al., 2014; Valizadeh et al., 2012; Vizard et al., 2020). Health and well-being are inextricably linked both to each other and to academic achievement (Davis et al., 2011; Fiscella & Kitzman, 2009; Ickovics et al., 2014). Health is underpinned by a healthy lifestyle and strong evidence has emerged showing that a healthy lifestyle is predictive of academic performance (Flueckiger et al., 2014). One might therefore expect a cluster of related outcomes in terms of health behaviours, well-being, and academic performance. This study aims to explore the relationship between academic expectation stress and health and well-being in school aged children and the potential mediating role of psychological capital and self-compassion. In addition, the aim is to explore the role of demographic and back ground factors and parenting in the process.
The influence parents have on their children’s academic development has been termed parental academic socialisation (Loughlin-Presnal & Bierman, 2017; Puccioni, 2015; Suizzo & Soon, 2006; Taylor et al., 2004) and has been strongly linked to parents’ general approach to child-rearing in terms of parental style (Bingham et al., 2017). Parental academic socialisation draws on the original model of parenting styles from Baumrind (1991) which describes three dimensions of authoritative, authoritarian, and permissive styles. Suizzo and Soon (2006), focusing specifically on parental influence on academic development, developed a three-factor model and a measure identifying three dimensions of parental active involvement, parental emotional support, and parental demandingness. The model was developed by assessing a sample of 249 college students in terms of the parenting approach their parents used with them. This made the resulting measure appropriate for the current study. In terms of the evidence on parental involvement it could be argued that parental active involvement combined with emotional support and moderate levels of demand would have a positive impact while active involvement that is less supportive and more demanding would have a negative impact on both achievement and well-being (Westerlund et al., 2015). Parenting styles are largely influenced by the socioecological context in which they evolve including SES and parental education (Roubinov and Boyce 2017).
Recent research on mediators of stress has generated an extensive literature on two constructs; self-compassion (Neff et al., 2007a, b) and psychological capital (Luthans et al., 2007; Newman et al., 2014). Both constructs have emerged from positive psychology and offer a shift away from a deficit model of stress to one which focuses on building resilience and well-being and therefore a more preventative option. The importance of resilience is highlighted in the seminal work of Michael Ungar (Ungar, 2018).
Self-compassion refers to kind and caring feelings towards oneself when faced with personal distress and the acknowledgement that one’s suffering, failures and shortfalls are all part of life (Birnie et al., 2010; Neff & McGehee, 2010; Neff et al., 2005). Research suggests that self-compassion might offer a useful avenue through which young people can reduce stress (Bluth et al., 2015; Zhang et al., 2016). Several studies have demonstrated a positive relationship between self-compassion and indicators of well-being, including happiness, optimism (Neff et al., 2007a), self-esteem (Barry et al., 2015), emotional intelligence (Heffernan et al., 2010), and health-promoting behaviours (Sirois, 2014). Accordingly, research also shows a negative relationship between self-compassion and anxiety (Neff et al., 2007b), depression (Ghorbani et al., 2012), burnout (Durkin et al., 2016), stress, emotion regulation difficulties (Finlay-Jones et al., 2015), self‐rumination, anger (Neff & Vonk, 2009), and aggression (Barry et al., 2015). Allen and Leary (2010) report that more self-compassionate individuals are less likely to magnify negative events, feel anxious after stressful situations, and avoid challenges for fear of failure.
Psychological capital (PsyCap) emerged in the context of occupational health and comprises four components; resilience, hope, self-efficacy and optimism (Jafri, 2013; Luthans et al., 2007), which act as a buffer to stress (Avey et al., 2009; Datu & Valdez, 2015; Rahimnia et al., 2013). Luthans et al. (2007), defined psychological capital as “an individual’s positive psychological state of development and is characterized by: (1) having confidence (self-efficacy) to take on and put in the necessary effort to succeed at challenging tasks; (2) making a positive attribution (optimism) about succeeding now and in the future; (3) persevering toward goals and, when necessary, redirecting paths to goals (hope) in order to succeed; and (4) when beset by problems and adversity, sustaining and bouncing back and even beyond (resilience) to attain success”.
It has been shown that when the components of PsyCap are combined as a second-order, core factor it predicts performance and satisfaction better than each of the four factors that make it up (Luthans et al., 2007). The construct has been generalised to life stress beyond the occupational context (Krasikova et al. 2015; Lorenz et al. 2016) and evidence shows it is positively related to physical and psychological well-being (Siu, 2013), but negatively related to anxiety and depressive symptoms (Liu et al., 2013), and burnout (Peng et al., 2013). Research on PsyCap as a protective factor against stress with potential mediating effects, proposes that this higher-order construct could provide a pathway to increase student resistance to stress, as well as pave the way in which individual’s assess and interpret situations to reframe them as exciting challenges rather than unbearable pressures (Riolli et al., 2012). It is argued that someone who is hopeful, optimistic, ego resilient and efficacious will be more likely to have more effective coping resources (Riolli et al., 2012).
The socioecological context of health and well-being is rooted in SES and the relationship between SES and health behaviours in adults is well established (Pampel et al., 2010), and there is a growing literature on health behaviour and SES in children (Coombs et al., 2013; Kipping et al., 2015). The relationship between SES and psychological well-being in adults is well established (Fassbender & Leyendecker, 2018), but less attention has been paid to SES and well-being in children (Bøe et al., 2012). Bøe et al. (2012) show evidence for a clear and consistent link between low SES and poor mental health in 11–13-year-old children. The relationship between SES and health-related quality of life has also been documented (Mielck et al. 2014). However, the relationship between SES and general quality of life is less clear. In one study of Australian men both those at the upper end of the scale and those at the lower end exhibited poorer quality of life (Brennan et al., 2013). The relationship between SES and educational attainment is complex and variable in strength depending on social contexts and educational systems (Broer et al., 2019). SES is generally construed as a combination of occupation, income, and education and one consistent finding is that well educated mothers may place more value on their children’s academic achievement resulting in more involvement (Augustine, 2017).
Aims
The current study aimed to explore health behaviour, quality of life and well-being in older children in relation to social background, parental academic socialisation and academic expectation stress, and the role of emerging constructs of self-compassion and psychological capital as potential protective factors. Based on the evidence reviewed a model was constructed as shown in Fig. 1. The aim was to test the efficacy of this model. Based on the evidence reviewed it is argued that parental academic socialisation and academic expectation stress will have an impact on student well-being, quality of life and health practices. It is further proposed that the impact will be mediated by psychological capita and self-compassion. Important context variables are age, sex, SES, mother’s education, and family stability. The relationships are complex which possibly explains why they have not been jointly explored previously. In the context of growing concern over student mental health, by combining these variables this study has the potential to inform pastoral support and interventions.
Method
Design: this was a cross-sectional survey design using questionnaire data collection
Participants: A total of 373 children (150 males and 223 females) aged between 11 and 15 years were assessed. Of these, 50 were 11 years old, 70 were 12 years old, 84 were 13 years old, 89 were 14 years old, and 70 were 15 years old. In terms of ethnicity 263 were White British, 59 were Asian British, and 51 were Black British. The SES and educational background of the sample are shown in Table 1.
Table 1
SES and educational background for the sample
Socioeconomic status (SES)
N
%
Mother’s education
N
%
Higher managerial and professional
10
2.7
Primary
43
11.5
Lower managerial and professional
10
2.7
Lower secondary
110
29.5
intermediate
44
11.8
Upper secondary
82
22.0
small employers and own accounts
109
29.2
Tertiary
90
24.1
Lower supervisory and technical
78
20.9
Postgraduate
48
12.9
Semi-routine
54
14.5
Total
373
100.0
Routine
33
8.8
Unemployed
35
9.4
Total
373
100.0
The children were attending a medium sized regional school which serviced a small town, three villages and a rural area in England in the United Kingdom (UK). Participants were asked for, details on age, gender, and father’s and mother’s occupation and highest level of education. Father and mother’s occupation was used to code Socioeconomic Status (SES) Parental education was scored as highest qualification and recoded in line with the International Standard of Educational Classification (OECD/Eurostat/UNESCO Institute for Statistics, 2015). Socioeconomic status was recorded as the highest of father’s or mother’s occupation and recoded in line with the National Statistics Socioeconomic Classification (Rose et al., 2003).
Measures
The Academic Expectation Stress Inventory (AESI: Ang & Huan, 2006), is a nine-item scale that measures the level of stress derived from demands placed on the student by themselves and by parents and teachers. Items are rated on a 5-point Likert scale that ranges from 1 = Never True to 5 = Almost Always True. The scale produces a global measure of mental well-being by adding together the scores on the nine items. The AESI has been shown to be a valid and reliable measure (Ang & Huan, 2006). The Cronbach’s alpha for this scale in this study is 0.91.
The Warwick Edinburgh Mental Well-being Scale-short form (Tennant et al., 2007) is a seven-item scale comprises items that relate to the different aspects of positive mental health. Participants are asked to respond based on their experience over the past two weeks. The scale uses a 5-point Likert scale ranging from 1 = None of the Time to 5 = All of the Time. Level of positive mental well-being is calculated by summing the scores of the seven items with a higher score indicative of a higher level of positive mental well-being. The Cronbach’s alpha for the scale in this study is 0.93.
The Compound PsyCap (CPC-12) Scale is a composite measure of hope, resilience, self-efficacy, and optimism, encompassing 12 items. Each of the four components is reported on a 6-point Likert scale from Strongly Disagree (=1) to Strongly Agree (=6). It measures psychological capital in a universal manner. The CPC-12 has been demonstrated to have good reliability and external validity (Lorenz et al., 2016). In this study, the Cronbach’s alpha for the CPC-12 scale was 0.93.
The Self-Compassion Scale- Short Form (SCS-SF); Neff (2003) was used to measure self-compassion in this study. This is a 12-item scale with responses rated on a 5-point Likert scale where 1 = Almost Always and 5 = Almost Never. Level of self-compassion is calculated by adding the items scores and higher scores reflect more self-compassion. Cronbach’s alphas for the scale in this study was 0.86.
The Parental Academic Socialisation scale (Suizzo & Soon, 2006) was used in this study to measure parent involvement in their student’s education. This 31-item scale was developed by Suizzo and Soon (2006), who reported strong reliability and validity. The scale comprises 3 dimensions, emotional support (Cronbach’s alpha = 0.91), active involvement (Cronbach’s alpha = 0.78) and demandingness (Cronbach’s alpha = 0.73). It has previously been used as a single composite measure of parental academic socialisation and as a measure of the three separate constructs.
To measure quality of life the Youth Quality of Life Scale – Short Form (Patrick et al., 2002) was employed. It is a 15 -item measure of general quality of life in youth ages 11–18 years regardless of chronic conditions and disabilities. It has a Cronbach Alpha score of 0.85.
The Good Health Practices Scale (GHPS) is a 16-item questionnaire which aims to measure how much the participant agrees with engaging with health behaviours. It uses a 5-point Likert scale measuring how strongly they agree or disagree with the health statements. The scale has been shown to have good internal reliability and applicable for both genders (Hampson et al., 2019).
Procedure: The sample were drawn from one medium sized regional school in the UK. The school was a public school and serviced a small town, three villages and a rural area. While there are no doubt differences between schools on all sorts of measures there is no standard statistics to make a generalisable comparison. On the other hand, the study aimed to look at variables which impact on well-being and quality of life and while there may be factors which impact on these variables from school to school it is the relationship between variables that we are interested in. For example, regional and demographic differences may influence levels of parental academic socialisation and / or academic expectation stress, our focus is on how parental academic socialisation and academic expectation stress impact on quality of life and well-being.
Following University Ethics Committee approval permission was sought from the school to undertake the research. The school cooperated and organised parental permission for the study. Questionnaire packs were distributed to children in class by the teachers. Each pack contained an information leaflet and a consent form which children signed before research commenced. Children took the pack home with them and were asked to return it when completed. All children were provided with a questionnaire pack, a total of 630 children in total. Of these 373 usable questionnaires were returned, a response rate of 59.2%.
Data analysis
Data were entered into SPSS 26 and after cleaning was analysed using Pearson Bivariate correlations, Hierarchical Multiple Regression Analysis (HMRA), and Path Analysis using AMOS 26 Structural Equation Modelling software. In order to be entered as independent or predictor variables in the HMRA and Path Analysis all dichotomous variables were scored 0,1. Father and mother education level and SES as ordinal variables were dummy coded.
Results
The first stage in analysis involved bivariate correlations to explore the bivariate relationships between GHP, QoL, well-being and AES, and a range of background and psychological variables as shown in Table 2. There is a pattern of correlations with well-being, QoL, and GHP involving mother’s education, crowding, parental academic socialisation, AES, psychological capital and self-compassion which point to a path model as illustrated in Fig. 1.
Table 2
Bivariate correlations between background, parental academic socialisation, academic expectation stress, psychological capital and health and well-being
1
2
3
4
5
6
7
8
9
10
11
12
13
1. Age
2. Socioeconomic Status
−0.01
3. Fathers education
−0.06
0.15**
4. Mothers education
−0.17**
0.02
0.26**
5. Crowding Index
−0.11*
0.48**
0.14**
0.02
6. Emotional support
−0.12*
0.01
−0.06
0.08
−0.13*
7. Active involvement
−0.32**
−0.09
−0.02
0.45**
−0.03
0.24**
8. Demandingness
0.08
0.06
0.06
0.05
0.11*
−0.20**
0.04
9. Academic expectation
−0.12*
0.15**
−0.01
−0.05
0.15**
−0.18**
−0.07
0.22**
10. Psychological Capital
−0.14**
0.18**
−0.06
0.08
−0.27**
0.39**
0.16**
−0.00
−0.26**
11. Self-compassion
0.09
0.22**
−0.02
0.11*
−0.12*
0.07
0.04
−0.13*
−0.64**
0.26**
12. Quality of Life
−0.16**
0.03
0.01
0.16**
−0.10
0.42**
0.24**
0.05
−0.26**
0.55**
0.17**
13. Good Health Behaviour
−0.06
0.15**
−0.11*
0.03
−0.23**
0.29**
0.16**
−0.07
−0.20**
0.45**
0.26**
0.31**
14. Well-being
−0.12*
0.10
0.04
0.18**
−0.16**
0.44**
0.20**
0.03
−0.49**
0.59**
0.36**
0.87**
0.34**
*p < 0.05, **p < 0.01
To explore these relationships more robustly Hierarchical Multiple Regression Analysis (HMRA) was applied to identify the predictive relationships with well-being, quality of life, and good health practices separately.
Well-being was entered as the dependent variable in the first HMRA (see Table 2). On the first step sex (β = 0.15, p < 0.01) and age (β = −0.12, p < 0.01) were entered as predictor variables and accounted for 4% of the variance in well-being. On step 2 father’s education, mother’s education, children of divorce, and SES, were entered and accounted for a further 17% of the variance. Mother’s education (β = 0.35, p < 0.001), children of divorce (β = −0.15, p < 0.001), and SES (β = 0.10, p < 0.01), contributed significant portions of variance. On the next step the dimensions of parental academic socialisation, emotional support, active involvement, and demandingness, were entered and added a further 7% to variance explained. Emotional support (β = 0.32, p < 0.001), and demandingness (β = 0.11, p < 0.05), contributed significantly to variance explained. On step 4 academic expectation stress (β = −0.47, p < 0.001), was added and contributed an additional 19% to explained variance. On the final step psychological capital and self-compassion were added and contributed another 11% of variance. Only psychological capital was significant (β = 0.38, p < 0.001). Overall, the model explained 58% of the variance in well-being.
Quality of life was entered as the dependent variable in the next HMRA (Table 3). On the first step sex (β = 0.14, p < 0.01) and age (β = −0.15, p < 0.01) were entered as predictor variables and accounted for 5% of the variance in quality of life. On step 2 father’s education, mother’s education, children of divorce, and SES, were entered and accounted for a further 15% of the variance. Only mother’s education (β = 0.38, p < 0.001), contributed a significant portion of variance. On the next step the dimensions of parental academic socialisation, emotional support, active involvement, and demandingness, were entered and added a further 4% to variance explained. Only emotional support (β = 0.21, p < 0.001), contributed significantly to variance explained. On step 4 academic expectation stress (β = −0.37, p < 0.001), was added and contributed an additional 12% to explained variance. On the final step psychological capital and self-compassion were added and contributed another 9% of variance. Only psychological capital was significant (β = 0.35, p < 0.001). Overall, the model explained 45% of the variance in quality of life.
Table 3
HMRA to identify the predictors of well-being
B
SE B
β
Step 1: R2 = 0.04, F(2370) = 7.22, p < 0.001
Age
−0.663
0.279
−0.121**
Sex
2.256
0.767
0.150**
Step 2: R2 Δ = 0.17, F(4366) = 19.14, p < 0.001
Age
−0.385
0.259
−0.070
Sex
1.401
0.713
0.093*
Father’s education
0.018
0.258
0.003
Mother’s education
2.094
0.294
0.349***
Children of divorce
2.621
0.795
−0.154***
SES
1.134
0.523
0.104*
Step 3: R2 Δ = 0.07, F(3363) = 11.24, p < 0.001
Age
−0.327
0.262
−0.060
Sex
1.082
0.707
0.072
Father’s education
0.188
0.252
0.035
Mother’s education
1.041
0.347
0.174**
Children of divorce
2.181
0.770
0.129**
SES
1.070
0.508
0.098*
Emotional Support
1.899
0.336
0.318***
Active Involvement
0.095
0.305
0.016
Demandingness
0.644
0.276
0.111*
Step 4: R2 Δ = 0.19, F(1362) = 133.85, p < 0.001
Age
−0.829
0.228
−0.151***
Sex
0.554
0.606
0.037
Father’s education
0.080
0.216
0.015
Mother’s education
0.991
0.297
0.165***
Children of divorce
1.345
0.663
0.079
SES
0.868
0.435
0.080*
Emotional Support
1.624
0.288
0.272***
Active Involvement
−0.170
0.262
−0.029
Demandingness
1.266
0.242
0.219***
Academic Expectation Stress
−0.415
0.036
−0.473***
Step 5: R2 Δ = 0.11, F(2360) = 44.28, p < 0.001
Age
−0.794
0.224
−0.145***
Sex
0.900
0.599
0.060
Father’s education
0.161
0.212
0.030
Mother’s education
0.928
0.291
0.155**
Children of divorce
1.449
0.649
0.085
SES
0.678
0.428
0.062
Emotional Support
1.421
0.286
0.238***
Active Involvement
−0.198
0.256
−0.033
Demandingness
1.207
0.237
0.209***
Academic Expectation Stress
−0.387
0.036
−0.441***
Psychological capital
3.585
0.391
0.379***
Self-compassion
0.118
0.159
0.034
Total R2 = 0.58
*p < 0.05, **p < 0.01, ***p < 0.001
Good Health Practices was entered as the dependent variable in the next HMRA (Table 4). On the first step sex and age were entered as predictor variables and accounted for a nonsignificant less than 1% of the variance in good health practices (p = 0.192). On step 2 father’s education, mother’s education, children of divorce, and SES, were entered and accounted for a further 7% of the variance. Father’s education (β = 0.11, p < 0.05), mother’s education (β = 0.20, p < 0.001), and SES (β = 0.13, p < 0.01), contributed a significant portion of variance. On the next step the dimensions of parental academic socialisation, emotional support, active involvement, and demandingness, were entered and added a further 3% to variance explained. Only emotional support (β = 0.22, p < 0.001), contributed significantly to variance explained. On step 4 academic expectation stress (β = −0.19, p < 0.001), was added and contributed an additional 3% to explained variance. On the final step psychological capital and self-compassion were added and contributed another 10% of variance. Psychological capital (β = 0.32, p < 0.001), and self-compassion (β = 0.19, p < 0.001), were significant. Overall, the model explained 23% of the variance in good health practices.
Table 4
HMRA to identify the predictors of quality of life
B
SE B
β
Step 1: R2 = 0.05, F(2370) = 8.65, p < 0.001
Age
−2.847
0.937
−0.154**
Sex
7.214
2.571
0.143**
Step 2: R2 Δ = 0.15, F(4366) = 17.55, p < 0.001
Age
−1.854
0.874
−0.101*
Sex
3.991
2.410
0.079
Father’s education
0.482
0.872
0.026
Mother’s education
7.634
0.993
0.378***
Children of divorce
5.951
2.685
0.104*
SES
1.448
1.766
0.039
Step 3: R2 Δ = 0.04, F(3363) = 5.66, p < 0.001
Age
−1.235
0.904
−0.067
Sex
3.092
2.439
0.061
Father’s education
0.120
0.870
0.007
Mother’s education
4.769
1.197
0.236***
Children of divorce
4.949
2.656
0.087
SES
0.994
1.754
0.027
Emotional Support
4.218
1.158
0.210***
Active Involvement
1.860
1.052
0.093
Demandingness
0.627
0.952
0.032
Step 4: R2 Δ = 0.12, F(1362) = 68.99, p < 0.001
Age
−2.569
0.845
−0.139**
Sex
1.689
2.245
0.033
Father’s education
0.167
0.799
0.009
Mother’s education
4.636
1.099
0.230***
Children of divorce
2.726
2.453
0.048
SES
0.458
1.611
0.012
Emotional Support
3.485
1.066
0.173***
Active Involvement
1.154
0.969
0.058
Demandingness
2.279
0.896
0.117
Academic Expectation Stress
−1.104
0.133
−0.374***
Step 5: R2 Δ = 0.09, F(2360) = 27.32, p < 0.001
Age
−1.563
0.802
−0.085*
Sex
3.890
2.118
0.077
Father’s education
0.242
0.749
0.013
Mother’s education
3.647
1.036
0.181***
Children of divorce
4.313
2.302
0.075
SES
−1.537
1.530
−0.042
Emotional Support
1.460
1.036
0.073
Active Involvement
1.320
0.906
0.066
Demandingness
1.076
0.853
0.055
Academic Expectation Stress
−0.914
0.160
−0.310***
Psychological capital
11.119
1.505
0.349***
Self-compassion
−0.488
0.612
−0.042
Total R2 = 0.45
*p < 0.05. **p < 0.01 ***p < 0.001
Psychological capital was entered as the dependent variable in the next HMRA (Table 5). On the first step sex and age were entered as predictor variables and accounted for 2% of the variance in psychological capital. Age accounted for a significant amount of variance (β = −0.15, p < 0.01). On step 2 father’s education, mother’s education, children of divorce, and SES, were entered and accounted for a further 15% of the variance. Mother’s education (β = 0.31, p < 0.001), and SES (β = 0.17, p < 0.01), contributed a significant portion of variance. On the next step the dimensions of parental academic socialisation, emotional support, active involvement, and demandingness, were entered and added a further 6% to variance explained. Only emotional support (β = 0.31, p < 0.001), and demandingness (β = 0.12, p < 0.001), contributed significantly to variance explained. On step 4 academic expectation stress (β = −0.26, p < 0.001), was added and contributed an additional 6% to explained variance. On the final step self-compassion was added and contributed another 2% of variance (β = 0.16, p < 0.001). Overall, the model explained 31% of the variance in psychological capital.
Table 5
HMRA to identify the predictors of good health practices
B
SE B
β
Step 1: R2 = 0.009, F(2370) = 1.66, p = 0.192
Age
−0.033
0.042
−0.042
Sex
−0.187
0.114
−0.085
Step 2: R2 Δ = 0.07, F(4366) = 7.09, p < 0.001
Age
−0.018
0.041
−0.023
Sex
−0.253
0.112
−0.115*
Father’s education
0.090
0.041
0.113*
Mother’s education
0.175
0.046
0.199***
Children of divorce
0.010
0.125
0.004
SES
0.200
0.082
0.125**
Step 3: R2 Δ = 0.03, F(3363) = 4.58, p < 0.01
Age
0.000
0.042
0.000
Sex
−0.270
0.114
−0.122**
Father’s education
0.065
0.041
0.081
Mother’s education
0.057
0.056
0.065
Children of divorce
−0.041
0.124
−0.016
SES
0.178
0.082
0.111*
Emotional Support
0.193
0.054
0.220***
Active Involvement
0.040
0.049
0.046
Demandingness
0.014
0.045
0.017
Step 4: R2 Δ = 0.03, F(1362) = 13.82, p < 0.001
Age
−0.030
0.042
−0.038
Sex
−0.301
0.113
−0.137**
Father’s education
0.071
0.040
0.089
Mother’s education
0.054
0.055
0.062
Children of divorce
−0.091
0.123
−0.036
SES
0.166
0.081
0.104*
Emotional Support
0.177
0.053
0.202***
Active Involvement
0.024
0.049
0.027
Demandingness
0.051
0.045
0.060
Academic Expectation Stress
−0.025
0.007
−0.193***
Step 5: R2 Δ = 0.10, F(2360) = 24.82, p < 0.001
Age
0.010
0.040
0.012
Sex
−0.210
0.107
−0.095*
Father’s education
0.049
0.038
0.062
Mother’s education
0.009
0.052
0.010
Children of divorce
−0.021
0.116
−0.008
SES
0.076
0.077
0.048
Emotional Support
0.109
0.052
0.124*
Active Involvement
0.032
0.046
0.037
Demandingness
0.001
0.043
0.002
Academic Expectation Stress
0.002
0.008
0.015
Psychological capital
0.437
0.076
0.315***
Self-compassion
0.098
0.031
0.192***
Total R2 = 0.23
*p < 0.05. **p < 0.01 ***p < 0.001
Self-compassion was entered as the dependent variable in the next HMRA (Table 6). On the first step sex and age were entered as predictor variables and accounted for less than 1% of the variance in self-compassion. On step 2 father’s education, mother’s education, children of divorce, and SES, were entered and did not account a significant percentage of the variance. On the next step the dimensions of parental academic socialisation, emotional support, active involvement, and demandingness, were entered and added 2% to variance explained. Only demandingness (β = 0.14, p < 0.01), contributed significantly to variance explained. On step 4 academic expectation stress (β = −0.65, p < 0.001), was added and contributed an additional 37% to explained variance. Overall, the model explained 40% of the variance in self-compassion.
Table 6
HMRA to identify the predictors of psychological capital
B
SE B
β
Step 1: R2 = 0.02, F(2370) = 4.33, p < 0.05
Age
−0.085
0.030
−0.146**
Sex
−0.063
0.082
−0.039
Step 2: R2 Δ = 0.15, F(4366) = 15.89, p < 0.001
Age
−0.064
0.028
−0.111*
Sex
−0.136
0.077
−0.086
Father’s education
0.053
0.028
0.092
Mother’s education
0.199
0.032
0.313***
Children of divorce
−0.052
0.086
−0.029
SES
0.199
0.057
0.173***
Step 3: R2 Δ = 0.06, F(3363) = 10.03, p < 0.001
Age
−0.061
0.028
−0.106*
Sex
−0.169
0.077
−0.106*
Father’s education
0.033
0.027
0.057
Mother’s education
0.094
0.038
0.149**
Children of divorce
−0.097
0.084
−0.054
SES
0.195
0.055
0.169***
Emotional Support
0.194
0.036
0.307***
Active Involvement
0.000
0.033
0.000
Demandingness
0.073
0.030
0.119**
Step 4: R2 Δ = 0.06, F(1362) = 30.59, p < 0.001
Age
−0.091
0.028
−0.157***
Sex
−0.200
0.074
−0.126**
Father’s education
0.039
0.026
0.068
Mother’s education
0.091
0.036
0.144**
Children of divorce
−0.146
0.081
−0.081
SES
0.183
0.053
0.159***
Emotional Support
0.178
0.035
0.281***
Active Involvement
−0.016
0.032
−0.025
Demandingness
0.109
0.030
0.179***
Academic Expectation Stress
−0.024
0.004
−0.261***
Step 5: R2 Δ = 0.02, F(2360) = 7.91, p < 0.01
Age
−0.090
0.028
−0.156***
Sex
−0.197
0.073
−0.124**
Father’s education
0.036
0.026
0.063
Mother’s education
0.088
0.036
0.139**
Children of divorce
−0.142
0.080
−0.079
SES
0.178
0.053
0.154***
Emotional Support
0.184
0.035
0.291***
Active Involvement
−0.015
0.032
−0.023
Demandingness
0.108
0.029
0.177***
Academic Expectation Stress
−0.014
0.006
−0.156**
Self-compassion
0.060
0.021
0.161***
Total R2 = 0.31
*p < 0.05. **p < 0.01 ***p < 0.001
The significant partial correlations from the series of HMRAs above provided general support for the model proposed in Fig. 1. In order to put these relationships into a more easily recognised form and to further test the paths involved the Structural Equation programme in AMOS 26 was used (Table 7).
Table 7
HMRA to identify the predictors of self-compassion
B
SE B
β
Step 1: R2 = 0.009, F(2370) = 1.60, p = 0.202
Age
0.139
0.081
0.089
Sex
0.122
0.223
0.028
Step 2: R2 Δ = 0.016, F(4366) = 1.50, p = 0.201
Age
0.151
0.082
0.097
Sex
0.083
0.226
0.019
Father’s education
−0.024
0.082
−0.015
Mother’s education
0.112
0.093
0.065
Children of divorce
0.293
0.252
0.060
SES
0.238
0.166
0.076
Step 3: R2 Δ = 0.02, F(3363) = 2.33, p < 0.05
Age
0.192
0.086
0.123*
Sex
0.165
0.232
0.038
Father’s education
−0.006
0.083
−0.004
Mother’s education
0.076
0.114
0.045
Children of divorce
0.264
0.253
0.054
SES
0.173
0.167
0.055
Emotional Support
0.007
0.110
0.004
Active Involvement
0.087
0.100
0.051
Demandingness
−0.223
0.091
−0.135**
Step 4: R2 Δ = 0.37, F(1362) = 230.31, p < 0.001
Age
−0.006
0.069
−0.004
Sex
−0.043
0.182
−0.010
Father’s education
−0.048
0.065
−0.031
Mother’s education
0.057
0.089
0.033
Children of divorce
−0.066
0.199
−0.014
SES
0.093
0.131
0.030
Emotional Support
−0.101
0.087
−0.059
Active Involvement
−0.018
0.079
−0.011
Demandingness
0.022
0.073
0.013
Academic Expectation Stress
−0.164
0.011
−0.651***
Total R2 = 0.40
*p < 0.05. **p < 0.01 ***p < 0.001
The first model tested was for well-being as shown in Fig. 2. It appears that the model is a good fit for the data with χ2 of 18.06, DF = 16, p = 0.320 and χ2/ degrees of freedom (CMIN/DF) is 1.129. The comparative fit index (CFI) is 0.99, the Incremental Fit Index (IFI) is 0.99. The Root Mean Square Error of Approximation (RMSEA) is 0.019 and the probability of a close fit (PCLOSE) is significant (PCLOSE = 0.928, p < 0.001).
Fig. 2
Path model of well-being; (Med Mother’s education, SC self compassion, GHP Good Health Behaviour, SES socioeconomic status, Dem demandingness, ES emotional support, CoD Children of Divorce, AExp academic expectation stress, PsyCap Psychological capital)
×
Similarly, a model for QoL was tested as per Fig. 3. This model is also a good fit for the data with χ2 of 20.51, DF = 16, p = 0.198 and χ2/ degrees of freedom (CMIN/DF) is 1.282. The comparative fit index (CFI) is 0.99, the Incremental Fit Index (IFI) is 0.99. The Root Mean Square Error of Approximation (RMSEA) is 0.028 and the probability of a close fit (PCLOSE) is significant (PCLOSE = 0.868, p < 0.001).
Fig. 3
Path model of Quality of Life; (Med Mother’s education, SC self compassion, QoL quality of Life, GHP Good Health Behaviour, SES socioeconomic status, Dem demandingness, ES emotional support, CoD Children of Divorce, AExp academic expectation stress, PsyCap Psychological capital)
×
Discussion
It has been empirically established that health and well-being are inextricably link to academic performance in school children (Ickovics et al., 2014). The aim of the current study was to explore the relationship between home background, parental influence, academic expectation stress and health behaviour, well-being and quality of life in older school children and in particular to test the role of psychological capital and self-compassion in the process. This was done by testing the model shown in Fig. 1. Firstly, the data show a strong and negative impact of academic expectation stress on well-being and quality of life. While there was a significant inverse correlation with good health behaviour this did not translate into an effect in path analysis. This could be because the relationship between stress and health behaviour is complex and multifaceted (Schneiderman et al., 2005) in that while engaging in positive health behaviours (healthy diet, exercise, etc.) can alleviate stress, there is evidence that poor health behaviour (poor diet, lack of exercise) is a response to life stress and a means of coping.
Academic expectation stress was related to self-compassion in a relationship which indicates that individuals who are compassionate towards the self, experience less academic expectation stress. This is likely to be a two-way relationship but cannot be explicated in cross sectional data. Academic expectation stress was inversely correlated with psychological capital but in the path analysis this relationship was negligible. However, it has an indirect relationship with psychological capital via self-compassion. This suggests a moderation effect of self-compassion.
Academic stress is predicted by socioeconomic status (SES), positive parenting, and children of divorce in the path model. It would appear that children from higher SES backgrounds, from intact home backgrounds, and more overinvolved and less emotionally supportive parents experience higher levels of academic expectation stress.
SES is also predictive of good health behaviour, well-being, quality of life, self-compassion and psychological capital in that those who are better off are more likely to show self-compassion, to exhibit greater levels of psychological capital, to engage in healthier lifestyles, and to report better well-being and quality of life. This supports previous research which shows a link with health behaviour (Coombs et al., 2013; Kipping et al., 2015), well-being (Bøe et al., 2012), and quality of life (Didsbury et al., 2016), although the latter has been health-related quality of life. The findings regarding SES and self-compassion and psychological capital appear to be novel as there does not appear to be any previous evidence.
In terms of parental academic socialisation, we found that a combination of parental emotional support and positive active involvement in their child’s education was directly related to quality of life and well-being and also had an indirect effect through self-compassion and psychological capital. This is cross sectional data, but it is reasonable to suggest that the most likely mechanism is that warm and engaged parenting encourages self-compassion and helps build psychological capital in children. There is evidence for this in relation to self-compassion (Neff & McGehee, 2010).
Mother’s education is linked to higher self-compassion, well-being and better quality of life. There is some previous evidence linking mother’s education to quality of life in adulthood (Richter & Lemola, 2017), and substantial evidence linking it to academic achievement (Magnuson, 2007).
The main limitation of this study was its cross-sectional design which limit any strong conclusions from the findings. However, there was a relatively large sample. Having said that the findings do confirm some previous research and point the direction for taking the research further.
Theoretically the research literature provides evidence of relationships between some of the variables measured in this study. Academic expectation stress and parental academic socialisation has been shown to separately impact well-being (Boonk et al., 2018; Ceballo et al., 2014; El Nokali et al., 2010; Poots & Cassidy, 2020; Vasquez et al., 2016), but their joint effect has not been investigated. These effects have been looked at from a deficit perspective with little recognition of their positive impact and no evidence of variables that might mediate this positive impact. The current study, albeit correlational and cross-sectional, brings these variables together and applies a positive psychology perspective in identifying the potential mediating impact of psychological capital and self-compassion.
In conclusion the findings of this study suggest that the broad model in Fig. 1 is valid. It shows that academic expectation stress is impacted by family background, parenting, and economic advantage. It also shows that academic expectation stress is linked to well-being, quality of life, and indirectly to health behaviour. It provides some evidence that self-compassion may moderate the impact of psychological capital on academic expectations stress. As such it suggests that a focus on self-compassion and psychological capital may be useful in enabling children to deal with the stressful demands of education and as a by-product may increase academic attainment.
Compliance with Ethical Standards
Conflict of Interest
The authors declare no competing interests.
Ethical Approval
The study was approved by the University Research Ethics Committee (UUREC) REC/18/0019.
Informed Consent
Informed consent was obtained from all participants and parents / guardians.
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