The Personal and Contextual Contributors to School Belongingness among Primary School Students
The Personal and Contextual Contributors to School Belongingness among Primary School Students
Sharmila Vaz 0 1 2 3 4 5
Marita Falkmer 0 1 2 3 4 5
Marina Ciccarelli 0 1 2 3 4 5
Anne Passmore 0 1 2 3 4 5
Richard Parsons 0 1 2 3 4 5
Tele Tan 0 1 2 3 4 5
Torbjorn Falkmer 0 1 2 3 4 5
0 Funding: This project was funded by a Doctoral scholarship provided by the Centre for Research into Disability and Society and the School of Occupational Therapy and Social Work, Curtin University , Perth , Australia. It was part of a larger study that was awarded the 2007 Social Determinants for Health Research award by Healthway Australia. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript
1 Data Availability Statement: All relevant data are within the paper
2 Academic Editor: Shelly Russell-Mayhew, University of Calgary , CANADA
3 1 School of Occupational Therapy & Social Work, Curtin University , Perth, Western Australia , Australia , 2 School of Education and Communication, CHILD programme, Institution of Disability Research Jonkoping University , Jonkoping , Sweden , 3 School of Pharmacy, Curtin University , Perth, Western Australia , Australia , 4 Department of Mechanical Engineering, Curtin University , Perth, Western Australia , Australia , 5 Rehabilitation Medicine, Department of Medicine and Health Sciences (IMH), Faculty of Health Sciences, Linkoping University & Pain and Rehabilitation Centre, UHL, County Council , Linkoping , Sweden
4 School Belongingness among Primary School Students
5 Hagborg WJ (1994) An exploration of school membership among middle- and high-school students. Journal of Psychoeducational Assessment 12 : 312-323
School belongingness has gained currency among educators and school health professionals as an important determinant of adolescent health. The current cross-sectional study presents the 15 most significant personal and contextual factors that collectively explain 66.4% (two-thirds) of the variability in 12-year old students' perceptions of belongingness in primary school. The study is part of a larger longitudinal study investigating the factors associated with student adjustment in the transition from primary to secondary school. The study found that girls and students with disabilities had higher school belongingness scores than boys, and their typically developing counterparts respectively; and explained 2.5% of the variability in school belongingness. The majority (47.1% out of 66.4%) of the variability in school belongingness was explained by student personal factors, such as social acceptance, physical appearance competence, coping skills, and social affiliation motivation; followed by parental expectations (3% out of 66.4%), and school-based factors (13.9% out of 66.4%) such as, classroom involvement, task-goal structure, autonomy provision, cultural pluralism, and absence of bullying. Each of the identified contributors of primary school belongingness can be shaped through interventions, system changes, or policy reforms.
Competing Interests: The authors have declared
that no competing interests exist.
understanding factors associated with school belongingness, education leaders and teachers
can facilitate the inclusiveness of school environments.
Drawing on the existing knowledge base, the current study aims to bridge the gap in the
literature about the factors associated with primary school belongingness, and present the most
influential personal and contextual factors, using a non US sample of primary school students
with, and without disability.
Aims and objectives
Data collection procedure
Survey questionnaires were administered to all participants, in the second semester (Terms 3
and 4) of the final year in primary school (classes 6 or 7). Administration guidelines were
developed to minimise bias.
Data collection instruments
Sample size estimation
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School Belongingness among Primary School Students PLOS ONE | DOI:10.1371/journal.pone.0123353 April 15, 2015 6 / 21
recommended by instrument developers were followed to replace missing values in these
questionnaires. In cases where guidelines were not available, missing values were replaced using
mean value substitution . Only small amounts of data were missing (< 2.5% at scale level),
and independent samples ttests confirmed that the profiles of those whose data were missing
for various questions were similar to those who responded.
Descriptive statistics were run to summarise the profiles of study participants. In order to
test for the effect of clustering of students (i.e., nesting of students in classes within schools) on
their school belongingness scores, a Hierarchical Linear Model was fitted using the mixed
procedure in SAS.
Pearson correlation coefficients were used to examine associations between independent
variables (IV; student personal factors and contextual factors) and the dependent variable (DV;
school belongingness score) prior to undertaking regression. Multiple linear regression models
were thereafter fitted to describe the relations between the set of IVs (continuous and
categorical) and the primary school belongingness score. Traditional regression summarizes the
relationship between the DV and IVs by describing the mean of the response for each fixed value
of the IV, using a function referred to as the conditional mean of the response [82,83]. Because
linear regression exclusively focuses on the conditional mean, it can detract attention away
from the properties of the whole distribution and thus fail to identify informative trends in the
response distribution. The straightforward assumptions of a linear relationship between IVs
and DV, and that the linear relationship increases smoothly across the range of the IVs, were
tested by dividing each IV into quartiles . Gender, disability status and household-SES
levels were taken as fixed factors and each IV was regressed to the school belongingness score,
using General Linear Model Analysis of Variance (ANOVA). In instances where the school
belongingness score appeared to vary in a linear fashion across the three or four quartile
categories of the IV; the IV was reverted to its original continuous scale. The final presentation of IVs
thus varied as a function of whether their marginal mean estimates supported a consistent
linear trend across the school belongingness score. Dummy variables were created to represent
categorical IVs (personal, family and school contextual factors) incorporated into the regression
The assumptions of linear regression were tested by undertaking preliminary screening of
the data through examination of residuals; examination of the scatterplot of residuals against
predicted values; and testing for multivariate outliers . No obvious pattern to the errors
was detected through examination of the residual scatterplots. No multivariate outliers were
found in any of the steps .
A three-step process was followed to develop the model of primary school belongingness.
Step 1: Covariates. Linear regression models with interaction terms were fitted to test the
influence of gender, disability, and household-SES on students school belonging scores.
Interaction terms were dropped from the model if they were found not to be significant.
Step 2: Covariates + Identification of student personal factors and contextual factors
added in each block. The covariates were added in Step 1 and stepwise backwards
elimination was undertaken to identify the significant factors (p < .05) within student personal, family,
and school contexts that were associated with belongingness in primary school.
Step 3: Rating the explanatory power of independent variables. The explanatory power
of factors in blocks was assessed on the basis of how much each factor block added to the
prediction of school belongingness, over and above that accounted for by the preceding block
The order of entry of blocks into the analysis was:
Block 1: Covariates (gender, disability, and SES);
Block 2: Student personal factors;
Block 3: Family factors; and
Block 4: School and classroom factors.
Output checks from Standard Multiple regression in SPSS that houses the Tolerance,
Variance Inflation Factor (VIF) and the Collinearity Diagnostics output suggested
multi-collinearity was not a problem . Following convention, a p-value < .05 was taken to indicate a
statistically significant association in all tests.
Characteristic of the studys sample
Testing the effect of clustering of students in classes on their school
Predictors of primary school belongingness at the level of the individual
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Block 2. The addition of student personal factors enabled the model to explain 49.5% of
the variability in school belongingness. The increment in the models predictive power was
significant (R change = .471, F statistic for R change = 67.17, p < .001).
Five student personal attributes significantly contributed to the primary school belongingness
model. Higher belongingness was associated with concurrent high levels of social acceptance
competence (Beta = .13, p = .001), low physical appearance competence (Beta = .10, p = .005),
and high social affiliation motivational goal orientation (Beta = .15, p <.001). The use of
low-levels of problem-solving coping skills relative to the average problem-solving group (Beta = -.16,
p < .001), and frequent use of non-productive coping strategies (such as, worrying, ignoring the
problem at hand, and self-blame) (Beta = -.22, p < .001) was associated with lower school
belongingness. Students perceptions of scholastic competence, the pursuit of academic goals for
schooling, and their mental health functioning did not influence their school belongingness
Block 3. With the addition of family factors in Block 3, the models predictive power
increased to 52.5% (R change = .030, F statistic for R change = 11.12, p < .001). Students whose
parents reported low school-based involvement (Beta = -.09, p = .008) were less likely to feel
they belonged in school, while those whose parents expected them to secure a university degree
were more likely to feel belongingness (Beta = .10, p = .006). Other parent factors, such as social
support and parental self-efficacy did not significantly contribute to the model of school
Block 4. School and classroom factors when added in Block 4, enabled the model to
explain 66.4% of the variance in school belongingness (R change = .139, F statistic for R
change = 24.29, p < .001). Students who perceived their classroom to have low level task-goal
structure (Beta = -.11, p = .006) were less likely to belong when compared to their counterparts
who reported average level task-goal structure. Positive associations were found between school
belongingness and involvement in classroom activities (Beta = .17, p < .001); and
belongingness to highly autonomous (Beta = .11, p = .006) and culturally pluralistic classroom
environments (Beta = .17, p < .001). Students were less likely to feel belongingness if their parents
reported that their teachers extended low invitations for parental involvement in their
schooling (Beta = -.07, p = .033). Students who reported being bullied in primary school also reported
lower concurrent school belongingness (Beta = -.10, p = .003).
It is encouraging that each of the influences we identified can be shaped by educators through
implementation of whole-of-school and classroom-based interventions, and policy reforms in
the various education systems.
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