ArticlePDF Available


Research focused on student belonging has sometimes used available measures in a unidimensional way despite evidence of multidimensionality in these scales. This study introduces a new unidimensional measure of school belonging that is psychometrically robust with preliminary evidence of construct validity that we call the Simple School Belonging Scale (SSBS).
The Simple School Belonging Scale
The Simple School Belonging Scale: Working towards a unidimensional measure of student
Erin Feinauer Whiting
Brigham Young University
Department of Teacher Education
Kimberlee Everson
Western Kentucky University
Erika Feinauer
Brigham Young University
Draft Submitted to Measurement and Evaluation in Counseling and Development
Published Online 2017
Full Citation: Whiting, E. F., Everson, K., & Feinauer, E. (in press). The
Simple School Belonging Scale: Working towards a unidimensional measure of
student belonging. Measurement and Evaluation in Counseling and
Development. DOI:
Link to 50 free copies:
The Simple School Belonging Scale
The Simple School Belonging Scale: Working towards a unidimensional measure of student
A student’s sense of belonging, and other closely associated constructs of school community,
have been shown to relate to a large variety of psychological, health-related, and academic factors in
school (Allen & Bowles, 2012; Anderman, 2003; Battistich, Solomon, Kim, Watson, & Schaps,
1995; CDC, 2009a; 2009b; Goodenow & Grady, 1993; Libbey, 2007; MacNeil, Prater & Busch,
2009; Osterman, 2000; Sergiovanni, 1994; Solomon, Watson, Battistich et al, 1996; Voelkl, 2012;
Wingspread, 2004). Conversely, for all students, a lack of school belonging is associated with
loneliness, emotional distress, psychosocial disturbance, suicide, mental illness, and depression
(Allen & Bowles, 2012). School connectedness and belonging has been found to be second only to
family connection in protecting children and adolescents against emotional distress, eating disorders,
and suicide (CDC, 2009a; 2009b). In fact, it has been suggested that connectedness to school is the
strongest protective factor in decreasing negative behaviors such as substance abuse, school
absenteeism, early sexual involvement, and violence for both boys and girls in 7th through 12th grades
(CDC, 2009b; see also Resnick, Bearman, Blume et al, 1997).
School transitions are periods of heightened physical and emotional upheaval for students
(Harter, Whitesell, & Kowalski, 1992) and can interfere with developing a sense of belonging in the
school community. This is especially marked for students transitioning out of elementary schools to
middle school or junior high school who are also experiencing a transition to adolescence, which can
be emotionally disorienting and uncomfortable (Eccles & Roeser, 2010). Middle schools or junior
high schools typically combine students from several elementary schools. They are larger and often
contain a more diverse student body (Eccles & Roeser, 2010). The organization of the school day is
also new, with classes changing every 45-50 minutes, requiring students to adjust to a setting that
requires more organizational skills, increased levels of independence and self-governing, as well as
The Simple School Belonging Scale
increased demands for social awareness (Midgely, Anderman, & Hicks, 1995). Navigating this new
setting includes having multiple teachers and more complex peer interactions throughout the day
(Eccles & Roeser, 2010; Benner, 2011; Wigfield & Wagner 2005). For students at this transition to
the secondary education school environment, school often includes changes in friendships and peer
groups, and can feel impersonal and isolating for many students negatively impacting their sense of
belonging at school (Benner, 2011). This critical stage in schooling provides an interesting and
constructive setting for examining school belonging and the measurement of belonging.
School belonging has been measured in various ways across school settings and age ranges. For
example, Libbey (2004) found that although many scholars acknowledge the importance of belonging
for students and schools, there is a lack of consistency in how this construct is defined and
operationalized in research. She found more than 21 different measures of belonging in an extensive
review of literature on belonging in schools. In fact, many of the related constructs in the literature,
which include school bonding, attachment, relatedness, membership, and others, use similar wording
in their items and scales (Libbey, 2004). Despite this conceptual inconsistency, the Psychological
Sense of School Membership (PSSM, Goodenow, 1993) scale was developed in middle schools for
the use of researchers and school practitioners and has been widely used in research examining
belonging and feeling connectedness to school for students in middle and high schools.
Previous studies using the PSSM have found a sense of belonging or connectedness to
positively correlate with school success and motivation (Goodenow, 1993; McMahon, Parnes, Keys,
& Viola, 2008). Research also has found moderate correlations with better school attendance
(Sanchez, Colon, & Esparza, 2005), academic self-efficacy (Ibanez, Kuperminc, Jurkovic, & Perilla,
2004; Gutman & Midgley, 2000), and GPA (Anderman, 2003; Booker, 2007; Gutman & Midgley,
2000). Additionally, negative relationships have been found between the PSSM scores and scores on
The Simple School Belonging Scale
the Child Depression Index (Shochet, Dadds, Ham, & Montague, 2006). Increased feelings of school
connectedness, as measured by the PSSM, have been found to be related to lower levels of anxiety
(McMahon et al., 2008).
The PSSM was developed by Carol Goodenow (1993) to examine student perceptions of
belonging as it relates to academic motivation in school. She defines the construct measured by the
scale as the “extent to which students feel personally accepted, respected, included and supported by
others in the school environment” (1993, p.80). Forty-two items were initially constructed focusing
on perceptions of liking, personal inclusion, acceptance, respect and encouragement as well as more
general sense of belonging (Goodenow, 1993). These were paired down to 28 before administering
the scale in middle school and junior high school settings. Initially, one third of the questions were
purposefully phrased in a negative direction, and all questions used a 5-point Likert scale (true- not
true)(Goodenow, 1993). Her 18-item measure was developed by removing items that contributed to
low score reliability and exhibited minimal response variance (Goodenow, 1993; You et al, 2011).
Recent research reveals more than 42 studies using the PSSM with an additional 213
references to this scale (You, Ritchey, Furlong, Shochet & Boman, 2011). However only 27 of these
studies use the full 18-question scale as developed by Goodenow (1993) and there are concerns about
the level of inconsistency in the literature in how it is interpreted and used across these studies (You
et al, 2011). As You and associates (2001) note, the PSSM is almost always used as a unidimensional
measure despite conflicting psychometric evidence of its dimensional structure.Uses of the PSSM,
largely as a unidimensional construct, have been helpful for raising questions about the importance of
belonging in schools. Further, Ye and Wallace (2014) argue, “Having a psychometrically sound
measure of students’ sense of school belonging permits future intervention-based work in schools” (p.
213) and suggest that such a scale might be helpful in identifying students who need additional
The Simple School Belonging Scale
support or in monitoring teacher effectiveness. In practice, a clear unidimensional scale of school
belonging with strong psychometric properties would be of value to the field. However, it has been
difficult to find consensus on the appropriate use of the PSSM as a unidimensional approach to
measure school belonging.
Recent research indicates that the PSSM scale is multi-dimensional with debate in the
literature as to both the structure and interpretation of the factors (Cheung & Hui, 2003; Cheung,
2004; Harborg, 1994; 1998; O’Farrell & Morrison, 2003; Ye &Wallace, 2014; You et al, 2011).
Because the PSSM was originally developed as a unidimensional scale, it is not always clear how it is
best adapted to be able to use it as such. Scholars have variously dropped items problematic for
unidimensional use and in efforts to improve psychometric properties (Anderman, 2003; Gutman &
Midgely, 2000; Hagborg, 1994; Hagborg, 1998) or borrowed a few questions to add and compliment
other related items (Voelkl, 1996) but there is not a systematic and agreed upon adaptation for use.
Additionally, there is variability in the resulting factor structures of the PSSM tested in previous
A few notable studies have focused on understanding and unpacking the multidimentionality of
the PSSM in an effort to more clearly define school belonging as measured by this scale. Hagborg
(1994) first raised questions about the PSSM scale reflecting a unidimensional construct, and
attempted to identify subcomponents through a principal components analysis. He identified a three-
factor solution, including the dimensions belonging, rejection, and acceptance. However, he was
unable to identify clear distinctions between the separate dimensions of the scale because of cross-
loadings across factors. As a result he recommended reducing the full 18-item measure because of
these cross loadings to a modified 11-item unidimensional scale (Hagborg, 1994; Hagborg, 1998)
rather than pursuing a three-dimensional understanding of school belonging. Similarly, Cheung and
The Simple School Belonging Scale
Hui (2003; Cheung, 2004) conducted a principal components analysis on a Chinese version of the
PSSM and identified a two-factor solution, comprising of the dimensions school belonging (13 items)
and feelings of rejection (5 items).
You and associates (2011) examined the factor structure of the PSSM using both exploratory
and confirmatory factor analyses using split-half random samples. These authors identified a three-
factor solution, comprised of the factors they called caring relationships, acceptance, and rejection,
and eliminated the possibility of a hierarchical structure with one higher order factor. In line with
other work with the PSSM, these authors found that many items cross-loaded across factors. However
their recommendation was a reduction of items from 18 to 12 retaining all three factors. Likewise, Ye
and Wallace (2014) conducted Exploratory Factor Analysis (EFA) and Confirmatory Factor Analyses
(CFA). These authors discovered a four-factor solution, including three substantive factors and a
method factor. Three items that either cross-loaded on the three substantive factors or had weak
loadings were eliminated from the scale. Ye and Wallace (2014) labeled the substantive factors as
identification and participation in school (6 items), perception of fitting in among peers (5 items),
and generalized connection to teachers (4 items). Additionally, they identified a method factor,
which included all of the negatively worded items (5 items) which were also found to cross-load on
every other factor. These authors argue that this fourth factor is a method factor rather than a true
rejection factor identified in other studies. They argue that a true rejection factor should exist across
domains and contexts, which is not the case in the negatively worded items on the PSSM reflected in
this factor. They further conclude that the rejection factor identified by other authors is most likely
simply a method effect.
Finally, O’Farrell and Morrison (2003) found that all but five items on the PSSM cross-loaded
onto other scales through an exploratory factor analysis of the PSSM along with several other scales
The Simple School Belonging Scale
related to school bonding. These authors suggest that only five items on the PSSM represent
something unique and assert that the construct of school belonging or bonding is indeed complex.
Clearly constructs related to school belonging must be clearly articulated and discretely measured in
order to be useful for stakeholders seeking to improve student experiences.
[Insert Table 1 about here]
From the above reviewed studies, we see the varying and sometimes conflicting ways in
which the PSSM has been shown to measure sense of belonging in schools (see Table 1), which has
led to some confusion about the underlying conceptualization of the construct. You and associates
(2011) assert that much more work needs to be done to understand the factor structure of the PSSM in
order to resolve inconsistencies among studies. The lack of clarity has led to further questions about
the overall continued usefulness of the PSSM as the primary measure used by scholars measuring
students’ sense of belonging at their school, especially when used in a unidimensional application.
Although a multidimensional model of school belonging is clearly important and warrants continued
investigation, unidimentional uses of available measures (such as the PSSM) also suggests the
practical importance of having a reliable and validated simple scale as a starting point for scholars
examining school belonging.
The current study again examines the factor structure of the PSSM in one sample and then
presents work toward the construction and psychometric analysis of a new unidimensional measure of
belonging that we have called the Simple School Belonging Scale (SSBS). The goal of this project is
to return to efforts in the development of a strong unidimensional scale of school belonging, using the
PSSM as a place to start, in order to have a reliable and practical scale for both research scholars and
school practitioners. In this paper we examine the overall structure of the PSSM with our sample in
Phase 1, we explore the potential of a new unidimensional belonging scale using the PSSM with the
The Simple School Belonging Scale
addition of new items in Phase 2, and validate and examine the psychometric properties of data for
this new unidimensional belonging scale in Phase 3.
This project is part of an ongoing collaboration with one junior high school, including grades
7, 8 and 9, located in the intermountain region of the United States. Approximately 900 students were
surveyed about their school experiences at the beginning and end of the school year for 3 consecutive
years. This school is the only middle level school in the town and represents a cross section of the
overall population. A majority of students are White European American and speak English as a first
language, however about 16% of the school population identify as Hispanic or Latino. Additionally,
about 39.5% of students participate in the national free and reduced lunch program at this school.
This sample, like others used to look at the PSSM factor structure, is a convenience sample and
therefore limited in some ways. However, as all students at this school participated in the survey our
sample represents the population of this particular community and school. As previous work with
convenience samples shows various outcomes in the factor structure of the PSSM, we begin by
looking at the factor structure in our own sample to place our work in context and continue to explore
these factor variations.
Data Collection
In the spring of 2013, a 45-minute survey was administered to all students through an online
survey program in the computer lab during school. As part of this survey students answered questions
taken from the Vaux Social Support Record (VSSR, Vaux et al, 1986), a nine-item index of social
support adapted from the original 23-item Social Support Appraisals scale (SS-A, Vaux et al, 1986),
and the full PSSM scale (Goodenow, 1993). In addition to the PSSM, fourteen additional items
The Simple School Belonging Scale
related to the construct of school belonging were included in the survey. The intent in adding
additional items was to modify and extend the PSSM to create a reliable unidimensional scale that
effectively measured school belonging. In order to accomplish this, a pool of additional questions
were developed by the authors from a review of literature and research on belonging. We followed
recommendations by Worthington and Whittaker (2006) who recommend an expert review of a
limited number of items for content validity during scale development stage. They recommend very
limited, if any, construct validity work (convergent, discriminant) at this development stage and argue
that it is best to keep the questionnaire short and central to the purpose as other items may “interact”
with the items being tested and affect response patterns on the critical items that are being tested in
this stage. We selected these 14 items after a review by a panel of scholars for content validity and
clarity, sensitive to the limitations of space in the survey. These were placed as a separate set of items
in the survey along with the PSSM and the VSSR. Various demographic student data was also
gathered from the survey and from the school.
We adopted a four-point likert scale (“NO!,” “no,” “yes,” “YES!”) after considering research
arguing for and against the use of a middle response category in Likert type scales (e.g., Clark &
Watson, 1995; Krosnick, Holbrook, Berent, Carson, Hanemann, Kopp, et al, 2002; Nowlis, Kahn, &
Dhar, 2002). Research indicates that middle response categories can be inconsistent, reflecting
situational endorsements and can be indications of ambivalence, confusion or a form of nonresponse
(Kulas & Stachowski, 2013; Hernández, Drasgow, & González-Romá, 2004). Further, prior studies
have used a four-point scale with adolescents (CDC, 2014). Thus, after consultation with the school
administration and counselors at the school, we deemed it appropriate for our purposes with this
population and age group for these measures.
Data Analysis
The Simple School Belonging Scale
The goal of the first phase of analyses in this study was to replicate the findings from prior
scholars using exploratory and confirmatory factor analyses (CFA). Based on preliminary findings
from these analyses, we then explored alternative structures to the PSSM based on our sample. The
goal of Phase 2 of our analysis was to use the additional information contained in the 14 new
belonging items to both better understand the structure of the PSSM and to identify a supportable
unidimensional adaptation of a belonging scale. To this end, we repeated these EFA and CFA
analyses with the addition of the additional 14 new belonging items to the PSSM questions. Given the
history of using the PSSM as a one-dimensional measure of belonging, our goal of this phase was to
develop a more psychometrically sound unidimensional belonging scale. In Phase 3 we examined the
scale developed in Phase 2 for item difficulty, item and test information, and item discrimination
statistics in order to better understand the adequacy of the scale.
Procedures. To begin our analyses in Phase 1, the overall sample was randomly split into two
subsamples. Sample A comprised the development sample, and Sample B the validation sample. The
881 students included in the spring 2013 panel were randomly split into two groups for analysis.
Sample A included 392 students and Sample B included 465 students. Males consisted of 47.8% of
the students in Sample A and 50.9% in Sample B. Students with free or reduced lunch status included
37.5% of the students in Sample A and 44.5% in Sample B. In Sample A, 80.3% students identified
as white and in Sample B 77.7% identified as white. 9.2% of the students in Sample A identified
Spanish as their dominant language and 7.7% in Sample B. Sample A included 127 seventh graders,
126 eighth graders, and 139 ninth graders compared to 144 seventh graders, 165 eighth graders, and
154 ninth graders in Sample B. On average, the students in Sample A had lived in the local
community for 9.18 years (SD = 4.66) while the students in Sample B had lived in the community for
9.27 years (SD = 4.64).
The Simple School Belonging Scale
For Phase 1 and Phase 2, a hypothesized structure of belonging was identified using EFA with
the development sample (Sample A), including possible item deletions. We began with EFA because
the variety of structures uncovered by prior studies left us unsure as to whether any prior discovered
structure, or something entirely new, might be discovered in our sample. The final hypothesized
structure resulting from EFA was tested in the validation sample (Sample B) using CFA. Although
similar analyses were performed in both Phase 1 and Phase 2 of our study Phase 2 includes new items
in addition to the PSSM that are analyzed in Phase 1.
A WLSMV (robust weighted least squares) estimator was used in MPLUS for both the EFA
and CFA analyses due to the fact that normality could not reasonably be assumed (Brown, 2006;
Muthen & Muthen, 1998-2001). For both EFA and CFA analyses, model fit was examined using the
root mean square error of approximation (RMSEA), the Comparative Fit Index (CFI), and the Tucker
Lewis coefficient (TLI). The RMSEA was considered acceptable if its confidence limits included
0.08 and was considered to be good if they included 0.05, with values closer to zero representing
better fit. The CFI and TLI were considered to indicate good fit if they were above 0.95, and marginal
fit if between .90 and .95, which is in accordance with current standards for these fit statistics
(Bandalos & Finney, 2010; Brown, 2006). However, we chose to interpret these criteria as guidelines
rather than as firm rules (Worthington & Whittaker, 2006).
In examining items with large cross-loadings, we followed the advice of Worthington and
Whittaker (2006) and determined a priori a threshold that would be consistently used for determining
whether cross-loadings suggested item removal. In keeping with their suggestion that that threshold
be set as low as possible provided reliability and validity do not suffer, we used a threshold of .20,
with the understanding that we would increase that threshold if needed. This threshold partly reflected
The Simple School Belonging Scale
our preference for a shorter scale with approximate simple structure, if possible, in order to maximize
usefulness to practitioners and also reduce survey burden when the scale was used in future studies.
Phase 3 analyses were conducted to investigate the psychometric properties and to verify the
new belonging scale specified in Phase 2. These analyses were conducted in R software (R Core
Team, 2014) using the grm function, an estimator based on Samejima’s graded response model
(1969), in the ltm package (Rizopoulos, 2006). This function uses an approximate marginal maximum
likelihood estimation approach. Because sample size requirements are large for polytomous scales,
the entire sample (N = 857) was used for these item response theory-based analyses. A minimum
sample size of 500, with 1000 or more preferred, is considered appropriate for graded response
models (Reise & Yu, 1990). Our purpose, however, was to examine item quality, not to calibrate
particular items, making a split sample less necessary for the IRT analyses. Category response and
information curves were examined for apparent usefulness of the item categories, coverage of the
intended range of the trait, and appropriate discrimination at various levels of the trait. As part of
Phase 3, evidence of construct validity was established by correlating our new unidimensional
belonging scale to the Vaux Social Support Record (Vaux et al, 1986) with the expectation that the
two scales would be strongly, but not perfectly, correlated. Additional construct validity was
established by correlating the scale with the number of years the student had resided in the local
community. This relationship was expected to be weak, but significant and positive.
Phase 1: PSSM Factor Structure
Exploratory factor analyses. Using Sample A, exploratory factor analyses were conducted in
MPLUS (Muthén & Muthén, 1998-2011) using the WLSMV estimator. Factors were rotated using an
The Simple School Belonging Scale
oblique (Geomin) rotation, following Ye and Wallace (2014). Results comparing 2 and 3 factor
models using Sample A are presented in this section.
An examination of eigen-values (λ1 = 9.01, λ2 = 2.11, λ3 = 1.21, λ4 = 0.81) in the EFA initially
suggested a three-factor solution using either the oft-used λ = 1.0 cutoff, examination of scree plots,
and parallel analysis. In the two-factor model, we found inadequate fit (χ2 = 757.41, df = 118, p =
0.000, CFI = .933, TLI = .913, RMSEA = .118). The three-factor model fit noticeably better (χ2 =
496.92, df = 102, p = 0.000, CFI = .959, TLI = .938, RMSEA = .100) with a chi-square difference test
showing statistical significance (Δχ2 = 260.49, Δdf = 16, p < .001), however the RMSEA was still
unacceptably high, as the confidence interval [.091, .109] did not contain even the most liberally
accepted value of .08. The CFI and TLI fit statistics for the 3-factor model, however, indicated good
and adequate model fit respectively. In spite of findings from Ye and Wallace’s (2014) study pointing
to a four-factor model, the Eigen-values from these data provided no justification for a four factor
model in our analyses.
Examination of factor loadings for the three-factor model (Table 2), suggested the majority of
items (13) loaded on the first factor and the other 5 loaded on the second factor. This division is
aligned cleanly with the positive versus negative wording of the items. Unlike Ye and Wallace’s
(2014) finding, only one of the negative items is cross-loaded on another factor suggesting little
evidence of a method effect. The third factor includes at least three items, but the factor loadings are
mostly under 0.50. Thus, the third factor appears to be weakly defined. In addition, all of the items
loading on this factor are cross-loaded onto one of the other factors, with cross-loadings of at
least .554. In fact, only one item from Factor 3 does not cross-load with Factor 1. Thus factor 3 does
not appear to represent a factor that is clearly distinguishable from the others. Correlations among the
factors are included in Table 3.
The Simple School Belonging Scale
[Insert Table 2 about here]
[Insert Table 3 about here]
As our goal is to identify independent factors of belonging, one possibility suggested by our
EFA was to eliminate all items that loaded on the ill-defined third factor, and accept a reduced two-
factor instrument. In this scenario, if the six items with loadings on Factor 3 greater than 0.20 are
eliminated, eight items remain to measure Factor 1 and four items remain to measure Factor 2. We re-
ran the EFA with items 4, 5, 7, 9, 14, and 15 removed and only allowing two factors. Fit statistics
were mixed (χ2 = 278.95, df = 43, p = 0.000, CFI = .963, TLI = .943, RMSEA = .119, Upper limit =
0.132, Lower limit = 0.106). Factors were strongly correlated (r = .53). We conclude, however, that a
2-factor reduced model is the best fit for the PSSM in Sample A and proceed with a CFA to confirm
the model.
Confirmatory factor analyses. In order to validate the findings of a two-factor, 12-item
model suggested by the exploratory factor analyses in Sample A, a CFA was conducted using our
validation sample, Sample B. All factor loadings were moderate to strong (above 0.50) and
statistically significant as shown in Table 2. The factor correlation was high (r = -0.71) suggesting
that the positive and negatively worded items may only be distinguished due to a method effect. Fit
statistics, however, were inconsistent in reflecting even adequate model fit (χ2 = 433.30, df = 53, p =
0.000, CFI = .942, TLI = .928, RMSEA = .125, Upper limit = 0.136, Lower limit = 0.114).
Modification indices suggest a large number of potential error covariances or factor cross-loadings.
The model was not modified, however, as the purpose of the CFA was model validation, not
exploration, and model modifications at this stage were likely to capitalize on chance.
In addition, we estimated the model with negatively worded items as a method effect
(correlated covariances) rather than as a second factor. Model fit using this approach was slightly
The Simple School Belonging Scale
better than when fitting a two factor model, but reached good fit standard for only the CFI fit statistic
2 = 345.43, df = 48, p = 0.000, CFI = .955, TLI = .938, RMSEA = .116, Upper limit = 0.104, Lower
limit = 0.127).
Our results in Phase 1 indicate that the PSSM is not a unidimensional measure of belonging
and does not have good fit as a two-factor model even after eliminating cross loading items. This is in
line with previous work in other samples (Cheung & Hui, 2003; Cheung, 2004; Hagborg, 1994; 1998;
O’Farrell & Morrison, 2003; Ye & Wallace, 2014; You et al, 2011), although we found differences
across the development (Sample A) and validation (Sample B) samples in our own analysis of the
structure of this measure.
In sum, our findings differ from previous scholars in that our analysis pointed to a two-factor
model after removing the six items that loaded onto an unspecifiable third factor. Following Ye and
Wallace (2014), we also explored the possibility that the third factor represented a method effect due
to the negative wording of the items. However, unlike Ye and Wallace, we did not find that all
negatively worded items were cross-loaded with other factors, suggesting the possibility that the
feeling of rejection factor may indeed be a unique construct. As these authors suggest, however,
examining responses to these items on an instrument that contains items from a variety of scales may
help uncover whether these items represent only method effect or represent a substantive construct.
Despite the fact that the PSSM is often used as a unidimensional scale measuring belonging, our
findings suggest that this is an inappropriate use of this scale.
Phase 2: PSSM adding Additional Belonging Items
The goal of the second phase of this study was to determine whether the PSSM could be
improved as a measure of belonging with approximate simple structure with the addition of new
items. The following EFA and CFA analyses explore the development of an optimal unidimensional
The Simple School Belonging Scale
belonging scale using the combined set of items from the PSSM and the 14 new items designed to
measure sense of belonging.
Exploratory Factor Analyses. As in Phase 1, EFAs were estimated in MPLUS using the
WLSMV estimator and Geomin rotation with Sample A. Eigen-values suggested a four-factor
solution when the additional items were included (λ1 = 16.43, λ2 = 3.05, λ3 = 1.68, λ4 = 1.34, λ5 =
0.95), but a three-factor solution was also estimated for comparison. The three-factor solution had
adequate fit on all measures (χ2 = 1563.62, df = 403, p = 0.000, CFI = .948, TLI = .937, RMSEA
= .086, Upper limit = .090, Lower limit = .081). However, the four-factor solution had excellent fit (χ2
= 1194.48, df = 374, p = 0.000, CFI = .964, TLI = .952, RMSEA = .075).
The pattern of factor loadings for the four-factor solution (Table 4) revealed many significant
cross-loadings. Factor 1 included most of the positively worded items and, as in Phase 1, Factor 2
included all the negatively worded items. The third factor in this model was constructed similarly to
the third factor found in Phase 1, when only items from the PSSM were included. In this model,
Factor 3 is more cohesive though still comprised of items only from the PSSM. The addition of the
new items appears to have clarified the factor structure, with many squared factor loadings above
0.50 and at least two of the items are measured without cross-loading on other factors. The fourth
factor is unique among the factors in that it includes a balance of positively and negatively worded
items. All of the factor four items, however, had cross-loadings on either Factor 1 or Factor 2 of at
least .578, making this factor independently uninterruptable. Interestingly, even following Ye and
Wallace’s (2014) approach where the factor representing negative items is considered a method
effect, considering Factor 4 as an independent factor remains problematic in our analyses. Factor
correlations are included in Table 5.
[Insert Table 4 about here]
The Simple School Belonging Scale
[Insert Table 5 about here]
In sum, additional items were designed to represent the construct of school belonging and
included in the analyses in order to validate the constructs represented by the PSSM itself. We
uncovered a three-factor structure for our sample in our EFA. The first factor seemed best represented
by a factor we called school belonging, the feeling that a student feels comfortable, accepted, and
liked at the school. The second factor, feelings of rejection, included primarily the negative items.
However, significant negative loadings on the second factor in the EFA for the positively-worded
items “I can really be myself at this school” and “I fit in with other students at (school name)” may
provide evidence of a substantive rejection factor rather than a method effect. Cross-loadings,
however, muddy the interpretation of this factor and only two items, both negatively worded, were
identified to measure the factor during the CFA. Thus, this factor is underspecified and may not
validly represent the breadth of the construct. A third factor identified in the EFA, connection to
teachers, was also underspecified (two items) once cross-loaded items were removed for the CFA
analysis. While EFA suggested a fourth factor, school loyalty, which included both positively and
negatively worded items, all items were cross-loaded on other factors. Thus the school loyalty factor
cannot be measured as an independent construct. Among these four factors, then, only the school
belonging factor, indicated by ten items, is potentially fully specified.
Based on these exploratory analyses, two final approaches to modeling belonging from these
data emerged as options to be confirmed through CFA. The first approach considered included
eliminating all items that loaded strongly on the problematic Factor 4, with any other items with
significant cross-loadings also removed. This model would retain the ten items that loaded cleanly on
Factor 1, the two items that loaded cleanly on Factor 2, and the two items that loaded cleanly on
Factor 3. As noted above, this multidimensional approach raised question about the possibility of
The Simple School Belonging Scale
being fully specified. The second approach retains the ten items on Factor 1 and eliminates all other
items. This approach is in line with our overarching research goal, seeking to confirm a
unidimensional model of belonging.
Confirmatory Factor Analyses. Confirmatory factor analyses using Sample B revealed that
both approaches to the data that emerged from the EFA were viable models. A multifactor model was
found to have good fit (χ2 = 276.61, df = 74, p = 0.000, CFI = .975, TLI = .969, RMSEA = .077,
Upper Limit = .067, Lower Limit = .086), after dropping items from Factor 4 as suggested by the
EFA. The second approach, specifying a unifactor model, also was confirmed to have good fit. As
our goal in these analyses was to explore the feasibility of developing a robust unidimensional model
in order to advance the work of belonging among adolescent students, we present the results of this
second approach, the unifactor model, in this paper.
The ten-item unifactor model had good fit (χ2 = 150.50, df = 35, p = 0.000, CFI = .982, TLI
= .977, RMSEA = .084, Upper Limit = .098, Lower Limit = .071). Interestingly this factor included 5
items from the PSSM and 5 items from the new belonging questions added in Phase 2. All
standardized loadings were large (at least 0.635) and statistically significant (Table 5). The internal
consistency as measured by Cronbach’s alpha was 0.91 for the scores estimated using this unifactor
model. Using Raykov’s (2004) CFA-based method, the scale reliability of the scores was 0.96.
Phase 3: Item Response and Construct Validation of the Unidimensional Scale
The results of our confirmatory factor analysis in Phase 2 show that our 10-item one factor
model represents a robust unidimensional measure of student belonging. These encouraging results
led us to further test the psychometric properties of the scores in this new belonging scale through an
item response analysis and construct validation, which we carried out in Phase 3 of this study.
The Simple School Belonging Scale
Item Response Analysis. Using the graded response model (Samejima, 1969), the final
unidimensional factor model converged and reported a negative log likelihood of -7960.872 with AIC
= 16001.74 and BIC = 16192.11. These measures are most interpretable in comparing models, with
lower values representing better fit. Item parameter estimates indicate all items are discriminating
(discrimination parameters greater than 1.0), suggesting a much higher probability of selecting a
higher response category if the person has a greater sense of belonging. Thresholds for each item are
fairly evenly spaced and non-overlapping (Table 6) ), indicating all response categories are
functioning well with each category representing a higher degree of belonging. Item category
response curves (Figure 1) verify the distinct functioning of the response categories for this sample.
[Insert Table 6 about here]
[Insert Figure 1 about here]
In addition, item information curves (Figure 2) suggest that the items provide optimal
information(the item curves are peaked) about respondents with ability levels between -2 and 2 on
the scale. For our scale, 97.87% of respondents had factor scores in this ability range, as estimated by
the model. In essence, the IRT analysis suggests that the items individually extract helpful
information that allows for fine distinctions in the levels of belonging possessed by the respondents to
this survey.
[Insert Figure 2 about here]
Construct Validation. While we made significant efforts toward content validity we also
found some limited evidence of construct or criterion validity. The size of the loadings from the CFA
for the ten-item unidimensional school belonging scale as well as the reliability evidence suggest high
levels of factor cohesion. Using Sample B in MPLUS, evidence of construct validity was found
through correlating the new ten-item school belonging scale with the Vaux School Support Scale
The Simple School Belonging Scale
(1986). Although both scales had items measuring student perceptions of whether people at school
care and can help students at school in one form or another, items do not overlap in these two scales.
When both scales were included, the model had mediocre fit (χ2 = 1018.92, df = 103, p = 0.000, CFI
= .935, TLI = .924, RMSEA = .138, Upper Limit = .146, Lower Limit = .131). However the
correlation between the two constructs was r = 0.64, which aligns with expectations, suggesting some
evidence of construct validity. Model fit might be improved by adding error covariances within the
social support scale. However, we felt we had found adequate evidence of validity without making
revisions to the measurement of school support. The belonging scale correlated weakly with the
number of years the student had lived in the local community (r = 0.142, p = .007), as expected (see
also Gallagher, 1996). This provides some limited evidence of discriminant validity, however, much
more work related to validating this scale in in order. As we have exhausted the limits of this
particular data, future work with a new sample can extend this work and gather more evidence of
construct validity.
In sum, the scale tested in our analyses in Phase 3 that includes five PSSM items and five new
items, has strong psychometric properties, including high score reliability. These findings point to the
construction of a new, robust, unidimensional, measure of school belonging with minimal
measurement error. We have called this new measure the Simple School Belonging Scale (SSBS).
The development of this new scale is significant because it provides a unidimensional scale that can
be used to compare school belonging across groups and track change in school belonging for
individuals across time.
Having a sense of belonging in school is protective for students and supports the psychosocial
and academic wellbeing of students. This is particularly interesting in middle level education during
The Simple School Belonging Scale
which time students are in a crucial transition time. Unfortunately, there has not been consensus in the
field on ways to conceptualize and measure student belonging. One commonly used measure has
been the PSSM, which has generally been applied unidimensionally and without much psychometric
substantiation. We argue that a unidimensional measure of student belonging in schools is warranted
to assist researchers and practitioners in intervention-based work and increase insight into helpful
approaches for student belonging (Ye &Wallace, 2014).
The main contribution from this study is the presentation of a new measure of school
belonging, the Simple School Belonging Scale (SSBS). The SSBS contains 10 items, 5 taken from the
PSSM and 5 from a set of new items collected for this study. Results from our analyses reveal that the
SSBS is psychometrically sound with preliminary evidence of construct validity. Interestingly, the
inclusion of these new belonging items also clarified the structure of the PSSM items in our
exploratory factor analyses.
Our study builds on the work by scholars who began to critique the PSSM in an effort to
improve the measurement of school belonging overall. This study extends the work of previous
scholars by developing and testing a new measure of belonging that is more appropriate for
unidimensional applications than previously used measures such as the PSSM. Although this is an
important contribution, it is just one step forward in conceptualizing and measuring school belonging
in more coherent and unified ways. Future research should attend to validation of the SSBS across
age groups and across varied contexts in order to continually advance the theoretical and
methodological underpinnings of student belonging.
The continued use of the PSSM as a unidimensional measure of belonging in research
suggests the usefulness and demand for a simple unidimensional scale. Indeed, there is much that can
be learned by examining an overall sense of belonging in schools with a simple reliable
The Simple School Belonging Scale
unidimensional tool. However, we should also acknowledge the difficulties revealed in work to
develop such a scale. Our work here has been interested in developing a psychometrically strong
unidimensional measure of belonging that can be consistently used by researchers and practitioners in
the field. Yet, we also recognize the overwhelming evidence of the complexity surrounding
measurement of school belonging that must be closely examined as we go forward. Although we did
not pursue further analysis due to our specific purpose in this study, our own work suggests that a
two-dimensional approach might also yield productive insight into the conceptual terrain of school
belonging. There is certainly much more work to be done in unpacking and further specifying
constructs related to belonging. We encourage future research to expand understandings of how
concepts of school belonging, connectedness, bonding, social support, and other related constructs
relate and differ from each other.
The Simple School Belonging Scale
Ainscow, M. (2005). Developing inclusive education systems: what are the levers for change?
Journal of Educational Change, 6(2), 109–124. Doi:10.1007/s10833-005-1298-4
Allen, K. A., & Bowles, T. (2012). Belonging as a Guiding Principle in the Education of Adolescents.
Australian Journal of Educational and Developmental Psychology, 12, 108-119.
Anderman, L. (2003). Academic and Social Perceptions as Predictors of Change in Middle School
Students ’ Sense of School Belonging. Journal of Experimental Education, 72(1), 5–22.
Bandalos, D. L., and Finney, S. J. (2010). Factor analysis: Exploratory and confirmatory. In G. H.
Hancock & R. O. Mueller (Eds.), The Reviewer’s Guide to Quantitative Methods in the Social
Sciences (93-114). New York: Routledge.
Battistich, V., Solomon, D., Kim, D. I., Watson, M., & Schaps, E. (1995). Schools as communities,
poverty levels of student populations, and students’ attitudes, motives, and performance: A
multilevel analysis. American Educational Research Journal, 32(3), 627-658.
Benner, A. D. (2011). The transition to high school: Current knowledge, future directions.
Educational psychology review, 23(3), 299-328.
Booker, K. C. (2007). Likeness, comfort, and tolerance: Examining African American adolescents’
sense of school belonging. The Urban Review, 39, 301-317. Doi:10.1007/s11256-007-0053-y
Brown, T. (2006). Confirmatory Factor Analysis for Applied Research. New York: Guilford Press.
Centers for Disease Control and Prevention (CDC) (2014). C4. Prosocial Involvement, Opportunities
and Rewards—Seattle Social Development Project. In Attitude and Belief Assessments.
Retrieved at
Centers for Disease Control and Prevention. (2009a). Fostering School connectedness: improving
student health and academic achievement. Atlanta, GA: U.S. department of health and human
services. Retrieved from Centers for disease control and prevention. Accessed at
Centers for Disease Control and Prevention. (2009b). School connectedness: strategies for increasing
protective factors among youth. Atlanta, GA: U.S. department of health and human services.
Retrieved from Centers for disease control and prevention. Accessed at
Cheung, H. Y. (2004). Comparing Shanghai and Hong Kong students’ psychological sense of school
membership. Asia Pacific Education Review, 5(1), 34-38.
Cheung, H. Y., & Hui, S. K. F. (2003). Mainland immigrant and Hong Kong local students’
psychological sense of school membership. Asia Pacific Education Review, 4(1), 67-74.
The Simple School Belonging Scale
Clark, L. A., & Watson, D. (1995). Constructing validity: Basic issues in objective scale
development. Psychological Assessment, 7, 309–319. Doi:10.1037/1040-3590.7.3.309.
Eccles, J. S., & Roeser, R. W. (2010). An ecological view of schools and development. Handbook of
research on schools, schooling, and human development, 6-21.
Gallagher, S. L. (1996). Adolescents’ perceived sense of belonging. Unpublished master’s thesis, Fort
Hays State University, Hays, KS.
Goodenow, C. (1993). The psychological sense of school membership among adolescents: Scale
development and educational correlates. Psychology in the Schools, 30(1), 79–90. Retrieved
Goodenow, C., & Grady, K. E. (1993). The Relationship of School Belonging and Friends’ Values to
Academic Motivation Among Urban Adolescent Students. The Journal of Experimental
Education, 62(1), 60–71. Doi:10.1080/00220973.1993.9943831
Gutman, L. M., & Midgley, C. (2000). The role of protective factors in supporting the academic
achievement of poor African American students during the middle school transition. Journal
of Youth & Adolescence, 29, 224-248. Doi:10.1023/A:1005108700243
Hagborg, W. J. (1994). An Exploration of School Membership among Middle- and High-School
Students. Journal of Psychoeducational Assessment, 12(4), 312–323. Retrieved from
Hagborg, W. J. (1998). An investigation of a brief measure of school membership.
Adolescence, 461-468.
Harter, S., Whitesell, N. R., & Kowalski, P. (1992). Individual differences in the effects of
educational transitions on young adolescent’s perceptions of competence and motivational
orientation. American Educational Research Journal, 29(4), 777-807.
Hernández, A., Drasgow, F., & González-Romá, V. (2004). Investigating the functioning of the
middle category by means of a mixed-measurement model. Journal of Applied Psychology,
89, 687–699. Doi:10.1037/ 0021-9010.89.4.687.
Ibanez, G. E., Kuperminc, G. P., Jurkovic, G., & Perilla, J. (2004). Cultural attributes and adaptations
linked to achievement and motivation among Latino adolescents. Journal of Youth and
Adolescence, 33, 559-568. Doi:10.1023/B:JOYO.0000048069.22681.2c
Krosnick, J. A., Holbrook, A. L., Berent, M. K., Carson, R. T., Hanemann, W. M., Kopp, R.J., et al.
(2002). The impact of ‘‘no opinion’’ response options on data quality: Non-attitude reduction
or an invitation to satisfice? Public Opinion Quarterly, 66, 371–403. Doi:10.1086/341394.
The Simple School Belonging Scale
Kulas, J. T. & Stachowski, A. A. (2013). Respondent rational for neither agreeing nor disagreeing:
Person and item contributors to middle category endorsement intent on Likert personality
indicators. Journal of Research in Personality, 47(4), 254-262.
Libbey, H. P. (2004). Measuring student relationships to school: attachment, bonding,
connectedness, and engagement. Journal of School Health, 74(7), 274-283.
Libbey, H. P. (2007). School connectedness: influence above and beyond family connectedness.
United states: UMI.
Ma, X. (2003). Sense of Belonging to School : Can Schools Make a Difference ? Journal of
Educational Research, 96(6), 340–349.
MacNeil, A. J., Prater, D. L., & Busch, S. (2009). The effects of school culture and climate on student
achievement. International Journal Leadership in Education, 12(1), 73–84.
McMahon, S. D., Parnes, A. L., Keys, C. B., & Viola, J. J. (2008). School belonging among low-
income urban youth with disabilities: Testing a theoretical model. Psychology in the Schools,
45, 387-401. Doi:10.1002/pits.20304
Midgley, C., Anderman, E., & Hicks, L. (1995). Differences between elementary and middle school
teachers and students: A goal theory approach. The Journal of Early Adolescence, 15(1), 90-
Muthén, L. K., & Muthén, B. O. (1998-2011). Mplus User's Guide. Sixth Edition. Los Angeles, CA:
Muthén & Muthén.
Nowlis, S. M., Kahn, B. E., & Dhar, R. (2002). Coping with ambivalence: The effect of removing a
neutral option on consumer attitude and preference judgments. Journal of Consumer
Research, 29, 319–334.
O’Farrell, S. L., Morrison, G. M. (2003). A factor analysis exploring school bonding and related
constructs among upper elementary students. California School Psychologist, 8, 52-72.
Osterman, K. F. (2000). Students’ Need for Belonging in the School Community. Review of
Educational Research, 70(3), 323–367. doi:10.3102/00346543070003323
Raykov, T. (2004). Behavioral scale reliability and measurement invariance evaluation using latent
variable modeling. Behavior Therapy, 35, 89-103.
Reise, S. P., & Yu, J. (1990). Parameter recovery in the graded response model using MULTILOG.
Journal of Educational Measurement, 27 (2), 133-144.
Resnick, M.D., Bearman, P.S., Blume, R.W., et al. (1997). Protecting adolescents from harm.
Findings from the National Longitudinal Study on Adolescent Health. JAMA: The Journal of
The Simple School Belonging Scale
the American Medical Association, 278 (10):823-832.
R Core Team (2014). R: A language and environment for statistical computing (Version 3.1.1)
[Computer software]. Vienna, Austria: R Foundation for Statistical Computing. Program
available at
Rizopoulos, D. (2006). ltm: An R package for latent variable modeling and item response theory
analyses, Journal of Statistical Software, 17(5), 1-25. Available at
Samejima, F. (1969). Estimation of latent ability using a response pattern of graded scores.
Psychometrika Monograph Supplement, 34, 100–114.
Sanchez, B., Colon, Y., & Esparza, P. (2005). The role of sense of school belonging and gender in the
academic adjustment of Latino adolescents. Journal of Youth & Adolescence, 34, 619-628.
Shochet, I. M., Dadds, M. R., Ham, D., & Montague, R. (2006). School connectedness is an
underemphasized parameter in adolescent mental health: Results of a community prediction
study. Journal of Clinical Child and Adolescent Psychology, 35, 170-179.
Sergiovanni, T. J. (1994). Building Community in Schools. Catholic Education (pp. 253–257).
Solomon, D., Watson, M., Battistich, V., Schaps, E., & Delucchi, K. (1996). Creating classrooms that
students experience as communities. American Journal of Community Psychology, 24(6),
719–748. Doi:10.1007/BF02511032
Vaux, A., Phillips, J., Holly, L., Thomson, B., Williams, D., & Stewart, D. (1986). The social support
appraisals (SS-A) scale: Studies of reliability and validity. American Journal of Community
Psychology, 14(2), 195-218.
Voelkl, K. E. (1996). Measuring Students’ Identification with School. Educational and Psychological
Measurement, 56(5), 760–770. Retrieved from
Voelkl, K. E. (2012). School identification. In Handbook of research on student engagement (pp.
193-218). Christenson, S., Reschly, A. L., & Wylie, C. [Eds.]. York, NY: Springer.
Worthington, R. L., & Whittaker, T. A. (2006). Scale development research: A content analysis and
recommendations for best practices. The Counseling Psychologist, 34, 806-836.
Wingspread. (2004). Wingspread declaration on school connections. Journal of School Health, 74(7),
The Simple School Belonging Scale
Wigfield, A., & Wagner, A. L. (2005). Competence, motivation, and identity development during
adolescence. Handbook of competence and motivation, 222-239.
Ye, F., & Wallace, T. L. (2014). Psychological Sense of School Membership Scale Method Effects
Associated With Negatively Worded Items. Journal of Psychoeducational Assessment, 32(3),
You, S., Ritchey, K. M., Furlong, M. J., Shochet, I., & Boman, P. (2011). Examination of
the latent structure of the psychological sense of school membership scale. Journal of
Psychoeducational Assessment, 29(3), 225-237.
The Simple School Belonging Scale
Table 1
Factor identifications for the PSSM in prior studies
Number Item
Cheung & Hui
You et al.
Ye & Wallace
1I feel like a real part of
(school name).
belonging Removed
Identification &
participation in
2People here notice when
I am good at something. Belonging School
belonging Acceptance Removed
3It is hard for people like
me to be accepted here. Rejection Feeling of
rejection Rejection Perception of fitting
in among peers
Other students in this
school take my opinions
Belonging School
belonging Acceptance Perception of fitting
in among peers
Most teachers at this
school are interested in
Belonging School
connection to
6Sometimes I don't feel as
if I belong here. Rejection Feeling of
rejection Rejection
Identification &
participation in
There's at least one
teacher or adult in this
school that I can talk to if
I have a problem.
Belonging School
connection to
8People at this school are
friendly to me. Belonging School
belonging Removed Perception of fitting
in among peers
Teachers here are not
interested in people like
Belonging Feeling of
connection to
10 I am included in lots of
activities at this school. Belonging School
belonging Acceptance
Identification &
participation in
I am treated with as
much respect as other
Belonging School
belonging Removed Removed
12 I feel very different from
most other students here. Rejection Feeling of
rejection Removed
Identification and
participation in
13 I can really be myself at
this school. Belonging School
belonging Acceptance Perception of fitting
in among peers
14 The teachers here respect
connection to
15 People here know that I
can do good work. Belonging School
belonging Removed Removed
16 I wish I were in a
different school. Acceptance Feeling of
rejection Rejection
Identification &
participation in
17 I feel proud of belonging Acceptance School Removed Identification &
The Simple School Belonging Scale
to (school name). belonging participation in
18 Other students here like
me the way I am. Belonging School
belonging Acceptance Perception of fitting
in among peers
The Simple School Belonging Scale
Table 2
Phase 1: Exploratory and confirmatory factor loadings, PSSM
EFA Factor Loadings CFA Standardized Loadings
Item 1 2 3 1 2
1 0.836* -0.118* -0.045 0.850
2 0.758* -0.010 -0.196* 0.692
3 0.021 0.750* 0.004 0.762
4 0.783* 0.113* -0.276*
5 0.805* 0.066 0.275*
6 -0.046 0.857* 0.045 0.823
7 0.554* -0.021 0.398*
8 0.756* -0.210* -0.046 0.794
9 0.007 0.574* -0.414*
10 0.647* -0.025 -0.028 0.595
11 0.693* -0.195* 0.032 0.774
12 -0.003 0.755* 0.052 0.502
13 0.663* -0.252* 0.006 0.779
14 0.730* 0.014 0.564*
15 0.722* -0.111* 0.239*
16 -0.245* 0.575* -0.134* 0.815
17 0.762* -0.119* 0.047 0.836
18 0.677* -0.175* -0.009 0.842
*Significant at p<0.05
The Simple School Belonging Scale
Table 3
PSSM 3-Factor EFA: Factor Correlations
Factor 1 Factor 2 Factor 3
Factor 1 1.000
Factor 2 -.479 1.000
Factor 3 -.289 .200 1.000
The Simple School Belonging Scale
Table 4
Phase 2: Exploratory and confirmatory factor loadings, PSSM + New Items
PSSM Questions
EFA Factors Loadings
CFA Standardized
Loadings (Unifactor
CFA Standardized Loadings
(Multi-factor Model)
1 2 3 4 1 1 2 3
1 I feel like a real part of (school name). 0.769* -0.022 0.039 0.276*
2People here notice when I am good at
something. 0.730* 0.013 0.071 -0.055 0.729 0.727
3It is hard for people like me to be accepted
here. -0.048 0.729* -0.089 0.176*
4Other students in this school take my opinions
seriously. 0.829* 0.112* -0.054 -0.039 0.730 0.719
5Most teachers at this school are interested in
me. 0.386* 0.082* 0.545* 0.044
6 Sometimes I don't feel as if I belong here. -0.195* 0.779* 0.021 0.008 0.959
7There's at least one teacher or adult in this
school that I can talk to if I have a problem. 0.063 -0.011 0.605* 0.109* 0.715
8 People at this school are friendly to me. 0.648* -0.159* 0.198* -0.003 0.748 0.768
9Teachers here are not interested in people like
me. 0.310* 0.555* -0.488* -0.019
10 I am included in lots of activities at this
school. 0.490* 0.02 0.248* 0.035 0.635 0.636
11 I am treated with as much respect as other
students. 0.517* -0.169* 0.314* -0.110*
12 I feel very different from most other students
here. -0.102 0.699* -0.004 0.019 0.508
13 I can really be myself at this school. 0.484* -0.244* 0.258* -0.006
14 The teachers here respect me. 0.045 -0.001 0.832* 0.097* 0.754
15 People here know that I can do good work. 0.279* -0.136* 0.610* -0.091*
The Simple School Belonging Scale
16 I wish I were in a different school. -0.016 0.603* -0.086* -0.548*
17 I feel proud of belonging to (school name). 0.624* 0.005 0.046 0.503*
18 Other students here like me the way I am. 0.578* -0.160* 0.191* -0.043 0.837 0.802
Additional Belonging Questions
1 I feel loyal to people in (school name). 0.633* 0.121* 0.034 0.380*
2 I feel like I belong to (school name). 0.624* -0.123* -0.043 0.443*
I would be willing to work together with
others on something to improve (school
0.336* 0.147* 0.320* 0.384*
4I like to think of myself as similar to others at
(school name). 0.667* -0.085* -0.003 0.170* 0.685 0.679
5Given the opportunity, I would move to a
different school. 0.080* 0.608* 0.007 -0.683*
6 People at (school name) care if I am absent. 0.824* 0.025 -0.09 -0.031 0.739 0.728
7 I fit in with other students at (school name). 0.722* -0.305* -0.042 -0.005
8 I participate in activities at (school name). 0.439* 0.056 0.282* 0.134*
9I would rather attend a different junior high
school. -0.031 0.578* 0.000 -0.666*
10 I feel out of place at (school name). -0.302* 0.685* 0.067* -0.162*
11 I feel like my ideas count at (school name). 0.671* 0.024 0.181* 0.042 0.791 0.800
12 (School name) is a comfortable place for me. 0.726* -0.053* 0.003 0.331*
13 I feel like I matter to people at (school name). 0.857* -0.049* 0.008 0.071* 0.890 0.885
14 People really listen to me when I am at school. 0.814* -0.003 0.098* -0.097* 0.837 0.838
*Significant at p<0.05
The Simple School Belonging Scale 34
The Simple School Belonging Scale
Table 5
PSSM + New Items 4-Factor EFA: Factor Correlations
Factor 1 Factor 2 Factor 3 Factor 4
Factor 1 1.000
Factor 2 -.399 1.000
Factor 3 .623 -.183 1.000
Factor 4 .240 -.126 .306 1.000
The Simple School Belonging Scale
Table 6
Phase 3: Item parameter estimates from graded response model: SSBS
Item Source Threshold 1 Threshold 2 Threshold 3 Discrimination
People here notice when I am good at something. PSSM 2 -1.91 -0.71 0.85 2.10
Other students in this school take my opinions
seriously. PSSM 4 -1.81 -0.34 1.62 2.09
People at this school are friendly to me. PSSM 8 -2.13 -1.22 0.78 2.36
I am included in lots of activities at this school. PSSM 10 -1.99 -0.32 1.48 1.47
Other students here like me the way I am. PSSM 18 -2.20 -1.32 0.50 2.25
I like to think of myself as similar to others at (school
name). New 4 -1.58 -0.47 1.19 1.86
People at (school name) care if I am absent. New 6 -1.72 -0.59 0.95 2.10
I feel like my ideas count at (school name). New 11 -1.53 -0.29 1.29 2.49
I feel like I matter to people at (school name). New 13 -1.55 -0.68 0.77 3.86
People really listen to me when I am at school. New 14 -1.47 -0.43 0.99 3.25
The Simple School Belonging Scale
Figure 1. Sample category response curve for item 4, suggesting good category functioning and
good discrimination. Curves for other items on the scale are similar.
The Simple School Belonging Scale
Figure 2. Item information curves for final unidimensional scale showing peak information is
available between -2 and 2.
... Single items on national surveys (e.g., NCES, 2012) present psychometric limits and alternative instruments with improved psychometric qualities for sampled data have been developed (e.g., Slaten et al., 2018;Whiting et al., 2018). For instance, the Simple School Belonging Scale (SSBS) scale by Whiting was developed in response to multidimensionality issues demonstrated by the PSSM but specifically designed for adolescents, not postsecondary students. ...
... Specifically, we hypothesized that scores in the online context will be slightly lower than scores in the face-to-face context given that face-to-face courses tend to lend themselves to more interactions. Fourth, we expected scores on the BCBS to have the strongest positive relationship with scores from instruments measuring the sense of belonging at the university level and social connectedness (Slaten et al., 2018;Whiting et al., 2018). Fifth, we expected medium to strong positive correlations between BCBS and academic motivation scores. ...
... The current study examined postsecondary students' sense of belonging to other students in their course. Initially, a pool of 20 items was written by the authors based on themes regarding postsecondary students' qualitative descriptions of sense of belonging in online and face-to-face modalities (Author et al., 2021), considering the current sense of belonging instruments (Goodenow, 1993;Slaten et al., 2018;Whiting et al., 2018), and according to guidelines for best practices in educational and psychological measurement (AERA et al., 2014;Bandalos, 2018). A set of 20 items were iteratively refined based on expert reviews and cognitive interviewing until the final set of items was determined. ...
Full-text available
Sense of belonging is an important topic in higher education. However, few studies have examined this important construct at the course level and in the online learning context; even fewer are quantitative by design. The aim of our study was to develop and evaluate a measure of sense of belonging that could be used across different postsecondary learning contexts. A psychometric investigation was conducted at a large, US southeastern university on data using the newly developed Brief Course Belonging Scale (BCBS). Results provide evidence for the unidimensional treatment of BCBS data across delivery context, convergent validity for BCBS scores as they relate positively to belonging at the university level, connectedness, and academic motivation, and discriminant validity for BCBS scores as they related minimally with loneliness. Differential item functioning was detected on one item, but this did not jeopardize score validity and reliability. Specific psychometric implications regarding the domain-specificity of the course delivery context as well as the administration of the novel instrument to a more broad, and diverse student population are recommended.
... Evaluation measures and testing procedures could not be standardised across schools because they needed to be constructively aligned with the specific intervention goals and modes of delivery in each school. However, one measure that was in common across a subset of the interventions (i.e., those focusing on re-establishing a sense of social connectedness) was the Simple School Belonging Scale (Whiting et al., 2018), which has preliminary evidence of adequate content and construct validity (Whiting et al., 2018). Other evaluation items focused on participants' experiences of the intervention (e.g., "What did you enjoy most/least about the activities?"; "How do you think the activities could be improved?") ...
... Evaluation measures and testing procedures could not be standardised across schools because they needed to be constructively aligned with the specific intervention goals and modes of delivery in each school. However, one measure that was in common across a subset of the interventions (i.e., those focusing on re-establishing a sense of social connectedness) was the Simple School Belonging Scale (Whiting et al., 2018), which has preliminary evidence of adequate content and construct validity (Whiting et al., 2018). Other evaluation items focused on participants' experiences of the intervention (e.g., "What did you enjoy most/least about the activities?"; "How do you think the activities could be improved?") ...
Full-text available
In 2020, schools worldwide closed due to the COVID-19 pandemic. Almost one million young people and children were impacted in Ireland, with those from ‘marginalised’ backgrounds being especially vulnerable due to pre-existing inequalities. The Crisis Coping for Marginalised Young People: Living and Learning through COVID- 19 project aimed to explore youth pandemic life and learning experiences and to support the needs of, particularly marginalised, young people, culminating in the implementation of supports for students in schools. Here, we present a praxeological account of the benefits and challenges associated with our novel methodology which involved working ‘through’ 14 final-year student teachers’ practitioner research projects in their designated disadvantaged or socio-demographically diverse placement schools (11) across six counties in the Republic of Ireland, involving 269 students. Supervised closely by the lead researchers, the teacher-researchers conducted empirical research in their schools (involving questionnaires with students and interviews with Principals) to inform the design of academic, social and mixed school-based interventions which were subsequently implemented and evaluated. The empirical findings pointed to young people’s concerns about social isolation, the stability of friendships and having fallen behind academically, and Principals’ concerns about supporting those from marginalised backgrounds and about creating a safe and happy environment upon return to in-person school. In this paper, we highlight our significantly improved understanding of the COVID-related experiences of young people from marginalised backgrounds but point to the uncertain effectiveness of the interventions for improving their educational readjustment. Further, we critically interrogate the challenges encountered which constrained the lead researchers’ and teacher-researchers’ actions.
... Social-emotional competencies. The CNMI Public School System administered a social-emotional competencies survey in May 2019 that assessed students' self-reported responses to items in each of five domains (Transforming Education, 2016;Whiting et al., 2017). Five sets of scale scores ranging from 1 to 5 (where higher scores reflected greater social-emotional competency) were created by averaging self-reported responses to items in each domain: ...
... The CNMI Public School System provided researchers with data from a social-emotional competencies survey administered in May 2019 to students in grades 11 and 12, which included items from the California Office to Reform Education Social and Emotional Learning Survey (Transforming Education, 2016) and the Simple School Belonging Scale (Whiting et al., 2017). Educators use aggregated scores on five domains -self-management, growth mindset, self-efficacy, sense of belonging, and social awareness -to monitor students' social-emotional competencies and inform practices to promote the competencies being assessed (Taylor et al., 2018). ...
Full-text available
This study addressed the need expressed by education stakeholders in the Commonwealth of the Northern Mariana Islands to better understand their high school students’ social-emotional competencies and how those competencies might be associated with students’ academic and behavioral outcomes in high school and college. Social-emotional competencies refer to the knowledge, beliefs, and behaviors that help students recognize and manage their emotions, build positive relationships, and make responsible decisions. In May 2019 grade 11 and 12 students who were enrolled in high schools within the Commonwealth of the Northern Mariana Islands Public School System responded in May 2019 to survey questions regarding their self-management, growth mindset, self-efficacy, sense of belonging, and social awareness using a 5-point scale, with higher scores reflecting greater social-emotional competencies. The study found that high school students and high school students who went on to attend Northern Marianas College scored highest in self-management and lowest in self-efficacy. High school students with higher growth mindset or self-efficacy scores had higher high school grade point averages and grade 10 ACT Aspire math and reading scale scores. Higher self-efficacy scores were also associated with fewer days absent from high school. Students with higher social awareness scores had lower high school grade point averages. Among the high school students who went on to attend college at Northern Marianas College, higher growth mindset scores were associated with higher first semester college grade point averages, after student characteristics were controlled for. None of the four other social-emotional competency domains was associated with any of the college academic or behavioral outcomes.
... School belonging was measured using the 10-item Simple School Belonging Scale (SSBS) [49], with items rated on a 5-point scale (1 = completely disagree, 5 = completely agree). Academic buoyancy was measured with a 3-item scale (e.g. ...
Full-text available
Especially since the 2010s, we have seen rapidly increasing discussion and research on the causal and correlational relations between digital gaming and different dimensions of well-being. This quantitative study presents a starting point of a four-year longitudinal study of the connections between adolescents’ gaming motives, gaming culture participation, and different aspects of psychosocial well-being (digital engagement, internalising symptoms, and academic adjustment) in a sample (N=2053) of actively gaming Finnish 6th and 8th graders (ages 11–14). Results show three distinct player profiles differing in gaming motives and well-being correlates: escapist game players, achiever game players, and recreational game players. These provide a starting point for exploring both the interactions between gaming and well-being and the stability of gaming motives over time.
... Second, this study contributes to the growing body of literature supporting the multidimensional nature of the PSSM. Future research on the correlates of school belonging must guard against treating the PSSM as a unidimensional measure, or else use newer unidimensional tools for measuring school belonging like the Simple School Belonging Scale [112]. ...
Full-text available
Feeling a sense of belonging at school is associated with important positive outcomes for youth and requires youth to engage in positive social relationships. Yet there is a limited understanding of the social factors most associated with youths' school belonging and limited evidence about whether correlates of school belonging vary for marginalized groups like newcomers compared to majority groups. Sweden provides an important context for investigation of these issues because, over the past two decades, the country has experienced an influx of asylum seekers and educational reforms that have altered the composition and functioning of Swedish secondary schools. This study addresses these gaps by (1) investigating which of eight social factors are associated with school belonging among diverse Swedish youth, and (2) examining whether newcomer status moderates the relationship between social factors and school belonging. Hierarchical regression and moderation analyses were used to analyze data from 14 to 19 year-old (n = 233) newcomers and non-newcomers in Sweden. An exploratory factor analysis revealed that the school belonging measure contained two factors: positive perceptions and negative perceptions (reverse coded). For both, stronger school belonging was associated with lower perceived ethnic discrimination. Positive perceptions of school belonging were also associated with more prosocial behaviours and lower emotional problems. Negative perceptions of school belonging were associated with more peer problems. Notably, quantity and quality of peer relationships were not associated with school belonging. There was no consistent evidence of newcomer status moderating the relationship between social factors and school belonging. These results highlight factors associated with school belonging which are modifiable and amenable to intervention or impact by policy-ethnic discrimination, prosocial behaviour, and emotional and peer problems. The absence of moderation by newcomer status suggests that school belonging interventions or related policies are likely to affect newcomer and non-newcomer students similarly.
... Information about participation in FRL was obtained from official school records and student responses were checked against school records to fill in missing data. Finally, school sense of belonging was measured on the survey using the Simple School Belonging Scale (SSBS) which includes 10 items designed to measure overall belonging at school (Whiting, et al., 2018). ...
Full-text available
This study explores open-ended student responses representing advice for belonging from all students in one junior high school with 3 grades of youth ages 12–16 (n = 618). Nearly 5% of responses indicated that there was no way to belong at all. A variety of ideas about what matters for belonging in school emerged, including features of academic life and relationships with teachers, as well as friendships. Surprisingly, responses suggesting personal dispositional qualities far exceeded any other emergent themes. These included calls to be nice and to be outgoing as well as calls to avoid being ‘weird’. Managing and forming friendships were also very important. Chi-square analysis was used to explore differences across basic student characteristics for student positioning toward these emergent concepts of belonging. Gender and grade level stood out as significant, raising questions about how schools can organize to support belonging for students in middle level education. These youth represent the school context as a social and emotional space where they perceive normative dispositions are managed for belonging and where they grapple with authenticity. Implications surface for how to support students during important school transitions by attending to the social and emotional geographies over which young adolescents must traverse.
... This study employs the Simple Student Belonging Scale (SSBS) as a general unidimensional measure of individual students' overall sense of belonging at their school (Whiting et al., 2018). Students taking the survey may choose from a 4-point scale (NO!, no, yes, YES!) to what level they agree with 10 statements of belonging (i.e. ...
Full-text available
We explore student lunchtime experiences as they relate to student sense of belonging. We use SPSS Two‐Step cluster analysis and logistic regression of data from a schoolwide survey (n = 830) in the United States. Stepwise modeling is used to determine the importance of clusters representing lunchtime activity preferences and love of lunch on belonging scores. Loving lunch significantly positively affects school belonging. Students naturally group into five distinct different activity profiles based on lunchtime preferences. These profiles are significantly related to a sense of belonging. Being active with peers during lunch was most strongly correlated with sense of belonging. Lunchtime warrants more attention for fostering a sense of belonging in the school community. Broadening lunchtime activity options, especially in schools where there are few available ways for socializing and being active, has the potential to support the diverse needs of students and increase belonging.
Full-text available
National Journal of Education, ISSN 0972 9569, Vol. XVIII No. (1), January 2020 Published in January 2023 The suitability of 45 items for measuring student belongingness was investigated to develop and validate a Student Belongingness Scale (SBS) through factor analysis. The SBS was administered randomly to 96 boys and 195 girls, total of 291 secondary and higher secondary students with 15.19 as mean age. The data were subjected to exploratory and confirmatory factor analysis. Twelve items were dropped, resulting in the retention of 37 items on the final version. Exploratory factor analysis through SPSS ver. 26, revealed that the items on the final version of SBS loaded on 3 factors, which accounted for 33.873% of the total scale variance. SEM of data-driven measurement model with 3 constructs namely parent, friend, and school belongingness obtained from AMOS achieved absolute model fit, consist of 32 Items with CMIN = 836.389, DF = 457, CMIN/DF = 1.830, CFI = 0.809, SRMR = 0.073, RMSEA = 0.054 and PClose = 0.155. The scale had a Cronbach’s Alpha reliability coefficient of 0.864. Once the teacher comes to know about the parent, friend and school belongingness of students, then it would be certainly helpful in their academic guidance and counselling.
Conference Paper
Full-text available
Την άνοιξη του 2020, λόγω της πανδημίας Covid-19, εισήχθη στην Ελλάδα η σχολική εξ αποστάσεως διδασκαλία, μετασχηματίζοντας την εκπαίδευση και αναδεικνύοντας νέες απαιτήσεις και ρόλους για τους εκπαιδευτικούς. Η παρούσα ποσοτική έρευνα μελέτησε την υλοποίηση της τηλεκπαίδευσης (Μάρτιος 2021), μέσα από τις απαντήσεις 180 διδασκόντων ΔΕ. Από τη σύγκριση των δεξιοτήτων και πρακτικών τους, τόσο κατά τη διετία 2019-21, όσο και γενικότερα, πριν και μετά την εμπειρία αυτή, αποκαλύπτεται η ετοιμότητα ανταπόκρισής τους στις προκλήσεις του επαγγέλματος, αποτυπώνεται η επίδραση στην επαγγελματική τους ανάπτυξη και αναδεικνύεται η διάθεση για μετάβαση σε νέα σχήματα διδασκαλίας και πρακτικών. Σημείο-κλειδί για την εξαγωγή των συμπερασμάτων αποτελούν οι ιδιάζουσες ψυχολογικές συνθήκες κάτω από τις οποίες εργάστηκαν εκπαιδευτικοί και μαθητές, λόγω πανδημίας.
Full-text available
Students' subjective sense of school belonging recently has been identified as a potentially important influence on academic motivation, engagement, and participation, especially among students from groups at risk of school dropout. Students' friends also influence their academic motivation, sometimes negatively. In this study, the relationship among early adolescent students' sense of school belonging, perceptions of their friends' academic values, and academic motivation was investigated among 301 African-American, White/Anglo, and Hispanic students in two urban junior high schools. School belonging was significantly associated with several motivation-related measures—expectancy of success, valuing schoolwork, general school motivation, and self-reported effort. Students' beliefs about their friends' academic values were more weakly related to these outcomes. The correlations between school belonging and the motivation-related measures remained positive and statistically significant even after the effects of friends' academic values were partialled out. School belonging was more highly associated with expectancy for success among Hispanic students than among African-American students, and among girls than among boys.
Full-text available
According to many seasoned survey researchers, offering a no-opinion option should reduce the pressure to give substantive responses felt by respondents who have no true opinions. By contrast, the survey satisficing perspective suggests that no-opinion options may discourage some respondents from doing the cognitive work necessary to report the true opinions they do have. We address these arguments using data from nine experiments carried out in three household surveys. Attraction to no-opinion options was found to be greatest among respondents lowest in cognitive skills (as measured by educational attainment), among respondents answering secretly instead of orally, for questions asked later in a survey, and among respondents who devoted little effort to the reporting process. The quality of attitude reports obtained (as measured by over-time consistency and responsiveness to a question manipulation) was not compromised by the omission of no-opinion options. These results suggest that inclusion of no-opinion options in attitude measures may not enhance data quality and instead may preclude measurement of some meaningful opinions.
Full-text available
Defining sense of community as a feeling of belongingness within a group, this article reviews research about students' sense of acceptance within the school community to address three questions: Is this experience of belongingness important in an educational setting? Do students currently experience school as a community? And how do schools influence students' sense of community? Conceptually, the review reflects a social cognitive perspective on motivation. This theoretical framework maintains that individuals have psychological needs, that satisfaction of these needs affects perception and behavior, and that characteristics of the social context influence how well these needs are met. The concern here is how schools, as social organizations, address what is defined as a basic psychological need, the need to experience belongingness. The findings suggest that students' experience of acceptance influences multiple dimensions of their behavior but that schools adopt organizational practices that neglect and may actually undermine students' experience of membership in a supportive community.
Full-text available
This exploratory study examined whether associations between perceived school experiences and achievement motivation varied by language acculturation and generational status among a sample of immigrant and U.S. born Latino adolescents (n = 129). Ogbu''s (1993) notion of primary and secondary cultural differences was adapted to better suit comparisons within this Latino group using the terms cultural attributes and cultural adaptations. Academic competence, school belonging, and parent involvement were positively related to achievement motivation. Academic competence and parent involvement were strongly related to achievement motivation among students who spoke English or were born in the U.S., suggesting that these associations may be cultural adaptations. Future intervention programs for Latino students, regardless of acculturation or generational status, should focus on making them feel supported and included. Acculturated Latino youth and youth who have lived in the U.S. for a long time should be targeted for programs that enhance academic competence and parent involvement.
Full-text available
The aim of this study was to examine the roles of sense of belonging and gender in the academic outcomes of urban, Latino adolescents. It was expected that sense of belonging would play a different role in males' and females' academic adjustment. Participants (N = 143) included mostly Mexican and Puerto Rican seniors from a large, urban high school. The academic outcomes assessed were grade point average, absenteeism, motivation, effort, and educational aspirations and expectations. As hypothesized, females consistently had more positive academic outcomes than males. Sense of school belonging significantly predicted academic outcomes, including academic motivation, effort, and absenteeism. Regression analyses did not show that gender explained differences in the relationship between sense of belonging and academic outcomes. Implications and future directions for research on urban Latino males and females are discussed.
The authors conducted a content analysis on new scale development articles appearing in the Journal of Counseling Psychology during 10 years (1995 to 2004). The authors analyze and discuss characteristics of the exploratory and confirmatory factor analysis procedures in these scale development studies with respect to sample characteristics, factorability, extraction methods, rotation methods, item deletion or retention, factor retention, and model fit indexes. The authors uncovered a variety of specific practices that were at variance with the current literature on factor analysis or structural equation modeling. They make recommendations for best practices in scale development research in counseling psychology using exploratory and confirmatory factor analysis.
A primary goal of scale development is to create a valid measure of an underlying construct. We discuss theoretical principles, practical issues, and pragmatic decisions to help developers maximize the construct validity of scales and subscales. First, it is essential to begin with a clear conceptualization of the target construct. Moreover, the content of the initial item pool should be overinclusive and item wording needs careful attention. Next, the item pool should be tested, along with variables that assess closely related constructs, on a heterogeneous sample representing the entire range of the target population. Finally, in selecting scale items, the goal is unidimensionality rather than internal consistency; this means that virtually all interitem correlations should be moderate in magnitude. Factor analysis can play a crucial role in ensuring the unidimensionality and discriminant validity of scales. (PsycINFO Database Record (c) 2012 APA, all rights reserved)
Positive school environments and school belonging have been associated with a variety of positive academic, social, and psychological outcomes among youth. Yet, it is not clear how these constructs are related, and few studies have focused on urban at-risk youth with disabilities. This study examines baseline survey data from 136 low-income African American and Latino students in grades 5 to 12, most of whom have disabilities, recently transferred following a school closure. Using structural equation modeling, we tested a model that examined the relationships among school stressors and resources, school belonging, academic outcomes (school satisfaction and academic self-efficacy), and psychological outcomes (anxiety and depression). This model was an excellent fit with the data, and findings indicate that school belonging plays a central role in explaining how school context can affect both psychological and academic outcomes. This model has implications for school-based interventions that can enhance student success and well-being. © 2008 Wiley Periodicals, Inc.
Although prior research has shown sense of community in schools to be related to many positive student characteristics, effective interventions that can create or enhance this sense have not been demonstrated. In this paper we describe a comprehensive elementary school program, implemented by teachers, that was successful in creating a sense of community in the classrooms, as perceived by students. The program was implemented in three elementary schools in a suburban school district; three additional schools in the same district served as a comparison group. The program, which emphasized cooperative learning, the importance of democratic and prosocial values, student autonomy and self-direction, and a child-centered approach to teaching and classroom management, was experienced by a cohort of students from kindergarten through Grade 4, and by a subset of that cohort through Grade 6. Sense of community was assessed—by questionnaire—in Grades 4, 5, and 6; various student outcomes were assessed via questionnaire and interview. Results indicated that the program was successful in heightening students’ sense of community, and that the sense of community—by itself and in combination with program status—related positively to a number of student outcomes. There was also suggestive evidence that students who experienced their classroom as a community attempted to abide by its norms and values, and that the authority structure of the classroom was an important determinant of students’ experience of community and of some of its observed effects.
This study investigated sense of school belonging in a sample of 13 African American high school students. Findings suggest that students felt a stronger sense of connection to their school community when they perceived fewer differences between themselves and others in the school body. In addition, student responses revealed that feelings of comfort and tolerance were essential to personal descriptions of belongingness. Although, likeness and comfort were important when students discussed school belongingness, the same was not true of factors related to academic performance. Limitations of the study and directions for future work are addressed.