Conference Program

School-related economic difficulties represent a critical yet
underexplored dimension of educational inequality, with parental perceptions
of financial strain related to school playing a pivotal role in
shaping adolescents’ educational trajectories and pathway choices. Despite
growing interest in the socioeconomic determinants of educational
decisions, the literature has predominantly relied on general measures of
economic hardship, lacking domain-specific instruments capable of capturing
the specific financial pressures families face within educational
contexts [1].
This study addresses this gap by developing and validating a novel psychometric
measure of school-related economic difficulties tailored to the
Italian educational system. Data were collected from 2,215 parents of
children aged 12–16 through a structured online questionnaire administered
between July and August 2025 as part of the EduCAR Youth
project. Quota sampling based on geographical area and municipality
size ensured national representativeness. The sample comprised 55.6%
women and 44.4% men, predominantly aged 45–54 years. Educational
attainment was relatively high, with 51.3% of families including at least
one university graduate. Children were predominantly enrolled in upper
secondary school (62.6%), with academic tracks (licei) being the most
common choice (64.2%).
We employed Item Response Theory (IRT) to construct the measurement
scale, specifically utilizing a two-parameter logistic (2PL) model to assess
dichotomous responses capturing whether families had experienced
financial strain across specific school-related domains [2, 3]. An initial
pool of eight items was subjected to exploratory factor analysis, which
revealed a clear unidimensional structure. One item was removed due
to local dependence. The final seven-item scale covers domains including
the purchase of textbooks and school supplies, access to private tutoring,

digital equipment for studying, participation in school trips, foreign language
courses, and school choice. The instrument demonstrated excellent
internal consistency reliability (ω = 0.94), with all items exhibiting high
discrimination parameters (a range: 2.22–3.16), satisfactory item-level
fit statistics (S-χ2 non-significant; RMSEA well below 0.08 for all items)
and a high TIF = 12, on the moderate-to-high difficulty range (b range:
0.39-1.25). Yen’s Q3 statistics confirmed the absence of problematic local
dependence across all final item pairs.
The distribution of latent trait estimates showed moderate positive skewness
(M = 0.29, SD = 0.66, skewness = 0.77), with the majority of families
reporting relatively low school-related economic difficulties, while
a substantial minority experienced significant financial strain. Systematic
group differences emerged across a range of sociodemographic and
educational characteristics. Younger parents, residents of Southern and
Central Italy, single-parent households, larger families, and those with
lower occupational status and educational attainment reported significantly
higher levels of difficulty. Regarding educational variables, higher
difficulty levels were associated with enrollment in technical institutes
and use of educational support services.
The validated seven-item scale offers a concise, psychometrically robust
instrument for identifying families at risk of educational deprivation and
for supporting the design of targeted educational policies and interventions.
Future research should examine longitudinal relationships between
perceived economic difficulties and actual educational outcomes, assess
cross-cultural validity beyond the Italian context, and integrate objective
socioeconomic indicators to complement self-report data.