Towards a Multi-Informant Assessment of Math Anxiety in Primary School Children

A comprehensive understanding of children’s psychological functioning benefits from a multi-informant approach, gathering information from parents, teachers, and, when possible, the children themselves. This strategy enhances reliability, validity, and contextual coverage, addressing the limitations of relying solely on self-reports in young populations. Building on this rationale, the present study aimed to develop and validate parent- and teacher-proxy versions of the Abbreviated Math Anxiety Scale for elementary school children, complementing child self-report measures. A total of 1146 children (50.66% females) aged 6 to 11 years, along with their parents and teachers, participated in the study. Confirmatory factor analyses supported the hypothesized two-factor structure, reflecting learning-related and evaluation-related math anxiety. All scales demonstrated good internal consistency, and correlations among informants were small-to-medium, highlighting the unique contribution of each perspective. Multi-informant scores were negatively associated with children’s mathematical competence, and each informant’s perspective uniquely explains variance in mathematical competence, with teachers’ ratings showing the strongest association. These findings underscore the importance of a multi-informant assessment for capturing children’s math anxiety more accurately, enabling a nuanced understanding of its impact on academic outcomes and supporting early identification and targeted interventions.

Authors

Institutions

Publication Details

Journal
Behavioral Sciences
Published
2026-10-08
DOI
https://doi.org/10.3390/bs16101838
Primary Topic
Education, Achievement, and Giftedness
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Towards a Multi-Informant Assessment of Math Anxiety in Primary School Children

Caterina Primi, Maria Anna Donati, Laura Di Leonardo
Behavioral Sciences
Education, Achievement, and Giftedness
article

Towards a Multi-Informant Assessment of Math Anxiety in Primary School Children

Caterina Primi, Maria Anna Donati, Laura Di Leonardo
article en

Abstract

A comprehensive understanding of children’s psychological functioning benefits from a multi-informant approach, gathering information from parents, teachers, and, when possible, the children themselves. This strategy enhances reliability, validity, and contextual coverage, addressing the limitations of relying solely on self-reports in young populations. Building on this rationale, the present study aimed to develop and validate parent- and teacher-proxy versions of the Abbreviated Math Anxiety Scale for elementary school children, complementing child self-report measures. A total of 1146 children (50.66% females) aged 6 to 11 years, along with their parents and teachers, participated in the study. Confirmatory factor analyses supported the hypothesized two-factor structure, reflecting learning-related and evaluation-related math anxiety. All scales demonstrated good internal consistency, and correlations among informants were small-to-medium, highlighting the unique contribution of each perspective. Multi-informant scores were negatively associated with children’s mathematical competence, and each informant’s perspective uniquely explains variance in mathematical competence, with teachers’ ratings showing the strongest association. These findings underscore the importance of a multi-informant assessment for capturing children’s math anxiety more accurately, enabling a nuanced understanding of its impact on academic outcomes and supporting early identification and targeted interventions.

Behavioral SciencesVol. 16(10)
University of Florence (IT)
Openalex Percentile: Top 7%
Education, Achievement, and Giftedness
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.