Evidence map›Paper›PMID 40264220›Full record

ArticleBMC psychology2025

Fast and effective assessment for individuals with special needs form optimization and prediction models.

Bilal Baris Alkan, Muhammet Kumartas, Serafettin Kuzucuk, Nesrin Alkan

Abstract read
In one paragraph

Article in BMC psychology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Bilal Baris AlkanMeasurement and Evaluation in Education, Faculty of Education, University of Akdeniz, Dumlupınar Boulevard, Campus, Antalya, 07058, Turkey. bbalkan@akdeniz.edu.tr.
Muhammet KumartasGuidance and Psychological Counselling, Beyşehir Guidance and Research Center, Konya, 42700, Turkey.
Serafettin KuzucukMeasurement and Evaluation in Education, Faculty of Education, University of Akdeniz, Dumlupınar Boulevard, Campus, Antalya, 07058, Turkey.
Nesrin AlkanFaculty of Economics and Administrative Sciences, Akdeniz University, Dumlupınar Boulevard, Campus, Antalya, 07058, Turkey.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The aim of this study was to determine which items in the psychological assessment forms used by counselling and research centres for individuals with special needs are effective in classifying individuals into special needs diagnostic categories. Data were obtained from the psychological assessment request forms of 1814 individuals aged 6 to 12 years who were referred to the centre between 2019 and 2023 with suspected special needs and who were classified as having special needs based on psychological and developmental assessments. In addition, we wanted to develop new predictive models using machine learning methods based on these items. Optimizing the psychological assessment application form so that it contains fewer questions may help to make the assessment process faster and more effective. It is expected that the results of this study will make an important contribution to saving time and energy for experts and individuals.

Indexed as

Machine LearningMental DisordersNeeds AssessmentChildFemaleHumansMaleAssessmentMachine learningModelPredictionSpecial needs

Identifiers

PMID40264220
PMCPMC12016118

What OpenQuestion holds

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LicenceCC BY
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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.