ОПИТУВАЛЬНИК «ГРАМОТНОСТІ ЩОДО ПСИХІЧНОГО ЗДОРОВ’Я»: ОПИС, АДАПТАЦІЯ, ЗАСТОСУВАННЯ

Purpose. The article presents the results of the Ukrainian version of the Mental Health Literacy questionnaire adaptation. Methods. To test the methodology, statistical research methods were used, namely: Shapiro-Wilk test, factor analysis, Pearson correlation, and Ferguson delta index. Results. Mental health literacy is recognized as a prerequisite for early recognition and intervention in mental disorders. The Mental Health Literacy Questionnaire (MHLq) was developed by a group of Portuguese scientists L. Campos, P. Dias, F. Palha, A. Duarte, E. Veiga to comprehensively assess awareness in the field of mental health, rather than its individual aspects. The methodology aims to study the following aspects of mental health: knowledge of mental health problems, misconceptions/stereotypes, help-seeking and first aid skills, self-help strategies, and overall mental health awareness. The adaptation of the questionnaire was carried out in accordance with standard algorithms for adapting foreign-language psychodiagnostic tools: the English version was translated into Ukrainian, and test-retest reliability, parallel form reliability and internal consistency were checked. Conclusions. Testing the Mental Health Literacy questionnaire and verifying its psychometric characteristics makes it possible to state that the developed questionnaire can be used to assess this construct, and this thesis is confirmed by the obtained statistical data.

Authors

Publication Details

Journal
Psychological Prospects Journal
Published
2024-12-01
DOI
https://doi.org/10.29038/2227-1376-2024-44-kos
Primary Topic
Mental Health Treatment and Access
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

ОПИТУВАЛЬНИК «ГРАМОТНОСТІ ЩОДО ПСИХІЧНОГО ЗДОРОВ’Я»: ОПИС, АДАПТАЦІЯ, ЗАСТОСУВАННЯ

Наталія Коструба
Psychological Prospects Journal
Mental Health Treatment and Access
article

ОПИТУВАЛЬНИК «ГРАМОТНОСТІ ЩОДО ПСИХІЧНОГО ЗДОРОВ’Я»: ОПИС, АДАПТАЦІЯ, ЗАСТОСУВАННЯ

Наталія Коструба
article en

Abstract

Purpose. The article presents the results of the Ukrainian version of the Mental Health Literacy questionnaire adaptation. Methods. To test the methodology, statistical research methods were used, namely: Shapiro-Wilk test, factor analysis, Pearson correlation, and Ferguson delta index. Results. Mental health literacy is recognized as a prerequisite for early recognition and intervention in mental disorders. The Mental Health Literacy Questionnaire (MHLq) was developed by a group of Portuguese scientists L. Campos, P. Dias, F. Palha, A. Duarte, E. Veiga to comprehensively assess awareness in the field of mental health, rather than its individual aspects. The methodology aims to study the following aspects of mental health: knowledge of mental health problems, misconceptions/stereotypes, help-seeking and first aid skills, self-help strategies, and overall mental health awareness. The adaptation of the questionnaire was carried out in accordance with standard algorithms for adapting foreign-language psychodiagnostic tools: the English version was translated into Ukrainian, and test-retest reliability, parallel form reliability and internal consistency were checked. Conclusions. Testing the Mental Health Literacy questionnaire and verifying its psychometric characteristics makes it possible to state that the developed questionnaire can be used to assess this construct, and this thesis is confirmed by the obtained statistical data.

Psychological Prospects Journal(44)
Quality Education
Openalex Percentile: Top 71%
Mental Health Treatment and Access
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.