Evidence map›Paper›PMID 37558996›Full record

ArticleBMC psychiatry2023

Psychometric properties of an Arabic translation of the multidimensional assessment of interoceptive awareness (MAIA-2) questionnaire in a non-clinical sample of Arabic-speaking adults.

Feten Fekih-Romdhane, Diana Malaeb, Mirna Fawaz, Nancy Chammas, Michel Soufia, Sahar Obeid, Souheil Hallit

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Article in BMC psychiatry, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.

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14citing papers in PubMed
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1 · What the graph read from it

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3 · Its place in the literature

Who cites it

14 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

7 authors.

Feten Fekih-RomdhaneThe Tunisian Center of Early Intervention in Psychosis, Department of psychiatry "Ibn Omrane", Razi hospital, 2010, Manouba, Tunisia.
Diana MalaebCollege of Pharmacy, Gulf Medical University, Ajman, United Arab Emirates.
Mirna FawazFaculty of Health Sciences, Beirut Arab University, Tareek Al Jadida, Afeef Al Tiba, 1105, Beirut, Lebanon.
Nancy ChammasSchool of Medicine and Medical Sciences, Holy Spirit University of Kaslik, P.O. Box 446, Jounieh, Lebanon.
Michel SoufiaSchool of Medicine and Medical Sciences, Holy Spirit University of Kaslik, P.O. Box 446, Jounieh, Lebanon.
Sahar Obeid *Social and Education Sciences Department, School of Arts and Sciences, Lebanese American University, Jbeil, Lebanon.
Souheil Hallit *School of Medicine and Medical Sciences, Holy Spirit University of Kaslik, P.O. Box 446, Jounieh, Lebanon. souheilhallit@hotmail.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundInteroception refers to processes through which the nervous system identifies, analyzes, and integrates the information generated by the physiological state of the body (e.g., from internal organs such as the stomach, heart, or lungs). Despite its potential interest for clinical research and its wide use globally, no Arabic adaptation and validation of the Multidimensional Assessment of Interoceptive Awareness (MAIA-2) questionnaire exists to date. The goal of this study was to examine the psychometric properties of an Arabic translation of the MAIA-2 in a sample of Arabic-speaking community adults from Lebanon. We hypothesized that the Arabic version of the MAIA-2 would yield adequate internal consistency coefficients; the 8-factor structure model would show a good fit to our data, with measurement invariance and good convergent validity.

methodThe Arabic adaptation of the MAIA-2 was developed using the forward-backward translation method. A non-clinical sample of Arabic-speaking adults (n = 359, 59.9% females, mean age = 22.75 years (SD = 7.04)) took part of this validation study. To check if the model was adequate, several fit indices were calculated: the normed model chi-square (χ²/df), the Steiger-Lind root mean square error of approximation (RMSEA), the Tucker-Lewis Index (TLI) and the comparative fit index (CFI). Values ≤ 3 for χ²/df, and ≤ 0.08 for RMSEA, and 0.90 for CFI and TLI indicate good fit of the model to the data.

resultsConfirmatory Factor Analyses corroborated the validity of the original 8-factor structure of the MAIA-2 [χ

conclusionWe contribute the literature by providing the first Arabic adaptation and validation of a measure assessing the multidimensional construct of self-reported interoception. The Arabic MAIA-2 demonstrated good psychometric properties. We thus preliminarily recommend its use to measure the interoceptive awareness construct among Arabic-speaking communities worldwide.

Indexed as

TranslationsAdultFemaleHumansMalePsychometricsReproducibility of ResultsSelf ReportSurveys and QuestionnairesYoung AdultArabicInteroceptionInteroceptive awarenessMAIA-2Psychometric properties

Identifiers

PMID37558996
PMCPMC10410825

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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.