Investigating the Construct Validity and Reliability of the Test of Motor Competence Across Iranians’ Lifespan

Sedigheh Salami; Paulo Felipe Ribeiro Bandeira; Parvaneh Dehkordi; Fatemah Sohrabi; Clarice Martins; Michael Duncan; Louise Hardy; Amir Sham

doi:10.1177/00315125231152669

Investigating the Construct Validity and Reliability of the Test of Motor Competence Across Iranians’ Lifespan

Sedigheh Salami, Paulo Felipe Ribeiro Bandeira, Parvaneh Dehkordi, Fatemah Sohrabi, Clarice Martins, Michael Duncan, Louise Hardy, Amir Sham

Research output: Contribution to journal › Article › peer-review

1 Citation (Scopus)

130 Downloads (Pure)

Abstract

Motor competence (MC) has been extensively examined in children and adolescents, but has not been studied among adults nor across the lifespan. The Test of Motor Competence (TMC) assesses MC in people aged 5-85 years. Among Iranians, aged 5-85 years, we aimed to determine the construct validity and reliability of the TMC and to examine associations between TMC test items and the participants’ age, sex, and body mass index (BMI). We conducted confirmatory factor analysis (CFA) to evaluate the TMC’s factorial structure by age group and for the whole sample. We explored associations between the TMC test items and participant age, sex, and BMI using a network analysis machine learning technique (Rstudio and qgraph). CFA supported the construct validity of a unidimensional model for motor competence for the whole sample (RMSEA = .003; CFI = .998; TLI= .993) and for three age groups (RMSEA<.08; CFI and TLI> .95). Network analyses showed fine motor skills to be the most critical centrality skills, reinforcing the importance of fine motor skills for performing and participating in many daily activities across the lifespan. We found the TMC to be a valid and reliable test to measure MC across Iranians’ lifespan. We also demonstrated the advantages of using a machine learning approach via network analysis to evaluate associations between skills in a complex system.

Original language	English
Pages (from-to)	658-679
Number of pages	22
Journal	Perceptual and Motor Skills
Volume	130
Issue number	2
Early online date	7 Feb 2023
DOIs	https://doi.org/10.1177/00315125231152669
Publication status	Published - Apr 2023

Bibliographical note

Copyright © and Moral Rights are retained by the author(s) and/ or other copyright owners. A copy can be downloaded for personal non-commercial research or study, without prior permission or charge. This item cannot be reproduced or quoted extensively from without first obtaining permission in writing from the copyright holder(s). The content must not be changed in any way or sold commercially in any format or medium without the formal permission of the copyright holders.

This document is the author’s post-print version, incorporating any revisions agreed during the peer-review process. Some differences between the published version and this version may remain and you are advised to consult the published version if you wish to cite from it.

Funder

The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: Paulo Felipe Ribeiro Bandeira — BPI-Fundação Cearense de Apoio ao Desenvolvimento Científico e Tecnológico — Research Productivity Grant 04-2022. The others received no financial support for the research, authorship, and/or publication of this article

Keywords

lifespan
machine learning
motor competence
network perspective
Experimental and Cognitive Psychology
Sensory Systems

Access to Document

10.1177/00315125231152669

Post-PrintAccepted author manuscript, 1.19 MB

Cite this

@article{a4a93e0c4e344ea6ba26dd8ed7caa1ae,

title = "Investigating the Construct Validity and Reliability of the Test of Motor Competence Across Iranians{\textquoteright} Lifespan",

abstract = "Motor competence (MC) has been extensively examined in children and adolescents, but has not been studied among adults nor across the lifespan. The Test of Motor Competence (TMC) assesses MC in people aged 5-85 years. Among Iranians, aged 5-85 years, we aimed to determine the construct validity and reliability of the TMC and to examine associations between TMC test items and the participants{\textquoteright} age, sex, and body mass index (BMI). We conducted confirmatory factor analysis (CFA) to evaluate the TMC{\textquoteright}s factorial structure by age group and for the whole sample. We explored associations between the TMC test items and participant age, sex, and BMI using a network analysis machine learning technique (Rstudio and qgraph). CFA supported the construct validity of a unidimensional model for motor competence for the whole sample (RMSEA = .003; CFI = .998; TLI= .993) and for three age groups (RMSEA<.08; CFI and TLI> .95). Network analyses showed fine motor skills to be the most critical centrality skills, reinforcing the importance of fine motor skills for performing and participating in many daily activities across the lifespan. We found the TMC to be a valid and reliable test to measure MC across Iranians{\textquoteright} lifespan. We also demonstrated the advantages of using a machine learning approach via network analysis to evaluate associations between skills in a complex system. ",

keywords = "lifespan, machine learning, motor competence, network perspective, Experimental and Cognitive Psychology, Sensory Systems",

author = "Sedigheh Salami and {Ribeiro Bandeira}, {Paulo Felipe} and Parvaneh Dehkordi and Fatemah Sohrabi and Clarice Martins and Michael Duncan and Louise Hardy and Amir Sham",

note = "Copyright {\textcopyright} and Moral Rights are retained by the author(s) and/ or other copyright owners. A copy can be downloaded for personal non-commercial research or study, without prior permission or charge. This item cannot be reproduced or quoted extensively from without first obtaining permission in writing from the copyright holder(s). The content must not be changed in any way or sold commercially in any format or medium without the formal permission of the copyright holders. This document is the author{\textquoteright}s post-print version, incorporating any revisions agreed during the peer-review process. Some differences between the published version and this version may remain and you are advised to consult the published version if you wish to cite from it. ",

year = "2023",

month = apr,

doi = "10.1177/00315125231152669",

language = "English",

volume = "130",

pages = "658--679",

journal = "Perceptual and Motor Skills",

issn = "0031-5125",

publisher = "Ammons Scientific",

number = "2",

}

TY - JOUR

T1 - Investigating the Construct Validity and Reliability of the Test of Motor Competence Across Iranians’ Lifespan

AU - Salami, Sedigheh

AU - Ribeiro Bandeira, Paulo Felipe

AU - Dehkordi, Parvaneh

AU - Sohrabi, Fatemah

AU - Martins, Clarice

AU - Duncan, Michael

AU - Hardy, Louise

AU - Sham, Amir

N1 - Copyright © and Moral Rights are retained by the author(s) and/ or other copyright owners. A copy can be downloaded for personal non-commercial research or study, without prior permission or charge. This item cannot be reproduced or quoted extensively from without first obtaining permission in writing from the copyright holder(s). The content must not be changed in any way or sold commercially in any format or medium without the formal permission of the copyright holders. This document is the author’s post-print version, incorporating any revisions agreed during the peer-review process. Some differences between the published version and this version may remain and you are advised to consult the published version if you wish to cite from it.

PY - 2023/4

Y1 - 2023/4

N2 - Motor competence (MC) has been extensively examined in children and adolescents, but has not been studied among adults nor across the lifespan. The Test of Motor Competence (TMC) assesses MC in people aged 5-85 years. Among Iranians, aged 5-85 years, we aimed to determine the construct validity and reliability of the TMC and to examine associations between TMC test items and the participants’ age, sex, and body mass index (BMI). We conducted confirmatory factor analysis (CFA) to evaluate the TMC’s factorial structure by age group and for the whole sample. We explored associations between the TMC test items and participant age, sex, and BMI using a network analysis machine learning technique (Rstudio and qgraph). CFA supported the construct validity of a unidimensional model for motor competence for the whole sample (RMSEA = .003; CFI = .998; TLI= .993) and for three age groups (RMSEA<.08; CFI and TLI> .95). Network analyses showed fine motor skills to be the most critical centrality skills, reinforcing the importance of fine motor skills for performing and participating in many daily activities across the lifespan. We found the TMC to be a valid and reliable test to measure MC across Iranians’ lifespan. We also demonstrated the advantages of using a machine learning approach via network analysis to evaluate associations between skills in a complex system.

AB - Motor competence (MC) has been extensively examined in children and adolescents, but has not been studied among adults nor across the lifespan. The Test of Motor Competence (TMC) assesses MC in people aged 5-85 years. Among Iranians, aged 5-85 years, we aimed to determine the construct validity and reliability of the TMC and to examine associations between TMC test items and the participants’ age, sex, and body mass index (BMI). We conducted confirmatory factor analysis (CFA) to evaluate the TMC’s factorial structure by age group and for the whole sample. We explored associations between the TMC test items and participant age, sex, and BMI using a network analysis machine learning technique (Rstudio and qgraph). CFA supported the construct validity of a unidimensional model for motor competence for the whole sample (RMSEA = .003; CFI = .998; TLI= .993) and for three age groups (RMSEA<.08; CFI and TLI> .95). Network analyses showed fine motor skills to be the most critical centrality skills, reinforcing the importance of fine motor skills for performing and participating in many daily activities across the lifespan. We found the TMC to be a valid and reliable test to measure MC across Iranians’ lifespan. We also demonstrated the advantages of using a machine learning approach via network analysis to evaluate associations between skills in a complex system.

KW - lifespan

KW - machine learning

KW - motor competence

KW - network perspective

KW - Experimental and Cognitive Psychology

KW - Sensory Systems

UR - http://www.scopus.com/inward/record.url?scp=85147704034&partnerID=8YFLogxK

U2 - 10.1177/00315125231152669

DO - 10.1177/00315125231152669

M3 - Article

SN - 0031-5125

VL - 130

SP - 658

EP - 679

JO - Perceptual and Motor Skills

JF - Perceptual and Motor Skills

IS - 2

ER -

Investigating the Construct Validity and Reliability of the Test of Motor Competence Across Iranians’ Lifespan

Abstract

Bibliographical note

Funder

Keywords

Access to Document

Other files and links

Fingerprint

Cite this