Revised Measure of Environmental Qualities of Activity Settings (MEQAS) for youth leisure and life skills activity settings

Abstract

Purpose: The aim was to create an expanded version of a published observer-rated Measure of Environmental Qualities of Activity Settings (MEQAS-32). Method: Testing was conducted using a diverse sample of activity settings. Raters completed the original MEQAS questionnaire (MEQAS-66) for 76 youth leisure and life skills activity settings. Scales for the revised measure (MEQAS-48) were determined using a two-step approach: (a) developing a theoretically-based model based on item-to-item linkages, and (b) confirmatory factor analysis. Results: The analysis revealed a good fitting 9-factor model (CFI= 0.965, RMSEA= 0.049). Five of the six MEQAS-32 scales remained and were validated in an independent dataset. Four additional scales were identified in the MEQAS-48: Comfortable Place-related Qualities, Opportunities for Privacy/Relaxation, Opportunities to Interact with Peers, and Opportunities for Cooperative Group Activity. Opportunities for Choice and Opportunities for Personal Growth were significantly correlated with corresponding youth experiences. Construct validity was demonstrated through predictions for various types of activities. Conclusions: The MEQAS-48 more completely reflects the original conceptualization of the measure’s content than does the MEQAS-32. Findings suggest the increased utility of the measure due to broader coverage of environmental qualities. The MEQAS-48 can be used to assess environmental qualities for research, program design, and clinical practice.

Implications for Rehabilitation

• The MEQAS is the first observer-completed measure of environmental qualities of activity settings.

• Compared to the MEQAS-32, the MEQAS-48 captures a broader range of important environmental qualities, including comfortable place-related qualities, and opportunities for privacy/relaxation, peer interaction, and cooperative group activity.

• The MEQAS-48 has clinical utility for use in program design and development, and research utility for understanding environmental qualities.

Keywords:

• Adolescents
• environmental qualities
• observational measure
• opportunities
• psychometric properties

Acknowledgements

We extend our thanks to Madhu Pinto for assistance with data collection and analyses, and acknowledge our coauthors on previous work on the MEQAS, including Beata Batorowicz, Margot McMain-Klein, Theresa Petrenchik, and Laura Thompson.

Declaration of interest

This work was supported by the CIHR Team in Optimal Environments for Severely Disabled Youth, funded by the Canadian Institutes of Health Research [TWC-95045]. Gillian King holds the Canada Research Chair in Optimal Care for Children with Disabilities, funded by the Canadian Institutes of Health Research. The authors alone are responsible for the content and writing of this paper.

Notes

¹ Because the small sample size of Group 2 was not conducive to maximum likelihood (ML) categorical estimation (used in the initial analyses), the partial test for metric invariance was undertaken with least-squares (LS) categorical estimation. When we repeated the initial analyses (with Group 1) with LS-categorical estimation, we discovered that the fit statistics were quite different between the two methods, with the LS-categorical estimation indicating poor model fit. Inspection of the parameter estimates revealed slightly different loadings, but within factors there was never more than one item ordered differently between the two sets of results. The two methods produced nearly identical ordering of items within factors (with only a few discrepancies), giving us confidence in the results. Although, Rhemtulla [34] looked at the differences between LS-categorical estimation and ML-continuous estimation methods, we are not aware of work comparing LS- and ML-categorical methods.