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27-03-2015 | Uitgave 10/2015

Quality of Life Research 10/2015

Measurement invariance of English and French Health Education Impact Questionnaire (heiQ) empowerment scales validated for cancer

Tijdschrift:
Quality of Life Research > Uitgave 10/2015
Auteurs:
Jennifer Brunet, Sophie Lauzier, H. Sharon Campbell, Lise Fillion, Richard H. Osborne, Elizabeth Maunsell

Abstract

Purpose

If measurement invariance (MI) is demonstrated for a scale completed by respondents from two different language groups, it means that the scale measures the same construct in the same way in both groups. We assessed MI of the French- and English-language versions of the five Health Education Impact Questionnaire (heiQ) empowerment scales validated for the cancer setting.

Methods

Data came from two cross-sectional studies of Canadian cancer survivors (704 English, 520 French). Single-group confirmatory factor analysis (CFA) was used to test whether the hypothesized factor structure of the French-language heiQ empowerment scales fit the data. Multi-group CFAs were conducted to assess different levels of MI conditions (configural, metric, scalar, strict, as well as MI of factor variances, covariances, and latent means) of the French- and English-language heiQ empowerment scales.

Results

The correlated five-factor model showed good fit in both language groups (goodness-of-fit indices: CFI ≥ .97; RMSEA ≤ .07). Goodness-of-fit indices and tests of differences in fit between models supported MI of the five-factor model across the two language groups (∆CFI ≤ −.010 combined with ∆RMSEA ≤ .015).

Conclusions

The French- and English-language heiQ empowerment scales measure the same five dimensions of empowerment in the same way across both language groups. Thus, any observed similarities or differences between French- and English-speaking respondents completing these scales are valid and reflect similarities or differences in empowerment across language groups, not measurement artifact. Consequently, heiQ empowerment data from English- and French-speaking respondents can be directly pooled or contrasted in data analyses.

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