National Institutes of Health Toolbox Emotion Battery for English- and Spanish-speaking adults: normative data and factor-based summary scores

Abstract

Background

The National Institutes of Health Toolbox Emotion Battery (NIHTB-EB) is a “common currency”, computerized assessment developed to measure the full spectrum of emotional health. Though comprehensive, the NIHTB-EB’s 17 scales may be unwieldy for users aiming to capture more global indices of emotional functioning.

Methods

NIHTB-EB was administered to 1,036 English-speaking and 408 Spanish-speaking adults as a part of the NIH Toolbox norming project. We examined the factor structure of the NIHTB-EB in English- and Spanish-speaking adults and developed factor analysis-based summary scores. Census-weighted norms were presented for English speakers, and sample-weighted norms were presented for Spanish speakers.

Results

Exploratory factor analysis for both English- and Spanish-speaking cohorts resulted in the same 3-factor solution: 1) negative affect, 2) social satisfaction, and 3) psychological well-being. Confirmatory factor analysis supported similar factor structures for English- and Spanish-speaking cohorts. Model fit indices fell within the acceptable/good range, and our final solution was optimal compared to other solutions.

Conclusion

Summary scores based upon the normative samples appear to be psychometrically supported and should be applied to clinical samples to further validate the factor structures and investigate rates of problematic emotions in medical and psychiatric populations.

Keywords:

• emotional functioning
• NIH Toolbox Emotion Battery
• factor analyses
• summary scores
• normative data

Supplementary materials

Table S1 Emotion Battery scales in factor solutions examined for best model fit

Table S2 Summary score formulas

Table S3 English-speaking raw scores conversion to standard scores

Table S4 Spanish-speaking raw scores conversion to standard scores

Acknowledgments

This study was supported by a cooperative agreement from the National Institutes of Health to Northwestern University (U2CCA186878; PI: David Cella, PhD). These contents do not necessarily represent an endorsement by the US Federal Government (refer www.healthmeasures.net for additional information). Funding for HealthMeasures was provided by the National Institutes of Health grant U2C CA186878. We wish to thank Michael Thomas, PhD, for his invaluable consultation on statistical methodologies used in this manuscript.

Disclosure

The authors report no conflicts of interest in this work.