Dataset Information

Exploratory factor analysis of the Dizziness Handicap Inventory (German version).

ABSTRACT:

Background

The Dizziness Handicap Inventory (DHI) is a validated, self-report questionnaire which is widely used as an outcome measure. Previous studies supported the multidimensionality of the DHI, but not the original subscale structure. The objectives of this survey were to explore the dimensions of the Dizziness Handicap Inventory - German version, and to investigate the associations of the retained factors with items assessing functional disability and the Hospital Anxiety and Depression Scale (HADS). Secondly we aimed to explore the retained factors according to the International Classification of Functioning, Disability and Health (ICF).

Methods

Patients were recruited from a tertiary centre for vertigo, dizziness or balance disorders. They filled in two questionnaires: (1) The DHI assesses precipitating physical factors associated with dizziness/unsteadiness and functional/emotional consequences of symptoms. (2) The HADS assesses non-somatic symptoms of anxiety and depression. In addition, patients answered the third question of the University of California Los Angeles-Dizziness Questionnaire which covers the impact of dizziness and unsteadiness on everyday activities. Principal component analysis (PCA) was performed to explore the dimensions of the DHI. Associations were estimated by Spearman correlation coefficients.

Results

One hundred ninety-four patients with dizziness or unsteadiness associated with a vestibular disorder, mean age (standard deviation) of 50.6 (13.6) years, participated. Based on eigenvalues greater one respectively the scree plot we analysed diverse factor solutions. The 3-factor solution seems to be reliable, clinically relevant and can partly be explained with the ICF. It explains 49.2% of the variance. Factor 1 comprises the effect of dizziness and unsteadiness on emotion and participation, factor 2 informs about specific activities or effort provoking dizziness and unsteadiness, and factor 3 focuses on self-perceived walking ability in relation to contextual factors. The first factor correlates moderately with disability and the HADS (values >/=0.6). The second factor is comparable with the original physical subscale of the DHI and factors retained in previous studies.

Conclusions

The results of the present survey can not support the original subscale structure of the DHI. Therefore only the total scale should be used. We discuss a possible restructuring of the DHI.

SUBMITTER: Kurre A

PROVIDER: S-EPMC2850321 | biostudies-literature | 2010 Mar

REPOSITORIES: biostudies-literature

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Publications

Exploratory factor analysis of the Dizziness Handicap Inventory (German version).

Kurre Annette A Bastiaenen Caroline Hg CH van Gool Christel Jaw CJ Gloor-Juzi Thomas T de Bruin Eling D ED Straumann Dominik D

BMC ear, nose, and throat disorders 20100315

<h4>Background</h4>The Dizziness Handicap Inventory (DHI) is a validated, self-report questionnaire which is widely used as an outcome measure. Previous studies supported the multidimensionality of the DHI, but not the original subscale structure. The objectives of this survey were to explore the dimensions of the Dizziness Handicap Inventory - German version, and to investigate the associations of the retained factors with items assessing functional disability and the Hospital Anxiety and Depre ...[more]

PMID: 20230621

Similar Datasets

Project description:BackgroundThe impact of dizziness on quality of life is often assessed by the Dizziness Handicap Inventory (DHI), which is used as a discriminate and evaluative measure. The aim of the present study was to examine reliability and validity of a translated Norwegian version (DHI-N), also examining responsiveness to important change in the construct being measured.MethodsTwo samples (n = 92 and n = 27) included participants with dizziness of mainly vestibular origin. A cross-sectional design was used to examine the factor structure (exploratory factor analysis), internal consistency (Cronbach's alpha), concurrent validity (Pearson's product moment correlation r), and discriminate ability (ROC curve analysis). Longitudinal designs were used to examine test-retest reliability (intraclass correlation coefficient (ICC) statistics, smallest detectable difference (SDD)), and responsiveness (Pearson's product moment correlation, ROC curve analysis; area under the ROC curve (AUC), and minimally important change (MIC)). The DHI scores range from 0 to 100.ResultsFactor analysis revealed a different factor structure than the original DHI, resulting in dismissal of subscale scores in the DHI-N. Acceptable internal consistency was found for the total scale (alpha = 0.95). Concurrent correlations between the DHI-N and other related measures were moderate to high, highest with Vertigo Symptom Scale-short form-Norwegian version (r = 0.69), and lowest with preferred gait (r = - 0.36). The DHI-N demonstrated excellent ability to discriminate between participants with and without 'disability', AUC being 0.89 and best cut-off point = 29 points. Satisfactory test-retest reliability was demonstrated, and the change for an individual should be >/= 20 DHI-N points to exceed measurement error (SDD). Correlations between change scores of DHI-N and other self-report measures of functional health and symptoms were high (r = 0.50 - 0.57). Responsiveness of the DHI-N was excellent, AUC = 0.83, discriminating between self-perceived 'improved' versus 'unchanged' participants. The MIC was identified as 11 DHI-N points.ConclusionsThe DHI-N total scale demonstrated satisfactory measurement properties. This is the first study that has addressed and demonstrated responsiveness to important change of the DHI, and provided values of SDD and MIC to help interpret change scores.

Dataset Information

Exploratory factor analysis of the Dizziness Handicap Inventory (German version).

Background

Methods

Results

Conclusions

Publications

Exploratory factor analysis of the Dizziness Handicap Inventory (German version).

Similar Datasets

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