Using an analytical hierarchy process (AHP) for weighting items of a measurement scale: a pilot study.

Détails

ID Serval
serval:BIB_384255126F7A
Type
Article: article d'un périodique ou d'un magazine.
Collection
Publications
Institution
Titre
Using an analytical hierarchy process (AHP) for weighting items of a measurement scale: a pilot study.
Périodique
Revue d'epidemiologie et de sante publique
Auteur⸱e⸱s
Benaïm C., Perennou D.A., Pelissier J.Y., Daures J.P.
ISSN
0398-7620 (Print)
ISSN-L
0398-7620
Statut éditorial
Publié
Date de publication
02/2010
Peer-reviewed
Oui
Volume
58
Numéro
1
Pages
59-63
Langue
anglais
Notes
Publication types: Comparative Study ; Journal Article ; Validation Studies
Publication Status: ppublish
Résumé
Many clinical scales contain items that are scored separately prior to being compiled into a single score. However, if the items have different degrees of importance, they should be weighted differently before being compiled. The principal aims of this study were to show how the "analytic hierarchy process" (AHP), which has never been used for this purpose, can be applied to weighting the six items of the "London handicap scale", and to compare the AHP to the "conjoint analysis" (CA), which was previously implemented by Harwood et al. (1994) [1].
In order to assess the relative importance of the six items, we submitted AHP and CA to a group of 10 physiatrists. We compared the methods in terms of item ranking according to importance, assessment of fictitious patients based on weights determined by each method, and perceived difficulty by the physiatrist.
For both techniques, "Physical independence" (PHY) was the best-weighted item, but other ranks varied depending on the technique. AHP was better than CA in terms of accuracy (global assessment of the clinical status) and perceived difficulty.
AHP may be used to reveal the importance that experts assign to the items of a multidimensional scale, and to calculate the appropriate weights for specific items. For this purpose, AHP seems to be more accurate than CA.
Mots-clé
Activities of Daily Living, Attitude of Health Personnel, Choice Behavior, Data Interpretation, Statistical, Decision Support Techniques, Disability Evaluation, Humans, Linear Models, Mobility Limitation, Occupations, Orientation, Physical and Rehabilitation Medicine/methods, Physical and Rehabilitation Medicine/standards, Pilot Projects, Psychometrics, Severity of Illness Index, Social Behavior, Socioeconomic Factors, Statistics, Nonparametric, Surveys and Questionnaires
Pubmed
Web of science
Création de la notice
29/11/2018 10:03
Dernière modification de la notice
21/08/2019 6:33
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