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      Psychometric Properties of the Oral Health Values Scale and Cultural Adaptation in the Indian Population

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          Abstract

          Aim: The Oral Health Values Scale is a multidimensional instrument that identifies and measures a person's values related to oral health. This scale has been validated in American respondents. This study aims to evaluate the adaptability and validity of the Oral Health Values Scale in the Hindi language (H-OHVS).

          Methodology: A total of 240 adults participated in the study that was carried out from July to November 2022. An offline one-to-one survey was carried out to collect data by an investigator blinded to the study protocol. The translation and testing of the OHVS were carried out based on the cross-cultural adaptation guidelines of the American Academy of Orthopedic Surgeons (AAOS) Evidence-Based Medicine Committee. The content validity was assessed by an expert panel. Construct validity was analyzed through Exploratory Factor Analysis (EFA), utilizing principal component analysis with varimax rotation. The internal consistency of the Hindi version of OHVS was evaluated using Cronbach’s alpha.

          Results: The results showed that H-OHVS had an Item-level Construct Validity Index (I-CVI) ranging from 0.82 to 1.00. Two components, compliance and hesitance, were formed on H-OHVS accounting for 63.91% of the cumulative variance. The resulting model fit indices on confirmatory factor analysis presented an adequate fit to the data. The overall Cronbach's alpha coefficient for H-OHVS (α = 0.868) presents excellent internal consistency.

          Conclusions: The study findings provide a certain degree of evidence in favor of this scale and establish the Oral Health Values Scale (OHVS) as a psychometrically sound measure.

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          Most cited references15

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          Guidelines for the Process of Cross-Cultural Adaptation of Self-Report Measures

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            Measuring health-related quality of life.

            Clinicians and policymakers are recognizing the importance of measuring health-related quality of life (HRQL) to inform patient management and policy decisions. Self- or interviewer-administered questionnaires can be used to measure cross-sectional differences in quality of life between patients at a point in time (discriminative instruments) or longitudinal changes in HRQL within patients during a period of time (evaluative instruments). Both discriminative and evaluative instruments must be valid (really measuring what they are supposed to measure) and have a high ratio of signal to noise (reliability and responsiveness, respectively). Reliable discriminative instruments are able to reproducibly differentiate between persons. Responsive evaluative measures are able to detect important changes in HRQL during a period of time, even if those changes are small. Health-related quality of life measures should also be interpretable--that is, clinicians and policymakers must be able to identify differences in scores that correspond to trivial, small, moderate, and large differences. Two basic approaches to quality-of-life measurement are available: generic instruments that provide a summary of HRQL; and specific instruments that focus on problems associated with single disease states, patient groups, or areas of function. Generic instruments include health profiles and instruments that generate health utilities. The approaches are not mutually exclusive. Each approach has its strengths and weaknesses and may be suitable for different circumstances. Investigations in HRQL have led to instruments suitable for detecting minimally important effects in clinical trials, for measuring the health of populations, and for providing information for policy decisions.
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              Sample size used to validate a scale: a review of publications on newly-developed patient reported outcomes measures

              Purpose New patient reported outcome (PRO) measures are regularly developed to assess various aspects of the patients’ perspective on their disease and treatment. For these instruments to be useful in clinical research, they must undergo a proper psychometric validation, including demonstration of cross-sectional and longitudinal measurement properties. This quantitative evaluation requires a study to be conducted on an appropriate sample size. The aim of this research was to list and describe practices in PRO and proxy PRO primary psychometric validation studies, focusing primarily on the practices used to determine sample size. Methods A literature review of articles published in PubMed between January 2009 and September 2011 was conducted. Three selection criteria were applied including a search strategy, an article selection strategy, and data extraction. Agreements between authors were assessed, and practices of validation were described. Results Data were extracted from 114 relevant articles. Within these, sample size determination was low (9.6%, 11/114), and were reported as either an arbitrary minimum sample size (n = 2), a subject to item ratio (n = 4), or the method was not explicitly stated (n = 5). Very few articles (4%, 5/114) compared a posteriori their sample size to a subject to item ratio. Content validity, construct validity, criterion validity and internal consistency were the most frequently measurement properties assessed in the validation studies. Approximately 92% of the articles reported a subject to item ratio greater than or equal to 2, whereas 25% had a ratio greater than or equal to 20. About 90% of articles had a sample size greater than or equal to 100, whereas 7% had a sample size greater than or equal to 1000. Conclusions The sample size determination for psychometric validation studies is rarely ever justified a priori. This emphasizes the lack of clear scientifically sound recommendations on this topic. Existing methods to determine the sample size needed to assess the various measurement properties of interest should be made more easily available. Electronic supplementary material The online version of this article (doi:10.1186/s12955-014-0176-2) contains supplementary material, which is available to authorized users.
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                Author and article information

                Journal
                Cureus
                Cureus
                2168-8184
                Cureus
                Cureus (Palo Alto (CA) )
                2168-8184
                9 February 2024
                February 2024
                : 16
                : 2
                : e53942
                Affiliations
                [1 ] Division of Public Health Dentistry, All India Institute of Medical Sciences, New Delhi, IND
                [2 ] Department of Biostatistics, All India Institute of Medical Sciences, New Delhi, IND
                [3 ] Department of Dentistry, All India Institute of Medical Sciences, New Delhi, IND
                [4 ] Conservative Dentistry and Endodontics, Sardar Patel Postgraduate Institute of Dental and Medical Sciences, New Delhi, IND
                Author notes
                Article
                10.7759/cureus.53942
                10925842
                38469005
                fa9ff8f6-ce0a-494c-b837-8389e15e942d
                Copyright © 2024, Bhadauria et al.

                This is an open access article distributed under the terms of the Creative Commons Attribution License CC-BY 4.0., which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

                History
                : 9 February 2024
                Categories
                Epidemiology/Public Health
                Dentistry

                scale validation,oral health care,oral health,questionnaire development and validation,psychometric properties

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