38 research outputs found
The development and psychometric properties of the Arabic version of the child oral health impact profile-short form (COHIP- SF 19)
BACKGROUND: This study aims to cross-culturally adapt the original English-language COHIP-SF 19 to Arabic culture and to test its psychometric properties in a community sample. METHODS: The Arabic COHIP-SF 19 was developed and its psychometric properties were examined in a population-based sample of 876 schoolchildren who were aged 12 years of age, in Benghazi, Libya. The Arabic COHIP-SF 19 was tested for its internal consistency, reproducibility, construct validity, factorial validity and floor as well as ceiling effects. A Mann-Whitney U test was used to compare the mean scores of COHIP-SF 19 by participants' caries status and self-reported oral health rating, satisfaction and treatment need. RESULTS: The Arabic COHIP-SF 19 was successfully and smoothly developed. It showed an acceptable level of equivalence to the original version. Overall, the internal consistency and reproducibility were acceptable to excellent, with a Cronbach's alpha of 0.84 and an intra-class correlation coefficient (ICC) of 0.76. All hypotheses predefined to test construct validity were confirmed. That is, children who had active dental caries, and who rated their oral health as poor, were not satisfied with their oral health or indicated the need of treatment had lower COHIP-SF 19 scores (P < 0.05). Floor or ceiling effects were not observed. The exploratory Factorial analysis suggested a 4-component solution and deletion of one item. CONCLUSION: The Arabic COHIP-SF 19 was successfully developed. The measure demonstrated satisfactory reliability and validity to estimate OHRQoL in a representative sample of 12-year-old schoolchildren
Health communication in primary health care -A case study of ICT development for health promotion
“This program should come with a warning sign!”: Mental wellness in occupational therapy and physical therapy students
Statistical power as a function of Cronbach alpha of instrument questionnaire items
Abstract Background In countless number of clinical trials, measurements of outcomes rely on instrument questionnaire items which however often suffer measurement error problems which in turn affect statistical power of study designs. The Cronbach alpha or coefficient alpha, here denoted by C α , can be used as a measure of internal consistency of parallel instrument items that are developed to measure a target unidimensional outcome construct. Scale score for the target construct is often represented by the sum of the item scores. However, power functions based on C α have been lacking for various study designs. Methods We formulate a statistical model for parallel items to derive power functions as a function of C α under several study designs. To this end, we assume fixed true score variance assumption as opposed to usual fixed total variance assumption. That assumption is critical and practically relevant to show that smaller measurement errors are inversely associated with higher inter-item correlations, and thus that greater C α is associated with greater statistical power. We compare the derived theoretical statistical power with empirical power obtained through Monte Carlo simulations for the following comparisons: one-sample comparison of pre- and post-treatment mean differences, two-sample comparison of pre-post mean differences between groups, and two-sample comparison of mean differences between groups. Results It is shown that C α is the same as a test-retest correlation of the scale scores of parallel items, which enables testing significance of C α . Closed-form power functions and samples size determination formulas are derived in terms of C α , for all of the aforementioned comparisons. Power functions are shown to be an increasing function of C α , regardless of comparison of interest. The derived power functions are well validated by simulation studies that show that the magnitudes of theoretical power are virtually identical to those of the empirical power. Conclusion Regardless of research designs or settings, in order to increase statistical power, development and use of instruments with greater C α , or equivalently with greater inter-item correlations, is crucial for trials that intend to use questionnaire items for measuring research outcomes. Discussion Further development of the power functions for binary or ordinal item scores and under more general item correlation strutures reflecting more real world situations would be a valuable future study
Polysialic acid bioengineering of cancer and neuronal cells by N-acyl sialic acid precursor treatment
Peer reviewed: YesNRC publication: Ye