Displaying publications 141 - 160 of 271 in total

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  1. Mamat M, Samad SA, Hannan MA
    Sensors (Basel), 2011;11(6):6435-53.
    PMID: 22163964 DOI: 10.3390/s110606435
    This paper reports the design of an electronic nose (E-nose) prototype for reliable measurement and correct classification of beverages. The prototype was developed and fabricated in the laboratory using commercially available metal oxide gas sensors and a temperature sensor. The repeatability, reproducibility and discriminative ability of the developed E-nose prototype were tested on odors emanating from different beverages such as blackcurrant juice, mango juice and orange juice, respectively. Repeated measurements of three beverages showed very high correlation (r > 0.97) between the same beverages to verify the repeatability. The prototype also produced highly correlated patterns (r > 0.97) in the measurement of beverages using different sensor batches to verify its reproducibility. The E-nose prototype also possessed good discriminative ability whereby it was able to produce different patterns for different beverages, different milk heat treatments (ultra high temperature, pasteurization) and fresh and spoiled milks. The discriminative ability of the E-nose was evaluated using Principal Component Analysis and a Multi Layer Perception Neural Network, with both methods showing good classification results.
    Matched MeSH terms: Principal Component Analysis
  2. Zhang Y, Vankan D, Zhang Y, Barker JS
    Anim. Genet., 2011 Aug;42(4):366-77.
    PMID: 21749419 DOI: 10.1111/j.1365-2052.2010.02166.x
    Data from three published studies of genetic variation at 18 microsatellite loci in water buffalo populations in China (18 swamp type, two river type), Nepal (one wild, one domestic river, one hybrid) and south-east Asia (eight swamp, three river) were combined so as to gain a broader understanding of genetic relationships among the populations and their demographic history. Mean numbers of alleles and expected heterozygosities were significantly different among populations. Estimates of θ (a measure of population differentiation) were significant among the swamp populations for all loci and among the river populations for most loci. Differentiation among the Chinese swamp populations (which was due primarily to just one population) was much less than among the south-east Asian. The Nepal wild animals, phenotypically swamp type but genetically like river type, are significantly different from all the domestic river populations and presumably represent the ancestral Bubalus arnee (possibly with some river-type introgression). Relationships among the swamp populations (D(A) genetic distances, principal component analysis and structure analyses) show the south-east Asian populations separated into two groups by the Chinese populations. Given these relationships and the patterns of genetic variability, we postulate that the swamp buffalo was domesticated in the region of the far south of China, northern Thailand and Indochina. Following domestication, it spread south through peninsular Malaysia to Sumatra, Java and Sulawesi, and north through China, and then to Taiwan, the Philippines and Borneo.
    Matched MeSH terms: Principal Component Analysis
  3. Abdullah MZ, Saat AB, Hamzah ZB
    Environ Monit Assess, 2012 Jun;184(6):3959-69.
    PMID: 21822578 DOI: 10.1007/s10661-011-2236-y
    Biomonitoring of multi-element atmospheric deposition using terrestrial moss is a well-established technique in Europe. Although the technique is widely known, there were very limited records of using this technique to study atmospheric air pollution in Malaysia. In this present study, the deposition of 11 trace metals surrounding the main petroleum refinery plant in Kerteh Terengganu (eastern part of peninsular Malaysia) has been evaluated using two local moss species, namely Hypnum plumaeforme and Taxithelium instratum as bioindicators. The study was also done by means of observing whether these metals are attributed to work related to oil exploration in this area. The moss samples have been collected at 30 sampling stations in the vicinity of the petrochemical industrial area covering up to 15 km to the south, north, and west in radius. The contents of heavy metal in moss samples were analyzed by energy dispersive x-ray fluorescence technique. Distribution of heavy metal content in all mosses is portrayed using Surfer software. Areas of the highest level of contaminations are highlighted. The results obtained using the principal components analysis revealed that the elements can be grouped into three different components that indirectly reflected three different sources namely anthropogenic factor, vegetation factor, and natural sources (soil dust or substrate) factor. Heavy metals deposited mostly in the distance after 9 km onward to the western part (the average direction of wind blow). V, Cr, Cu, and Hg are believed to have originated from local petrochemical-based industries operated around petroleum industrial area.
    Matched MeSH terms: Principal Component Analysis
  4. Lau CK, Heng YS, Hussain MA, Mohamad Nor MI
    ISA Trans, 2010 Oct;49(4):559-66.
    PMID: 20667537 DOI: 10.1016/j.isatra.2010.06.007
    The performance of a chemical process plant can gradually degrade due to deterioration of the process equipment and unpermitted deviation of the characteristic variables of the system. Hence, advanced supervision is required for early detection, isolation and correction of abnormal conditions. This work presents the use of an adaptive neuro-fuzzy inference system (ANFIS) for online fault diagnosis of a gas-phase polypropylene production process with emphasis on fast and accurate diagnosis, multiple fault identification and adaptability. The most influential inputs are selected from the raw measured data sets and fed to multiple ANFIS classifiers to identify faults occurring in the process, eliminating the requirement of a detailed process model. Simulation results illustrated that the proposed method effectively diagnosed different fault types and severities, and that it has a better performance compared to a conventional multivariate statistical approach based on principal component analysis (PCA). The proposed method is shown to be simple to apply, robust to measurement noise and able to rapidly discriminate between multiple faults occurring simultaneously. This method is applicable for plant-wide monitoring and can serve as an early warning system to identify process upsets that could threaten the process operation ahead of time.
    Matched MeSH terms: Principal Component Analysis
  5. Arifin N, Peng KS, Long K, Ping TC, Affandi Yusoff MS, Nor Aini I, et al.
    J Sci Food Agric, 2010 Apr 30;90(6):943-8.
    PMID: 20355133 DOI: 10.1002/jsfa.3886
    This study aims to investigate the textural properties and sensory qualities of cookies made from medium- and long-chain triacylglycerol (MLCT)-enriched margarines. Margarine with formulations of MLCT:palm olein:palm stearin, 60:30:10 and 70:20:10, were selected to produce cookies. The textural properties of cookies were determined using a texture analyser. Quantitative descriptive analysis (QDA) and acceptance test were carried out to describe the attributes and to evaluate the degree of liking of cookies, respectively.
    Matched MeSH terms: Principal Component Analysis
  6. Ng SC, Raveendran P
    IEEE Trans Biomed Eng, 2009 Aug;56(8):2024-34.
    PMID: 19457744 DOI: 10.1109/TBME.2009.2021987
    The mu rhythm is an electroencephalogram (EEG) signal located at the central region of the brain that is frequently used for studies concerning motor activity. Quite often, the EEG data are contaminated with artifacts and the application of blind source separation (BSS) alone is insufficient to extract the mu rhythm component. We present a new two-stage approach to extract the mu rhythm component. The first stage uses second-order blind identification (SOBI) with stationary wavelet transform (SWT) to automatically remove the artifacts. In the second stage, SOBI is applied again to find the mu rhythm component. Our method is first compared with independent component analysis with discrete wavelet transform (ICA-DWT) as well as SOBI-DWT, ICA-SWT, and regression method for artifact removal using simulated EEG data. The results showed that the regression method is more effective in removing electrooculogram (EOG) artifacts, while SOBI-SWT is more effective in removing electromyogram (EMG) artifacts as compared to the other artifact removal methods. Then, all the methods are compared with the direct application of SOBI in extracting mu rhythm components on simulated and actual EEG data from ten subjects. The results showed that the proposed method of SOBI-SWT artifact removal enhances the extraction of the mu rhythm component.
    Matched MeSH terms: Principal Component Analysis
  7. Fornarino S, Pala M, Battaglia V, Maranta R, Achilli A, Modiano G, et al.
    BMC Evol. Biol., 2009;9:154.
    PMID: 19573232 DOI: 10.1186/1471-2148-9-154
    Central Asia and the Indian subcontinent represent an area considered as a source and a reservoir for human genetic diversity, with many markers taking root here, most of which are the ancestral state of eastern and western haplogroups, while others are local. Between these two regions, Terai (Nepal) is a pivotal passageway allowing, in different times, multiple population interactions, although because of its highly malarial environment, it was scarcely inhabited until a few decades ago, when malaria was eradicated. One of the oldest and the largest indigenous people of Terai is represented by the malaria resistant Tharus, whose gene pool could still retain traces of ancient complex interactions. Until now, however, investigations on their genetic structure have been scarce mainly identifying East Asian signatures.
    Matched MeSH terms: Principal Component Analysis
  8. Praveena SM, Ahmed A, Radojevic M, Abdullah MH, Aris AZ
    Bull Environ Contam Toxicol, 2008 Jul;81(1):52-6.
    PMID: 18506379 DOI: 10.1007/s00128-008-9460-3
    Spatial variations in estuarine intertidal sediment have been often related to such environmental variables as salinity, sediment types, heavy metals and base cations. However, there have been few attempts to investigate the difference condition between high and low tides relationships and to predict their likely responses in an estuarine environment. This paper investigates the linkages between environmental variables and tides of estuarine intertidal sediment in order to provide a basis for describing the effect of tides in the Mengkabong lagoon, Sabah. Multivariate statistical technique, principal components analysis (PCA) was employed to better interpret information about the sediment and its controlling factors in the intertidal zone. The calculation of Geoaccumulation Index (I(geo)) suggests the Mengkabong mangrove sediments are having background concentrations for Al, Cu, Fe, and Zn and unpolluted for Pb. Extra efforts should therefore pay attention to understand the mechanisms and quantification of different pathways of exchange within and between intertidal zones.
    Matched MeSH terms: Principal Component Analysis
  9. Djong TH, Matsui M, Kuramoto M, Belabut DM, Sen YH, Nishioka M, et al.
    Zoolog Sci, 2007 Dec;24(12):1197-212.
    PMID: 18271636 DOI: 10.2108/zsj.24.1197
    In order to elucidate the taxonomic status of the Fejervarya limnocharis complex relative to Malaysia and Japan populations, morphological observations and molecular phylogenetic analysis were carried out using three populations from Indonesia (type locality), Malaysia, and Japan. In addition, we conducted histological and spermatogenic observations using hybrids among these populations. Principal component and cluster analyses demonstrated that these populations could be clearly separated from one another. Abnormal testes were found in the hybrids between the Japan and Indonesia populations and between the Japan and Malaysia populations, but testes of the controls and hybrids between the Malaysia and Indonesia populations were quite normal. The mean number of univalents per cell was 5.42, 4.58, and 0.20 in hybrids between the Indonesia and Japan populations, Malaysia and Japan populations, and Indonesia and Malaysia populations, respectively. Sequence divergences in 16S rRNA and Cyt b genes were 0-0.4% (xbar=0.2%) and 0.3-1.5% (xbar=1.0%), respectively, between the Malaysia and Indonesia populations, and 2.4-2.6% (xbar=2.5%) and 11.0-12.0% (xbar=11.5%) between the Japan population and F. limnocharis complex, including the Malaysia and Indonesia populations and F. multistriata from China. This study indicated that the Malaysia population and F. multistriata from China should be designated as a subspecies of topotypic F. limnocharis, and that the Japan population should be regarded as a distinct species.
    Matched MeSH terms: Principal Component Analysis
  10. Sidi H, Naing L, Midin M, Nik Jaafar NR
    J Sex Med, 2008 Oct;5(10):2359-66.
    PMID: 18086161
    The concept of a sexual response cycle (SRC) for women has gained interest lately with the reintroduction of terms with new definitions and a new model for the sexual response, especially the Basson's circular model.
    Matched MeSH terms: Principal Component Analysis
  11. Subari N, Mohamad Saleh J, Md Shakaff AY, Zakaria A
    Sensors (Basel), 2012;12(10):14022-40.
    PMID: 23202033 DOI: 10.3390/s121014022
    This paper presents a comparison between data from single modality and fusion methods to classify Tualang honey as pure or adulterated using Linear Discriminant Analysis (LDA) and Principal Component Analysis (PCA) statistical classification approaches. Ten different brands of certified pure Tualang honey were obtained throughout peninsular Malaysia and Sumatera, Indonesia. Various concentrations of two types of sugar solution (beet and cane sugar) were used in this investigation to create honey samples of 20%, 40%, 60% and 80% adulteration concentrations. Honey data extracted from an electronic nose (e-nose) and Fourier Transform Infrared Spectroscopy (FTIR) were gathered, analyzed and compared based on fusion methods. Visual observation of classification plots revealed that the PCA approach able to distinct pure and adulterated honey samples better than the LDA technique. Overall, the validated classification results based on FTIR data (88.0%) gave higher classification accuracy than e-nose data (76.5%) using the LDA technique. Honey classification based on normalized low-level and intermediate-level FTIR and e-nose fusion data scored classification accuracies of 92.2% and 88.7%, respectively using the Stepwise LDA method. The results suggested that pure and adulterated honey samples were better classified using FTIR and e-nose fusion data than single modality data.
    Matched MeSH terms: Principal Component Analysis
  12. Fadilah N, Mohamad-Saleh J, Abdul Halim Z, Ibrahim H, Syed Ali SS
    Sensors (Basel), 2012;12(10):14179-95.
    PMID: 23202043 DOI: 10.3390/s121014179
    Ripeness classification of oil palm fresh fruit bunches (FFBs) during harvesting is important to ensure that they are harvested during optimum stage for maximum oil production. This paper presents the application of color vision for automated ripeness classification of oil palm FFB. Images of oil palm FFBs of type DxP Yangambi were collected and analyzed using digital image processing techniques. Then the color features were extracted from those images and used as the inputs for Artificial Neural Network (ANN) learning. The performance of the ANN for ripeness classification of oil palm FFB was investigated using two methods: training ANN with full features and training ANN with reduced features based on the Principal Component Analysis (PCA) data reduction technique. Results showed that compared with using full features in ANN, using the ANN trained with reduced features can improve the classification accuracy by 1.66% and is more effective in developing an automated ripeness classifier for oil palm FFB. The developed ripeness classifier can act as a sensor in determining the correct oil palm FFB ripeness category.
    Matched MeSH terms: Principal Component Analysis
  13. Zarcinas BA, Ishak CF, McLaughlin MJ, Cozens G
    Environ Geochem Health, 2004 Dec;26(4):343-57.
    PMID: 15719158
    In a reconnaisance soil geochemical and plant survey undertaken to study the heavy metal uptake by major food crops in Malaysia, 241 soils were analysed for cation exchange capacity (CEC), organic carbon (C), pH, electrical conductivity (EC) and available phosphorus (P) using appropriate procedures. These soils were also analysed for arsenic (As), cadmium (Cd), cobalt (Co), chromium (Cr), copper (Cu), mercury (Hg), nickel (Ni), lead (Pb) and zinc (Zn) using aqua regia digestion, together with 180 plant samples using nitric acid digestion. Regression analysis between the edible plant part and aqua regia soluble soil As, Cd, Cr, Cu, Hg, Ni, Pb and Zn concentrations sampled throughout Peninsular Malaysia, indicated a positive relationship for Pb in all the plants sampled in the survey (R2 = 0.195, p < 0.001), for Ni in corn (R2 = 0.649, p < 0.005), for Cu in chili (R2 = 0.344, p < 0.010) and for Zn in chili (R2 = 0.501, p < 0.001). Principal component analysis of the soil data suggested that concentrations of Co, Ni, Pb and Zn were strongly correlated with concentrations of Al and Fe, which is suggestive of evidence of background variations due to changes in soil mineralogy. Thus the evidence for widespread contamination of soils by these elements through agricultural activities is not strong. Chromium was correlated with soil pH and EC, Na, S, and Ca while Hg was not correlated with any of these components, suggesting diffuse pollution by aerial deposition. However As, Cd, Cu were strongly associated with organic matter and available and aqua regia soluble soil P, which we attribute to inputs in agricultural fertilisers and soil organic amendments (e.g. manures, composts).
    Matched MeSH terms: Principal Component Analysis
  14. Mosleh MA, Manssor H, Malek S, Milow P, Salleh A
    BMC Bioinformatics, 2012;13 Suppl 17:S25.
    PMID: 23282059 DOI: 10.1186/1471-2105-13-S17-S25
    Freshwater algae can be used as indicators to monitor freshwater ecosystem condition. Algae react quickly and predictably to a broad range of pollutants. Thus they provide early signals of worsening environment. This study was carried out to develop a computer-based image processing technique to automatically detect, recognize, and identify algae genera from the divisions Bacillariophyta, Chlorophyta and Cyanobacteria in Putrajaya Lake. Literature shows that most automated analyses and identification of algae images were limited to only one type of algae. Automated identification system for tropical freshwater algae is even non-existent and this study is partly to fill this gap.
    Matched MeSH terms: Principal Component Analysis
  15. Sim JH, Tong WT, Hong WH, Vadivelu J, Hassan H
    Med Educ Online, 2015;20:28612.
    PMID: 26511792 DOI: 10.3402/meo.v20.28612
    INTRODUCTION: Assessment environment, synonymous with climate or atmosphere, is multifaceted. Although there are valid and reliable instruments for measuring the educational environment, there is no validated instrument for measuring the assessment environment in medical programs. This study aimed to develop an instrument for measuring students' perceptions of the assessment environment in an undergraduate medical program and to examine the psychometric properties of the new instrument.
    METHOD: The Assessment Environment Questionnaire (AEQ), a 40-item, four-point (1=Strongly Disagree to 4=Strongly Agree) Likert scale instrument designed by the authors, was administered to medical undergraduates from the authors' institution. The response rate was 626/794 (78.84%). To establish construct validity, exploratory factor analysis (EFA) with principal component analysis and varimax rotation was conducted. To examine the internal consistency reliability of the instrument, Cronbach's α was computed. Mean scores for the entire AEQ and for each factor/subscale were calculated. Mean AEQ scores of students from different academic years and sex were examined.
    RESULTS: Six hundred and eleven completed questionnaires were analysed. EFA extracted four factors: feedback mechanism (seven items), learning and performance (five items), information on assessment (five items), and assessment system/procedure (three items), which together explained 56.72% of the variance. Based on the four extracted factors/subscales, the AEQ was reduced to 20 items. Cronbach's α for the 20-item AEQ was 0.89, whereas Cronbach's α for the four factors/subscales ranged from 0.71 to 0.87. Mean score for the AEQ was 2.68/4.00. The factor/subscale of 'feedback mechanism' recorded the lowest mean (2.39/4.00), whereas the factor/subscale of 'assessment system/procedure' scored the highest mean (2.92/4.00). Significant differences were found among the AEQ scores of students from different academic years.
    CONCLUSIONS: The AEQ is a valid and reliable instrument. Initial validation supports its use to measure students' perceptions of the assessment environment in an undergraduate medical program.
    KEYWORDS: assessment environment; development; instrument; psychometric properties; validation
    Matched MeSH terms: Principal Component Analysis
  16. Abdullah P, Abdullah SMS, Jaafar O, Mahmud M, Khalik WMAWM
    Mar Pollut Bull, 2015 Dec 15;101(1):378-385.
    PMID: 26476861 DOI: 10.1016/j.marpolbul.2015.10.014
    Characterization of hydrochemistry changes in Johor Straits within 5 years of monitoring works was successfully carried out. Water quality data sets (27 stations and 19 parameters) collected in this area were interpreted subject to multivariate statistical analysis. Cluster analysis grouped all the stations into four clusters ((Dlink/Dmax) × 100<90) and two clusters ((Dlink/Dmax) × 100<80) for site and period similarities. Principal component analysis rendered six significant components (eigenvalue>1) that explained 82.6% of the total variance of the data set. Classification matrix of discriminant analysis assigned 88.9-92.6% and 83.3-100% correctness in spatial and temporal variability, respectively. Times series analysis then confirmed that only four parameters were not significant over time change. Therefore, it is imperative that the environmental impact of reclamation and dredging works, municipal or industrial discharge, marine aquaculture and shipping activities in this area be effectively controlled and managed.
    Matched MeSH terms: Principal Component Analysis
  17. Abdul-Hamid NA, Abas F, Ismail IS, Shaari K, Lajis NH
    J Food Sci, 2015 Nov;80(11):H2603-11.
    PMID: 26457883 DOI: 10.1111/1750-3841.13084
    This study aimed to examine the variation in the metabolite profiles and nitric oxide (NO) inhibitory activity of Ajwa dates that were subjected to 2 drying treatments and different extraction solvents. (1)H NMR coupled with multivariate data analysis was employed. A Griess assay was used to determine the inhibition of the production of NO in RAW 264.7 cells treated with LPS and interferon-γ. The oven dried (OD) samples demonstrated the absence of asparagine and ascorbic acid as compared to the freeze dried (FD) dates. The principal component analysis showed distinct clusters between the OD and FD dates by the second principal component. In respect of extraction solvents, chloroform extracts can be distinguished by the absence of arginine, glycine and asparagine compared to the methanol and 50% methanol extracts. The chloroform extracts can be clearly distinguished from the methanol and 50% methanol extracts by first principal component. Meanwhile, the loading score plot of partial least squares analysis suggested that beta glucose, alpha glucose, choline, ascorbic acid and glycine were among the metabolites that were contributing to higher biological activity displayed by FD and methanol extracts of Ajwa. The results highlight an alternative method of metabolomics approach for determination of the metabolites that contribute to NO inhibitory activity.
    Matched MeSH terms: Principal Component Analysis
  18. Ismail A, Toriman ME, Juahir H, Zain SM, Habir NL, Retnam A, et al.
    Mar Pollut Bull, 2016 May 15;106(1-2):292-300.
    PMID: 27001716 DOI: 10.1016/j.marpolbul.2015.10.019
    This study presents the determination of the spatial variation and source identification of heavy metal pollution in surface water along the Straits of Malacca using several chemometric techniques. Clustering and discrimination of heavy metal compounds in surface water into two groups (northern and southern regions) are observed according to level of concentrations via the application of chemometric techniques. Principal component analysis (PCA) demonstrates that Cu and Cr dominate the source apportionment in northern region with a total variance of 57.62% and is identified with mining and shipping activities. These are the major contamination contributors in the Straits. Land-based pollution originating from vehicular emission with a total variance of 59.43% is attributed to the high level of Pb concentration in the southern region. The results revealed that one state representing each cluster (northern and southern regions) is significant as the main location for investigating heavy metal concentration in the Straits of Malacca which would save monitoring cost and time.

    CAPSULE: The monitoring of spatial variation and source of heavy metals pollution at the northern and southern regions of the Straits of Malacca, Malaysia, using chemometric analysis.

    Matched MeSH terms: Principal Component Analysis
  19. Keowmani T, Lee LW
    Patient Prefer Adherence, 2016;10:205-11.
    PMID: 26955264 DOI: 10.2147/PPA.S96880
    PURPOSE: To study the validity and reliability of the Malay version of the Specific Thalassemia Quality of Life Instrument (STQOLI) in Sabah's adult thalassemia patients.
    PATIENTS AND METHODS: This cross-sectional study was done at Thalassemia Treatment Centre, Queen Elizabeth Hospital in Sabah, Malaysia. Eighty-two adult thalassemia patients who fulfilled the inclusion and exclusion criteria were conveniently selected for participation in the study. The English version of STQOLI was translated into Malay by using forward and back translations. The content of the questionnaire was validated by the chief hematologist of the hospital. The construct validity of the 40-item questionnaire was assessed by principal component analysis with varimax rotation and the scale reliability was assessed by Cronbach's alpha.
    RESULTS: The study failed to replicate the internal structure of the Greek STQOLI. Instead, 12 factors have been identified from the exploratory factor analysis, which accounted for 72.2% of the variance. However, only eight factors were interpretable. The factors were iron chelation pump impact, transfusion impact, time spent on treatment and its impact on work and social life, sex life, side effects of treatment, cardiovascular problems, psychology, and iron chelation pill impact. The overall scale reliability was 0.913.
    CONCLUSION: This study was unable to replicate the internal structure of the Greek STQOLI in Sabah's adult thalassemia patients. Instead, a new structure has emerged that can be used as a guide to develop a questionnaire specific for adult thalassemia patients in Sabah. Future research should focus on the eight factors identified from this study.
    KEYWORDS: Malay; STQOLI; reliability; transfusion; validity
    Matched MeSH terms: Principal Component Analysis
  20. Ahmadi K, Reidpath DD, Allotey P, Hassali MAA
    BMC Med Educ, 2016 May 30;16:155.
    PMID: 27240562 DOI: 10.1186/s12909-016-0676-3
    BACKGROUND: The attitudes of healthcare professionals towards HIV positive patients and high risk groups are central to the quality of care and therefore to the management of HIV/AIDS related stigma in health settings. Extant HIV/AIDS stigma scales that measure stigmatising attitudes towards people living with HIV/AIDS have been developed using scaling techniques such as principal component analysis. This approach has resulted in instruments that are often long. Mokken scale analysis is a nonparametric hierarchical scaling technique that can be used to develop unidimensional cumulative scales. This technique is advantageous over the other approaches; as the scales are usually shorter, while retaining acceptable psychometric properties. Moreover, Mokken scales also make no distributional assumptions about the underlying data, other than that the data are capable of being ordered by item and by person. In this study we aimed at developing a precise and concise measure of HIV/AIDS related stigma among health care professionals, using Mokken scale analysis.
    METHODS: We carried out a cross sectional survey of healthcare students at the Monash University campuses in Malaysia and Australia. The survey consisted of demographic questions and an initial item pool of twenty five potential questions for inclusion in an HIV stigma scale.
    RESULTS: We analysed the data using the mokken package in the R statistical environment providing a 9-item scale with high reliability, validity and acceptable psychometric properties, measuring and ranking the HIV/AIDS related stigmatising attitudes.
    CONCLUSION: Mokken scaling procedure not only produced a comprehensive hierarchical scale that could accurately order a person along HIV/AIDS stigmatising attitude, but also demonstrated a unidimensional and reliable measurement tool which could be used in future studies. The principal component analysis confirmed the accuracy of the Mokken scale analysis in correctly detecting the unidimensionality of this scale. We recommend future works to study the generalisability of this scale in a new population.
    Matched MeSH terms: Principal Component Analysis
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