Displaying publications 1 - 20 of 58 in total

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  1. Cheah KJ, Abdul Manaf Z, Fitri Mat Ludin A, Razalli NH, Mohd Mokhtar N, Md Ali SH
    JMIR Mhealth Uhealth, 2024 Mar 12;12:e49055.
    PMID: 38532298 DOI: 10.2196/49055
    BACKGROUND: The success of mobile apps in improving the lifestyle of patients with noncommunicable diseases through self-management interventions is contingent upon the emerging growth in this field. While users of mobile health (mHealth) apps continue to grow in number, little is known about the quality of available apps that provide self-management for common noncommunicable diseases such as diabetes, hypertension, and obesity.

    OBJECTIVE: We aimed to investigate the availability, characteristics, and quality of mHealth apps for common noncommunicable disease health management that included dietary aspects (based on the developer's description), as well as their features for promoting health outcomes and self-monitoring.

    METHODS: A systematic search of English-language apps on the Google Play Store (Google LLC) and Apple App Store (Apple Inc) was conducted between August 7, 2022, and September 13, 2022. The search terms used included weight management, obesity, diabetes, hypertension, cardiovascular diseases, stroke, and diet. The selected mHealth apps' titles and content were screened based on the description that was provided. Apps that were not designed with self-management features were excluded. We analyzed the mHealth apps by category and whether they involved health care professionals, were based on scientific testing, and had self-monitoring features. A validated and multidimensional tool, the Mobile App Rating Scale (MARS), was used to evaluate each mHealth app's quality based on a 5-point Likert scale from 1 (inadequate) to 5 (excellent).

    RESULTS: Overall, 42 apps were identified. Diabetes-specific mHealth apps accounted for 7% (n=3) of the market, hypertension apps for 12% (n=5), and general noncommunicable disease management apps for 21% (n=9). About 38% (n=16) of the apps were for managing chronic diseases, while 74% (n=31) were for weight management. Self-management features such as weight tracking, BMI calculators, diet tracking, and fluid intake tracking were seen in 86% (n=36) of the apps. Most mHealth apps (n=37, 88%) did not indicate whether there was involvement of health professionals in app development. Additionally, none of the apps reported scientific evidence demonstrating their efficacy in managing health. The overall mean MARS score was 3.2 of 5, with a range of 2.0 to 4.1. Functionality was the best-rated category (mean score 3.9, SD 0.5), followed by aesthetics (mean score 3.2, SD 0.9), information (mean score 3.1, SD 0.7), and engagement (mean score 2.9, SD 0.6).

    CONCLUSIONS: The quality of mHealth apps for managing chronic diseases was heterogeneous, with roughly half of them falling short of acceptable standards for both quality and content. The majority of apps contained scant information about scientific evidence and the developer's history. To increase user confidence and accomplish desired health outcomes, mHealth apps should be optimized with the help of health care professionals. Future studies on mHealth content analysis should focus on other diseases as well.

  2. Zhang H, Ramamoorthy A, Rengarajan T, Iyappan P, Alahmadi TA, Wainwright M, et al.
    J Biochem Mol Toxicol, 2024 Jan;38(1):e23578.
    PMID: 37927152 DOI: 10.1002/jbt.23578
    Lung cancer is one of the most common cancers in men. Although many diagnostic and treatment regimens have been followed in the treatment for lung cancer, increasing mortality rate due to lung cancer is depressing and hence requires alternative plant based therapeutics with with less side-effects. Myrtenol exhibits anti-inflammatory and antioxidant properties. Hence we intended to study the effect of Myrtenol on B(a)P-induced lung cancer. Our study showed that B(a)P lowered hematological count, decreased phagocyte and avidity indices, nitroblue tetrazolium (NBT) reduction, levels of immunoglubulins, antioxidant levels, whereas Myrtenol treatment restored them back to normal levels. On the other hand, xenobiotic and liver dysfunction marker enzymes and pro-inflammatory cytokines were elevated on B(a)P exposure, which retuned back to normal by Myrtenol. This study thus describes the immunomodulatory and antioxidant effects of Myrtenol on B[a]P-induced immune destruction.
  3. Hussein-Al-Ali SH, Abudoleh SM, Abualassal QIA, Abudayeh Z, Aldalahmah Y, Hussein MZ
    IET Nanobiotechnol, 2022 May;16(3):92-101.
    PMID: 35332980 DOI: 10.1049/nbt2.12081
    Silver nanoparticles (AgNPs) have shown potential applications in drug delivery. In this study, the AgNPs was prepared from silver nitrate in the presence of alginate as a capping agent. The ciprofloxacin (Cipro) was loaded on the surface of AgNPs to produce Cipro-AgNPs nanocomposite. The characteristics of the Cipro-AgNPs nanocomposite were studied by X-ray diffraction (XRD), UV-Vis, transmission electron microscopy (TEM), thermogravimetric analysis (TGA), scanning electron microscopy (SEM), Fourier-transform infra-red analysis (FT-IR) and zeta potential analyses. The XRD of AgNPs and Cipro-AgNPs nanocomposite data showed that both have a crystalline structure in nature. The FT-IR data indicate that the AgNPs have been wrapped by the alginate and loaded with the Cipro drug. The TEM image showed that the Cipro-AgNPs nanocomposites have an average size of 96 nm with a spherical shape. The SEM image for AgNPs and Cipro-AgNPs nanocomposites confirmed the needle-lumpy shape. The zeta potential for Cipro-AgNPs nanocomposites exhibited a positive charge with a value of 6.5 mV. The TGA for Cipro-AgNPs nanocomposites showed loss of 79.7% in total mass compared to 57.6% for AgNPs which is due to the Cipro loaded in the AgNPs. The release of Cipro from Cipro-AgNPs nanocomposites showed slow release properties which reached 98% release within 750 min, and followed the Hixson-Crowell kinetic model. In addition, the toxicity of AgNPs and Cipro-AgNPs nanocomposites was evaluated using normal (3T3) cell line. The present work suggests that Cipro-AgNPs are suitable for drug delivery.
  4. Abdul Wahab P, Mohd Yusoff D, Abdul Kadir A, Ali SH, Yeong Yeh L
    Clin Nurs Res, 2022 Feb;31(2):348-355.
    PMID: 34340590 DOI: 10.1177/10547738211033934
    This study aimed to determine the prevalence, symptoms, and associated factors of chronic constipation among older adults in the North-East of Peninsular Malaysia. A cross-sectional study was conducted among older patients from four health clinics. A total of 400 older patients participated, with a mean age of 68.7 (SD = 6.4) years. The prevalence of chronic constipation was 14.8%. The highest symptom reported was the inability to pass stool (98.3%). Chronic constipation was significantly associated with older age (OR = 2.97; 95% CI [1.17, 7.54]; p = .022), inadequate plain water intake per day (OR = 2.13; 95% CI [1.13, 4.02]; p = .020), hypertension (OR = 2.22; 95% CI [1.07, 4.61]; p = .033), and hyperlipidemia (OR = 2.52; 95% CI [1.24, 5.11]; p = .010). Identification of chronic constipation should be done as part of routine clinic visits, especially for older patients with cardiovascular disease.
  5. Haque F, Ibne Reaz MB, Chowdhury MEH, Md Ali SH, Ashrif A Bakar A, Rahman T, et al.
    Comput Biol Med, 2021 12;139:104954.
    PMID: 34715551 DOI: 10.1016/j.compbiomed.2021.104954
    BACKGROUND: Diabetic Sensorimotor polyneuropathy (DSPN) is one of the major indelible complications in diabetic patients. Michigan neuropathy screening instrumentation (MNSI) is one of the most common screening techniques used for DSPN, however, it does not provide any direct severity grading system.

    METHOD: For designing and modeling the DSPN severity grading systems for MNSI, 19 years of data from Epidemiology of Diabetes Interventions and Complications (EDIC) clinical trials were used. Different Machine learning-based feature ranking techniques were investigated to identify the important MNSI features associated with DSPN diagnosis. A multivariable logistic regression-based nomogram was generated and validated for DSPN severity grading using the best performing top-ranked MNSI features.

    RESULTS: Top-10 ranked features from MNSI features: Appearance of Feet (R), Ankle Reflexes (R), Vibration perception (L), Vibration perception (R), Appearance of Feet (L), 10-gm filament (L), Ankle Reflexes (L), 10-gm filament (R), Bed Cover Touch, and Ulceration (R) were identified as important features for identifying DSPN by Multi-Tree Extreme Gradient Boost model. The nomogram-based prediction model exhibited an accuracy of 97.95% and 98.84% for the EDIC test set and an independent test set, respectively. A DSPN severity score technique was generated for MNSI from the DSPN severity prediction model. DSPN patients were stratified into four severity levels: absent, mild, moderate, and severe using the cut-off values of 17.6, 19.1, 20.5 for the DSPN probability less than 50%, 75%-90%, and above 90%, respectively.

    CONCLUSIONS: The findings of this work provide a machine learning-based MNSI severity grading system which has the potential to be used as a secondary decision support system by health professionals in clinical applications and large clinical trials to identify high-risk DSPN patients.

  6. Khandakar A, Chowdhury MEH, Ibne Reaz MB, Md Ali SH, Hasan MA, Kiranyaz S, et al.
    Comput Biol Med, 2021 10;137:104838.
    PMID: 34534794 DOI: 10.1016/j.compbiomed.2021.104838
    Diabetes foot ulceration (DFU) and amputation are a cause of significant morbidity. The prevention of DFU may be achieved by the identification of patients at risk of DFU and the institution of preventative measures through education and offloading. Several studies have reported that thermogram images may help to detect an increase in plantar temperature prior to DFU. However, the distribution of plantar temperature may be heterogeneous, making it difficult to quantify and utilize to predict outcomes. We have compared a machine learning-based scoring technique with feature selection and optimization techniques and learning classifiers to several state-of-the-art Convolutional Neural Networks (CNNs) on foot thermogram images and propose a robust solution to identify the diabetic foot. A comparatively shallow CNN model, MobilenetV2 achieved an F1 score of ∼95% for a two-feet thermogram image-based classification and the AdaBoost Classifier used 10 features and achieved an F1 score of 97%. A comparison of the inference time for the best-performing networks confirmed that the proposed algorithm can be deployed as a smartphone application to allow the user to monitor the progression of the DFU in a home setting.
  7. Ali SH, Ahmad Rahman NH, Mohd Shariff N, Karim J, Chin KY
    J Adv Nurs, 2021 Sep;77(9):3933-3939.
    PMID: 34028853 DOI: 10.1111/jan.14880
    AIMS: To determine the challenges perceived by final-year nursing students in the clinical learning environment.

    DESIGN: Data-based convergent mixed-method systematic review.

    METHODS: Three electronic databases (Web of Science, Scopus, and Cumulative Index to Nursing and Allied Health Literature) will be used in the identification stage. The first search will use the search string for each database to identify relevant studies. The articles retrieved will be screened by year of publication, article type and language. Abstracts and full-text of selected studies will be screened for eligibility independently by a minimum of two reviewers. The reference lists will be manually screened to identify additional publications. The quality assessment will be conducted by two reviewers using the Mixed Methods Appraisal Tools. Quantitative and mixed-method studies will be transformed into qualitative. A thematic approach will be used to synthesize and report the data. Ethics approval and funding have been approved in April 2020.

    DISCUSSION: This study will synthesize the types of challenges perceived by final-year undergraduate nursing students in different clinical learning environments across the country.

    IMPACT: The proposed study findings will help nursing education stakeholders and faculty provide assistance to final-year nursing students in their transition year to become registered nurses.

  8. Ying K, Rostenberghe HV, Kuan G, Mohd Yusoff MHA, Ali SH, Yaacob NS
    PMID: 33670850 DOI: 10.3390/ijerph18052351
    Caregiving for children with cerebral palsy (CP) has proved to negatively impact on the physical and psychological well-being of their primary caregivers. The aim of the current study was to examine the overall impact of caregiving for children with CP on the primary caregivers' health-related quality of life (HRQOL) and family functioning, and to identify potential factors associated with primary caregivers' HRQOL and family functioning. The cross-sectional study involved a total of 159 primary caregivers of children with CP with a mean age of 42.8 ± 8.4 years. Demographic data and information on the physical and leisure activities of the primary caregivers were collected, and their quality of life (QOL) was measured based on the self-reported Pediatric Quality of Life Inventory Family Impact Module (PedsQL FIM). Primary caregivers in the current study have shown good HRQOL and family functioning, with scores of 82.4 and 85.3 out of 100, respectively. Through multiple linear regression analyses, the mother's level of education, family monthly income, sleeping problems in children with CP, and the existence of children with other types of disability have been identified as factors contributing to HRQOL and family functioning. The findings help set out the course for stakeholders to establish action to enhance the QOL of primary caregivers.
  9. Hussein-Al-Ali SH, Abudoleh SM, Hussein MZ, Bullo S, Palanisamy A
    IET Nanobiotechnol, 2021 Feb;15(1):79-89.
    PMID: 34694731 DOI: 10.1049/nbt2.12009
    In this study, ellagic acid (ELA), a skin anticancer drug, is capped on the surface(s) of functionalised graphene oxide (GO) nano-sheets through electrostatic and π-π staking interactions. The prepared ELA-GO nanocomposite have been thoroughly characterised by using eight techniques: Fourier-transform infrared spectroscopy (FTIR), zeta potential, X-ray diffraction (XRD), thermogravimetric analysis (TGA), Raman spectroscopy, atomic force microscopy (AFM) topographic imaging, transmission electron microscopy (TEM), and surface morphology via scanning electron microscopy (SEM). Furthermore, ELA drug loading and release behaviours from ELA-GO nanocomposite were studied. The ELA-GO nanocomposite has a uniform size distribution averaging 88 nm and high drug loading capacity of 30 wt.%. The in vitro drug release behaviour of ELA from the nanocomposite was investigated by UV-Vis spectrometry at a wavelength of λmax 257 nm. The data confirmed prolonged ELA release over 5000 min at physiological pH (7.4). Finally, the IC50 of this ELA-GO nanocomposite was found to be 6.16 µg/ml against B16 cell line; ELA and GO did not show any cytotoxic effects up to 50 µg/ml on the same cell lines.
  10. Hussein-Al-Ali SH, Hussein MZ, Bullo S, Arulselvan P
    Int J Nanomedicine, 2021;16:6205-6216.
    PMID: 34526768 DOI: 10.2147/IJN.S312752
    Introduction: Traditional cancer therapies may have incomplete eradication of cancer or destroy the normal cells. Nanotechnology solves the demerit by a guide in surgical resection of tumors, targeted chemotherapies, selective to cancerous cells, etc. This new technology can reduce the risk to the patient and automatically increased the probability of survival. Toward this goal, novel iron oxide nanoparticles (IONPs) coupled with leukemia anti-cancer drug were prepared and assessed.

    Methods: The IONPs were prepared by the co-precipitation method using Fe+3/Fe+2ratio of 2:1. These IONPs were used as a carrier for chlorambucil (Chloramb), where the IONPs serve as the cores and chitosan (CS) as a polymeric shell to form Chloramb-CS-IONPs. The products were characterized using transmission electron microscopy (TEM), powder X-ray diffraction (PXRD), scanning electron microscopy (SEM) analysis, Fourier transform infrared spectroscopy (FTIR), vibrating sample magnetometry (VSM) analyses, and thermal gravimetric analysis (TGA).

    Results: The as-prepared IONPs were found to be magnetite (Fe3O4) and were coated by the CS polymer/Chloramb drug for the formation of the Chloramb-CS-IONPs. The average size for CS-IONPs and Chloramb-CS-IONPs nanocomposite was found to be 15 nm, with a drug loading of 19% for the letter. The release of the drug from the nanocomposite was found to be of a controlled-release manner with around 89.9% of the drug was released within about 5000 min and governed by the pseudo-second order. The in vitro cytotoxicity studies of CS-IONPs and Chloramb-CS-IONPs nanocomposite were tested on the normal fibroblast cell lines (3T3) and leukemia cancer cell lines (WEHI). Chloramb in Chloramb-CS-IONPs nanocomposite was found to be more efficient compared to its free form.

    Conclusion: This work shows that Chloramb-CS-IONPs nanocomposite is a promising candidate for magnetically targeted drug delivery for leukemia anti-cancer agents.

  11. Al-Qazzaz NK, Sabir MK, Bin Mohd Ali SH, Ahmad SA, Grammer K
    J Healthc Eng, 2021;2021:8537000.
    PMID: 34603651 DOI: 10.1155/2021/8537000
    Investigating gender differences based on emotional changes becomes essential to understand various human behaviors in our daily life. Ten students from the University of Vienna have been recruited by recording the electroencephalogram (EEG) dataset while watching four short emotional video clips (anger, happiness, sadness, and neutral) of audiovisual stimuli. In this study, conventional filter and wavelet (WT) denoising techniques were applied as a preprocessing stage and Hurst exponent (Hur) and amplitude-aware permutation entropy (AAPE) features were extracted from the EEG dataset. k-nearest neighbors (kNN) and support vector machine (SVM) classification techniques were considered for automatic gender recognition from emotional-based EEGs. The main novelty of this paper is twofold: first, to investigate Hur as a complexity feature and AAPE as an irregularity parameter for the emotional-based EEGs using two-way analysis of variance (ANOVA) and then integrating these features to propose a new CompEn hybrid feature fusion method towards developing the novel WT_CompEn gender recognition framework as a core for an automated gender recognition model to be sensitive for identifying gender roles in the brain-emotion relationship for females and males. The results illustrated the effectiveness of Hur and AAPE features as remarkable indices for investigating gender-based anger, sadness, happiness, and neutral emotional state. Moreover, the proposed WT_CompEn framework achieved significant enhancement in SVM classification accuracy of 100%, indicating that the novel WT_CompEn may offer a useful way for reliable enhancement of gender recognition of different emotional states. Therefore, the novel WT_CompEn framework is a crucial goal for improving the process of automatic gender recognition from emotional-based EEG signals allowing for more comprehensive insights to understand various gender differences and human behavior effects of an intervention on the brain.
  12. Sabbagh HAK, Hussein-Al-Ali SH, Hussein MZ, Abudayeh Z, Ayoub R, Abudoleh SM
    Polymers (Basel), 2020 Apr 01;12(4).
    PMID: 32244671 DOI: 10.3390/polym12040772
    The goal of this study was to develop and statistically optimize the metronidazole (MET), chitosan (CS) and alginate (Alg) nanoparticles (NP) nanocomposites (MET-CS-AlgNPs) using a (21 × 31 × 21) × 3 = 36 full factorial design (FFD) to investigate the effect of chitosan and alginate polymer concentrations and calcium chloride (CaCl2) concentration ondrug loading efficiency(LE), particle size and zeta potential. The concentration of CS, Alg and CaCl2 were taken as independent variables, while drug loading, particle size and zeta potential were taken as dependent variables. The study showed that the loading efficiency and particle size depend on the CS, Alg and CaCl2 concentrations, whereas zeta potential depends only on the Alg and CaCl2 concentrations. The MET-CS-AlgNPs nanocomposites were characterized by X-ray diffraction (XRD), Fourier-transform infrared spectroscopy (FTIR), thermal gravimetric analysis (TGA), scanning electron microscopy (SEM) and in vitro drug release studies. XRD datashowed that the crystalline properties of MET changed to an amorphous-like pattern when the nanocomposites were formed.The XRD pattern of MET-CS-AlgNPs showed reflections at 2θ = 14.2° and 22.1°, indicating that the formation of the nanocompositesprepared at the optimum conditions havea mean diameter of (165±20) nm, with a MET loading of (46.0 ± 2.1)% and a zeta potential of (-9.2 ± 0.5) mV.The FTIR data of MET-CS-AlgNPs showed some bands of MET, such as 3283, 1585 and 1413 cm-1, confirming the presence of the drug in the MET-CS-AlgNPs nanocomposites. The TGA for the optimized sample of MET-CS-AlgNPs showed a 70.2% weight loss compared to 55.3% for CS-AlgNPs, and the difference is due to the incorporation of MET in the CS-AlgNPs for the formation of MET-CS-AlgNPs nanocomposites. The release of MET from the nanocomposite showed sustained-release properties, indicating the presence of an interaction between MET and the polymer. The nanocomposite shows a smooth surface and spherical shape. The release profile of MET from its MET-CS-AlgNPs nanocomposites was found to be governed by the second kinetic model (R2 between 0.956-0.990) with more than 90% release during the first 50 h, which suggests that the release of the MET drug can be extended or prolonged via the nanocomposite formulation.
  13. Mohd Ali SH, Omar N, Shafie MS, Nik Ismail NA, Hadi H, Nor FM
    Anat Cell Biol, 2020 Mar;53(1):27-35.
    PMID: 32274246 DOI: 10.5115/acb.19.135
    Research in forensic anthropology is recent in Malaysia due to limited access to documented skeletal collections. However, advanced imaging techniques provide virtual bone samples for use in morphometric studies to establish population-specific standards by virtual anthropology. This study examined sexual dimorphism in the subpubic angle using a three-dimensional computed tomography model of the pelvis, in a contemporary Malaysian population. The sample comprised multidetector computed tomography (MDCT) scans of 50 male and 50 female adults. Segmentation of the MDCT scans was performed using 3D Slicer, and four landmarks were acquired using Stratovan Checkpoint for the subpubic angle measurement. The technical error of measurement (TEM), relative TEM, and coefficient of reliability (R) exhibited high reliability in measurements. Results showed that the subpubic angle in males was 68.6°±7.6° and in females 87.4°±6.5°. The subpubic angle in females was significantly larger than in males (P<0.001). Inverse correlation was found between the subpubic angle and age, in both males (r=-0.449, P<0.01) and females (r=-0.385, P<0.01). The overall accuracy of sex estimation using the subpubic angle was 94% (P<0.001). The subpubic angle, with a demarcating point of 78.6°, showed a sensitivity and specificity of 94% in the classification of female individuals. In conclusion, sex estimation using the subpu bic angle is highly accurate, with a high degree of expected sensitivity and specificity in the Malaysian population.
  14. Ahmad R, Rahman NA, Hasan R, Yaacob NS, Ali SH
    Spec Care Dentist, 2020 Jan;40(1):62-70.
    PMID: 31774579 DOI: 10.1111/scd.12436
    AIMS: To investigate the oral health and nutritional status of children with cerebral palsy (CP).

    METHODS AND RESULTS: Oral health assessment included dental caries and dental plaque maturity scores (DPMS) while the nutritional assessment included children's height-for-age Z-score (HAZ), body mass index-for-age Z-score (BAZ), mid-upper-arm circumference (MUAC), nutrient intake, cariogenic food frequency (CFF) and daily sugar exposure (DSE). Ninety-three CP children were recruited. The prevalence of caries was 81.7% (95% CI: 72.7%-88.3%). The median (IQR) of the DMFT and dft scores were 0.5(4.0) and 3.0(8.0), respectively. Most of the participants had acid-producing plaque (90.3%), severely stunted (81.4%), and 45% were severely thin with acute malnutrition. Intakes of calcium, iron, zinc, vitamin A, vitamin D and total fat were below 77% of the Recommended Nutrient Intakes for Malaysian children (RNI 2017). Nine types of cariogenic foods/drinks were consumed moderately, and DSE indicated that 45% of the children were at moderate risk of dental caries.

    CONCLUSION: Untreated dental caries, severe stunting and thinness were prevalent, and cariogenic foods/drinks were consumed moderately suggesting a moderate risk of caries. Therefore, controlling cariogenic food intake is crucial, but monitoring daily nutrient intake is needed for the optimum growth of children with CP.

  15. Abdul Wahab P, Mohd Yusoff D, Abdul Kadir A, Ali SH, Lee YY, Kueh YC
    PeerJ, 2020;8:e8581.
    PMID: 32175185 DOI: 10.7717/peerj.8581
    Background: Chronic constipation is a common symptom among the elderly, and it may affect their quality of life (QoL). A lack of available research focused on the elderly means that this effect is not well understood. This study aimed to develop and validate a new scale (Elderly-Constipation Impact Scale (E-CIS)) to measure the impact of chronic constipation on QoL among the elderly.

    Methods: A pool of items was generated from a qualitative study, literature reviews, and expert reviews. Exploratory factor analysis (EFA) was performed on the original 40 items of the E-CIS and followed by 27 items for confirmatory factor analysis (CFA). A total of 470 elderly people with chronic constipation were involved.

    Results: The mean age of the participants was 68.64 ± 6.57. Finally, only 22 items were indicated as appropriately representing the E-CIS, which were grouped into seven subscales: 'daily activities', 'treatment satisfaction', 'lack of control of bodily function', 'diet restriction', 'symptom intensity', 'anxiety' and 'preventive actions'. The scale was confirmed as valid (root mean square error of approximation (RMSEA) = 0.04, comparative fit index (CFI) = 0.961, Tucker-Lewis index (TLI) = 0.952 and chi-square/degree of freedom (chiSq/df) = 1.44) and reliable (Cronbach's alpha: 0.66-0.85, composite reliability (CR) = 0.699-0.851) to assess the impact of chronic constipation on the elderly's QoL.

    Conclusions: The E-CIS is useful to measure the impact of chronic constipation on the elderly's QoL. A further test is needed to determine the validity and reliability of this scale in other elderly population.

  16. Kohno A, Dahlui M, Nik Farid ND, Ali SH, Nakayama T
    BMJ Open, 2019 09 03;9(9):e027377.
    PMID: 31481551 DOI: 10.1136/bmjopen-2018-027377
    OBJECTIVE: To examine individual, familial, community and societal issues surrounding the reasons for child marriage in Kelantan, Malaysia.

    DESIGN: Qualitative study by means of semistructured interviews with women and key informants, using social-ecological model as a conceptual framework.

    SETTING: Interviews were conducted in Kota Bharu district, Kelantan, a northeast state in Peninsular Malaysia.

    PARTICIPANTS: Eighteen women of reproductive age (18 to 44 years old) that experienced their first marriage below the age of 18, as well as five key informants, consisting of a government officer, a community leader, an officer from religious department and two mothers. The women were recruited from a reproductive health clinic. The key informants who had specialised knowledge related to child marriage were selectively chosen.

    RESULTS: Three themes emerged that aligned with the social-ecological model: immaturity in decision-making, family poverty and religious and cultural norms.

    CONCLUSIONS: The findings imply that sex education and awareness-building activities regarding the consequences of child marriage must be implemented to eradicate child marriage in Malaysia. Such implementation must be coordinated as a team-based approach involving experts in such fields as law, religion, psychology, social-welfare and public health. In order to increase the awareness of child marriage consequences, the target for awareness must extend not only to the adolescent girls and their families, but also to the community and society at large by clearly communicating the negative consequences of and addressing the drivers for child marriage.

  17. Alhasa KM, Mohd Nadzir MS, Olalekan P, Latif MT, Yusup Y, Iqbal Faruque MR, et al.
    Sensors (Basel), 2018 Dec 11;18(12).
    PMID: 30544953 DOI: 10.3390/s18124380
    Conventional air quality monitoring systems, such as gas analysers, are commonly used in many developed and developing countries to monitor air quality. However, these techniques have high costs associated with both installation and maintenance. One possible solution to complement these techniques is the application of low-cost air quality sensors (LAQSs), which have the potential to give higher spatial and temporal data of gas pollutants with high precision and accuracy. In this paper, we present DiracSense, a custom-made LAQS that monitors the gas pollutants ozone (O₃), nitrogen dioxide (NO₂), and carbon monoxide (CO). The aim of this study is to investigate its performance based on laboratory calibration and field experiments. Several model calibrations were developed to improve the accuracy and performance of the LAQS. Laboratory calibrations were carried out to determine the zero offset and sensitivities of each sensor. The results showed that the sensor performed with a highly linear correlation with the reference instrument with a response-time range from 0.5 to 1.7 min. The performance of several calibration models including a calibrated simple equation and supervised learning algorithms (adaptive neuro-fuzzy inference system or ANFIS and the multilayer feed-forward perceptron or MLP) were compared. The field calibration focused on O₃ measurements due to the lack of a reference instrument for CO and NO₂. Combinations of inputs were evaluated during the development of the supervised learning algorithm. The validation results demonstrated that the ANFIS model with four inputs (WE OX, AE OX, T, and NO₂) had the lowest error in terms of statistical performance and the highest correlation coefficients with respect to the reference instrument (0.8 < r < 0.95). These results suggest that the ANFIS model is promising as a calibration tool since it has the capability to improve the accuracy and performance of the low-cost electrochemical sensor.
  18. Mukherjee TI, Pillai V, Ali SH, Altice FL, Kamarulzaman A, Wickersham JA
    Int J Drug Policy, 2017 09;47:144-152.
    PMID: 28652072 DOI: 10.1016/j.drugpo.2017.05.041
    BACKGROUND: Approximately 40%-90% of people who inject drugs (PWID) in Malaysia have hepatitis C (HCV). PWID continue to be disproportionately affected by HCV due to their lack of knowledge, perceived risk and interest in HCV treatment. Education interventions may be an effective strategy for increasing HCV knowledge in PWID, and harm reduction services are uniquely positioned to implement and deploy such interventions.

    METHODS: We recruited 176 clients from methadone maintenance treatment (MMT: N=110) and needle/syringe programs (NSP: N=66) between November 2015 and August 2016. After baseline knowledge assessments, clients participated in a standardized, 45-min HCV education program and completed post-intervention knowledge assessments to measure change in knowledge and treatment interest.

    RESULTS: Participants were mostly male (96.3%), Malay (94.9%), and in their early 40s (mean=42.6years). Following the intervention, overall knowledge scores and treatment interest in MMT clients increased by 68% and 16%, respectively (p<0.001). In contrast, NSP clients showed no significant improvement in overall knowledge or treatment interest, and perceived greater treatment barriers. Multivariate linear regression to assess correlates of HCV knowledge post-intervention revealed that optimal dosage of MMT and having had an HIV test in the past year significantly increased HCV knowledge. Having received a hepatitis B vaccine, however, was not associated with increased HCV knowledge after participating in an education session.

    CONCLUSION: Generally, HCV knowledge and screening is low among clients engaged in MMT and NSP services in Malaysia. Integrating a brief, but comprehensive HCV education session within harm reduction services may be a low-cost and effective strategy in improving overall HCV knowledge and risk behaviors in resource-limited settings. In order to be an effective public health approach, however, education interventions must be paired with strategies that improve social, economic and political outcomes for PWID. Doing so may reduce HCV disparities by increasing screening and treatment interest.

  19. Rahman AA, Rahman RA, Ismail SB, Ibrahim MI, Ali SH, Salleh H, et al.
    Asia Pac J Public Health, 2015 Mar;27(2):NP1549-56.
    PMID: 22751680 DOI: 10.1177/1010539512449856
    The objective of this cross-sectional study was to determine the factors associated with the attitudes toward premarital sexual activities among school-going adolescents in Kelantan, Malaysia. It was conducted among 1032 secondary school students using a self-administered validated questionnaire. Multiple logistic regression revealed that the risk factors for having permissive attitudes toward practice of premarital sexual activities were male students (odds ratio [OR] = 1.83; 95% confidence interval [CI] = 1.34-2.48), being less religious (OR = 2.02; 95% CI = 1.49-2.73), and younger age group of students (13 to 14 years old; OR = 1.42; 95% CI = 1.05-1.92). Having good knowledge on sexual and reproductive health was a protective factor against permissive sexual attitude (OR = 0.27; 95% CI = 0.20-0.36). In conclusion, male and young adolescents were at risk of having permissive attitudes toward sexual behaviors, but good knowledge on sexual and reproductive health and being more religious may protect them from it.
  20. Al-Qazzaz NK, Bin Mohd Ali SH, Ahmad SA, Islam MS, Escudero J
    Sensors (Basel), 2015;15(11):29015-35.
    PMID: 26593918 DOI: 10.3390/s151129015
    We performed a comparative study to select the efficient mother wavelet (MWT) basis functions that optimally represent the signal characteristics of the electrical activity of the human brain during a working memory (WM) task recorded through electro-encephalography (EEG). Nineteen EEG electrodes were placed on the scalp following the 10-20 system. These electrodes were then grouped into five recording regions corresponding to the scalp area of the cerebral cortex. Sixty-second WM task data were recorded from ten control subjects. Forty-five MWT basis functions from orthogonal families were investigated. These functions included Daubechies (db1-db20), Symlets (sym1-sym20), and Coiflets (coif1-coif5). Using ANOVA, we determined the MWT basis functions with the most significant differences in the ability of the five scalp regions to maximize their cross-correlation with the EEG signals. The best results were obtained using "sym9" across the five scalp regions. Therefore, the most compatible MWT with the EEG signals should be selected to achieve wavelet denoising, decomposition, reconstruction, and sub-band feature extraction. This study provides a reference of the selection of efficient MWT basis functions.
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