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Development of a questionnaire for assessing factors predicting blood donation among university students: a pilot study

Jalalian M, Latiff L, Hassan ST, Hanachi P, Othman M

Southeast Asian J. Trop. Med. Public Health, 2010 May;41(3):660-6.
PMID: 20578556

University students are a target group for blood donor programs. To develop a blood donation culture among university students, it is important to identify factors used to predict their intent to donate blood. This study attempted to develop a valid and reliable measurement tool to be employed in assessing variables in a blood donation behavior model based on the Theory of Planned Behavior (TPB), a commonly used theoretical foundation for social psychology studies. We employed an elicitation study, in which we determined the commonly held behavioral and normative beliefs about blood donation. We used the results of the elicitation study and a standard format for creating questionnaire items for all constructs of the TPB model to prepare the first draft of the measurement tool. After piloting the questionnaire, we prepared the final draft of the questionnaire to be used in our main study. Examination of internal consistency using Chronbach's alpha coefficient and item-total statistics indicated the constructs "Intention" and "Self efficacy" had the highest reliability. Removing one item from each of the constructs, "Attitude," "Subjective norm," "Self efficacy," or "Behavioral beliefs", can considerably increase the reliability of the measurement tool, however, such action is controversial, especially for the variables "attitude" and "subjective norm." We consider all the items of our first draft questionnaire in our main study to make it a reliable measurement tool.
Fulltext Clear cell adenocarcinoma of the cervix in a ten-year-old girl without prenatal diethylstilbestrol exposure

Andi Asri AA, Lim BK, Lim YK, A Latiff L

Singapore Med J, 2016 Aug;57(8):470.
PMID: 27549741 DOI: 10.11622/smedj.2016138
A systematic review of security and privacy issues in the internet of medical things; the role of machine learning approaches

Hameed SS, Hassan WH, Abdul Latiff L, Ghabban F

PeerJ Comput Sci, 2021;7:e414.
PMID: 33834100 DOI: 10.7717/peerj-cs.414

Background: The Internet of Medical Things (IoMTs) is gradually replacing the traditional healthcare system. However, little attention has been paid to their security requirements in the development of the IoMT devices and systems. One of the main reasons can be the difficulty of tuning conventional security solutions to the IoMT system. Machine Learning (ML) has been successfully employed in the attack detection and mitigation process. Advanced ML technique can also be a promising approach to address the existing and anticipated IoMT security and privacy issues. However, because of the existing challenges of IoMT system, it is imperative to know how these techniques can be effectively utilized to meet the security and privacy requirements without affecting the IoMT systems quality, services, and device's lifespan.
Methodology: This article is devoted to perform a Systematic Literature Review (SLR) on the security and privacy issues of IoMT and their solutions by ML techniques. The recent research papers disseminated between 2010 and 2020 are selected from multiple databases and a standardized SLR method is conducted. A total of 153 papers were reviewed and a critical analysis was conducted on the selected papers. Furthermore, this review study attempts to highlight the limitation of the current methods and aims to find possible solutions to them. Thus, a detailed analysis was carried out on the selected papers through focusing on their methods, advantages, limitations, the utilized tools, and data.
Results: It was observed that ML techniques have been significantly deployed for device and network layer security. Most of the current studies improved traditional metrics while ignored performance complexity metrics in their evaluations. Their studies environments and utilized data barely represent IoMT system. Therefore, conventional ML techniques may fail if metrics such as resource complexity and power usage are not considered.
Dietary intake of patients with angiographically defined coronary artery disease and that of healthy controls in Iran

Nazeminezhad R, Tajfard M, Latiff LA, Mouhebati M, Esmaeily H, Ferns GA, et al.

Eur J Clin Nutr, 2014 Jan;68(1):109-13.
PMID: 24219895 DOI: 10.1038/ejcn.2013.205

The aim of this study was to investigate the relationship between dietary intake and biomarkers of cardiovascular risk in individuals with and without angiographically defined coronary artery disease.
Medical researchers in non-English countries and concerns about unintentional plagiarism

Hosseini MJ, Bazargani R, Latiff L, Hanachi P, Hassan ST, Othman M

J Med Ethics Hist Med, 2009;2:14.
PMID: 23908728
Knowledge, Prevention Strategies, and Intervention Tactics: Traumas and Motor Vehicle Accidents

Syed Hassan ST, Jamaludin H, Raman RA, A Latiff L, Mohd Riji H

Bull Emerg Trauma, 2013 Jan;1(1):3-4.
PMID: 27162813
Fulltext Depression and its associated factors among secondary school students in Malaysia

Abdul Latiff L, Tajik E, Ibrahim N, Abubakar AS, Ali SS

Southeast Asian J. Trop. Med. Public Health, 2016 Jan;47(1):131-41.
PMID: 27086434

Research in the field of factors associated with depression among adolescents is lacking in Malaysia. The aims of the present study were to assess the current prevalence of depression and its related factors among secondary school students in Pasir Gudang, South Malaysia. In this cross sectional study, 2,927 secondary school students (13-17 years old) from urban areas were screened for symptoms of mental disorder as well as demographic and risk behaviors using a validated Depression, Anxiety and Stress Scale (DASS) 12 questionnaire. The majority of the respondents (53.8%) were Malay, of which 53.1% were female. Symptoms of mild depression were found in 33.2% of the respondents, while the prevalence of the symptoms of moderate, severe, and extremely severe depression was 21.5%, 18.1%, and 3.0%, respectively. Logistic regression suggested that participants who were Chinese or had a lower average grade were three times more likely to have depression, while those who came from a single-parent family were twice as likely to have this condition. This study indicated that academic performance and risk behaviors along with the demographic characteristics are important contributors to adolescent depression.
A study on level of physical activity, depression, anxiety and stress symptoms among adolescents

Tajik E, Abd Latiff L, Adznam SN, Awang H, Yit Siew C, Abu Bakar AS

J Sports Med Phys Fitness, 2017 Oct;57(10):1382-1387.
PMID: 28004901 DOI: 10.23736/S0022-4707.16.06658-5

BACKGROUND: Inadequate physical activity has adverse health consequences among adolescents. Mental health problem can be developed by lack of physical activity however it is controversial. The current study aimed to examine the association between level of physical activity with depression, anxiety and stress symptoms among adolescents.
METHODS: A representative sample of 1747 adolescents (13-14 years) was randomly selected from 6 schools in a south part of Malaysia. Respondents were asked to fill consent form, and questionnaires including Depression Anxiety and Stress Scale-21 and Physical Activity Questionnaire for Adolescents.
RESULTS: Majority of respondents (71.9%) was Malay and more than half of the adolescents had low physical activity. About 40% had depression symptoms, followed by anxiety symptoms (65.9%) and stress symptoms (38.5%). Level of physical activity was significantly associated with gender, anxiety and stress (P<0.001). There were no associations with race, religion and depression symptom.
CONCLUSIONS: This study provides some evidence among school-going adolescents related to anxiety and stress symptoms and low physical activities. Further studies are needed to show the protection effects of higher physical activity for depression, anxiety and stress symptoms in adolescents.
Fulltext Protective Effects of Nigella sativa on Metabolic Syndrome in Menopausal Women

Ibrahim RM, Hamdan NS, Ismail M, Saini SM, Abd Rashid SN, Abd Latiff L, et al.

Adv Pharm Bull, 2014;4(1):29-33.
PMID: 24409406 DOI: 10.5681/apb.2014.005

PURPOSE: This study was conducted in menopausal women to determine the metabolic impact of Nigella sativa.
METHODS: Thirty subjects who were menopausal women within the age limit of 45-60 were participated in this study and randomly allotted into two experimental groups. The treatment group was orally administered with N. sativa seeds powder in the form of capsules at a dose of 1g per day after breakfast for period of two months and compared to control group given placebo. Anthropometric and biochemical parameters were measured at baseline, 1st month, 2nd month and a month after treatment completed to determine their body weight, serum lipid profile and fasting blood glucose (FBG).
RESULTS: The treatment group showed slight reduction with no significant difference in body weight changes of the respondents. However, significant (p<0.05) improvement was observed in total cholesterol (TC), triglycerides (TG), low density lipoprotein cholesterol (LDL-C), high density lipoprotein cholesterol (HDL-C), and blood glucose (p<0.05).
CONCLUSION: These results suggested that treatment with N. sativa exert a protective effect by improving lipid profile and blood glucose which are in higher risk to be elevated during menopausal period.
Fulltext A Hybrid Lightweight System for Early Attack Detection in the IoMT Fog

Hameed SS, Selamat A, Abdul Latiff L, Razak SA, Krejcar O, Fujita H, et al.

Sensors (Basel), 2021 Dec 11;21(24).
PMID: 34960384 DOI: 10.3390/s21248289

Cyber-attack detection via on-gadget embedded models and cloud systems are widely used for the Internet of Medical Things (IoMT). The former has a limited computation ability, whereas the latter has a long detection time. Fog-based attack detection is alternatively used to overcome these problems. However, the current fog-based systems cannot handle the ever-increasing IoMT's big data. Moreover, they are not lightweight and are designed for network attack detection only. In this work, a hybrid (for host and network) lightweight system is proposed for early attack detection in the IoMT fog. In an adaptive online setting, six different incremental classifiers were implemented, namely a novel Weighted Hoeffding Tree Ensemble (WHTE), Incremental K-Nearest Neighbors (IKNN), Incremental Naïve Bayes (INB), Hoeffding Tree Majority Class (HTMC), Hoeffding Tree Naïve Bayes (HTNB), and Hoeffding Tree Naïve Bayes Adaptive (HTNBA). The system was benchmarked with seven heterogeneous sensors and a NetFlow data infected with nine types of recent attack. The results showed that the proposed system worked well on the lightweight fog devices with ~100% accuracy, a low detection time, and a low memory usage of less than 6 MiB. The single-criteria comparative analysis showed that the WHTE ensemble was more accurate and was less sensitive to the concept drift.
Testing comparison models of DASS-12 and its reliability among adolescents in Malaysia

Osman ZJ, Mukhtar F, Hashim HA, Abdul Latiff L, Mohd Sidik S, Awang H, et al.

Compr Psychiatry, 2014 Oct;55(7):1720-5.
PMID: 24952938 DOI: 10.1016/j.comppsych.2014.04.011

OBJECTIVE: The 21-item Depression, Anxiety and Stress Scale (DASS-21) is frequently used in non-clinical research to measure mental health factors among adults. However, previous studies have concluded that the 21 items are not stable for utilization among the adolescent population. Thus, the aims of this study are to examine the structure of the factors and to report on the reliability of the refined version of the DASS that consists of 12 items.
METHOD: A total of 2850 students (aged 13 to 17 years old) from three major ethnic in Malaysia completed the DASS-21. The study was conducted at 10 randomly selected secondary schools in the northern state of Peninsular Malaysia. The study population comprised secondary school students (Forms 1, 2 and 4) from the selected schools.
RESULTS: Based on the results of the EFA stage, 12 items were included in a final CFA to test the fit of the model. Using maximum likelihood procedures to estimate the model, the selected fit indices indicated a close model fit (χ(2)=132.94, df=57, p=.000; CFI=.96; RMR=.02; RMSEA=.04). Moreover, significant loadings of all the unstandardized regression weights implied an acceptable convergent validity. Besides the convergent validity of the item, a discriminant validity of the subscales was also evident from the moderate latent factor inter-correlations, which ranged from .62 to .75. The subscale reliability was further estimated using Cronbach's alpha and the adequate reliability of the subscales was obtained (Total=76; Depression=.68; Anxiety=.53; Stress=.52).
CONCLUSION: The new version of the 12-item DASS for adolescents in Malaysia (DASS-12) is reliable and has a stable factor structure, and thus it is a useful instrument for distinguishing between depression, anxiety and stress.