METHODS: Seven hundred seventy individuals aged 55 years (lower age limit) and above were interviewed as to whether they experienced pruritus during the preceding week and the locations involved if present. The association between generalised pruritus, sleep quality, and major systemic risk factors were explored.

RESULTS: 5.97% of respondents reported generalised pruritus. Generalised pruritus was associated with poorer sleep quality, with Pittsburgh Sleep Quality Index score above 6. Mean haemoglobin level was lower in subjects with generalised pruritus (13.14 g/dL) but there was no significant difference in the frequency of generalised pruritus and severe generalized pruritus between subjects with clinically defined anaemia. Also, there were no significant associations between other major systemic risk factors and generalised pruritus in this population-based study. There was no association between generalised pruritus with depression, anxiety or stress.

Patients and methods: This cross-sectional study included 167 SLE patients (21 males, 146 females; mean age 38.2±9.8 years; range, 20 to 60 years) recruited from the outpatient Rheumatology and Nephrology clinics. Face-to-face interviews were conducted to record patients' socio- demographics (age, sex, ethnicity, marital status, and occupation) and SLE disease characteristics (system involvement, age onset, and presence of organ damage). Disease activity was assessed using the Systemic Lupus Erythematosus Disease Activity Index-2000 (SLEDAI-2K). Short form 36 (SF-36) was used to determine health-related quality of life (HRQoL) while Work Productivity and Activity Impairment (WPAI) questionnaire was used to assess the four domains of absenteeism, presenteeism, overall work productivity, and non-work related ADL impairment. Univariate analyses and multivariable regression analysis examined the association of demographic variables, SLE disease characteristics, and activity with reduced HRQoL and WPAI scores.

Results: The majority of the patients were Malays (59.3%), followed by Chinese (34.7%) and Indian (3.6%) patients. More than two-thirds of the patients reported some degree of impairment in their work productivity and ADL due to the disease. The absenteeism rate was 10.4% in the past one week and their indirect costs were 2,875.17 Malaysian ringgits (US $701.22) in the past seven days. Significant predictors of higher work productivity and ADL impairment scores were higher disease activity, more frequent SLE flares, lupus nephritis, and hematological involvement of SLE. Patients with higher work productivity and ADL impairment scores were also strongly associated with poor QoL. No ethnic disparities of work productivity and ADL impairment were found.

DESIGN: Prospective, non-randomized trial.

SETTING: Naturalistic driving in Malaysia.

PARTICIPANTS: Heavy vehicle drivers in Malaysia were assigned to the Device (n = 25) or Control condition (n = 34).

INTERVENTION: Both conditions were monitored for driving events at work over 4-weeks in Phase 1, and 12-weeks in Phase 2. In Phase 1, the Device condition wore the device operated in the silent mode (i.e., no drowsiness alerts) to examine the accuracy of the device in predicting driving events. In Phase 2, the Device condition wore the device in the active mode to examine if drowsiness alerts from the device influenced the rate of driving events (compared to Phase 1).

MEASUREMENTS: All participants were monitored for harsh braking and harsh acceleration driving events and self-reported sleep duration and sleepiness daily.

METHODS: First, 130 subjects were surveyed by self-entry questionnaire for statistical factors related to social demographics and sedentary behavior. These factors were age (years), gender (man/woman), body mass index (BMI, kg/m2), educational history (>13 years, %), employment (full-time or part-time, yes, %), alcohol intake (a certain amount, yes, %), smoking behavior (yes, %), and marital status (yes, %). BMI, as obtained from the participants' weight and height, was collected from the self-reported questionnaire and assessed. Sitting behavior time as an index of sedentary behavior on workdays, non-workdays, and total time was identified by questionnaire. Data were analyzed using the chi square-test and t-test, respectively. The criterion for a statistically significant difference was p < 0.05.

RESULTS: Finally, 107 subjects (68 men, 39 women) were analyzed. The ratios of social demographic factors of the men versus women group were age (58.5 ± 14.7 vs. 61.0 ± 12.1 years, p = 0.36), BMI (23.1 ± 2.6 vs. 21.8 ± 2.6 kg/m2, p = 0.01), educational history (86.7% vs. 56.4%, p < 0.001), employment (51.5% vs. 10.3%, p <0.001), alcohol intake (86.7% vs. 35.9%, p < 0.001), smoking behavior (30.9% vs. 10.3%, p = 0.01), and marital status (88.2% vs. 100%, p = 0.02). Sitting behavior time was 501.8 ± 254.6 vs. 346.0 ± 153.4 minutes (p < 0.001) on workdays, 415.1 ± 225.3 vs. 320.6 ± 178.7 minutes (p = 0.019) on non-workdays, and 458.5 ± 203.9 vs. 333.3 ± 132.1 minutes (p < 0.001) in total.

METHODS: A cross-sectional HRQoL survey of Malaysian children with TDT was conducted using the PedsQL™ 4.0 Generic Core Scales. Patients with non-transfusion dependent thalassemia and other haemoglobinopathies were excluded. Parent-proxy and self-reported HRQoL scores were obtained using a multi-stage convenient sampling. The relationship between HRQoL scores and demographic factors were tested using association, correlation and regression analysis.

METHODS: This cross-sectional study was conducted from July to October 2016. All the 140 doctors in 12 public primary care clinics in Kuala Lumpur were invited to participate in this study. However, only 122 doctors (females, 82.8%) completed the self-administered questionnaire that assessed their demography, clinical experience, SCI practice and its barriers, self-efficacy in delivering and knowledge on smoking and SCI.

RESULTS: Only 42.6% of the doctors had good SCI practice. Almost all doctors assessed the smoking status of their patients (98.4%) and advised them to quit (98.4%). However, lesser proportions of the doctors followed up the practice of patients (50.0%), taught smokers on various methods of quit smoking (46.70%) and discussed about the barriers and resources to quit prior to the quit date (27.9%). Less than one-fourth of the doctors were confident in providing SCI. Although 69.7% had previous training in SCI, many felt they had inadequate knowledge (56.6%) and skills (47.5%). Only 11.5% of doctors thought their previous training was enough. Having higher level of knowledge on smoking and SCI was significantly associated with good SCI practice [adjusted Odds Ratio (95% Confidence Intervals): 1.21 (1.02, 1.43), p=0.026].

METHOD: The study was a cross-sectional design in nature, using self-reported questionnaires among the university students in Malaysia. Participants were selected using a convenience sampling approach. Perceptions regarding social support and physical environment were assessed using the Malay-translated version scales. The standard forward-backwards translation was conducted to translate the English version of the scales to the Malay version. Confirmatory factor analysis (CFA) was used to validate the translated version scales; composite reliability (CR) and average variance extracted (AVE) were computed.

RESULTS: A total of 857 students participated in this study (female: 49.1%, male: 50.9%). The mean age of the participants was 20.2 (SD = 1.6). The fit indices of the initial hypothesized measurement models (social support and physical environment) were not satisfactory. Further improvements were made by adding covariances between residuals' items within the same factor for each hypothesized model. The final re-specified measurement models demonstrated adequate factor structure for the social support scale with 24 items (CFI = .932, TLI = .920, SRMR = .054, RMSEA = .061), and the physical environment scale with five items (CFI = .994, TLI = .981, SRMR = .013, RMSEA = .054). The CR was .918 for family support, .919 for friend support, .813 for perceived availability, and .771 for perceived quality. The AVEs were .560 for family support, .547 for friend support, .554 for perceived availability, and .628 for perceived quality. The intra-class correlation (ICC) based on test-retest was .920 for family support, .984 for friend support, .895 for availability of facilities, and .774 for quality of facilities.

CONCLUSION: The Malay version of the social support scale for exercise and the physical environment scale for physical activity were shown to have adequate psychometric properties for assessing perceived social support and physical environment among the university students in Malaysia.

OBJECTIVE: The present study aims to examine differences in psychological factors, disability and subjective fatigue between subgroups of LBP based on their chronification grade.

METHODS: Twenty-one healthy controls (HC) and 54 LBP patients (categorized based on the grades of chronicity into recurrent LBP (RLBP), non-continuous chronic LBP (CLBP), or continuous (CLBP)) filled out a set of self-reporting questionnaires.

RESULTS: The Hospital Anxiety and Depression Scale (HADS) and Multidimensional Pain Inventory (MPI) scores indicated that anxiety, pain severity, pain interference and affective distress were lower in HC and RLBP compared to non-continuous CLBP. Anxiety scores were higher in non-continuous CLBP compared to RLBP, continuous CLBP and HC. The Pain Catastrophizing Scale for Helplessness (PSCH) was higher in non-continuous CLBP compared to HC. The Survey of Pain Attitudes (SOPA) showed no differences in adaptive and maladaptive behaviors across the groups. The Pain Disability Index (PDI) measured a higher disability in both CLBP groups compared to HC. Moreover, the Rolland Morris Disability Questionnaire (RMDQ) showed higher levels of disability in continuous CLBP compared to non-continuous CLBP, RLBP and HC. The Checklist Individual Strength (CIS) revealed that patients with non-continuous CLBP were affected to a higher extent by severe fatigue compared to continuous CLBP, RLBP and HC (subjective fatigue, concentration and physical activity). For all tests, a significance level of 0.05 was used.