This study evaluated the convergent, discriminant, construct, concurrent and discriminative validity of the Medical Student Wellbeing Index (MSWBI) as well as to evaluate its internal consistency and optimal cut-off total scores to detect at least moderate levels of general psychological distress, stress, anxiety and depression symptoms. A cross sectional study was done on 171 medical students. The MSWBI and DASS-21 were administered and returned immediately upon completion. Confirmatory factor analysis, reliability analysis, ROC analysis and Pearson correlation test were applied to assess psychometric properties of the MSWBI. A total of 168 (98.2%) medical students responded. The goodness of fit indices showed the MSWBI had a good construct (χ(2)=6.14, p=0.803, RMSEA<0.001, RMR=0.004, GFI=0.99, AGFI=0.97, CFI=1.00, IFI=1.02, TLI=1.04). The Cronbach's alpha value was 0.69 indicating an acceptable level of internal consistency. Pearson correlation coefficients and ROC analysis suggested each MSWBI's item showed adequate convergent and discriminant validity. Its optimal cut-off scores to detect at least moderate levels of general psychological distress, stress, anxiety, and depression were 1.5, 2.5, 1.5 and 2.5 respectively with sensitivity and specificity ranged from 62 to 80% and the areas under ROC curve ranged from 0.71 to 0.83. This study showed that the MSWBI had good level of psychometric properties. The MSWBI score more than 2 can be considered as having significant psychological distress. The MSWBI is a valid and reliable screening instrument to assess psychological distress of medical students.
The Nursing Stress Scale (NSS) has been shown to be a valid and reliable instrument to assess occupational stressors among nurses. The NSS, which was previously used in the English version, was translated and back-translated into Bahasa Melayu. This study was conducted to assess the reliability of the Bahasa Melayu version of the NSS among nurses for future studies in this country. The reliability of the NSS was assessed after its readministration to 30 nurses with a 2-week interval. The Spearman coefficient was calculated to assess its stability. The internal consistency was measured through 4 measures: Cronbach's α, Spearman-Brown, Guttman split-half, and standardized item α coefficients. The total response rate was 70%. Test-retest reliability showed remarkable stability (Spearman's ρ exceeded .70). All 4 measures of internal consistency among items indicated a satisfactory level (coefficients in the range of .68 to .87). In conclusion, the Bahasa Melayu version of the NSS is a reliable and useful instrument for measuring the possible stressors at the workplace among nurses.
BACKGROUND: Several disease specific instruments have been developed to identify and assess diabetes distress. In Malaysia, the Problem Areas in Diabetes Scale has been validated in Malay, but it does not have specific domains to assess the different areas of diabetes-related distress. Hence, we decided to use the Diabetes Distress Scale instead. To date, only the Malay version of the Diabetes Distress Scale has been validated in Malaysia. However, English is widely spoken by Malaysians, and is an important second language in Malaysia. Therefore, our aim was to determine the validity and reliability of the English version of the Diabetes Distress Scale among patients with type 2 diabetes in Malaysia.
METHODS: The Diabetes Distress Scale was administered to 114 patients with type 2 diabetes, who could understand English, at baseline and 4 weeks later, at a primary care clinic in Malaysia. To assess for convergent validity, the Depression Anxiety Stress Scale was administered at baseline. Discriminative validity was assessed by analysing the total diabetes distress scores of participants with poor (HbA1c > 7.0%) and good glycaemic control (HbA1c ≤ 7.0%).
RESULTS: The majority of our participants were male 65(57.0%), with a median duration of diabetes of 9.5 years. Exploratory factor analysis showed that the Diabetes Distress Scale had 4 subscales, as per the original Diabetes Distress Scale. The overall Cronbach's α was 0.920 (range = 0.784-0.859 for each subscale). The intraclass correlation ranged from 0.436 to 0.643 for test-retest. The Diabetes Distress Scale subscales were significantly correlated with the different subscales of the Depression Anxiety Stress Scale (spearman's rho range = 0.427-0.509, p
This small, cross-sectional study assessed the reliability of 3 scales from the Job Content Questionnaire (JCQ)-decision latitude, psychological job demand, and social support-in a group of office workers in a multinational company in Kuala Lumpur. A universal sample of 30 white-collar workers from a department of the company self-administered the English version of the JCQ comprising 21 core items selected from the full recommended version of 49 items on-site. Reliability (internal consistency) was evaluated using Cronbach's alpha coefficients for each scale. Corrected item-total correlation was presented for each and every item. Cronbach's alpha coefficients were acceptable for decision latitude (.76) and social support (.79) but slightly lower for psychological job demand (.64). Values for all item-total correlations for all 3 scales were greater than .3. In conclusion, this study suggests that the JCQ is a reliable scale for assessing job stress in this group of workers.
Exposure to mental stress for long period leads to serious accidents and health problems. To avoid negative consequences on health and safety, it is very important to detect mental stress at its early stages, i.e., when it is still limited to acute or episodic stress. In this study, we developed an experimental protocol to induce two different levels of stress by utilizing a mental arithmetic task with time pressure and negative feedback as the stressors. We assessed the levels of stress on 22 healthy subjects using frontal electroencephalogram (EEG) signals, salivary alpha-amylase level (AAL), and multiple machine learning (ML) classifiers. The EEG signals were analyzed using a fusion of functional connectivity networks estimated by the Phase Locking Value (PLV) and temporal and spectral domain features. A total of 210 different features were extracted from all domains. Only the optimum multi-domain features were used for classification. We then quantified stress levels using statistical analysis and seven ML classifiers. Our result showed that the AAL level was significantly increased (p < 0.01) under stress condition in all subjects. Likewise, the functional connectivity network demonstrated a significant decrease under stress, p < 0.05. Moreover, we achieved the highest stress classification accuracy of 93.2% using the Support Vector Machine (SVM) classifier. Other classifiers produced relatively similar results.
In real-life applications, electroencephalogram (EEG) signals for mental stress recognition require a conventional wearable device. This, in turn, requires an efficient number of EEG channels and an optimal feature set. This study aims to identify an optimal feature subset that can discriminate mental stress states while enhancing the overall classification performance. We extracted multi-domain features within the time domain, frequency domain, time-frequency domain, and network connectivity features to form a prominent feature vector space for stress. We then proposed a hybrid feature selection (FS) method using minimum redundancy maximum relevance with particle swarm optimization and support vector machines (mRMR-PSO-SVM) to select the optimal feature subset. The performance of the proposed method is evaluated and verified using four datasets, namely EDMSS, DEAP, SEED, and EDPMSC. To further consolidate, the effectiveness of the proposed method is compared with that of the state-of-the-art metaheuristic methods. The proposed model significantly reduced the features vector space by an average of 70% compared with the state-of-the-art methods while significantly increasing overall detection performance.
Previous works on the effects of salivary alpha amylase in respond to various stressors report encouraging findings on it being a good indicator of stress. Ellestad protocol is a clinical procedure to screen for coronary artery disease by introducing exercise induced physical stress. If a salivary based biomarker profile in accordance to a stress test protocol could be established, the critical stress state which disable rational decision making could be ascertained in a standardized procedure. This technique would serve to aid human resource management in times of critical events such as rescue, firefighting or even military, that would potentially prevent unnecessary sacrifice of human lives. In this pilot study with five healthy volunteers performing the Ellestad protocol treadmill, a measurement profile with physiologic and salivary based biomarker is obtained. It is found that the alpha amylase levels or the changes in it as workload changes from resting-walking-running at ease-exhaustive running, is relatively more significant in reflecting the stress state than heart rate and blood pressure. Moreover, it is strongly associated with mood state with correlation coefficient of 0.8 and significance of 0.01.