Assessing the measurement invariance of the 10-item Centre for Epidemiological Studies Depression Scale and Beck Anxiety Inventory questionnaires across people living with HIV/AIDS and healthy people

Psychometric Properties and Cross-Cultural Invariance of the Beck Depression Inventory-II and Beck Anxiety Inventory among a Representative Sample of Spanish, Portuguese, and Brazilian Undergraduate Students

Clinical psychologists often use the Beck Depression Inventory, 2nd edition (BDI-II), and Beck Anxiety Inventory (BAI) to aid in the diagnosis of mental health issues and verify the effectiveness of treatments. Despite this common practice, studies that implement a cross-cultural design to check psychometric properties and the invariance of these scales are still scarce in the literature, which can lead to biased results that prevent comparisons among different groups. The present study investigated the internal structure of both tools and their level of invariance. From a representative sample of undergraduate students from Spain (n = 1216), Portugal (n = 426), and Brazil (n = 315), Confirmatory Factor Analysis and Multigroup Confirmatory Factor Analysis were performed. The results revealed suitable fit indices for the two-factor structure of the BDI-II and BAI, assessed by Confirmatory Factor Analysis procedures. Additionally, the two-factor model of the BDI-II reached invariant properties at three levels, whereas the structural model of the BAI did not. Altogether, these results suggest using the BDI-II in this group in these three countries and imply that BAI scores should be interpreted cautiously.

Suicidal ideation of people living with HIV and its relations to depression, anxiety and social support

BACKGROUND

The HIV/AIDS (human immunodeficiency virus/acquired immune deficiency syndrome) remains a global threat to health. Suicidal ideation has been a serious public health problem among people living with HIV (PLWH). However, the suicide prevention mechanism among PLWH still unclear. This study aims to analyze the suicidal ideation and its related factors in PLWH, and further explore the relationships between suicidal ideation and depression, anxiety and perceived social support.

METHODS

This is a cross-sectional study. A total of 1146 PLWH were investigated by the general information questionnaire, the perceived social support scale (PSSS), the Beck scale for suicide ideation of Chinese version (BSI-CV), the generalized anxiety disorder scale-2 (GAD-2) and the patient health questionnaire-2 (PHQ-2) though the WeChat in China in 2018. By using statistical description and the binary unconditional logistic regression, we assessed the incidence of suicidal ideation and its related factors in PLWH. Besides, the intermediary effect of social support between anxiety, depression and suicidal ideation were explored by the stepwise test and Bootstrap method.

RESULTS

The incidence of suicide ideation was 54.0% (619/1146) among the PLWH in the last week or during the most serious depression. Binary logistic regression analysis results showed that the PLWH who with short time for HIV positive diagnosis (aOR (adjusted odd ratio) = 1.754, 95% CI (confidence interval):1.338-2.299), low monthly income (aOR = 1.515, 95%CI:1.098-2.092), other chronic diseases except HIV (aOR = 1.555, 95%CI:1.134-2.132), irregular lovers (aOR = 1.369, 95%CI:1.021-1.837), anxiety (aOR = 2.711, 95%CI:1.767-4.161), depression (aOR = 1.614, 95%CI:1.078-2.417), low PSSS (aOR = 2.139, 95%CI:1.345-3.399) had high risk of suicide ideation.The social support played a mediating role between the anxiety (the mediating effect accounted for 30.43% of the total effect), depression (the mediating effect accounted for 23.76% of the total effect) and the suicide ideation among PLWH.

CONCLUSION

The incidence of suicide ideation of PLWH was high. Anxiety, depression, and social support are the key factors of suicide ideation of PLWH. Social support plays a partial mediating role between anxiety, depression and suicidal ideation, which provides a new approach for prevention of suicidal ideation in PLWH and should be known widely for people to prevent suicide.

Computer assisted identification of stress, anxiety, depression (SAD) in students: A state-of-the-art review

Stress, depression, and anxiety are a person's physiological states that emerge from various body features such as speech, body language, eye contact, facial expression, etc. Physiological emotion is a part of human life and is associated with psychological activities. Sad emotion is relatable to negative thoughts and recognized in three stages containing stress, anxiety, and depression. These stages of Physiological emotion show various common and distinguished symptoms. The present study explores stress, depression, and anxiety symptoms in student life. The study reviews the psychological features generated through various body parts to identify psychological activities. Environmental factors, including a daily routine, greatly trigger psychological activities. The psychological disorder may affect mental and physical health adversely. The correct recognition of such disorder is expensive and time-consuming as it requires accurate datasets of symptoms. In the present study, an attempt has been made to investigate the effectiveness of computerized automated techniques that include machine learning algorithms for identifying stress, anxiety, and depression mental disorder. The proposed paper reviews the machine learning-based algorithms applied over datasets containing questionnaires, audio, video, etc., to recognize sad details. During the review process, the proposed study found that artificial intelligence and machine learning techniques are well recommended and widely utilized in most of the existing literature for measuring psychological disorders. The various machine learning-based algorithms are applied over datasets containing questionnaires, audio, video, etc., to recognize sad details. There has been continuous monitoring for the body symptoms established in the various existing literature to identify psychological states. The present review reveals the study of excellence and competence of machine learning techniques in detecting psychological disorders' stress, depression, and anxiety parameters. This paper shows a systematic review of some existing computer vision-based models with their merits and demerits.

Evaluation of psychological stress, cortisol awakening response, and heart rate variability in patients with chronic prostatitis/chronic pelvic pain syndrome complicated by lower urinary tract symptoms and erectile dysfunction

BACKGROUND

Mental stress and imbalance of its two neural stress systems, the autonomic nervous system (ANS) and the hypothalamic-pituitary-adrenal (HPA) axis, are associated with chronic prostatitis/chronic pelvic pain syndrome (CP/CPPS) and erectile dysfunction (ED). However, the comprehensive analyses of psychological stress and stress systems are under-investigated, particularly in CP/CPPS patients complicated by lower urinary tract symptoms (LUTS) and ED.

MATERIALS AND METHODS

Participants were 95 patients in CP/CPPS+ED group, 290 patients in CP/CPPS group, 124 patients in ED group and 52 healthy men in control group. The National Institutes of Health Chronic Prostatitis Symptom Index (NIH-CPSI), the International Index of Erectile Function-5 (IIEF-5) and the International Prostate Symptom Score (IPSS) were used for assessing the disease severity of CP/CPPS, LUTS and ED. Psychometric self-report questionnaires including the Beck Anxiety Inventory (BAI), Perceived Stress Scale (PSS), Type A Personality Test (TAPT) and Symptom Checklist 90 (SCL-90) were completed for distress from physical symptoms. Twenty-five subjects per group were randomly selected for further investigating the changes of the HPA axis and ANS. Saliva samples were taken on 3 consecutive days at 8 specific times with strict reference to time of morning awakening for evaluation of free cortisol. Heart rate variability (HRV) as marker of the ANS was measured using 24 h electrocardiography, and time-and frequency-domain variables were analyzed.

RESULTS

The BAI and SCL-90 scores were significantly higher in the CP/CPPS+ED, CP/CPPS and ED groups compared with the control group (p < 0.01). The PSS scores of both groups with ED were significantly higher than the control group (p < 0.01). Compared with the CP/CPPS group, the differences of PSS, SCL-90 and TAPT scores were statistically significant in CP/CPPS+ED patients (p < 0.01). The IPSS scores were shown to have significantly positive correlations with BAI (r = 0.32, p < 0.0001), PSS (r = 0.18, p < 0.01) and SCL-90 (r = 0.19, p < 0.01) in the CP/CPPS patients. However, in all subjects, the IIEF-5 scores were shown to have significantly negative correlations with BAI (r = -0.17，p < 0.001), PSS (r = -0.25，p < 0.0001), SCL-90 (r = -0.20，p < 0.001) and quality of life score in NIH-CPSI (r = -0.14，p = 0.0075). Cortisol awakening response (CAR) parameters and diurnal cortisol levels did not significantly vary between the four groups. Time-dependent parameters of HRV also did not differ significantly across groups. In the frequency domain analysis, low frequency (LF) was significantly lower in ED patients when compared with CP/CPPS+ED patients (p = 0.044) and healthy controls (p = 0.005), high frequency (HF) power was significantly higher in healthy controls compared to patients with ED (p < 0.001), CP/CPPS (p < 0.001) and CP/CPPS+ED (p < 0.001), and the CP/CPPS+ED group had significantly higher LF/HF ratio than the control group (p = 0.001).

CONCLUSION

CP/CPPS and ED patients score exceedingly high on most psychosocial variables. The symptom scores of LUTS and ED positively correlate with the severity of psychological stress. Our findings also suggest that the ANS sympathovagal imbalance is associated with ED and LUTS in CP/CPPS, whereas HPA axis activity is not.