Avicenna Journal of Neuro Psycho Physiology
Volume:10 Issue: 1, Feb 2023

Some non-ordinary spiritual experiences cannot be explained on a purely materialistic basis since the materialistic model could only partially explain them. The four main groups of such phenomena are: (I) Mediumship: why do some texts have accurate, verifiable information in controlled and blind studies that exclude fraud or coincidence? (II) Memories of past lives: how could some reports have precise verifiable matches, sometimes even with birthmarks from the previous persona? (III) Near-death experiences: how could a few people remember actual events that occurred in the resuscitation period when brain activity was absent? (IV) End-of-life experiences: how come people with dementia due to irreversible brain damage can experience paradoxical lucidity phenomenon? There are aspects in these phenomena that point to the survival of consciousness after death, coming from rigorous research published in peer-reviewed journals. Therefore, science needs a paradigm shift to accommodate the idea of consciousness as an element independent of the brain.

Developing a valid and reliable questionnaire is an essential step in field studies. The present study aimed to evaluate the psychometric properties of the socio-cognitive determinants of water intake questionnaire behaviors among patients with kidney stones in the west of Iran.

Construct items were elicited from interviewing patients with kidney stones, experts, and socio-cognitive items pool-related similar questionnaires. Internal consistency, as well as face, content, and construct validity, were evaluated. Data were analyzed in SPSS (version 20.0). Based on Eigenvalues of ≥ 1.00 and factor loadings of ≥ 0.40, five determinants were extracted.

The calculated Kaiser-Meyer-Olkin (KMO) value was 0.697. The socio-cognitive determinants of water intake questionnaires were found to have acceptable internal consistency (Cronbach alpha of determinants between 0.65-0.85), and the theoretical assumptions for face, content, and construct validities were confirmed. The Intra-class Correlation Coefficient (ICC) of socio-cognitive determinants was high (ICC between 0.810 - 0.911). In general, the five studied socio-cognitive determinants explained 73.83% of the variance in the proposed model.

The socio-cognitive determinants of the water intake questionnaire were revealed to have an acceptable psychometric evaluation. The questionnaire could be used to predict or explain water intake behavior in order to develop programs to increase water intake behavior among patients with kidney stones.

Electroencephalography (EEG) analysis is an important tool for neuroscience, brain-computer interface studies, and biomedical studies. The primary purpose of Brain-Computer Interface (BCI) studies is to establish communication between disabled individuals, other individuals, and machines with brain signals. Interpreting and classifying the brain's response during different cognitive tasks will contribute to brain-computer interface studies. Therefore, in this study, five cognitive tasks were classified from EEG signals.

In this study, five neuropsychological tests (Öktem Verbal Memory Processes Test, WMS-R Visual Memory Subtest, Digit Span Test, Corsi Block Test, and Stroop Test) were administered to 30 healthy individuals. The tests assess the volunteers' abilities in verbal memory, visual memory, attention, concentration, working memory, and reaction time. The EEG signals were recorded while the tests were administered to the volunteers. The tests were classified using two different deep learning algorithms, 1D Convolutional Neural Networks (CNN) and Long Short-Term Memory (LSTM), from the recorded EEG signals.

When the success of the tests was evaluated, classification success was achieved with an accuracy of 88.53% in the CNN deep learning algorithm and 89.80% in the LSTM deep algorithm. Precision, recall, and F1-score values for CNN were calculated at 0.88, 0.87, and 0.87, respectively, while precision, recall, and f1-score values for the LSTM network were obtained at 0.90, 0.89, and 0.89.

Following the findings of the present study, five different cognitive tasks were able to be classified with high accuracy from EEG signals using deep learning algorithms.

Cognitive-Behavioral Therapy (CBT) is used as one of the main treatments for panic disorder, yet fewer people with panic disorder receive medication-based treatment. The present study aimed to determine the difference between the effectiveness of cognitive-behavioral therapy and a combination of cognitive-behavioral therapy and medication in patients with panic attacks who have recovered from Covid-19 in Ramsar, Iran.

This quasi-experimental study was conducted based on a pre-test and post-test design with a control group. The statistical population included patients who were referred to hospitals and medical centers in Ramsar in 2022. A total of 30 cases were randomly selected using the Albanian Panic and Phobia Questionnaire and structural clinical interview. One group received 12 sessions of CBT, one group received a combination of medication and CBT, and the other group received no training. The obtained data were analyzed using the statistical methods of univariate and multivariate analysis of covariance.

The significant difference in the post-test between the CBT and the control group (P<0.001) in the variable of the combination of CBT and medication with the control group, there is a significant difference in the post-test  (P<0.001). The results of the post hoc test demonstrated that the effectiveness of the combination of CBT and medication was significantly higher than that of the CBT and the control group (P<0.001(.

As evidenced by the results of this study, combined CBT and medication in the short term effectively improved and reduced panic symptoms of patients with panic disorder.

Despite an overwhelming disease burden, nursing shortages are evident in Sub-Saharan Africa, with the potential for significant healthcare crises. Nurses face increased work demands and chronic stress due to a skilled personnel shortage, which may lead to stress. The present study aimed to examine chronic stress and its correlates among nurses in central Uganda.

The 12-item Short Form Survey (SF-12) for the assessment of chronic stress among nurses, a validated and standardized tool, was used in this cross-sectional study in 2022. For explanatory analysis, the items were combined with dichotomous variables reflecting predictors of chronic stress. These items were used to create dichotomous variables denoting frequent and demanding challenges for exploratory analysis. The relationship between the variables and high levels of chronic stress was investigated using a multivariate logistic regression model.

Based on the findings, the majority, 485 (76.0%), had chronic stress. The results indicate that the correlates of chronic stress among participants were widowhood (AOR: 0.040; 95% CI: 0.013-0.127; P= <0.001), being worried about looming deadlines (aOR: 0.003; 95% CI: 0.001-0.023; P = <0.001), long working hours (AOR: 0.283; 95% CI: 0.159-0.504; p=<0.001), insufficient job control (AOR: 0.304; 95% CI: 0.127-0.727; P = 0.007), and inadequate rewards (AOR: 2.554; 95% CI: 1.170-5.574; P = 0.019).

According to our findings, three in four nurses in central Uganda suffer from chronic stress. This can exert a negative impact on their overall well-being and caring behaviors. Chronic stress was associated with widowhood, a looming deadline, long working hours, insufficient job control, and inadequate rewards. It is critical to adapt interventions, such as hiring additional nurses, to reduce workload and ensure adequate rest periods.

Breast cancer is linked to neuropsychiatric conditions, particularly depression, which lowers life expectancy. Studies from Sub-Saharan Africa, however, have revealed conflicting prevalence rates of depression.

To assess the combined prevalence of breast cancer-related depression among patients in Sub-Saharan Africa.

 The following search terms—depression, depressive disorders, breast cancer, mammary cancer, mammary adenocarcinoma and breast carcinoma, and Sub-Saharan African—were used to conduct a systematic search for English articles on depression published in PubMed, Scopus, Web of Science, African Journal Online, and Google Scholar. A meta-command was used to combine the results of different studies on depression linked to breast cancer through a random effects model at a 95% confidence interval in Stata software (version 17).

After the elimination of duplicates, 9,272 articles were still found after the electronic search yielded 12051 results. A number of 19 articles were still available after abstract and title screening, and they underwent full-text screening. A number of 10 articles were removed for a variety of reasons, including the lack of the full text (n=2), incorrect publication type (n=2), and not reporting the full outcome of interest (n=6). In Sub-Saharan Africa, the combined prevalence of breast cancer patients was 60%. (95CI, 0.51-0.69). The prevalence rates of depression among breast cancer patients in East Africa, South Africa, and West Africa were reported as 64% (95CI, 0.51-0.75),  60% (95CI, 0.53-0.67), and 55%. (95CI, 0.36-0.73), respectively. 

In Sub-Saharan Africa, about 6 in 10 cancer patients experience depression. Since depression negatively affects the quality of life, it is important to properly diagnose depression in order to treat it effectively with the fewest possible side effects.