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The purpose of this study was to evaluate the psychosocial impact during the current epidemic situation of COVID-19 in Pakistan.

A total of 1,149 respondents were recruited in the study. Mental health status and psychological impact of COVID-19 outbreak were measured by impact of events scale–revised (IES-R) instrument and depression, anxiety and stress scales (DASS-21), respectively.

Results of IES-R revealed moderate or severe psychological impact in 13.05% respondents (score > 33). DAAS score revealed that severe and extremely severe depression (score: 21–42), anxiety (score: 15–42) and stress (score: 27–42) were reported in 6.35%, 6.87% and 2.78% respondents, respectively. Higher levels of stress, anxiety and depression were recorded in female gender, student, medical professionals, farmer and daily wages employed, exhibiting significant (p < 0.05) association with psychological impact of the COVID-19 outbreak. Majority of respondents received increased support, shared feeling and family care.

Mild to moderate psychological impact on mental health status was recorded in this study, which enables further planning and opportunities for health authorities to design psychological interventions for the improvement of negative psychological impact of COVID-19 epidemic in vulnerable groups.

Depression is a mental health problem characterized by a persistent sense of sadness and loss of interest. EEG signals are regarded as the most appropriate instruments for diagnosing depression because they reflect the operating status of the human brain. The purpose of this study is the early detection of depression among people using EEG signals.

(i) Artifacts are removed by filtering and linear and non-linear features are extracted; (ii) feature scaling is done using a standard scalar while principal component analysis (PCA) is used for feature reduction; (iii) the linear, non-linear and combination of both (only for those whose accuracy is highest) are taken for further analysis where some ML and DL classifiers are applied for the classification of depression; and (iv) in this study, total 15 distinct ML and DL methods, including KNN, SVM, bagging SVM, RF, GB, Extreme Gradient Boosting, MNB, Adaboost, Bagging RF, BootAgg, Gaussian NB, RNN, 1DCNN, RBFNN and LSTM, that have been effectively utilized as classifiers to handle a variety of real-world issues.

1. Among all, alpha, alpha asymmetry, gamma and gamma asymmetry give the best results in linear features, while RWE, DFA, CD and AE give the best results in non-linear feature. 2. In the linear features, gamma and alpha asymmetry have given 99.98% accuracy for Bagging RF, while gamma asymmetry has given 99.98% accuracy for BootAgg. 3. For non-linear features, it has been shown 99.84% of accuracy for RWE and DFA in RF, 99.97% accuracy for DFA in XGBoost and 99.94% accuracy for RWE in BootAgg. 4. By using DL, in linear features, gamma asymmetry has given more than 96% accuracy in RNN and 91% accuracy in LSTM and for non-linear features, 89% accuracy has been achieved for CD and AE in LSTM. 5. By combining linear and non-linear features, the highest accuracy was achieved in Bagging RF (98.50%) gamma asymmetry + RWE. In DL, Alpha + RWE, Gamma asymmetry + CD and gamma asymmetry + RWE have achieved 98% accuracy in LSTM.

A novel dataset was collected from the Central Institute of Psychiatry (CIP), Ranchi which was recorded using a 128-channels whereas major previous studies used fewer channels; the details of the study participants are summarized and a model is developed for statistical analysis using N-way ANOVA; artifacts are removed by high and low pass filtering of epoch data followed by re-referencing and independent component analysis for noise removal; linear features, namely, band power and interhemispheric asymmetry and non-linear features, namely, relative wavelet energy, wavelet entropy, Approximate entropy, sample entropy, detrended fluctuation analysis and correlation dimension are extracted; this model utilizes Epoch (213,072) for 5 s EEG data, which allows the model to train for longer, thereby increasing the efficiency of classifiers. Features scaling is done using a standard scalar rather than normalization because it helps increase the accuracy of the models (especially for deep learning algorithms) while PCA is used for feature reduction; the linear, non-linear and combination of both features are taken for extensive analysis in conjunction with ML and DL classifiers for the classification of depression. The combination of linear and non-linear features (only for those whose accuracy is highest) is used for the best detection results.

This study aims to evaluate the effect of Alpha-Stim Anxiety, Insomnia and Depression (AID) cranial electrotherapy stimulation (CES) on anxiety, depression and health-related quality of life for primary care social prescribing service patients with anxiety symptoms.

Open-label patient cohort design with no control group. A total of 33 adult patients (average age 42 years) completed six weeks of Alpha-Stim AID use. Pre- and post-intervention assessment with participant self-report measures: Patient Health Questionnaire (PHQ-9), Generalised Anxiety Disorder (GAD-7) and European Quality of Life Five Dimension (EQ-5D-5L).

Reliable improvement and remission rates, respectively, were 53.39% and 33.3% for GAD-7; 46.7% and 29.5% for PHQ-9. There was a significant improvement in GAD-7 and PHQ-9 with large effect sizes. EQ-5D-5L results showed significant improvements in health-related quality of life. Perceived quality of life increased by 0.17 on the health index score, with the intervention adding 1.68 quality-adjusted life years (QALYs).

Alpha-Stim AID can be delivered through a primary health-care social prescribing service and most patients will use as prescribed and complete treatment course. Alpha-Stim AID CES may be an effective anxiety and depression treatment for people with anxiety symptoms. The widespread roll-out of Alpha-Stim AID in health-care systems should be considered.

To the best of the authors’ knowledge, this is the first study to respond to the UK’s National Institute for Health and Care (NICE) request for the collection of real-world data to understand better Alpha-Stim AID in relation to people’s treatment uptake, response rates and treatment completion rates (NICE, 2021).

The purpose of this study is to examine the mental health challenges of residents of Barbados during the COVID-19 pandemic and the relationships between residents’ demographics, COVID-19 perceptions and mental health outcomes.

The study surveyed 450 predominantly Black Caribbean respondents to examine their mental ill-health on the various dimensions of the General Health Questionnaire (GHQ)-28 measure and the relationships with demographics and COVID-19 perceptions.

Confirmatory factor analysis confirmed the four-factor model solution of GHQ-28 over the single factor solution. Barbadians were generally mild in their mental ill-health on the somatic symptoms, social dysfunction and severe depression dimensions but were at least moderately strained on the anxiety and insomnia dimensions. Younger and unemployed Barbadian respondents reported more adverse mental health outcomes, and perceived severity of COVID-19 infection significantly predicted three of the four dimensions of mental distress (excluding severe depression).

The study used a cross-sectional self-report survey research design which does not permit causal inferences. Further research is advised to ascertain the longitudinal effects of COVID-19 perceptions over time on mental health outcomes.

The study’s findings suggest the need for nation-wide, multi-stakeholder interventions or approaches in responding mental health challenges of the population during this crisis.

The study was the first to examine the mental health outcomes, using GHQ-28, in a small Caribbean country – which represents an underserved space in mental health research. It is the first to empirically examine the relationship between COVID-19 perceptions of Afro-Caribbean people in this region and their resultant mental health outcomes.

This study aims to investigate the impact of job loss on the mental health of individuals in Tunisia during the COVID-19 crisis.

In this research, the authors use the counterfactual decomposition technique and the potential outcome approach. In the first part, the authors calculated mental health indicators for all individuals included in the sample based on the World Health Organization-5 items. The individuals were then grouped into two subpopulations: the first group included those who had lost their jobs and the second group included individuals whose status in the labor market had remained unchanged. In the second part, the authors used the Blinder and Oaxaca decomposition to explain the mean difference in the mental health scores between the two groups and determine the factors contributing to this difference.

The empirical results identified symptoms of depressed mood, decreased energy and loss of interest in several individuals. Based on these three symptoms, the authors were able to classify individuals into three types of depression: mild, moderate and severe. In addition, it appeared that job loss had significantly contributed to the worsening mental health of the individuals.

Although the psychological impact of the COVID-19 outbreak among health-care professionals has been the subject of other studies in health literature on Tunisia, to the best of the authors’ knowledge, no research has addressed the impact of job loss on the mental health of Tunisian workers. Thus, this study fills this gap in the literature.

The study aims to identify the predictors of depression and anxiety among carers of hospitalized patients with mental illness in Eradah Complex for Mental Health Hospital.

A descriptive correlational study design was conducted using a convenient sample of family carers of patients with mental illness (N = 216). The study used the Beck Depression Inventory and Anxiety Inventory scales.

The results of regression models revealed that the socio-demographic characteristics of the family carers showed that age is a statistically significant predictor of family carers depression and anxiety scores. In addition, the age of the family carers explained 36% of the variance in the family carers depression and anxiety scores, while marital status explained 64% of the total variance in the family carers’ depression and anxiety scores. Furthermore, having received support in caring significantly predicted depression and anxiety scores, and this was the case for occupation status and being diagnosed with any form of chronic illness.

Based on the findings of this study, the authors opine that evaluations of carers’ cognitive strategies and social support are needed to determine the risk of depression in carers of mental patients.

This study is the one of the limited studies conducted in Saudi Arabia to identify predictor of depression and anxiety among caregivers of hospitalized patients with mental illness. The study has used a validated scales to assess the main study outcomes.

Nutrition Bio Shield (NBS) supplement is a natural product that is processed from whole wheat grains. This study aims to determine its effects on depression, anxiety, stress and food craving in women with depression and obesity in a double-blind randomized clinical trial.

Fifty-six eligible clients with body mass index ≥ 25 and mild or moderate depression signed the informed consent form. They were randomly assigned to receive daily 5 g of NBS or placebo. The assessments included the depression, anxiety and stress-21 questionnaire, food craving questionnaire, visual analogue scale for appetite, precise anthropometric measurements and body composition analyses. The assessments were conducted at the baseline and repeated after four and eight weeks. One month after the study completion, the participants’ weight was assessed. The authors analyzed the data by independent sample t-test, repeated measures analysis of variance and multivariate analyses of covariance (MANCOVA).

At the baseline, no significant differences were observed between the groups regarding the main and demographic variables. After four weeks, stress reduced significantly in the NBS group (p = 0.04), and after eight weeks, anxiety (p = 0.02), stress (p = 0.008) and food craving (p = 0.05) reduced significantly in the NBS group compared with the placebo. After controlling for the demographic variables and baseline measurements, MANCOVA model revealed a significant effect of NBS in reducing anxiety (Eta-squared = 0.28; p = 0.001) and stress (Eta-squared = 0.19; p = 0.009). Fisher’s exact test showed no significant difference regarding side effects between NBS and placebo (p = 0.47).

NBS supplement is a patent and natural product that is processed from whole wheat grains. This product was efficient in reducing stress and anxiety after controlling for demographic variables and baseline measurements compared with the placebo and was safe.

This study aimed to examine the mental health information entities and associations between the biomedical, psychological and social domains of bipolar disorder (BD) by analyzing social media data and scientific literature.

Reddit posts and full-text papers from PubMed Central (PMC) were collected. The text analysis was used to create a psychological dictionary. The text mining tools were applied to extract BD entities and their relationships in the datasets using a dictionary- and rule-based approach. Lastly, social network analysis and visualization were employed to view the associations.

Mental health information on the drug side effects entity was detected frequently in both datasets. In the affective category, the most frequent entities were “depressed” and “severe” in the social media and PMC data, respectively. The social and personal concerns entities that related to friends, family, self-attitude and economy were found repeatedly in the Reddit data. The relationships between the biomedical and psychological processes, “afraid” and “Lithium” and “schizophrenia” and “suicidal,” were identified often in the social media and PMC data, respectively.

Mental health information has been increasingly sought-after, and BD is a mental illness with complicated factors in the clinical picture. This paper has made an original contribution to comprehending the biological, psychological and social factors of BD. Importantly, these results have highlighted the benefit of mental health informatics that can be analyzed in the laboratory and social media domains.

This study aimed to analyze the effect of Trauma-Focused Cognitive Behavior Therapy (TF-CBT) on the depression level and quality of life of the elderly in an earthquake-affected district of North Lombok Regency, Indonesia.

A Randomized Controlled Trial (RCT) with a population of two elderly groups living in an earthquake-affected district was used in this study. The intervention comprised giving TF-CBT. There were three research instruments applied to determine the variables, namely, the Clinician-Administered PTSD Scale (CAPS-5), the Geriatric Depression Scale 15 (GDS 15) and the World Health Organization Quality of Life-BREF (WHOQOL-BREF). All instruments were adopted and translated using back translation to Bahasa Indonesia, which is appropriate at the suggestion of the WHO. To investigate the effect of the intervention, we used hierarchical linear models (HLM) with intent-to-treat analysis. The patent parameter effect was tested using the Wald test (t-test) with a confidence Interval of 95 per cent.

The final analysis applied CAPS-5 and showed that there was a decrease in the PTSD of the respondents, which was down to only 8 (17.8 per cent) in the post-test. The same situation happened for the depression variable (2.8 per cent) after it was assessed using GDS-15C. The Quality of life (WHOQoL-BREF) variable was divided into Physical (50.7), Psychological (57.1), Social (53.6) and Environmental (45.7). These components show there to be a significant result in terms of improving the quality of life of the elderly victims of the earthquake. The finding highlights that applying TF-CBT in the elderly population can significantly drop post-traumatic stress disorder and depression level and enhanced quality of life.

The intervention decreased the depression level and improved the quality of life of the elderly as found in the six- week follow-up. Longer training and integration with the structured local wisdom could be necessary to better address the mental health of the elderly affected by the earthquake. Moreover, strengthening the role of the family as the primary caregiver is required to improve the outcome.

This is the first study that has attempted to use TF-CBT as a method of treatment for the elderly to decrease their depression and to increase quality of life among the Indonesian elderly who have experienced an earthquake. This paper provides knowledge on the effectiveness of TF-CBT that can be used by therapists to treat depression problems suffered by the elderly in a post-disaster area.