International PRISMA scoping review to understand mental health interventions for depression in COVID-19 patients

Explainable Depression Classification Based on EEG Feature Selection From Audio Stimuli

With the development of affective computing and Artificial Intelligence (AI) technologies, Electroencephalogram (EEG)-based depression detection methods have been widely proposed. However, existing studies have mostly focused on the accuracy of depression recognition, ignoring the association between features and models. Additionally, there is a lack of research on the contribution of different features to depression recognition. To this end, this study introduces an innovative approach to depression detection using EEG data, integrating Ant-Lion Optimization (ALO) and Multi-Agent Reinforcement Learning (MARL) for feature fusion analysis. The inclusion of Explainable Artificial Intelligence (XAI) methods enhances the explainability of the model's features. The Time-Delay Embedded Hidden Markov Model (TDE-HMM) is employed to infer internal brain states during depression, triggered by audio stimulation. The ALO-MARL algorithm, combined with hyper-parameter optimization of the XGBoost classifier, achieves high accuracy (93.69%), sensitivity (88.60%), specificity (97.08%), and F1-score (91.82%) on a auditory stimulus-evoked three-channel EEG dataset. The results suggest that this approach outperforms state-of-the-art feature selection methods for depression recognition on this dataset, and XAI elucidates the critical impact of the minimum value of Power Spectral Density (PSD), Sample Entropy (SampEn), and Rényi Entropy (Ren) on depression recognition. The study also explores dynamic brain state transitions revealed by audio stimuli, providing insights for the clinical application of AI algorithms in depression recognition.

Guiding future research on psychological interventions in people with COVID-19 and post COVID syndrome and comorbid emotional disorders based on a systematic review

Objective

The COVID-19 pandemic has been emotionally challenging for the entire population and especially for people who contracted the illness. This systematic review summarizes psychological interventions implemented in COVID-19 and long COVID-19 patients who presented comorbid emotional disorders.

Methods and measures

3,839 articles were identified in 6 databases and 43 of them were included in this work. Two independent researchers selected the articles and assessed their quality.

Results

2,359 adults were included in this review. Severity of COVID-19 symptoms ranged from asymptomatic to hospitalized patients; only 3 studies included long COVID-19 populations. Similar number of randomized controlled studies (n = 15) and case studies (n = 14) were found. Emotional disorders were anxiety and/or depressive symptoms (n = 39) and the psychological intervention most represented had a cognitive behavioral approach (n = 10). Length of psychological programs ranged from 1-5 sessions (n = 6) to 16 appointments (n = 2). Some programs were distributed on a daily (n = 4) or weekly basis (n = 2), but other proposed several sessions a week (n = 4). Short (5-10 min, n = 4) and long sessions (60-90 min, n = 3) are proposed. Most interventions were supported by the use of technologies (n = 18). Important risk of bias was present in several studies.

Conclusion

Promising results in the reduction of depressive, anxiety and related disorders have been found. However, important limitations in current psychological interventions were detected (i.e., duration, format, length, and efficacy of interventions were not consistently established across investigations). The results derived from our work may help to understand clinical practices in the context of pandemics and could guide future efforts to manage emotional suffering in COVID-19 patients. A stepped model of care could help to determine the dosage, length and format of delivery for each patient.Systematic review registration: PROSPERO 2022 CRD42022367227. Available from: https://www.crd.york.ac.uk/prospero/display_record.php?ID=CRD42022367227.

Mindfulness Interventions and Surveys as Tools for Positive Emotional Regulation During COVID-19: A Scoping Review

Objectives

The COVID-19 pandemic has caused high mortality rates worldwide, as well as consequent psychological and physical stress. The present study aimed to review the main existing scientific research studies conducted since the onset of the COVID-19 that have used mindfulness-based interventions (MBIs) as tools for emotional regulation, aiming to improve individuals’ ability to cope with general stress caused by pandemic periods and their consequences (e.g., contagion, confinement, loss of loved ones or job stability) especially related with anxiety, stress, depression, or emotional dysregulation.

Method

To this aim, six databases (i.e., PubMed, Medline, Embase, Scopus, Web of Science, and Science Direct) were consulted and analyzed following PRISMA-Sc guidelines.

Results

Of the 16 studies selected, 7 are clinical trials that used MBIs, and 9 are online surveys in which mindfulness and emotional regulation variables were assessed to explore their interrelations. Generally, the analysis suggested that the cultivation of MBI strategies for treating anxiety and depression during COVID-19 confinement periods resulted in improved psychological well-being.

Conclusions

MBI techniques can be considered useful intervention tools in current and future worldwide changing situations, in which personal development and resilience should be considered an urgent issue for both educational and preventive health practices. Conversely, there are also some limitations that arose from the field of MBI research that hopefully might be addressed in future research (such as the diversity of intervention techniques used across studies).

Pre registration

This study is not preregistered.

Unified Protocol for the transdiagnostic treatment of emotional disorders in people with post COVID-19 condition: study protocol for a multiple baseline n-of-1 trial

Background

Post COVID-19 syndrome, defined as the persistence of COVID-19 symptoms beyond 3 months, is associated with a high emotional burden. Post COVID-19 patients frequently present comorbid anxiety, depressive and related disorders (emotional disorders, EDs) which have an important impact on their quality of life. Unfortunately, psychological interventions to manage these EDs are rarely provided to post COVID-19 patients. Also importantly, most psychological interventions do not address comorbidity, namely simultaneous EDs present in COVID-19 patients. This study will explore the clinical utility and acceptability of a protocol-based cognitive-behavioral therapy called the Unified Protocol for the transdiagnostic treatment of EDs in patients suffering post COVID-19 condition.

Methods

A multiple baseline n-of-1 trial will be used, as it allows participants to be their own comparison control. Sample will be composed of 60 patients diagnosed with post COVID-19 conditions and comorbid EDs from three Spanish hospitals. After meeting the eligibility criteria, participants will answer the pre-assessment protocol and then they will be randomly assigned to three different baseline conditions (6, 8, or 10 days of assessments before the intervention). Participants and professionals will be unblinded to participants' allocation. Once the baseline assessment has been completed, participants will receive the online psychological individual intervention through video-calls. The Unified Protocol intervention will comprise 8 sessions of a 1 h duration each. After the intervention, participants will answer the post-assessment protocol. Additional follow-up assessments will be conducted at one, three, six, and twelve months after the intervention. Primary outcomes will be anxiety and depressive symptoms. Secondary outcomes include quality of life, emotion dysregulation, distress tolerance, and satisfaction with the programme. Data analyses will include between-group and within-group differences and visual analysis of patients' progress.

Discussion

Results from this study will be disseminated in scientific journals. These findings may help to provide valuable information in the implementation of psychological interventions for patients suffering post COVID-19 conditions.

Clinical trial registration

https://clinicaltrials.gov, identifier (NCT05581277).

Identification of Paddy Croplands and Its Stages Using Remote Sensors: A Systematic Review

Rice is a staple food that feeds nearly half of the world's population. With the population of our planet expected to keep growing, it is crucial to carry out accurate mapping, monitoring, and assessments since these could significantly impact food security, climate change, spatial planning, and land management. Using the PRISMA systematic review protocol, this article identified and selected 122 scientific articles (journals papers and conference proceedings) addressing different remote sensing-based methodologies to map paddy croplands, published between 2010 and October 2022. This analysis includes full coverage of the mapping of rice paddies and their various stages of crop maturity. This review paper classifies the methods based on the data source: (a) multispectral (62%), (b) multisource (20%), and (c) radar (18%). Furthermore, it analyses the impact of machine learning on those methodologies and the most common algorithms used. We found that MODIS (28%), Sentinel-2 (18%), Sentinel-1 (15%), and Landsat-8 (11%) were the most used sensors. The impact of Sentinel-1 on multisource solutions is also increasing due to the potential of backscatter information to determine textures in different stages and decrease cloud cover constraints. The preferred solutions include phenology algorithms via the use of vegetation indices, setting thresholds, or applying machine learning algorithms to classify images. In terms of machine learning algorithms, random forest is the most used (17 times), followed by support vector machine (12 times) and isodata (7 times). With the continuous development of technology and computing, it is expected that solutions such as multisource solutions will emerge more frequently and cover larger areas in different locations and at a higher resolution. In addition, the continuous improvement of cloud detection algorithms will positively impact multispectral solutions.

Psychological treatments for the mental health symptoms among individuals infected with COVID-19: a scoping review protocol

INTRODUCTION

Mental health symptoms such as depression, anxiety and sleep problems are commonly observed in individuals suffering from acute COVID-19 infection to post-COVID-19 syndrome. Studies have provided preliminary evidence for the efficacies of cognitive behavioural therapy, mindfulness-based interventions, acceptance and commitment therapy, and many other treatments for this population. Although there have been attempts to synthesise the literature on these psychological interventions, previous reviews have been limited in terms of the sources, symptoms and interventions that they included. Furthermore, most studies reviewed were conducted in early 2020, when COVID-19 had only recently been classified as a global pandemic. Since then, substantial research has been conducted. As such, we sought to provide an updated synthesis of the available evidence of treatments for the range of mental health symptoms associated with COVID-19.

METHODS AND ANALYSIS

This scoping review protocol was developed according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses Extension for Scoping Reviews. Systematic searches were carried out on scientific databases (PubMed, Web of Science, PsycINFO and Scopus) and clinical trial registries (ClinicalTrials.gov, WHO ICTRP, EU Clinical Trials Register and Cochrane Central Register of Controlled Trials) to identify studies that have or will assess the efficacy or any aspects of psychological treatment for acute to post-COVID-19 syndrome. The search was conducted on 14 October 2022 and identified 17 855 potentially eligible sources/studies published since 1 January 2020 (duplicates removed). Six investigators will independently carry out titles and abstract screening, full-text screening and data charting and the results will be summarised using descriptive statistics and narrative synthesis.

ETHICS AND DISSEMINATION

Ethical approval is not required for this review. The results will be disseminated through a peer-reviewed journal, conference presentations and/or academic newspapers. This scoping review has been registered with Open Science Framework (https://osf.io/wvr5t).

Primary Mental Health Care in a New Era

Clinical experience and scientific studies highlight the pivotal role that primary health care services have and should have as a gateway to the health care system and as a first point of contact for patients with mental disorders, particularly-but not exclusively-for patients with a disorder in the spectrum of common mental disorders [...].