Machine Learning Model for Computer-Aided Depression Screening among Young Adults Using Wireless EEG Headset.

Depression is a disorder that if not treated can hamper the quality of life. EEG has shown great promise in detecting depressed individuals from depression control individuals. It overcomes the limitations of traditional questionnaire-based methods. In this study, a machine learning-based method for detecting depression among young adults using EEG data recorded by the wireless headset is proposed. For this reason, EEG data has been recorded using an Emotiv Epoc+ headset. A total of 32 young adults participated and the PHQ9 screening tool was used to identify depressed participants. Features such as skewness, kurtosis, variance, Hjorth parameters, Shannon entropy, and Log energy entropy from 1 to 5 sec data filtered at different band frequencies were applied to KNN and SVM classifiers with different kernels. At AB band (8-30 Hz) frequency, 98.43 ± 0.15% accuracy was achieved by extracting Hjorth parameters, Shannon entropy, and Log energy entropy from 5 sec samples with a 5-fold CV using a KNN classifier. And with the same features and classifier overall accuracy = 98.10 ± 0.11, NPV = 0.977, precision = 0.984, sensitivity = 0.984, specificity = 0.976, and F1 score = 0.984 was achieved after splitting the data to 70/30 ratio for training and testing with 5-fold CV. From the findings, it can be concluded that EEG data from an Emotiv headset can be used to detect depression with the proposed method.

The impact of the COVID-19 pandemic on depression in community-dwelling older adults: a prospective cohort study.

BACKGROUND: There are growing concerns about the impact of the COVID-19 pandemic on the mental health of older adults. We examined the effect of the pandemic on the risk of depression in older adults. METHODS: We analyzed data from the prospective cohort study of Korean older adults, which has been followed every 2 years. Among the 2308 participants who completed both the third and the fourth follow-up assessments, 58.4% completed their fourth follow-up before the outbreak of COVID-19 and the rest completed it during the pandemic. We conducted face-to-face diagnostic interviews using Mini International Neuropsychiatric Interview and used Geriatric Depression Scale. We performed generalized estimating equations and logistic regression analyses. RESULTS: The COVID-19 pandemic was associated with increased depressive symptoms in older adults [b (standard error) = 0.42 (0.20), p = 0.040] and a doubling of the risk for incident depressive disorder even in euthymic older adults without a history of depression (odds ratio = 2.44, 95% confidence interval 1.18-5.02, p = 0.016). Less social activities, which was associated with the risk of depressive disorder before the pandemic, was not associated with the risk of depressive disorder during the pandemic. However, less family gatherings, which was not associated with the risk of depressive disorder before the pandemic, was associated with the doubled risk of depressive disorder during the pandemic. CONCLUSIONS: The COVID-19 pandemic significantly influences the risk of late-life depression in the community. Older adults with a lack of family gatherings may be particularly vulnerable.

Association of depressive symptoms with Geriatric Locomotive Function Scale score in community-dwelling older adults living in the state of emergency.

BACKGROUND: Under the state of emergency, it has been reported that the amount of physical activity among community-dwelling older adults has decreased significantly due to refraining from going out, and there are strong concerns about the Geriatric Locomotive Function Scale and deterioration of mental health. Therefore, this study aimed to investigate whether the depressive state before the coronavirus disease 2019 (COVID-19) pandemic affected the 25-Geriatric Locomotive (GLFS) score during the COVID-19 pandemic among community-dwelling older adults. METHODS: The participants were 194 community-dwelling older adults (45 men, 149 women) with an average age of 75.5 ± 5.5 years who responded to a self-administered survey conducted three times (preliminary, second, and third) from before the 2018 COVID-19 pandemic to March 2021. Individuals with a score of ≥ 10 on the Geriatric Depression Scale 15 (GDS 15) were excluded. The survey items included the 25-question Geriatric Locomotive Function Scale (GLFS25), GDS 15, and other basic attributes. Those with scores of 5 to 9 on the GDS 15 and those with scores of 0 to 4 were assigned to the depressive symptoms (DS) group and the non-DS group, respectively. Statistical analysis was performed using two-way analysis of variance. The Mann-Whitney U test was used for comparisons between the groups. RESULTS: In total, 187 patients were included in the analysis, excluding 7 patients. GLFS 25 showed a significant increase in scores at the second and third time points compared with baseline, and a main effect was confirmed in both groups, with no interaction effect. The second time, the score was 10.0 ± 8.5 and 13.7 ± 10.5 in the non-DS and DS groups, respectively. The third time, the non-DS and DS groups scored 10.8 ± 10.5 and 14.9 ± 10.1 points, respectively, indicating a significant difference. CONCLUSIONS: Our results revealed that the increase in the GLFS 25 score in community-dwelling older adults during the COVID-19 pandemic was related to their DS during normal times before the pandemic. Evaluating such individuals and providing social support may effectively reduce the deterioration of the GLFS 25 score.

Perception, views, and barriers of primary care doctors regarding screening of depression among elderly patients attending public healthcare clinics in Kuching district: a qualitative study.

INTRODUCTION: Depression in the elderly constitutes 7.3% of the total Malaysian national prevalence of depression. However, depression is commonly underdiagnosed by primary care physicians, which may impact coexisting comorbid conditions and general well-being. As depression in the elderly increases with age, its prevalence is expected to become even more significant due to the increased life expectancy and isolation during the pandemic. This study aims to determine the perceptions, views and barriers encountered among primary care physicians on screening for depression among the elderly. MATERIALS AND METHODS: This qualitative study involved five public healthcare clinics in the Kuching district with indepth interviews (IDI) conducted on 14 primary care doctors (PCDs). Semi-structured interviews and in-depth discussions were conducted via videoconferencing. One representative was selected from each clinic at initiation, followed by snowball method for subsequent subject selection until saturation of themes. Interviews were transcribed verbatim, and analysis based on framework analysis principles via NVivo software. Themes were analysed deductively according to study objectives and evidence from literature. RESULTS: Three main themes emerged from the IDI: (1) The perception of depression in elderly patients, (2) The perceived barriers to screening, and (3) The screening processes. Majority of the PCDs perceived depression as part of ageing process. Time constraints, lack of privacy in consultation rooms, dominant caregivers and failure to recognise recurrent somatic symptoms as part of depression influenced PCDs decision to screen. Screening was technically challenging for PCDs to use the DASS-21, which was not socio-culturally validated for local native population. Only 21.4% of respondents (3/14) reported screening at least three out 10 elderly patients seen over 1- month period. During the covid pandemic, due to the same human resource support and practices, most participants thought their screening for depression in elderlies had not changed. CONCLUSION: Awareness of depression among PCDs needs to be re-enforced via continuous medical education programs to use appropriate screening tools, address infrastructure related barriers to optimise screening practices. The use of appropriate locally validated and socio-culturally adapted tool is vital to correctly interpret the screening test for patients.

Impact of covid-19 pandemic over depressive symptoms among mothers from a population-based birth cohort in southern brazil.

PURPOSE: Our aim was to assess the impact of COVID-19 on depressive symptoms among mothers from a population-based birth cohort in Pelotas, Southern Brazil. METHODS: A subgroup of mothers from the Pelotas 2004 Birth Cohort was assessed pre-pandemic (November,2019 to March,2020) and mid-pandemic (August-December,2021). In both follow-ups, depressive symptoms were assessed using the Edinburgh Postnatal Depression Scale (EPDS). Pre-pandemic (T1) and pandemic-related predictors (T2) were analyzed. Prevalence of depression (EPDS score ≥ 13) at T1 and T2 were compared with chi-square test. Changes in EPDS from T1 to T2 were estimated by multivariate latent change score modelling. RESULTS: 1,550 women were assessed. Prevalence of depression increased 38.1% (from 18.9% at T1 to 26.1% at T2) (p < 0.001). At T1, higher schooling, higher family income and being employed or working were related to lower EPDS, whereas being beneficiary of a cash transfer program and a larger number of people living in the household predicted higher EPDS. The deterioration of ones' own perception of quality of overall health (ß = 0.191; SE = 0.028; p < 0.001) and worst family financial situation due to the pandemic (ß = 0.083; SE = 0.024; p = 0.001) predicted the increase in EPDS from T1 to T2. CONCLUSION: Almost two years after the beginning of the pandemic, the prevalence of depressive symptoms among the women was higher than before the pandemic. The deterioration of ones' own perception of quality of overall health and worst family financial situation due to the pandemic are proxies for the effect of COVID-19 pandemic (the true exposure of interest) in the women mental health.

Mental health and drug use in college students: Should we take action?

BACKGROUND: College students are vulnerable to suffering from anxiety and depression. Moreover, mental disorders can contribute to drug consumption or inappropriate use of prescribed drugs. Studies on this topic in Spanish college students are limited. This work analyses anxiety and depression and psychoactive drug intake pattern in the post-COVID era in college students. METHODS: An online survey was conducted among college students from UCM (Spain). The survey collected data including demographic, academic student perception, GAD-7 and PHQ-9 scales, and psychoactive substances consumption. RESULTS: A total of 6798 students were included; 44.1 % (CI95%: 42.9 to 45.3) showed symptoms of severe anxiety and 46.5 % (CI95%: 45.4 to 47.8) symptoms of severe or moderately severe depression. The perception of these symptoms did not change after returning to face-to-face university classes in the post-COVID19 era. Despite the high percentage of cases with clear symptoms of anxiety and depression, most students never had a diagnosis of mental illnesses [anxiety 69.2 % (CI95%: 68.1 to 70.3) and depression 78.1 % (CI95%: 77.1 to 79.1)]. Regarding psychoactive substances, valerian, melatonin, diazepam, and lorazepam were the most consumed. The most worrying issue was the consumption of diazepam, 10.8 % (CI95%: 9.8 to 11.8), and lorazepam, 7.7 % (CI95%: 6.9 to 8.6) without medical prescription. Among illicit drugs, cannabis is the most consumed. LIMITATIONS: The study was based on an online survey. CONCLUSIONS: The high prevalence of anxiety and depression aligned with poor medical diagnosis and high intake of psychoactive drugs should not be underestimated. University policies should be implemented to improve the well-being of students.

Prevalence, correlates, and network analysis of depression and its association with quality of life in survivors with myocardial infarction during the COVID-19 pandemic.

BACKGROUND: Depression is common among myocardial infarction (MI) survivors and is strongly associated with poor quality of life (QOL). The aim of this study was to examine the prevalence, correlates and the network structure of depression, and its association with QOL in MI survivors during the COVID-19 pandemic. METHODS: This cross-sectional study evaluated depression and QOL in MI survivors with the Chinese version of the nine-item Patient Health Questionnaire (PHQ-9) and the World Health Organization Quality of Life-BREF (WHOQOL-BREF), respectively. Univariable analyses, multivariable analyses, and network analyses were performed. RESULTS: The prevalence of depression (PHQ-9 total score ≥ 5) among 565 MI survivors during the COVID-19 pandemic was 38.1 % (95 % CI: 34.1-42.1 %), which was significantly associated with poor QOL. Patients with depression were less likely to consult a doctor regularly after discharge, and more likely to experience more severe anxiety symptoms and fatigue. Item PHQ4 "Fatigue" was the most central symptom in the network, followed by PHQ6 "Guilt" and PHQ2 "Sad mood". The flow network showed that PHQ4 "Fatigue" had the highest negative association with QOL. CONCLUSION: Depression was prevalent among MI survivors during the COVID-19 pandemic and was significantly associated with poor QOL. Those who failed to consult a doctor regularly after discharge or reported severe anxiety symptoms and fatigue should be screened for depression. Effective interventions for MI survivors targeting central symptoms, especially fatigue, are needed to reduce the negative impact of depression and improve QOL.

Six addiction components of problematic social media use in relation to depression, anxiety, and stress symptoms: a latent profile analysis and network analysis.

BACKGROUNDS: Components of addiction (salience, tolerance, mood modification, relapse, withdrawal, and conflict) is the most cited theoretical framework for problematic social media use (PSMU). However, studies criticized its ability to distinguish problematic users from engaged users. We aimed to assess the association of the six criteria with depression, anxiety, and stress at a symptom level. METHODS: Ten thousand six hundred sixty-eight participants were recruited. Bergen Social Media Addiction Scale (BSMAS) was used to detect six addiction components in PSMU. We applied the depression-anxiety-stress scale to assess mental distress. Latent profile analysis (LPA) was conducted based on BSMAS items. Network analysis (NA) was performed to determine the symptom-symptom interaction of PSMU and mental distress. RESULTS: (1) Social media users were divided into five subgroups including occasional users (10.6%, n = 1127), regular users (31.0%, n = 3309), high engagement low risk users (10.4%, n = 1115), at-risk users (38.1%, n = 4070), and problematic users (9.8%, n = 1047); (2) PSMU and mental distress varied markedly across subgroups. Problematic users had the most severe PSMU, depression, anxiety, and stress symptoms. High engagement users scored high on tolerance and salience criteria of PSMU but displayed little mental distress; (3) NA showed conflict and mood modification was the bridge symptoms across the network, while salience and tolerance exhibited weak association with mental distress. CONCLUSIONS: Salience and tolerance might not distinguish engaged users from problematic users. New frameworks and assessment tools focusing on the negative consequences of social media usage are needed.

Prevalence of mental health problems among children with long COVID: A systematic review and meta-analysis.

INTRODUCTION: The number of children with mental health problems has more than doubled since the COVID-19 pandemic. However, the effect of long Covid on children's mental health is still debatable. Recognising long Covid as a risk factor for mental health problems in children will increase awareness and screening for mental health problems following COVID-19 infection, resulting in earlier intervention and lower morbidity. Therefore, this study aimed to determine the proportion of mental health problems post-COVID-19 infection in children and adolescents, and to compare them with the population with no previous COVID-19 infection. METHODOLOGY: A systematic search was done in seven databases using pre-defined search terms. Cross-sectional, cohort and interventional studies reporting the proportion of mental health problems among children with long COVID in the English language from 2019 to May 2022 were included. Selection of papers, extraction of data and quality assessment were done independently by two reviewers. Studies with satisfactory quality were included in meta-analysis using R and Revman software programmes. RESULTS: The initial search retrieved 1848 studies. After screening, 13 studies were included in the quality assessments. Meta-analysis showed children who had previous COVID-19 infection had more than two times higher odds of having anxiety or depression, and 14% higher odds of having appetite problems, compared to children with no previous infection. The pooled prevalence of mental health problems among the population were as follows; anxiety: 9%(95% CI:1, 23), depression: 15%(95% CI:0.4, 47), concentration problems: 6%(95% CI: 3, 11), sleep problems: 9%(95% CI:5, 13), mood swings: 13% (95%CI:5, 23) and appetite loss: 5%(95% CI:1, 13). However, studies were heterogenous and lack data from low- and middle-income countries. CONCLUSION: Anxiety, depression and appetite problems were significantly increased among post-COVID-19 infected children, compared to those without a previous infection, which may be attributed to long COVID. The findings underscore the importance of screening and early intervention of children post-COVID-19 infection at one month and between three to four months.

Depression and anxiety during and after episodes of COVID-19 in the community.

Understanding the connection between physical and mental health with evidence-based research is important to inform and support targeted screening and early treatment. The objective of this study was to document the co-occurrence of physical and mental health conditions during and after the experience of symptomatic SARS-CoV-2 illness episodes. Drawing from a national symptoms' surveillance survey conducted in the UK in 2020, this study shows that individuals with symptomatic forms of SARS-CoV-2 (identified by anosmia with either fever, breathlessness or cough) presented significantly higher odds of experiencing moderate and severe anxiety (2.41, CI 2.01-2.90) and depression (3.64, CI 3.06-4.32). Respondents who recovered from physical SARS-CoV-2 symptoms also experienced higher odds of anxiety and depression in comparison to respondents who never experienced symptoms. The findings are robust to alternative estimation models that compare individuals with the same socioeconomic and demographic characteristics and who experienced the same local and contextual factors such as mobility and social restrictions. The findings have important implications for the screening and detection of mental health disorders in primary care settings. They also suggest the need to design and test interventions to address mental health during and after physical illness episodes.

High prevalence of mental disorder symptoms among medical and other health specialties residents during the COVID-19 pandemic.

BACKGROUND: The COVID-19 pandemic put healthcare professionals, including residents (postgraduate trainees of health professions), under intense physical and psychological stress, hence at risk for mental disorders. We evaluated the prevalence of mental disorders among healthcare residents during the pandemic. METHODS: From July to September 2020, residents in medicine and other healthcare specialties in Brazil were recruited. The participants completed electronic forms with validated questionnaires (DASS-21, PHQ-9, BRCS) to screen for depression, anxiety, and stress, and to evaluate resilience. Data on potential predisposing factors for mental disorders were also collected. Descriptive statistics, chi-squared, students t, correlation and logistic regression models were applied. The study received ethical approval, and all participants provided informed consent. RESULTS: We included 1313 participants (51.3% medical; 48.7% nonmedical) from 135 Brazilian hospitals; mean (SD) age: 27.8 (4.4) years; 78.2% females; 59.3% white race. Of all participants, 51.3%, 53.4% and 52.6% presented symptoms consistent with depression, anxiety, and stress, respectively; 61.9% showed low resilience. Nonmedical residents exhibited higher anxiety compared to medical residents (DASS-21 anxiety score, mean difference: 2.26; 95% CI: 1.15-3.37; p < 0.001). In multivariate analyses, having any pre-existent, nonpsychiatric chronic disease was associated with higher prevalence of symptoms indicative of depression (odds ratio, OR: 2.05; 95% CI: 1.47-2.85, on DASS-21 | OR: 2.26; 95% CI: 1.59-3.20, on PHQ-9), anxiety (OR: 2.07; 95% CI: 1.51-2.83, on DASS-21), and stress (OR: 1.53; 95% CI: 1.12-2.09, on DASS-21); other predisposing factors were identified; by contrast, high resilience (BRCS score) was protective against symptoms of depression (OR 0.82; 95% CI: 0.79-0.85, on DASS-21 | OR 0.85; 95% CI: 0.82-0.88, on PHQ-9), anxiety (OR 0.90; 95% CI: 0.87-0.93, on DASS-21), and stress (OR 0.88; 95% CI: 0.85-0.91, on DASS-21); p < 0.05 for all outcomes. CONCLUSIONS: We found a high prevalence of mental disorder symptoms among healthcare residents during COVID-19 pandemic in Brazil. Nonmedical residents exhibited higher levels of anxiety than medical ones. Some predisposing factors for depression, anxiety and stress among residents were identified.

Depression and anxiety among the University community during the Covid-19 pandemic: a study in Southern Brazil.

This study aimed to assess the mental health of a University community in South Brazil during the COVID-19 pandemic. A cross-sectional web-based survey was conducted between July-August 2020 through a self-administered questionnaire. All University staff and students were eligible. Depression was measured using the Patient Health Questionnaire-9 and anxiety by the Generalized Anxiety Disorder-7. To evaluate the effect of social distancing and mental health factors on outcomes, Poisson regression models with robust variance were performed, estimating Prevalence Ratios (PR) and 95% Confidence Intervals (95%CI). 2,785 individuals participated in the study. Prevalence of depression and anxiety were 39.2% (95%CI 37.3-41.1) and 52.5% (95% CI 50.6-54.4), respectively. Undergraduate students showed a higher prevalence of the outcomes. Not leaving the house routinely, mental health care, and previous diagnosis of mental illness were associated with both outcomes. Those with a previous medical diagnosis of depression had a 58% (PR 1.58; 95%CI 1.44; 1.74) and anxiety a 72% (PR 1.72; 95%CI 1.56; 1.91) greater prevalence of depression than their peers. An alarming prevalence of psychopathologies was observed. Despite the well-known benefits of social distancing to public health, it requires a surveillance on the population's mental health, especially students and those with previous mental illness diagnosis.

Treating depression with a smartphone-delivered self-help cognitive behavioral therapy for insomnia: study protocol for a parallel group randomized controlled trial.

BACKGROUND: Depression is a major public health concern. Emerging research has shown that cognitive behavioral therapy for insomnia (CBT-I) is effective in treating individuals with comorbid insomnia and depression. Traditional face-to-face CBT-I encounters many obstacles related to feasibility, accessibility, and help-seeking stigma. CBT-I delivered via smartphone application could be a potential solution. This paper reports a protocol designed to evaluate the efficacy of a self-help smartphone-based CBT-I, using a waitlist group as control, for people with major depression and insomnia. METHODS: A two-arm parallel randomized controlled trial is conducted in a target sample of 285 non-suicidal Hong Kong Chinese older than 17 years of age with major depression and insomnia. Participants complete an online rapid screening, followed by a telephone diagnostic interview. Those who meet the eligibility criteria are randomized in a ratio of 1:1 to receive either CBT-I immediately or to a waitlist control condition. The CBT-I consists of six weekly modules and is delivered through a smartphone application proACT-S. This smartphone app has been pilot tested and revamped to improve user experience. An online randomized algorithm is used to perform randomization to ensure allocation concealment. The primary outcomes are changes over the measurement points in sleep quality, insomnia severity, and depression severity. The secondary outcomes include changes over the measurement points in anxiety, subjective health, treatment expectancy, and acceptability of treatment. Assessments are administered at baseline, post-intervention, and 6-week follow-up. The recruitment is completed. Important adverse events, if any, are documented. Multilevel linear mixed model based on intention-to-treat principle will be conducted to examine the efficacy of the CBT-I intervention. DISCUSSION: It is expected that proACT-S is an efficacious brief sleep-focused self-help treatment for people with major depression and insomnia. If proven efficacious, due to its self-help nature, proACT-S may be applicable as a community-based early intervention, thereby reducing the burden of the public healthcare system in Hong Kong. TRIAL REGISTRATION: ClinicalTrials.gov NCT04228146 . Retrospectively registered on 14 January 2020.

Psychological intervention for negative emotions aroused by COVID-19 pandemic in university students: A systematic review and meta-analysis.

The COVID-19 pandemic has been suggested to cause psychological problems such as anxiety, depression, panic, and insomnia. This systematic review and meta-analysis aims to assess the efficacy of psychological interventions (including CBT, DBT, and mindfulness based interventions) in reducing distressing feelings in college students during the COVID-19 pandemic. Randomized controlled trials (RCTs) on psychological interventions for reducing negative emotions among college students during the COVID-19 epidemic were searched in databases Web of Science, PubMed, Cochrane Library, Embase, Scopus, PsychInfo, CNKI, WanFang, and VIP. We utilized Cochrane risk of bias assessment technique to assess the quality of included RCTs. The data were analyzed using RevMan 5.4. Eight RCTs were finally included involving 1,496 participants. According to the meta-analysis results, psychotherapies could significantly alleviate anxiety, depression, and stress symptoms among university students, [MD = -0.98, 95%CI (-1.53, -0.43), p<0.001] [SMD = -0.47, 95%CI (-0.77, -0.16), p = 0.003] [MD = -1.53, 95%CI (-2.23, -0.83), p <0.001]. The difference in attenuation of somatization symptoms between the two groups was not statistically significant [SMD = -0.42, 95%CI (-1.41, 0.56), p = 0.40]. Psychotherapy might effectively alleviate anxiety, depression, and stress in university students caused by the COVID-19 pandemic. It could be considered the preferred strategy for reducing negative emotions and improving the quality of life of university students.

Association between recent COVID-19 diagnosis, depression and anxiety symptoms among slum residents in Kampala, Uganda.

BACKGROUND: Despite the known link between poor living conditions and mental health, there has been little research on the mental health of slum dwellers worldwide. Although the Coronavirus disease 2019 (COVID-19) pandemic has led to an increase in mental health issues, little focus has been given to the impact on slum dwellers. The study aimed to investigate the association between recent COVID-19 diagnosis and the risk of depression and anxiety symptoms among people living in an urban slum in Uganda. METHODS: A cross-sectional study was conducted among 284 adults (at least 18 years of age) in a slum settlement in Kampala, Uganda between April and May 2022. We assessed depression symptoms and anxiety using validated Patient Health Questionnaire (PHQ-9) and Generalized Anxiety Disorder assessment tool (GAD-7) questionnaires respectively. We collected data on sociodemographic characteristics, and self-reported recent COVID-19 diagnosis (in the previous 30 days). Using a modified Poisson regression, adjusted for age, sex, gender and household income, we separately provided prevalence ratios and 95% confidence intervals for the associations between recent COVID-19 diagnosis and depressive and anxiety symptoms. RESULTS: Overall, 33.8% and 13.4% of the participants met the depression and generalized anxiety screening criteria respectively and 11.3% were reportedly diagnosed with COVID-19 in the previous 30 days. People with recent COVID-19 diagnosis were more likely to be depressed (53.1%) than those with no recent diagnosis (31.4%) (p<0.001). Participants who were recently diagnosed with COVID-19 reported higher prevalence of anxiety (34.4%) compared to those with no recent diagnosis of COVID-19 (10.7%) (p = 0.014). After adjusting for confounding, recent diagnosis with COVID-19 was associated with depression (PR = 1.60, 95% CI 1.09-2.34) and anxiety (PR = 2.83, 95% CI 1.50-5.31). CONCLUSION: This study suggests an increased risk of depressive symptoms and GAD in adults following a COVID-19 diagnosis. We recommend additional mental health support for recently diagnosed persons. The long-term of COVID-19 on mental health effects also need to be investigated.

Impact of elexacaftor/tezacaftor/ivacaftor on depression and anxiety in cystic fibrosis.

BACKGROUND: Cystic fibrosis (CF) is associated with worsening of depression and anxiety symptoms. Elexacaftor/tezacaftor/ivacaftor (Trikafta®), a cystic fibrosis transmembrane regulator (CFTR) modulator approved in 2019, significantly improves lung function, decreases pulmonary exacerbations, and improves quality of life. Studies are needed to evaluate the effects of Trikafta on symptoms of anxiety and depression. RESEARCH QUESTION: Do adults with CF report a change in depression and anxiety symptoms after Trikafta initiation? STUDY DESIGN AND METHODS: A retrospective chart review was conducted of patients with CF (n = 127) receiving care from January 2015 through February 2022. Data collected included demographics, annual PHQ-9 and GAD-7 scores, FEV1 percent predicted at each visit, BMI, consistency and timeline of Trikafta use, mental health diagnoses, counseling/psychotherapy use, psychiatric medication use, prescriber of psychiatric medications, number of psychiatric emergency department visits and psychiatric hospital admissions, and sleep disturbances. RESULTS: Of the 127 patients screened for eligibility, 100 patients were included. Data collected yielded 563 PHQ-9, 563 GAD-7, and 560 ppFEV1 data points. No significant changes in average PHQ-9 or GAD-7 scores were found after Trikafta initiation or due to the COVID-19 pandemic. However, 22% of patients initiated or had a change in psychiatric medications, and patients with changes in psychiatric medications had significantly higher PHQ-9 and GAD-7 scores than patients not prescribed psychiatric medications. Trikafta use improved lung function by an average of 5.23% (p = 8.56e-08). Around a quarter (23%) of all patients reported sleep issues after initiating Trikafta. INTERPRETATION: No significant changes in average PHQ-9 and GAD-7 scores were found after Trikafta initiation. A quarter of patients required a change in psychiatric medications, and significant differences in depression and anxiety scores were found between patients with a change in psychiatric medications and those not prescribed medication. Twenty-three percent of patients reported a prevalence of sleep issues after Trikafta initiation.

Factors associated with new-onset depressive symptoms in patients starting cardiac rehabilitation: Pre-COVID-19 and COVID-19 period comparison.

OBJECTIVE: We aim to: 1) investigate whether starting cardiac rehabilitation (CR) during the COVID-19 period was influential on new-onset depressive symptoms, 2) examine the relationship between sociodemographic and medical factors with the new-onset of depressive symptoms before and during the COVID-19 period in UK patients commencing CR. METHODS: The national audit of cardiac rehabilitation (NACR) data were used and the two years of data before COVID-19 and during COVID-19 were analysed (Feb,2018 - Nov,2021). Hospital Anxiety and Depression Scale measurement was used to assess depressive symptoms. Bivariate analysis and logistic regression were conducted to examine the influence of the COVID-19 period on new-onset depressive symptoms and the patient characteristics associated with it. RESULTS: 71055 patients screened for new-onset depressive symptoms were included in the analysis. Based on multivariate analysis, patients commencing CR during COVID-19 were 8% more likely to have new onset depressive symptoms compared to patients commencing before COVID-19. Smoking (OR: 1.26, 95%CI: 1.11, 1.43), physical inactivity (OR: 1.86, 95%CI: 1.74, 1.98), high anxiety (OR: 1.45, 95%CI: 1.44, 1.46), being male (OR: 1.21, 95%CI: 1.12, 1.30), single (OR: 1.25, 95%CI: 1.16, 1.35), having comorbidities of arthritis, diabetes, chronic bronchitis, emphysema, claudication (OR range: 1.19 to 1.60), receiving CABG treatment (OR: 1.47, 95%CI: 1.25, 1.73), and having heart failure (OR: 1.33, 95%CI: 1.19, 1.48) were the factors associated with having new-onset depressive symptoms at the start of CR. CONCLUSION: Our findings have shown that starting CR during the COVID-19 period was associated with increased odds of having new-onset depressive symptoms.

Identifying pathways between psychiatric symptoms and psychosocial functioning in the general population.

The present study aims to identify pathways between psychiatric network symptoms and psychosocial functioning and their associated variables among functioning clusters in the general population. A cross-sectional web-based survey was administered in a total of 3,023 individuals in Brazil. The functioning clusters were derived by a previous study identifying three different groups based on the online Functioning Assessment Short Test. Networking analysis was fitted with all items of the Patient-Reported Outcomes Measurement Information System for depression and for anxiety (PROMIS) using the mixed graphical model. A decision tree model was used to identify the demographic and clinical characteristics of good and low functioning. A total of 926 (30.63%) subjects showed good functioning, 1,436 (47.50%) participants intermediate functioning, and 661 (21.86%) individuals low functioning. Anxiety and uneasy symptoms were the most important nodes for good and intermediate clusters but anxiety, feeling of failure, and depression were the most relevant symptoms for low functioning. The decision tree model was applied to identify variables capable to discriminate individuals with good and low functioning. The algorithm achieved balanced accuracy 0.75, sensitivity 0.87, specificity 0.63, positive predictive value 0.63 negative predictive value 0.87 (p<0.001), and an area under the curve of 0.83 (95%CI:0.79-0.86, p<0.01). Our results show that individuals who present psychological distress are more likely to experience poor functional status, suggesting that this subgroup should receive a more comprehensive psychiatric assessment and mental health care.

The association between preconception cannabis use and depression and anxiety during pregnancy.

OBJECTIVE: Cannabis use among individuals of reproductive age has increased with cannabis legalization and heightened stress during the COVID-19 pandemic. Our study provides data on preconception cannabis use and cannabis use disorder (CUD) during the pandemic and models the association between preconception cannabis use and depression and anxiety during pregnancy. METHODS: Data on substance use and depression and anxiety symptoms were collected from questionnaires and the Structured Clinical Interview for DSM-5 (SCID-5) from pregnant individuals in Oregon in 2019-2022. Linear regression was used to model the association between the frequency of preconception cannabis use and scores on the Center for Epidemiological Studies of Depression-Revised (CESD-R) and Beck Anxiety Inventory (BAI). RESULTS: The prevalence of preconception cannabis use was 27.8% among 227 study participants. CUD was diagnosed in 19% of cannabis users, or 5.3% of the overall sample. Daily cannabis use, compared to rare/never use, was associated with increases in CESD-R (ß = 6.22, p 0.029) and BAI (ß = 4.71, p 0.045) scores. CONCLUSIONS: Cannabis use and CUD are common among individuals of reproductive age. Given the association between preconception cannabis use and depression and anxiety during pregnancy, more attention is needed on screening and counseling of cannabis use among people of reproductive age.