Self-Compassion, Anxiety and Depression Symptoms; the Mediation of Shame and Guilt

Self-compassion is related to psychological well-being and can improve mental health problems. The present study aimed to examine the relationship of self-compassion with anxiety and depression symptoms considering the mediating effects of shame and guilt. Two hundred forty-three participants in Iran completed the measures of Depression, Anxiety, Stress Scale (DASS), self-compassion Scale-Short Form (SCS-SF), and personal feelings questionnaire-2 (PFQ-2 Brief). The result showed that there was a significant negative correlation between self-compassion and shame, guilt, depression, and anxiety. The correlation between shame and guilt with depression and anxiety was also positive and significant. Mediation analysis was used to examine whether self-compassion predicted decreased symptoms of depression and anxiety through decreased shame and guilt. The results showed that self-compassion has a negative direct effect on depression symptoms. The direct effect of self-compassion on anxiety symptoms was not significant. Moreover, we found that shame and guilt mediate the relationship between self-compassion and depressive symptoms. However, the indirect effect of guilt on anxiety symptoms was not significant. The findings of the current study demonstrate that Self-compassion is linked to more psychological strengths and efficient emotional regulations, leading to less self-conscious emotions (shame and guilt) and decreased depression and anxiety symptoms.

Isolating unique variance in mental health outcomes attributable to personality variables and childhood emotional abuse

Introduction

University students are at high risk for anxiety and depression. Our main objective was to tease apart variance in symptom severity that was uniquely attributable to four associated variables that are frequently confounded: exposure to childhood emotional abuse, alexithymia, sensory processing sensitivity (SPS), and anxiety sensitivity (AS).

Methods

University students (N = 410) completed an online survey designed to measure our four key study variables along with several other potentially relevant variables including sex, physical activity levels, and perceived COVID-19 impacts.

Results

Over half of the participants reported moderate to extremely severe symptoms of anxiety and depression. Females reported stronger signs of SPS and AS and were more likely than males to have increased their moderate/vigorous exercise since the pandemic began. After controlling for the other variables, the best predictors of perceived COVID-19 impacts were SPS, childhood emotional abuse, and current levels of physical activity. Whereas all three personality variables and childhood emotional abuse emerged as significant predictors of both depression and anxiety, neither COVID-19 impacts nor physical activity levels accounted for unique variance in either model. Unexpectedly, male sex emerged as an additional risk factor for depression, raising the possibility that males experience unique stressors and societal pressures that increase their risk of depression.

Discussion

These findings help to clarify the links between childhood emotional abuse, personality traits implicated in emotional awareness and self-regulation, and mental health. They may have important implications for the development and implementation of individualized treatments for common mental disorders.

Effect of Dancing Interventions on Depression and Anxiety Symptoms in Older Adults: A Systematic Review and Meta-Analysis

This systematic review and meta-analysis (PROSPERO CRD42023428105) investigated the effect of dancing on depression and anxiety symptoms in older adults. Conducted up to October 2023, the search across seven databases and gray literature yielded 5020 records. Only randomized trials that analyzed dance interventions for depression and/or anxiety in older adults were included. Nineteen randomized trials, involving 508 participants in dance classes lasting 5 weeks to 18 months, were included and 16 were subjected to meta-analysis. Risk of bias was assessed using the Cochrane tool. The meta-analysis showed a statistically significant reduction in depression among older adults participating in dance interventions (p < 0.01). A decrease in depressive symptoms was significant compared to that in those involved in no other intervention (p = 0.02) but not compared to that achieved with other interventions in control groups (p = 0.96). Subgroup analysis showed no significant differences in depression scores for those with mild cognitive impairment (p = 0.47). These conclusions are associated with moderate bias and very low certainty. Due to heterogeneity and the small number of studies, conclusions for anxiety outcomes could not be drawn. These results underscore the potential clinical relevance of integrating dance into mental health interventions for older adults, thereby highlighting a promising avenue for enhancing the mental well-being of this demographic.

Assessing prognosis in depression: comparing perspectives of AI models, mental health professionals and the general public

BACKGROUND

Artificial intelligence (AI) has rapidly permeated various sectors, including healthcare, highlighting its potential to facilitate mental health assessments. This study explores the underexplored domain of AI's role in evaluating prognosis and long-term outcomes in depressive disorders, offering insights into how AI large language models (LLMs) compare with human perspectives.

METHODS

Using case vignettes, we conducted a comparative analysis involving different LLMs (ChatGPT-3.5, ChatGPT-4, Claude and Bard), mental health professionals (general practitioners, psychiatrists, clinical psychologists and mental health nurses), and the general public that reported previously. We evaluate the LLMs ability to generate prognosis, anticipated outcomes with and without professional intervention, and envisioned long-term positive and negative consequences for individuals with depression.

RESULTS

In most of the examined cases, the four LLMs consistently identified depression as the primary diagnosis and recommended a combined treatment of psychotherapy and antidepressant medication. ChatGPT-3.5 exhibited a significantly pessimistic prognosis distinct from other LLMs, professionals and the public. ChatGPT-4, Claude and Bard aligned closely with mental health professionals and the general public perspectives, all of whom anticipated no improvement or worsening without professional help. Regarding long-term outcomes, ChatGPT 3.5, Claude and Bard consistently projected significantly fewer negative long-term consequences of treatment than ChatGPT-4.

CONCLUSIONS

This study underscores the potential of AI to complement the expertise of mental health professionals and promote a collaborative paradigm in mental healthcare. The observation that three of the four LLMs closely mirrored the anticipations of mental health experts in scenarios involving treatment underscores the technology's prospective value in offering professional clinical forecasts. The pessimistic outlook presented by ChatGPT 3.5 is concerning, as it could potentially diminish patients' drive to initiate or continue depression therapy. In summary, although LLMs show potential in enhancing healthcare services, their utilisation requires thorough verification and a seamless integration with human judgement and skills.

Development of depression detection algorithm using text scripts of routine psychiatric interview

Background

A psychiatric interview is one of the important procedures in diagnosing psychiatric disorders. Through this interview, psychiatrists listen to the patient's medical history and major complaints, check their emotional state, and obtain clues for clinical diagnosis. Although there have been attempts to diagnose a specific mental disorder from a short doctor-patient conversation, there has been no attempt to classify the patient's emotional state based on the text scripts from a formal interview of more than 30 min and use it to diagnose depression. This study aimed to utilize the existing machine learning algorithm in diagnosing depression using the transcripts of one-on-one interviews between psychiatrists and depressed patients.

Methods

Seventy-seven clinical patients [with depression (n = 60); without depression (n = 17)] with a prior psychiatric diagnosis history participated in this study. The study was conducted with 24 male and 53 female subjects with the mean age of 33.8 (± 3.0). Psychiatrists conducted a conversational interview with each patient that lasted at least 30 min. All interviews with the subjects between August 2021 and November 2022 were recorded and transcribed into text scripts, and a text emotion recognition module was used to indicate the subject's representative emotions of each sentence. A machine learning algorithm discriminates patients with depression and those without depression based on text scripts.

Results

A machine learning model classified text scripts from depressive patients with non-depressive ones with an acceptable accuracy rate (AUC of 0.85). The distribution of emotions (surprise, fear, anger, love, sadness, disgust, neutral, and happiness) was significantly different between patients with depression and those without depression (p < 0.001), and the most contributing emotion in classifying the two groups was disgust (p < 0.001).

Conclusion

This is a qualitative and retrospective study to develop a tool to detect depression against patients without depression based on the text scripts of psychiatric interview, suggesting a novel and practical approach to understand the emotional characteristics of depression patients and to use them to detect the diagnosis of depression based on machine learning methods. This model could assist psychiatrists in clinical settings who conduct routine conversations with patients using text transcripts of the interviews.

Efficacy and safety of repeated transcranial magnetic stimulation combined with escitalopram in the treatment of major depressive disorder: a meta-analysis

Objective

This study was designed to systematically review the efficacy and safety of repeated transcranial magnetic stimulation (rTMS) combined with escitalopram in treating major depressive disorder (MDD).

Methods

Databases including PubMed, Embase, Cochrane, Web of Science, CNKI, Wanfang, VIP Journal, and China Biomedical Literature databases were electronically searched for randomized controlled trials of rTMS combined with escitalopram intervention for MDD treatment from the inception of these databases to 27 May 2023. Two reviewers independently screened the studies, extracted the data, and assessed the quality of the included studies. R 4.2.2 was then used for a meta-analysis.

Results

In total, 19 articles involving 1,032 patients were included. The results of the meta-analysis showed that Hamilton Depression Rating Scale (HAMD) scores were significantly lower in the group receiving rTMS combined with escitalopram (experimental group) than that in the control group [weighted mean difference (WMD) = -5.30, 95% confidence interval (95% CI): -6.44 to -4.17, p < 0.01]. The response rate of the experimental group was significantly higher than that of the control group [odds ratio (OR): 5.48; 95% CI: 3.72 to 8.07; p < 0.01]. No significant difference in the adverse reaction rate was observed between the two groups (OR: 1.04, 95% CI: 0.71 to 1.52, p = 0.82).

Conclusion

Our findings suggest that rTMS combined with escitalopram can benefit patients with MDD in a safe manner, which may help in guiding clinical practice.

Systematic review registration

DOI number: 10.37766/inplasy2023.11.0114, INPLASY2023110114.

Depressive disorder, bipolar disorder, and associated factors among adults, in the Eastern part of Ethiopia

BACKGROUND

Depressive disorder is one of the severe and common mental illnesses in the general population. Bipolar disorder is a severe, persistent mental illness associated with significant morbidity and mortality. However, there is a paucity of data on the prevalence of depressive disorder, and bipolar disorder in our study area.

OBJECTIVE

This study aimed to assess the prevalence of depressive and bipolar disorders among adults in Kersa, Haramaya, and Harar Health and Demographic Surveillance Sites in Eastern Ethiopia.

METHODS

A community-based cross-sectional study was conducted among 1,416 participants. A multi-stage sampling was employed to select the participants. DSM-5 diagnostic criteria was used to assess depressive disorder and bipolar disorder. Data was collected using a standard questionnaire. Data were entered into Epi-Data 3.1 and analyzed using SPSS version 26. Both binary and multivariate logistic regression analyses were done. Those with a p-value < 0.05 in the final model were considered statistically significant.

RESULTS

The overall prevalence of depressive and bipolar disorders among our study participants was 6.7% (95% CI: 5.40, 8.20) and 2.1% (95% CI: (1.40, 3.00), respectively. The independent predictors of depressive disorder included a family history of mental illness, chronic medical illnesses, unemployment, low educational status, divorced or widowed, poor social support, and current alcohol use or khat chewing. Single, males, divorced or widowed, and current consumers of alcohol were independent predictors for bipolar disorder.

CONCLUSIONS AND RECOMMENDATION

The results of our investigation showed that bipolar illness and depression were significant public health issues. It was shown that although bipolar disorder is highly prevalent in the society, depression is a widespread concern. As a result, it is imperative that the relevant body grow and enhance the provision of mental health services. Furthermore, research on the effects and burdens of bipolar disorder in the community is required.

Effectiveness of a supportive care program via a smartphone application on the quality of life and care burden among family caregivers of patients with major depressive disorder: a randomized controlled trial

BACKGROUND

The majority of patients with major depressive disorder require care that has generally affected caregivers' lives. Providing care could cause negative experiences as a care burden and deteriorate quality of life. However, there is a lack of evidence about caregiver training-based informatics and its impact on the caregiver's life.

METHODS

This experimental study was carried out in Mashhad, Iran. A total of 60 primary family caregivers of patients with major depressive disorder were included in the study between February and July 2021. The quadruple block randomization method was used to allocate the participants into control and intervention groups. In the intervention group, family caregivers used the application with weekly phone calls for one month. The app contains the most important points of patient care and has the possibility of communicating with the nurse. The Novak and Guest Care Burden Inventory and the short form of the World Health Organization Quality of Life Questionnaire were completed before and after the intervention. Data analysis was performed using chi-squared tests, independent sample t tests, and analysis of covariance.

RESULTS

At baseline, the mean scores of care burden and quality of life were homogeneous between the two groups. After the intervention, the mean scores of care burden and quality of life were significantly reduced and improved in the intervention group compared with the control group (p < 0.001).

CONCLUSIONS

Using the application with the ability to communicate with the caregiver, along with educational support, helps to strengthen the relationship between the family caregiver and the nurse. Despite the effectiveness of the present intervention, before including this form of implementation of support in care programs, it is necessary to evaluate its other positive aspects in future studies.

TRIAL REGISTRATION

Iranian Registry of Clinical Trials (IRCT), IRCT20210202050222N1. Registered on 05/02/2022.

A prospective cohort study to assess the prevalence and risk factors of antepartum depression and its effect on maternal and fetal outcome

Antepartum depression (APD) is a public health issue has negative repercussions on the health of the mother, child, and family. Early screening for APD will help in early detection and further prevention of postpartum depression and adverse maternal and fetal outcomes. This study was designed to determine i) the prevalence rate of APD in the Indian population and its associated risk factors, ii) the impact of APD on maternal and fetal outcomes. A retrospective cohort study was conducted among antenatal women in the third trimester and screened for antepartum depression between October 2021 and March 2022 by adopting the Edinburgh Postnatal Depression Scale (EPDS). In the study population, 36.6 % had mild to moderate level of depressive symptoms (EPDS score of 8-12) and 28 % had high levels of depressive symptoms (EPDS score of ≥13). An unplanned pregnancy, a history of abortion, and a history of any pregnancy complications were the likely maternal risk factors for developing antepartum depression. The APD risk was also likely to be increased by sociodemographic and personal factors such as insufficient family support, a history of domestic violence, marital dissatisfaction, and a partner with a poor level of education (P < 0.05). Women screened with antepartum depression had 58.34 times the likelihood of developing postpartum depression and a threefold greater risk of having premature delivery. These findings may help to improve pregnancy outcomes by early identification, referral for early treatment of antepartum depression, also inform maternal mental health service development and utilization for boosting women's mental wellbeing.

Religion and Spiritual Health in Patients With and Without Depression Receiving Hemodialysis: A Cross-Sectional Correlational Study

BACKGROUND

Hemodialysis is the most common therapy for managing patients with end-stage renal disease. Depression is one of the most common psychological problems faced by dialysis patients, and there is limited research on the influences of religion and spirituality on dialysis patients.

PURPOSE

This study was designed to compare religion and spiritual health status between hemodialysis patients with and without depressive symptoms.

METHODS

A cross-sectional survey was conducted on 137 hemodialysis patients living in Taiwan. The self-report instruments used included the Religious Beliefs Scale, Spiritual Health Scale-Short Form, and Beck Depression Inventory-II. Data were analyzed using t test, chi-square test, point-biserial correlation of variance, and logistic regression.

RESULTS

Most (63.5%) of the participants were classified with depression, of which most were male (70.1%), older (mean = 62.56 years), and unemployed (73.6%) and had less formal education. Fifty-two of the participants with depression had a 1- to 5-year duration of hemodialysis, whereas the nondepressed group had a higher mean score for number of religious activities, positive religious beliefs, and total score for spiritual health. Logistic regression showed an increased odds ratio ( OR ) of depression for participants with a duration of hemodialysis of 1-5 years ( OR = 3.64, 95% CI [1.01, 13.15]). Participants with higher scores for spiritual health had a lower risk of depression ( OR = 0.82, 95% CI [0.75, 0.90]), indicating a positive association between spiritual health and lower depression risk.

CONCLUSIONS/IMPLICATIONS FOR PRACTICE

The prevalence rate of depression in hemodialysis patients is higher than that in the general population. Providing screenings for spiritual health and depression as part of routine medical care for hemodialysis patients is recommended to detect spiritual distress and depression early.

Fatigue during the COVID-19 pandemic - prevalence and predictors: findings from a prospective cohort study

The COVID-19 pandemic and consequent lockdowns had a substantial impact on mental health. Distress and fatigue are highly correlated. However, little is known about the determinants of fatigue in the general population during the pandemic. This study aimed to examine the prevalence and predictors of fatigue during the COVID-19 pandemic in the UK population. Online surveys were completed by a UK community cohort in April 2020 (wave 1), July-September 2020 (wave 2) and November-December 2020 (wave 3). In total, 3097 participants completed the wave 1 survey, and 1385 and 1087 participants (85.4% women) completed wave 2 and 3 surveys respectively. Fatigue was assessed using the Chalder Fatigue Scale at waves 2 and 3. Hair samples were provided by 827 participants (90.6% women) at wave 1 and wave 2, which were analyzed to indicate HairE (stress hormone). The mean total fatigue score during wave 2 was 14.7 (SD = 4.7), significantly higher than pre-pandemic levels observed in the community (mean difference 0.50, p = .003). At wave 2, 614 (44.3%) participants met the case definition for fatigue, only 15.6% of whom indicated that fatigue lasted for more than 6 months (suggesting it had started prior to the pandemic). Predictors of fatigue at wave 3 included being in a risk group, depression and belief in having COVID-19, which explained 23.8% of the variability in fatigue scores. Depression at wave 1 was the only significant predictor of remaining a fatigue case at wave 3. Fatigue was highly prevalent in the UK community during the COVID-19 pandemic and limited people's daily function. Depression and sociodemographic variables were significant predictors of fatigue.

Recurrent Cerebral Infarction Due to Moyamoya Disease Complicated With Systemic Lupus Erythematosus: A Case Report and Literature Review

INTRODUCTION

We report a rare case of moyamoya disease caused by an RNF213 mutation, complicated with systemic lupus erythematosus.

CASE REPORT

A 32-year-old woman experienced 4 cerebral ischemia stroke events within 6 months. The main symptom was left limb weakness with blurred vision in the right eye. Results of digital subtraction angiography conducted at another hospital were consistent with moyamoya disease. On genetic testing, we found that the patient carried 2 mutations in the moyamoya disease-related gene RNF213 (p.R4810K, p.T1727M). On the basis of the laboratory immunologic indicators, such as positive antibodies and abnormal immunoglobulin levels and imaging examinations, the patient was finally diagnosed as moyamoya disease complicated with systemic lupus erythematosus. She was treated with aspirin, butylphthalide, urinary kallidinogenase, and sodium methylprednisolone.

CONCLUSIONS

This was a 32-year-old young patient diagnosed with moyamoya disease carrying RNF213 gene mutation and accompanied by lupus with cerebral ischemic event as the first occurrence. The patient's condition was complex; therefore, comprehensive analysis and in-depth consideration were needed to avoid a missed diagnosis and misdiagnosis. When the primary disease cannot be identified, genetic testing can help to clarify the diagnosis of moyamoya disease.

Psychological distress and voting behaviour in nine countries of the former Soviet Union

Poorer mental health is linked to a lower likelihood of voting in elections. However, little is known about this association in non-Western settings. This study examined the association between psychological distress and voting in nine countries of the former Soviet Union (FSU). Data were analysed from 18,000 respondents aged ≥ 18 in Armenia, Azerbaijan, Belarus, Georgia, Moldova, Kazakhstan, Kyrgyzstan, Russia and Ukraine collected during the Health in Times of Transition (HITT) survey in 2010/11. Information was collected on previous voting behaviour and future voting intentions. Psychological distress was assessed with a 12-item scale. In pooled multivariable logistic regression analyses psychological distress was significantly associated with 'never voting' (not having voted previously or intending to vote in future) and 'past voting only' (having voted previously but not intending to vote in future). In stratified analyses psychological distress was linked to never voting in women and working-age adults. The significant association between psychological distress and voting was observed only in hybrid political regimes. Psychological distress is associated with a reduced likelihood of voting in FSU countries especially among women, working-age adults and those in hybrid political regimes.

Risk of depression and anxiety disorders according to long-term glycemic variability

BACKGROUND

Poor glycemic control has been linked to psychiatric symptoms. However, studies investigating the relationship between glycemic variability (GV) and depression and anxiety disorders are limited. We investigated the association of GV with depression and anxiety disorders. In addition, the relationship between trends in fasting plasma glucose (FPG) levels and these disorders were explored.

METHODS

We analyzed the National Health Insurance Service-National Sample Cohort database (2002-2013) with 151,814 participants who had at least three health screenings between 2002 and 2010. Visit-to-visit FPG variability was measured as variability independent of the mean (VIM). Depression and anxiety disorders were diagnosed using ICD-10 codes (F41 for anxiety and F32 or F33 for depression) after index date. We analyzed the association between GV and incidences of these disorders using Kaplan-Meier and Cox proportional hazards methods. Trajectory analysis was conducted to explore the relationship between FPG trends and these disorders.

RESULTS

During follow-up, 7166 and 14,149 patients were newly diagnosed with depression and anxiety disorders, respectively. The highest quartile group of FPG-VIM had a greater incidence of depression and anxiety than the lowest quartile group, with adjusted hazard ratios of 1.09 (95 % confidence interval [CI]: 1.02-1.17) and 1.08 (95 % CI: 1.03-1.14). Group with persistent hyperglycemia, identified through trajectory clustering of FPG levels, had a 1.43-fold increased risk of depression compared to those with consistently low FPG levels.

LIMITATIONS

Potential selection bias by including participants with at least three health screenings.

CONCLUSIONS

High GV and persistent hyperglycemia are associated with increased incidence of depression and anxiety disorders.

Fatigue among Patients with Type 2 Diabetes Mellitus: The Impact of Spirituality and Illness Perceptions

Type 2 Diabetes Mellitus (T2DM) can cause fatigue, negatively affecting the daily functioning and health of individuals. The purpose of this study was to investigate the impact of spirituality and illness perceptions on fatigue among patients with Type 2 Diabetes Mellitus. In this cross-sectional, descriptive study, 100 patients with Type 2 Diabetes Mellitus completed the Fatigue Assessment Scale, the FACIT Sp-12 scale, and the Illness Perception Questionnaire-Revised assessing fatigue, spirituality, and illness perceptions, respectively. The mean age of the sample was 52.18 ± 15.53 years and 65% were insulin-treated patients. The mean score for the FACIT Sp-12 scale was 31.86 ± 7.7, for the FAS 27.0 ± 7.63, and for the Consequences and Emotional Representations of IPQ-R 25.5 ± 5.3. Statistically negative significant correlations were observed between the FACIT Sp-12 total score and the FAS subscales (r = -0.44 to -0.48, p < 0.01) and positive correlations between the "IP-Consequences and Emotional Representations" subscales and FAS scores. The total score of the FACIT Sp-12 (β = -0.35) was a negative predictor while Consequences and Emotional Representations (β = 0.28) were positive predictors of the total FAS Score. Participants scored moderate levels of total fatigue. Spirituality and positive illness perceptions may have a protective effect on the fatigue of patients with Type 2 Diabetes Mellitus.

Anxiety and Depression Symptoms During the COVID-19 Pandemic: A Cluster Analysis of Individuals Living in Portugal

INTRODUCTION

The COVID-19 pandemic is an illustration of how a physical illness can damage people's minds. In this regard, the goal of this study was to see how different sociodemographic and behavioral factors were linked to anxiety and depression symptoms in a group of individuals living in Portugal.

METHODS

Between November 2020 and February 2021, a cross-sectional, snowball online study was conducted. The study's target population was adults over the age of 18, residents of the country. For the statistical analysis, the clustering technique - K-means algorithm was applied. The chi-squared test was used to determine the relationships between clusters and sociodemographic and behavioral characteristics. Statistical analyses were conducted in R language, with a significance level of 0.05. A total of 453 participants were included.

RESULTS

The majority were female (69.8%), under the age of 40 (60.8%), with a higher education degree (75.3%), and not married (54.4%). Furthermore, the majority were from the country's north region (66%). Cluster 1 (n = 194) was characterized by low or nonexistent levels of anxiety and depression symptoms, which means normal; cluster 2 by severe symptoms (n = 82), meaning case; and cluster 3 by mild symptoms (n = 177), which means borderline. Younger participants (p-value 0.024), female (p-value 0.041), with drinking habits (p-value 0.002), food insecurity (p-value < 0.001), food affordability exacerbation (p-value < 0.001), comorbidity (p-value < 0.001), use of anxiolytics (p-value < 0.001), insufficient household income (p-value 0.017) and income change (p-value < 0.001) were significantly associated with the anxiety-depression clusters. From the three clusters, cluster 2 was mainly represented by younger participants, with more persons stating that their household income was insufficient and that their income has changed as a result of COVID-19 and that they had the highest probability of food insecurity.

CONCLUSION

The impacts of a crisis on mental health extend longer than the event itself. We were able to observe that younger women with insufficient household income who suffered a change in income due to COVID-19 and were classified as food insecure presented higher levels of anxiety and depression symptoms. These results highlight the presence of a social gradient where we saw that people who were less advantaged in terms of socioeconomic position presented worse mental health outcomes, stressing, in this sense, the need to bring the best public health responses for these specific groups of the population.

Association between Grit and depressive symptoms at the timing of job start among medical residents during the COVID-19 pandemic in Japan: a cross-sectional study

INTRODUCTION

The COVID-19 pandemic had an additional negative impact on the mental health of healthcare workers, including residents. Previous studies revealed that grit, which is an individual trait to achieve long-term goals unrelated to intelligence quotient, is not only positively associated with academic achievement and career success but also negatively correlated with depression. This study aimed to examine the association between grit and depressive symptoms among residents at the time of job start during the coronavirus disease 2019 (COVID-19) pandemic in Japan.

MATERIALS AND METHODS

This cross-sectional study used data from all post-graduate year 1 residents from March 2020 to April 2022 at Tokyo Medical and Dental University, Tokyo, Japan. Grit was measured by the Japanese version of Grit-S. The resident's depressive symptoms were assessed using the Center for Epidemiologic Studies Depression Scale. The association of interest was examined using logistic regression analysis.

RESULTS

Among 221 residents, 28 (12.7%) have depressive symptoms. One unit increase in Grit-S score after adjusting for age, sex, graduated university, and sleeping hours was associated with lower odds of having depressive symptoms by 63% (odds ratio [OR]: 0.37; 95% confidence interval [CI]: 0.19-0.74). Further, the perseverance of effort subscale score was associated with lower odds of having depressive symptoms after covariate adjustment (OR: 0.43; 95% CI: 0.22-0.84).

CONCLUSIONS

Higher grit scores were associated with lower odds of having depressive symptoms among residents at the timing of job start during the COVID-19 pandemic. Regular mental health assessment is particularly important for residents with low grit scores at entry.

The possible place for psychedelics in pharmacotherapy of mental disorders

Since its emergence in the 1960s, the serotonergic theory of depression bore fruit in the discovery of a plethora of antidepressant drugs affecting the lives of millions of patients. While crucial in the history of drug development, recent studies undermine the effectiveness of currently used antidepressant drugs in comparison to placebo, emphasizing the long time it takes to initiate the therapeutic response and numerous adverse effects. Thus, the scope of contemporary pharmacological research shifts from drugs affecting the serotonin system to rapid-acting antidepressant drugs. The prototypical representative of the aforementioned class is ketamine, an NMDA receptor antagonist capable of alleviating the symptoms of depression shortly after the drug administration. This discovery led to a paradigm shift, focusing on amino-acidic neurotransmitters and growth factors. Alas, the drug is not perfect, as its therapeutic effect diminishes circa 2 weeks after administration. Furthermore, it is not devoid of some severe side effects. However, there seems to be another, more efficient, and safer way to target the glutamatergic system. Hallucinogenic agonists of the 5-HT2A receptor, commonly known as psychedelics, are nowadays being reconsidered in clinical practice, shedding their infamous 1970s stigma. More and more clinical studies prove their clinical efficacy and rapid onset after a single administration while bearing fewer side effects. This review focuses on the current state-of-the-art literature and most recent clinical studies concerning the use of psychedelic drugs in the treatment of mental disorders. Specifically, the antidepressant potential of LSD, psilocybin, DMT, and 5-MeO-DMT will be discussed, together with a brief summary of other possible applications.

Psychological responses and associated factors during the initial lockdown due to the corona disease epidemic (COVID-19) among Norwegian citizens

BACKGROUND

Ongoing COVID-19 studies pay little attention to the risk or protective factors related to psychological stress.

AIMS

This study aims to estimate the prevalence of anxiety, depression and insomnia during the initial phase of the COVID-19 outbreak, and explore factors that might be associated with these outcomes.

METHODS

A population-based cross-sectional survey was conducted using snowball-sampling strategy. Participants from 18 years or older filled out an anonymous online questionnaire.

RESULTS

A total of 4527 citizens filled out the questionnaire. Prevalence rates were; insomnia 31.8%, anxiety 17.1% and depression 12.5%. Risk factors associated with anxiety, depression and insomnia were being single (OR = 0.75, OR = 0.57, OR = 0.59), unemployed (OR = 0.47, OR = 0.53, OR = 0.73), financial concerns (OR = 1.66, OR = 2.09, OR = 1.80) at risk for complication from COVID-19 (OR = 1.63, OR = 1.68, OR = 1.60), and being generally worried due to the COVID-19 (OR 0 3.06, OR = 1.41, OR = 1.74).

CONCLUSION

Being single, unemployed, at risk of health complications, or having concerns because of financial or other consequences of the pandemic are associated with mental health adversities such as anxiety, depression and insomnia during a pandemic lockdown.

Cortical GABA Levels Are Reduced in Post-Acute COVID-19 Syndrome

After recovering from the acute COVID-19 illness, a substantial proportion of people continue experiencing post-acute sequelae of COVID-19 (PASC), also termed "long COVID". Their quality of life is adversely impacted by persistent cognitive dysfunction and affective distress, but the underlying neural mechanisms are poorly understood. The present study recruited a group of mostly young, previously healthy adults (24.4 ± 5.2 years of age) who experienced PASC for almost 6 months following a mild acute COVID-19 illness. Confirming prior evidence, they reported noticeable memory and attention deficits, brain fog, depression/anxiety, fatigue, and other symptoms potentially suggestive of excitation/inhibition imbalance. Proton magnetic resonance spectroscopy (1H-MRS) was used to examine the neurochemical aspects of cell signaling with an emphasis on GABA levels in the occipital cortex. The PASC participants were compared to a control (CNT) group matched in demographics, intelligence, and an array of other variables. Controlling for tissue composition, biological sex, and alcohol intake, the PASC group had lower GABA+/water than CNT, which correlated with depression and poor sleep quality. The mediation analysis revealed that the impact of PASC on depression was partly mediated by lower GABA+/water, indicative of cortical hyperexcitability as an underlying mechanism. In addition, N-acetylaspartate (NAA) tended to be lower in the PASC group, possibly suggesting compromised neuronal integrity. Persistent neuroinflammation may contribute to the pathogenesis of PASC-related neurocognitive dysfunction.

The beneficial effects of vortioxetine on BDNF, CREB, S100B, β amyloid, and glutamate NR2b receptors in chronic unpredictable mild stress model of depression

BACKGROUND

Depression, one of the most significant mental disorders, is still poorly understood in terms of its pathogenetic mechanisms despite its well-recognized association with stress.

OBJECTIVES

The current study's goal was to ascertain how the novel antidepressant drug vortioxetine (VOR) affected the BDNF (brain-derived neurotrophic factor), S100, amyloid β (Aβ), CREB (cAMP response element-binding protein), and NR2B, as well as its impact on depression-like behaviors, and tissue damage in an experimental rodent model of depression caused by chronic unpredictable stress.

METHODS

We employed twenty-eight Wistar albino male rats, and we randomly divided them into four groups, each consisting of 7 rats: control, CUMS (chronic unpredictable mild stress), CUMS+vortioxetine (CUMS+VOR), and CUMS+fluoxetine (CUMS+FLU). Sucrose preference and forced swimming tests (SPT and FST, respectively), PCR, ELISA, and histopathological and immunohistochemical evaluation were made on brains.

RESULTS

The behaviors of reduced immobility in the FST and increased sucrose preference were observed in the CUMS group and they improved in the groups treated with VOR and FLU. Compared with the control group, the group exposed to CUMS showed increased Aβ and decreased BDNF, CREB, and S-100 expressions, as well as neuronal degeneration (p<0.001). VOR and FLU treatment ameliorate the findings.

CONCLUSIONS

This study demonstrated significant ameliorative effects of VOR in an experimental model of chronic unpredictable depression to reduce brain tissue damage and depression-like behaviors in rats. Effects of CUMS on the brain and possible effects of VOR.

Testosterone and aging male, a perspective from a developing country

PURPOSE

Hypogonadism is associated with a wide range of physical and psychological symptoms that can affect the overall health of men. However, in a developing country, there are several imposing challenges in the diagnosis and treatment of hypogonadism, including a lack of awareness and understanding of the condition among healthcare providers and patients, limited resources and the high cost of treatment. This review aimed to examine the potential benefits and risks of testosterone replacement therapy (TRT) and provides a perspective of a developing country on the topic.

MATERIALS AND METHODS

A comprehensive literature review was conducted to gather relevant information on the impact of testosterone deficiency on ageing males and the effectiveness of TRT for treating hypogonadism. Published peer-reviewed articles were analyzed to evaluate the benefits and risks of TRT. Additionally, the unique challenges faced in the diagnosis and treatment of hypogonadism in a developing country were considered.

RESULTS

Testosterone replacement therapy has been shown to be an effective treatment for hypogonadism, particularly in symptomatic men with low testosterone levels. It offers potential benefits such as improvements in symptoms and overall quality of life. However, there are associated risks and side effects that need to be considered. In a developing country, challenges such as limited awareness and understanding of hypogonadism, resource constraints, and high treatment costs pose additional barriers to accessing TRT and comprehensive care.

CONCLUSION

In conclusion, TRT holds promise as a treatment for hypogonadism, but its implementation and accessibility face significant challenges in a developing country. Addressing these challenges, including raising awareness, allocating resources, and finding cost-effective solutions, is crucial for ensuring that men with hypogonadism in such settings receive appropriate diagnosis and treatment. Further research and efforts are needed to improve the management of hypogonadism in developing countries and optimize the potential benefits of TRT for affected individuals.

Prediction and diagnosis of depression using machine learning with electronic health records data: a systematic review

BACKGROUND

Depression is one of the most significant health conditions in personal, social, and economic impact. The aim of this review is to summarize existing literature in which machine learning methods have been used in combination with Electronic Health Records for prediction of depression.

METHODS

Systematic literature searches were conducted within arXiv, PubMed, PsycINFO, Science Direct, SCOPUS and Web of Science electronic databases. Searches were restricted to information published after 2010 (from 1st January 2011 onwards) and were updated prior to the final synthesis of data (27th January 2022).

RESULTS

Following the PRISMA process, the initial 744 studies were reduced to 19 eligible for detailed evaluation. Data extraction identified machine learning methods used, types of predictors used, the definition of depression, classification performance achieved, sample size, and benchmarks used. Area Under the Curve (AUC) values more than 0.9 were claimed, though the average was around 0.8. Regression methods proved as effective as more developed machine learning techniques.

LIMITATIONS

The categorization, definition, and identification of the numbers of predictors used within models was sometimes difficult to establish, Studies were largely Western Educated Industrialised, Rich, Democratic (WEIRD) in demography.

CONCLUSION

This review supports the potential use of machine learning techniques with Electronic Health Records for the prediction of depression. All the selected studies used clinically based, though sometimes broad, definitions of depression as their classification criteria. The reported performance of the studies was comparable to or even better than that found in primary care. There are concerns with generalizability and interpretability.

Escitalopram versus other antidepressive agents for major depressive disorder: a systematic review and meta-analysis

BACKGROUND

Escitalopram is selective serotonin reuptake inhibitors (SSRIs) and one of the most commonly prescribed newer antidepressants (ADs) worldwide. We aimed to explore the efficacy, acceptability and tolerability of escitalopram in comparison with other ADs in the acute-phase treatment of major depressive disorder (MDD).

METHODS

Medline/PubMed, EMBASE, the Cochrane Library, CINAHL, and Clinical Trials.gov were searched from inception to July 10, 2023. Trial databases of drug-approving agencies were hand-searched for published, unpublished and ongoing controlled trials. All randomized controlled trials comparing escitalopram against any other antidepressant for patients with MDD. Responders and remitters to treatment were calculated on an intention-to-treat basis. For dichotomous data, risk ratios (RRs) were calculated with 95% confidence intervals (CI). Continuous data were analyzed using standardized mean differences (with 95% CI) using the random effects model.

RESULTS

A total of 30 studies were included in this meta‑analysis, among which sixteen trials compared escitalopram with another SSRI and 14 compared escitalopram with a newer AD. Escitalopram was shown to be significantly more effective than citalopram in achieving acute response (RR 0.67, 95% CI 0.50-0.87). Escitalopram was also more effective than citalopram in terms of remission (RR 0.53, 95% CI 0.30-0.93).

CONCLUSIONS

Escitalopram was superior to other ADs for the acute phase treatment of MDD in terms of efficacy, acceptability and tolerability. However, no significant difference was found between escitalopram and other ADs in early response or follow-up response to treatment of MDD.

Association between mitochondrial DNA levels and depression: a systematic review and meta-analysis

BACKGROUND

Mitochondrial dysfunction leading to disturbances in energy metabolism has emerged as one of the risk factors in the pathogenesis of depression. Numerous studies have identified alterations in the content of mitochondrial DNA (mtDNA) in peripheral blood and cerebrospinal fluid of individuals with depression. Researchers have sought to establish a clear association between mtDNA and depression. Consequently, we conducted a comprehensive meta-analysis to assess the existing evidence regarding the impact of mtDNA on depression.

METHODS

This study conducted a thorough search of the following databases up to March 13, 2023: PubMed, Embase, the Cochrane Library, the Web of Science, Wanfang Database, SINOMED, the China Science and Technology Journal Database, and China National Knowledge Infrastructure. The meta-analysis was carried out using RevMan (version 5.4) and Stata (version 16.0) software. In addition, publication bias was assessed with funnel plots, Begg's test and Egger's test.

RESULTS

Our analysis included data from 10 articles, including 12 studies for further examination. A total of 1400 participants were included in this study, comprising 709 (including 300 males and 409 females) patients with depression and 691 (including 303 males and 388 females) healthy controls. The average age of depressed patients was (42.98 ± 2.55) years, and the average age of healthy people was (41.71 ± 2.6) years. The scales used to assess outcomes are Hamilton-rating scale for Depression(4 articles), Montgomery-Asberg Depression Rating Scale(3 articles), and Mini-Internatioal Neuropsychiatric Interview (1 articles). The meta-analysis revealed significantly higher levels of mtDNA in circulating blood samples and skin fibroblasts of individuals with depression in comparison to healthy controls [standardized mean difference(SMD) = 0.42, 95% confidence intervals(CI): 0.16, 0.67].

CONCLUSIONS

Our study concludes that there is a significant (p < 0.05) increase in mtDNA levels in serum, plasma, and cerebrospinal fluid in individuals with depression. These findings suggest that mtDNA could serve as a potential biomarker for diagnosing depression.

REGISTRATION NUMBER

PROSPERO CRD42023414285.

Network analysis of depression and anxiety symptoms in Chinese rheumatoid arthritis patients

Background

Rheumatoid arthritis (RA) patients are susceptible to comorbid anxiety and depression. From the network model perspective, comorbidity is due to direct interactions between depression and anxiety symptoms. The objective of this study was to assess the network structure of depression and anxiety symptoms in Chinese RA patients and identify the central and bridge symptoms as well as how depression and anxiety symptoms are related to quality of life (QoL) in the network.

Methods

A total of 402 Chinese RA patients were included in this study. Depression and anxiety symptoms were measured by the Hospital Anxiety and Depression Scale (HADS). R software was used to estimate the network. Specifically, we computed the predictability, expected influence (EI) and bridge expected influence (BEI) for each symptom and showed a flow network of "QoL".

Results

Our network revealed that the strongest edge was D2 "See the bad side of things" and D3 "Not feeling cheerful" across the whole network. For centrality indices, D3 "Not feeling cheerful" and D6 "Feeling down" had the highest EI values in the network, while A4 "Trouble relaxing" and D6 "Feeling down" had the highest BEI values of their respective community. As to "QoL", the strongest direct edge related to it was A1 "Nervousness".

Conclusions

"Feeling down" and "Not feeling cheerful" emerged as the strongest central symptoms, while "Trouble relaxing" and "Feeling down" were bridge symptoms in the anxiety-depression network of RA patients. Intervention on depression and anxiety symptoms in nurses should prioritize these symptoms.

Estimation of life expectancy and healthcare cost in rheumatoid arthritis patients with and without depression: a population-based retrospective cohort study

Purpose

This study aimed to estimate the lifetime healthcare costs and loss of life expectancy (loss-of-LE) among patients with incident rheumatoid arthritis (RA) with and without depression.

Methods

This 18 years longitudinal cohort study used data from Taiwan's National Health Insurance Research Database. In total, 43,311 patients with RA were included. Among them, 1,663 patients had depressive disorders in the year preceding the RA diagnosis. The survival function for patients with RA with or without depression was estimated and extrapolated over a lifetime using the rolling extrapolation algorithm. The loss-of-LE was calculated by comparing the sex, age, and calendar year-matched referents from vital statistics. The average monthly cost was calculated as the sum of the monthly costs for all patients divided by the number of surviving patients. Lifetime healthcare costs were estimated by multiplying the monthly average cost by the monthly survival probability.

Results

The loss-of-LE for RA patients with and without depression was 5.60 years and 4.76 years, respectively. The lifetime costs of RA patients with and without depression were USD$ 90,346 and USD$ 92,239, respectively. However, the annual healthcare costs were USD$ 4,123 for RA patients with depression and USD$ 3,812 for RA patients without depression. Regardless of sex or age, RA patients with depression had higher annual healthcare costs than those without depression.

Conclusion

Patients with RA and depression have a high loss-of-LE and high annual healthcare costs. Whether treating depression prolongs life expectancy and reduces healthcare costs warrants further investigation.

Psilocybin-assisted therapy for depression: A systematic review and dose-response meta-analysis of human studies

Psilocybin is increasingly studied for its antidepressant effect, but its optimal dosage for depression remains unclear. We conducted a systematic review and a dose-response meta-analysis to find the optimal dosage of psilocybin to reduce depression scores. Following our protocol (CRD 42022220190) multiple electronic databases were searched from their inception until February 2023, to identify double-blind randomized placebo-controlled (RCTs) fixed-dose trials evaluating the use of psilocybin for adult patients with primary or secondary depression. A one-stage dose-response meta-analysis with restricted cubic splines was used. Cochrane risk of bias was used to assess risk of bias. Our analysis included seven studies with a total of 489 participants. Among these, four studies focused on primary depression (N = 366), including one study with patients suffering from treatment-resistant depression. The remaining three studies examined secondary depression (N = 123). The determined 95% effective doses per day (ED95) were 8.92, 24.68, and 36.08 mg/70 kg for patients with secondary depression, primary depression, and both subgroups, respectively. We observed significant dose-response associations for all curves, each plateauing at different levels, except for the bell-shaped curve observed in the case of secondary depression. Additionally, we found significant dose-response associations for various side effects, including physical discomfort, blood pressure increase, nausea/vomiting, headache/migraine, and the risk of prolonged psychosis. In conclusion, we discovered specific ED95 values for different populations, indicating higher ED95 values for treatment-resistant depression, primary depression, and secondary depression groups. Further RCTs are necessary for each population to determine the optimal dosage, allowing for maximum efficacy while minimizing side effects.

Evaluating workforce well-being: an investigation of healthcare professionals' mental health and burnout symptoms at the Tokyo 2020 and Beijing 2022 Paralympic Games

OBJECTIVE

To explore the prevalence of symptoms of mental health conditions and burnout of healthcare professionals (HCPs) working during the Tokyo 2020 Paralympic Games and the Beijing 2022 Paralympic Winter Games.

METHODS

In this cross-sectional, observational study, HCPs working during the Tokyo 2020 and Beijing 2022 Paralympic Games were asked to complete an online, anonymous survey, which included demographic questions and questions regarding mental health symptoms including depression (Patient Health Questionnaire 9-item depression scale) and anxiety (Generalized Anxiety Disorder 7-item scale) as well as burnout (Maslach Burnout Inventory-Human Services Survey: depersonalisation, emotional exhaustion, personal accomplishment). Correlation coefficients (r) were calculated between demographic characteristics and mental health symptoms.

RESULTS

In total, 256 HCPs (of 857 HCPs; 30%) completed the surveys. Twelve and eight per cent of HCP scores fell within the moderate to severe depression and moderate to severe anxiety categories, respectively. More than 30% reported moderate to high burnout (depersonalisation: 36%; emotional exhaustion: 36%; personal accomplishment: 58%). In addition, thoughts of self-harm and/or suicidality were reported by some HCPs (8%). Weak correlations were observed between age and depression (r=-0.13, p=0.046), anxiety (r=-0.16, p=0.010) and burnout (emotional exhaustion: r=-0.14, p=0.032; personal accomplishment: r=0.27, p<0.001).

CONCLUSION

Although most HCPs reported good mental health, this study suggests that a subset of HCPs experienced symptoms of depression, anxiety, burnout or thoughts of self-harm during the Tokyo 2020 and Beijing 2022 Paralympic Games. While the generalisability of these findings outside of COVID-19 restrictions should be tested, appropriate guidance and mental health support of HCPs leading up to the Paralympic Games should be prioritised.

Immunometabolic alterations in older adults with heightened depressive symptom trajectories: a network approach

Objective: To analyse the patterns of relationships between depressive symptoms and immunometabolic markers across longitudinal depression status in older people. Methods: A sample of 3349 older adults (55.21% women; initial age: m = 58.44, sd = 5.21) from the English Longitudinal Study of Ageing was used. Participants were classified according to their longitudinal depression status: minimal depressive symptoms (n = 2736), depressive episode onset (n = 481), or chronic depression (n = 132). Network analysis was used to study the relationships between depression symptoms (CES-D 8 items), inflammatory (white blood cell, C-reactive protein, fibrinogen) and metabolic biomarkers (metabolic syndrome markers). Results: Network structure remained invariant across groups. The minimal symptom group had higher overall strength than both clinical groups (p < .01). Moreover, significant relationships between symptoms and markers were observed across group-specific networks. C-reactive protein and effort symptom were positively connected in the minimal symptom group but not in the other groups. Loneliness and diastolic blood pressure were positively associated only in the chronic depression group. Finally, metabolic markers were identified as central nodes in the clinical status networks. Conclusion: The network analysis constitutes a useful approach to disentangle pathophysiological relationships that may maintain mental disorders in old age.

Fluoxetine combined with swimming exercise synergistically reduces lipopolysaccharide-induced depressive-like behavior by normalizing the HPA axis and brain inflammation in mice

Major depression disorder is a debilitating psychiatric disease affecting millions of people worldwide. This disorder is the leading cause of morbidity and mortality in high-income countries. Selective serotonin reuptake inhibitors such as fluoxetine are first-line drugs for treating depression-related disorders, but not all patients respond well to these antidepressants. This study aimed to evaluate whether fluoxetine combined with aerobic exercise can affect lipopolysaccharide (LPS)-induced depressive-like behavior, hypothalamic-pituitary-adrenal (HPA) axis dysregulation, and brain inflammation in mice. Male mice were exposed to fluoxetine, swimming exercise, or a combination of both and finally treated with LPS. We measured depression-related symptoms such as anhedonia, behavioral despair, weight gain, and food intake. Hormones (corticosterone and testosterone) and cytokines (IL-1β, IL-6, TNF-α, IL-10) were also measured in serum and brain (hippocampus and prefrontal cortex), respectively. The findings indicated that LPS induced anhedonia and behavioral despair and increased corticosterone, hippocampal IL-1β, TNF-α, and decreased testosterone and hippocampal IL-10 in mice. Fluoxetine and exercise separately reduced LPS-induced depressive-like behavior, while their combination synergistically reduced these symptoms in LPS-treated mice. We found fluoxetine alone increased food intake and body weight in LPS-treated mice. Fluoxetine and exercise combination reduced corticosterone, hippocampal TNF-α, and prefrontal IL-6 and TNF-α levels and increased testosterone and hippocampal and prefrontal IL-10 levels more effectively than fluoxetine alone in LPS-treated mice. This study suggests that swimming exercise combined with fluoxetine can affect depression-related behavior, HPA axis, and brain inflammation more effectively than when they are used separately.

Evaluation of Thiol/Disulfide Interrelation in Major Depressive Disorder

Objective

Although major depressive disorder (MDD) constitutes a significant part of mental health problems, its pathogenesis has not been fully elucidated. The inadequacy of diagnostic tests specific to MDD causes difficulty in diagnosis. Therefore, we investigated the situation of thiol/disulfide imbalance, which may play a role in the pathogenesis of many diseases, in MDD patients.

Methods

Forty-five MDD patients and 40 non-patient volunteers participated in our study. Sociodemographic data form, Beck Depression Scale, and Clinical Global Impression Scale were used in making the diagnosis and evaluation process.

Results

There was a significant difference between the MDD and non-patient groups in native thiol and total thiol levels, disulfide/native thiol, disulfide/total thiol, and native thiol/total thiol ratios. No significant difference was detected in terms of disulfide level between the 2 groups. There was no significant difference between the patients' thiol disulfide ratios and the severity of depression. There was no significant difference between the patients' symptom duration and thiol disulfide ratios. Nevertheless, a negative correlation was identified between the duration of the patients' symptoms and their disulfide levels.

Conclusion

When the results were examined in terms of thiol and disulfide ratios, they showed that thiol and disulfide ratios were impaired in depression. We think that thiol/disulfide parameters may be a biomarker candidate that can help in the diagnosis of MDD.

Prevalence and variability of depressive symptoms in Europe: update using representative data from the second and third waves of the European Health Interview Survey (EHIS-2 and EHIS-3)

BACKGROUND

Assessing the prevalence of clinically relevant depressive symptoms and their possible variation by country and over time could be a valuable resource to inform the development of public health policies and preventive resources to reduce mental health burden. We aimed to assess cross-national differences in the point prevalence of clinically relevant depressive symptoms in Europe in 2018-20, and to evaluate point prevalence differences between countries and over time between 2013-15 and 2018-20.

METHODS

In this population-based study, data from participants in the second and third waves of the European Health Interview Survey (EHIS-2 from 2013 to 2015 and EHIS-3 from 2018 to 2020) from 30 European countries were used (n=542 580). From the total sample, 283 692 participants belonging to EHIS-3 were included in the study (52·4% women and 47·5% men). The non-response in EHIS-3 ranged by country, from 12% to 78%. Point prevalence of clinically relevant depressive symptoms was evaluated using a cutoff score of 10 or more for the 8-item version of the Patient Health Questionnaire. Crude prevalence ratios and adjusted prevalence ratios (aPRs) were obtained to assess differences in the prevalence between countries and over time within countries.

FINDINGS

The point prevalence of clinically relevant depressive symptoms in Europe in 2018-20 was 6·54% (95% CI 6·34-6·73), ranging across countries from 1·85% (1·53-2·17) in Greece to 10·72% (10·04-11·40) in Sweden. Compared with the other European countries, those with the lowest aPRs were Greece, Serbia, and Cyprus and those with the highest aPRs were Belgium, Slovenia, and Croatia. A small but significant increase in the prevalence between EHIS-2 and EHIS-3 was observed (aPR 1·11 [1·07-1·14]). A wide variability over time in the point prevalence within countries was observed, ranging from an aPR of 0·63 (0·54-0·74) in Hungary to 1·88 (1·53-2·31) in Slovenia.

INTERPRETATION

This study, based on large and representative datasets and a valid and reliable screening tool for the assessment of depression, indicates that the point prevalence of clinically relevant depressive symptoms in Europe from 2013 to 2020 remains relatively stable, with wide variability between countries. These findings could be considered a baseline for monitoring the prevalence of clinically relevant depressive symptoms in Europe, and could inform policy for the development of preventive strategies for depression both at a country and European level.

FUNDING

Center for Biomedical Research in Epidemiology and Public Health Network and AGAUR.

Loneliness and depression: bidirectional mendelian randomization analyses using data from three large genome-wide association studies

Major depression (MD) is a serious psychiatric illness afflicting nearly 5% of the world's population. A large correlational literature suggests that loneliness is a prospective risk factor for MD; correlational assocations of this nature may be confounded for a variety of reasons. This report uses Mendelian Randomization (MR) to examine potentially causal associations between loneliness and MD. We report on analyses using summary statistics from three large genome wide association studies (GWAS). MR analyses were conducted using three independent sources of GWAS summary statistics. In the first set of analyses, we used available summary statistics from an extant GWAS of loneliness to predict MD risk. We used two sources of outcome data: the Psychiatric Genomics Consortium (PGC) meta-analysis of MD (PGC-MD; N = 142,646) and the Million Veteran Program (MVP-MD; N = 250,215). Finally, we reversed analyses using data from the MVP and PGC samples to identify risk variants for MD and used loneliness outcome data from UK Biobank. We find robust evidence for a bidirectional causal relationship between loneliness and MD, including between loneliness, depression cases status, and a continuous measure of depressive symptoms. The estimates remained significant across several sensitivity analyses, including models that account for horizontal pleiotropy. This paper provides the first genetically-informed evidence that reducing loneliness may play a causal role in decreasing risk for depressive illness, and these findings support efforts to reduce loneliness in order to prevent or ameliorate MD. Discussion focuses on the public health significance of these findings, especially in light of the SARS-CoV-2 pandemic.

Fear of COVID-19 Predicts Depression, Anxiety and Post-Traumatic Stress Disorders in Patients with Implantable Cardioverter Defibrillators and Is Mediated by Positive and Negative Affects-A Cross-Sectional Study

The COVID-19 pandemic affected both the physical and mental health of the general population. People with cardiac diseases seem to be particularly vulnerable to the implications of the pandemic. However, studies on the mental health impact of the COVID-19 pandemic on people with implantable cardioverter defibrillator (ICDs) are lacking. Thus, we aimed to explore the level of fear of COVID-19 and the prevalence of anxiety, depression and post-traumatic stress disorder (PTSD) in ICD patients. Furthermore, we aimed to identify novel predictors for anxiety, depression and PTSD, including COVID-19-related variables, and to assess whether positive affects (PAs) and negative affects (NAs) mediate the relationship between the level of fear of COVID-19 and anxiety, depression and PTSD, respectively. The data of 363 patients with ICDS who had been prospectively included in this study between 2020 and 2023, were analyzed. Potential predictors for anxiety, depression, and PTSD were identified using logistic regression. To identify indirect mediating effects of PAs and NAs, we applied the PROCESS regression path analysis modeling tool. The prevalence of anxiety was 9.19%, of depression 10.85%, and of PTSD 12.99%. Being unemployed was the strongest predictor for anxiety (OR = 10.39) and depression (OR = 6.54). Younger age predicted anxiety (OR = 0.95) and PTSD (OR = 0.92). Receiving low social support was associated with anxiety (OR = 0.91), depression (OR = 0.88) and PTSD (OR = 0.91). Patients with a history of COVID-19 (OR = 3.58) and those who did not feel well-informed about COVID-19 (OR = 0.29) were more likely to be depressed. Higher levels of fear of COVID-19 predicted anxiety (OR = 1.10), depression (OR = 1.12) and PTSD (OR = 1.14). The relationship between fear of COVID-19 and anxiety or depression was fully mediated by PAs and NAs, while NAs partially mediated the relationship between fear of COVID-19 and PTSD. Vulnerable subgroups of ICD patients may need additional psychological and educational interventions due to fear of COVID-19, anxiety, depression and PTSD during the pandemic.

The Mental Health Implications of Corporate Social Responsibility: The Significance of the Sense-Making Process and Prosocial Motivation

As corporate social responsibility (CSR) has progressively ascended to prominence among academics and industry professionals, numerous studies have embarked on examining its impact on employees' perceptions, attitudes, and behaviors. Notwithstanding, the current body of research has predominantly overlooked the influence of CSR on employees' mental health, encompassing depression, anxiety, and burnout. In order to acknowledge the critical role of employee mental health within an organization, our exploration is focused on discerning the effect of CSR on depressive states. Furthermore, our paper undertakes a thorough analysis of the link between CSR and depression, probing its underlying processes and potential contingent factors. We posit that CSR can alleviate the incidence of employee depression by amplifying the sense of meaningfulness that work provides. Moreover, the element of prosocial motivation among employees may act as a positive moderating variable that intensifies the beneficial effect of CSR on the sense of meaningfulness derived from work. By relying on data obtained through a tripartite online survey involving 214 South Korean workers, this paper scrutinized the proposed hypotheses via the application of moderated mediation analysis with structural equation modeling. We contend that the insights yielded by this study bear significant theoretical and practical implications.

Prefrontal Glutathione Levels in Major Depressive Disorder Are Linked to a Lack of Positive Affect

Major depressive disorder (MDD) is one of the most common neuropsychiatric disorders, with symptoms including persistent sadness and loss of interest. MDD is associated with neurochemical alterations in GABA, glutamate, and glutamine levels but, to date, few studies have examined changes in glutathione (GSH) in MDD. This study investigated changes in GSH in an unmedicated group of young adults, including 46 participants with current (n = 12) or past MDD (n = 34) and 20 healthy controls. Glutathione levels were assessed from GSH-edited magnetic resonance (MR) spectra, acquired from a voxel in the left prefrontal cortex, and depressive symptoms were evaluated with validated questionnaires and clinical assessments. Cortisol levels were also assessed as a marker for acute stress. Participants with current MDD demonstrated elevated GSH in comparison to participants with past MDD and controls, although the results could be influenced by differences in tissue composition within the MRS voxel. In addition, participants with both current and past MDD showed elevated cortisol levels in comparison to controls. No significant association was observed between GSH and cortisol levels, but elevated GSH levels were associated with a decrease in positive affect. These results demonstrate for the first time that elevated GSH in current but not past depression may reflect a state rather than a trait neurobiological change, related to a loss of positive affect.

Activation of mTORC1 Signaling Cascade in Hippocampus and Medial Prefrontal Cortex Is Required for Antidepressant Actions of Vortioxetine in Mice

BACKGROUND

Although thought of as a multimodal-acting antidepressant targeting the serotonin system, more molecules are being shown to participate in the antidepressant mechanism of vortioxetine. A previous report has shown that vortioxetine administration enhanced the expression of rapamycin complex 1 (mTORC1) in neurons. It has been well demonstrated that mTORC1 participates in not only the pathogenesis of depression but also the pharmacological mechanisms of many antidepressants. Therefore, we speculate that the antidepressant mechanism of vortioxetine may require mTORC1.

METHODS

Two mouse models of depression (chronic social defeat stress and chronic unpredictable mild stress) and western blotting were first used together to examine whether vortioxetine administration produced reversal effects against the chronic stress-induced downregulation in the whole mTORC1 signaling cascade in both the hippocampus and medial prefrontal cortex (mPFC). Then, LY294002, U0126, and rapamycin were used together to explore whether the antidepressant effects of vortioxetine in mouse models of depression were attenuated by pharmacological blockade of the mTORC1 system. Furthermore, lentiviral-mTORC1-short hairpin RNA-enhanced green fluorescence protein (LV-mTORC1-shRNA-EGFP) was adopted to examine if genetic blockade of mTORC1 also abolished the antidepressant actions of vortioxetine in mice.

RESULTS

Vortioxetine administration produced significant reversal effects against the chronic stress-induced downregulation in the whole mTORC1 signaling cascade in both the hippocampus and mPFC. Both pharmacological and genetic blockade of the mTORC1 system notably attenuated the antidepressant effects of vortioxetine in mice.

CONCLUSIONS

Activation of the mTORC1 system in the hippocampus and mPFC is required for the antidepressant actions of vortioxetine in mice.

Efficacy and safety of a vitamin-mineral intervention for symptoms of anxiety and depression in adults: A randomised placebo-controlled trial "NoMAD"

BACKGROUND

Anxiety and depression are increasingly burdening society. We investigated whether micronutrients (vitamins and minerals), improve anxiety and depression symptoms in an adult community setting.

METHODS

Participants (n = 150) describing functionally-impairing symptoms of anxiety/depression randomly received micronutrients or placebo for 10 weeks. Primary outcome measures were Patient Health Questionnaire-9 (PHQ-9), Generalised Anxiety Disorder Scale-7 (GAD-7), and Clinical Global Impression-Improvement scale (CGII). They were monitored online with regular phone contact with a clinical psychologist.

RESULTS

Linear mixed-effects modelling showed significant improvements in both groups, with the micronutrient group improving significantly more quickly on both the PHQ-9 (t = -2.17, p = 0.03) and the GAD-7 (t = -2.23, p = 0.03). Subsequent models with covariates showed that participant characteristics moderated time-by-group interactions; micronutrients provided fastest improvement relative to placebo for younger participants, those from lower socioeconomic groups and those who had previously tried psychiatric medication. On the CGII, there were no group differences at end-point ((F1,148) = 1.36, p = 0.25, d = 0.19, 95 % CI [-0.13 to 0.51]), with 49 % of the micronutrient and 44 % of the placebo groups being identified responders. Participants on micronutrients had significantly increased bowel motions compared with placebo. There was no increased suicidal ideation, no serious adverse events and the blind was adequately maintained. Drop out was low at 8.7 %.

LIMITATIONS

The improvement under placebo and lack of formal diagnoses limit generalizability.

CONCLUSIONS

Despite limited clinician contact, all participants improved significantly, though improvements were faster with micronutrients. Participants in some subgroups demonstrated a lower response to placebo, identifying where micronutrients may offer greatest potential as an intervention.

Patient characteristics, validity of clinical diagnoses and Outcomes Associated with Suicidality in Inpatients with Symptoms of Depression (OASIS-D): design, procedures and outcomes

BACKGROUND

Suicidality, ranging from passive suicidal thoughts to suicide attempt, is common in major depressive disorder (MDD). However, relatively little is known about patient, illness and treatment characteristics in those with co-occurring MDD and suicidality, including the timing of and factors associated with the offset, continuation or reemergence of suicidality. Here, we present the background, rationale, design and hypotheses of the Patient Characteristics, Validity of Clinical Diagnoses and Outcomes Associated with Suicidality in Inpatients with Symptoms of Depression (OASIS-D) study, an investigator-initiated, observational study, funded by Janssen-Cilag GmbH.

METHODS/RESULTS

OASIS-D is an eight-site, six-month, cohort study of patients aged 18-75 hospitalized with MDD. Divided into three sub-studies and patient populations (PPs), OASIS-D will (i) systematically characterize approximately 4500 consecutively hospitalized patients with any form of unipolar depressive episode (PP1), (ii) evaluate the validity of the clinical diagnosis of moderate or severe unipolar depressive episode with the Mini-International Neuropsychiatric Interview (M.I.N.I.) and present suicidality (at least passive suicidal thoughts) present ≥ 48 h after admission with the Sheehan-Suicide Tracking Scale (S-STS), assessing also predictors of the diagnostic concordance/discordance of MDD in around 500 inpatients (PP2), and (iii) characterize and prospectively follow for 6 months 315 inpatients with a research-verified moderate or severe unipolar depressive episode and at least passive suicidal thoughts ≥ 48 h after admission, evaluating treatment and illness/response patterns at baseline, hospital discharge, 3 and 6 months. Exploratory objectives will describe the association between the number of days with suicidality and utilization of outpatient and inpatient care services, and structured assessments of factors influencing the risk of self-injurious behavior without suicidal intent, and of continuous, intermittent or remitted suicidality during the 6-month observation period.

CONCLUSION

Despite their frequency and clinical relevance, relatively little is known about patient and treatment characteristics of individuals with MDD and suicidality, including factors moderating and mediating the outcome of both MDD and suicidality. Results of the OASIS-D study are hoped to improve the understanding of the frequency, correlates and 6-month naturalistic treatment and outcome trajectories of different levels of suicidality in hospitalized adults with MDD and suicidality.

TRIAL REGISTRATION

NCT04404309 [ClinicalTrials.gov].

Looking Beyond the Chair: Psycho-Perceptual Predictors of Sexual Distress and Sexual Satisfaction in Individuals with Spinal Cord Injury

Despite a large body of biomedical research, little is known about the psychological and perceptual predictors of sexual satisfaction (SS) and sexual distress (SD) post spinal cord injury (SCI). Guided by a bio-psycho-perceptual framework, this cross-sectional research aimed at assessing SS and SD in a large SCI sample using validated patient-reported outcome measures (PROM). Significant correlates and predictors of SS and SD were also identified. Ninety-one men and women with SCI completed PROMs of SS and SD, as well as psychological (mood, sexual and body esteem) and perceptual (interoceptive awareness, trait mindfulness, sexual mindfulness) factors. Neurological profiles were also assessed, along with experience of orgasm. Correlates of SS and SD were first identified using Pearson's correlations, then multiple hierarchical regression models were computed to isolate predictors. Orgasm experience and psychological factors emerged as moderate correlates of both SS and SD, while neurological factors did not. Interoceptive awareness and trait mindfulness showed weak associations with SD and none with SS. Among the tested predictors, experience of orgasm emerged as the strongest for SS (β = -.29, p < .01), followed by mood, which predicted SS and SD. Sexual and body esteem was predictive of SD only. In sexually active participants, sexual mindfulness predicted both SS (β = 0.55, p < .001) and SD (β = -0.56, p < .001) above and beyond all other variables. This study reveals unique aspects of SS and SD postinjury and supports further consideration of psychological and perceptual dimensions of SCI sexuality in rehabilitation research.

Dynamics of depressive states among university students in Japan during the COVID-19 pandemic: an interrupted time series analysis

BACKGROUND

The coronavirus disease 2019 (COVID-19) pandemic was reported to have increased depression among university students which was associated with impairments in their campus lives. This study examined changes in depressive states among Japanese university students during the COVID-19 pandemic.

METHODS

A secondary data analysis from a factorial randomized controlled trial involving smartphone-based cognitive-behavioral therapy was performed. Six cohorts (N = 1626) underwent an 8-week intervention during the spring or autumn of 2019-2021, with a 9-month follow-up. We evaluated participants' depressive states weekly using the Patient Health Questionnaire-9 (PHQ-9) during the intervention, with monthly evaluations thereafter. The follow-up periods included Japan's four states of emergency (SOEs) to control COVID-19. Hypothesizing that SOEs caused a sudden worsening of depressive states, Study 1 compared the cohorts' PHQ-9 scores, and Study 2 employed time series analysis with a mixed-effects model to estimate identified changes in PHQ-9 scores.

RESULTS

Although no changes in depressive states were observed in relation to the SOEs, Study 1 identified sudden increases in PHQ-9 scores at the 28-week evaluation point, which corresponded to the beginning of the new academic year for the three autumn cohorts. In contrast, the three spring cohorts did not exhibit similar changes. Study 2 showed that, for all three autumn cohorts (n = 522), the 0.60-point change was significant (95% CI 0.42-0.78; p < .001) at 28 weeks; that is, when their timeline was interrupted.

CONCLUSIONS

While the results do not indicate any notable impact of the SOEs, they highlight the influence of the new academic year on university students' mental health during COVID-19. Trial registration UMIN, CTR-000031307. Registered on February 14, 2018.

The Role of the Adrenal-Gut-Brain Axis on Comorbid Depressive Disorder Development in Diabetes

Diabetic patients are more affected by depression than non-diabetics, and this is related to greater treatment resistance and associated with poorer outcomes. This increase in the prevalence of depression in diabetics is also related to hyperglycemia and hypercortisolism. In diabetics, the hyperactivity of the HPA axis occurs in parallel to gut dysbiosis, weakness of the intestinal permeability barrier, and high bacterial-product translocation into the bloodstream. Diabetes also induces an increase in the permeability of the blood-brain barrier (BBB) and Toll-like receptor 4 (TLR4) expression in the hippocampus. Furthermore, lipopolysaccharide (LPS)-induced depression behaviors and neuroinflammation are exacerbated in diabetic mice. In this context, we propose here that hypercortisolism, in association with gut dysbiosis, leads to an exacerbation of hippocampal neuroinflammation, glutamatergic transmission, and neuronal apoptosis, leading to the development and aggravation of depression and to resistance to treatment of this mood disorder in diabetic patients.

Effective connectivity between deep brain stimulation targets in individuals with treatment-resistant depression

The therapeutic effect of deep brain stimulation on patients with treatment-resistant depression is strongly dependent on the connectivity of the stimulation region with other regions associated with depression. The aims of this study are to characterize the effective connectivity between the brain regions playing important roles in depression and further investigate the underlying pathophysiological mechanisms of treatment-resistant depression and the mechanisms involving deep brain stimulation. Thirty-three individuals with treatment-resistant depression and 29 healthy control subjects were examined. All subjects underwent resting-state functional MRI scanning. The coupling parameters reflecting the causal interactions among deep brain stimulation targets and medial prefrontal cortex were estimated using spectral dynamic causal modelling. Our results showed that compared to the healthy control subjects, in the left hemisphere of treatment-resistant depression patients, the nucleus accumbens was inhibited by the inferior thalamic peduncle and excited the ventral caudate and the subcallosal cingulate gyrus, which in turn excited the lateral habenula. In the right hemisphere, the lateral habenula inhibited the ventral caudate and the nucleus accumbens, both of which inhibited the inferior thalamic peduncle, which in turn inhibited the cingulate gyrus. The ventral caudate excited the lateral habenula and the cingulate gyrus, which excited the medial prefrontal cortex. Furthermore, these effective connectivity links varied between males and females, and the left and right hemispheres. Our findings suggest that intrinsic excitatory/inhibitory connections between deep brain stimulation targets are impaired in treatment-resistant depression patients, and that these connections are sex dependent and hemispherically lateralized. This knowledge can help to better understand the underlying mechanisms of treatment-resistant depression, and along with tractography, structural imaging, and other relevant clinical information, may assist to determine the appropriate region for deep brain stimulation therapy in each treatment-resistant depression patient.

Efficacy and acceptability of third-wave psychotherapies in the treatment of depression: a network meta-analysis of controlled trials

Introduction

In recent decades, various new psychotherapy approaches have been developed in an effort to overcome issues of non-response, referred to as "third-wave psychotherapies." How third-wave therapies perform in comparison to each other, to classical CBT, or other common comparators in the treatment of depression has not yet been systematically assessed.

Methods

We firstly determined the scope of the term "third-wave" by conducting a systematic search. The identified approaches were then used as search terms for the systematic review and network meta-analysis (NMA). We searched MEDLINE, CENTRAL, PsychINFO and Web of Science from inception until 31 July 2022. We assessed randomized controlled trials comparing third-wave psychotherapies to each other, CBT, treatment as usual (TAU), medication management, active control conditions, or waitlist (WL) in adult populations with depressive disorders. The treatments included were acceptance and commitment therapy, behavioral activation, cognitive behavioral analysis system of psychotherapy, dialectical behavioral therapy, mindfulness-based cognitive therapy, meta-cognitive therapy, positive psychotherapy and schema therapy. The primary outcome was depression severity (efficacy) at study endpoint, and the secondary outcome was all-cause discontinuation (acceptability). This review was registered in PROSPERO, identifier CRD42020147535.

Results

Of 7,971 search results, 55 trials were included in our NMA (5,827 patients). None of the third-wave therapies were more efficacious than CBT but most were superior to TAU [standardized mean differences (SMD) ranging between 0.42 (95% CI -0.37; 1.19) and 1.25 (0.48; 2.04)]. Meta-cognitive therapy (MCT) was more efficacious than three other third-wave therapy approaches. None of the third-wave treatments were more acceptable than WL or CBT. Twenty-seven percent of the trials were rated as low risk of bias. Confidence in the evidence was largely low according to GRADE. Inconsistency emerged for a small number of comparisons.

Interpretations

Third-wave therapies are largely efficacious and acceptable alternatives to CBT when compared to TAU, with few differences between them. The evidence so far does not point toward superiority or inferiority over CBT. Patient-level research may offer possibilities for tailoring individual psychotherapies to the needs of individual patients and future trials should make this data available. The evidence base needs to be broadened by sufficiently powered trials.

Reduced homovanillic acid, SDF-1α and SCGF-β levels in cerebrospinal fluid are related to depressive states in systemic lupus erythematosus

OBJECTIVE

This study aimed to seek a new method of evaluation and surrogate markers for diffuse neuropsychiatric SLE (NPSLE).

METHODS

We enrolled 44 patients with SLE between 2017 and 2020 who fulfilled at least one of three specific inclusion criteria: high disease activity, abnormal findings (cerebrospinal fluid [CSF] examination, brain MRI, or electroencephalography), or history of neuropsychiatric illness. Psychiatric symptom rating scales (PSYRATS) were evaluated retrospectively. The primary end point was the PSYRATS positivity rate in SLE patients who had not been diagnosed with diffuse NPSLE.

RESULTS

Based on the 1999 ACR classifications, 7 out of the 44 patients evaluated using PSYRATS had been diagnosed with diffuse NPSLE. PSYRATS positivity was seen in 13 out of 37 SLE patients (35.1%) who had not been diagnosed with diffuse NPSLE, and all these patients were positive for Montgomery-Åsberg Depression Rating Scale (MADRS), an indicator of depression state in PSYRATS. Additionally, in the 20 SLE patients exhibiting depression symptoms who were MADRS-positive, CSF concentrations of the neuroinflammatory markers homovanillic acid (HVA; P = 0.0400), stromal cell-derived factor-1α (SDF-1α; P = 0.0431) and stem cell growth factor-β (SCGF-1β; P = 0.0061) were significantly reduced compared with the 24 MADRS-negative SLE patients, and the levels of HVA, SDF-1α and SCGF-1β correlated with one another (P < 0.05).

CONCLUSION

Many patients with active SLE have subclinical depression, and MADRS evaluation of neuropsychiatric symptoms is useful for detecting them. Additionally, the decrease in CSF levels of HVA, SDF-1 α and SCGF-1β reflects the same pathology, and these may serve as surrogate markers.

Importance of different electronic medical record components for chronic disease identification in a Swiss primary care database: a cross-sectional study

BACKGROUND

Primary care databases collect electronic medical records with routine data from primary care patients. The identification of chronic diseases in primary care databases often integrates information from various electronic medical record components (EMR-Cs) used by primary care providers. This study aimed to estimate the prevalence of selected chronic conditions using a large Swiss primary care database and to examine the importance of different EMR-Cs for case identification.

METHODS

Cross-sectional study with 120,608 patients of 128 general practitioners in the Swiss FIRE ("Family Medicine Research using Electronic Medical Records") primary care database in 2019. Sufficient criteria on three individual EMR-Cs, namely medication, clinical or laboratory parameters and reasons for encounters, were combined by logical disjunction into definitions of 49 chronic conditions; then prevalence estimates and measures of importance of the individual EMR-Cs for case identification were calculated.

RESULTS

A total of 185,535 cases (i.e. patients with a specific chronic condition) were identified. Prevalence estimates were 27.5% (95% CI: 27.3-27.8%) for hypertension, 13.5% (13.3-13.7%) for dyslipidaemia and 6.6% (6.4-6.7%) for diabetes mellitus. Of all cases, 87.1% (87.0-87.3%) were identified via medication, 22.1% (21.9-22.3%) via clinical or laboratory parameters and 19.3% (19.1-19.5%) via reasons for encounters. The majority (65.4%) of cases were identifiable solely through medication. Of the two other EMR-Cs, clinical or laboratory parameters was most important for identifying cases of chronic kidney disease, anorexia/bulimia nervosa and obesity whereas reasons for encounters was crucial for identifying many low-prevalence diseases as well as cancer, heart disease and osteoarthritis.

CONCLUSIONS

The EMR-C medication was most important for chronic disease identification overall, but identification varied strongly by disease. The analysis of the importance of different EMR-Cs for estimating prevalence revealed strengths and weaknesses of the disease definitions used within the FIRE primary care database. Although prioritising specificity over sensitivity in the EMR-C criteria may have led to underestimation of most prevalences, their sex- and age-specific patterns were consistent with published figures for Swiss general practice.

Screening for Anxiety in Patients With Inflammatory Arthritis Using the Multidimensional Health Assessment Questionnaire

OBJECTIVE

To analyze the Multidimensional Health Assessment Questionnaire (MDHAQ) in screening for anxiety in patients with rheumatoid arthritis (RA) and psoriatic arthritis (PsA), compared to the Hospital Anxiety and Depression Scale (HADS) as the reference standard.

METHODS

Patients with a physician diagnosis of RA or PsA were invited to complete the MDHAQ and HADS at their routine rheumatology clinic visit. Sensitivity, specificity, percent agreement, and [Formula: see text] statistics were used to evaluate agreement between 2 MDHAQ items for anxiety and HADS subscale for Anxiety (HADS-A) score of ≥ 8. The first item is a question asked on a 4-point scale (0-3.3), and the second is a yes or no (blank) question asked within a 60-item review of symptoms (ROS) checklist.

RESULTS

The study included 183 participants, of whom 126 (68.9%) had RA and 57 (31.1%) had PsA. The mean age was 57.3 years and 66.7% were female. Positive screening for anxiety according to a HADS-A score of ≥ 8 was seen in 39.3% of patients. Compared to those with a HADS-A score of ≥ 8, patients with an MDHAQ score of ≥ 2.2 or a positive on ROS had a sensitivity of 69.9%, specificity of 73.6% and substantial agreement (agreement 80.9%, [Formula: see text] 0.59).

CONCLUSION

The MDHAQ provides information similar to the HADS in screening for anxiety in patients with RA and PsA. The use of this single questionnaire, which can also be used to monitor clinical status and to screen for fibromyalgia and depression without requiring multiple questionnaires, may prove a valuable tool in routine clinical practice.

Neuroinflammation: A Modifiable Pathway Linking Obesity, Alzheimer's disease, and Depression

Obesity, depression and Alzheimer's disease (AD) are three major interrelated modern health conditions with complex relationships. Early-life depression may serve as a risk factor for AD, while late-life depression may be a prodrome of AD. Depression affects approximately 23% of obese individuals, and depression itself raises the risk of obesity by 37%. Mid-life obesity independently increases AD risk, while late-life obesity, particularly metabolically healthy obesity, may offer protection against AD pathology. Chronic inflammation serves as a key mechanism linking obesity, AD, and depression, encompassing systemic inflammation from metabolic disturbances, immune dysregulation through the gut microbiome, and direct interactions with amyloid pathology and neuroinflammation. In this review, we explore the biological mechanisms of neuroinflammation in relation to obesity, AD, and depression. We assess the efficacy of therapeutic interventions targeting neuroinflammation and discuss current and future radiological imaging initiatives for studying neuroinflammation. By comprehending the intricate interplay among depression, obesity, and AD, especially the role of neuroinflammation, we can advance our understanding and develop innovative strategies for prevention and treatment.

Prevalence of depressive disorder in the adult population of Latin America: a systematic review and meta-analysis

Background

Depressive disorder is one of the leading causes of disability worldwide; however its prevalence and association with inequality and crime is poorly characterised in Latin America. This study aimed to: i. systematically review population-based studies of prevalence of ICD/DSM depressive disorder in Latin America, ii. report pooled regional, country, and sex-specific prevalence estimates, and iii. test its association with four country-level development indicators: human development (HDI), income (Gini) and gender inequality (GII), and intentional homicide rate (IHR).

Methods

We conducted a systematic review and meta-analysis of population-based studies reporting primary data on the prevalence of ICD/DSM depressive disorder in Latin America from 1990 to 2023, irrespective of language. We searched PubMed, PsycINFO, Cochrane Library, SciELO (regional database), LILAC (regional database), and available grey literature. Study quality was assessed using JBI's critical appraisal tools. We generated pooled estimates using random-effects meta-analysis; heterogeneity was assessed using the I2 statistic. Meta-regression analyses were used to test associations of depression prevalence with indicators of inequality and human development. The study was registered with PROSPERO (CRD42019143054).

Findings

Using data from 40 studies in Latin America, lifetime, 12-month, and current prevalence of ICD/DSM depressive disorder were calculated at 12.58% (95% CI 11.00%-14.16%); 5.30% (4.55-6.06%), and 3.12% (2.22-4.03), respectively. Heterogeneity was high across lifetime, 12-month, and current prevalence, sex, and countries. 12-month and current prevalence was associated with higher Gini and GII, 12-month prevalence with lower HDI, and current prevalence with higher IHR.

Interpretation

We found a high prevalence of ICD/DSM depressive disorders in Latin America, and a statistically significant association with inequality and development indicators. The high heterogeneity found across prevalence periods and the major gaps in country representation underscore the need to escalate efforts to improve mental health access and research capabilities in Latin America. Systematic, comparable prevalence estimates would inform more effective decision-making in the region.

Funding

Pfizer Independent Medical Education Grant.