Effects of Pandemic on Feelings of Depression in Italy: The Role of Age, Gender, and Individual Experiences During the First Lockdown

Associations Between Psychopathological Symptom Severity Amid the Pandemic and the Childhood Sociodemographic Environment

It is well-documented that childhood socioeconomic status (SES) is associated with various health conditions in adulthood. Here, we examine the extent to which childhood SES is associated with COVID-19 pandemic anxiety and depression. Participants (n = 212), recruited from Amazon Mechanical Turk, were assessed for depression and anxiety in February 2022 for both the current context and retrospective self-perceived early pandemic depression and anxiety (April 2020). Participants also reported childhood SES and current demographics. Consistent with predated findings, we show a strong, positive correlation between depression and anxiety under both conditions. Paternal unemployment in childhood was associated with increased anxiety, while maternal occupation was not. High household education in childhood was generally associated with greater anxiety and depression, similar to past studies examining education levels and depression. However, the shift from high school to post-secondary degrees (trade school and associate's) was associated with decreased anxiety and depression, which may reflect "essential work" careers, therefore indicating a dualism. Growing up in crowded, de-individualized spaces was associated with lower anxiety and depression, suggesting better conditioning for the imposition of COVID-19 quarantines. Pandemic-related unemployment was associated with an increase in anxiety and depression. Strong political views, regardless of ideology, were associated with increased anxiety. Finally, participants in our cohort perceived their mental health to be worse in the early pandemic for anxiety and depression, up 6.6% and 7.9%, respectively. Our work suggests a complex relationship between SES, demographics, and anxiety and depression during the pandemic. These findings emphasize the importance of exploring the dynamics between early SES and mental health in adulthood, particularly during extended societal stressors.

Deepening Depression in Women Balancing Work-Life Responsibilities and Caregiving during the COVID-19 Pandemic: Findings from Gender-Specific Face-to-Face Street Interviews Conducted in Italy

PURPOSE

This study investigated the impact of the COVID-19 pandemic on mental health, quality of life, and family functioning in a sample of the general female population, exploring difficulties encountered in managing family and work responsibilities and burden of care when taking care of a loved one. This study was, moreover, aimed at investigating factors capable of influencing severe depressive symptomatology in the context of socio-demographics, traumatic events, individual vulnerability, and family functioning.

METHOD

The sampling method used in this research was non-probability sampling. The survey took place during a Hospital Open Weekend (8-10 October 2021) organized by the National Gender Observatory on Women's Health "Fondazione Onda" on the occasion of the World Mental Health Day.

RESULTS

A total of 211 women were interviewed (mean age = 35.6, 53% living alone, more than 15% with financial difficulties, 47% exposed to the 2009 L'Aquila earthquake). More than 50% of the sample reported a higher complexity in managing their lives during the COVID-19 pandemic compared to their previous routine, with no statistically significant differences between working women and non-workers, although the latter obtained higher scores for depressive symptomatology and poorer quality of life. Compared to non-caregivers, female caregivers (22.3%) in charge of the care of loved ones affected by physical (10.9%) or psychiatric disabilities (11.4%) complained of a poorer quality of life, especially in general health perception (p = 0.002), physical function (p = 0.011), role limitations related to physical problems (p = 0.017), bodily pain (p = 0.015), mental health (p = 0.004), and social functioning (p = 0.007). Women caring for people affected by mental disorders seemed to experience a more significant worsening in vitality (p = 0.003) and social functioning (p = 0.005). Approximately 20% of the total sample reported severe depressive symptomatology. Previous access to mental health services (O.R. 10.923; p = 0.000), a low level of education (O.R. 5.410; p = 0.021), and difficulties in management of everyday lives during the COVID-19 pandemic (O.R. 3.598; p = 0.045) were found to be the main variables predictive of severe depressive psychopathology. Old age, good problem-solving skills, and ability to pursue personal goals were identified as protective factors.

CONCLUSIONS

The COVID-19 pandemic underlined the need for support amongst emotionally vulnerable women with pre-existing mental health conditions, partly reflecting the cumulative effects of traumas.

The evolution of research on depression during COVID-19: A visual analysis using Co-Occurrence and VOSviewer

Background

The COVID-19 pandemic has led to public health problems, including depression. There has been a significant increase in research on depression during the COVID-19 pandemic. However, little attention has been paid to the overall trend in this field based on bibliometric analyses.

Methods

Co-Occurrence (COOC) and VOSviewer bibliometric methods were utilized to analyze depression in COVID-19 literature in the core collection of the Web of Science (WOS). The overall characteristics of depression during COVID-19 were summarized by analyzing the number of published studies, keywords, institutions, and countries.

Results

A total of 9,694 English original research articles and reviews on depression during COVID-19 were included in this study. The United States, China, and the United Kingdom were the countries with the largest number of publications and had close cooperation with each other. Research institutions in each country were dominated by universities, with the University of Toronto being the most productive institution in the world. The most frequently published author was Ligang Zhang. Visualization analysis showed that influencing factors, adverse effects, and coping strategies were hotspots for research.

Conclusion

The results shed light on the burgeoning research on depression during COVID-19, particularly the relationship between depression and public health. In addition, future research on depression during COVID-19 should focus more on special groups and those at potential risk of depression in the general population, use more quantitative and qualitative studies combined with more attention to scale updates, and conduct longitudinal follow-ups of the outcomes of interventions. In conclusion, this study contributes to a more comprehensive view of the development of depression during COVID-19 and suggests a theoretical basis for future research on public health.

First-onset major depression during the COVID-19 pandemic: A predictive machine learning model

BACKGROUND

This study longitudinally evaluated first-onset major depression rates during the pandemic in Italian adults without any current clinician-diagnosed psychiatric disorder and created a predictive machine learning model (MLM) to evaluate subsequent independent samples.

METHODS

An online, self-reported survey was released during two pandemic periods (May to June and September to October 2020). Provisional diagnoses of major depressive disorder (PMDD) were determined using a diagnostic algorithm based on the DSM criteria of the Patient Health Questionnaire-9 to maximize specificity. Gradient-boosted decision trees and the SHapley Additive exPlanations technique created the MLM and estimated each variable's predictive contribution.

RESULTS

There were 3532 participants in the study. The final sample included 633 participants in the first wave (FW) survey and 290 in the second (SW). First-onset PMDD was found in 7.4% of FW participants and 7.2% of the SW. The final MLM, trained on the FW, displayed a sensitivity of 76.5% and a specificity of 77.8% when tested on the SW. The main factors identified in the MLM were low resilience, being an undergraduate student, being stressed by pandemic-related conditions, and low satisfaction with usual sleep before the pandemic and support from relatives. Current smoking and taking medication for medical conditions also contributed, albeit to a lesser extent.

LIMITATIONS

Small sample size; self-report assessment; data covering 2020 only.

CONCLUSIONS

Rates of first-onset PMDD among Italians during the first phases of the pandemic were considerable. Our MLM displayed a good predictive performance, suggesting potential goals for depression-preventive interventions during public health crises.