European Journal of Cardiovascular Medicine

Depression and anxiety represent two of the most common mental health disorders worldwide, affecting millions of individuals and posing significant healthcare challenges. These disorders can profoundly impact an individual's functioning and quality of life, leading to increased morbidity and mortality. Despite the known prevalence in the general population, depression and anxiety remain under-diagnosed and under-treated, particularly in non-psychiatric healthcare settings.[1]

Recent literature suggests that general medicine outpatients experience higher rates of depression and anxiety compared to the general population. These conditions often coexist with chronic medical illnesses, complicating treatment outcomes and worsening the disease burden. However, comprehensive data specifically quantifying the prevalence of these conditions among general medicine outpatients are sparse, particularly in tertiary care settings. This gap in data underscores the necessity for targeted research to understand the scope of these mental health challenges within this patient population.[2]

Screening for depression and anxiety in general medical settings is crucial as it provides an opportunity for early detection, intervention, and integration of care, which could improve patient outcomes significantly. The integration of mental health care with general medical practice is recommended by various health organizations globally. It is essential to explore the prevalence and implications of these conditions among general medicine outpatients to facilitate the development of effective healthcare strategies that address both physical and psychological aspects of patient health.[3]

Aim

To determine the prevalence of depression and anxiety among outpatients attending a general medicine clinic.

Objectives

1. To quantify the prevalence of depression in general medicine outpatients using the Patient Health Questionnaire (PHQ-9).
2. To quantify the prevalence of anxiety in general medicine outpatients using the Generalized Anxiety Disorder (GAD-7) scale.
3. To assess the comorbidity of depression and anxiety in this patient population.

Source of Data: The data was collected from patients attending the general medicine outpatient department at a tertiary care hospital.

Study Design: A cross-sectional analysis was conducted.

Study Location: The study was carried out at a tertiary care hospital in the outpatient department of general medicine.

Study Duration: The study was conducted from January 2022 to December 2022.

Sample Size: The study included 200 patients who visited the general medicine outpatient clinic during the study period.

Inclusion Criteria: Patients aged 18 years and above, attending the general medicine clinic, and consenting to participate were included.

Exclusion Criteria: Patients with severe cognitive impairments, those who were critically ill, and patients with a prior diagnosed psychiatric condition being treated were excluded from the study.

Procedure and Methodology: Eligible patients were administered the PHQ-9 and GAD-7 scales during their visit. Information was collected through face-to-face interviews and review of medical records.

Sample Processing: Not applicable as the study involved psychiatric assessment scales without biological samples.

Statistical Methods: Data were analyzed using descriptive statistics. Prevalence rates were calculated as percentages. Chi-square tests were used for testing associations between categorical variables.

Data Collection: Data were collected using structured questionnaires administered by trained healthcare professionals. Patient confidentiality was maintained throughout the study, and data were anonymized before analysis.

Table 1: Prevalence of Depression and Anxiety Among Outpatients

Table 2: Prevalence of Depression Using the PHQ-9

Table 3: Prevalence of Anxiety Using the GAD-7 Scale

Table 4: Comorbidity of Depression and Anxiety

The findings in Table 1, which show a 35% prevalence of depression and 30% of anxiety among general medicine outpatients, align with similar studies indicating high prevalence rates of these disorders in general medical settings. For instance, a study by van Dijk DA et al.(2023) [4] reported comparable rates, suggesting a significant overlap between physical health issues and mental health disorders. The odds ratios calculated emphasize a significant association and risk of these conditions in the outpatient setting, echoing findings from Faraj SS et al.(2023)[5] who observed that depression and anxiety significantly affect morbidity and quality of life in outpatients.

This table illustrates a graded increase in odds ratios with increasing severity of depression, a finding consistent with the systematic review by Doering S et al.(2023),[6] which confirmed that higher PHQ-9 scores correlate with greater disability and poorer health outcomes. The significant P-values for moderately severe and severe depression highlight critical points where depressive symptoms begin substantially impacting patient health, supporting the need for targeted interventions, as demonstrated in the research by Chen YH et al.(2023).[7]

The gradient increase in odds ratios for anxiety levels mirrors the trend observed in depression. The statistical significance of mild and severe anxiety underscores their impact on functional outcomes. This distribution is in line with the findings by Reinauer C et al.(2023),[8] who found that higher GAD-7 scores are strongly associated with greater impairment in daily living. The high prevalence of minimal anxiety suggests that many patients manage to keep their symptoms at a manageable level, potentially obscuring the need for clinical interventions. Zhang X et al.(2023)[9]

The substantial percentage of patients suffering from both depression and anxiety (20%) and the associated high odds ratio support the literature indicating a high degree of comorbidity between these conditions. The study by Bouchard V et al.(2023)[10] reflects similar observations, where patients with comorbid conditions tend to have more severe symptoms and poorer prognosis, making the case for integrated treatment approaches.

The cross-sectional analysis conducted to determine the prevalence of depression and anxiety among general medicine outpatients reveals significant findings that underscore the importance of integrating mental health services with general medical care. The study demonstrates that a considerable proportion of outpatients experience depression (35%) and anxiety (30%), with a noteworthy 20% of the patient population suffering from both conditions concurrently. These rates are substantially higher than those generally reported in the broader community, highlighting the specific vulnerabilities of individuals seeking general medical services.

The use of standardized diagnostic tools, the Patient Health Questionnaire (PHQ-9) for depression and the Generalized Anxiety Disorder (GAD-7) scale for anxiety, provided robust measures that confirmed the high prevalence of these mental health disorders. The findings from the study, supported by statistically significant odds ratios and confidence intervals, suggest that depression and anxiety are critical issues that can potentially impact the overall health outcomes and quality of life of outpatients.

This study's implications are profound, indicating a pressing need for routine screening for depression and anxiety in general medical settings. Early detection and treatment of these conditions can lead to better patient management and improved outcomes. Furthermore, the high comorbidity rates of depression and anxiety advocate for a more holistic approach to patient care, where mental health is considered integral to physical health.

By addressing these conditions proactively, healthcare providers can not only improve the efficacy of treatment for physical ailments but also enhance the overall well-being of their patients. The study reinforces the call for policy changes and resource allocation to support the integration of mental health services in general medical practices, ensuring a comprehensive healthcare model that effectively addresses the intertwined nature of physical and mental health.

1. Cross-Sectional Design: The inherent nature of the cross-sectional study design restricts the ability to determine causality between observed mental health conditions and patient characteristics or outcomes. This design only captures a snapshot in time, limiting the understanding of the progression and potential fluctuations in mental health status over time.
2. Self-Report Measures: The study relied heavily on self-reported data through the PHQ-9 and GAD-7 scales. While these are validated tools, they are subject to bias, including social desirability bias and recall bias, which might result in underreporting or overreporting of symptoms.
3. Sample Size and Generalizability: With a sample size of 200 patients, the findings may not be sufficiently generalizable to all general medicine outpatients, especially across different geographic or cultural settings. Larger, more diverse study populations are needed to enhance the generalizability of the results.
4. Single Setting: Data were collected from a single tertiary care center, which may limit the applicability of the results to other types of medical centers or outpatient clinics, including those in rural or underserved areas.
5. Exclusion Criteria: The exclusion of patients with prior diagnosed psychiatric conditions being treated might have resulted in an underestimation of the true prevalence of depression and anxiety in the outpatient setting, as these individuals often visit general medicine clinics.
6. Lack of Clinical Corroboration: The study did not include clinical evaluations or follow-ups to corroborate the self-reported data with clinical assessments, which could provide a more comprehensive picture of the mental health conditions.
7. Potential Confounders: There may have been additional confounding variables not controlled for in the study, such as socioeconomic status, the severity of physical health conditions, and access to mental health care, which could influence the prevalence rates of depression and anxiety.
8. Non-response Bias: The possibility of non-response bias exists if the individuals who chose not to participate were different in terms of their mental health status from those who did participate, potentially skewing the results.

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