Abstract
This study assesses the prevalence of anxiety and identify its influencing factors among patients under observation in the emergency department of a large tertiary care hospital, aiming to inform targeted psychological interventions. A cross-sectional study was conducted between March and November 2023, involving 98 patients who met the inclusion criteria. Anxiety levels were measured using the Generalized Anxiety Disorder-7 scale. Univariate and multivariate logistic regression analyses were performed to determine the association between anxiety and demographic or clinical variables. Among the participants, 32 patients (32.7%) exhibited anxiety symptoms, with 18 (18.4%) classified as mild, 10 (10.2%) as moderate, and 4 (4.1%) as severe. Multivariate analysis identified age 40 to 59 years (OR = 1.861, P = .007), high school education (OR = 2.809, P = .012), musculoskeletal disorders (OR = 5.07, P = .003), and high perceived illness severity (OR = 3.785, P = .004) as independent predictors of anxiety. Anxiety is prevalent among emergency department patients, particularly those aged 40 to 59, with high school education, musculoskeletal disorders, or perceived severe illness. Routine anxiety screening and targeted psychological support for these high-risk groups are recommended to improve mental health and overall care outcomes in emergency settings.
Keywords: anxiety, emergency department, GAD-7, influencing factors, patients on admission
1. Introduction
The emergency department plays a crucial role in hospitals, handling emergent conditions and acutely ill patients.[1] With the increasing pace of modern life and an aging population, the workload and complexity of cases in the emergency department have significantly risen.[2] During diagnosis and treatment, many patients experience psychological stress and anxiety due to the sudden onset of illness, severity of their condition, and uncertainty about waiting times.[3] Anxiety not only impacts patients’ mental health but can also negatively affect their physical condition, potentially delaying recovery and increasing healthcare resource utilization.[4]
In recent years, research on the psychological state of emergency department patients has gradually increased.[5] For instance, Gagliardi et al reported a 30% to 40% prevalence of anxiety symptoms among emergency department patients, with a positive correlation between waiting time and anxiety levels.[6] However, systematic studies on anxiety and its influencing factors in patients held for observation in the emergency department remain limited. Patients under observation often wait in the emergency observation room for further treatment decisions, a process that can be prolonged and characterized by uncertainty about their condition and a lack of family or social support.[7] Anxiety in these patients is not only a concern for their physical and mental health but also presents challenges for hospital emergency management.
Anxiety, a common negative emotional response, is often triggered by uncertainty and stress, impacting an individual’s well-being through various psychological and physiological mechanisms.[8] In patients retained in the emergency department, anxiety may be influenced by several factors, including demographic characteristics (e.g., age, gender, education level), clinical factors (e.g., type and severity of illness), and social support.[9] Anxiety can be assessed using standardized tools such as the Generalized Anxiety Disorder-7 (GAD-7) scale, with levels categorized as mild, moderate, or severe to facilitate detailed analysis of contributing factors.[10]
This cross-sectional study aimed to assess anxiety levels among patients admitted to the emergency department of a large tertiary hospital and analyze the factors influencing anxiety. Through systematic investigation and analysis, the study identifies key factors affecting patient anxiety, which holds significant theoretical and practical value for improving service quality in the emergency department and enhancing the patient experience.
2. Methodology
2.1. Study design
This study was approved by the Ethics Committee of West China Hospital. This study utilizes a cross-sectional design to systematically investigate and analyze the anxiety levels and influencing factors among patients in the emergency department of a large local tertiary hospital from March to November 2023. The study has received approval from the hospital ethics committee, and informed consent will be obtained from all participants. Participant privacy will be strictly protected, and all collected data will be anonymized.
2.2. Study population
This study was conducted in the emergency department of a large tertiary care hospital, with data collected from March to November 2023. A total of 98 patients admitted to the emergency department were included. Inclusion criteria were: aged 18 years or older, staying in the emergency department for at least 1 hour, providing voluntary informed consent, able to communicate effectively in Mandarin, and without a history of severe cognitive impairment or psychiatric illness. Exclusion criteria included: severe cognitive impairment or mental illness, critical illness or coma, severe hearing or speech impairment preventing communication, refusal to participate or failure to sign informed consent, repeat admissions, or special medical needs.
2.3. Collection of data
Data were collected using a structured questionnaire that included demographic details, healthcare-related information, and an anxiety assessment scale. Researchers obtained the data from patients after their admission, either through face-to-face interviews or self-completion of the questionnaires, ensuring standardization and consistency in data collection. All questionnaires were completed during the patient’s hospital stay to minimize any potential impact on their mood. Collected information included demographics such as age, gender, marital status, education level, occupation, income, and residence. Medical information gathered included duration of stay, type of illness, comorbidities, first-time admission, and health insurance status.
2.4. Assessment protocol
In this study, the GAD-7 scale was used to assess anxiety. The GAD-7 is a simple and validated self-assessment tool designed to screen and evaluate symptoms of GAD. It consists of 7 items, each addressing a different anxiety symptom experienced over the past 2 weeks, such as persistent worry, uncontrollable worry, irritability, and muscle tension. Each item is rated on a four-point scale from 0 (not at all) to 3 (almost daily), with a maximum score of 21. Higher scores indicate more severe anxiety, and a threshold of 10 typically denotes moderate anxiety, warranting further clinical evaluation. The GAD-7 categorizes anxiety levels as follows: 0 to 4 (no or very mild anxiety), 5 to 9 (mild anxiety), 10 to 14 (moderate anxiety), and 15 to 21 (severe anxiety). The GAD-7 is widely used in primary care, psychiatry, counseling, and research due to its brevity, ease of use, and strong reliability and validity, making it particularly effective as an initial screening tool to identify patients needing further intervention.
2.5. Variables
Main variables: anxiety level, categorized based on the GAD-7 scale score (0–4 as no or very mild anxiety, 5–9 as mild anxiety, 10–14 as moderate anxiety, 15–21 as severe anxiety). Independent variables included demographic factors: age, gender, marital status, education level, occupation, income, and place of residence. Medical-related factors included length of stay, type of illness, comorbidities, first-time admission, and health insurance status. Table 4 outlines how each variable was assigned to facilitate subsequent statistical analyses.
Table 4.
The assignment of independent variables.
| Independent variable | Variable name | Assignment description |
|---|---|---|
| Age (years) | X1 | ≤39 = 1, 40–59 = 2, 60–79 = 3, ≥80 = 4 |
| Educational level | X2 | Primary school or below = 1, junior high school = 2, senior high school = 3, university or above = 4 |
| Disease type | X3 | Circulatory system diseases = 1, musculoskeletal diseases = 2, respiratory diseases = 3, digestive system diseases = 4, hematological diseases = 5, urinary system diseases = 6, endocrine and metabolic diseases = 7, neurological diseases = 8, other = 9 |
| Self-perceived severity of disease | X4 | Mild = 1, moderate = 2, severe = 3 |
| Anxiety | Y | Yes = 1, no = 0 |
3. Results
3.1. Basic demographic and disease-related characteristics
This study included 98 patients admitted to the emergency department of a large tertiary hospital. The age distribution was: 18 patients (18.37%) ≤39 years, 30 patients (30.61%) aged 40–59 years, 35 patients (35.71%) aged 60–79 years, and 15 patients (15.31%) ≥80 years. In terms of gender, 32 (32.65%) were female and 66 (67.35%) were male. Most patients were married, with 71 (72.45%) married, 7 (7.14%) unmarried, 12 (12.24%) divorced, and 8 (8.16%) widowed. Educational levels included 15 patients (15.31%) with primary education or below, 35 (35.71%) with junior high school, 38 (38.78%) with senior high school, and 11 (11.22%) with university education or above. Occupational distribution showed 36 (36.73%) were farmers or migrant workers, 16 (16.33%) were company employees, 13 (13.27%) were civil servants or institution employees, 6 (6.12%) were freelancers, and 28 (28.57%) were unemployed or retired. Regarding place of residence, 79 patients (80.61%) were from urban areas and 19 (19.39%) from rural areas. Monthly household income distribution was: 19 patients (19.39%) with < RMB 4000/month, 56 (57.14%) with RMB 4000 to 8000/month, and 24 (24.49%) with > RMB 8000/month. Medical insurance status was as follows: 6 patients (6.12%) were self-funded, 16 (16.33%) had New Rural Co-operative Medical Care, 64 (65.31%) had urban medical insurance, and 12 (12.24%) had employees’ health insurance.
In terms of disease types, there were 36 patients (36.73%) with musculoskeletal diseases, 22 (22.45%) with respiratory diseases, 16 (16.33%) with digestive diseases, 4 (4.08%) with hematological diseases, 13 (13.27%) with circulatory diseases, 5 (5.1%) with urinary diseases, 3 (3.06%) with endocrine and metabolic diseases, and 1 (1.02%) with neurological diseases. Additionally, 1 patient (1.02%) had other diseases. Regarding disease awareness, 34 patients (34.69%) were unaware of their condition, 50 (51.02%) were partially aware, 11 (11.22%) were aware, and 5 (5.1%) were very aware. The self-perceived severity of illness was reported as mild by 9 patients (9.18%), moderate by 56 (57.14%), and severe by 34 (34.69%). For comorbidities, 38 patients (38.78%) had none, 45 (45.92%) had 1 to 2 comorbidities, and 17 (17.35%) had 3 or more. There were 36 patients (36.73%) admitted for the first time and 62 (63.27%) with previous admissions. Regarding length of observation, 8 patients (8.16%) stayed ≤ 12 hours, 49 (50%) stayed 12.01 to 24 hours, 15 (15.31%) stayed 24.01 to 36 hours, 9 (9.18%) stayed 36.01 to 48 hours, 6 (6.12%) stayed 48.01 to 60 hours, 7 (7.14%) stayed 60.01 to 72 hours, and 4 (4.08%) stayed > 72 hours. See Table 1 for details.
Table 1.
Demographic and related data of emergency observation patients (N = 98).
| Independent variable | Group | Number (n) | Percentage (%) |
|---|---|---|---|
| Age (years) | ≤39 | 18 | 18.37 |
| 40–59 | 30 | 30.61 | |
| 60–79 | 35 | 35.71 | |
| ≥80 | 15 | 15.31 | |
| Gender | Female | 32 | 32.65 |
| Male | 66 | 67.35 | |
| Marital status | Unmarried | 7 | 7.14 |
| Married | 71 | 72.45 | |
| Divorced | 12 | 12.24 | |
| Widowed | 8 | 8.16 | |
| Educational level | Primary school or below | 15 | 15.31 |
| Junior high school | 35 | 35.71 | |
| Senior high school | 38 | 38.78 | |
| University or above | 11 | 11.22 | |
| Occupation | Farmers or migrant workers | 36 | 36.73 |
| Company employees | 16 | 16.33 | |
| Civil servants or public institution employees | 13 | 13.27 | |
| Freelancers | 6 | 6.12 | |
| Unemployed or retired | 28 | 28.57 | |
| Residence | Urban | 79 | 80.61 |
| Rural | 19 | 19.39 | |
| Average monthly household income | <4000 CNY/month | 19 | 19.39 |
| 4000–8000 CNY/month | 56 | 57.14 | |
| >8000 CNY/month | 24 | 24.49 | |
| Medical insurance status | Self-paid | 6 | 6.12 |
| New rural cooperative medical scheme | 16 | 16.33 | |
| Urban medical insurance | 64 | 65.31 | |
| Employee health insurance | 12 | 12.24 | |
| Disease type | Musculoskeletal diseases | 36 | 36.73 |
| Respiratory diseases | 22 | 22.45 | |
| Digestive system diseases | 16 | 16.33 | |
| Hematological diseases | 4 | 4.08 | |
| Circulatory system diseases | 13 | 13.27 | |
| Urinary system diseases | 5 | 5.1 | |
| Endocrine and metabolic diseases | 3 | 3.06 | |
| Neurological diseases | 1 | 1.02 | |
| Other | 1 | 1.02 | |
| Disease awareness | Unaware | 34 | 34.69 |
| Somewhat aware | 50 | 51.02 | |
| Aware | 11 | 11.22 | |
| Very aware | 5 | 5.1 | |
| Self-perceived severity of disease | Mild | 9 | 9.18 |
| Moderate | 56 | 57.14 | |
| Severe | 34 | 34.69 | |
| Number of comorbidities | None | 38 | 38.78 |
| 1–2 | 45 | 45.92 | |
| ≥3 | 17 | 17.35 | |
| First time under observation | Yes | 36 | 36.73 |
| No | 62 | 63.27 | |
| Observation duration (hours) | ≤12.00 | 8 | 8.16 |
| 12.01–24.00 | 49 | 50 | |
| 24.01–36.00 | 15 | 15.31 | |
| 36.01–48.00 | 9 | 9.18 | |
| 48.01–60.00 | 6 | 6.12 | |
| 60.01–72.00 | 7 | 7.14 | |
| >72.00 | 4 | 4.08 |
3.2. Anxiety level
Among patients under observation, 32 (32.65%) experienced anxiety, while 66 (67.35%) did not, with a mean anxiety score of 2.61 ± 0.62. The distribution of anxiety severity was as follows: 18 patients (18.37%, 7.23 ± 0.39) had mild anxiety, 10 (10.20%, 11.56 ± 0.33) had moderate anxiety, and 4 (4.08%, 18.69 ± 1.01) had severe anxiety (Table 2, Figs. 1A, and 2A).
Table 2.
Anxiety levels of emergency department observation patients (N = 98).
| Independent variable | Group | Number (n) | Percentage (%) |
|---|---|---|---|
| Anxiety | |||
| Yes | 32 | 32.65 | |
| No | 66 | 67.35 | |
| Degree of anxiety | |||
| Mild | 18 | 18.37 | |
| Moderate | 10 | 10.20 | |
| Severe | 4 | 4.08 |
Figure 1.
(A) The anxiety score via GAD-7.
Figure 2.
(A) Composition of anxiety Pie chart.
3.3. Univariate analysis of the distribution of anxiety by basic demographic and disease-related characteristics
Univariate analysis of the 32 patients with anxiety showed that age, education level, type of illness, and self-perceived severity of illness were significantly associated with anxiety (Table 3). The highest prevalence of anxiety was observed in the 40 to 59 age group, at 56.67%, significantly higher than other age groups (χ²=7.953, P = .047). Anxiety was most prevalent among those with a high school education level, at 60.53%, which was significantly higher than other education levels (χ²=8.22, P = .042). Patients with musculoskeletal disorders had an anxiety prevalence of 61.11%, significantly higher than those with other systemic disorders (χ²=7.613, P = .006). Patients with severe self-perceived illness had an anxiety prevalence of 61.76%, significantly higher compared to those with mild or moderate conditions (χ²=7.443, P = .024). Other variables, including gender, marital status, occupation, place of residence, income, health insurance, disease perception, comorbidities, first-time stay, and length of observation, were not significantly correlated with anxiety levels.
Table 3.
Univariate analysis of anxiety in emergency department observation patients (N = 32).
| Independent variable | Group | Number (N) | Percentage (%) | χ2 | P value |
|---|---|---|---|---|---|
| Age (years) | ≤39 | 3 | 16.67 | 7.953 | .047 |
| 40–59 | 17 | 56.67 | |||
| 60–79 | 9 | 25.71 | |||
| ≥80 | 3 | 20.00 | |||
| Gender | Female | 9 | 28.13 | 2.472 | .116 |
| Male | 23 | 34.85 | |||
| Marital status | Unmarried | 1 | 14.29 | 0.64 | .887 |
| Married | 25 | 35.21 | |||
| Divorced | 4 | 33.33 | |||
| Widowed | 2 | 25.00 | |||
| Educational level | Primary school or below | 2 | 13.33 | 8.22 | .042 |
| Junior high school | 5 | 14.29 | |||
| Senior high school | 23 | 60.53 | |||
| University or above | 2 | 18.18 | |||
| Occupation | Farmers or migrant workers | 16 | 44.44 | 1.451 | .228 |
| Company employees | 4 | 25.00 | |||
| Civil servants or public institution employees | 3 | 23.08 | |||
| Freelancers | 1 | 16.67 | |||
| Unemployed or retired | 8 | 28.57 | |||
| Residence | Urban | 27 | 34.18 | 0.173 | .677 |
| Rural | 5 | 26.32 | |||
| Average monthly household income | <4000 CNY/month | 3 | 15.79 | 3.588 | .166 |
| 4000–8000 CNY/month | 25 | 44.64 | |||
| >8000 CNY/month | 4 | 16.67 | |||
| Medical insurance status | Self-paid | 1 | 16.67 | 0.148 | .700 |
| New rural cooperative medical scheme | 5 | 31.25 | |||
| Urban medical insurance | 23 | 35.94 | |||
| Employee health insurance | 3 | 25.00 | |||
| Disease type | Musculoskeletal diseases | 22 | 61.11 | 7.613 | .006 |
| Respiratory diseases | 6 | 27.27 | |||
| Digestive system diseases | 2 | 12.50 | |||
| Hematological diseases | 0 | 0.00 | |||
| Circulatory system diseases | 1 | 7.69 | |||
| Urinary system diseases | 1 | 20.00 | |||
| Endocrine and metabolic diseases | 0 | 0.00 | |||
| Neurological diseases | 0 | 0.00 | |||
| Other | 0 | 0.00 | |||
| Disease awareness | Unaware | 5 | 14.71 | 0.131 | .717 |
| Somewhat aware | 23 | 46.00 | |||
| Aware | 3 | 27.27 | |||
| Very aware | 1 | 20.00 | |||
| Self-perceived severity of disease | Mild | 2 | 22.22 | 7.443 | .024 |
| Moderate | 9 | 16.07 | |||
| Severe | 21 | 61.76 | |||
| Number of comorbidities | None | 8 | 21.05 | 2.254 | .324 |
| 1–2 | 20 | 44.44 | |||
| ≥3 | 4 | 23.53 | |||
| First time under observation | Yes | 14 | 38.89 | 0.369 | .544 |
| No | 18 | 29.03 | |||
| Observation duration (hours) | ≤12.00 | 1 | 12.50 | 0.184 | .668 |
| 12.01–24.00 | 16 | 32.65 | |||
| 24.01–36.00 | 7 | 46.67 | |||
| 36.01–48.00 | 3 | 33.33 | |||
| 48.01–60.00 | 2 | 33.33 | |||
| 60.01–72.00 | 2 | 28.57 | |||
| >72.00 | 1 | 25.00 |
2.6. Statistical analyses
All data analyses were conducted using SPSS 25.0, with a significance level set at P < .05. Descriptive statistics were used to summarize the basic characteristics of the sample and the distribution of anxiety levels, presented as frequencies and percentages. Univariate analyses were performed using chi-square tests or t tests to compare anxiety levels between groups and screen for potential influencing factors (see Table 3). Multivariate regression analysis was conducted using logistic regression models to assess the independent effects of multiple factors on anxiety, controlling for confounding variables and identifying significant predictors.
3.4. Multivariate logistic regression analysis of factors associated with anxiety distribution
With depression as the dependent variable, variables found significant in univariate analysis were included in the multivariate logistic regression model. The values assigned to the independent variables are shown in Table 4. The specific results were as follows: Regarding age, the risk of anxiety was significantly higher in the 40 to 59 years group (OR = 1.861, 95% CI: 1.182–2.928, P = .007) compared to the ≤39 years group; however, the 60 to 79 years group (OR = 1.793, 95% CI: 0.487–6.605, P = .379) and the ≥80 years group (OR = 1.524, 95% CI: 0.539–4.305, P = .427) were not significantly associated with anxiety. For education level, the high school group had a significantly higher risk of anxiety (OR = 2.809, 95% CI: 1.251–6.308, P = .012) compared to the primary school or below group, while the middle school group (OR = 1.141, 95% CI: 0.838–1.554, P = .403) and the university and above group (OR = 1.324, 95% CI: 0.943–1.859, P = .104) were not significantly associated with anxiety. In terms of disease type, musculoskeletal disorders significantly increased the risk of anxiety (OR = 5.07, 95% CI: 1.709–15.026, P = .003) compared to circulatory disorders, whereas other disease types (respiratory, digestive, etc) were not significantly associated with anxiety. Regarding self-perceived disease severity, the risk of anxiety was significantly higher in the severe perception group (OR = 3.785, 95% CI: 1.519–9.433, P = .004) compared to the mild perception group; no significant association was found in the moderate perception group (OR = 0.538, 95% CI: 0.266–1.086, P = .083). For details, see Table 5. In conclusion, multivariate analysis indicated that being aged 40 to 59 years, having a high school education, having musculoskeletal disorders, and perceiving the disease as severe were independent factors influencing anxiety in patients admitted to the emergency department.
Table 5.
Unconditional logistic regression analysis of factors influencing anxiety in the study population.
| Independent variable | Group | β | SE | Wald χ² | P | OR | 95% CI |
|---|---|---|---|---|---|---|---|
| Age (years, with < 39 years as reference) | 40–59 | 0.621 | 0.231 | 7.205 | .007 | 1.861 | 1.182–2.928 |
| 60-79 | 0.584 | 0.665 | 0.772 | .379 | 1.793 | 0.487–6.605 | |
| ≥80 | 0.421 | 0.53 | 0.632 | .427 | 1.524 | 0.539–4.305 | |
| Educational level (with primary school or below as reference) | Junior high school | 0.132 | 0.158 | 0.7 | .403 | 1.141 | 0.838–1.554 |
| Senior high school | 1.033 | 0.413 | 6.252 | .012 | 2.809 | 1.251–6.308 | |
| University or above | 0.281 | 0.173 | 2.642 | .104 | 1.324 | 0.943–1.859 | |
| Disease type (with circulatory system disease as reference) | Musculoskeletal diseases | 1.623 | 0.555 | 8.556 | .003 | 5.07 | 1.709–15.026 |
| Respiratory diseases | 0.828 | 0.75 | 1.221 | .269 | 2.289 | 0.526–9.950 | |
| Digestive system diseases | 0.329 | 0.602 | 0.298 | .585 | 1.39 | 0.427–4.516 | |
| Hematological diseases | ‐1.204 | 0.81 | 2.211 | .137 | 0.299 | 0.061–1.468 | |
| Urinary system diseases | 0.632 | 0.392 | 2.603 | .107 | 1.881 | 0.873–4.055 | |
| Endocrine and metabolic diseases | ‐1.003 | 0.862 | 1.352 | .245 | 0.367 | 0.068–1.988 | |
| Neurological diseases | ‐0.899 | 0.595 | 2.28 | .131 | 0.407 | 0.127–1.306 | |
| Other | ‐1.213 | 1.037 | 1.367 | .242 | 0.297 | 0.039–2.266 | |
| Self-perceived severity of disease (with mild as reference) | Moderate | ‐0.62 | 0.358 | 3.005 | .083 | 0.538 | 0.266–1.086 |
| Severe | 1.331 | 0.466 | 8.132 | .004 | 3.785 | 1.519–9.433 |
Bold values indicate statistical significance.
4. Discussion
This study investigated anxiety levels and associated factors among patients in the emergency department of a large tertiary hospital. The results showed that 32.65% of patients experienced anxiety. Univariate analysis identified significant associations between anxiety and age (40–59 years), education level (high school), type of illness (musculoskeletal disorders), and self-perceived severity of illness (severe). Multivariate logistic regression further confirmed that being aged 40 to 59 years, having a high school education, musculoskeletal disorders, and perceiving illness severity as severe were independent factors influencing anxiety in patients admitted to the emergency department.
In this study, we found that patients aged 40 to 59 had a significantly higher risk of anxiety compared to those aged ≤ 39, which may be related to increased stress from work and family responsibilities in this age group.[11] Additionally, patients with a high school education had a higher risk of anxiety compared to those with primary education or below, potentially reflecting the complex relationship between education level and anxiety, where higher education may be associated with greater occupational stress and social expectations.[12] Patients with musculoskeletal disorders also had a significantly higher risk of anxiety, likely due to chronic pain and functional limitations that impact daily life and work, contributing to anxiety. These disorders may activate stress-related physiological pathways, such as the hypothalamic-pituitary-adrenal (HPA) axis, and are associated with impaired mobility, reduced social participation, and a heightened perception of health-related uncertainty (all of which can exacerbate psychological distress).[13] Moreover, patients with self-perceived severe illness had a significantly higher risk of anxiety compared to those with mild perceptions, indicating that subjective perceptions of illness severity play a crucial role in anxiety development.[14]
The findings of this study regarding the relationship between age and anxiety are consistent with most of the literature, indicating that individuals aged 40 to 59 years experience higher levels of anxiety due to the stresses of middle age.[15] Regarding education level and anxiety, some studies suggest that higher education may increase anxiety risk due to increased occupational and social stress, while others have found that higher education is associated with lower anxiety levels. The present study supports the former view, potentially due to the specific characteristics of the study population and setting.[16] In terms of disease type, this study found that musculoskeletal disorders significantly increased anxiety risk, aligning with related research that highlights the impact of chronic pain on quality of life and psychological stress.[17] Furthermore, the relationship between self-perceived disease severity and anxiety has been supported by several studies, indicating that patients’ perceptions of their illness severity directly affect their psychological state.[18]
The main strength of this study is its use of a sample from the emergency department of a large tertiary hospital, providing high representativeness. Additionally, multivariate logistic regression analysis was employed, allowing effective control of confounding factors and identification of independent influencing variables, which enhances the credibility of the findings.[19] The study revealed higher levels of anxiety and its influencing factors among patients in the emergency department, suggesting that healthcare organizations should prioritize patients’ mental health in emergency management. For patients aged 40 to 59 years, with a high school education, musculoskeletal disorders, and high self-perceived disease severity, it is recommended to strengthen psychological support and interventions, such as providing psychological counseling and implementing a mental health screening mechanism, to reduce anxiety prevalence and improve overall patient outcomes.
Based on our findings, targeted interventions should be implemented for high-risk groups such as patients aged 40 to 59 years, those with high school education, musculoskeletal disorders, and high perceived illness severity. First, emergency departments should incorporate routine psychological screening using tools like the GAD-7 during triage or observation, especially for patients with pain-related complaints. Second, psychological support services, including brief cognitive-behavioral interventions, relaxation training, and access to mental health professionals, should be made available on-site or through referral pathways. Third, for patients with musculoskeletal disorders, integrated care models that combine pain management, physiotherapy, and psychological support may help alleviate both physical symptoms and associated anxiety. Finally, enhanced communication about illness severity and treatment plans can help reduce uncertainty and empower patients, which has been shown to mitigate anxiety levels. These interventions are feasible in the emergency setting and can be tailored based on available resources.
Nonetheless, this study has several limitations. First, the cross-sectional design restricts the ability to infer causality and does not establish the temporal sequence between variables, thereby limiting the interpretation of observed associations.[20] Second, the relatively small sample size (n = 98) reduces statistical power, particularly in subgroup analyses. Third, all data were obtained from a single tertiary hospital, which may introduce institutional bias and limit the generalizability of the findings to other populations and healthcare environments.[21]
To address these limitations, future research should consider expanding the sample size and incorporating multicenter samples to improve the external validity and applicability of the results. Moreover, longitudinal study designs are recommended to assess the dynamic evolution of anxiety symptoms over time and to better understand causal relationships between anxiety and clinical or demographic factors. Such approaches will enable researchers to identify high-risk periods and modifiable predictors of anxiety, contributing to more effective and timely mental health interventions in emergency care settings.
In summary, this study found that anxiety was common among emergency department patients, with age (40–59 years), high school education, musculoskeletal disorders, and perceived severe illness identified as independent risk factors. These findings underline the importance of early identification and targeted psychological support for high-risk groups. The statistical analyses helped clarify how different demographic and clinical characteristics contribute to anxiety risk. These insights can inform mental health screening and intervention strategies in emergency care settings. Future research should adopt longitudinal designs to explore causal relationships and symptom progression, examine underlying mechanisms (particularly in pain-related conditions) and validate findings through larger, multi-center studies to enhance generalizability.
Author contributions
Conceptualization: Qian Huang, Xiaoli Chen, Lei Ye.
Data curation: Qian Huang, Xiaoli Chen, Ling Zhu, Dongmei Diao, Lei Ye.
Formal analysis: Qian Huang, Xiaoli Chen, Ling Zhu, Dongmei Diao, Lei Ye.
Investigation: Qian Huang, Lei Ye.
Methodology: Qian Huang, Lei Ye.
Writing – original draft: Qian Huang, Xiaoli Chen, Ling Zhu, Dongmei Diao, Lei Ye.
Writing – review & editing: Qian Huang, Lei Ye.
Abbreviation:
- GAD-7
- Generalized Anxiety Disorder-7
The authors have no funding and conflicts of interest to disclose.
The datasets generated during and/or analyzed during the current study are available from the corresponding author on reasonable request.
How to cite this article: Huang Q, Chen X, Zhu L, Diao D, Ye L. A survey of anxiety and analysis of the factors influencing it in patients staying at the emergency department of a large comprehensive tertiary care center. Medicine 2025;104:28(e43165).
Contributor Information
Qian Huang, Email: YHaoRui0820@163.com.
Xiaoli Chen, Email: xjxqxq@163.com.
Ling Zhu, Email: 313632463@qq.com.
Dongmei Diao, Email: gdxmyeyyey@163.com.
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