Background
Nurses form the backbone of the global healthcare system, yet the profession faces a persistent and growing shortage. The World Health Organization projects a global shortfall of 10 million health workers by 2030, with nurses representing a substantial proportion of this deficit. This shortage is particularly acute in rapidly developing health systems, where increased demand for services is not matched by workforce growth. The resulting staffing shortages have increased workloads and extended shifts, directly contributing to heightened stress and poorer mental health outcomes among nurses. Mounting evidence links excessive work burden and high job demands to elevated risks of anxiety, depression, and burnout, conditions that not only affect nurses’ well-being but also compromise the quality and safety of patient care. Given the critical role outpatient nurses play in frontline care delivery, there is an urgent need to understand the interplay between work-related stressors and mental health within this population.
Objective
This study aims to explore the relationship between demographic factors, working conditions, and mental health outcome specifically burnout, depression, and anxiety—among outpatient nurses in a general hospital setting, addressing the gap in targeted research in this area.
Methods
A quantitative cross-sectional design study was conducted among outpatient nurses. Structured questionnaires were distributed online via the corporate email. Socio-demographic variables, workspace burden, and mental health factors (anxiety, stress, depression, and burnout), assessed using two established scales, were evaluated. STATA 17 was used to determined Statistical significance using T-tests, Mann-Whitney U tests, Kruskal-Wallis tests, and quantile regression, with a significance threshold set at p < 0.05.
Results
The study achieved a 96.6% response rate, with 286 out of 296 outpatient nurses participating. The majority were foreign females aged 31–40, with 65.6% holding a bachelor’s in nursing and 81.3% having over five years of experience. Approximately 44.9% and 44.5% of nurses reported experiencing some degree of mental or physical exhaustion, respectively. Despite these challenges, 62.9% were satisfied with their jobs. Burnout and anxiety were associated with younger age, education, and living status, with 31% experiencing burnout, 11.4% experiencing anxiety, and 39.9% experiencing depression. Regression analysis identified these factors as key predictors of mental health outcomes. Nurses with a diploma had significantly lower burnout levels compared to those with a Bachelor of Science in Nursing (β = -2.5, p = 0.027). Nurses living alone experienced significantly less burnout than those living with children (β= -7.5, p = 0.005) or with other family members (β = -4, p = 0.022). Anxiety was significantly higher among nurses aged 31–40 years compared to other age groups (β = 3, p = 0.043).
Conclusion
The study revealed moderate levels of burnout and depression, with a smaller but meaningful proportion of nurses reporting abnormal anxiety. Younger nurses (31–40 years), those with a bachelor’s degree, and those living alone appeared more vulnerable. These associations suggest potential targets for support, although causality cannot be inferred due to the cross-sectional design. While the conclusion appropriately identifies the need for targeted interventions to address burnout and anxiety, it falls short in providing specific, actionable recommendations. To enhance the study’s practical utility, it would be beneficial to include detailed strategies or proposals for interventions that healthcare organizations could implement to support the mental health of outpatient nurses.
Clinical trial number
Not applicable.
Supplementary Information
The online version contains supplementary material available at 10.1186/s12912-025-03758-7.
Keywords: Outpatient nurses, Burnout, Anxiety, Depression, Nursing shortage
What is already known
Addressing mental and physical fatigue in nurses is crucial for overall well-being
Long working hours and educational background contribute to burnout levels
Sleep pattern, age, education, and family engagement affect anxiety and depression
Supplementary Information
The online version contains supplementary material available at 10.1186/s12912-025-03758-7.
What this paper adds
Strategies addressing mental and physical fatigue that improve nurse well-being
Targeted interventions focusing on work hours and educational background
Background
In the healthcare sector, nurses are essential, constituting 59% of the workforce and delivering 80% of primary patient care [1]. Despite its critical role, the global nursing workforce faces severe shortages, with approximately 28 million nurses currently employed and an estimated demand of 36 million by 2030 [2]Such shortages are a growing crisis that hampers the delivery of optimal medical care and poses significant threats to healthcare access globally [3, 4]. The International Council of Nurses forecasts a global deficit of 13 million nurses by 2030 [5], highlighting the critical need for intervention.
This shortage varies significantly by region. For instance, the Canadian Federation of Nurses Union (CFNU) reported a 133% increase in vacancy listings between 2019 and 2021 [6], whereas Iran struggles with a critical shortage projected to worsen from 130,000 to 200,000 by 2030 [7]. Insufficient staffing jeopardises the overall standard of patient care and the health and welfare of nurses [8, 9].
The COVID-19 pandemic has heightened workplace stress for registered nurses (RNs), exposing them to risks such as inadequate protective gear, understaffing, and high patient-to-nurse ratios. These stressors contribute to secondary traumatic stress, influencing RNs’ intentions to leave the profession. A recent study has highlighted the need for occupational health nurses to advocate for the prevention of compassion fatigue, safer patient ratios, and improved staffing to retain nurses [10].
Chronic understaffing leads to significant mental health issues among nurses, including burnout, anxiety, stress, and depression, impairing their ability to perform effectively [11].
In the Gulf Cooperation Council Countries that includes Qatar, there are 49 nurses per 10,000 people compared to 80 in the Organization for Economic Co-Operation and Development (OECD) countries. Demand for staff is expected to increase by 240% by the mid-2040s [12]. In 2024, Forbes identified Qatar as the fifth richest nation by per capita Gross Domestic Product (GDP). Its aging and growing population of 2.7 million is made up of almost 88% foreign-born individuals. Healthcare is delivered by a mix of the public and private sectors, with approximately 80% of nurses employed in the public sector [13].
Highlighted research indicating that raising nurse-to-patient ratios from 1:4 to 1:6 resulted in a 7% increase in patient mortality [14]. The Qatar Supreme Council (QSC) implemented a minimum nurse-to-patient ratio of 1:5, though its effectiveness has yet to be evaluated [15].
Outpatient nurses act as frontline representatives of health services, shaping initial perceptions and confidence of the setting for patients [16]. In Qatar, Hamad General Hospital serves 80% of the country’s population and is the largest hospital within the medical system [17]. The nursing team across all outpatient departments collectively manages an influx of approximately 2,300 daily patients and around 600,000 patients annually across 1,752 clinics. offering appointments for a broad spectrum of specialties. Despite this high volume, there is a substantial shortage of approximately 90 nurses in the outpatient departments, which currently have 296 nurses.
The relationship between staff shortages and outcomes such as job satisfaction, work-life balance, and nurse retention is well-documented. However, most existing studies have focused on inpatient care, intensive care units, or specialty departments such as oncology, which have different dynamics and stressors compared to outpatient settings [6, 18–20].
Research in the Middle East, particularly in the Gulf region, has predominantly centred on job satisfaction and quality of work life, with minimal emphasis on how staffing levels directly influence mental health outcomes [21].
Global studies show a high prevalence of burnout, anxiety, and depression among nurses [6, 11]. Generally, in all cases of poor mental health, nurses often feel overwhelmed and struggle to maintain their professional responsibilities and advocate for patient care [22, 23]. Adequate nursing staff are positively associated with good mental health, while inadequate staffing has a negative impact [19, 24].
Although outpatient settings are often considered less demanding than inpatient care, they pose specific challenges that can affect nurses’ mental health.
Current research rarely addresses these issues, and specific data on their effects on outpatient nurses in Qatar is lacking. This study focuses on to explore the relationship between demographic factors, working conditions, and mental health outcome specifically burnout, depression, and anxiety—among outpatient nurses in a general hospital setting, addressing the gap in targeted research in this area.
To further enhance its relevance and contextualize the research question, I recommend adding a paragraph that explicitly establishes the link between work burden and the development of anxiety and depression. This addition would strengthen the rationale for investigating these variables in the study and provide a more compelling justification for the research.
Methods
Study design, and setting
This study used a cross-sectional design, suitable for providing a snapshot of a population as a comprehensive overview. However, it is unable to prove causality or evaluate changes over time or long-term consequences.
Nurses were invited to participate depending on their availability and willingness to provide informed consent (Appendix 2). Those who expressed interest received the participant information sheet (Appendix 3). All OPD departments, including medicine, surgery, and paediatrics, were approached and included in the study.
The inclusion criteria encompassed male and female nurses actively practicing in HGH OPD clinics, with at least one year of nursing experience, as this period is needed for nurses to gain independence within the organization. Proficiency in English was also required, as it is the lingua franca for all employees and the language chosen for the questionnaires. Nurses were included regardless of past mental health history to capture a broad spectrum of experiences.
Those not meeting these criteria were excluded.
Convenience sampling was employed due to being the most convenient method with a good response rate. However, this method can introduce selection bias and limit generalizability, as it may not reflect the broader population.
The study has adopted an applied primary data collection method, and the results are reported using Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) guidelines.
Data collection
A structured and validated questionnaire (Appendix 1) was employed, consisting of three sections: socio-demographic information (nationality, age, sex, education, marital status, health status, income), workplace burden assessment [25].
The Hospital Anxiety and Depression Scale (HADS) was chosen as a reliable tool for assessing anxiety and depression in a hospital outpatient clinic setting [26, 27]. The HADS consists of 14 items rated on a 4-point Likert scale. Burnout levels were measured using the Manual of Burnout assessment tool [28], (supplementary file1). The burnout assessment tool used in this study was selected based on its demonstrated reliability and validity in measuring burnout among healthcare professionals. This tool includes 12 items covering four key subdimensions: emotional exhaustion, physical exhaustion, cognitive impairment, and emotional distancing—each rated on a 4-point Likert scale. These dimensions are particularly relevant to the outpatient nursing context, where prolonged patient contact, limited staffing, and role ambiguity can affect both emotional and physical well-being. The instrument has previously shown strong internal consistency, with Cronbach’s alpha coefficients typically exceeding 0.80 across subscales in similar healthcare settings. The tool’s ability to capture subtle variations in fatigue and disengagement also allowed for a more nuanced understanding of burnout in this specific outpatient population. Both the burnout assessment tool and the Hospital Anxiety and Depression Scale (HADS) have demonstrated strong psychometric properties across diverse healthcare populations. While neither tool was developed exclusively for outpatient nurses, multiple studies have validated their use within outpatient and ambulatory care settings, confirming their appropriateness for this population. The burnout tool has been successfully applied in studies involving outpatient nursing staff, showing robust internal consistency (Cronbach’s alpha > 0.80) and strong construct validity in capturing occupational stressors specific to non-inpatient environments. Similarly, the HADS has been widely validated in hospital outpatient clinics and among nursing professionals, proving effective in identifying symptoms of anxiety and depression. The total scores for each subscale range from 0 to 21. Based on established and validated thresholds, participants’ scores were categorized into three groups: normal (0–7), borderline abnormal (8–10), and abnormal (11–21).
The work burden of outpatient nurses was assessed using a structured, self-administered questionnaire developed specifically for this study. The tool was designed to capture various dimensions of nurses’ occupational experience, with particular attention to factors that may influence mental health outcomes such as burnout, anxiety, and depression. Three key constructs assessed were physical activity, job satisfaction, and end-of-day emotional state (daily mood).
Physical activity was assessed using the item: “How often do you do physical workouts?” with response options rated on a 5-point Likert scale: Very Often (1), Often (2), Sometimes (3), Usually (4), Always (5). For analysis, responses were grouped into three categories to reflect overall activity levels: Normal (Very Often and Often), Borderline Abnormal (Sometimes), and Abnormal (Usually and Always).
Job satisfaction was measured using the item: “How do you describe your job satisfaction?” with five response options: Very Satisfied (1), Satisfied (2), Not Sure (3), Dissatisfied (4), Very Dissatisfied (5). For analytical clarity, responses were grouped into three categories: Satisfied (Very Satisfied and Satisfied), Not Sure, and Dissatisfied (Dissatisfied and Very Dissatisfied).
Daily mood was assessed with the item: “How do you feel by the end of the working day?” using a 5-point scale: Energetic (1), Less Energetic (2), Neutral (3), Exhausted (4), Very Exhausted (5). For descriptive purposes, responses were categorized as: Positive Mood (Energetic), Neutral Mood (Neutral and Less Energetic), and Negative Mood (Exhausted and Very Exhausted). This measure aimed to capture immediate post-shift emotional status, which can serve as an early indicator of chronic fatigue or emotional strain.
These three items were reviewed for content validity by a multidisciplinary expert panel and underwent minor revisions to ensure clarity, relevance, and applicability. The tool demonstrated strong internal consistency with a Cronbach’s alpha of 0.90, indicating excellent reliability. Furthermore, the questionnaire was administered in English, the official working language in the healthcare setting,
Data collection was conducted over three weeks, starting on 10 March 2024, with reminders sent twice per week. Nurses participating in the study completed the validated structured questionnaire, which took approximately 20 min. The questionnaires were distributed online through the hospital’s organizational website using Microsoft forms and emails. Charge nurses played a supportive role in promoting the study within their respective outpatient departments. Their responsibilities included informing eligible nurses about the research through verbal communication, unit noticeboards, and internal communication platforms. While they helped raise awareness and directed staff to the study invitation links, they were not involved in directly encouraging or pressuring staff to participate. Participation remained entirely voluntary, and charge nurses were instructed to avoid any form of coercion. Their involvement was limited to general promotion to maintain ethical standards and ensure that participants’ decisions to partake were made freely and independently.
Sample size
There are total 296 nurses working across different units in the OPD clinics at HGH. At first, we calculated a minimum required sample size of about 160 nurses, based on an estimate that around 30% might have experienced mental health issues. This was done using a standard formula with a 5% margin of error and 95% confidence level, and the sample was planned to be proportionally taken from different OPD units. However, to improve the strength and generalizability of the results, we decided to include all 296 nurses in the study. Involving the entire OPD nursing population was seen as more effective than selecting only a portion, as it allowed for better representation of all OPD clinics.
Data analysis
All statistical analyses were conducted using STATA version 17.0. Categorical data were expressed as frequency and percentage, while continuous data were summarized using median and interquartile range (IQR), given the non-normal distribution of some variables. Descriptive statistics summarised the demographic characteristics and data related to professional and coping strategies.
The burnout score was calculated as the sum of all the responses to the questionnaire. We obtained 286 responses out of 296, resulting in a missing data rate of about 3.4%, which is below the 5% threshold. If the missing data rate exceeded 5%, a multiple imputation analysis would have been required [29].
The normality of the distribution was assessed using the Kolmogorov test. Quantitative data were analysed using the Unpaired t-test or Mann Whitney U test, as well as Analysis of Variance (ANOVA) or Kruskal Walli’s test, depending on the distribution assumptions, to determine differences in means or medians between the scores and socio-demographic variables. Quantile regression analysis was used to assess and quantify the effects of different factors on the primary and secondary outcomes, with confidence intervals reported. All reported P values were two-tailed, with statistical significance defined as P values of < 0.05.
To assess nursing shortages, we conducted a comparison between the current number of employed nurses (as provided by the Director of Nursing Workforce of the institute) with the staffing levels required according to the institution’s established guidelines or standards of care. Shortages were quantified by calculating the discrepancy between the existing workforce and the optimal workforce size necessary to adequately address the workload demands.
Ethical approval and consent to participate
Ethical considerations were addressed in accordance with the guidelines outlined in the Declaration of Helsinki. Approval was obtained from the institutional review board of the hospital Medical Research Centre (MRC), under the number MRC-01-23-640. A research information sheet was provided, and informed consent was obtained from all participants involved in the research interview. Participants were provided with an information sheet explaining the study’s purpose, procedures, and their right to withdraw at any time without consequences. No identifiable data were collected to ensure confidentiality and anonymity. The study adhered to ethical guidelines for research involving human participants.
Results
Socio-Demographic characteristics
Out of 296 outpatient nurses who received the survey, 286 responded. The majority were non-Qatari female residents (98.3%), and 82.3% were aged between 31 and 50 years. Among them, 65.6% held a Bachelor of Science in Nursing, while 34.5% had a diploma or postgraduate qualification. Most participants were married (84.9%), and 92.6% did not live alone. Additionally, 665% were the primary earners in their households, 71.8% had children, and 55.9% reported being in debt (Table 1).
Table 1.
Comprehensive Socio-demographic, financial, living status, and educational profiles of participants
| Variables | n (%) | Variables | n (%) |
|---|---|---|---|
| Nationality | Do you rear children | ||
| Qatari | 5 (1.7%) | No | 79 (28.2%) |
| Non-Qatari | 281 (98.3%) | Yes | 201 (71.8%) |
| Sex | Education | ||
| Female | 221 (77.5%) | BSN | 185 (65.6%) |
| Male | 61 (21.4%) | Diploma | 71 (25.2%) |
| Not Available | 3 (1.1%) | Masters | 25 (8.9%) |
| - | - | Ph.D. | 1 (0.3%) |
| Sole earning member | Living Status | ||
| No | 97 (33.5%) | Alone | 21 (7.4%) |
| Yes | 184 (66.5%) | Children | 14 (4.9%) |
| - | - | Couple | 20 (7.0%) |
| - | - | Family | 221 (77.5%) |
| - | - | Roommate(s) | 9 (3.2%) |
| Age | Do you have pets | ||
| 20–30 years | 14 (4.9%) | No | 240 (84.5%) |
| 31–40 years | 153 (53.6%) | Yes | 44 (15.5%) |
| 41–50 years | 82 (28.7%) | Are you in debt | |
| Above 50 | 37 (12.8%) | No | 123 (44.1%) |
| Marital Status | Yes | 156 (55.9%) | |
| Married | 241 (84.8%) | - | - |
| Single | 31 (10.9%) | - | - |
| Divorced | 6 (2.1%) | - | - |
| Separated | 3 (1.1%) | - | - |
| Widowed | 3 (1.1%) | - | - |
| Qatari | 5 (1.7%) | No | 79 (28.2%) |
| Non-Qatari | 281 (98.3%) | Yes | 201 (71.8%) |
| Sex | Education | ||
| Female | 221 (77.5%) | BSN | 185 (65.6%) |
| Male | 61 (21.4%) | Diploma | 71 (25.2%) |
| Not Available | 3 (1.1%) | Masters | 25 (8.9%) |
| Ph.D. | 1 (0.3%) | ||
| Sole earning member | Living Status | ||
| No | 97 (33.5%) | Alone | 21 (7.4%) |
| Yes | 184 (66.5%) | Children | 14 (4.9%) |
| Are you in debt | Couple | 20 (7.0%) | |
| No | 123 (44.1%) | Family | 221 (77.5%) |
| Yes | 156 (55.9%) | Roommate(s) | 9 (3.2%) |
| Age | Do you have pets | ||
| 20–30 years | 14 (4.9%) | No | 240 (84.5%) |
| 31–40 years | 153 (53.6%) | Yes | 44 (15.5%) |
| 41–50 years | 82 (28.7%) | - | - |
| Above 50 | 37 (12.8%) | - | - |
| Marital Status | - | - | |
| Married | 241 (84.8%) | - | - |
| Single | 31 (10.9%) | - | - |
| Divorced | 6 (2.1%) | - | - |
| Separated | 3 (1.1%) | - | - |
| Widowed | 3 (1.1%) | - | - |
Work environment factors
Most participants were staff nurses (92.3%), and 81.3% had more than five years of experience. However, 75.5% worked 8-hour shifts, while 24.5% worked more than 8 h a day. A large proportion (90.8%) reported sleeping less than 7 h per night, and 42.3% reported having medical conditions. Access to education and training varied, with 46.8% having some access but lacking the time to participate. Gatherings were the most common social activities, attended by 27.5% of the participants (Table 2).
Table 2.
Comprehensive overview of job categories, educational attainment, work experience, lifestyle habits, health status, access to training, and social engagement among participants
| Job Category n (%) | Working hours per day n (%) | |||
|---|---|---|---|---|
| Charge Nurse | 11 (3.9%) | 8 h | 213(75.5%) | |
| Director of Nursing | 4 (1.4%) | More than 8 | 69 (24.5%) | |
| Head Nurse | 7 (2.4%) | Working hours per week n (%) | ||
| Staff Nurse | 260(92.3%) | 40 h | 202(71.4%) | |
| Experience in years n (%) | More than 40 h | 81 (28.6%) | ||
| 1–3 years | 28 (9.9%) | Do you have any health issues? n (%) | ||
| 3–5 years | 25 (8.8%) | No |
164 (57.7%) |
|
| >5 years | 231 (81.3%) | Yes |
120 (42.3%) |
|
| Sleeping time n (%) | Access to Education and Training n (%) | |||
| < 7 h | 258 (90.8%) | Extensive access and regular participation | 63 (22.3%) | |
| > 7 h | 26 (9.2%) | Limited access and difficult to participate | 66 (23.2%) | |
| Do you smoke n (%) | No access and opportunities to train 18(6.3%) | |||
| No |
269 (94.7%) |
Not aware of such things | 14 (1.4%) | |
| Yes |
15 (5.3%) |
Some access but don’t have time to spend | 133(46.8%) | |
| Engagement in social activities n (%) | ||||
| Educational workshops | 29 (10.1%) | Social gatherings | 78 (27.3%) | |
| Networking Events | 6 (2.10%) | Traveling | 15 (5.2%) | |
| Outdoor activities | 35(12.2%) | Volunteering | 9(3.1%) | |
| Religious / Spiritual activities | 51(17.8%) | None | 63 (22.0%) | |
Work burden
The majority of respondents (76.7%) reported having a normal level of physical workout, indicating generally healthy physical activity patterns. A smaller proportion, 11.7%, were classified as having borderline abnormal workout patterns, while an almost equal 11.6% reported abnormal levels of physical activity. This suggests that approximately one in four individuals may have suboptimal physical activity levels, which could pose a health risk over time. In terms of job satisfaction, 62.9% of respondents indicated they were satisfied with their job, reflecting a generally positive work environment or alignment with job roles. However, 19.1% expressed dissatisfaction, and another 18% were not sure about their job satisfaction. This implies that nearly 40% of respondents may be experiencing ambiguity or negative feelings towards their jobs, warranting further exploration into workplace morale or job stressors. When asked about their general feeling for the day, 24.6% reported feeling less energetic, 33.8% felt neutral, and 33.5% felt exhausted, indicating that a significant portion (over 90%) experienced moderate to low energy levels during the day. Only 8.1% reported feeling energetic, highlighting potential concerns regarding fatigue, burnout, or lack of vitality in daily routines among the population surveyed (Fig. 1).
Fig. 1.
Chart showing levels of physical workout, feel of the day and job satisfaction
Burnout
Approximately 44.9% of the nurses experienced some degree of mental exhaustion, with 34.8% feeling it significantly or frequently. Similarly, 44.5% reported some degree of physical exhaustion, while 34.9% felt physically drained fairly often or very often. The alignment of these percentages suggests a strong connection between mental and physical fatigue. Emotionally, 66.4% did not feel cynical about how others perceived their work, 54.1% recognised themselves in their workplace reactions, and 51.74% occasionally overreacted unintentionally. Most nurses did not struggle with concentration or make mistakes at work, with 61.53% and 63.98%, respectively, reporting no issues (Supplementary Table 1).
Burnout levels were categorized into tertiles: scores ranging from 0-6 were considered low, 7–12 moderate, and 13–36 high. This method of classification was chosen for its practicality and data-driven robustness, especially when a well-established clinical cut-off is unavailable or varies across settings. Tertile-based classification allows for the stratification of participants into approximately equal-sized groups based on score distribution, providing a clearer understanding of how burnout symptoms vary within the population. Low burnout was reported by 36.6% of the participants, while 31.7% had moderate burnout and another 31.7% experienced high burnout (Fig. 2). The average burnout score was 10.4 ± 7.68, with a median of 10 (interquartile range: 4 to 14.5), indicating an overall moderate level of burnout A more detailed presentation of the data distribution, such as a histogram, would also enhance the reader’s understanding of the burnout levels within the study population. (Supplementary Table 1).
Fig. 2.
Distribution of participants based on their levels of burnout
Anxiety and depression
The mean depression score was 9.3 ± 4.6, with a median of 9.0, (interquartile range: 6.0 to 13.0). These results indicate moderate levels within the surveyed population (Supplementary Table 2).
Regarding anxiety, most participants (76.7%) fell within the normal range, while 11.7% reported borderline anxiety and another 11.7% suffered from abnormal anxiety levels. For depression, 39.6% were classified as normal, 20.5% had borderline scores, and 39.9% had depression (Fig. 3).
Fig. 3.
Distribution of participants based on their levels of anxiety and depression
Bivariate analysis
Regarding burnout, nurses aged 31–40 years had the highest median score (11.0; interquartile range: 6.0 to 15.0; p = 0.003) compared to the 20–30 years group, which had a median of 6.5 (interquartile range: 3.0 to 9.0), the 41–50 years group (median 7; interquartile range: 4.0 to 15.0), and the > 50 years group (median 5; interquartile range: 3.0 to 11.0). Nurses holding a Bachelor of Science in Nursing degree had a higher median burnout score of 11.0 (interquartile range: 5.0 to 15.0) than those who had completed postgraduate studies (p = 0.023).
Nurses who lived with family (median 8.5; interquartile range: 4.5 to 13.0) and those with children (median 4.5; interquartile range: 3.0 to 19.0) had lower median burnout scores (p = 0.032) compared to those living with roommates (median 15; interquartile range: 11.0 to 16.0), alone (median 11; interquartile range: 10.0 to 15.0), or as couples (median 14, interquartile range: 7.5 to 18.5).
Prolonged working hours (40 + per week) resulted in the highest levels of burnout (median 12.0; interquartile range: 5.0 to 16.0) compared to those working 40 h per week (Table 3).
Table 3.
Association between Socio-demographic factors and burnout, anxiety, and depression
| Socio Demographic features | n (%) | Burnout | Anxiety | Depression | ||||
| Median (IQR) | P value | Median (IQR) | P value | Mean ± SD | P value | |||
| Age (Years) | 20–30 | 14 (4.8%) | 6.5 (3.0,9.0) | 0.003* | 3 (1.0,4.0) | 0.04* | 7.8 ± 4.8 | 0.61 |
| 31–40 | 153 (53.49%) | 11 (6.0,15.0) | 6 (3.0,8.0) | 9.3 ± 4.3 | ||||
| 41–50 | 82 (28.6%) | 7 (4.0,15.0) | 5 (3.0,7.0) | 9.3 ± 5.1 | ||||
| > 50 | 37 (12.9%) | 5 (3.0,11.0) | 6 (3.0,7.0) | 9.7 ± 4.3 | ||||
| Sex | Female | 221 (77.2%) | 9 (4.5,15.0) | 0.540 | 5 (3.0,7.5) | 0.45 | 9.5 ± 4.7 | 0.34 |
| Male | 61(21.3%) | 10 (4.0,12.5) | 5 (3.0,7.5) | 8.5 ± 4.1 | ||||
| NA | 3 (1%) | 14 (5.0,23.0) | 6 (5.0,18.0) | 10.7 ± 4.5 | ||||
| Citizen & residents | Non-Qatari | 281 (98.25%) | 10 (4.0,15.0) | 0.210 | 5 (3.0,7.0) | 0.23 | 9.3 ± 4.6 | 0.52 |
| Qatari | 5 (1.74%) | 12 (11.0,14.0) | 7 (6.0,7.0) | 8 ± 1.6 | ||||
| Education | Diploma | 71 (24.82%) | 7 (3.0,12.0) | 0.023 | 4 (2.0,7.0) | 0.018 | 7.6 ± 4.5 | 0.52 |
| BSN | 185 (64.68%) | 11 (5.0,15.0) | 6 (3.0,8.0) | 9.9 ± 4.3 | ||||
| Master/Ph.D. | 26 (9.09%) | 8 (3.0,14.0) | 6 (3.0,8.0) | 9.6 ± 5.1 | ||||
| Marital status | Divorced/ separated/widow | 12 (4.19%) | 4.5 (3.0,14.0) | 0.380 | 6 (3.5,8.5) | 0.15 | 10.8 ± 2.1 | 0.16 |
| Married | 241 (84.26%) | 10 (5.0,14.0) | 5 (3.0,7.0) | 9.1 ± 4.6 | ||||
| Single | 31 (10.83%) | 11 (3.0,16.0) | 7 (3.0,9.0) | 10.4 ± 4.6 | ||||
|
Sole Earning Member of the family |
No | 97 (33.91%) | 7.5 (4.5,13.0) | 0.390 | 5 (3.0,7.0) | 0.25 | 9.9 ± 4.4 | 0.21 |
| Yes | 184 (64.33%) | 10 (4.0,15.0) | 6 (3.0,8.0) | 9.1 ± 4.5 | ||||
| Are you in debt | No | 123 (43%) | 8 (4.0,14.0) | 0.120 | 5 (3.0,8.0) | 0.66 | 9.1 ± 4.5 | 0.35 |
| Yes | 156 (54.54%) | 11 (5.0,15.0) | 5.5 (3.0,7.0) | 9.6 ± 4.5 | ||||
| Having children | No | 79 (27.62%) | 10 (3.0,15.0) | 0.600 | 6 (3.0,7.0) | 0.73 | 9.1 ± 4.9 | 0.61 |
| Yes | 201 (70.27%) | 10 (5.0,15.0) | 5 (3.0,7.0) | 9.5 ± 4.4 | ||||
| Pets | No | 240 (83.91%) | 10 (5.0,15.0) | 0.320 | 5 (3.0,7.0) | 0.90 | 9.1 ± 4.5 | 0.14 |
| Yes | 44 (15.38%) | 9 (3.5,12.5) | 5 (3.0,7.0) | 10.2 ± 4.9 | ||||
| Living status | Alone | 21 (7.34%) | 11 (10.0,15.0) | 0.032* | 6 (5.0,8.0) | 0.52 | 10.5 ± 5.3 | 0.6 |
| Children | 14 (4.72%) | 4.5 (3.0,19.0) | 5 (3.0,7.0) | 9.9 ± 3.1 | ||||
| Couple | 20 (6.66%) | 14 (7.5,18.5) | 7 (3.0,7.5) | 10 ± 4.1 | ||||
| Family | 221 (77.27%) | 8.5 (4.5,13.0) | 5 (3.0,7.0) | 9.1 ± 4.6 | ||||
| Room mate | 9 (3.14%) | 15 (11.0,16.0) | 4 (1.0,9.0) | 9.6 ± 5.2 | ||||
| Experience (years) | < 3 years | 28 (9.86%) | 7.0 (3.0, 15.5) | 0.64 | 5.0 (3.0, 8.0) | 0.89 | 8.3 ± 3.8 | 0.34 |
| Between 3–5 years | 25 (8.80%) | 10.0 (5.0,15.0) | 6.0 (3.0, 7.0) | 8.7 ± 4.2 | ||||
| > 5 years | 231 (81.34%) | 10.0 (5.0, 14.0) | 5.0 (3.0, 7.0) | 9.5 ± 4.7 | ||||
| Job description | Charge nurse | 11 (3.84%) | 11 (5.0,15.0) | 0.630 | 7 (4.0,8.0) | 0.59 | 10.9 ± 3.4 | 0.14 |
| Dir of Nursing | 4 (1.39%) | 11 (8.0,16.5) | 6.5 (5.0,8.5) | 13 ± 5.2 | ||||
| Head Nurse | 7 (2.44%) | 5 (2.0,14.0) | 5 (3.0,7.0) | 11 ± 4.1 | ||||
| Staff Nurse | 260 (90.9%) | 10 (4.0,15.0) | 5 (3.0,7.0) | 9.1 ± 4.5 | ||||
| Daily working hours | 8 h | 213 (74.47%) | 9 (4.0,14.0) | 0.250 | 5 (3.0,7.0) | 0.42 | 9.1 ± 4.6 | 0.26 |
| > 8 h | 69 (24.12%) | 11 (5.0,16.0) | 6 (3.0,8.0) | 9.8 ± 4 | ||||
| Weekly working hours | 40 h | 202 (70.62%) | 9 (4.0,14.0) | 0.028* | 5 (3.0,7.0) | 0.31 | 9.2 ± 4.7 | 0.4 |
| > 40 h | 81 (28.32%) | 12 (5.0,16.0) | 6 (3.0,8.0) | 9.7 ± 4.2 | ||||
| Sleeping time | < 7 h | 258 (90.2%) | 10 (4.0,14.0) | 0.550 | 6 (3.0,7.5) | 0.04* | 9.2 ± 4.4 | 0.13 |
| > 7 h | 26 (9.09%) | 8.5 (3.0,15.0) | 4 (3.0,6.0) | 10.6 ± 5.3 | ||||
Mann Whiteney U test and Kruskul wallis test
*(P < 0.05) Statistically significant
However, regarding anxiety, there was a statistically significant difference across age groups (p = 0.035). Those over 50 years (median 6; interquartile range: 3.0 to 7.0) and those aged 31–40 years (median 6.0; interquartile range: 3.0 to 8.0) had the highest levels of anxiety compared to those aged 20 to 30 years and 41–50 years. Nurses with a Bachelor of Science in Nursing or a postgraduate degree tended to report higher anxiety levels than those with a diploma (p = 0.018).
Comparing sleep patterns of more or less than 7 h, a statistically significant p value was found (0.036), with anxiety median scores of 6.0 (interquartile range: 3.0 to 7.5) for nurses who slept less than 7 h.
No socio-demographic factors showed a statistically significant association with depression, suggesting that depressive symptoms did not vary meaningfully with age, education, living arrangement, or work hours in the sample studied. (Table 3).
Regression analysis
The relationships between predicted demographic and work-related factors and anxiety and burnout were examined. In the multiple linear regression models, Model 1 (burnout) included the variables: age, education, living status, and weekly working hours, while Model 2 (anxiety) included age, education, and weekly working hours. For burnout, the model showed that nurses living with children (β = -7.5; 95% CI: -12.73 to -2.27; p = 0.005) and those living with family (β = -4.0; 95% CI: -7.41 to -0.59; p = 0.022) had significantly lower burnout scores compared to those living alone. Nurses with a diploma had lower burnout than BSN holders (β = -2.5; 95% CI: -4.72 to -0.28; p = 0.027). However, weekly workload of more than 40 h per week, although associated with higher burnout (β = 1.5), did not reach statistical significance (p = 0.134), suggesting that while workload may contribute to burnout, its effect was not strong enough in the adjusted model.
For anxiety, nurses aged 31–40 years had significantly higher anxiety scores compared to those aged 20–30 (β = 3.0; 95% CI: 0.09 to 5.91; p = 0.043), though other predictors such as education and workload were not statistically significant. The R-squared for the burnout model was 0.068, indicating that approximately 6.8% of the variance in burnout was explained by the included predictors, and for the anxiety model, the R-squared was 0.047, indicating lower explanatory power. ; Table 4)
Table 4.
Regression analysis of Socio-demographic factors and their association with burnout, anxiety, and depression
| Factors | Burnout a | Anxiety b | ||
|---|---|---|---|---|
| Coefficient 95%(CI) |
p value | Coefficient 95%(CI) |
p value | |
| Age | ||||
| 20–30 years old | Ref | Ref | ||
| 31–40 years old | 2.5 (-2.96,7.96) | 0.368 | 3 (0.09,5.91) | 0.043 |
| 41–50 years old | 1 (-4.71,6.71) | 0.731 | 2 (-1.01,5.01) | 0.191 ` |
| > 50 years old | 0 (-6.12,6.12) | 0.999 | 3 (-0.31,6.31) | 0.075 |
| Education | ||||
| BSN | Ref | Ref | ||
| Diploma | -2.5 (-4.72, -0.28) | 0.027 | -1 (-2.51,0.51) | 0.195 |
| Master/Ph.D. | -1 (-4.2,2.2) | 0.539 | 1 (-1.14,3.14) | 0.357 |
| Living status | ||||
| Alone | Ref | - | - | |
| Children | -7.5 (-12.73, -2.27) | 0.005 | - | - |
| Couple | -0.5 (-5.13,4.13) | 0.832 | - | - |
| Family | -4 (-7.41, -0.59) | 0.022 | - | - |
| Roommate (s) | 0.5 (-5.33,6.33) | 0.866 | - | - |
| Weekly working load | ||||
| 40 h | Ref | Ref | ||
| More than 40 | 1.5 (-0.47,3.47) | 0.134 | 0.53 (-1.34,1.34) | 0.323 |
aModel (1): Adjusted burnout with age, education, living status, and weekly working hours
bModel (2): Adjusted anxiety with age, education, and weekly working hours
Although this study explored multiple predictors of mental health outcomes, regression analysis was not conducted for depression due to the absence of statistically significant associations in the bivariate analysis.
Discussion
This study aimed to explore the relationship between demographic characteristics, working conditions, and mental health outcomes specifically burnout, depression, and anxiety—among outpatient nurses in a general hospital in Qatar. By focusing on outpatient nurses, this research addressed a notable gap in existing literature that often emphasizes inpatient or critical care settings. The results indicated moderate levels of burnout and depression, and approximately onequarter of nurses reported borderline or abnormal anxiety. While concerning, these findings should be interpreted as indicators of risk rather than definitive diagnoses. They highlight the importance of monitoring and supporting the mental well-being of outpatient nurses, particularly in resourceconstrained settings.
Nurses aged 31 to 40 were particularly vulnerable to anxiety, which aligns with previous findings by Cañadas-De La Fuente et al. (2018), who also identified this age group as particularly susceptible to burnout [30]. Our study also found that nurses with higher educational qualifications were more likely to experience burnout. This finding is consistent with research conducted by Amin N at al. (2023) [31]. In contrast, Shahrour and Dardas (2020) found higher psychological distress among nurses under 30, suggesting that vulnerability may vary by setting and experience level [32].
Nurses with diplomas generally have fewer responsibilities, as their tasks tend to be more routine, leading to lower levels of stress [33].
Over time, this can result in higher levels of stress, job dissatisfaction, and an increased likelihood of leaving the profession [34] .Conversely, (Rashedi et al., 2014)found that less qualified nurses, who may lack extensive training and confidence, are more likely to encounter greater challenges in their roles, potentially leading to higher turnover rates within the nursing field [35]. Additionally, our study revealed that unmarried, childless and female nurses are more prone to anxiety [30]. Previous research supports this finding, showing elevated levels of depression and burnout among these groups [36]. The increased vulnerability of these nurses may be attributed to the demanding nature of their work, combined with the absence of a supportive family environment that could help mitigate negative attitudes towards colleagues. Interestingly, having parental responsibilities appears to reduce the likelihood of burnout, as they can decrease emotional overload and the sense of being overworked [30].
However, other studies have presented a different perspective. Rashedi et al.(2014) identified added responsibilities and conflicts between work and family life as factors that exacerbate burnout among married nurses [35]. Factors such as geographical location, organizational culture, and family status can influence a nurse’s well-being, leading to different outcomes in different settings [37]. The variability in research findings regarding factors predicting mental well-being may also be attributed to differences in methodologies, sample populations, statistical analyses, and organizational structures across studies. Predictive factors can moderate and influence the relationship between other variables and mental health, with specific combinations—such as sex, job satisfaction, and workplace culture—potentially contributing to the extent of their impact. While there are no specific tools or tangible means for gauging nursing staff shortages, it remains a long-standing issue that has been raised for more than two decades [38, 39]. Evidence indicates that the situation has deteriorated over time. Nursing shortages can be both a major cause and consequence of mental health problems [40]. If this issue persists, it will hinder healthcare delivery and negatively impact nurses’ physical and psychological well-being [41, 42]. In general, participants in our study reported moderate levels of mental health issues. This finding is similar to that of (Alfuqaha et al., 2019), who also found moderate levels of burnout among Jordanian nurses facing high workloads and inadequate resources [43]. (Mahmoudi et al., 2020) identified high levels of stress and burnout amongst Iranian nurses, as explained by the workload issues created by short staffing. In the context of more comprehensive research, our study predicted that mental health issues will be aggravated for the same reasons [44].
In Saudi Arabia, (Qedair et al., 2022) discovered that inpatient nurses experience higher levels of stress than those working in outpatient settings [45]. However, nurses in our study reported moderate levels of mental health impairment, which should not be overlooked. A study involving 50,000 registered nurses in the U.S. revealed that 31.5% of them left their jobs due to burnout [45]. Mental exhaustion often triggers staff shortages, creating a cycle of negative consequences. Adequate staffing is essential to ensure quality care and improve patient outcomes. Mental exhaustion often triggers staff shortages, creating a cycle of negative consequences [46]. Nursing shortages are a global issue, and the Gulf Countries Council region is not immune. Approximately 52% of the Gulf Countries Council population, or about 30 million people, are foreign nationals, with this percentage varying widely within the region—from 39% in Saudi Arabia to 88% in Qatar [47]. This reliance on expatriate labour leads to demographic imbalances, particularly in the nursing workforce. Expatriate nurses account for 51% of the nursing workforce in Oman [32], around 60–70% in Saudi Arabia [48], and 90% in Qatar [49] .
This heavy dependence on expatriate nurses can lead to workforce instability and potentially create a crisis if they decide to leave the country.
Nursing careers in the Gulf Countries Council face numerous challenges due to various factors [50]. While much of the research on this issue comes from Saudi Arabia, the findings are applicable across the Gulf region due to similar socio-demographic factors. Recruiting nationals for nursing education poses a challenge due to the profession’s less favourable reputation, which hinders the growth of the healthcare system and necessitates substantial resources for nurse recruitment and training (20). Additionally, cultural norms in Saudi Arabia often discourage women from working as nurses, leading many Saudi female nurses to prefer weekday shifts or outpatient clinics to better accommodate their family needs [48]. Expatriate nurses often fill the remaining shifts, contributing to dissatisfaction and potentially harming their well-being [51]. This was evident in a study by (Qedair et al., 2022) which found that non-Saudi nurses exhibited significantly higher rates of burnout than their Saudi counterparts [45]. Moreover, non-Saudi registered nurses often show lower resilience than Saudi nationals, possibly due to difficulties adapting to local cultural and social standards [34]. This lack of emotional attachment to the organisation significantly predicts expatriate nurses’ turnover. This high turnover, coupled with short-term contracts, contributes to frequent staff shortages [32].
Our survey sample included 98% of migrant staff, suggesting that the related problems outlined above are likely to be particularly concerning in Qatar, even compared to other countries in the Gulf region. This heavy reliance on expatriate nurses poses a significant challenge to the stability and sustainability of the regional nursing workforce. If these issues are not addressed, they could exacerbate the existing mental health problems among nurses. The discussion section provides a sound overview of the existing literature. However, to further strengthen the manuscript, I encourage you to integrate a more explicit interpretation of your own findings in relation to these existing studies. Elaborate on how your results either support, contradict, or expand upon the current understanding of the topic. Providing your unique perspective and insights based on your data will significantly enhance the value of the discussion.
Limitations
This study has several limitations. First, its cross-sectional design prevents establishing causal links between workload, demographics, and mental health outcomes. Second, self-reported measures may have introduced recall or social desirability bias. Third, although validated instruments were used, cultural nuances may not have been fully captured in a multinational workforce. Fourth, the sample consisted almost entirely of expatriate nurses (98%), limiting generalizability to Qatari nationals. Finally, regression models explained only a small proportion of variance (6.8% for burnout, 4.7% for anxiety), indicating that additional unmeasured factors likely play a substantial role. Additionally, although English was the language used for the survey, all participants were non-native speakers. This raises the possibility of subtle misunderstandings regarding specific questions or answer choices, and some questions may have been interpreted differently by participants from diverse backgrounds.
To the best of our knowledge, this is the first cross-sectional study of its kind conducted among outpatient nurses at a general hospital in Qatar. Moreover, while the nature of the study may not capture fluctuations in mental health and staffing levels, it can pave the way for a more comprehensive scrutiny of the long-term dynamic relationship between these variables. Therefore, it contributes to the limited knowledge within this population.
Recommendations
To address the mental health challenges and workforce shortages highlighted in this study, stronger regional collaboration is essential. Standardizing nursing education across the GCC and Middle East can ensure consistent training and improve cross-border mobility. Harmonizing licensing and credentialing systems through mutual recognition agreements would streamline recruitment processes. Joint recruitment strategies such as regional scholarships and public campaigns can help attract national talent into the nursing profession. Targeted retention strategies, including flexible scheduling and confidential counseling services, could be beneficial. However, the effectiveness of these approaches should be evaluated in future studies before widespread adoption.
Establishing a regional mental health support framework with standardized burnout management protocols would further support nurse well-being. Access to confidential counseling, peer support programs, and manager-led mental health training should be prioritized. A centralized GCC Nursing Workforce Observatory could track staffing trends, migration, and burnout to inform policy decisions. Promoting multi-country research on nurse well-being and retention can generate locally relevant evidence. These coordinated actions will enhance workforce resilience, ensure sustainable staffing, and strengthen the overall quality of care across the region.
Conclusions
This study found moderate levels of burnout and depression and identified that a smaller proportion of outpatient nurses reported abnormal anxiety. Associations with age, educational level, and living status were observed but explained only limited variance. These findings underscore the importance of monitoring nurse well-being in outpatient settings but should be interpreted cautiously given methodological constraints. Future longitudinal and mixedmethods studies are needed to better understand causal pathways and to inform tailored interventions.
Relevance of clinical practice
To the researcher’s knowledge, this was the first cross-sectional study conducted among OPD nurses at Hamad General Hospital in Qatar. While the study’s design may not reflect changes in mental health and staffing levels over time, it serves as a basis for a more in-depth examination of their long-term relationship. As such, it contributes to the limited existing knowledge in this population group.
Supplementary Information
Below is the link to the electronic supplementary material.
Acknowledgements
Sincere appreciation is extended to Ms. Khadija Al Shukaili, Executive Director of Nursing & Midwifery at Hamad General Hospital, and her staff for their support of this project.
Author contributions
The authors confirm contribution to the paper as follows: Conceptualization, Methodology: ANA, AO and KS; Data Curation: ANA; Analysis and interpretation of results: KS and AO; Writing - Original Draft; ANA; Review & Editing: AO and KS, Writing - Review & Editing the Final Draft: ANA and KS. All authors read and approved of the final manuscript.
Funding
The publication of this article was funded by the Medical Research center at Hamad medical corporation.
Data availability
Data and materials are available upon request, subject to certain access restrictions related to ethical, legal, or commercial sensitivities. Requests can be made to the corresponding author.
Declarations
Competing interests
The authors declare no competing interests.
Footnotes
Publisher’s note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
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Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Supplementary Materials
Data Availability Statement
Data and materials are available upon request, subject to certain access restrictions related to ethical, legal, or commercial sensitivities. Requests can be made to the corresponding author.