Alarm Fatigue and Professional Quality of Life Among Nursing Staff in Intensive Care Settings in Jordan: A Cross‐Sectional Study

ABSTRACT

Background

Alarm fatigue occurs when nursing staff are exposed to clinically excessive false alarms, leading to sensory overload and desensitization. It is a global occupational health concern in intensive care settings, with numerous studies investigating this complex phenomenon.

Aim

To investigate the levels of alarm fatigue, its determinants and its association with professional quality of life among nurses in intensive care settings in Amman, Jordan.

Study Design

A cross‐sectional descriptive quantitative study was conducted. All nurses were recruited from eight hospitals in Amman, Jordan, representing public, educational and private sectors. Data were collected using alarm fatigue and professional quality of life questionnaires. The data were analysed using chi‐squared, one‐way ANOVA, Kruskal–Wallis and multiple linear regression.

Results

In total, 250 nurses were recruited. Overall, 59.2% of nurses reported moderate alarm fatigue, and 28.8% reported severe alarm fatigue. Burnout and secondary traumatic stress were significantly associated with alarm fatigue (p < 0.001). Five factors (shift type, hospital sector, burnout, secondary traumatic stress and compassion satisfaction) explained 16.5% of the variance in alarm fatigue scores. Compassion satisfaction was not significantly associated with alarm fatigue, suggesting that nurses may retain professional fulfillment despite high alarm exposure. Shift type (p = 0.031) and hospital sector (p = 0.042) were significantly associated with alarm fatigue. Intensive care nurses working on ABC shift patterns and in the public sector experienced high levels of alarm fatigue.

Conclusions

The findings highlight the necessity of nursing administrators to develop alarm management policies and training courses for intensive care nurses. Nursing education policymakers should incorporate alarm fatigue and burnout concepts into nursing curricula.

Relevance to Clinical Practice

This study reveals how alarm fatigue adversely affects nurses' professional quality of life in intensive care settings. It provides evidence for targeted interventions to reduce alarm fatigue and improve nurse well‐being.

Impact Statements

• What is known about the topic

  • ○
    Nurses in critical care settings are frequently exposed to alarm fatigue, which has been linked to burn, stress, staff turnover and poor sleep quality.
  • ○
    Few studies in Western, Asia and Middle Eastern countries have examined its association with the professional quality of life.
• What this paper adds

  • ○
    To our knowledge, this study is among the first in the Middle East to investigate alarm fatigue in a large sample of intensive care nurses and to examine its relationship with burnout and secondary traumatic stress.
  • ○
    This study also identified key predictors of alarm fatigue, including shift type, hospital sector, burnout, secondary traumatic stress and compassion satisfaction.
  • ○
    These findings enhance understanding of alarm fatigue in Jordan and highlight the need for targeted interventions to improve nurses' well‐being and the quality of patient care in Jordan and similar Middle Eastern healthcare settings.

1. Background

The critical environment is highly demanding, characterized by high patient acuity, complex technology and the need for constant vigilance, all of which contribute to fatigue and reduced performance among nurses [1]. In these settings, nurses continuously monitor patients and respond to medical alarms generated by physiological monitors, telemetry systems, infusion pumps and ventilators [2, 3, 4, 5]. Excessive exposure to false or clinically insignificant alarms leads to alarm fatigue, which may result in desensitization, delayed responses, missed alarms, inappropriate alarm deactivation and reduced trust in clinical alarm systems [6, 7, 8, 9, 10].

In 2020, the Emergency Care Research Institute (ECRI) identified medical alarm hazards among the top 10 health technology risks [11]. Alarm fatigue is increasingly recognized as an occupational health concern that affects frontline nurses and compromises patient safety and quality of care [5].

Professional quality of life (ProQOL) consists of three components: compassion satisfaction, which promotes resilience and job fulfillment; burnout, characterized by emotional exhaustion and reduced professional efficacy; and secondary traumatic stress, which results from indirect exposure to trauma and may cause intrusive thoughts, sleep disturbances, fear and avoidance behaviours. ProQOL is measured using the 30‐item Professional Quality Of Life Questionnaire, developed by Figley in 1995 and revised in 2005 and 2009 [12]. Poor professional quality of life has been linked to absenteeism, job dissatisfaction and compromised patient care [13, 14, 15, 16, 17, 18]. Alarm fatigue contributes to occupational stress, burnout and decreased professional efficacy [19, 20, 21, 22]. Chronic exposure to alarms has been associated with burnout and secondary traumatic stress, both key components of compassion fatigue [23, 24, 25]. Previous studies have reported significant associations between alarm fatigue, burnout and compassion fatigue—core elements of ProQOL—particularly among ICU nurses, who may be especially vulnerable to these conditions [15, 19, 20, 21, 22, 23, 24, 25]. Nevertheless, empirical evidence examining how alarm fatigue specifically affects real‐time professional quality of life in Jordanian ICUs—beyond general stress or burnout inventories—remains limited, particularly across different hospital sectors (public, private and educational). Compassion fatigue represents the negative dimension of ProQOL (burnout, secondary traumatic stress), whereas compassion satisfaction reflects its positive dimension [12]. Therefore, this study aims to examine the association between alarm fatigue and professional quality of life among ICU nurses in Jordan, using a descriptive, cross‐sectional, correlational design, with the goal of informing alarm management policies and nurse well‐being strategies in Jordanian intensive care settings.

Jordan is small, resource‐constrained, middle‐income in the Middle East, with a population of 11.06 million [26]. Its healthcare system includes governmental, private, Royal Medical Services and university‐affiliated hospitals. According to the Ministry of Health (2022) Jordan has 31 479 registered nurses and 5935 associate nurses. The governmental sector operates 31 hospitals with 5884 beds and employs 7655 registered nurses and 2097 associate nurses, with an occupancy rate of 73.2%. The educational sector includes two hospitals: Jordan University Hospital (625 beds; 69.0% occupancy) and King Abdullah University Hospital (611 beds; 69.3% occupancy). The Royal Medical Services manage 15 hospitals (3350 beds; 66.6% occupancy), whereas the private sector includes 70 hospitals with 5529 beds (40.3% occupancy) and employs 17 258 nurses [27]. According to the World Health Organization (2023), Jordan has 33.33 nursing and midwifery personnel per 10 000 population [28]. Nurse‐to‐patient ratios vary by hospital sector and unit, with ratios of approximately 1:1 in private hospitals and 1:2 in public hospitals [29]. In Jordanian and broader Middle Eastern nursing contexts, occupational stress and burnout have been linked to reduced patient safety outcomes [13, 14]. However, alarm fatigue extends beyond general stress to include technology‐related desensitization and delayed clinical responses.

According to the World Health Organization (2023), Jordan has 33.33 nursing and midwifery personnel per 10 000 population [30]. Nurse‐to‐patient ratios vary by hospital sector and unit, with ratios of approximately 1:1 in private hospitals and 1:2 in public hospitals [31]. In Jordanian and broader Middle Eastern nursing contexts, occupational stress and burnout have been linked to reduced patient safety outcomes [15, 16]. However, alarm fatigue extends beyond general stress to include technology‐related desensitization and delayed clinical responses.

1.1. Literature Gap

Previous studies conducted in Jordan have examined alarm fatigue and professional quality of life as separate phenomena [30, 31, 32, 33]. However, research exploring the relationship between these constructs—particularly while considering socio‐demographic factors and variations across organizational and healthcare system characteristics—remains limited in Western, Asian and Middle Eastern contexts, including Jordan. Thus, this study provides empirical, quantitative evidence on alarm fatigue as a distinct occupational phenomenon that may modify professional quality of life—a dimension not fully captured by separate studies of burnout or stress alone. Addressing this gap is essential to generate evidence that can inform targeted interventions, enhance nurses' well‐being and improve patient care across healthcare systems in the region.

1.2. Study Aims and Research Questions

This study aimed to investigate the levels and determinants of alarm fatigue and its association with professional quality of life among nursing staff working in intensive care settings in Jordan. To achieve this aim, the following research questions were formulated:

What are the levels of alarm fatigue among nursing staff in Jordan's intensive care settings?

Is alarm fatigue associated with the three components of professional quality of life (burnout, secondary traumatic stress and compassion satisfaction) among nursing staff in Jordan's intensive care settings?

Are nurses' socio‐demographic and professional characteristics (age, sex, marital status, number of children, educational level, monthly income, hospital sector, shift type, work unit, length of experience, nurse‐to‐patient ratio, alarm management training) associated with their levels of alarm fatigue?

What are the key determinants of alarm fatigue among nursing staff in Jordan's intensive care settings?

2. Design and Methods

2.1. Ethical Considerations

Ethical approval was obtained from the research committees of the eight participating hospitals. Private hospitals provided administrative approval for participation. Informed consent emphasized voluntary participation, anonymity and the right to withdraw at any time. Permission to use all research instruments was obtained from the original authors Participants received no financial or other incentives; all responses were anonymized using unique participant codes (Appendices B and E in the Supporting Information).

Ethical approval details are as follows: Educational Hospital (Jordan University Hospital): 29‐02‐2024, approval no: 1020246259. Governmental hospital (Al Basheer Hospital): 23‐01‐2024, approval no: NA. Governmental hospital (Prince Hamza Hospital): 04‐03‐2024, approval no: 2987. Private hospital (Jordan Hospital): 23‐01‐2024. Private hospital (Al Istishari Hospital): 25‐01‐2024. Private hospital (Al Khalidi Hospital): 24‐01‐2024. Private hospital (Al Hayat General Hospital): 25‐01‐2024. Private hospital (Arab Medical Centre): 24‐03‐2024.

2.2. Study Design

A descriptive cross‐sectional quantitative design was used to examine alarm fatigue and professional quality of life. Socio‐demographic and professional characteristics—including age, sex, marital status, number of children, income, hospital sector, educational level, intensive care experience, nurse‐to‐patient ratio, shift type, unit type and alarm management training—were considered independent variables.

2.3. Study Settings

The study was conducted in eight hospitals in Amman, representing three healthcare sectors: public, educational and private sectors which were randomly selected. Hospital names are withheld for blinded peer review; however, the sample included two public hospitals, one educational hospital and five private hospitals in Amman, Jordan.

Nurses worked under different scheduling systems. Some followed a rotating three‐shift system—A shift (7 AM–3 PM), B shift (3 PM–11 PM) and C shift (11 PM–7 AM)—whereas others worked combined shifts (AB or BC), resulting in 8‐ or 16‐h duty periods. In other hospitals, nurses worked a two‐shift system consisting of 12‐h day and night shifts.

2.4. Sample Size and Sampling

Participants were registered nurses working in critical care settings (CCUs, ICUs, NICUs, SICUs, PICUs). The sample size was calculated using G*POWER (Version 3.1.9.7) [34], with α = 0.05, power = 0.8, effect size f ² = 0.072 [17] resulting in a required sample of 226 nurses. To account for potential missing data, the final sample was increased to 250 participants.

A multistage cluster sampling technique was employed (Figure 1). In the first stage, hospitals were randomly selected from different healthcare sectors. In the second stage, intensive care units were randomly selected based on unit size. In the final stage, convenience sampling was used due to rotating shifts, heavy workloads and variable nurse availability during data collection, which made probabilistic sampling impractical. Nurses who met the inclusion criteria and were available at the time of data collection were invited to participate. All questionnaires were administered electronically using Google Forms. The head nurses of the participating ICUs facilitated recruitment by sharing the survey link with eligible nurses. In addition, the principal investigator, a master's degree researcher, directly approached eligible participants and invited them to participate in the study.

FIGURE 1.

Cluster sampling chart (N = 250).

A response rate could not be calculated because the total number of eligible ICU nurses who received or viewed the survey invitation across the participating hospitals could not be determined due to electronic distribution through professional networks.

Inclusion criteria: bedside care providers with ≥ 6 months ICU experience in a staff nurse role.

Exclusion criteria: nurses in administrative roles or with < 6 months of ICU experience.

2.5. Data Collection Tools

1. Socio‐demographic questionnaire: Collected participant characteristics (Appendix D in the Supporting Information).

2. Alarm fatigue questionnaire: A 13‐item instrument scored on a 5‐point Likert scale (total score range 0–52). Scores are categorized as: 0–7 (no alarm fatigue), 8–20 (low), 21–32 (moderate) and 33–52 (severe). The tool demonstrated strong content validity (CVI = 0.92) and reliability (Cronbach's α = 0.91) [13, 17]. Prmission to use the instrument was obtained from the original author (Appendices A and B in the Supporting Information).

3. Professional quality of life questionnaire: A 30‐item scale comprising three subscales: Compassion Satisfaction (α = 0.88), Burnout (α = 0.75) Secondary Traumatic Stress (α = 0.81). Responses are rated on a 5‐point Likert scale and categorized as low, average or high. The instrument is publicly available and does not require permission for use [12] (Appendix C in the Supporting Information).

Thus, higher AF scores indicate greater alarm fatigue (range 0–52, with ≥ 33 classified as severe), whereas higher ProQOL subscale scores indicate greater compassion satisfaction, burnout or secondary traumatic stress.

Both questionnaires were administered in English, as nursing education and clinical documentation are primarily conducted in English. Previous Jordanian studies have successfully used the English versions of these instruments [30, 31, 33].

2.6. Data Collection Procedure

Ethical approvals were obtained from the participating hospitals between January and March 2024. The researcher met with unit head nurses to explain the study purpose and procedures. Participants were recruited using convenience sampling, and informed consent was obtained electronically before survey completion (Appendix E in the Supporting Information).

2.7. Data Analysis

Data were analysed using IBM SPSS Statistics (Version 27) [35]. Descriptive statistics (frequencies, percentages, means and standard deviations) were calculated for socio‐demographic variables, alarm fatigue and ProQOL scores.

Chi‐squared tests examined associations between alarm fatigue categories and ProQOL components. One‐way ANOVA, chi‐squared and Kruskal–Wallis tests were used to assess the relationship between alarm fatigue and socio‐demographic characteristics.

Multiple linear regression analysis was conducted to identify predictors of alarm fatigue. Statistical significance was set at p < 0.05 with 95% confidence intervals.

3. Results

3.1. Sample Characteristics

All 250 nurses worked in intensive care units of eight hospitals in Amman, Jordan; no participants were excluded due to incomplete data, of whom 60.4% (n = 151) were female, 39.6% (n = 99) were male. Participants' ages ranged from 22 to 56 years (M = 32.31, SD = 6.72). Most were married (58%, n = 145), held a bachelor's degree in nursing (83.2%, n = 208) and worked in the public sector (52.4%, n = 131). The majority of nurses (78%) worked rotating A/B/C shifts, and 62% had not received formal alarm management training. Mean monthly income was 593.59 JD (SD = 191.84). Critical care experience ranged from 0 to 27 years (M = 8.05, SD = 5.91) (Table 1).

TABLE 1.

Sample characteristics (N = 250).

Characteristic	n (%)	Min–max	Mean (SD)
Age		22–56	32.31 (6.72)
Sex
Male	99 (39.6)
Female	151 (60.4)
Marital status
Single	94 (37.6)
Married	145 (58)
Divorced/widow	11 (4.4)
Number of children
None	115 (46)
One	30 (12)
Two	32 (12.8)
Three	42 (16.8)
Four and more	31 (12.4)
Educational level
Undergraduate (associate/BSN)	208 (83.2)
Graduate degree (MS/PhD)	42 (16.8)
Hospital sector
Governmental	131 (52.4)
Educational	59 (23.6)
Private	60 (24.0)
Shift type
A/B/C shifts	195 (78)
Day/night shifts	55 (22)
Unit of work
General ICCU/CCU/medical ICU	145 (58)
Neurological ICU/surgical ICU/kidney transplant unit	52 (20.8)
Emergency ICU	26 (10.4)
Paediatric ICU/neonatal ICU	27 (10.8)
Patient assigned average number
One	13 (5.2)
Two	76 (30.4)
Three	86 (34.4)
Four	23 (9.2)
Five and more	52 (20.8)
Alarm management courses
Taken	95 (38)
Not taken	155 (62)
Monthly income in Jordanian Dinar	186	260–1750	593.59 (191.84)
Length of intensive care units work experience		0–27	8.05 (5.91)

Abbreviation: SD: standard deviation.

3.2. Alarm Fatigue and Professional Quality of Life Scores

The mean alarm fatigue score was 28.39 (SD = 6.54; range 8–44). Low alarm fatigue was reported by 12% (n = 30), moderate by 59.2% (n = 148) and severe by 28.8% (n = 72).

For ProQOL subscales, the mean compassion satisfaction score was 38.55 (SD = 6.86; range 10–50); low compassion satisfaction was reported by 3.2% (n = 8), moderate by 61.6% (n = 154) and high by 35.2% (n = 88).

The mean burnout score was 28.42 (SD = 4.04; range 12–39). Low burnout was reported by 8.4% (n = 21), moderate by 91.6% (n = 229), and no participants reported high burnout.

The mean secondary traumatic stress was 31.50 (SD = 7.29; range 10–50). Low levels were reported by 11.6% (n = 29), moderate by 82.4% (n = 206) and high by 6% (n = 15).

3.3. Relationships Between Alarm Fatigue and ProQOL and Socio‐Demographic Differences in Alarm Fatigue Scores

Alarm fatigue scores were significantly associated with burnout and secondary traumatic stress scores. No significant association was found between alarm fatigue and compassion satisfaction (Table 2).

TABLE 2.

Socio‐demographic differences in total alarm fatigue score and the relationships between alarm fatigue and professional quality of life aspects (N = 250).

Variable	F	df between groups	df total	p
Compassion satisfaction	0.040	2	249	0.961
Burnout	11.14	2	249	0.000*
Secondary traumatic stress	35.99	2	249	0.000*

Alarm fatigue category	n (%)		n (%)
	Shift type		Hospital sector
	A/B/C	Day/night	Public	Educational	Private
Low alarm fatigue	18 (9.2)	12 (21.8)	11 (36.7)	12 (40)	7 (23.3)
Moderate alarm fatigue	117 (60)	31 (56.4)	74 (50.5)	33 (22.3)	41 (27.7)
Severe alarm fatigue	60 (30.8)	12 (21.8)	46 (63.9)	14 (19.4)	12 (16.7)

Abbreviation: df: degrees of freedom.

^*Statistically significant, p < 0.001.

Significant associations were observed between alarm fatigue levels, hospital sector (p = 0.042) as well as shift type (p = 0.031) (Table 3). Nurses working rotating A/B/C shifts had higher proportions of severe alarm fatigue compared with those working day–night shifts. Nurses working in public hospitals had higher proportions of severe alarm fatigue (63.9%) compared to those in educational (19.4%) or private (16.7%) hospitals.

TABLE 3.

Two‐step multilinear regression models of hospital sector, shift type, compassion satisfaction score, burnout score and secondary traumatic stress score on alarm fatigue (N = 250).

Model	Factor	Standardized beta	t	p	Adjusted R 2	R 2 change
1	Hospital sector	−0.138	−1.923	0.056	0.022	0.030*
	Shift type	−0.057	−0.788	0.431
2	Hospital sector	−0.087	−1.295	0.197	0.1548	0.1355*
	Shift type	−0.080	−1.186	0.237
	Compassion satisfaction score	0.006	0.093	0.926
	Burnout score	0.174	2.530	0.012*
	Secondary traumatic stress score	0.263	3.983	0.000*

Note: Overall model F(df) 9.625 (5), p = 0.000, R ² = 0.165, adjusted R ² = 0.148.

^*Statistically significant, p < 0.001.

No significant associations were found between alarm fatigue scores and age, sex, marital status, number of children, educational level, work unit, nurse–patient ratio or participation in alarm management training.

The Kruskal–Wallis test indicated no significant differences in alarm fatigue based on years of work experience (H(2) = 1.376, p = 0.503) or monthly income (H(2) = 3.720, p = 0.156).

Although alarm fatigue levels varied across critical care units, with moderate fatigue being most common, unit type was not significantly associated with alarm fatigue.

3.4. Predictors of Alarm Fatigue

A two‐step multiple linear regression analysis was conducted. In Model 1, hospital sector and shift type were entered, explaining 3% of the variance in alarm fatigue (R ² = 0.03, p = 0.024). In Model 2, compassion satisfaction, burnout and secondary traumatic stress were added, increasing the explained variance to 16.5% (ΔR ² = 0.135, p < 0.001).

Burnout (β = 0.174, p = 0.012) and secondary traumatic stress (β = 0.263, p < 0.001) were significant predictors of alarm fatigue, whereas compassion satisfaction was not. The regression model was statistically significant (F = 9.625, p < 0.001) but explained only 16.5% of the variance in alarm fatigue, indicating that burnout and secondary traumatic stress, while associated, are not the dominant determinants (Table 3).

4. Discussion

4.1. Alarm Fatigue Levels

Our findings that ICU nurses in Jordan experience moderate alarm fatigue align with Salameh et al. in Palestine and Alkubati et al. in Saudi Arabia, suggesting that moderate alarm fatigue is a consistent finding across Middle Eastern ICUs. International ICU settings report similar levels of alarm fatigue among critical care nurses [16, 17, 19, 20, 30, 32, 36, 37, 38]. The high‐intensity nature of critical care—characterized by heavy workload, continuous monitoring and frequent alarms—likely contributes to this pattern.

Variations in alarm fatigue levels across studies may reflect differences in workplace design, workload and organizational culture. Suboptimal ICU layouts, inefficient equipment placement and long walking distances increase physical and cognitive demands, which may contribute to fatigue [4, 9, 16, 17, 18, 19, 37, 38, 39, 40, 41, 42, 43, 44]. Alarm management practices, availability of structured policies, training and nurses' education and experience levels may also influence alarm fatigue [7, 36, 44].

Contextual healthcare differences may further explain these findings. A comparison between ICU nurses in Jordan and the United Arab Emirates showed that Jordanian nurses reported higher workloads and patient ratios, which may contribute to fatigue levels observed. In this study [43].

Overall, the literature suggests that moderate alarm fatigue is common among ICU nurses globally and requires targeted interventions.

4.2. Professional Quality of Life and Its Association With Alarm Fatigue

Nurses demonstrated moderate‐to‐high compassion satisfaction, moderate burnout and moderate secondary traumatic stress. Burnout and secondary traumatic stress were significant predictors of alarm fatigue, indicating that psychological strain plays a key role in nurses' responses to alarm burden. Similarly, Aqtam and Shouli (2026) reported that moral distress and psychological trauma among nurses in West Bank governmental hospitals were associated with reduced professional quality of life, reinforcing the link between psychological strain and occupational outcomes in the region. These findings align with research among critical care nurses in other contexts [15, 19, 20, 21, 22, 23, 24, 25, 45, 46].

The absence of a significant association between alarm fatigue and compassion satisfaction suggests that nurses may retain a sense of professional meaning despite high workload and stress. Professional values, resilience and ethical work climates may buffer the negative impact of alarm [14, 46].

Previous research generally shows positive associations between alarm fatigue, burnout and secondary traumatic stress and an inverse relationship with compassion satisfaction [17, 45]. However, some studies have reported no direct relationship between alarm fatigue and professional quality of life, although a substantial problem of nurses experiencing alarm fatigue were identified as being at risk for compassion fatigue and near risk for burnout [7]. These findings suggest that contextual, cultural and organizational factors may influence how alarm fatigue relates to professional equality of life, highlighting the importance of considering psychosocial and workplace factors when addressing alarm fatigue.

4.3. Alarm Fatigue Determinants and Associating Factors

Hospital sector and shift type were significantly associated with alarm fatigue. Nurses working in public hospitals and rotating shifts reported higher fatigue levels. Public hospitals in Jordan often operate under high occupancy and resource constraints, which may increase workload and exposure to alarms [17, 36]. This finding is consistent with Ayed et al., who reported that perceived worries about AI adoption among NICU nurses were higher in under‐resourced settings, suggesting that systemic resource limitations may amplify occupational stressors such as alarm fatigue. Overcrowding and staffing pressure can intensify cognitive load and stress, contributing to fatigue [47, 48, 49, 50].

Although the nurse‐to‐patient ratio was not a significant factor in this study, most participants cared for multiple patients simultaneously. Prior research suggests higher patient loads are linked to increased alarm fatigue, though underreporting may occur due to desensitization [7, 16, 36].

Shift work also appears to contribute to fatigue. Rotating and night shifts are associated with sleep disruption, stress, reduced performance and psychological strain [7, 16, 17, 47]. Evidence from Jordan indicates that night‐shift healthcare workers experience poorer sleep and higher psychological distress [48, 49].

Although unit type was not significantly associated with alarm fatigue, critical care environments are consistently reported as high‐risk settings due to technological intensity and constant monitoring demands [7, 16, 19, 41].

4.4. Predictors of Alarm Fatigue

Burnout and secondary traumatic stress were the strongest predictors of alarm fatigue. These findings emphasize the role of psychological well‐being in shaping nurses' response to alarm exposure. Previous research has also highlighted demographic, occupational and organizational factors—including workload, experience and alarm management practices as contributors [16, 17, 18, 19, 37]. While burnout and secondary traumatic stress were significant predictors, the low R ² (0.165) suggests that other factors—such as moral distress [13], resilience [50] or unit layout [42]—may play important roles. Evidence suggests that structured align management training, improved staffing adequacy and system‐level alarm customization may help mitigate alarm fatigue [51, 52, 53, 54, 55]. Effective interventions should integrate behavioural and organizational strategies, including training, shift scheduling optimization and evidence‐based alarm management protocols.

4.5. Limitations of the Study

This study has several limitations. First, although a multistage cluster design was planned, the final relied on convenience sampling due to workload constraints, which may have introduced selection bias. Second, the use of self‐administered questionnaires may have resulted in response and social desirability biases. Third, data collection via an online platform required internet access, which may have limited participation for some nurses.

Fourth, the sample was limited to Amman, Jordan, with a predominantly female sample (60.4%); findings may not be generalizable to male‐majority ICU teams or to healthcare systems with different alarm management technologies.

Fifth, the cross‐sectional design precludes any causal inference; the reported ‘prediction’ is statistical, not temporal or causal.

Sixth, the study did not objectively measure alarm response times or false alarm rates; self‐reported alarm fatigue scores may be subject to recall or desirability bias. Finally, although English versions of the instruments were used, this is unlikely to have significantly affected validity, as English is the primary language of nursing education and documentation in Jordan, and these tools have been successfully used locally. The study also did not examine institutional alarm policies or technological differences across hospitals, which may influence alarm burden.

5. Implications

These findings support the need for multi‐level interventions targeting both organizational systems and nurses' psychological well‐being. At the clinical level, structured alarm management training and standardized, patient‐tailored alarm protocols should be implemented. From a managerial perspective, optimizing shift systems, promoting supportive leadership, strengthening teamwork and ensuring manageable workloads are essential to reduce alarm burden. In‐service training should focus not only on alarm management technical skills but also on psychological coping strategies to mitigate burnout and secondary traumatic stress.

At the policy level, the development of national alarm management guidelines and investments in smart alarm technologies may help address systemic contributors to alarm fatigue. Integrating alarm management competencies into undergraduate and continuing nursing education can further strengthen safe alarm practices. Hospital administrators should consider shift type and hospital sector when designing alarm management protocols, as these factors significantly influence alarm fatigue levels.

Nursing curricula should integrate alarm fatigue and professional quality of life as core competencies, using simulation‐based training from ICU settings.

Future research should prioritize longitudinal and interventional studies to examine casual pathways and evaluate the effectiveness of organizational and behavioural strategies in reducing alarm fatigue.

6. Conclusion

This study found that critical care nurses in Jordan experience predominantly alarm fatigue, which was significantly associated with burnout and secondary traumatic stress, but not compassion satisfaction. Hospital sector and shift eye were significantly related to alarm fatigue levels. Burnout and secondary traumatic stress emerged as key predictors, highlighting the close interplay between psychological strain and alarm‐related burden in critical care environments. These findings underscore the need for organizational and psychosocial strategies to mitigate alarm fatigue and support nurses' professional quality of life.

Funding

The authors have nothing to report.

Ethics Statement

This study was approved by the Institutional Review Board (IRB) committees of multiple hospitals in Jordan. Ethical approval details are as follows: The University of Jordan, School of Nursing (affiliated university hospital: Jordan University Hospital) (approval no: 1020246259 | approval date: 29‐02‐2024). Al Bashir Hospital (governmental hospital) (approval no: 3652 | approval date: 23‐01‐2024). Prince Hamza Hospital (governmental hospital) (approval no: 2987 | approval date: 04‐03‐2024). Al‐Istishari Hospital (private hospital) (approval obtained verbally from administrators on 25‐01‐2024) Al‐Kaldi Medical Centre (private hospital) (approval obtained on 25‐01‐2024 [no approval number]). Al‐Hayat General Hospital (private hospital) (approval obtained verbally from administrators on 24‐01‐2024). Jordan Hospital (private hospital) (approval obtained on 25‐01‐2024 [no approval number]). Arab Medical Centre (private hospital) (approval no: 43 | approval date: 24‐03‐2024). All procedures followed the ethical guidelines of the Declaration of Helsinki.

Consent

Written informed consent was obtained from all participating nurses before data collection.

Conflicts of Interest

The authors declare no conflicts of interest.

Supporting information

Supporting Information: S1: The supplementary material includes the data collection questionnaire and relevant study consent/approval documents.

Data Availability Statement

The datasets generated and analysed during the current study are available from the corresponding author upon reasonable request.