Factors Associated with Insomnia and Aggression among Healthcare Workers during COVID-19 Pandemic
Abstract
:1. Introduction
- There is a relationship between the occurrence of insomnia, sleep disturbance, and increased aggression among medical personnel during the COVID-19 pandemic.
2. Materials and Methods
2.1. Settings and Design
2.2. Research Instruments
- The Buss–Perry Aggression Questionnaire (BPAQ) is a measure of aggression in adults. It consists of 29 items, subdivided into four factors: Physical aggression (9 items), verbal aggression (5 items), anger (8 items), and hostility (8 items) [27]. The BPAQ sub-scales include different numbers of questions, therefore each scale shows a different value range. However, for each range, a higher score means a greater intensity of a given type of aggressive tendency. There are no norms that allow one to determine the exact score that would mark “great intensity”. Nevertheless, for each subscale, it is possible to calculate the mean score for a question and interpret it according to the Key as per individual question—where (having reversed the score in respective questions) 1 would indicate “definitely not”, 2 “rather not”, 3 “difficult to say”, 4 “rather yes”, and 5 “definitely yes”. Cronbach’s alpha for the BPAQ is 0.89, for physical aggression is 0.85, for verbal aggression is 0.72, for anger is −0.83, and for hostility is −0.77.
- Athens Insomnia Scale (AIS) includes 8 questions and is a common and easily interpretable screening tool used to measure insomnia, with a total score ranging from 0 to 24 points. The first five items relate to sleep-related symptoms and correspond to criterion A of the ICD-10 diagnosis of inorganic insomnia. If a given symptom occurred at least three times a week during a one-month period, it is to be marked –, which is consistent with the duration and frequency of symptoms required for the ICD-10 diagnosis of insomnia (criterion B). The remaining three items refer to daytime functioning (mood, physical and mental performance, sleepiness) and correspond to criterion C of the ICD-10 diagnosis of insomnia, which includes complaints about insomnia consequences experienced during the day. Cronbach’s alpha for the AIS is 0.90 [38].
- The Pittsburgh Sleep Quality Index (PSQI) is a self-rated questionnaire used for the assessment of the quality of sleep and sleep disturbances over a 1-month time interval. Nineteen individual items generate seven “component” scores, namely, subjective sleep quality, sleep latency, sleep duration, habitual sleep efficiency, sleep disturbances, use of sleeping medication, and daytime dysfunction. The sum of scores for the seven components yields one global score. The PSQI has a sensitivity of 89.6% and specificity of 86.5% for identifying cases with a sleep disorder, using a cut-off score of 5. Cronbach’s alpha for the PSQI is 0.83 [39].
- Self-administered questionnaire—includes questions about sociodemographic data (age, marital status, parental status, place of residence, and education), employment (ward, employment), history of exposure to COVID-19, and additional information required in relation to COVID-19 collected using the authors’ questionnaire.
2.3. Statistical Analysis
3. Results
3.1. Characteristics of the Respondents
3.2. Analysis of the Severity of Insomnia and Aggression among Healthcare Workers during the SARS-CoV-2 Pandemic
3.3. Analysis of the Relationship between Sociodemographic Variables (Age, Education, Place of Residence, Marital Status) and Sleep Disorder and Aggression among Healthcare Workers during the SARS-CoV-2 Pandemic
3.4. Analysis of the Relationship between Work-Related Variables (Work Experience, Contact with a Patient Diagnosed with COVID-19) on Sleep Disorder and Aggression among Healthcare Workers during the SARS-CoV-2 Pandemic
3.5. Analysis of the Correlation between Aggression and Sleep Disorder among Healthcare Workers during the SARS-CoV-2 Pandemic
4. Discussion
4.1. Analysis of the Severity of Insomnia and Aggression among Healthcare Workers during the SARS-CoV-2 Pandemic
4.2. Analysis of the Relationship between Sociodemographic Variables (Age, Education, Place of Residence, Marital Status) on Sleep Disorder and Aggression among Healthcare Workers during the SARS-CoV-2 Pandemic
4.3. Analysis of the Relationship between Medical Variables on Sleep Disorder and Aggression among Healthcare Workers during the SARS-CoV-2 Pandemic
5. Implications
- It is necessary to establish and implement screening programs and preventive measures concerning sleep disorders to help healthcare workers identify and overcome sleep disturbances. They must be encouraged to apply evidence-based strategies, e.g., cognitive-behavioral therapy, meditation, sports, and healthcare interventions. Moreover, medical personnel should be trained in identifying and treating sleep problems in various populations.
- Studies should be conducted with the aim of determining the extent of insomnia by its severity; it is necessary to conduct longitudinal studies to determine whether insomnia is short-term or long-term.
- To ensure the wellbeing of healthcare workers and quality of care during a pandemic, it is vital to provide targeted preventive measures and psychological support to the group. Additionally, effective programs for fighting aggression may have a positive effect on the sleep of healthcare workers.
- Good-quality sleep is of fundamental importance to safety in the workplace and the health of healthcare workers. By means of assessing sleep quality during times of crisis, medical personnel can identify possible means of promoting health and safety through education on sleep hygiene, monitoring sleepiness or fatigue, and the assessment of the possibility of changing organizational policy.
- The COVID-19 pandemic has had a drastic effect on the functioning of healthcare in Poland. The physical and emotional load on healthcare workers is substantial and constitutes an additional risk to providing patient care and the productivity of a hospital. It is necessary to conduct further research on the relationship between workplace violence in medical facilities and pandemic-related factors. Aggression from patients is indeed an obstacle to ensuring the best practices and providing efficient care. It is a challenge that may delay treatment and allocation and inhibit the best possible result of hospital treatment. Therefore, it is vital to implement more safety precautions, reduce workplace violence, improve communication and problem-solving methods with respect to patient care, and introduce training courses with respect to the means of coping with aggression.
6. Limitation
- The study was conducted in one medical facility in Szczecin during the second wave of the pandemic, therefore the possibility of generalization of the obtained results may be limited.
- The data were collected with self-report questionnaires and not with clinical interviews.
- Objective sleep measurement data were not collected to confirm the subjective reports of sleep.
- One of the disadvantages of adopting a convenient sample was the small sample size. A larger study group would provide greater statistical power.
7. Conclusions
- A considerable proportion of HCWs have experienced sleep disturbances during the outbreak, stressing the need to establish ways to reduce long-term adverse outcomes associated with chronic insomnia and mental health problems and adjust interventions under pandemic conditions.
- Our study demonstrates a significant association between sociodemographic variables (age, gender, and marital and parental status) and work-related variables (work time and work experience, working with COVID-19 patients) and the prevalence of insomnia or aggression among healthcare workers during the COVID-19 outbreak.
- Insomnia and sleep disturbance were found to be connected to aggression. It transpires that sleep plays a significant role in aggressive behavior. Further studies are necessary to demonstrate the relationship between sleep disturbance and aggression, and to investigate the moderating and intervening variables that would explain when and in what way aggression affects sleep. Since nurses are subject to different types of aggression and experience sleep disturbance, it is vital to implement appropriate interventions to protect the mental health of nurses, not only during the pandemic, characterized by an increase in aggressive behavior and sleep disturbance but also on a regular basis. Positive attitudes towards work and well-rested personnel may provide better patient care and superior quality of service.
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
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Severity Category | |||
---|---|---|---|
Variables (Points) | n | % | |
AIS | No insomnia disorder | 50 | 18.94 |
Yes > 8 points | 214 | 81.06 | |
PSQI | Good sleep quality | 58 | 21.97 |
Poor sleep quality | 206 | 78.03 |
BPAQ | M | SD | Average per Question | Me | Min–Max | Q1–Q3 |
---|---|---|---|---|---|---|
Total aggression | 70.18 | 17.14 | 2.42 | 71 | 38–117 | 57–84 |
physical aggression | 18.96 | 6.13 | 2.11 | 18 | 9–37 | 13–25 |
verbal aggression | 13.77 | 3.62 | 2.75 | 14 | 5–24 | 11–16 |
Anger | 18.78 | 5.87 | 2.68 | 20 | 7–32 | 14–24 |
Hostility | 18.67 | 6.11 | 2.33 | 19 | 8–39 | 13–24 |
Variables (Points) | Age | ||
---|---|---|---|
r | p | ||
AIS | 0.022 | 0.725 | |
PSQI | 0.01 | 0.873 | |
BPAQ | Total aggression | −0.133 | 0.031 |
physical aggression | −0.085 | 0.169 | |
verbal aggression | −0.138 | 0.025 | |
Anger | −0.151 | 0.014 | |
Hostility | −0.089 | 0.149 |
Variables | AIS | PSQI | |||
---|---|---|---|---|---|
M | SD | M | SD | ||
Gender ^ | Women (n = 218) | 9.67 | 4.28 | 8.42 | 3.2 |
Men (n = 46) | 9.15 | 3.43 | 7.89 | 3.17 | |
p | 0.366 | 0.468 | |||
Marital status | Single—A (n = 74) | 8.62 | 3.76 | 7.84 | 2.99 |
Formal relationship—B (n = 145) | 10.1 | 4.13 | 8.62 | 3.24 | |
Informal relationship—C (n = 45) | 9.49 | 4.54 | 8.29 | 3.3 | |
p * | 0.043 B > A | 0.133 | |||
Parental status | Childless—A (n = 73) | 8.27 | 3.65 | 7.69 | 2.78 |
with underage children—B (n = 82) | 9.89 | 3.4 | 8.16 | 2.83 | |
with adult children—C (n = 109) | 10.23 | 4.75 | 8.74 | 3.65 | |
p | 0.004 C,B > A | 0.35 | |||
Education | secondary medical—A (n = 83) | 9.19 | 4.69 | 8.29 | 3.53 |
Higher education (Bachelor)—B (n = 116) | 10.28 | 3.62 | 9.04 | 2.8 | |
Higher education (Master)—C (n = 65) | 8.83 | 4.12 | 7.17 | 3.1 | |
p * | 0.038 B > A,C | 0.002 B > A,C |
Variables | Total Aggression | Physical Aggression | Verbal Aggression | Anger | Hostility | ||||||
---|---|---|---|---|---|---|---|---|---|---|---|
M | SD | M | SD | M | SD | M | SD | M | SD | ||
Gender ^ | Women (n = 218) | 70.65 | 17.55 | 18.54 | 6.23 | 13.73 | 3.69 | 19.2 | 5.59 | 19.18 | 6.13 |
Men (n = 46) | 67.93 | 15.02 | 20.98 | 5.28 | 13.96 | 3.31 | 16.8 | 6.81 | 16.24 | 5.47 | |
p | 0.351 | 0.017 | 0.431 | 0.032 | 0.002 | ||||||
Marital status * | Single—A (n = 74) | 67.08 | 18.52 | 17.66 | 6.38 | 13.58 | 3.9 | 17.81 | 6.02 | 18.03 | 6.24 |
Formal relationship—B (n = 145) | 72.19 | 16.34 | 19.71 | 6.08 | 13.73 | 3.45 | 19.63 | 5.58 | 19.12 | 5.95 | |
Informal relationship—C (n = 45) | 68.8 | 16.78 | 18.67 | 5.6 | 14.22 | 3.72 | 17.64 | 6.25 | 18.27 | 6.42 | |
p * | 0.059 | 0.032 B > A | 0.433 | 0.063 | 0.559 | ||||||
Parental status | Childless—A (n = 73) | 69.85 | 19.07 | 17.51 | 6.44 | 14.03 | 4.14 | 19.16 | 6.13 | 19.15 | 7.2 |
with underage children—B (n = 82) | 69.94 | 16.15 | 20.34 | 5.63 | 13.52 | 3.14 | 18.61 | 5.88 | 17.46 | 5.43 | |
with adult children—C (n = 109) | 70.58 | 16.63 | 18.89 | 6.1 | 13.79 | 3.61 | 18.65 | 5.73 | 19.25 | 5.71 | |
p | 0.77 | 0.007 B > A | 0.802 | 0.899 | 0.08 | ||||||
Education * | secondary medical—A (n = 83) | 63.4 | 18.22 | 17.55 | 6.48 | 12.47 | 3.56 | 16.67 | 5.73 | 16.43 | 6.46 |
Higher education (Bachelor)—B (n = 116) | 78.13 | 14.03 | 21.12 | 5.97 | 14.66 | 3.32 | 21.7 | 4.71 | 20.65 | 5.25 | |
Higher education (Master)—C (n = 65) | 64.65 | 14.93 | 16.89 | 4.64 | 13.51 | 3.86 | 16.26 | 5.67 | 17.98 | 6.03 | |
p * | <0.001 B > C,A | <0.001 B > A,C | <0.001 B > C,A | <0.001 B > A,C | <0.001 B > C,A |
Variables (Points) | Work Experience | Work Time | |||
---|---|---|---|---|---|
r | p | r | p | ||
AIS | 0.045 | 0.469 | 0.124 | 0.044 | |
PSQI | 0.011 | 0.856 | −0.027 | 0.667 | |
BPAQ | Total aggression | −0.138 | 0.025 | 0.068 | 0.272 |
physical aggression | 0.08 | 0.195 | 0.168 | 0.006 | |
verbal aggression | 0.139 | 0.023 | −0.132 | 0.032 | |
Anger | −0.165 | 0.007 | 0.121 | 0.05 | |
Hostility | −0.098 | 0.112 | −0.057 | 0.354 |
Variables | AIS | PSQI | |||
---|---|---|---|---|---|
M | SD | M | SD | ||
Place of work | Non-invasive treatment ward—A (n = 33) | 10.7 | 4.45 | 7.79 | 2.39 |
Surgical ward—B (n = 71) | 10.13 | 3.77 | 8.44 | 3.42 | |
Highly specialised ward—C (n = 124) | 9.73 | 3.88 | 8.74 | 3.05 | |
Other—D (n = 36) | 6.97 | 4.52 | 7.31 | 3.65 | |
p | 0.002 A,B,C > D | 0.056 | |||
Type of employment | Employment contract (n = 192) | 9.45 | 4.17 | 8.3 | 3.37 |
No employment contract (n = 71) | 9.93 | 4.11 | 8.49 | 2.7 | |
p | 0.23 | 0.391 |
Variables | Total Aggression | Physical Aggression | Verbal Aggression | Anger | Hostility | ||||||
---|---|---|---|---|---|---|---|---|---|---|---|
M | SD | M | SD | M | SD | M | SD | M | SD | ||
Place of work | Non-invasive treatment ward—A (n = 33) | 61.06 | 21.7 | 17.15 | 6.08 | 12.33 | 5 | 15.42 | 5.96 | 16.15 | 7.01 |
Surgical ward—B (n = 71) | 76.9 | 17.17 | 19.83 | 6.6 | 14.32 | 3.64 | 21.18 | 5.21 | 21.56 | 5.91 | |
Highly specialised ward—C (n = 124) | 70.12 | 15.17 | 19.07 | 5.84 | 13.93 | 3.11 | 18.95 | 5.72 | 18.17 | 5.47 | |
Other—D (n = 36) | 65.47 | 13.6 | 18.5 | 6 | 13.47 | 3.52 | 16.53 | 5.48 | 16.97 | 5.84 | |
p | <0.001 * B > C,D,A C > A | 0.16 | 0.037 B,C > A | <0.001 B > C > D,A | <0.001 B > C,D,A | ||||||
Type of employment^ | Employment contract (n = 192) | 69.4 | 17.23 | 18.75 | 6.22 | 13.81 | 3.68 | 18.35 | 5.71 | 18.48 | 6.17 |
No employment contract (n = 71) | 72.11 | 16.9 | 19.41 | 5.86 | 13.63 | 3.49 | 19.87 | 6.23 | 19.2 | 5.99 | |
p | 0.309 | 0.255 | 0.783 | 0.043 | 0.758 |
Variables (Points) | AIS | PSQI | |||
---|---|---|---|---|---|
r | p | r | p | ||
BPAQ | Total aggression | 0.329 | <0.001 | 0.306 | <0.001 |
physical aggression | 0.272 | <0.001 | 0.214 | <0.001 | |
verbal aggression | 0.176 | 0.004 | 0.265 | <0.001 | |
Anger | 0.308 | <0.001 | 0.295 | <0.001 | |
Hostility | 0.239 | <0.001 | 0.219 | <0.001 |
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Cybulska, A.M.; Weymann, A.; Rachubińska, K.; Grochans, S.; Wójcik, G.; Grochans, E. Factors Associated with Insomnia and Aggression among Healthcare Workers during COVID-19 Pandemic. Int. J. Environ. Res. Public Health 2023, 20, 1433. https://doi.org/10.3390/ijerph20021433
Cybulska AM, Weymann A, Rachubińska K, Grochans S, Wójcik G, Grochans E. Factors Associated with Insomnia and Aggression among Healthcare Workers during COVID-19 Pandemic. International Journal of Environmental Research and Public Health. 2023; 20(2):1433. https://doi.org/10.3390/ijerph20021433
Chicago/Turabian StyleCybulska, Anna Maria, Agnieszka Weymann, Kamila Rachubińska, Szymon Grochans, Grzegorz Wójcik, and Elżbieta Grochans. 2023. "Factors Associated with Insomnia and Aggression among Healthcare Workers during COVID-19 Pandemic" International Journal of Environmental Research and Public Health 20, no. 2: 1433. https://doi.org/10.3390/ijerph20021433
APA StyleCybulska, A. M., Weymann, A., Rachubińska, K., Grochans, S., Wójcik, G., & Grochans, E. (2023). Factors Associated with Insomnia and Aggression among Healthcare Workers during COVID-19 Pandemic. International Journal of Environmental Research and Public Health, 20(2), 1433. https://doi.org/10.3390/ijerph20021433