The relationship between sleep quality and fear of COVID-19,anxiety,personality traits in working women

Abstract

BACKGROUND:

Disasters such as the COVID-19 pandemic have serious traumatic effects on people, who may experience sleep problems, anxiety, and fear in the face of such a stressor.

OBJECTIVE:

This study is conducted to examine the relationship between sleep quality and fear of COVID-19, anxiety, and personality traits in working women.

METHOD:

This research was a descriptive study between June to August 2021. The study was conducted with 425 participants. The Pittsburgh Sleep Quality Index, COVID-19 Fear Scale, Beck Anxiety Scale, and the revised Eysenck Personality Questionnaire-Short Form were applied to the participants. T-test, ANOVA, and Pearson correlation analysis, were used.

RESULTS:

In the study, it was found that the total average score of the Fear of COVID-19 Scale was 18.83±5.5, while the score of sleep quality was 5.40±3.3 and the anxiety score was 14.01±12.4. On the other hand, the score of Extraversion was determined as 3.73±1.7, Neuroticism was 3.79±1.8, and Psychoticism was 1.97±1 in the study. Moreover, a statistically significant positive correlation was found between sleep quality and fear of COVID-19, anxiety, and neuroticism in working women (p < 0.05).

CONCLUSION:

Sleep quality, sleep latency, sleep disturbance; daytime dysfunction, use of sleep medication, sleep duration, sleep latency with anxiety; sleep latency, sleep quality, daytime dysfunction, sleep duration were found to be linked to neuroticism, and use of sleep medication and sleep duration were found to be linked to psychoticism. It was concluded that there was a relationship between sleep quality and fear of COVID-19, anxiety, and personality traits in working women.

Keywords

Distress fear pandemic personality sleep gender

1 Introduction

The COVID-19 pandemic, which causes severe acute respiratory syndrome, has caused significant morbidity and mortality on a global scale. In the wake of the coronavirus pandemic, there has been an increase in the incidence of sleep disorders, characterized by poor sleep quantity, quality, or timing. More than 20% of patients were found to experience sleep disturbance in the short/medium term (3 to <6 months/6 to <12 months after infection) [1, 2]. The COVID-19 pandemic has created many mental health difficulties, including loneliness, fear, anxiety, stress, fatigue, and health issues. The pandemic has also led to major changes in behavior due to social distancing and changes in the work or study environment (home office). Some studies have shown that these factors negatively affect the sleep process by causing circadian rhythm disorders during the pandemic [3, 4]. Sleep is essential for optimal brain function and physical and mental well-being, maintaining overall health. Although it plays a critical role in physical and mental health, sleep disorders are generally disregarded. Sleep disorders are a widespread problem, constituting a global epidemic that threatens the health and life quality of approximately 30% of the world’s population [5]. The World Health Organization states a “global insomnia epidemic,” with nearly two-thirds of adults getting less than 8 hours of sleep per night [6, 7]. Although the importance of sleep for physical health has been known for a long time, recently, there has been increasing interest in the relationship between sleep and mental health in the academic community [8]. Previous studies have determined that poor sleep quality, one of the defining features of chronic insomnia, leads to impaired memory and cognitive functions. In particular, poor sleep quality has been associated with metabolic syndrome and cardiological problems and has been shown to seriously affect individuals’ quality of life and well-being [2 –4]. However, the relationship between sleep quality, psychological problems and personality traits still remains unclear.

Studies have shown that women are more prone to experience sleep disturbances than men [9, 10]. Poor sleep quality prevalence among women is % 47, and the possibility of insomnia in women is 1.3 to 1.8 times more than in men [9]. In addition, sleep disorders due to anxiety are more often observed in women, and the reason for that is speculated to be gender differences [10]. Psychological factors such as anxiety can also influence the quality of sleep and sleep reactivity. Sleep reactivity is the difference in people’s reactions to stressful situations. Sleep disorders are more common in people with high sleep reactivity. High sleep reactivity is associated with cognitive and emotional overstimulation and stress, and can even lead to the development of depression and anxiety [11]. It is known that high levels of chronic stress can accelerate sleep-related disorders [12]. Sleep quality can differ depending on sleep environment, stress, or disease. A study conducted on healthy participants shows that these individuals’ sleep quality changed very little in two years and keeps a decisive correlation in one year [13]. Considering the impact of sleep disorders on overall quality of life and health, especially during stressful times such as COVID-19, it is important to identify individuals who report sleep disorders.

Considering the high frequency of sleep disorders and their negative effects on the individual, an increasing number of researches are being conducted to understand the predisposing factors that can be related to sleep and sleep disorders. Personality traits have been associated with personal sleep quality. It has been shown that positive personality traits lead to a better capacity for emotional regulation [14]. Especially neuroticism is thought to be related to falling asleep in the daytime and nighttime insomnia. Studies have shown that women show higher levels of neuroticism than men [15, 16]. In addition to this, low personality trait was discovered to be related in general to sleep quality and aggressiveness [16, 17]. In this vein, although the reasons for this relationship are unclear, personality traits can predict information about people’s sleep process. Although there is evidence indicating a correlation between personality and sleep traits the results can still be controversial [18, 19].

Sleep problems can lead to decreased health-related quality of life, decreased workplace productivity, and increased health-related problems. Epidemiological studies have shown that sleep disorders are quite common in the working population worldwide [20, 21]. Not getting enough rest due to long working hours can lead to sleep disorders that can affect personal health. It has been determined that sleep problems due to shift work, especially in women, increase the risk of depression and suicidal tendencies [22]. In particular, anxiety and fear related to COVID-19 poses a risk for sleep disorders, and changes in the work or working environment during this process may lead to major changes in behavior and contribute to sleep disorders.

Fear is a vital reaction that occurs as a stimulus as a result of an event perceived as a threat. Fears about COVID-19 are fears about contagion and risks. In particular, this fear is a critical factor in understanding individuals’ reaction to a threat to health. Because when this fear is disproportionate, it can become harmful to health [23, 24]. The emergence of any infectious disease often triggers fear, anxiety and some other symptoms of mental illness [25]. Research suggests that fear of contracting COVID-19, stress, anxiety symptoms have a higher prevalence rate [26, 27]. A high rate of fear of COVID-19 was detected among individuals in Turkey [28]. It is possible that individuals with COVID-related fear and anxiety cannot manage these distressing emotions and therefore experience sleep disorders. Therefore, examining COVID-19 fear and anxiety will contribute to the emerging literature on how the COVID-19 pandemic affects sleep quality in a global context.

Although the existing literature contributes to the understanding of the COVID 19 process and the relationships between sleep disorders, personality and sleep disorders, there is no study examining the effects of these variables on the sleep process concurrently in working women. It is not clear which personality traits support sleep disorders in women and the contribution of anxiety and fear of infection to COVID-19 to sleep disorders, especially during periods of intense stress such as COVID-19. The aim of the study was to investigate sleep disorders in women during COVID-19 and the relationship between sleep disorders and personality traits, anxiety, and fear of COVID-19.

2 Method

2.1 Study design and setting

This research was effectuated as a descriptive study between June to August 2021 to evaluate the correlation between sleep quality, fear of COVID-19, anxiety, and personality traits in female participants. Nurses working full time during the day (8 hours between 08:00–16:00) were included in the study. Nurse shifts working in hospitals in Turkey are often classified according to the time of day as follows: Day shift (8 hours between 08:00–16:00); Evening shift (12 hours between 16:00-08). Those who worked the evening shift were excluded from the study. The study was conducted with 425 participants. A post hoc power analysis was performed with the G-Power Data Analysis program based on the present study’s data. In the power analysis using independent samples t-test at 95% confidence interval and p < 0.05 significance level, the sample size was calculated as 425 participants. The effect size of the study was moderate (0.5), its power was determined as 0.96, and it was concluded that the sample was a good representative of the population [29].

2.2 Measures

Data were collected through the Personal Questionnaire Form, Fear of COVID-19 Scale, Pittsburgh Sleep Quality Index, Beck Anxiety Inventory, and Short-Form Revised Eysenck Personality Questionnaire.

2.2.1 Personal information form

This form consisted of 10 questions about sociodemographic traits such as age, gender, and educational status.

2.2.2 Fear of COVID-19 scale

This scale was developed by Satıcı et al. [30] to determine the fears of participants due to COVID-19. The scale consisted of four Likert types, 7 items, and one dimension. There was no reverse item in the scale. The total score that was obtained from the scale reflected the level of fear of the coronavirus (COVID-19) experienced by the individual. The scores that could be obtained from the scale ranged from 7 to 35. A high score meant having a high level of fear of the coronavirus. While Cronbach’s Alpha internal consistency coefficient of the scale was 0.90 [18], that value in this study had been found as 0.93.

2.2.3 Pittsburgh Sleep Quality Index (PSQI)

The Pittsburgh Sleep Quality Index was developed by Buysse et al. [31]. The validity and reliability of the scale in Turkey were conducted by Ağargün et al. [32]. PSQI contains 24 questions in total, 19 of which are self-report questions. The remaining 5 questions are answered by the person’s roommate or spouse (if available). The answer is not included in the score when calculating it. The 19th item was questioned whether the participant had any roommates or spouses. It cannot be included in the score when calculating the answer. Both total score and component scores are calculated based on the first 18 questions. That index gave information about 7 components including sleep quality (component 1), sleep latency (component 2), sleep duration (component 3), sleep efficiency (component 4), sleep disturbance (component 5), use of sleep medication (component 6) and daytime dysfunction (component 7). Each one receives points from 0 to 3. The sum of these 7 component scores shows the PSQI score. The total PSQI score varied between 0–21. While the sleep quality of participants with a total score of 5 or less is considered “good”, the sleep quality of individuals with a score of 5 or above is considered “bad”. As the scale score increases, sleep quality worsens. While Cronbach’s alpha reliability coefficient of the scale was 0.81 [32]. That value in this study had been found as 0.80.

2.2.4 Beck Anxiety Inventory (BAI)

The scale was developed by Beck et al. [33] and its Turkish adaptation was done by Ulusoy et al. [34]. The BAI evaluates the frequency of anxiety symptoms experienced by a person. The Scale contained 21 items and 13 items of them evaluated subjective anxiety and the last 8 items evaluated somatic symptoms. Answers were scored between 0 and 3, and the total score that could be obtained was 63. The high score obtained from the scale indicated the severity of the anxiety experienced by the individual. The scale is rated as follows: Low anxiety is evaluated as 8–15 points, moderate anxiety is evaluated as 16–25 points, and severe anxiety is evaluated as 26–63 points. While Cronbach’s alpha internal consistency coefficient of the scale was 0.93, that value in this study had been found as 0.90.

2.2.5 Short-Form Revised Eysenck Personality Questionnaire (EPQ-S)

The EPQ-S was prepared by Francis et al. [35] after reviewing the Eysenck Personality Questionnaire (EPQ) and its short form (48 items). The Turkish validity and reliability study of the EPQ-S was conducted by Karancı et al. in 2007 [36]. The questionnaire had 24 items evaluating personality traits under three main categories: extraversion, neuroticism, and psychoticism. In addition, a “lying” subscale aimed to prevent bias during the implementation of the questionnaire and to monitor its validity. Each category in the scale is evaluated using six items; Participants are asked to answer “yes” or “no” to 24 questions. The score for each personality trait ranged between 0 and 6. The Cronbach’s alpha values of the scale were found to be 0.65, 0.78, 0.42, and 0.64 for the neuroticism, extraversion, psychoticism, and lying subscales, respectively [36]. In the present study, Cronbach’s alpha values of the scale were found as 0.71, 0.76, 0.44, and 0.63 for the neuroticism, extraversion, psychoticism, and lying subscales, respectively.

2.3 Data collection

Data collection tools were reached to the users who were members of various forums or social media groups on the Internet, with the support of professional survey companies. There was an informed consent form that described the data collection tool and explained the aim and scope of the research in the link sent to the participants. Participants who had agreed to participate in the study continued the study by clicking the “I agree to participate in the study” button before filling out the questionnaires. So, consent had been obtained in the digital environment. Participants who had accepted the questionnaire had answered the data collection tools online the questionnaire was applied by taking the necessary precautions so as not to allow more than one answer.

2.4 Statistical analysis

SPSS (IBM SPSS Statistics version 22.0; SPSS Inc., Chicago, IL) was used for statistical analysis. The categorical variables were presented as numbers and percentages, whereas the continuous variables were given as arithmetic mean and standard deviation. The Kolmogorov–Smirnov test was used to determine the normal distribution of data. T- and F-tests, Pearson correlation analyses and Multiple Regression Analysis were used to determine the relationship between the independent and dependent variables. The reliability coefficients (Cronbach’s alpha) of the scales were determined by reliability analysis. The results were evaluated at a 95% confidence interval. Statistical significance was defined as a p-value of 0.05 for all analyses.

3 Results

3.1 Sociodemographic and some characteristics of the participants

The sociodemographic characteristics of the participants are shown in Table 1.

Table 1
Sociodemographic and some characteristics of the participants (n = 425)

Variables Mean±SD Min-max

Age 21.3±1.9 20–29

n %

Education level

Primary education (primary-middle-high school) 89 20.9

University and above 336 79.1

Mother’s education level

Primary-middle school 332 78.1

High school 63 14.8

University and above 30 7.1

Father’s education level

Primary-middle school 289 68.0

High school 95 22.4

University and above 41 9.6

Marital status

Unmarried/Single 411 96.7

Married 14 3.3

Having children

Yes 7 1.6

No 418 98.4

PSQI

Poor sleep quality 242 56.9

Good sleep quality 183 43.1

BAI

Minimal anxiety 154 36.2

Mild anxiety 124 29.2

Moderate anxiety 67 15.8

Severe anxiety 80 18.8

TOTAL 425 100

Variables	Mean±SD	Min-max
Age	21.3±1.9	20–29
	n	%
Education level
Primary education (primary-middle-high school)	89	20.9
University and above	336	79.1
Mother’s education level
Primary-middle school	332	78.1
High school	63	14.8
University and above	30	7.1
Father’s education level
Primary-middle school	289	68.0
High school	95	22.4
University and above	41	9.6
Marital status
Unmarried/Single	411	96.7
Married	14	3.3
Having children
Yes	7	1.6
No	418	98.4
PSQI
Poor sleep quality	242	56.9
Good sleep quality	183	43.1
BAI
Minimal anxiety	154	36.2
Mild anxiety	124	29.2
Moderate anxiety	67	15.8
Severe anxiety	80	18.8
TOTAL	425	100

PSQI: Pittsburgh Sleep Quality Index; BAI: Beck Anxiety Inventory.

3.2 Distribution of Fear of COVID-19 Scale, PSQI and BAI scales by sociodemographic traits of working women

According to the education level of the women it was found statistically significant difference in PSQI scores (p < 0.05). No statistically significant difference was determined in the fear of COVID-19, sleep quality and anxiety scores in terms of the participant’s mother’s education level, father’s education level, marital status, and having children (p > 0.05) (Table 2).

Table 2
Distribution of Fear of COVID-19 Scale, PSQI and BAI scales by sociodemographic traits of women (n = 425)

Variables Fear of COVID-19 Scale PSQI BAI

Poor sleep Good sleep Minimal Mild Moderate Severe

quality quality anxiety anxiety anxiety anxiety

Mean±SD Test n % n % Test n % n % n % n % Test

Education level

Primary education (primary-middle-high school) 18.9±5.9 t = 0.334 p = 0.738 34 14.0 55 30.1 x² = 16.12 p = 0.000^* 34 22.1 27 21.8 10 14.9 18 22.5 x² = 1.75 p = 0.625

University and above 18.7±5.4 208 86.0 128 69.9 120 77.9 97 78.2 57 85.1 62 77.5

Mother’s education level

Primary-middle school 18.7±5.6 F = 0.141 p = 0.868 192 79.3 140 76.5 x² = 1.19 p = 0.551 127 82.5 94 75.8 49 73.1 62 77.5 x² = 3.70 p = 0.717

High school 19.1±5.3 32 13.2 31 16.9 17 11.0 20 16.1 13 19.4 13 16.3

University and above 18.4±5.6 18 7.4 14 6.6 10 6.5 10 8.1 5 7.5 5 6.3

Father’s education level

Primary-middle school 18.7±5.6 F = 2.778 p = 0.063 166 68.6 123 67.2 x² = 0.712 p = 0.700 104 67.5 85 68.5 45 67.2 55 68.8 x² = 6.52 p = 0.367

High school 19.5±5.4 51 21.1 44 24.0 39 25.3 26 21.0 11 16.4 19 23.8

University and above 17.1±4.9 25 10.3 16 8.8 11 7.1 13 10.5 11 16.4 6 7.5

Marital status

Unmarried/Single 18.7±5.6 t = –1.319 p = 0.188 236 97.5 175 95.6 x² = 1.171 p = 0.279 150 97.4 119 96.0 64 95.5 78 97.5 x² = 2.05 p = 0.561

Married 20.71±4.9 6 2.5 8 4.4 4 2.6 5 4.0 3 4.5 2 2.5

Having children

Yes 19.8±5.8 t = 0.514 p = 0.607 3 1.2 4 2.2 x² = 0.576 p = 0.448 2 1.3 1 0.8 3 4.5 1 1.3 x² = 4.04 p = 0.256

No 18.7±5.8 239 98.8 179 97.8 152 98.7 123 99.2 64 95.5 79 98.8

Variables	Fear of COVID-19 Scale	PSQI	BAI
Education level
Primary education (primary-middle-high school)	18.9±5.9	t = 0.334 p = 0.738	34	14.0	55	30.1	x² = 16.12 p = 0.000^*	34	22.1	27	21.8	10	14.9	18	22.5	x² = 1.75 p = 0.625
University and above	18.7±5.4		208	86.0	128	69.9		120	77.9	97	78.2	57	85.1	62	77.5
Mother’s education level
Primary-middle school	18.7±5.6	F = 0.141 p = 0.868	192	79.3	140	76.5	x² = 1.19 p = 0.551	127	82.5	94	75.8	49	73.1	62	77.5	x² = 3.70 p = 0.717
High school	19.1±5.3		32	13.2	31	16.9		17	11.0	20	16.1	13	19.4	13	16.3
University and above	18.4±5.6		18	7.4	14	6.6		10	6.5	10	8.1	5	7.5	5	6.3
Father’s education level
Primary-middle school	18.7±5.6	F = 2.778 p = 0.063	166	68.6	123	67.2	x² = 0.712 p = 0.700	104	67.5	85	68.5	45	67.2	55	68.8	x² = 6.52 p = 0.367
High school	19.5±5.4		51	21.1	44	24.0		39	25.3	26	21.0	11	16.4	19	23.8
University and above	17.1±4.9		25	10.3	16	8.8		11	7.1	13	10.5	11	16.4	6	7.5
Marital status
Unmarried/Single	18.7±5.6	t = –1.319 p = 0.188	236	97.5	175	95.6	x² = 1.171 p = 0.279	150	97.4	119	96.0	64	95.5	78	97.5	x² = 2.05 p = 0.561
Married	20.71±4.9	6	2.5	8	4.4	4	2.6	5	4.0	3	4.5	2	2.5
Having children
Yes	19.8±5.8	t = 0.514 p = 0.607	3	1.2	4	2.2	x² = 0.576 p = 0.448	2	1.3	1	0.8	3	4.5	1	1.3	x² = 4.04 p = 0.256
No	18.7±5.8	239	98.8	179	97.8	152	98.7	123	99.2	64	95.5	79	98.8

PSQI: Pittsburgh Sleep Quality Index; BAI: Beck Anxiety Inventory, ^*p < 0.05 t = t test F = ANOVA test.

3.3 Distribution of scores for Fear of COVID-19 Scale, PSQI, BAI, and EPQ-S subscales

In the study, the total average scores of the PSQI (5.48±3.3, min:0-max:19); sleep quality (1.26±0.8, min:0-max:19); sleep latency (1.36±0.9, min:0-max:3); sleep duration (0.37±0.8, min:0-max:3); sleep efficiency (0.49±0.9, min:0-max:3); sleep disturbance (0.78±0.4, min:0-max:3); use of sleep medication (0.21±0.6, min:0-max:3); daytime dysfunction (1.00±0.9, min:0-max:3); Fear of COVID-19 Scale (18.77±5.6, min:7-max:35); BAI (14.01±12.4, min:0-max:63); Extraversion (3.73±1.7, min:0-max:6), Neuroticism (3.79±1.8, min:0-max:6), and Psychoticism (1.97±1.2, min:0-max:6) were found respectively (Table 3).

Table 3
Distribution of Scores for PSQI, Fear of COVID-19 Scale, BAI, and EPQ-S subscales mean scores (n = 425)

Scales Mean±SD Min-Max

PSQI 5.48±3.3 0-19

PSQI subscales

Sleep quality 1.26±0.82 0-3

Sleep latency 1.36±0.90 0-3

Sleep duration 0.37±0.80 0-3

Sleep efficiency 0.49±0.91 0-3

Sleep disturbance 0.78±0.41 0-3

Use of sleep medication 0.21±0.62 0-3

Daytime dysfunction 1.00±0.92 0-3

Fear of COVID-19 Scale 18.77±5.6 7-35

BAI 14.01±12.4 0-63

EPQ-S Extraversion 3.73±1.7 0-6

EPQ-S Neuroticism 3.79±1.8 0-6

EPQ-S Psychoticism 1.97±1.2 0-6

Scales	Mean±SD	Min-Max
PSQI	5.48±3.3	0-19
PSQI subscales
Sleep quality	1.26±0.82	0-3
Sleep latency	1.36±0.90	0-3
Sleep duration	0.37±0.80	0-3
Sleep efficiency	0.49±0.91	0-3
Sleep disturbance	0.78±0.41	0-3
Use of sleep medication	0.21±0.62	0-3
Daytime dysfunction	1.00±0.92	0-3
Fear of COVID-19 Scale	18.77±5.6	7-35
BAI	14.01±12.4	0-63
EPQ-S Extraversion	3.73±1.7	0-6
EPQ-S Neuroticism	3.79±1.8	0-6
EPQ-S Psychoticism	1.97±1.2	0-6

PSQI: Pittsburgh Sleep Quality Index; BAI: Beck Anxiety Inventory; EPQ-S: Short-Form Revised Eysenck Personality Questionnaire.

3.4 Correlation between mean scores of COVID-19 Fear Scale, PSQI, BAI and EPQ-S subscales

A positive, weak and statistically significant relationship was found between PSQI scale scores and Fear of COVID-19 Scale scores (p < 0.05). Increased PSQI scores mean that sleep quality worsens. As the level of fear of COVID 19 increases, sleep quality worsens (Table 4).

Table 4
Correlation between mean scores of COVID-19 Fear Scale, PSQI, BAI and EPQ-S subscales (n = 425)

Scales PSQI Fear of COVID-19 Scale BAI Extraversion Neuroticism Psychoticism

r r r r r r

PSQI –

Fear of COVID-19 Scale 0.167^ –

BAI 0.538^ 0.211^ –

Extraversion –0.030 0.076 –0.073 –

Neuroticism 0.221^ 0.127^* 0.349^** –0.114^* –

Psychoticism 0.053 –0.099^* 0.047 0.009 0.111^** –

Scales	PSQI	Fear of COVID-19 Scale	BAI	Extraversion	Neuroticism	Psychoticism
PSQI	–
Fear of COVID-19 Scale	0.167^**	–
BAI	0.538^**	0.211^**	–
Extraversion	–0.030	0.076	–0.073	–
Neuroticism	0.221^**	0.127^*	0.349^**	–0.114^*	–
Psychoticism	0.053	–0.099^*	0.047	0.009	0.111^**	–

^*p < 0.05, ^*^*p < 0.001.

A positive, weak and statistically significant relationship was found between PSQI scale scores and Neuroticism scores (p < 0.05). As the level of neuroticism increases, sleep quality worsens (Table 4).

A positive, moderate and statistically significant relationship was found between PSQI scale scores and BAI Scale scores (p < 0.05). As anxiety scores increase, sleep quality worsens (Table 4).

3.5 Multiple Regression Analysis of PSQI Mean Scores with Independent Variables

In the multiple regression model, participants’ PSQI Mean Scores were taken as the dependent variable, while age, educational level, mother’s education level, father’s education level, marital status, having children, fear of COVID-19 Scale, BAI, Extraversion, Neuroticism and Psychoticism Mean Scores were taken as independent variables. As a result of multiple regression analysis, the model was found to be statistically significant (F = 18.128, p < 0.001). In the model, it was observed that 33% of the variance in the sleep quality level of the participants was explained by the independent variables (R² = 0.326). Table 5 shows the independent variables included in the model and the effect sizes of these variables. According to Table 5, the education level and anxiety level of the participants are statistically significant in the model; It was found that the variables of age, mother’s education level, father’s education level, marital status, having children, fear of COVID-19 Scale level, Extraversion, Neuroticism and Psychoticism level were not statistically significant. According to this model, when the education level increases by 1 degree, sleep quality levels increase by 1.26 units (increase in PSQI scores means that sleep quality worsens) (i.e., as the education level increases, sleep quality worsens); It is seen that as the anxiety level increases by 1 unit, sleep quality levels increase by 0.14 units (that is, as the anxiety level increases, sleep quality worsens).

Table 5
Multiple regression analysis of PSQI mean scores with independent variables (n = 425)

Independent Variables PSQI

B SH_B Beta t p

Constant –1.142 4.150 – –0.275 0.783

Age –0.121 0.076 –0.072 –1.587 0.113

Educational level 1.259 0.332 0.157 3.795 0.000^^

Mother’s education level –0.249 0.258 –0.045 –0.965 0.335

Father’s education level 0.369 0.231 0.075 1.599 0.111

Marital status 0.241 1.081 0.013 0.223 0.824

Having children 0.948 1.462 0.037 0.648 0.517

Fear of COVID-19 Scale 0.038 0.025 0.065 1.548 0.122

BAI 0.138 0.012 0.522 11.644 0.000^^

Extraversion 0.013 0.075 0.007 0.171 0.865

Neuroticism 0.072 0.081 0.039 0.883 0.378

Psychoticism 0.130 0.109 0.050 1.194 0.233

R = 0.571 R² = 0.326 F = 18.128 p = 0.000^^

Independent Variables	PSQI
Constant	–1.142	4.150	–	–0.275	0.783
Age	–0.121	0.076	–0.072	–1.587	0.113
Educational level	1.259	0.332	0.157	3.795	0.000^^
Mother’s education level	–0.249	0.258	–0.045	–0.965	0.335
Father’s education level	0.369	0.231	0.075	1.599	0.111
Marital status	0.241	1.081	0.013	0.223	0.824
Having children	0.948	1.462	0.037	0.648	0.517
Fear of COVID-19 Scale	0.038	0.025	0.065	1.548	0.122
BAI	0.138	0.012	0.522	11.644	0.000^^
Extraversion	0.013	0.075	0.007	0.171	0.865
Neuroticism	0.072	0.081	0.039	0.883	0.378
Psychoticism	0.130	0.109	0.050	1.194	0.233
	R = 0.571	R² = 0.326	F = 18.128	p = 0.000^^

^*^*p < 0.05.

4 Discussion

Four important findings were obtained in this study. First, it was found that working women’s fear of COVID-19 was slightly higher than moderate. Second, it was claimed that women had high anxiety levels. Third, neurotic personality traits were found as more dominant, and finally, a relationship between the sleep quality of working women and fear of COVID-19, anxiety level, and neurotic personality traits was found.

Quality sleep is important for the physical and mental well-being of individuals. When an individual state that s/he falls asleep in the first 30 minutes, does not wake up more than once at night, sleeps at least seven hours a day, and feels rested during the day, it means quality sleep [37]. Deterioration of sleep quality causes insufficient sleep and prolonged wakefulness, insomnia, poor sleep quality, nightmares, and fatigue. Age, gender, education, low socioeconomic status, depression, anxiety, and traumas such as COVID-19 can be considered potential risk factors for poor sleep quality and the development of sleep disorders [38]. There is an increase in both sleep and mental disorders due to increasing traumatic life events in the world [39]. Quarantine measures taken due to the pandemic had a traumatic effect on people’s mental health. Even if these measures were removed in Turkey as in the world, it was observed that the pandemic affects individuals. After the pandemic, problems in terms of physical, economic, social, and spiritual occurred in individuals. Fear of COVID-19 or sleep disorders may develop together with anxiety about viral diseases. This study, it was aimed to evaluate the relationship between sleep quality and fear of COVID-19, anxiety, and personality traits in working women.

It is stated that sleep disorders and poor sleep quality are more common in women. Sleep quality is a subjective indicator that includes how individuals feel rested when they wake up. It is claimed that women have poor sleep quality and are more vulnerable to sleep problems during the pandemic period [38, 40]. In this study, it was reported that the sleep quality of women was poor and the female gender affected sleep quality in studies in parallel with this finding [41, 42].

Mental disorders are more common in women than in men. It is stated that this situation can be related to physiological conditions such as genetic predisposition, and hormone and cortisol levels between men and women [42]. According to Özdin et al. [43], female gender was a risk factor for anxiety in a study that assesses both depression and anxiety in the Turkish population during the COVID-19 pandemic. Similarly, Pieh et al. [42] reported a female had high depression and anxiety scores. On the other hand, it was determined that the anxiety levels of women were moderate in this study. The low anxiety levels of women in our study may be related to the period of study. Furthermore, the cultural differences between the measurement tools and sample group used in other studies may be affected the anxiety level.

Fear is one of the emotions that arise concerning a real threat; it is essential for an individual’s survival. In addition, high-level fear has a more destructive effect than a functional effect. Individuals experienced high levels of fear for themselves and others with the thought of becoming infected during the pandemic [44, 45]. Studies show that women have higher fear of contamination by COVID-19 [46, 47]. Taking into consideration the studies, it was determined that the fear scores of COVID-19 were slightly higher than the moderate level for women in this study. Although the pandemic process was over, some factors such as the increasing number of cases and deaths in countries, emerging new variants, faster contamination of the virus, uncertainties about the pandemic process, and the inability to spread effective immunization may cause people to be afraid.

Fear of COVID-19 is a mental issue known as corona phobia or a fear of contamination of COVID-19 that results in physical symptoms such as palpitations, shivering, shortness of breath, dizziness, changes in appetite, and insomnia [48]. The fear that occurs during the pandemic period increases the anxiety levels of both healthy individuals and people who have mental health problems [49]. According to the literature, it is reported that anxiety harms sleep quality [39, 50]. Parallel to the literature, it is found that there is a weak positive correlation between sleep quality and fear of COVID-19 in women in our study.

The relationship between psychological disorders such as anxiety and stress and sleep quality are discussed in the studies [51, 52]. Sleep disorder is an essential public health problem that affects people of all ages. Sleep disorders can cause some negative consequences such as fatigue, sleepiness, and low neurocognitive performance [53]. Both impaired sleep behavior and sleep difficulties cause higher levels of depression, anxiety, and stress [54]. It is thought that sleep disorder is the main symptom of anxiety and depression. Follow-up studies show that sleep disturbance can be a predictor of future anxiety and depression levels, and these studies indicate that there may be an interactive relationship between emotional and sleep disorders [55]. It is reported that good sleep quality reduces depression, anxiety, and stress [56]. Studies show that there is a positive and significant relationship between poor sleep quality and anxiety [42, 57]. In parallel with the literature, it was found that there was a positive moderate level of significance between sleep quality and anxiety in our study.

Personality plays an important role in facilitating or complicating how people perceive and react to events at critical times. Personality traits can be considered important markers for understanding individual differences when people adapt to environmental factors [58]. Personality can be defined as our feelings, behaviors, and thoughts; it is an effort to cope with negative events that separate us from each other. Personality traits shape an individual’s thoughts, feelings, and behavioral actions [59]. In this study, it was determined that the personality traits of women were neurotic, then extroverted, and finally psychotic. This makes us think that the lower sleep quality of the women explains the high fear of COVID-19.

The neurotic personality characteristic can be classified by emotional instability, pessimism, irritability, and sadness. As this personality characteristic increases in individuals, COVID-19 anxiety symptoms may also increase. Therefore, the sleep quality of individuals can be affected negatively. An increase in sleep quality may cause a decrease in somatic symptoms and anxiety levels in individuals [51]. Studies have shown that personality traits are associated with sleep quality, but neurotic personality traits are inversely related to good sleep quality [60, 61]. Poor sleep quality can cause both physical and psychological problems in individuals [18]. By supporting the literature knowledge, it can be seen that there is a weak positive correlation between sleep quality and neuroticism scores in this study.

In this study, it is seen that there is a significant difference in sleep quality scores in terms of the education level of the women, and the sleep quality of the women who have high education levels is poor. This finding is supported by conducting some studies in the literature [40 , 62]. It is clear to say that the awareness of individuals and the ways of obtaining information increase when the level of education increases. It is thought that the obtained information may cause anxiety in individuals and the sleep quality of individuals is poor because of this.

There is no significant difference in the fear of COVID-19, sleep quality, and anxiety levels in terms of age, employment, marital status, the status of having children, and the number of children. While some literature information supports our findings [60, 61], some cannot [39].

4.1 Limitations

There were a few limitations in the study. The present study is cross-sectional in nature and used the simple random probability sampling method. However, one of its limitations may be selection bias as it included only volunteering participants. In other words, the participants may have intentionally given misleading answers to questions. In addition, certain negativities are possible, such as security concerns related to the electronic environment, uncertainty of respondents, problems with access to the questionnaire, misunderstanding the sensitivity of the research, incorrect e-mail addresses and problems with access to the web page. Necessary explanations about the study were made in the informed consent form, and the participants were allowed to approve this form online before answering the study questions. In this way, misunderstandings and bias regarding the study questions were tried to be prevented. Last limitation of the study, evening shift workers were excluded from the study because night working hours would cause circadian rhythm sleep disorders. In addition, the results are applicable only to the participants surveyed, which cannot be generalized to other populations.

5 Conclusion

It was concluded that there is a relationship between sleep quality, sleep latency, sleep disorder, daytime dysfunction and fear of COVID-19, anxiety and neurotic personality traits in working women. Fear of COVID-19 is an important factor contributing to a high risk of anxiety disorder, and neuroticism is an important factor contributing to anxiety. Differences were found in women’s anxiety levels according to their educational level. It has also been found that anxiety level is related to neurotic features. It is important for mental health professionals to gain awareness that personality traits and anxiety levels should be taken into account in managing women’s sleep during crisis periods such as pandemics.

Ethical approval

The study was carried out in line with the principles of the Helsinki Declaration. Before the study, approval was obtained from the Ege University scientific research ethics committee of the university (21-11.IT/12).

Informed consent

Individual consents were obtained from all individual participants included in the study.

Conflict of interest

The authors declare that they have no conflict of interest.

Footnotes

Acknowledgments

The authors thank all individuals who participated in the research.

Funding

The author(s) received no financial support for the research, authorship, and/or publication of this article.

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Independent Variables	PSQI
	B	SH_B	Beta	t	p
Constant	–1.142	4.150	–	–0.275	0.783
Age	–0.121	0.076	–0.072	–1.587	0.113
Educational level	1.259	0.332	0.157	3.795	0.000^^
Mother’s education level	–0.249	0.258	–0.045	–0.965	0.335
Father’s education level	0.369	0.231	0.075	1.599	0.111
Marital status	0.241	1.081	0.013	0.223	0.824
Having children	0.948	1.462	0.037	0.648	0.517
Fear of COVID-19 Scale	0.038	0.025	0.065	1.548	0.122
BAI	0.138	0.012	0.522	11.644	0.000^^
Extraversion	0.013	0.075	0.007	0.171	0.865
Neuroticism	0.072	0.081	0.039	0.883	0.378
Psychoticism	0.130	0.109	0.050	1.194	0.233
	R = 0.571	R² = 0.326	F = 18.128	p = 0.000^^