The role of psychological inflexibility on post-traumatic stress symptoms among COVID-19 survivors

Abstract

Background

The COVID-19 outbreak spread rapidly around the world, causing a pandemic and negatively affecting the mental health of society. During this process, one of the most mentally affected groups has been patients who contracted COVID-19. Post-traumatic stress disorder (PTSD) is reported to be an important public health problem after pandemics. In this study, we aimed to investigate the relationship between psychological inflexibility, which is thought to underlie mental problems and PTSD symptoms in Covid-19 survivors.

Methods

A total of 194 patients over 18 years old who were admitted to the Chest Diseases Outpatient Clinic with a previous COVID-19 infection and who agreed to participate were included in the study. Socio-demographic information form as well as questionnaire forms for Hospital Anxiety and Depression Scale (HADS), Acceptance and Action Questionnaire II (AAQ-II), Impact of Events Scale-Revised (IES-R) and Insomnia Severity Index (ISI) were conducted on the patients.

Results

Female gender, participants with lower education level, and those with additional chronic diseases had significantly higher IES-R values (p = 0.014, p = 0.029 and p = 0.011, respectively). IES-R scores showed a significant positive correlation with HADS-Anxiety (A) (p < 0.001), HADS-Depression (D) (p < 0.001), AAQ-II (p < 0.001) and ISI (p < 0.001) scores. AAQ-II also scores significantly associated with HADS-A scores (p = 0.0053), and similarly, the effect of HADS-A scores on IES-R scores was also significant (p = 0.0009). The mediating role of HADS-A scores in the effect of AAQ-II scores on IES-R scores was significant (β = 0.0757, 95% CI = 0.0024 to 0.1785). AAQ-II scores had a significantly associated with ISI scores (β = 0.1263, p = 0.0033). Similarly, ISI scores had a significant association with IES-R scores (β = 1.3882, p < 0.001). In this model, ISI scores significantly mediated the relationship between AAQ-II scores and IES-R scores (β = 0.1753, 95% CI = 0.0640 to 0.3060).

Conclusion

In our study, we found that female gender, low education level and additional chronic diseases were associated with PTSD symptoms in COVID-19 survivors. We also found that psychological inflexibility may be a common factor associated with PTSD, depression and anxiety symptoms and insomnia severity. Psychotherapeutic interventions to reduce psychological inflexibility, especially in patients who suffered an infection like COVID-19 during the pandemics, may prevent these patients from experiencing anxiety, depression, PTSD symptoms and sleep problems.

Introduction

The COVID-19 outbreak spread widely around the world in a short period of a few months, causing a pandemic. In many countries, countermeasures have had to be taken, including closure of workplaces and schools, curfews, social distancing rules and quarantine [1]. Primarily affecting the respiratory system, COVID-19 has caused respiratory distress in patients and even death in severe cases [2]. According to the World Health Organization (WHO) data, as of November 19, 2023, more than 772 million confirmed cases and more than six million deaths have been reported worldwide [3].

The COVID-19 pandemic has also negatively affected people’s mental health. During this process, one of the most mentally affected groups has been patients who contracted COVID-19. In a systematic review and meta-analysis of early pandemic studies, it was reported that the prevalence of anxiety, depression and sleep disorders in COVID-19 patients was higher than in the general population [4]. Post-traumatic stress disorder (PTSD) is also a major public health concern after pandemics caused by infectious diseases, including COVID-19 [5]. In a meta-analysis of 13 studies in patients who suffered COVID-19, the pooled prevalence of PTSD was estimated to be 16% [6]. Conditions such as baseline depression and anxiety symptoms, social isolation or long hospitalization period, female gender, dyspnea, life threat perception and lack of social support in patients who contracted COVID-19 during the pandemic were found to be factors associated with PTSD [7–9]. Acceptance and Commitment Therapy (ACT) is a modern process-based cognitive behavioral therapy that focuses on the basic mechanisms underlying change, as opposed to approaches that focus on traditional diagnostic categories. Based on functional contextualism as a philosophy of science, ACT addresses the functioning of human cognition through Relational Framework Theory (RFT), exhibiting a “process based” that aims to transform the function and context of these contents on the individual rather than changing the form of cognitive contents. The psychological inflexibility (PI) at the center of this model is a transdiagnostic concept defined as a pattern in which behavior is excessively controlled by the individual’s thoughts, feelings and other internal experiences, or avoided at the expense of more effective and meaningful actions [10, 11].

Instead of targeting the topographic features of specific symptoms, targeting the basic processes underlying these symptoms, that is, the sub-processes of psychological flexibility such as acceptance, cognitive decoupling, contact with the present moment and value-oriented action, allows the individual to improve his quality of life. This process-based approach allows it to be applied effectively not in a specific diagnostic group, but in a wide range of areas where psychological flexibility plays a key role, such as depression, anxiety, chronic pain, somatization, stress and sleep disorders [11–14]. PI is not an immutable and inflexible process, but rather changeable in different contexts with psychotherapeutic interventions [15].

In general, psychiatric studies on COVID-19 have been conducted on healthcare professionals and the general population, yet fewer studies have been conducted on COVID-19 survivors [16].

In the literature, there are studies conducted in other groups during the COVID-19 pandemic period, which associate PI with PTSD symptoms [17–20], mood symptoms [21] and anxiety symptoms [22]. However, these studies were carried out on different samples of the general population. To the best of our knowledge, there is no study in literature regarding the relationship between PI and PTSD symptoms, considering the mediating effects of anxiety symptoms and sleep disturbances in COVID-19 survivors. In our study, we mainly aimed to investigate the relationship between PI and PTSD symptoms in individuals who contracted COVID-19. It was also aimed to examine the role of depression, anxiety and sleep in such probable relationships.

Considering the presence of relatively high rates of PTSD symptoms and other mental problems among COVID-19 survivors even one year later [23], early recognition of these problems and identification of factors associated with these problems are important for potential interventions.

Methods

Study design and sample

A total of 210 patients over 18 years old, who were admitted to the Chest Diseases Outpatient Clinic at Alanya Alaaddin Keykubat University Faculty of Medicine, Alanya Training and Research Hospital, between August 1, 2021, and February 1, 2022, for COVID-19 infection, confirmed positive by PCR tests and who agreed to participate, were included in this study. A total of 16 patients who were on active psychiatric treatment and filled out the scales incompletely were excluded. Hence, a total of 194 patients were included in the study. Self-report scales were used in this study. Written informed consent was obtained from the participants after explaining the purpose and method of the study and how to complete the scales. The research protocol was approved by the local ethics committee (Date: 09.06.2021, Decision Num: 10 − 01). Those with clinically significant cognitive impairment and active mental disorders, and those who completed the scales incompletely were excluded. The study was conducted in accordance with the Helsinki Declaration Principles.

After obtaining informed consent from the patients who agreed to participate in the study, in addition to the sociodemographic information form, the questionnaires for Hospital Anxiety and Depression Scale (HADS) [24], Acceptance and Action Questionnaire II (AAQ-II) [10], Impact of Events Scale-Revised (IES-R) [25] and Insomnia Severity Index (ISI) [26], the validity and reliability studies of which were conducted to test the hypothesis, were completed.

Measurements

Sociodemographic and clinical characteristics form

It is an interview questionnaire designed by researchers, which includes information on age, gender, education, occupational and marital status, comorbid physical diseases (obesity, asthma, etc.) and clinical characteristics related to trauma.

Hospital Anxiety and Depression Scale (HADS)

It is a self-administered scale that screens patients for symptoms of anxiety and depression and is frequently used in hospital settings [24]. The cut-off score of the HADS depression and anxiety subscales is ≥ 8. The Turkish translation of the scale was validated by Aydemir et al. [27].

Acceptance and Action Questionnaire II (AAQ-II)

It is a seven-item Likert-type scale that measures PI [10]. The scale has been adapted into Turkish. The increase in the scores obtained from the scale indicates an increase in PI and experiential avoidance [28].

Impact of Events Scale-Revised (IES-R)

It is a scale consisting of 22 items and 3 subscales that assesses traumatic stress symptoms and severity [25]. Turkish validity and reliability study was conducted, and the internal consistency coefficient was calculated as 0.94 for the total score [29]. The maximum score that can be obtained from the scale is 88, and it was determined that people who scored 24 or higher experienced mild or more severe PTSD [30].

Insomnia Severity Index (ISI)

It was developed to assess the severity of insomnia [26]. Turkish validity and reliability study of the scale was conducted in 2010 [31]. The scale consists of seven questions, and the items are scored between 0 and 4. Scores that can be obtained from the scale vary between 0 and 28. High scores on the scale indicate deterioration in sleep quality.

Statistical analysis

Descriptive statistics of the data were calculated as mean and standard deviation for continuous data. The examination of whether the data obtained through the scales were normally distributed was performed by examining the kurtosis skewness results, Q-Q plot and histogram graphs. Values in the range ± 1 for kurtosis and skewness were interpreted as normal distribution [32]. Whether the variances were homogeneously distributed was interpreted by Levene’s test. VIF values were reviewed for multicollinearity. Pearson correlation coefficients were calculated for correlation between the data. Three separate mediation models were tested in which IES-R was the outcome variable (Y), AAQ-II was the predictor (X) and HADS-Anxiety (A), HADS-Depression (D) and ISI were the mediating variables separately. For each mediating variable, other variables (HADS-A, HADS-D and ISI) as well as age, gender, education level and presence of comorbidity were controlled. Mediation analysis was performed using SPSS PROCESS V.2.16.1. Mediation models were tested using bootstrap analysis. In these analyses, the mediation effect was considered significant if the 95% bias-corrected and accelerated confidence intervals (CIs) (lower and upper bounds) for the indirect effect (IE) based on 5000 boots trapped samples were not equal to zero [33]. P < 0.05 was considered significant. SPSS version 22 was used for all examinations and calculations.

Results

The study included 194 patients diagnosed with COVID-19 who volunteered to participate in the study after informed consent. 117 (60.3%) of the participants were female. The mean age was 45.83 (± 13.27). 84 (43.3%) of the patients had comorbidities and 29 (14.9%) were smokers. 43 (22.2%) were hospitalized due to COVID-19. 11 (5.7%) were followed up in intensive care conditions. 135 (69.6%) of the participants were vaccinated for COVID-19. The sociodemographic characteristics of the participants is shown in Table 1.

Table 1.

Comparison of IES-R results in terms of sociodemographic characteristics

							95% CI of the Difference
		N	Mean	Std. D	t	p	Lower	Upper
Gender	Female	117	29.84	18.752
	Male	77	23.56	16.196	2.480	0.014	1.282	11.276
Marital Status	Married	154	26.30	17.851
	Single/divorce/widowed	40	31.38	18.246	-1.595	0.112	-11.353	1.200
Education	Primary School	99	30.10	19.271
	High school and beyond	95	24.47	16.186	2.198	0.029	0.577	10.677
Comorbidity	Yes	84	31.07	19.188
	No	110	24.50	16.574	2.555	0.011	1.498	11.645
Previous psychiatric illness	Yes	18	32.33	22.123
	No	176	26.84	17.524	1.236	0.218	-3.277	14.273
Smoking	Yes	29	23.34	14.418
	No	165	28.05	18.510	-1.300	0.195	-11.841	2.434
Hospitalization	Yes	43	31.47	19.771
	No	151	26.17	17.359	1.709	0.089	-0.815	11.401
Bereavement	Yes	30	31.10	17.682
	No	164	26.66	18.030	1.244	0.215	-2.600	11.483
Need for intensive care follow-up	Yes	11	29	20.5–46.5
	No	183	24	13.0-37.5	-0.987	0.360	-6.00	18.00
Vaccination	Yes	135	27.12	18.202
	No	59	27.86	17.683	-0.265	0.791	-6.301	4.809

CI Confidence Interval, Independent sample t-Test

Women had statistically significantly higher mean IES-R values than men (t ₍₁₉₂₎ = 2.480, p = 0.014). Participants with lower education level and those with additional chronic diseases had significantly higher IES-R values (t ₍₁₉₂₎ = 2.198, p = 0.029 and t ₍₁₉₂₎ = 2.555, p = 0.011, respectively). IES-R values did not show a significant difference in terms of marital status (p = 0.112), past psychiatric illness (p = 0.218), smoking (p = 0.195), need for hospitalization (p = 0.089), need for intensive care follow-up (p = 0.360), bereavement (p = 0.215) and vaccination (p = 0.791) investigated in the study (Table 1).

The mean and standard deviation values of the scales used in the study are shown in Table 2. All measurements showed kurtosis and skewness values supporting normal distribution (In addition, histogram and Q-Q plot graphs were analyzed to evaluate normal distribution). IES-R scores were significantly positively associated with HADS-A (r = 0.61, p < 0.001), HADS-D (r = 0.54, p < 0.001), AAQ-II (r = 0.49, p < 0.001) and ISI (r = 0.66, p < 0.001) scores. There was no multicollinearity among the predictor variables to be tested (VIF values between 1.396 and 2.089). All scales had very good internal consistency results as determined by Cronbach’s alpha (Table 2).

Table 2.

Descriptive statistics and correlation values of the scales used in the study

N = 194	Mean ± SD (Min-Max)	HADS-D	HADS-A	AAQ-II	ISI	IES-R	Skew	Kurt	α
Age	45.83 ± 13.27(18–78)	0.17*	-0.01	0.05	0.03	0.09	-	-	-
HADS-D	7.41 ± 4.87 (0–21)	1	0.67**	0.45**	0.41**	0.54**	0.451	-0.436	0.819
HADS-A	8.20 ± 4.57 (0–19)		1	0.49**	0.48**	0.61**	0.315	-0.660	0.854
AAQ-II	19.25 ± 9.45 (7–46)		-	1	0.43**	0.49**	0.736	-0.129	0.916
ISI	9.19 ± 5.51 (0–24)		-	-	1	0.66**	0.480	-0.317	0.871
IES-R	27.35 ± 18 (0–80)		-	-	-	-	0.667	-0.188	0.939

α Cronbach’s alpha, HADS-D Hospital Anxiety and Depression Scale-Depression, HADS-A Hospital Anxiety and Depression Scale-Anxiety, AAQ-II Acceptance and Action Questionnaire II, IES- R Impact of Events Scale-Revised, ISI Insomnia Severity Index

^** P < 0.001, ^* p < 0.05

In the first model (Fig. 1A), in which AAQ-II scores were the predictor, IES-R scores were the dependent variable and HADS-A was the mediator, AAQ-II significantly associated with HADS-A (β = 0.0773, p = 0.0053), and similarly the effect of HADS-A on IES-R was also significant (β = 0.9786, p = 0.0009). The mediating role of HADS-A in the effect of AAQ-II on IES-R was significant (β = 0.0757, 95% CI = 0.0024 to 0.1785) (Table 3). Approximately 58% of the variance in IES-R was explained by the variables constituting the first model (Adj. R2 = 0.5759).

Fig. 1.

Mediation models. A Mediation Model : Effect of AAQ-II on IES-R through HADS-A. AAQ II : Acceptance and Action Questionnaire-II, HADS-A : Hospital Anxiety and Depression Scale-Anxiety, IES-R : Impact of Event Scale-Revised. C : Total effect, C': Direct effect. *p<0,05, ** p<0,01, *** p<0,001. B Mediation Model : Effect of AAQ-II on IES-R through ISI. AAQ II : Acceptance and Action Questionnaire-II, ISI : Insomnia Severity Index, IES-R : Impact of Event Scale-Revised. C: Total effect, C': Direct effect. *p < 0,05, ** p<0,01, *** p<0,001

Table 3.

Mediation analysis for IES-R outcome variable

		β	SE	P	95% CI
					LLCI	ULCI
Total Effect	AAQ-II→HADS-A →IES-R	0.2958	0.1110	0.0084	0.0769	0.5147
	AAQ-II →ISI→IES-R	0.3954	0.1225	0.0015	0.1538	0.6370
Indirect Effects	AAQ-II →HADS-A →IES-R	0.0757	0.0450	-	0.0024	0.1785
	AAQ-II →ISI→IES-R	0.1753	0.0624	-	0.0640	0.3060
Direct Effect	(AAQ-II →IES-R)	0.2201	0.1102	0.0474	0.0026	0.4376

CI Confidence interval, LLCI The lower limit confidence interval, ULCI The upper limit confidence interval, HADS-A Hospital Anxiety and Depression Scale-Anxiety, AAQ-II Acceptance and Action Questionnaire II, IES- R Impact of Events Scale-Revised, ISI Insomnia Severity Index

In the second model in which HADS-D was tested as a mediator, AAQ-II scores significantly associated with HADS-D (β = 0.068, p = 0.0298). However, HADS-D did not significantly associate with IES-R scores (β = 0.489, p = 0.0577). Therefore, the second model mediation effect was not tested. In the third model in which the mediating role of ISI scores was examined (Fig. 1B), AAQ-II scores had a significantly associated with ISI (β = 0.1263, p = 0.0033). Similarly, ISI scores had a significant association with IES-R (β = 1.3882, p < 0.001). In this model, ISI significantly mediated the relationship between AAQ-II and IES-R [β = 0.1753, 95% CI = 0.0640 to 0.3060) (Table 3). Approximately 45% of the variance in IES-R was explained by the variables comprising this model (Adj. R2 = 0.4489).

Discussion

As the most important result in our study, we found that PI is associated with PTSD symptoms in COVID-19 survivors. Our results also revealed the mediating role of anxiety and sleep problems in this effect of PI on PTSD symptoms. In the literature review, the relationship between PI and PTSD symptoms during the COVID-19 pandemic has mostly been examined in general population samples, whereas it has not been sufficiently investigated in clinical populations. Our findings are consistent with previous studies linking PI with PTSD symptoms, and high level of PI may exacerbate the emergence of PTSD symptoms [17–20, 34]. The COVID-19 pandemic has caused intense stress on patients, and high levels of PI, also during stressful life events, can prevent a person from adapting to adverse situations and worsen mental health [35]. It has also been shown during the COVID-19 pandemic that psychological flexibility, which is also considered as the opposite of PI, is protective against psychological distress [36].

In our theoretical framework individuals with higher PI may experience greater emotional dysregulation and maladaptive avoidance following COVID-19 infection [37]. This may increase anxiety symptoms [38], which in turn may be associated with higher PTSD symptoms [39]. In summary, anxiety symptoms were evaluated as a theoretically plausible indirect pathway in the association between PI and PTSD symptoms. Longitudinal and prospective studies support the view that PI is a risk factor present before the onset of the disease and a predictor of the disease course [40, 41]. Second, PI is not limited to a single diagnosis; rather, it is a common underlying process in many different disorders, such as depression, anxiety, OCD, and PTSD [37, 38, 42]. Additionally, the PI scores at the start of treatment can predict symptom levels at the end of treatment. Specifically, in patients with PTSD, severity levels have been found to be the only significant predictor of symptom levels at discharge [41]. In our study, we also found that PI was significantly associated with anxiety and depressive symptoms in patients who contracted COVID-19. Studies conducted during the COVID-19 pandemic have demonstrated correlations between PI and various psychological issues, such as depressive and anxiety symptoms across different sample sizes [22, 43–46], and results consistent with our findings were obtained. PI focuses on how individuals relate to their distress rather than the distress itself. As an indicator of PI, patients’ careful attention to their distressing feelings and thoughts related to the pandemic, or their resistance to these experiences during the respective period, may have heightened their anxiety and depressive symptoms while reducing their resilience to mental health issues [12, 37, 47]. People with high PI may struggle to manage their emotions and thoughts in a flexible and healthy manner, a challenge that becomes even more pronounced in situations like a coronavirus infection [37].

Another finding in our study was that there was a significant association between anxiety symptoms and PTSD symptoms who contracted COVID-19. Previous studies on these subjects obtained results consistent with this finding of ours. Studies conducted during the pandemic showed that anxiety symptoms in patients who suffered COVID-19 [8], fears and worries in university students under quarantine [48], and health anxiety in the general population [39] have been shown to be associated with PTSD symptoms. Infected patients with high anxiety symptoms may have been more affected by the negative factors associated with COVID-19 during the pandemic and may have been more concerned about their health, economic situation, relatives and conditions such as quarantine. This may have increased the PTSD symptoms of the patients. In conclusion, our study’s findings, along with a review of existing literature, suggest that anxiety serves as a mediator in the relationship between PI and PTSD symptoms.

In our study, we also found that PI had significant associaton with sleep problems, and sleep problems had significant association with PTSD symptoms in patients who contracted COVID-19. In our therotical framework, sleep disturbance was evaluated as a theoretically plausible indirect pathway in the association between PI and PTSD symptoms. Thus, we observed that PI indirectly affects PTSD symptoms through sleep problems. In other words, those with higher PI had more sleep problems and those with more sleep problems had higher PTSD symptoms. PI has been associated with maladaptive emotional processing, cognitive hyperarousal, and experiential avoidance, all of which may negatively affect sleep quality [49–51]. Sleep disturbances, in turn, have consistently been linked to PTSD symptoms, particularly in critically ill populations [52, 53]. There are studies looking at the effect of psychological flexibility (the opposite of PI) on sleep in different groups, although not in patients who suffered from a COVID-19 infection during the pandemic. In these studies, similar to our findings, psychological flexibility was found to be positively associated with sleep quality in nurses [54] and negatively associated with insomnia symptoms in the general population [55]. In addition, the relationship between insomnia severity and PTSD symptoms, which is another finding of ours, is consistent with the findings that poor sleep quality increases the severity of post-traumatic stress symptoms in patients who suffered COVID-19 [56] and that subjective poor sleep quality is a predictor of PTSD symptoms in the general population during the pandemic [57].

In our study, we found that female gender and lower education level were associated with higher PTSD scores. The mean values of IES-R, which investigates PTSD symptoms, were higher in female COVID-19 survivors compared to males. Our finding is consistent with studies conducted in patients who suffered from infections during the COVID-19 pandemic and the previous SARS pandemic [7, 58–61] and the prevalence of PTSD in the general population [62]. Underlying psychological, genetic and hormonal factors in women may have contributed to higher susceptibility to PTSD following a stressor [63, 64]. One of our findings was that patients with lower education levels had higher IES-R scores. A study conducted on this subject during the pandemic also supported our findings, namely it was found that among COVID-19 survivors, patients with low education level were more likely to develop PTSD [60]. It is stated that patients with a higher level of education may apply better coping methods because they have better social support and economic resources [65, 66]. Accordingly, patients with higher education levels who suffered COVID-19 may have been less affected by the disease process, and PTSD symptoms may have appeared less.

In our study, we determined that among COVID-19 survivors, patients with comorbid chronic diseases had higher PTSD symptoms. In support of our findings, a study conducted in patients who contracted the disease during the previous SARS outbreak found that the presence of chronic medical illness before SARS was a factor associated with chronic PTSD [61]. In a study conducted in COVID-19 survivors, obesity was also reported to be a risk factor for PTSD [67]. A study conducted in the USA found the prevalence of PTSD to be higher in black adults with two or more of the conditions associated with COVID-19 mortality, i.e. obesity, hypertension, diabetes, heart disease or asthma [68]. The fact that diseases such as diabetes, hypertension and chronic lung diseases were expressed as risky conditions for COVID-19 mortality, especially in the early stages of the COVID-19 pandemic, may have caused these patients to feel more threatened than others, causing them to be more traumatized during the pandemic.

While we speculated that depression might be linked to PTSD, additional analyses were not performed due to the results being only marginally significant. These findings do not suggest an absence of a connection between depressive and PTSD symptoms in this group; more extensive researches are required in this field.

Strengths and limitations

The cross-sectional nature of our study requires a cautious approach to the results that contain causal relationships. We used self-report measures to assess PTSD, depression, anxiety, sleep problems and PI. We were unable to obtain additional information on psychiatric diagnoses because we were unable to conduct a structured psychiatric interview. Therefore, our data may be prone to bias due to common method variance. We conducted our study on a population of COVID-19 survivors; thus, we cannot generalize our study to other populations. Studies conducted during the pandemic have usually been carried out online in the general population and healthcare workers. There are very few studies in patients who contracted COVID-19. Our study is the first to evaluate the effect of PI on PTSD symptoms in COVID-19 survivors, and the direct application of the scales to patients in an outpatient setting renders this study significant.

Conclusions

In this study, we found that female gender, low education level and additional chronic diseases constitute risk groups for PTSD after COVID-19 infection. We also found that PI may be a common factor associated with anxiety, depression, PTSD symptoms and insomnia severity. Psychotherapy interventions such as process-based and ACT-based interventions targeting PI to reduce PI, especially in patients who suffered COVID-19 during the pandemic, may prevent these patients from experiencing PTSD, anxiety and depression symptoms, and sleep problems. Our current findings support the development and assessment of psychotherapeutic interventions that encourage the alleviation of PI during the pandemics like COVID-19.

Abbreviations

PTSD

Post-traumatic stress disorder

PI

Psychological inflexibility

HADS

Hospital Anxiety and Depression Scale

AAQ-II

Acceptance and Action Questionnaire II

IES-R

Impact of Events Scale-Revised

SPSS

Statistical Package for the Social Sciences

ISI

Insomnia Severity Index

CIs

Confidence intervals

IE

Indirect effect

Authors’ contributions

KK contributed to the study conception, data collection, and writing; and approved the final version. TK contributed to the study conception, data collection and interpretation, and review; and approved the final version. SK contributed to the study conception, data interpretation, and review; and approved the final version. VD contributed to the study conception, data interpretation, and review; and approved the final version.

Funding

No funding was received for this study.

Data availability

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

Declarations

I confirm all relevant ethical guidelines have been followed, and ethics approval has been obtained.

Ethics approval and consent to participate

The study was approved by the Clinical Research Ethics Committee of the Faculty of Medicine at Alanya Alaaddin Keykubat University (Approval date: 09 June 2021; Decision No: 10 − 01). All procedures performed in this study involving human participants were conducted in accordance with the ethical standards of the institutional research committee and with the 1964 Declaration of Helsinki and its later amendments. Informed consent was obtained from all participants prior to their inclusion in the study.

Consent for publication

Not applicable.

Competing interests

The authors declare no competing interests.