Assessing Stigma Towards Chronic Insomnia: The Role of Health Status and Life Quality

The objective of this study was to explore the stigma and related inuencing factors in patients with chronic insomnia disorder (CID). A total of 70 CID patients and 70 healthy controls (CON) were enrolled in the study. The Pittsburgh Sleep Quality Index (PSQI) and the 17-Item Hamilton Depression Rating Scale (HAMD-17) were used to assess sleep quality and depressive symptoms, respectively. The Chinese-Beijing version of the Montreal Cognitive Assessment scale (MoCA-C) was used to assess cognitive function. Stigma and life quality were measured using the Chronic Stigma Scale and the 36-Item Short-Form Health Survey (SF-36). between with the the had higher for total (U = 662.0, p < 0.001), internalized stigma (U = 593.0, p < 0.001), stigma (U = 1568.0, p < 0.001), PSQI (U = 2485.0, p < 0.001) and HAMD-17 (U = 69.5, p < 0.001) as well as lower scores for MoCA-C (U = 3997.5, p < 0.001) and SF-36 for the items of physical role (U = 1560.5, p < 0.001), (U = 1633.5, p < health (U = 1194.0, p < vitality (U = 1169.5, p < social function (U = 1703.0, p = 0.001), emotional role (U = 1451.5, p < mental health (U 1147.0, p and (U different the with and HAMD-17 while negatively correlated with one of the regression analysis


Introduction
Stigma manifests as both prejudice of and rejection from society towards patients who suffer from a speci c pathology. A patient's internalization of such discrimination can have repercussions on their state of mind and quality of life. 1 It is possible to distinguish between "enacted stigma", which consists of actual discrimination and rejection by society towards the patient, and "internalized stigma", whereby the patient becomes aware of the discrimination and internalizes the negative impact of their disease. 2 Different degrees of stigma seriously affect physical health conditions, which can subsequently exacerbate mental health conditions and further harm an individual's health. 3 Additionally, mental disorders have been reported to accompany stigmatization, which results in increased psychological distress and decreased health-related quality of life. 4 Depression is a common mental health disorder, with more than 300 million people affected worldwide; one of the barriers to treatment is social stigma. 5 Despite the high personal burden for individuals with depression, not all individuals seek professional treatment, and an increasing number of studies globally have shown that stigma is a barrier to individuals seeking help. 6-8 Insomnia is not only a risk factor for depression but also a frequent complaint of patients with depression. [9][10][11] Symptoms of insomnia are considered a critical feature of mental disorders, and a better understanding of the processes involved can contribute to the re nement of pathophysiological concepts and therapeutic approaches for depressive disorders. 12 Research has shown that increased stress and depressive symptoms are closely associated with weight stigma in adolescents, which can result in poorer global sleep quality and more daytime dysfunction. 13 However, despite the high comorbidity of depression and insomnia, 14 the role that stigma plays in chronic insomnia disorder (CID) remains unclear.
This study aimed to better understand: 1) the risk of stigma in patients with CID and 2) related in uencing factors of stigma in CID patients. Our study may contribute to the knowledge gap regarding chronic insomnia stigma and offer a better understanding of the experiences of individuals with sleep disorders who experience stigma.

Subjects
A total of 70 CID patients were recruited from the Clinic of Sleep and Memory Disorder of the A liated Chaohu Hospital of Anhui Medical University between September 2019 and June 2020. In addition to meeting the International Classi cation of Sleep Disorders, Third Edition (ICSD-3) diagnostic criteria for CID, 15 inclusion criteria for patients were as follows: (1) aged between 18 and 75 years; (2) had at least 6 years of education without problems in comprehension; (3) not taking drugs that could potentially interfere with sleep, cognitive function or endocrine function in the 3 months prior to enrolment; and (4) voluntarily participating in the study after providing written informed consent. Exclusion criteria were as follows: (1) somatic comorbidity (including immunologic, endocrine, cardiovascular, neurologic, liver, kidney or organic brain disease); (2) history of substance abuse; (3) recent infection or in ammation (within 2 weeks of the start of the study); (4) taking drugs that could affect sleep, mood, immune function or cognition; and (5) pregnant or lactating women.
We also recruited 70 healthy controls (CON) based on similar background information to that of the experimental group (

General data collection
General information was collected using a questionnaire, which included sex, age, education level, illness duration, medical history and family medical history.

Evaluation of sleep quality
Sleep quality was assessed using the PSQI, which has seven components including subjective sleep quality, sleep latency, sleep duration, habitual sleep e ciency, sleep disturbance, use of sleep medication and daytime dysfunction during the previous month, which are scored on a 4-point rating scale ranging from 0 (none) to 3 (≥ 3 times per week). 16 In China, a score ≥ 7 has high diagnostic sensitivity and speci city for distinguishing patients with poor sleep from healthy subjects. 18 Total PSQI scores range from 0-21, with a higher score corresponding to poorer sleep quality. 16

Assessment of depression severity
Depression severity was assessed using the HAMD-17, which comprises 17 items relating to depressed mood, feelings of guilt and suicide, sleep, work and activities. 19 A score < 7 indicates a healthy state, whereas scores of 7-17, 18-24 and > 24 correspond to mild, moderate and severe depression, respectively.

Cognitive assessment
The MoCA-C is a widely used cognitive screening tool with good reliability and validity. 20 The MoCA-C comprises eight dimensions: visual space and executive function, naming, attention, language, abstraction, short-term memory, delayed recall and orientation. 21 The maximum score is 30 points, and a score ≥ 26 indicates normal cognitive function. 20

Stigma evaluation
The Stigma Scale for Chronic Illness (SSCI) is a 24-item measure of stigma, which evaluates the degree of stigma of chronic neurological diseases and includes 13 internalized and 11 enacted items. 22 Each item is rated using the following response format: 1 = never, 2 = rarely, 3 = sometimes, 4 = often and 5 = always. The total score ranges from 24 to 120 points and indicates the severity of stigma suffered by the patient. A score < 8 indicates a healthy state, whereas scores > 20 and > 35 correspond to mild and severe stigma, respectively. 22

Assessment of life quality
The Medical Outcomes Study (MOS) 36-Item Short-Form Health Survey (SF-36) measures health-related quality of life, functioning and well-being and has strong reliability and validity for use in both general and disease-speci c populations. 23 The survey assesses eight dimensions of health, which include: physical function, physical role, body pain, general health, vitality, social function, emotional role and mental health. It also contains an additional item of health transition, which is not part of any dimension and measures the declared evolution of health. [24][25] Higher scores correspond to better health-related life quality. 23 2.8 Statistical analysis SPSS version 20 for windows was used for statistical analyses. Continuous normally distributed data are presented as means ± standard deviations and were evaluated using Student's t-test to compare differences between groups and one-way analysis of variance to determine main effects. The least signi cant difference test was used for multiple comparisons. Non-normally distributed data are expressed as P50 (P25 and P75), and differences between groups were analysed using the rank-sum test for two independent samples with a completely randomized design (Mann-Whitney U). Categorical data were analysed using a chi-squared test. To control for the confounding factors and their in uence on the variables, correlations between stigma scores and illness duration (controlling for sex, age and educational level), PSQI score (controlling for sex, age, educational level, illness duration and HAMD-17 score), HAMD-17 score (controlling for sex, age, educational level, illness duration and PSQI score), MoCA-C score (controlling for sex, age, educational level, illness duration, PSQI score and HAMD-17 score) and SF-36 score (controlling for sex, age, educational level, illness duration, PSQI score, HAMD-17 score and MoCA-C score) were assessed using partial correlation analysis. Multiple linear regression was used to explore the correlation between stigma and related in uencing factors and identify the contribution of each related in uencing factor to changes in stigma. Two-sided p values ≤ 0.05 were considered statistically signi cant.

Sleep quality and depression severity
PSQI scores differed signi cantly between groups (U = 2485.0, p < 0.001), and the CID group had signi cantly higher scores than the control group. HAMD-17 scores differed signi cantly between groups (U = 69.5, p < 0.001); the score of the CID group was almost six times higher than that of the health controls (Table 1).

Cognitive function
There were signi cant differences in MoCA-C scores between the two groups (U = 3997.5, p < 0.001). Patients with CID had signi cantly lower total MoCA-C scores ( Table 1).

Multiple linear regression between stigma scores and related factors
For the regression analysis in the CID group, scores for the different items of stigma were de ned as the dependent variable and those for all related factors were de ned as independent variables based on the partial correlation analysis. Results revealed a signi cant linear regression, in which illness duration was independently positively correlated with total (β = 0.433, p < 0.001), internalized (β = 0.326, p < 0.001) and enacted (β = 0.441, p < 0.001) stigma scores. The SF-36 item of mental health was independently negatively correlated with total (β = −0.346, p = 0.007) and internalized (β = −0.377, p = 0.004) stigma (Table 4).

CID patients have an increased risk of stigma
As a particularly burdensome personal and social challenge, stigma is closely related to mental disorders, such as depression. 26, 27 Several severe physical disorders are also accompanied by stigmatization. 28-30 People living with human immunode ciency virus (HIV) who experience HIV-related stigma are prone to experiencing more depressive symptoms and poorer sleep quality. 31 Although 50-80% of individuals with a chronic disease experience stigma at varying levels, [32][33] little is known about the extent to which stigma impacts chronic insomnia. In the present study, we found that compared with healthy subjects, CID patients had higher stigma ratios and scores. This indicated that CID patients have some degree of stigma, and the level of stigma is signi cantly higher than that of controls. This may be because stigma exerts a negative in uence on sleep due to increased negative self-thought and activation of the ruminative thought process. [34][35] Indeed, individuals with severe sleep problems are more likely to have depression, which may exacerbate the severity of stigma in CID patients. 36

Lower life quality in CID patients
Life quality is a major outcome variable in the evaluation of alternative treatments for sleep disorders. 37 Poor-quality sleep can negatively affect an individual's subjective well-being and quality of life. 38 Particularly under pathological conditions, high quality of life positively affects sleep. 39 In the present study, we also found that CID patients had signi cantly lower scores than controls in most domains of the SF-36, which included physical role, body pain, general health, vitality, social function, emotional role, mental health and health transition, which suggests that CID negatively impacts quality of life. However, we did not nd a signi cant difference in the item of physical function between the two groups. Even in the partial correlation analysis, the item of physical function did not correlate with any of the domains of stigma. Such a discrepancy may be attributed to several factors, such as ethnic origin, sex, comorbidities and differences in the severity of insomnia. [40][41][42] Further studies are required to reach a de nitive conclusion.

Relationship between stigma scores and related in uencing factors
With a prolonged disease course, patients under chronic disease conditions exhibit different levels of stigma. 43 A recent study in high-school students suggested that stigma is strongly and consistently associated with negative psychological health, which includes depressive symptoms and anxiety. [44][45][46] However, stigma alleviates throughout the life span as individuals acquire the experience to cope with their surroundings. For instance, in a study in multiple sclerosis (MS) patients by Spencer et al., patients with MS who were particularly concerned and distressed by stigma early in the course of their illness restructured their lives by adapting to the social aspects of their illness, which mitigated the impact of stigma. 47 In our study, both the partial correlation and multiple linear regression analyses showed that the longer the illness duration, the higher the stigma score, which is in line with previous studies. To gain a comprehensive understanding of stigma changes, it would be meaningful to further observe these populatuons in future studies. Moreover, stigma is in uenced not only by illness duration, 48-49 and identifying other in uencing factors is necessary.
Life quality is a critical factor that promotes the progression of stigma. 50 Individuals with serious mental illness die prematurely by decades, which is not driven by increased suicides or injuries but by poor physical health, which is in uenced by stigma. 51 Our results showed that stigma scores were negatively correlated with most of the subitems of the SF-36, which suggested that stigma in CID patients is related to health quality. Interestingly, the multiple linear regression analysis showed that only the mental health item of the SF-36 was an independent risk factor of stigma, which further demonstrates the in uence of mental health on stigma. In other words, mental illness severity should be considered a predictor of stigma among people with mental health problems. [52][53] This may be because mental disorders, such as depression, affect the perception of the circumstances of daily life. 54 In individuals with mental disorders, stigma may represent a potent stressor that disrupts sleep and impairs health and quality of life. 55 Furthermore, via the content and process of stigma, discrimination has a signi cant indirect effect on sleep disturbance in these individuals. 56 In the present study, the partial correlation analysis in the CID patients revealed that poor sleep quality and severe depression were positively correlated with different aspects of stigma, such as total and internalized stigma. However, these correlations were not observed in the subsequent multiple linear regression analysis. These results suggest that in CID patients, the effect of stigma on sleep quality and depression severity is largely dependent on illness duration and life quality, especially mental health.

Conclusion
Patients with CID had an increased risk of stigma, and illness duration and mental health were the main factors related to stigma. Our results provide a solid foundation to develop and implement interventions for CID patients and suggested that different levels of stigma underlie CID. Caregivers should prioritize monitoring CID patients living with high levels of stigma and developing targeted interventions to eliminate the stigmatization of this group.

Declarations
Ethical approval and consent to participate A liated Chaohu Hospital of Anhui Medical University Ethics Committee (approval no. 201805-kyxm-01). All participants who met the inclusion and exclusion criteria were informed of all essential information regarding the research project, and we obtained a signed informed consent form before the interviews.

Consent for publication
Not applicable.

Available of data and materials
Not applicable.

Competing interests
The authors declare no con icts of interest.

Role of funding sources
This work was nancially supported by the National Natural Science Foundation of China (grant no. 81671316) and the Natural Science Foundation of Anhui Medical University (grant nos. 2020xkj053 and 2018xkj066). These funding sources had no role in the study design, analysis, data interpretation or decision to submit the article for publication.

Authors' contributions
Gui-Hai Chen and Hui-Qin Sun conceived, designed, and supervised the study. Shuo He and Xue-Jia Ke performed statistical analyses and drafted the manuscript. Yun Wang and Deng-Zhi Xia participated in project supervision. Yan Wu, Xiao-Yi Kong and Ping Zhang collected and organized the data. All authors read and approved the nal manuscript.