Dental and Medical Problems

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Dental and Medical Problems

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doi: 10.17219/dmp/177008

Publication type: original article

Language: English

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Orzeszek S, Martynowicz H, Smardz J, et al. Assessment of sleep quality in patients with orofacial pain and headache complaints: A polysomnographic study [published online as ahead of print on June 4, 2024]. Dent Med Probl. doi:10.17219/dmp/177008

Assessment of sleep quality in patients with orofacial pain and headache complaints: A polysomnographic study

Sylwia Orzeszek1,A,B,C,D,F, Helena Martynowicz2,A,B,C,D,E, Joanna Smardz1,A,B,C,D,E, Anna Wojakowska2,B,D,E, Wojciech Bombała3,C,D,E, Grzegorz Mazur2,A,C,D,F, Mieszko Wieckiewicz1,A,B,C,D,E

1 Department of Experimental Dentistry, Outpatient Clinic for Temporomandibular Disorders, Wroclaw Medical University, Poland

2 Clinical Department of Internal and Occupational Diseases, Hypertension and Clinical Oncology, Wroclaw Medical University, Poland

3 Statistical Analysis Centre, Wroclaw Medical University, Poland

Graphical abstract


Graphical abstracts

Abstract

Background. Sleep is a physiological function essential for survival, recovery, tissue repair, memory consolidation, and brain function. Pain is also an indispensable aspect of human life. The coexistence of sleep disorders and pain is often described in the literature, yet it is critical to define sleep not only subjectively but also using objective instrumental methods, such as polysomnography, that provide data on sleep quality.

Objectives. The aim of the study was to determine the relationship between orofacial pain (OFP), headache (HA) and sleep quality using subjective and objective sleep quality assessment methods. Additionally, we aimed to explore whether poor sleep quality was related to OFP and HA alone or was influenced by the coexistence of psycho-emotional factors such as depression, anxiety and stress.

Material and methods. A single-night video-polysomnography was performed on patients from the Outpatient Clinic for Temporomandibular Disorders at Wroclaw Medical University, Poland, who had been diagnosed with OFP and HA. Additionally, questionnaires were employed to assess sleep quality, pain, HA, and the psycho-emotional state.

Results. There was no statistically significant relationship between the severity of OFP and HA and polysomnographic sleep quality parameters. On the other hand, the quality of sleep as determined by questionnaire studies correlated markedly with the severity of experienced pain. The severity of pain was found to be significantly correlated with depression, anxiety and perceived stress scores.

Conclusions. The psycho-emotional aspects are of critical importance in the perception of OFP and HA. They can be associated with worsened subjective sleep quality, insomnia or daytime sleepiness. Therefore, the treatment of such patients must be preceded by a comprehensive assessment of their psycho-emotional state, as anxiety, stress and depression can significantly influence the course of the disease and the response to treatment procedures.

Keywords: sleep quality, polysomnography, headache, orofacial pain, psycho-emotional state

Introduction

Sleep is a physiological function essential for recovery from fatigue, tissue repair, memory consolidation, and brain function.1 It is an active neurobehavioral state that is maintained through a highly organized interaction of neurons and neural circuits in the central nervous system (CNS).1 Pain is an indispensable part of human life, acting as a physical and emotional signal of body damage that strongly motivates human behavior.1 Orofacial pain (OFP) encompasses a heterogeneous group of con­ditions, including dental, mucosal, musculoskeletal, neuro­vascular, and neuropathic pain,1 and can be classified in terms of acuity and chronicity. However, the definition of chronic pain, which is pain that persists for more than 3 months, is not useful for assessing OFP and headache (HA) for chronicity.2, 3, 4 In OFP and HA, chronic pain is defined as pain that occurs more than 15 days per month and lasts more than 4 hours daily for at least the preceding 3 months.2

Disorders of systems regulating pain and sleep can have a broad negative impact on health and well-being. Sleep complaints are present in 67–88% of individuals suffering from chronic pain disorders.5, 6, 7 Moreover, at least 50% of those with insomnia, the most commonly diagnosed sleep disorder, suffer from chronic pain.8, 9 Several studies that described a strong correlation between pain occurrence and decreased sleep quality also highlighted the crucial role of the psycho-emotional state of patients, including depression, somatization and anxiety.10, 11, 12, 13, 14, 15 A number of studies investigating the relationship between OFP (especially pain associated with temporomandibular disorders (TMD)) and HA and the deterioration of sleep quality demonstrated an association between sleep disturbances and mood swings, impaired memory and cognition, changes in the immune system, and somatic pain complaints.1, 2, 9, 16

Previous studies have indicated the existence of a two-way relationship between pain and sleep quality. Sleep disorders can impair regenerative physiological processes and functions that support homeostasis. These disorders contribute to the development and persistence of chronic pain and poorer patient response to treatment, which makes pain management more difficult.17, 18 Other studies have shown that pain can negatively affect sleep via cortical arousal mechanisms that interfere with falling asleep and maintaining sleep.19 In contrast with acute pain, in which the relationship is linear and rapidly reversible, chronic pain has been described as a vicious cycle with mutual deleterious influences between disturbed sleep and pain.20 Many authors have also considered the possibility that the pain itself does not cause sleep quality deterioration in patients with OFP but rather psycho-emotional disturbance, such as high levels of stress, anxiety and depression, which are very common in patients suffering from pain.

The psycho-emotional state is a vital factor in the deterioration of sleep quality.21, 22 However, the major­ity of existing research used subjective sleep quality indicators, such as questionnaires, which inadequately assess sleep quality. Polysomnography is a reliable and objective method for evaluating sleep quality. The objective of this study was to assess the relationship between pain, HA and sleep quality through the use of both subjective and objective assessment methods. All patients underwent a single-night video-polysomnography, and the data was compared to the results of sleep quality questionnaires. The study also aimed to explore whether low sleep quality was solely related to pain and HA, or whether it was influenced by the coexistence of psycho-emotional factors such as depression, anxiety and stress.

Material and methods

Participants

The study participants were patients of the Outpatient Clinic for Temporomandibular Disorders at Wroclaw Medical University in Poland. Patients who reported OFP and/or HA and/or impaired sleep quality were referred for a single-night video-polysomnography at the Clinic of Internal Medicine, Occupational Diseases, Hypertension and Clinical Oncology at Wroclaw Medical University, where, in addition to undergoing a polysomno­graphic examination, they completed several ques­tionnaires related to their psycho-emotional state, sleep quality and pain. The study group consisted of patients who reported primary HA and OFP. Primary HA was defined as pain occurring in temporal relationship to the onset of pain, with no underlying pathological process, disease or traumatic injury. This included migraine, tension-type HA and trigeminal autonomic cephalalgias.3 Orofacial pain encompasses myofascial OFP (pain localized to the masticatory muscles, with or without functional impairment), temporomandibular joint (TMJ) pain (pain localized to the TMJ, occurring at rest or during jaw movement or palpation) and OFP that resembles presentations of primary HA (pain in the orofacial area resembling one of the primary HA types in pain character, duration and intensity, with or without the associated symptoms of these HA types but without concomitant HA).4 The study protocol was approved by the Ethical Committee of Wroclaw Medical University (approval No. KB-794/2019). All study participants were informed of the purpose of the study and consented to participate. The study was conducted in accordance with the Declaration of Helsinki for research involving human subjects. The study was registered in the ClinicalTrials.gov database (identifier No. NCT04214561).

Inclusion criteria

The study included individuals over the age of 18 who reported OFP and/or HA and/or impaired quality of sleep and who were willing to participate.

Exclusion criteria

The main exclusion criteria were addiction to a drug or medication, the use of medicines that significantly affect the function of the nervous and muscular systems, severe systemic diseases, severe mental disorders, including significant mental disabilities, less than 4 hours of sleep recorded using polysomnography, and lack of consent to participate. Pregnant women, patients with a diagnosed sleep apnea disorder and those using a mandibular advancement device (MAD) or continuous positive airway pressure (CPAP) were excluded from the study.

Video-polysomnography procedure

The patients underwent a single-night video-polysomnography examination in the Sleep Laboratory at Wroclaw Medical University using a Nox A1s (Nox Medical, Reykjavík, Iceland) device. The recording was performed between 10.00 pm and 6.00 am, taking into account the patient’s individual preferences and sleeping habits. The polysomnographic examinations included electroencephalography, electrocardiography, electro­oculography, and electromyography recordings from the chin area and bilaterally from the regions of the masseter muscles, motion recording of abdominal and thoracic breathing activity, assessment of body position, and audio and video recording. A pulse oximeter (NONIN 3150 WristOx 2; Nonin Medical Inc., Plymouth, USA) was used to record oxygen saturation and pulse, while Noxturnal software (Nox Medical), developed for sleep recording and analysis, facilitated data analysis.

Pain assessment

McGill Pain Questionnaire

The McGill Pain Questionnaire (MPQ) contains 78 words that describe the experience of pain and provides scores that range from 0 (no pain) to 78 (severe pain). Results are considered clinically significant when the total value is greater than 5.21 A study by Melzack and Katz assessing the multidimensional nature of pain experience demonstrated that the short-form MPQ (SF-MPQ) is a reliable, valid and consistent measurement tool. The SF-MPQ is suitable for use in specific research settings where the time available to obtain information from patients is limited and where the aim is to obtain information that extends beyond the measurement of pain intensity.23, 24

Graded Chronic Pain Scale

The Graded Chronic Pain Scale (GCPS) allows for the grading of chronic pain severity, disability score and disability points. The following classifications are provided: Grade 0 – no pain in the previous 6 months; Grade I – low-intensity characteristic pain intensity <50, low disability, with <3 disability points; Grade II – high-intensity characteristic pain intensity 50, low disability, with <3 disability points; Grade III – moderately limiting high disability score of 3 to 4 disability points (regardless of characteristic pain intensity); and Grade IV – a severely limiting high disability score of 5 to 6 disability points (regardless of characteristic pain intensity).25 Sharma et al. reported that the reliability of the one-month GCPS is equal to or better than the six-month version in terms of pain intensity, days of disability, pain interference, chronic pain grade, and high-impact pain.26 The study demonstrated that the GCPS is a reliable and valid tool for measuring pain intensity and pain interference.26

Headache Impact Test-6

The Headache Impact Test-6 (HIT-6) score ranges from 36 to 78, with a score ≤49 indicating no or little impact of HA on daily activities, 50–55 indicating a slight impact, 56–59 a significant impact, and ≥60 a severe impact. A study demonstrated that the HIT-6 is a reliable and valid instrument for measuring the impact of HA on daily life in both episodic and chronic migraine sufferers. The internal consistency reliability among migraine sufferers was high, ranging between 0.82 and 0.90.27

Migraine Disability Assessment

The Migraine Disability Assessment (MIDAS) involves the summation of the total number of days indicated in questions 1–5. The grading system includes the following: Grade I – little or no disability over 0–5 days; Grade II – mild disability across 6–10 days; Grade III – moderate disability over 11–20 days; and Grade IV – severe disability for more than 21 days.27 Stewart et al. demonstrated moderately high test-retest reliability of the MIDAS score for HA sufferers and a correlation with clinical judgment on the need for medical care.28 The MIDAS score is calculated by summing the number of days missed from work or school, days missed from household chores, days spent on non-work activities, and days spent at work or school, as well as days spent on household chores where productivity was reduced by at least 50% over the previous 3 months. The correlation between the MIDAS summary score and an equivalent daily diary score was 0.63, while the group estimate of the MIDAS score was found to be a valid estimate of a rigorous diary-based measure of disability. In addition, the mean and median values for the MIDAS score in a population-based sample of migraine cases were comparable to those of equivalent diary measures.28

Temporomandibular disorder pain screener

Individuals with a score of 3 or above on the TMD pain screener (range 0–7) are predicted to have painful TMD based on the Diagnostic Criteria for Temporomandibular Disorders (DC/TMD) and are, therefore, considered to have a positive TMD pain test result. The TMD pain screener demonstrated excellent sensitivity and specificity levels, as well as validity in correctly identifying participants with pain-related TMD (sensitivity of 99%) and healthy controls (specificity of 97%). The short screener correctly identified individuals with symptoms of competing conditions, including non-painful TMJ disorder (specificity of 95%) and HA not related to TMD (specificity of 96%).29

Subjective assessment of sleep quality

Insomnia Severity Index

The Insomnia Severity Index (ISI) has a minimal score of 0 and a maximal score of 28. A value of up to 10 is considered within the normal range, while a score of 8–14 indicates subthreshold insomnia. A score of 15–21 indicates significant moderate insomnia, while a score of 22–28 is indicative of severe insomnia.30

Pittsburgh Sleep Quality Index

The Pittsburgh Sleep Quality Index (PSQI) is a tool designed to assess sleep quality over a one-month interval. The measure is comprised of 19 individual items, divided into 7 components of sleep quality, which collectively yield a single global score, ranging from 0 to 21. A lower score indicates better sleep quality. A total score of 5 is considered a designated cut-off point for poor sleep quality.31

Epworth Sleepiness Scale

The Epworth Sleepiness Scale (ESS) is a validated eight-item questionnaire that is used to assess subjective sleepiness. The ESS values range from 0 (unlikely to fall asleep in any situation) to 24 (high chance of falling asleep in all 8 situations). The final ESS score indicates normal sleepiness (1–10), mild daytime sleepiness (11–14), average daytime sleepiness (15–18), or severe daytime sleepiness (>18).32

Psycho-emotional state assessment

Sense of Stress Questionnaire

The Sense of Stress Questionnaire (KPS) is designed to assess the structure of stress sensations. The questionnaire comprises 27 statements that can be used to calculate an overall score of an individual’s generalized stress level. In addition, 3 results related to emotional tension, intrapsychic stress (resulting from a confrontation with oneself) and external stress (resulting from the confrontation of the individual with the burdens perceived in the social and external worlds) are generated. The questionnaire also contains the scale of lies.33

Perceived Stress Scale-10

The Perceived Stress Scale-10 (PSS-10) results range from 0 to 40. Scores between 0 and 13 are indicative of low stress, scores between 14 and 26 indicate moderate stress, and scores between 27 and 40 are indicative of high perceived stress.34

Patient Health Questionnaire-9

Subjects rate the Patient Health Questionnaire-9 (PHQ-9) responses on a scale of 0 to 3 based on the frequency with which a given symptom has manifested in the last 2 weeks. Total scores for the 9 items range from 0 to 27, with a score of 10 or above indicating a high risk of a depressive episode. The higher the score, the greater the risk of depression. Scores are interpreted as follows: no depression (<5); mild depression (5–9); moderate depression (10–14); moderately severe depression (15–19); or severe depression (20).35

Beck Depression Inventory

The Beck Depression Inventory (BDI) is a 21-item self-rated scale that evaluates key symptoms of depression, including mood, pessimism, sense of failure, self-dissatisfaction, guilt, punishment, self-loathing, self-accusation, suicidal ideation, crying, irritability, social withdrawal, indecisiveness, body image change, work difficulty, insomnia, fatigability, loss of appetite, weight loss, somatic preoccupation, and loss of libido. A total score of 0–13 is considered within the minimal range, while 14–19 is indicative of mild depression, 20–28 of moderate depression, and 29–63 of severe depression.36

Beck Anxiety Inventory

The Beck Anxiety Inventory (BAI) score is calculated by summing 21 items and can range between 0 and 63 points. A total score of 0–7 is interpreted as minimal anxiety, 8–15 as mild anxiety, 16–25 as moderate anxiety, and 26–63 as severe anxiety.37, 38

Generalized Anxiety Disorder-7

The Generalized Anxiety Disorder-7 (GAD-7) questionnaire consists of 7 items and the GAD-7 score can range from 0 to 21 points. The cut-off points for mild, moderate and severe anxiety are 5, 10 and 15, respectively.39

Statistical analysis

The medical history, questionnaires and polysomnographic data were entered into a database and subjected to statistical analysis.

The non-parametric Kendall’s Tau correlation coeffi­cient was employed to assess the relationship between the variables, with the choice of the coefficient being deter­mined by the fact that the variables did not have a normal distribution. A p-value for a correlation coefficient below 0.05 was considered statistically significant. The estima­tion of the sample size (N) was conducted using the power.cor function and the genefu package (https://rdrr.io/bioc/genefu/man/power.cor.html). The sample size for the Kendall correlation significance was calculated on the assump­tion that the expected value of the correlation coefficient would be 0.7 and that the expected width of the confidence interval would be 0.05. The calculated sample size was 22. Therefore, the 114 patients enrolled in the study constitute a sufficient base for the detection of differences and cor­relations between the examined parameters.

Results

Study sample

A total of 114 Caucasian adults (72 females and 42 males), aged 21–71 years (mean (M= 37.67 years), participated in the study.

Relationship between pain and headache and subjective assessment of sleep quality

The severity of pain experienced by the participants was assessed using 4 independent questionnaires, as illustrated in Table 1. Taking into account the GCPS values, 64 participants reported experiencing low-intensity pain, with none to low pain-related disability (Grade I), 2 participants described their complaints as high-intensity pain without pain-related disability (Grade IIa), 15 stated that the pain they felt was of a high intensity and caused low pain-related disability (Grade IIb), 11 described their pain as a high-intensity pain causing moderately limiting disability (Grade III), while only 2 participants described their pain level as high-severity with severely limiting disability (Grade IV). The remaining participants did not report pain.

The HIT-6 questionnaire results provided information on the impact of HA on functioning at work, school, home, and in various social settings. The results indicated that 48 subjects reported little or no impact of HA on their daily activities, 14 subjects reported a slight impact, 11 individuals reported a significant impact, and a severe HA effect on daily activities was reported by 35 subjects.

The impact of HA on functioning at work, home and in social settings was assessed using the MIDAS scale. Participants were classified into 4 disability groups based on the number of days they had to limit their activities due to HA. Little or no disability was reported by 52 participants (Grade I), 10 reported mild disability (Grade II), 15 – moderate disability (Grade III), and 23 – severe disability (Grade IV). A clinically significant pain level was reported by 40 participants in the SF-MPQ study. The remaining participants did not report any pain, and the complaints were not clinically significant. At the same time, clinically significant TMD-related pain was recorded for 41 participants who completed the TMD pain screener.

The participants completed questionnaires designed to assess their sleep quality. In the PSQI, the cut-off point indicating poor sleep quality was reached by 73 subjects, while 36 subjects were classified as having normal sleep quality. The ISI indicated that 29 participants had normal sleep quality, 33 individuals had subthreshold insomnia, 21 – significant moderate insomnia, and 6 – severe insomnia. According to the ESS, 61 respondents exhibited no abnormalities, 18 displayed mild daytime sleepiness, 7 had average daytime sleepiness, and 2 exhibited severe daytime sleepiness. Table 1 provides a summary of the aforementioned results.

The Kendall’s Tau correlation coefficient showed a statistically significant association between self-reported pain severity and decreased sleep quality. Furthermore, there was a correlation between greater pain and related disability, as assessed using the GCPS, and subjective sleep quality, as assessed using the PSQI and ISI questionnaires. The correlation between the increased pain reported in the SF-MPQ and the worsened sleep quality observed in the ISI and PSQI scores was statistically significant. Participants whose scores exceeded the cut-off point in the TMD pain screener exhibited a deterioration in sleep quality, as indicated by the ISI and PSQI scores. The relationship between the increase in pain complaints reported in the HIT-6 questionnaire and the deterioration in sleep quality observed in the PSQI, ISI and ESS questionnaires was also statistically significant. A similar relationship was observed between the MIDAS questionnaire values and the PSQI, ISI and ESS scores. Consequently, the current research indicates that pain and related disability were the cause of poor sleep quality. Table 2 illustrates the presence of subjective sleep disturbances based on the increase in reported pain.

Relationship between pain and headache and the assessment of sleep quality in polysomnography

The quality of sleep was also objectively evaluated in a sleep research laboratory. All participants underwent a polysomnographic examination, which recorded the parameters necessary for the objective assessment of sleep quality. A statistical analysis was conducted, including the following polysomnographic parameters: total sleep time (TST), which represents the sum of time spent asleep in minutes; wake after sleep onset (WASO), which refers to waking up after falling asleep; sleep latency (SL), which is defined as the time from turning off the light to falling asleep (and is considered the first occurrence of non-rapid eye movement (NREM) stage 2); and sleep efficiency (SE), which is calculated as TST/total time in bed (TBT) × 100%. Table 3 presents the results of the polysomnographic examination.

The results of the Kendall’s Tau test were unexpected, as the quality of sleep measured during polysomnography did not show a statistically significant relationship with an increase in the intensity of reported pain and related disability. Only participants whose scores exceeded the cut-off point on the TMD pain screener demonstrated a reduction in the WASO parameter in the polysomnographic examination. The relationship between the increase in reported pain complaints in questionnaire studies and selected parameters assessed in polysomnography are presented in Figure 4.

A statistical analysis was conducted to assess the relationship between the SE and SL measured in the polysomnographic examination. The parameters were defined by the participants as 2 of the 7 components of sleep quality in the PSQI questionnaire (C2 falling asleep – analysis of the SL in minutes and the number of nights where the SL was extended to more than 30 min; C4 SE – quantitative assessment of the ratio of TST to TBT). The results of the comparison between the SL and SE are presented in Table 5.

The relationship between sleep quality parameters derived from polysomnography and sleep quality as assessed subjectively by participants in questionnaire studies is summarized in Table 6. The lack of correlation between these parameters confirms that subjectively assessed sleep quality is influenced by factors other than pain, as pain alone did not correlate with the occurrence of sleep disorders in the polysomnographic examination.

Relationship between the level of anxiety, depression and stress, and the subjective assessment of sleep quality

The PSS-10 and KPS questionnaires assessed perceived stress levels, the BDI and PHQ-9 evaluated depression, and the GAD-7 and BAI measured anxiety. Table 7 presents the number of participants at risk of psycho-emotional disturbances, defined as an increased sense of anxiety, stress and/or depression.

The statistical analysis revealed a significant correlation between the occurrence of pain, its severity and pain-related disability that causes limitations in everyday professional, family and social activities and affects the participants’ psycho-emotional state. This relationship is presented in Table 8.

The relationship between subjective sleep disturbances and the psycho-emotional state was significant. Increased anxiety, stress and depression scores correlated with a decrease in subjective sleep quality. Furthermore, a decreased psycho-emotional status was consistently correlated with increased participant complaints of poor sleep quality (as measured by the PSQI), increased daytime sleepiness (as measured by the ESS) and increased insomnia severity (as measured by the ISI). The relationship was more pronounced than that between perceived pain and the subjective assessment of sleep quality. Therefore, the psycho-emotional state of patients may be a factor influencing their perception of sleep quality (Table 9).

Relationship between the level
of anxiety, depression and stress, and
the objective assessment of sleep quality in polysomnography

The analysis of the impact of the psycho-emotional state on sleep quality, as measured using polysomno­graphy, revealed that the relationship between the 2 variables is not straightforward or statistically unambiguous. Patients with higher stress levels (as measured by the KPS) exhibited a shortened TST (p = 0.017), worse SE (p = 0.031), longer SL (p = 0.030), and a longer WASO (p = 0.028). However, this relationship was only found for TST (p = 0.049) when measuring stress levels using the PSS-10. There was no longer a significant correlation with WASO (p = 0.115), SL (p = 0.615) or SE (p = 0.235). The examination of other sleep parameters during polysomno­graphy did not reveal any abnormalities in participants with elevated levels of stress, anxiety or depression. The data is presented in Table 10.

Discussion

The objective of the study was to determine the relationship between reported OFP, HA and sleep quality using subjective and objective assessment methods. The study also aimed to explore whether the poor quality of sleep was only related to OFP and HA, or whether it was influenced by the coexistence of psycho-emotional factors such as depression, anxiety and stress. Even though the relationship between OFP and HA and the deterioration of sleep quality was reported by patients in questionnaire studies, no significant deviations were found in the objective study using polysomnography despite complaints reported by patients. However, the study revealed that patients who reported reduced sleep quality in questionnaire studies also exhibited elevated levels of stress, anxiety and depression.

Many studies have demonstrated that individuals with severe and prolonged pain and HA exhibit elevated levels of stress, anxiety and depression. These studies also indicated that psycho-social factors play a vital role in predisposing to, and the course of, severe pain or HA and their treatment.40, 41, 42 Such a relationship is in line with the results of the current study, which confirms the crucial role of the psycho-emotional state of patients suffering from pain in the course of the disease and the selection of treatment methods, which should aim to improve patient well-being and include psychological consultations and, if required, psychiatric consultations for support and multi-directional therapy.

Yap et al. examined the effect of the severity of TMD pain on sleep quality and the impact of TMD diagnosis type on sleep disorders.43 Their findings indicated that individuals with moderate to severe pain had sig­nificantly worse sleep than those with mild pain. Partici­pants with pain-related and/or intra-articular TMD reported significantly worse sleep quality than TMD-free controls. In addition, individuals with muscle pain and those with muscle pain and joint pain presented sig­nificantly worse sleep than those with non-painful joint disorders. However, in this study, sleep quality was only assessed using the PSQI.43 Kim and Kim also reported significant differences in global PSQI scores between 3 pain diagnosis groups in Korean TMD patients.44 Other authors indicated that reduced sleep quality in participants with pain associated with TMD can negatively impact treatment outcomes and quality of life.45, 46 The findings of the cited studies contrast with the results of the current study, which indicate pain as the primary cause of sleep quality abnormalities reported by patients. On the other hand, Yatani et al. demonstrated that poor sleep quality may not be solely attributed to elevated pain severity.47 Their findings indicated that psychological distress and low perceived life control contributed to reduced sleep quality.47 A similar conclusion can be drawn from the observations in the current study.

When discussing the issue of pain and sleep quality, it is important to consider the neurobiological aspect of OFP and the neural processes underlying sleep, particularly the mechanisms underlying the interactions between pain and sleep, including sleep disturbances. Chronic pain is often associated with poor sleep quality, which can also be a cause of pain. This interdependence indicates that the reduction of OFP and the improvement of sleep quality should be targeted together.20 Patients with chronic pain tend to exhibit either short or long sleep durations and also experience depressive mood symptoms.48, 49 According to other authors, chronic pain may increase the risk of insomnia,50 and insomnia may be associated with a reduction in pain tolerance and lower SE.51

Lavigne and Sessle state that, during normal sleep in healthy adults, nociceptive transmission is partially impaired to maintain sleep continuity, resulting in a higher threshold of excitability or a lower rate of response to noxious stimuli in light sleep (stages N1 and N2) and in deep sleep (stage N3), where it is even more important.20 However, this relationship is variable in REM sleep. These processes ensure that low-intensity stimuli have little or no effect on the quality of sleep if the sleep takes place in good conditions.20 Consequently, the link between pain and sleep quality, especially chronic pain, is indisputable. However, it must not be forgotten that there are also processes that prevent ailments from affecting the quality and course of sleep.

In their study, Dubrovsky et al. employed double-night polysomnography to assess sleep quality, using Symptom Checklist-90 to evaluate depressive symptoms and the PSQI to assess subjective sleep quality.52 The findings of their study were comparable to those of the current study. Increased self-reported sleep problems in women with myofascial pain were more attributable to reporting depressive symptoms than to pain intensity or objective polysomnography measures. The authors warned against assuming that myofascial pain is associated with poor sleep quality and highlighted the potential of question­naire studies such as the PSQI to effectively diagnose the presence of sleep disorders in study participants. Further­more, the authors advised that more attention should be paid to the necessity of objective sleep quality diagnostics, which can be achieved through polysomnographic exami­nation. This method does not often show deviations from the norm. As such, the poor sleep quality reported by patients suffering from pain may be caused by psycho-emotional disturbances.52 In contrast, Smith et al. revealed that approx. 36% of participants with TMD pain suffered from insomnia, 28% had sleep apnea, and some patients were also diagnosed with a mild form of sleep-disordered breathing known as respiratory effort-related arousals.53

When considering the relationship between pain, sleep quality and the psycho-emotional state, it is important to acknowledge the role of the pituitary hormones pathway. The daily rhythm of cortisol secretion is relatively stable and primarily under the influence of the circadian clock. Moreover, the activity of the hypothalamic–pituitary–adrenal (HPA) axis is modulated by many different factors, of which sleep has a modest but significant impact. Sleep onset has an inhibitory effect on cortisol secretion, while awakenings and sleep offset are associated with cortisol stimulation. During waking, a correlation between cortisol secretory bursts and indices of central arousal has also been detected. A lack of sleep and/or a reduction in sleep quality results in a slight activation of the axis, while sudden changes in sleep duration cause a profound disrup­tion of the circadian rhythm of cortisol.54 The HPA axis is also vital for stress adaptation, with its activation causing the secretion of glucocorticoids. The HPA stress response is primarily driven by neural mechanisms and involves the release of corticotropin-releasing hormone (CRH) from hypothalamic paraventricular nucleus (PVN) neurons. The pathways that activate CRH release are stressor dependent. Reactive responses to homeostatic disruption frequently involve direct noradrenergic or peptidergic drive of PVN neurons by sensory relays, whereas anticipatory responses use oligosynaptic pathways originating in upstream limbic structures. These relationships are complex and require further study.54, 55

Many studies have been conducted on the relationship between pain and sleep disorders. The results of some of these studies are presented in this paper. However, only one of these studies used a subjective assessment of sleep quality, i.e., polysomnography. In the current study, all patients underwent a polysomnographic examination, which enabled a comparison of their reports of poorer sleep quality with the objective sleep quality parameters derived from polysomnography. An additional advantage of this study was the comparison of pain levels and sleep quality reported by patients and sleep parameters from polysomnography with the psycho-emotional state of the patients.

Limitations

The limitations of the study relate to the use of single-night video-polysomnography and the discrepancy between the sleep laboratory environment and the participant’s usual sleeping conditions. The negative impact of the new environment on sleep quality is most pronounced during the first night spent in the sleep laboratory. Another limitation of the current research was the use of questionnaires to diagnose pain and HA, with no instrument used to objectively measure pain severity. Additionally, the analysis of the examined relationships did not account for gender.

Conclusions

Orofacial pain (OFP resembling presentations of primary HA, myofascial OFP and TMJ pain) and HA are serious and very common problems. Among the difficulties reported by patients dealing with pain, sleep disturbances are frequently observed. As such, the role of sleep disorders in pain patients cannot be neglected, and the possibility of sleep disturbances, sleep apnea, sleep-related hypoxia, and insomnia in patients with OFP or HA should always be considered. However, the results of this study indicate that the poor sleep quality reported by a patient may not be related to sleep disorders as determined by polysomnographic examination. Indeed, long-term pain is frequently associated with the co-occurrence of disorders of the patient’s psycho-emotional state, including anxiety, depression and increased stress levels. Therefore, the psycho-emotional state of a patient suffering from pain may be the underlying cause of the subjective deterioration in sleep quality. Consequently, patients with long-lasting pain should also be examined for psycho-emotional disorders and, if indicated, provided with professional care.

Self-reporting of poor sleep quality may be enhanced by the incorporation of polysomnography into the diagnostic process, which should be considered the gold standard for the diagnosis of sleep disorders. Therefore, the identification of comorbidities, a detailed study of the psycho-emotional state of the patient, and questionnaire studies on sleep quality are essential for selecting the most effective management strategy for patients with OFP or HA. The current study found that the presence and intensity of patient-reported OFP and HA reduced sleep quality subjectively, but not objectively. Furthermore, these rela­tionships were impacted by the presence of psycho-emotional disorders. However, the lack of comprehensive data on the mechanisms involved in the interactions between OFP and sleep warrants further research.

Ethics approval and consent to participate

The study protocol was approved by the Ethical Committee of Wroclaw Medical University (approval No. KB-794/2019). All study participants were informed of the purpose of the study and consented to participate. The study was conducted in accordance with the Declaration of Helsinki for research involving human subjects.

Data availability

The data that supports the findings of this study is available from the corresponding author on reasonable request. The data is not publicly available due to privacy or ethical restrictions.

Consent for publication

Not applicable.

Tables


Table 1. Questionnaire results on pain severity, impact of pain on daily activities, perceived disability due to pain, sleep quality, insomnia, and daytime sleepiness reported by the participants

Questionnaire

Result

Subjects
n (%)

GCPS

Grade 0

20 (17.54)

Grade I

64 (56.14)

Grade IIa

2 (1.76)

Grade IIb

15 (13.16)

Grade III

11 (9.64)

Grade IV

2 (1.76)

HIT-6

no or little impact

48 (44.44)

slight impact

14 (12.96)

significant impact

11 (10.19)

severe impact

35 (32.41)

MIDAS

Grade I

52 (52.00)

Grade II

10 (10.00)

Grade III

15 (15.00)

Grade IV

23 (23.00)

SF-MPQ

≤5

74 (64.91)

>5

40 (35.09)

TMD pain screener

≤3

47 (53.41)

>3

41 (46.59)

PSQI

≤5

36 (33.03)

>5

73 (66.97)

ISI

normal

29 (32.59)

subthreshold insomnia

33 (37.07)

significant moderate insomnia

21 (23.60)

severe insomnia

6 (6.74)

ESS

normal

61 (69.31)

mild daytime sleepiness

18 (20.46)

average daytime sleepiness

7 (7.96)

GCPS – Graded Chronic Pain Scale; HIT-6 – Headache Impact Test-6; MIDAS – Migraine Disability Assessment; SF-MPQ – short-form McGill Pain Questionnaire; TMD – temporomandibular disorders; PSQI – Pittsburgh Sleep Quality Index; ISI – Insomnia Severity Index; ESS – Epworth Sleepiness Scale.
Table 2. Presence of subjective sleep disturbances based on the increase in pain reported by the participants

Pair of variables

n

Kendall’s Tau

Z

p-value

GCPS & PSQI global score

110

0.159381

2.468092

0.014*

GCPS & ISI

87

0.204041

2.798379

0.005*

GCPS & ESS

87

−0.007137

−0.097879

0.922

HIT-6 & PSQI global score

108

0.197245

3.025658

0.002*

HIT-6 & ISI

88

0.343241

4.735509

<0.001*

HIT-6 & ESS

85

0.254950

3.454555

0.001*

MIDAS & PSQI global score

101

0.248177

3.677424

<0.001*

MIDAS & ISI

82

0.410572

5.460118

<0.001*

MIDAS & ESS

81

0.164313

2.171236

0.030*

SF-MPQ & PSQI global score

114

0.290926

4.588840

<0.001*

SF-MPQ & ISI

89

0.359480

4.988756

<0.001*

SF-MPQ & ESS

88

0.138921

1.916616

0.055

TMD pain screener & PSQI global score

88

0.228828

3.157022

0.002*

TMD pain screener & ISI

66

0.272170

3.230833

0.001*

TMD pain screener & ESS

87

0.042816

0.587212

0.557

* statistically significant (p < 0.05, Kendall’s Tau correlation).
Table 3. Results of polysomnographic examination

Parameter

M

Me

Minimum

Maximum

Lower quartile

Upper quartile

Quartile deviation

SD

TST

434.0883

449.0000

145.4000

530.5000

399.5000

481.2000

81.70000

68.62323

WASO

43.6350

29.5000

0.5000

171.0000

17.5000

57.0000

39.50000

38.13132

SL

19.0922

14.9000

0.3000

68.1000

6.6000

25.4000

18.80000

16.06708

SE

86.2447

88.1000

59.1000

97.9000

80.6000

93.4000

12.80000

8.75870

TST – total sleep time; WASO – wake after sleep onset; SL – sleep latency; SE – sleep efficiency; M – mean; Me – median; SD – standard deviation.
Table 4. Relationship between pain complaints reported in questionnaire studies and selected parameters of sleep quality assessed in polysomnography

Pair of variables

n

Kendall’s Tau

Z

p-value

TMD pain screener & TST

80

−0.019701485

−0.25865555

0.796

TMD pain screener & WASO

80

−0.1873126

−2.45917716

0.014*

TMD pain screener & SL

80

0.0706424102

0.927445358

0.354

TMD pain screener & SE

80

0.0693498556

0.910475753

0.363

HIT-6 & TST

98

0.0455309984

0.664223607

0.507

HIT-6 & WASO

98

−0.102724483

−1.49858402

0.134

HIT-6 & SL

98

−0.035229518

−0.51394168

0.607

HIT-6 & SE

98

0.0281436189

0.41056987

0.681

MIDAS & TST

92

0.114810466

1.62095682

0.105

MIDAS & WASO

92

−0.094433626

−1.33326548

0.182

MIDAS & SL

92

0.0688945252

0.972690504

0.331

MIDAS & SE

92

0.0321546277

0.453976581

0.650

GCPS & TST

100

0.0637825268

0.940261478

0.347

GCPS & WASO

100

−0.060060854

−0.88539778

0.376

GCPS & SL

100

0.052715005

0.777107635

0.437

GCPS & SE

100

−0.016318200

−0.24055766

0.810

* statistically significant (p < 0.05, Kendall’s Tau correlation).
Table 5. Comparison of sleep latency and sleep efficiency in questionnaire studies and polysomnographic examination

Pair of variables

n

Kendall’s Tau

Z

p-value

TMD pain screener & SL

80

0.070642

0.927445

0.354

TMD pain screener & SE

80

0.069349

0.910475

0.363

TMD pain screener & PSQI SL

85

0.183346

2.48432

0.013*

TMD pain screener & PSQI habitual SE

85

0.164382

2.22736

0.026*

HIT-6 & SL

98

−0.035229

−0.51394

0.607

HIT-6 & SE

98

0.0281436

0.410569

0.681

HIT-6 & PSQI SL

107

0.053866

0.82232

0.411

HIT-6 & PSQI habitual SE

107

0.173293

2.64551

0.008*

MIDAS & SL

92

0.068894

0.97269

0.331

MIDAS & SE

92

0.032154

0.45397

0.650

MIDAS & PSQI SL

100

0.166755

2.45825

0.014*

MIDAS & PSQI habitual SE

100

0.211255

3.11425

0.002*

GCPS & SL

100

0.052715

0.77710

0.437

GCPS & SE

100

−0.016318

−0.24055

0.810

GCPS & PSQI SL

107

0.019255

0.29394

0.769

GCPS & PSQI habitual SE

107

0.109976

1.67891

0.093

* statistically significant (p < 0.05, Kendall’s Tau correlation).
Table 6. Comparison of sleep quality parameters derived from polysomnography with those obtained in questionnaire studies

Pair of variables

n

Kendall’s Tau

Z

p-value

TST & ISI

81

0.091348

1.20708

0.227

TST & ESS

81

0.074740

0.98762

0.323

TST & PSQI global score

103

0.101410

1.51797

0.129

WASO & ISI

81

0.021504

0.28415

0.776

WASO & ESS

81

−0.110765

−1.46365

0.143

WASO & PSQI global score

103

0.008127

0.12165

0.903

SL & ISI

81

0.104323

1.37853

0.168

SL & ESS

81

−0.068686

−0.90762

0.364

SL & PSQI global score

103

0.0257558

0.38553

0.700

SE & ISI

81

−0.039522

−0.5222

0.601

SE & ESS

81

0.1059903

1.40056

0.161

SE & PSQI global score

103

−0.052512

−0.7860

0.432

GCPS & SL

100

0.052715

0.77710

0.437

GCPS & SE

100

−0.016318

−0.24055

0.810

GCPS & PSQI SL

107

0.019255

0.29394

0.769

GCPS & PSQI habitual SE

107

0.109976

1.67891

0.093

* statistically significant (p < 0.05, Kendall’s Tau correlation).
Table 7. Stress, anxiety and depression levels reported by the participants

Questionnaire

Result

Subjects
n (%)

PSS-10

low level of stress

30 (27.78)

moderate level of stress

65 (60.19)

high level of stress

13 (12.04)

KPS

STEN 1–4

74 (66.67)

STEN 5–6

26 (23.42)

STEN 7–10

11 (9.91)

BDI

no depression

72 (65.45)

mild depression

22 (20.00)

moderate depression

11 (10.00)

severe depression

5 (4.55)

PHQ-9

no depression

33 (30.28)

mild depression

41 (37.61)

moderate depression

24 (22.02)

moderately severe depression

8 (7.34)

severe depression

3 (2.75)

GAD-7

minimal anxiety

55 (51.89)

mild anxiety

33 (31.13)

moderate anxiety

11 (10.38)

severe anxiety

7 (6.60)

BAI

minimal anxiety

77 (73.33)

moderate anxiety

16 (15.24)

severe anxiety

12 (11.43)

PSS-10 – Perceived Stress Scale-10; KPS – Sense of Stress Questionnaire;
BDI – Beck Depression Inventory; PHQ-9 – Patient Health Questionnaire-9; GAD-7 – Generalized Anxiety Disorder-7; BAI – Beck Anxiety Inventory.
Table 8. Relationship between the level of anxiety, depression and stress, and pain severity

Pair of variables

n

Kendall’s Tau

Z

p-value

TMD pain screener & PSS-10

85

0.271585

3.679949

<0.001*

TMD pain screener & KPS

87

0.245056

3.360890

0.001*

TMD pain screener & BDI

86

0.280451

3.823269

<0.001*

TMD pain screener & PHQ-9

86

0.327406

4.463393

<0.001*

TMD pain screener & BAI

83

0.330526

4.423432

<0.001*

TMD pain screener & GAD-7

83

0.370594

4.959670

<0.001*

GCPS & PSS-10

106

0.273809

4.159796

<0.001*

GCPS & KPS

109

0.193104

2.976261

0.003

GCPS & BDI

108

0.250197

3.837918

<0.001*

GCPS & PHQ-9

108

0.273731

4.198926

<0.001*

GCPS & BAI

104

0.302987

4.558022

<0.001*

GCPS & GAD-7

104

0.293885

4.421089

<0.001*

HIT-6 & PSS-10

108

0.226315

3.471580

0.001*

HIT-6 & KPS

107

0.300810

4.592199

<0.001*

HIT-6 & BDI

108

0.348665

5.348384

<0.001*

HIT-6 & PHQ-9

107

0.330598

5.046953

<0.001*

HIT-6 & BAI

104

0.319397

4.804873

<0.001*

HIT-6 & GAD-7

105

0.310308

4.691280

<0.001*

MIDAS & PSS-10

100

0.330638

4.874154

<0.001*

MIDAS & KPS

100

0.275152

4.056203

<0.001*

MIDAS & BDI

101

0.400234

5.930566

<0.001*

MIDAS & PHQ-9

101

0.332793

4.931234

<0.001*

MIDAS & BAI

99

0.377552

5.536881

<0.001*

MIDAS & GAD-7

99

0.328361

4.815483

<0.001*

* statistically significant (p < 0.05, Kendall’s Tau correlation).
Table 9. Relationship between the level of anxiety, depression and stress, and the subjective assessment of sleep quality

Pair of variables

n

Kendall’s Tau

Z

p-value

PSS-10 & PSQI

108

0.324845

4.982985

<0.001*

PSS-10 & ISI

88

0.394190

5.438427

<0.001*

PSS-10 & ESS

85

0.212189

2.875137

0.004*

KPS & PSQI

112

0.302435

4.727067

<0.001*

KPS & ISI

88

0.339918

4.689672

<0.001*

KPS & ESS

87

0.200043

2.743542

0.006*

BDI & PSQI

110

0.405912

6.285733

<0.001*

BDI & ISI

88

0.428127

5.906635

<0.001*

BDI & ESS

86

0.272479

3.714598

<0.001*

PHQ-9 & PSQI

109

0.437751

6.746935

<0.001*

PHQ-9 & ISI

87

0.480670

6.592274

<0.001*

PHQ-9 & ESS

86

0.341903

4.661024

<0.001*

BAI & PSQI

106

0.402993

6.122401

<0.001*

BAI & ISI

85

0.409755

5.552148

<0.001*

BAI & ESS

83

0.192642

2.578127

0.010*

GAD-7 & PSQI

106

0.355888

5.406769

<0.001*

GAD-7 & ISI

86

0.428333

5.839290

<0.001*

GAD-7 & ESS

84

0.208219

2.804021

0.005*

* statistically significant (p < 0.05, Kendall’s Tau correlation).
Table 10. Relationship between the level of anxiety, depression and stress, and the objective assessment of sleep quality in polysomnography

Pair of variables

n

Kendall’s Tau

Z

p-value

PSS-10 & TST

98

0.135076

1.97055

0.049*

PSS-10 & WASO

98

−0.108172

−1.57806

0.115

PSS-10 & SL

98

−0.034472

−0.50289

0.615

PSS-10 & SE

98

0.081371

1.18708

0.235

KPS & TST

102

0.159898

2.38142

0.017*

KPS & WASO

102

−0.147246

−2.19299

0.028*

KPS & SL

102

−0.145709

−2.17009

0.030*

KPS & SE

102

0.1446899

2.1549

0.031*

BDI & TST

100

0.074851

1.10343

0.270

BDI & WASO

100

−0.080055

−1.18014

0.238

BDI & SL

100

−0.1006566

−1.483847

0.138

BDI & SE

100

0.08106160

1.1949840

0.232

PHQ-9 & TST

99

0.072239

1.05941

0.289

PHQ-9 & WASO

99

−0.098424

−1.44341

0.149

PHQ-9 & SL

99

0.0114757

0.168293

0.866

PHQ-9 & SE

99

0.0490954

0.719996

0.472

BAI & TST

96

0.106368

1.53526

0.125

BAI & WASO

96

−0.075987

−1.09676

0.273

BAI & SL

96

0.01954793

0.282144

0.778

BAI & SE

96

0.02843335

0.410392

0.682

GAD-7 & TST

98

0.125856

1.83603

0.066

GAD-7 & WASO

98

−0.077735

−1.13403

0.257

GAD-7 & SL

98

0.078594

1.146563

0.252

GAD-7 & SE

98

0.028898

0.421578

0.673

* statistically significant (p < 0.05, Kendall’s Tau correlation).

References (55)

  1. Klasser GD, Almoznino G, Fortuna G. Sleep and orofacial pain. Dent Clin North Am. 2018;62(4):629–656. doi:10.1016/j.cden.2018.06.005
  2. Ananthan S, Benoliel R. Chronic orofacial pain. J Neural Transm (Vienna). 2020;127(4):575–588. doi:10.1007/s00702-020-02157-3
  3. Mier RW, Dhadwal S. Primary headaches. Dent Clin North Am. 2018;62(4):611–628. doi:10.1016/j.cden.2018.06.006
  4. Pigg M, Nixdorf DR, Law AS, et al. New International Classification of Orofacial Pain: What is in it for endodontists? J Endod. doi:10.1016/j.joen.2020.12.002
  5. Finan PH, Goodin BR, Smith MT. The association of sleep and pain: An update and a path forward. J Pain. 2013;14(12):1539–1552. doi:10.1016/j.jpain.2013.08.007
  6. Dopheide JA. Insomnia overview: Epidemiology, pathophysiology, diagnosis and monitoring, and nonpharmacologic therapy. Am J Manag Care. 2020;26(4 Suppl):S76–S84. doi:10.37765/ajmc.2020.42769
  7. Nijs J, Mairesse O, Neu D, et al. Sleep disturbances in chronic pain: Neurobiology, assessment, and treatment in physical therapist practice. Phys Ther. 2018;98(5):325–335. doi:10.1093/ptj/pzy020
  8. Trauer JM, Qian MY, Doyle JS, Rajaratnam SMW, Cunnington D. Cognitive behavioral therapy for chronic insomnia: A systematic review and meta-analysis. Ann Intern Med. 2015;163(3):191–204. doi:10.7326/M14-2841
  9. Haack M, Simpson N, Sethna N, Kaur S, Mullington J. Sleep deficiency and chronic pain: Potential underlying mechanisms and clinical implications. Neuropsychopharmacology. 2020;45(1):205–216. doi:10.1038/s41386-019-0439-z
  10. Wieckiewicz M, Jenca A, Seweryn P, et al. Determination of pain intensity, pain-related disability, anxiety, depression, and perceived stress in Polish adults with temporomandibular disorders: A prospective cohort study. Front Integr Neurosci. 2022;16:1026781. doi:10.3389/fnint.2022.1026781
  11. Wieckiewicz M, Grychowska N, Nahajowski M, et al. Prevalence and overlaps of headaches and pain-related temporomandibular disorders among the Polish urban population. J Oral Facial Pain Headache. 2020;34(1):31–39. doi:10.11607/ofph.2386
  12. Manfredini D, Borella L, Favero L, Ferronato G, Guarda-Nardini L. Chronic pain severity and depression/somatization levels in TMD patients. Int J Prosthodont. 2010;23(6):529–534. PMID:21209988.
  13. Manfredini D, Favero L, Del Giudice A, Masiero S, Stellini E, Guarda-Nardini L. Axis II psychosocial findings predict effectiveness of TMJ hyaluronic acid injections. Int J Oral Maxillofac Surg. 2013;42(3):364–368. doi:10.1016/j.ijom.2012.10.033
  14. Sójka A, Stelcer B, Roy M, Mojs E, Pryliński M. Is there a relationship between psychological factors and TMD? Brain Behav. 2019;9(9):e01360. doi:10.1002/brb3.1360
  15. Schiffman E, Ohrbach R, Truelove E, et al. Diagnostic Criteria for Temporomandibular Disorders (DC/TMD) for Clinical and Research Applications: Recommendations of the International RDC/TMD Consortium Network* and Orofacial Pain Special Interest Group†. J Oral Facial Pain Headache. 2014;28(1):6–27. doi:10.11607/jop.1151
  16. Dreweck FDS, Soares S, Duarte J, Conti PCR, De Luca Canto G, Porporatti AL. Association between painful temporomandibular disorders and sleep quality: A systematic review. J Oral Rehabil. 2020;47(8):1041–1051. doi:10.1111/joor.12993
  17. Almoznino G, Benoliel R, Sharav Y, Haviv Y. Sleep disorders and chronic craniofacial pain: Characteristics and management possibilities. Sleep Med Rev. 2017;33:39–50. doi:10.1016/j.smrv.2016.04.005
  18. O’Gara BP, Gao L, Marcantonio ER, Subramaniam B. Sleep, pain, and cognition: Modifiable targets for optimal perioperative brain health. Anesthesiology. 2021;135(6):1132–1152. doi:10.1097/ALN.0000000000004046
  19. Hudson AN, Van Dongen HPA, Honn KA. Sleep deprivation, vigilant attention, and brain function: A review. Neuropsychopharmacology. 2020;45(1):21–30. doi:10.1038/s41386-019-0432-6
  20. Lavigne GJ, Sessle BJ. The neurobiology of orofacial pain and sleep and their interactions. J Dent Res. 2016;95(10):1109–1116. doi:10.1177/0022034516648264
  21. Sánchez Romero EA, Martínez-Pozas O, García-González M, et al. Association between sleep disorders and sleep quality in patients with temporomandibular joint osteoarthritis: A systematic review. Biomedicines. 2022;10(9):2143. doi:10.3390/biomedicines10092143
  22. Maślak-Bereś M, Loster JE, Wieczorek A, Loster BW. Evaluation of the psychoemotional status of young adults with symptoms of temporomandibular disorders. Brain Behav. 2019;9(11):e01443. doi:10.1002/brb3.1443
  23. Melzack R. The short-form McGill Pain Questionnaire. Pain. 1987;30(2):191–197. doi:10.1016/0304-3959(87)91074-8
  24. Melzack R, Katz J. The McGill Pain Questionnaire: Appraisal and current status. In: Turk DC, Melzack R, eds. Handbook of Pain Assessment. New York, NY: The Guilford Press; 2001:35–52.
  25. Von Korff M, DeBar LL, Krebs EE, Kerns RD, Deyo RA, Keefe FJ. Graded chronic pain scale revised: Mild, bothersome, and high-impact chronic pain. Pain. 2020;161(3):651–661. doi:10.1097/j.pain.0000000000001758
  26. Sharma S, Kallen MA, Ohrbach R. Graded Chronic Pain Scale: Validation of 1-month reference frame. Clin J Pain. 2021;38(2):119–131. doi:10.1097/AJP.0000000000001005
  27. Yang M, Rendas-Baum R, Varon SF, Kosinski M. Validation of the Headache Impact Test (HIT-6™) across episodic and chronic migraine. Cephalalgia. 2011;31(3):357–367. doi:10.1177/0333102410379890
  28. Stewart WF, Lipton RB, Kolodner KB, Sawyer J, Lee C, Liberman JN. Validity of the Migraine Disability Assessment (MIDAS) score in comparison to a diary-based measure in a population sample of migraine sufferers. Pain. 2000;88(1):41–52. doi:10.1016/S0304-3959(00)00305-5
  29. Gonzalez YM, Schiffman E, Gordon SM, et al. Development of a brief and effective temporomandibular disorder pain screening questionnaire: Reliability and validity. J Am Dent Assoc. 2011;142(10):1183–1191. doi:10.14219/jada.archive.2011.0088
  30. Bastien CH, Vallières A, Morin CM. Validation of the Insomnia Severity Index as an outcome measure for insomnia research. Sleep Med. 2001;2(4):297–307. doi:10.1016/s1389-9457(00)00065-4
  31. Manzar MD, BaHammam AS, Hameed UA, et al. Dimensionality of the Pittsburgh Sleep Quality Index: A systematic review. Health Qual Life Outcomes. 2018;16(1):89. doi:10.1186/s12955-018-0915-x
  32. Silva GE, Vana KD, Goodwin JL, Sherrill DL, Quan SF. Identification of patients with sleep disordered breathing: Comparing the four-variable screening tool, STOP, STOP-Bang, and Epworth Sleepiness Scales. J Clin Sleep Med. 2011;7(5):467–472. doi:10.5664/jcsm.1308
  33. Plopa M, Makarowski R. Kwestionariusz Poczucia Stresu. 1st ed. Warszawa, Poland: VIZJA PRESS & IT; 2010.
  34. Bastianon CD, Klein EM, Tibubos AN, Brähler E, Beutel ME, Petrowski K. Perceived Stress Scale (PSS-10) psychometric properties in migrants and native Germans. BMC Psychiatry. 2020;20(1):450. doi:10.1186/s12888-020-02851-2
  35. Spitzer RL, Kroenke K, Williams JB. Validation and utility of a self-report version of PRIME-MD: The PHQ primary care study. Primary Care Evaluation of Mental Disorders. Patient Health Questionnaire. JAMA. 1999;282(18):1737–1744. doi:10.1001/jama.282.18.1737
  36. Richter P, Werner J, Heerlein A, Kraus A, Sauer H. On the validity of the Beck Depression Inventory. A review. Psychopathology. 1998;31(3):160–168. doi:10.1159/000066239
  37. Beck AT, Ward CH, Mendelson M, Mock J, Erbaugh J. An inventory for measuring depression. Arch Gen Psychiatry. 1961;4:561–571. doi:10.1001/archpsyc.1961.01710120031004
  38. Przepiorka A, Blachnio A, Cudo A. The role of depression, personality, and future time perspective in internet addiction in adolescents and emerging adults. Psychiatry Res. 2019;272:340–348. doi:10.1016/j.psychres.2018.12.086
  39. Williams N. The GAD-7 questionnaire. Occup Med. 2014;64(3):224. doi:10.1093/occmed/kqt161
  40. Lei J, Fu J, Yap AUJ, Fu KY. Temporomandibular disorders symptoms in Asian adolescents and their association with sleep quality and psychological distress. Cranio. 2016;34(4):242–249. doi:10.1179/2151090315y.0000000021
  41. Florjański W, Orzeszek S. Role of mental state in temporomandibular disorders: A review of the literature. Dent Med Probl. 2021;58(1):127–133. doi:10.17219/dmp/132978
  42. Ekici Ö. Association of stress, anxiety, and depression levels with sleep quality in patients with temporomandibular disorders. Cranio. 2023;41(5):407–415. doi:10.1080/08869634.2020.1861886
  43. Yap AU, Cao Y, Zhang MJ, Lei J, Fu KY. Temporomandibular disorder severity and diagnostic groups: Their associations with sleep quality and impairments. Sleep Med. 2021;80:218–225. doi:10.1080/08869634.2019.1682750
  44. Kim HK, Kim ME. Phenotyping 1488 patients with painful temporomandibular disorders and its relevance to subjective sleep quality: A key step for stratified medicine. Cranio. 2019;39(6):491–501. doi:10.1080/08869634.2019.1682750
  45. Jiménez-Silva A, Peña-Durán C, Tobar-Reyes J, Frugone-Zambra R. Sleep and awake bruxism in adults and its relationship with temporomandibular disorders: A systematic review from 2003 to 2014. Acta Odontol Scand. 2017;75(1):36–58. doi:10.1080/00016357.2016.1247465
  46. Bastos Machado de Resende CM, de Oliveira Medeiros FGL, de Figueiredo Rêgo CR, de Sousa Leite Bispo A, Seabra Barbosa GA, Oliveira de Almeida E. Short-term effectiveness of conservative therapies in pain, quality of life, and sleep in patients with temporomandibular disorders: A randomized clinical trial. Cranio. 2021;39(4):335–343. doi:10.1080/08869634.2019.1627068
  47. Yatani H, Studts J, Cordova M, Carlson CR, Okeson JP. Comparison of sleep quality and clinical and psychologic characteristics in patients with temporomandibular disorders. J Orofac Pain. 2002;16(3):221–228. PMID:12221738.
  48. Kundermann B, Hemmeter-Spernal J, Huber MT, Krieg JC, Lautenbacher S. Effects of total sleep deprivation in major depression: Overnight improvement of mood is accompanied by increased pain sensitivity and augmented pain complaints. Psychosom Med. 2008;70(1):92–101. doi:10.1097/PSY.0b013e31815c1b5d
  49. Edwards RR, Almeida DM, Klick B, Haythornthwaite JA, Smith MT. Duration of sleep contributes to next-day pain report in the general population. Pain. 2008;137(1):202–207. doi:10.1016/j.pain.2008.01.025
  50. Agmon M, Armon G. Increased insomnia symptoms predict the onset of back pain among employed adults. PLoS One. 2014;9(8):e103591. doi:10.1371/journal.pone.0103591
  51. Sivertsen B, Lallukka T, Petrie KJ, Steingrímsdóttir ÓA, Stubhaug A, Nielsen CS. Sleep and pain sensitivity in adults. Pain. 2015;156(8):1433–1439. doi:10.1097/j.pain.0000000000000131
  52. Dubrovsky B, Janal MN, Lavigne GJ, et al. Depressive symptoms account for differences between self-reported versus polysomnographic assessment of sleep quality in women with myofascial TMD. J Oral Rehabil. 2017;44(12):925–933. doi:10.1111/joor.12552
  53. Smith MT, Wickwire EM, Grace EG, et al. Sleep disorders and their association with laboratory pain sensitivity in temporomandibular joint disorder. Sleep. 2009;32(6):779–790. doi:10.1093/sleep/32.6.779
  54. Balbo M, Leproult R, Van Cauter E. Impact of sleep and its disturbances on hypothalamo-pituitary-adrenal axis activity. Int J Endocrinol. 2010:2010:759234. doi:10.1155/2010/759234
  55. Herman JP, McKlveen JM, Ghosal S, et al. Regulation of the hypothalamic-pituitary-adrenocortical stress response. Compr Physiol. 2016;6(2):603–621. doi:10.1002/cphy.c150015