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Keywords:

  • neuroticism;
  • perfectionism;
  • polysomnography;
  • primary insomnia;
  • punctuality

Summary

  1. Top of page
  2. Summary
  3. Introduction
  4. Methods
  5. Results
  6. Discussion
  7. Declarations of Interest
  8. References

Primary insomnia is a prevalent sleep disorder affecting approximately 3% of the general population. Studies suggest that personality traits such as perfectionism and neuroticism might be implicated in the aetiology of the disorder. However, to date, no study has investigated behavioural indicators of these factors in a hypothesis-driven manner. In the present study, we assessed punctuality as a behavioural indicator of perfectionism and neuroticism in 635 consecutive clinical patients of the sleep laboratory of the Department of Psychiatry and Psychotherapy, University of Freiburg Medical Center. The primary aim was to compare primary insomnia patients (= 148) with another group of patients with other sleep-related diagnoses (= 487). Primary insomnia patients arrived on average 4 min earlier when compared to other patients (= 0.041). However, this effect failed to reach statistical significance when correcting for the influence of potential confounding variables. Of note, we found a strong relationship between polysomnographic sleep parameters and punctuality. That is, short sleep duration was associated significantly with early arrival times at the sleep laboratory (= 0.023). These findings support the proposal that personality traits, which we predict underlie obsessive punctuality, may be involved in the aetiology of objectively defined sleep disturbances. Clinical implications of the current results for cognitive behavioural treatments of insomnia are discussed.


Introduction

  1. Top of page
  2. Summary
  3. Introduction
  4. Methods
  5. Results
  6. Discussion
  7. Declarations of Interest
  8. References

Chronic insomnia is defined by persistent difficulties initiating or maintaining sleep or non-restorative sleep accompanied by significant daytime impairments (Edinger et al., 2004). It affects about 10% of the general population and commonly occurs as a comorbid condition in other medical or mental disorders. Primary insomnia (PI), an exclusionary diagnosis of poor sleep, ruling out psychiatric, medical, substance and additional sleep-related pathology, is estimated to affect up to 3% of the general population (Ohayon, 2002).

Current aetiological models of insomnia highlight the role of cognitive, emotional and physiological hyperarousal (Espie et al., 2006; Harvey, 2002; Perlis et al., 1997; Riemann et al., 2010). Consistent with this hyperarousal perspective, personality factors are also assumed to be involved in the development and maintenance of insomnia (Van de Laar et al., 2010). More specifically, questionnaire studies have revealed increased levels of perfectionism (Azevedo et al., 2010; Jansson-Fröjmark and Linton, 2007; Lundh et al., 1994; Vincent and Walker, 2000) and neuroticism (Dorsey and Bootzin, 1997; Freedman and Sattler, 1982; LeBlanc et al., 2007) in insomnia patients, compared with normal-sleeping controls. However, to date, no study has investigated putative behavioural indicators of these personality factors in a hypothesis-driven manner. In insomnia patients, only a few possible and plausible behavioural indicators of perfectionism and/or neuroticism exist. First, insomnia patients sometimes perform better than controls in cognitive tasks (Shekleton et al., 2010), which might be due to increased cognitive effort, possibly reflecting greater degrees of perfectionistic tendencies (see, e.g. Schmidt et al., 2010). Secondly, clinical interaction with insomnia patients, although admittedly not subject to scientific scrutiny and rigour, often reveals characteristics that might relate to the concept of perfectionism, such as high levels of motivation, organization, obsessiveness and self-discipline.

Another possible behavioural indicator of perfectionism and/or neuroticism is punctuality—the ability to be on time—which is central to our everyday work and social lives. Punctuality can also be relatively easy to measure. Despite the important role of situational factors in moderating punctuality, previous studies have demonstrated clearly that the time when people arrive at a specific meeting is related to personality factors (Back et al., 2006; Richard and Slane, 1990). More specifically, Back et al. (2006) reported that neuroticism, conscientiousness and agreeableness are related to earlier arrival times. Of particular relevance, neuroticism has been shown to be consistently elevated in insomnia (Van de Laar et al., 2010) as well as in other clinical psychiatric conditions (Kendler and Myers, 2010; Kubicka et al., 2001).

The current study aimed at investigating punctuality, indexed by the difference between arrival time and specified clinical appointment time, in patients of the sleep laboratory at the Department of Psychiatry and Psychotherapy, University of Freiburg Medical Center. The main purpose was to compare insomnia patients and patients with other sleep-related diagnoses. By so doing, this is the first investigation that used a putative behavioural indicator of perfectionism and neuroticism for investigating insomnia patients. It must be stressed that this study reflects a retrospective, hypothesis-driven analysis of patient data collected over a 4-year period. Our main hypothesis was that insomnia patients would arrive earlier to diagnostic appointments than patients suffering from other sleep-disordered conditions.

Methods

  1. Top of page
  2. Summary
  3. Introduction
  4. Methods
  5. Results
  6. Discussion
  7. Declarations of Interest
  8. References

Participants

In the current study, data of 728 consecutive in-patients of the sleep laboratory at the Department of Psychiatry and Psychotherapy, University of Freiburg Medical Center, that were investigated between 2007 and 2010, were analysed retrospectively. Punctuality data are only available from 2007 onwards because of a change in clinical data assessment. Patients were referred to the psychiatric/neurological sleep laboratory by their primary care provider or by a medical specialist. All subjects gave their informed written consent prior to inclusion in the study. The study protocol was approved by the local ethics committee of the University of Freiburg Medical Center.

Twenty-one patients below the age of 18 years were excluded, because children and adolescents were typically brought by their parents to the sleep laboratory, resulting in a strong influence of the parent’s own level of punctuality on actual arrival time. Additionally, 72 patients were excluded because they were either >60 min too early or >60 min too late. The rationale behind this was the assumption that large differences between scheduled and actual arrival times were very likely to be caused by incidents or by misunderstandings about the scheduled arrival time. The described procedure resulted in a final sample size of 635 patients (367 women, 268 men; age 46.0 ± 15.0 years).

Among these, 148 patients (103 women, 45 men; age 46.8 ± 13.1 years) met the diagnostic criteria for PI according to DSM-IV-TR (American Psychiatric Association, 2000). Exclusion criteria for this group included the presence of any other sleep disorder, clinically relevant medical or neurological disorders, a positive urine drug screen and any history of psychiatric disorder or serious medical illness in the past. The diagnostic procedure consisted of a standard physical and psychiatric examination conducted by a physician of our sleep laboratory, electrocardiogram (ECG), electroencephalogram (EEG) and routine laboratory investigations (blood cell count, liver, renal and thyroid function).

The diagnoses of the 487 other patients (264 women, 223 men; age 45.7 ± 15.6 years) included other sleep-related disorders (sleep-related breathing disorders, sleep-related movement disorders, parasomnias, circadian rhythm disorders and other hypersomnias) and sleep disorders secondary to medical or psychiatric disorders (mainly affective disorders, substance-related disorders and schizophrenia).

Polysomnography and questionnaires

All participants were scheduled for at least two consecutive nights of polysomnography (PSG) sleep monitoring. A standard laboratory procedure and PSG montage, which have been described in detail elsewhere (e.g. Spiegelhalder et al., 2010), were followed on both nights. Sleep was recorded for 8 h from ‘lights out’ (22:00–23:00 hour) until ‘lights on’ (06:00–07:00 hour), and was scored visually by experienced raters according to the criteria of Rechtschaffen and Kales (1968).

Subjective estimates of total sleep time (TST), sleep onset latency (SOL) and sleep quality were assessed with the ‘Schlaffragebogen A’ (SF-A; Görtelmeyer, 1981). This questionnaire was administered in the morning after each PSG night and captures subjective aspects of sleep in the preceding night. Subjective sleep efficiency was calculated using SF-A wake times and PSG-documented bedtimes, as SF-A records the beginning but not the end of bedtime. Additionally, participants were asked to complete the Pittsburgh Sleep Quality Index (PSQI; Buysse et al., 1989) and Epworth Sleepiness Scale (ESS; Johns, 1991) for assessing general sleep quality and daytime sleepiness.

Analysis

Arrival times were recorded when patients registered for the sleep laboratory examination at the administration desk of the psychiatric clinic. Of note, by this point patients were familiar with the clinic/route to the clinic as they had previously completed an intake interview in the outpatient facility, scheduled approximately 2–8 weeks prior to the overnight stay. Differences between actual and scheduled arrival times were used to index punctuality with positive scores, indicating an arrival after the scheduled time, and negative scores, indicating an arrival prior to the scheduled time. The distance between patients’ homes and the sleep laboratory was calculated using geographical coordinates of German postal codes as obtained by the open geo-coordinates database (http://opengeodb.de).

Descriptive presentation of the data includes mean values and standard deviations. Linear regression analyses and two-sample t-tests were used for investigating the impact of age, gender, distance from the sleep laboratory, years of education, scheduled arrival time and primary insomnia diagnosis on the punctuality index. The association between objective and subjective sleep parameters and punctuality was analysed using multiple linear regression analyses, where age and gender were used as covariates. The level of significance was set at < 0.05 (two-tailed) for all analyses. Varying degrees of freedom reflect missing values.

Results

  1. Top of page
  2. Summary
  3. Introduction
  4. Methods
  5. Results
  6. Discussion
  7. Declarations of Interest
  8. References

Sample characteristics and punctuality

The mean scheduled arrival time was 11:01 hour ± 75 min and the mean actual arrival time was 10:59 hour ± 75 min, resulting in a mean value of the punctuality index of −1.7 ± 22.4 min. Age was associated significantly with the punctuality index (t(633) = −2.17, = 0.031), with older patients arriving earlier than younger ones. Although women (−3.1 ± 21.2 min) arrived earlier than men (0.2 ± 23.8 min), on average, this difference narrowly failed to reach statistical significance (t(633) = 1.80, = 0.071). Years of education was also related significantly to punctuality (t(553) = 3.58, < 0.001), with higher-educated individuals being later than lower-educated ones. Furthermore, the punctuality index was correlated with the scheduled arrival time (t(633) = −3.36, < 0.001), with patients scheduled earlier in the day arriving later than patients whose appointment was scheduled later. The distance of the patients’ home from the sleep laboratory was also correlated with punctuality (t(621) = −3.11, = 0.002), indicating that patients with a longer distance to travel arrived earlier at the sleep laboratory relative to patients who lived closer to the sleep laboratory.

Primary insomnia and punctuality

Groups (PI versus other diagnoses) did not differ significantly in age (t(633) = 0.83, = 0.41), years of education (t(553) = 1.19, = 0.24), scheduled arrival time (t(633) = 0.25, = 0.81) or distance from home (t(621) = 1.27, = 0.21). However, gender was different (χ2(1,633) = 10.51, = 0.001), with the PI group having a higher percentage of females than the group of other sleep-related diagnoses (70% versus 54%).

Primary insomnia patients had a mean punctuality index of −4.9 ± 19.8 min, while patients with other diagnoses had a mean punctuality index of −0.9 ± 23.0 min. The group comparison revealed that insomnia patients arrived significantly earlier than patients with other diagnoses (t(633) = −2.06, = 0.041). When controlling for age, gender, years of education, scheduled arrival times and distance from home in a multiple linear regression analysis, the PI diagnosis did not have a significant impact on punctuality (t(546) = −0.918, = 0.36). The majority of patients with other diagnoses than primary insomnia had a combination of different comorbid psychiatric and/or sleep-related disorders (= 355, punctuality index: −1.3 ± 23.6 min). The other groups included patients with depression and insomnia (= 61, punctuality index: −1.1 ± 23.4), non-rapid eye movement (NREM) parasomnias (= 24, punctuality index: 2.0 ± 21.1), narcolepsy (= 14, punctuality index: 9.1 ± 20.3), restless leg syndrome (RLS)/periodic limb movement disorder (PLMD) (= 13, punctuality index: −1.4 ± 19.2), idiopathic hypersomnia (= 12, punctuality index: −5.4 ± 16.2), and patients with sleep apnoea disorder (= 8, punctuality index: 0.6 ± 23.3).

PSG-determined sleep and punctuality

The results of the linear regression analyses with PSG-defined sleep parameters as independent variables, and punctuality index as the dependent variable are presented in Table 1. Age, gender, years of education, scheduled arrival times and distance from home were controlled for statistically in these analyses. While the first night served for adaptation to the laboratory setting, punctuality was related significantly to PSG-determined sleep parameters of the second night. More specifically, being early was associated with shorter total sleep time (TST), lower sleep efficiency, more wake time after sleep onset, a higher percentage of wake time and a lower percentage of Stage 2 sleep. The association between poor sleep and early arrival is exemplified in Fig. 1. The analyses of the first night revealed no statistically significant results.

Table 1.   Means and standard deviations of polysomnography (PSG) parameters for the full sample of patients. Additionally, the results of linear regression analyses are presented in which PSG parameters were used as independent variables and punctuality index as the dependent variable. In these analyses, age, gender, years of education, scheduled arrival times and distance from home were statistically controlled
 First nightSecond nightFirst nightSecond night
tPtP
  1. PLMS: periodic leg movements during sleep; REM: rapid eye movement; SOL: sleep onset latency; SPT: sleep period time; WASO: wake after sleep onset.

Total sleep time (min)352.4 ± 73.2378.0 ± 65.20.300.7632.270.023
Sleep efficiency (%)73.4 ± 15.278.6 ± 13.30.280.7812.360.019
WASO (min)89.1 ± 56.871.7 ± 52.10.130.894−2.070.039
SOL (min)29.7 ± 30.222.9 ± 21.8−1.460.144−1.670.095
Arousal index (h−1)20.8 ± 10.518.3 ± 9.4−1.110.2670.050.964
WAKE % SPT20.5 ± 13.616.2 ± 12.2−0.170.869−2.420.016
S1% SPT12.0 ± 7.110.6 ± 5.9−1.220.222−0.490.624
S2% SPT47.4 ± 12.350.0 ± 11.50.670.5052.700.007
SWS % SPT4.9 ± 6.75.2 ± 6.9−0.810.4150.110.915
REM % SPT14.4 ± 6.017.2 ± 6.0−0.320.7530.230.816
Sleep apnoea index (h−1)2.0 ± 5.80.950.344
PLMS arousal index (h−1)2.2 ± 5.10.970.333
image

Figure 1.  Means and standard errors of the punctuality index for quartiles of second night total sleep time (TST) as determined by polysomnography (PSG) (1. quartile: TST < 346.5 min; 2. quartile: 346.5 min ≤ TST < 393.0 min; 3. quartile: 393.0 min ≤ TST < 423.0 min; 4. quartile: 423.0 min ≤ TST).

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Subjectively determined sleep and punctuality

The results of the linear regression analyses with subjective sleep parameters as independent variables and the punctuality index as dependent variable are presented in Table 2. Again, age, gender, years of education, scheduled arrival times and distance from home were controlled statistically. The only result that reached statistical significance was the association between subjective SOL in the second night and the punctuality index indicating that individuals who arrive early estimate their SOL as longer in the second night.

Table 2.   Means and standard deviations of subjective sleep-related data for the full sample of patients. Again, the results of linear regression analyses are presented with subjective sleep parameters as independent variables and punctuality index as the dependent variable. Age, gender, years of education, scheduled arrival times and distance from home were controlled in these analyses
 First nightSecond nightFirst nightSecond night
tPtP
  1. ESS: Epworth Sleepiness Scale; PSQI: Pittsburgh Sleep Quality Index; SOL: sleep onset latency.

Total sleep time (min)390.5 ± 83.2400.8 ± 81.51.840.0670.810.416
Sleep efficiency (%)83.9 ± 14.786.1 ± 13.61.430.1530.720.472
SOL (min)25.0 ± 20.221.4 ± 18.4−1.930.054−2.700.007
Sleep quality2.5 ± 0.82.8 ± 0.81.410.1591.300.193
PSQI10.2 ± 4.3−0.470.641
ESS8.9 ± 5.70.580.565

Discussion

  1. Top of page
  2. Summary
  3. Introduction
  4. Methods
  5. Results
  6. Discussion
  7. Declarations of Interest
  8. References

In the present study we investigated the relationship between sleep disturbances and punctuality. PI patients arrived earlier when compared to patients with other sleep-related diagnoses. However, this effect did not reach statistical significance when correcting for potential confounding variables. We found a strong relationship between PSG-determined sleep parameters [i.e. short sleep duration, decreased sleep efficiency and Stage 2 percentage and increased wake after sleep onset (WASO)] and enhanced punctuality. However, PSG parameters of the first night were not related to punctuality, which may reflect unstable effects on sleep quality due to ‘first night’ and ‘reverse first night’ effects (Hauri and Olmstead, 1989; Toussaint et al., 1995).

Both the finding in PI patients and the association between objectively determined sleep disturbances and earlier arrival times might be explained by current theories about the involvement of personality factors in the development and maintenance of insomnia. That is, perfectionism and neuroticism may be important factors for both sleep disturbances and punctuality. Concerning this, it can be speculated that these personality traits are associated with cognitive processes known to interfere with the ability to obtain restorative sleep, for example sleep effort (Espie et al., 2006), or monitoring for internal and external sleep-related cues (Harvey, 2002). Of note, the current study is the first to employ a behavioural indicator of perfectionism and neuroticism in a hypothesis-driven way.

An alternative, although speculative, explanation for the current findings is that sleeping less may make individuals vigilant to possible sleep-related daytime impairment (regardless of the underlying sleep disorder pathology), prompting them to try to ‘compensate’ for, or off-set, potential negative daytime consequences. Given the situational context of seeking help in a clinical setting, this might result in an over-compensation for perceived difficulties (i.e. ability to plan for the journey and be prepared for the clinician–patient interaction) and, thus, lead to early arrival times. One further explanation is that the significant results of our study are driven mainly by daytime sleepiness in patients with hypersomnias, possibly leading to being late for appointments. However, daytime sleepiness, at least measured by the ESS, was not related significantly to our punctuality index.

The notable differences between objective and subjective sleep parameters and their relationship to the punctuality index in the current study are surprising. However, from a methodological viewpoint, it is important to note that the strongest correlations were found between objectively measured behaviours, namely polysomnographically determined sleep parameters and punctuality. In comparison, retrospective subjective ratings might be influenced more strongly by random or systematic errors.

Several limitations of the current study need to be addressed. First, the study design does not permit investigations of causality; therefore, conclusions about the significance of the results for understanding the pathology of insomnia have to be drawn cautiously. Secondly, our ‘punctuality index’ is not determined only by patients’ personality, but is likely to be impacted by a variety of situational factors that were not assessed systematically in the current study. Thirdly, our study sample is a very heterogeneous group, including patients with different diagnoses, different medication and large ranges for age and duration of sleep disorders. While also increasing error variance this leads, however, to a higher ecological validity of the results. Furthermore, measures of self-report personality including neuroticism, perfectionism and conscientiousness were not assessed in the current study and should be included in future investigations. This would also allow for more sophisticated analyses of the relationship between personality traits, corresponding behaviours and sleep parameters, perhaps using structural equation modelling, to better appreciate the nature of causal pathways. Assessing these data in a longitudinal design would also increase our knowledge about the stability of the observed behaviour. That said, previous data support the assumption that trait-like self-report punctuality maps onto objective state measures of punctuality (Richard and Slane, 1990). The exclusion of participants being either >60 min too early or >60 min too late was based only on our clinical impression that these cases were caused by incidents or misunderstandings. Future prospective investigations should directly assess subjective reasons for being too early or too late. Finally, a healthy control group was not investigated in the current study. Concerning this, it has to be borne in mind that healthy controls would be in a completely different situation when arriving at the sleep laboratory (e.g. for study purposes), and that seeking help for a problem probably exerts a stronger influence on punctuality, although this awaits empirical confirmation.

Despite these limitations, the current investigation revealed an association between sleep disturbances and punctuality, which might be an expression of enhanced personality traits such as perfectionism or neuroticism, although this awaits further investigations incorporating questionnaire measures of these stable traits. Perfectionism has not only been found in insomnia patients. It is a construct that is probably related to different psychopathological conditions such as eating disorders, anxiety disorders and depression (Egan et al., 2011; Shafran and Mansell, 2001). Accordingly, cognitive–behavioural treatment programmes for perfectionism have been developed which lead to significant improvements in measures of psychopathology (Riley et al., 2007; Steele and Wade, 2008). Therefore, it seems to be worthwhile to study the impact of perfectionism treatment programmes on sleep disturbances which might extend the current cognitive behavioural treatments of insomnia (CBT-I; National Institutes of Health, 2005). Furthermore, perfectionism and neuroticism might have a differing impact on current CBT-I components. It can be speculated that perfectionistic traits may help some patients adhere to sleep restriction therapy, through rigorous implementation of prescribed bed- and rising times, 7 days a week. Conversely, perfectionism may impair the efficacy of stimulus control therapy because patients may implement the ‘quarter-of-an-hour rule’ in a very literal manner (i.e. ‘it has to be exactly 15 min’), leading to clock monitoring and arousal, and perhaps ultimately delayed sleep-initiation and re-initiation. Such interesting hypotheses would benefit from rigorous assessment in future research.

Declarations of Interest

  1. Top of page
  2. Summary
  3. Introduction
  4. Methods
  5. Results
  6. Discussion
  7. Declarations of Interest
  8. References

This was not an industry-sponsored study. Dr Nissen has received speaker honoraria from Sanofi-Aventis and Lundbeck. Dr Riemann has received research support from Sanofi-Aventis and has participated in speaking engagements for Sanofi-Aventis. Dr Spiegelhalder, Mr Regen, Dr Kyle, Mr Endres and Dr Feige have indicated no financial conflicts of interest.

References

  1. Top of page
  2. Summary
  3. Introduction
  4. Methods
  5. Results
  6. Discussion
  7. Declarations of Interest
  8. References
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