Time Estimation in Chronic Insomnia Sufferers

Transcription

1 Time Estimation in Chronic Insomnia Sufferers Isabelle Rioux, MPs 1,2 ; Sébastien Tremblay, PhD 1 ; Célyne H. Bastien, PhD 1,2 1 École de psychologie, Université Laval, Québec, Canada; 2 Laboratoire de neurosciences comportementales humaines, Centre de recherche Université Laval-Robert Giffard, Beauport, Québec, Canada Study Objective: The objective of the present study is 2-fold: (1) compare the time-estimation performance of chronic insomnia sufferers to that of good sleepers and (2) evaluate the severity of the sleep complaint in order to assess its association with the time-estimation performance. Design: Between subjects design. Participants: The sample included 11 individuals suffering from chronic primary insomnia (7 women and 4 men, mean age = years, SD = 12.71) and 11 good sleepers (5 women and 6 men, mean age = years, SD = 7.86). Interventions: N/A. Measurements and Results: All participants completed a time-estimation task, namely a finger-tapping task. The results indicate no significant between-group differences on time-estimation data, as well as no significant relationship between severity of insomnia complaint and estimation of time. Conclusion: These results suggest that the tendency to misestimate sleep difficulties is not linked to impaired time estimation-specific processes in insomnia sufferers, as measured with the present task. Keywords: Insomnia, misestimation, time estimation, finger-tapping task Citation: Rioux I; Tremblay S; Bastien CH et al. Time estimation in chronic insomnia sufferers. SLEEP 2006;29(4): INTRODUCTION A RECENT EPIDEMIOLOGIC REVIEW INDICATES THAT BETWEEN 30% AND 48% OF ADULTS COMPLAIN OF IN- SOMNIA SYMPTOMS, AND NEARLY 6% OF adults experience an insomnia complaint that is important enough to warrant an insomnia diagnosis. 1 Insomnia sufferers often report daytime impairments that they attribute to their sleep disturbances and that reduce their quality of life. 2 Sleep disturbances can also exacerbate comorbid medical conditions and increase utilization of health-care resources 3,4 or lead to other psychopathology. 5 In most clinical settings, it is the nature and the severity of the patients subjective complaints of sleep disturbances that guide evaluation and treatment decisions. Interestingly, these complaints are not always confirmed objectively, 6-8 and the extent to which the sleep misperception is in fact linked to time-estimation deficits is still poorly understood. Several studies have reported that insomnia sufferers tend to overestimate their sleep-onset latency and their wake after sleep onset, as well as to underestimate their total sleep time relative to polysomnographic measures In addition, the overestimation of the wake after sleep onset and the underestimation of total sleep time seem more pronounced in individuals suffering from chronic insomnia whose complaint expresses more severe sleep disturbances. 12 On the other hand, many good sleepers provide estimates of sleep-onset latency and total sleep time that are in agreement with polysomnographic measures or only slightly misperceive their sleep-wake parameters. 8,13,14 As previously observed by Moore Disclosure Statement This was not an industry supported study. Drs. Bastien, Rioux, and Tremblay have indicated no financial conflicts of interest. Submitted for publication July 2005 Accepted for publication November 2005 Address correspondence to: Célyne H. Bastien, PhD, École de Psychologie, Université Laval, Québec, Québec, Canada, G1K 7P4; Tel: (418) , ext 8344; Fax: (418) ; Celyne.bastien@psy.ulaval.ca and cited in Downey and Bonnet, 15 insomnia sufferers overestimate their sleep-onset latency by an average of 42.8 minutes, whereas good sleepers overestimate by an average of only 1.4 minutes. Some authors have suggested that subjective-objective sleep discrepancies in insomnia sufferers may be attributable to an impairment of time estimation and, hence, underscore the need for focused studies of time estimation. 16 Nevertheless, very little attention has been devoted to testing the latter assumption. In an attempt to study time estimation in individuals with insomnia, Moore and her colleagues 17 investigated whether insomnia sufferers are poor estimators of time by asking them to estimate various time intervals (i.e., 5-second, 35-second, and 19- minute intervals) 5 times during a day. Moreover, the duration of a 19-minute afternoon nap also had to be estimated. Estimates were made on log sheets after the presentation of the time intervals, which were defined by auditory markers. This study showed no evidence that insomnia sufferers, relative to normal sleepers, misestimate time during the day. However, compared with individuals in the control group, individuals with insomnia tended to overestimate the time allowed for the nap. In 2002, Belleville and Morin 18 compared the performance of individuals with insomnia and good sleepers on 4 verbal estimation tasks. As was observed in a previous time-estimation study with naps, 17,19 their results suggested that insomnia sufferers display less accuracy in the verbal estimation of a prospective 12.5-minute interval in a sleep-related condition (i.e., during an afternoon nap) relative to good sleepers. Belleville and Morin s results 18 also showed that insomnia sufferers tended to exhibit less accuracy in the verbal estimation of a retrospective 12.5-minute interval in a sleep-unrelated condition (i.e., when waiting in a room) relative to good sleepers. Finally, no evidence of significant time-estimation impairment was found among insomnia sufferers when estimating a prospective 35-second interval, as well as a prospective 3-minute interval. More recently, Tang and Harvey 20 used short and long time intervals (i.e., 5-second, 15-second, 35-second, 1-minute and 15- minute intervals) to assess the effect of context (i.e., laboratory vs home) and arousal (i.e., cognitive and physiologic) on time estimation in 20 insomniacs and 20 good sleepers. The experimental 486 Time Estimation and Insomnia Rioux et al

2 design used a computer (i.e., laboratory setting) or cassette player (i.e., home setting) to generate a sound marking the beginning and the end of each time intervals. No between-group differences were observed in time estimation on any time interval whether participants estimated time at home or in the laboratory. Although participants did not differ on general level of cognitive and physiologic arousal, in both groups, time-estimation judgments, especially the 15-second and 15-minute intervals, were correlated with the level of arousal. Although informative, the above-mentioned studies present methodologic limitations. First of all, these studies did not use daily subjective estimates of sleep-wake parameters to discriminate between insomnia sufferers and good sleepers. Instead they relied on global and retrospective reports, which are more subject to exaggeration and are less reliable. 18 Second, many experts in the time-estimation field believe that the verbal or written estimation methods, which were used to study time estimation in insomnia sufferers, are neither accurate nor reliable In addition, these tasks seem prone to a response bias of reporting the estimated duration with the preferred digits of 0 and 5. 22,23,25-28 Finally, available data on time estimation in insomnia sufferers mainly rely on the use of long time intervals. In contrast with shorter intervals, higher variability, as well as poorer accuracy, have been shown with longer base durations. 29,30 Although ecologically adapted for the insomnia population, longer intervals may not be sensitive enough to detect small but real time-accuracy performance differences between groups. As such, shorter intervals are better suited to detect subtle time-estimation deficits. The first objective of the present study was to compare the time-estimation performance of chronic insomnia sufferers to that of good sleepers through an accurate task frequently used in the field of human timing, namely a finger-tapping task, which implies the reproduction of short time intervals. 31,32 Time estimation was evaluated in both groups with prospective time intervals (i.e., knowing in advance that a time judgment will have to be provided). These prospective time intervals are known to be less incidental and less variable than retrospective time intervals (i.e., unexpected instruction to provide a time judgment after the temporal interval). 25,29,33,34 If insomnia sufferers exhibit time-estimation impairment, one could expect an interference not strictly with retrospective verbal reports of sleep quality and severity upon arising, but also interference when estimating prospective short time durations. A Finally, for exploratory purposes and since psychological characteristics may lead to overestimation of sleep disturbance among insomnia sufferers, this study investigated the relationship between the presence of depressive or anxiety symptoms and time-estimation measures. METHOD Participants Participants were recruited through media advertisements. The participants were 22 community-dwelling adults, including 11 individuals suffering from chronic primary insomnia (i.e., 4 men A The rationale behind the current investigation of time estimation in insomnia is grounded on the notion of internal clock as a governing principle in the assessment of time sense. Of course, there are non-clock views of timing such as that based on the notion of rhythm. However, it is noteworthy that the use of a finger-tapping task enables us to generalize the results beyond a strict clock time perspective. and 7 women) and 11 (i.e., 6 men and 5 women) self-defined good sleepers. Participants had a mean age of years (SD = 10.46; range = 27 to 66 years). Participants had a mean education level of years (SD = 3.81) and were predominantly married (68.2%). The majority of participants was employed (57.2%) or retired (23.8%). The mean duration of insomnia was years (SD = 9.45) for the insomnia sufferers group. The individuals suffering from chronic primary insomnia had to meet the following inclusion criteria: (1) presence of a subjective complaint of insomnia, defined as difficulty initiating (i.e., sleeponset latency > 30 minutes) and/or maintaining sleep (i.e., time awake after sleep onset > 30 minutes) present at least 3 nights per week; (2) insomnia duration of at least 6 months; (3) insomnia or its perceived consequences causing marked distress or significant impairment of occupational or social functioning (e.g., problem of concentration); and (4) presence of a subjective complaint of at least 1 negative daytime consequence attributed to insomnia (e.g., fatigue, mood disturbances). The good sleepers did not meet any of the above-mentioned criteria for insomnia and reported being satisfied with their sleep. Exclusion criteria for all participants were (1) presence of a significant current medical (e.g., cancer, diabetes) or neurological disorder (e.g., dementia, Parkinson disease) that compromises sleep; (2) presence of a major psychopathology (e.g., major depressive disorder, anxiety disorders); (3) presence of a sleep disorder other than primary insomnia (e.g., periodic limb movements, sleep apnea); (4) a score of 23 or higher on the Beck Depression Inventory 38 ; (5) use of psychotropic or other medications known to alter sleep (e.g., bronchodilators); and (6) use of a sleep-promoting agent (e.g., benzodiazepines). For the participants with insomnia, the criteria are consistent with those of the International Classification of Sleep Disorders 39 and the Diagnostic and Statistical Manual of Mental Disorders (DSM- IV) 40 for chronic and primary insomnia. 41 All participants were free from psychotropic drugs for at least a 2-week period prior to entering the study and reported normal hearing. Recruiting and Clinical Procedure After an initial phone interview to determine participants eligibility, participants underwent a screening evaluation composed of a semi-structured sleep history interview to diagnose insomnia, the completion of questionnaires aimed at evaluating the presence of psychological symptoms (Beck Depression Inventory, Beck Anxiety Inventory), 38,42 and physical status. The Insomnia Interview Schedule 43 was used to assess sleep history and insomnia complaints. The Insomnia Interview Schedule also has a section for psychological screening (i.e., presence of psychopathology) and physical status. Various subjective sleep measures were used such as the Insomnia Severity Index (ISI), 43 and daily sleep diaries 43 completed by all the participants for a 2-week period. Participants meeting the above-mentioned criteria then completed the time-estimation task in the laboratory. For all participants, tasks were performed between 7:30 PM and 9:30 PM. Sleep-Wake Parameters Sleep Diary The Sleep Diary 43 is a daily journal used to assess subjective sleep quality. The various sleep-wake parameters derived for this study were sleep-onset latency, referred to as the amount of time 487 Time Estimation and Insomnia Rioux et al

3 from initial lights-out to sleep-onset; wake after sleep onset, defined as the amount of time awake from sleep-onset until the last awakening; early morning awakening, referred to as the amount of time awake from the last awakening to arising time; frequency of awakenings, defined as total number of awakenings during the night; total wake time, obtained by summing sleep-onset latency, wake after sleep onset, and early morning awakening; total sleep time, referred to as the subtraction of total wake time from the amount of time in bed; and finally, sleep efficiency, defined as the ratio of total sleep time divided by time in bed, expressed as a percentage. The Sleep Diary is usually completed upon arising each morning for a 2-week baseline period in order to provide a stable index of sleep complaints. 43 A mean was calculated for each of the derived variables. Insomnia Severity Index The ISI 43 is a reliable and valid, brief, self-report instrument that yields a quantitative index of perceived insomnia severity. 44,45 The ISI comprises 7 items targeting the severity of sleep disturbances, the satisfaction relative to sleep, the degree of impairment of daytime functioning caused by the sleep disturbances, and the noticeability of impairment attributed to the sleep problem, as well as the degree of distress and concern related to the sleep problem. Each item is rated on a 5-point Likert scale, and the total score ranges from 0 to 28. A higher score reveals more severe insomnia. The ISI partly reflects the diagnostic criteria outlined in the DSM-IV. 40,44 Experimental Paradigm Apparatus and Stimuli A PC-compatible computer running Micro Experimental Laboratory (MEL) software controlled stimuli presentations. Participants were tested individually, seated in a soundproof laboratory, at a distance of about 60 cm from the computer screen. Temporal intervals lasting 500, 1500, and 4000 milliseconds were presented. The order of presentation of the different intervals was counterbalanced. Auditory markers defining the intervals were used in a synchronization phase (50 ms; 1 khz). The aim of this synchronization phase was to gradually stabilize the tapping performance. The preferred hand rested on the keyboard of the computer, and the space bar was used to reproduce the time intervals. Temporal intervals were recorded to the nearest millisecond. Procedure Participants were given standard instructions on the computer screen, informing them of the nature of the time-estimation task, which consists of producing a series of taps separated by a duration corresponding to the target interval. 31,46 The time-estimation task is illustrated in Figure 1. In the synchronization phase, participants were requested to tap in synchrony with the tone presentations (i.e., at the same rate). In the continuation phase, the tones were discontinued and participants were instructed to continue tapping at the same frequency. 47 For each of the temporal intervals, participants were asked to complete 6 series of 31 finger taps, marking 30 intervals, after the initial synchronization phase. Pauses were introduced between each series. These pauses could be prolonged if needed, since the beginning of the next series is under the participants control. Participants started the temporal Synchronization phase Continuation phase Figure 1 Finger-tapping task with the synchronization and continuation phases. In the synchronization phase, participants were instructed to begin, when ready, to tap in synchrony with the tone presentations defining the time intervals (i.e., 500 ms, 1500 ms, or 4000 ms). In the continuation phase, the tones are discontinued. Hence, participants were requested to continue tapping at the same frequency. The space bar was used to reproduce the time intervals. Note that the synchronization phase was not retained for analysis. interval presentation by pressing the space bar on the keyboard of the computer. This key press triggered the tone presentation. The task lasted 20 to 25 minutes. The performance in the continuation phase was retained for analysis. Time-Estimation Measures Various outcome measures of time estimation for each time interval were derived, including the mean intertap intervals, the standard deviation of intertap intervals, the mean percentage error rate, and the mean coefficient of variation, as well as the ratio. The mean percentage error rate is defined as the subtraction of the interval duration from the correspondent mean intertap interval, divided by the interval duration, multiplied by A higher mean percentage error rate reveals poorer performance. The mean coefficient of variation is referred to as the ratio of the standard deviation of intertap durations divided by the mean intertap durations. The coefficient of variation, a Weber-like index of time sensitivity, provides the quantification of timing accuracy as a function of subjective duration. 26,48 A higher coefficient of variation indicates higher variability and, hence, a poorer performance. Furthermore, the ratio is referred to as the mean intertap intervals divided by the correspondent interval duration. 26 It is common practice to calculate and report ratios in order to compare duration of judgments across conditions and experiments that used different durations. 33 The ratio also represents a widely accepted approach for quantification of timing accuracy and illustrates the extent to which subjective time estimation resembles objective time duration. Values of this ratio greater than 1 would mean that the participant has provided an overestimation of the objective duration, whereas values of this ratio below 1 would indicate that the participant has displayed an underestimation of the objective duration. Finally, values of this ratio equal to 1 would mean that the participant has provided a perfect estimate of the interval duration. This dependent variable will be used to examine the relationship between time estimation and severity of insomnia. Once participants were asked to complete 6 series of finger taps for each interval duration, a mean was calculated for each time-estimation variable. RESULTS Descriptive Statistics Table 1 summarizes descriptive statistics and effect sizes 49,50 on selected sociodemographic, sleep, and psychological measures. 488 Time Estimation and Insomnia Rioux et al

4 Table 1 Descriptive Variables Variable Insomnia Sufferers Good Sleepers Cohen d Sociodemographic, y Age ± a ± 7.86 a.31 Education ± 5.29 b ± 2.35 c.30 Sleep Insomnia ± 9.45 a duration, y Insomnia ± 4.93 d 4.73 ± 2.28 a * 2.86 Severity Index Psychological Beck Depression 9.80 ± 5.85 d 2.91 ± 3.62 a * 1.38 Inventory e Beck Anxiety 4.80 ± 4.05 d 2.18 ± 2.18 a.78 Inventory Data are presented as mean ± SD unless otherwise indicated. a n = 11 b n = 7 c n= 9 d n= 10 e Items targeting sleep difficulties were included in the total score *p <.01 Missing data were observed for 2 good sleepers and 4 insomnia sufferers for Education and for 1 insomnia sufferer on the ISI, Beck Depression Inventory, and Beck Anxiety Inventory. Independent-samples t tests were conducted to determine whether groups were equivalent on those variables. No significant differences were found for age (t 20 =.75, p =.46) and education (t 14 = -.63, p =.54). There were significant between-group differences on self-report measures of insomnia severity and depression. Indeed, insomnia sufferers exhibited more severe sleep disturbances on the ISI (t 19 = -6.82, p <.01) and reported more depressive symptoms on the BDI (t 19 = -3.28, p <.01) relative to good sleepers. There were no significant between-group differences on the BAI (t 19 = -1.87, p =.08), although individuals with insomnia tended to report more anxiety symptoms than good sleepers. Sleep-Wake Parameters Sleep Diary Means, standard deviations, and effect sizes 49,50 for sleep-wake measures obtained from daily sleep diary are presented in Table 2. Independent-samples t tests were computed to determine whether there were significant group differences on those variables. There were significant between-group differences on daily sleep-diary measures, including the sleep-onset latency, (t 19 = -3.36, p <.01, the wake after sleep onset, (t 19 = -3.21, p <.01), the frequency of awakenings, (t 19 = -2.58, p <.05), the total wake time, (t 19 = -4.13, p <.01), the total sleep time, (t 19 = 3.33, p <.01), and the sleep efficiency, (t 19 = 3.77, p <.01). There was no significant betweengroup difference on the early morning awakening, (t 19 = -1.83, p =.08), although the difference was close to statistical significance. As expected, insomnia sufferers reported more sleep disturbances than good sleepers. Time-Estimation Measures Means, standard deviations, and effect sizes 49,50 for time-estimation measures are presented in Table 3 and Table 4. For each Table 2 Subjective Sleep-Wake Measures Variable Insomnia Sufferers a Good Sleepers b Cohen d Sleep-onset ± ± 6.71** 1.41 latency Wake after sleep ± ± 9.21** 1.35 onset Early morning ± ± awakening Frequency of 2.18 ± ± 0.59* 1.08 awakenings Total wake time ± ± 21.53** 1.73 Total sleep time ± ± 39.45** 1.40 Sleep efficiency ± ± 4.48** 1.58 Data are presented as mean ± SD in minutes, except sleep efficiency, and frequency of awakenings a n = 10 b n = 11. *p <.05 **p <.01 Table 3 Time-Estimation Measures Variable Insomnia Sufferers a Good Sleepers a Cohen d 500-ms interval Mean intertap ± ± interval, ms Standard ± ± deviation, ms Error rate, % ± ± Coefficient of 6.09 ± ± variation, % 1500-ms interval Mean intertap ± ± interval, ms Standard ± ± deviation, ms Error rate, % ± ± Coefficient of 8.47 ± ± variation, % 4000-ms interval Mean intertap ± ± interval, ms Standard ± ± deviation, ms Error rate, % ± ± Coefficient of ± ± variation, % Data are presented as mean ± SD. a n = 11. series, the first 3 intertap intervals were discarded to ensure stabilization of tapping performance. Thus, 27 intertap intervals comprised each series. Moreover, for each participant, outliers were identified (± 3 SD from the mean) and removed (8.02% of the intertap intervals). A 1-way multivariate analysis of variance (MANOVA) was computed in order to determine the effect of group on the selected time-estimation measures (i.e., the mean intertap intervals, the Standard Deviation of intertap intervals, the mean percentage error rates, the mean coefficients of variation, and the ratios) as well as to detect a possible effect of order of presentation, given that a practice effect has already been shown 489 Time Estimation and Insomnia Rioux et al

5 Table 4 Ratios of Mean Intertap Intervals Over the Objective Duration Ratios Insomnia Sufferers a Good Sleepers a Cohen d 500-ms interval 1.07 ± ± ms interval 1.00 ± ± ms interval 1.05 ± ± Data are presented as mean ± SD unless otherwise indicated. a n = 11. for a prospective 35-second interval. 18 There was no significant group effect on the time-estimation measures (Wilks Λ =.50, F 12,5 =.412, p =.90). Hence, time estimation did not differ between the 2 groups. Finally, there were no significant effect of order of presentation (Wilks Λ =.11, F 24,10 =.82, p =.67), nor any significant interaction between the groups and the order of presentation, (Wilks Λ =.05, F 24,10 = 1.48, p =.263). As a consequence of these findings, follow-up tests to the MANOVA were not conducted on the dependent variables. Inspection of values of Tables 1 to 4 reveals that effect sizes related to sociodemographic data and sleep measures ranged from medium to large, whereas those related to time-estimation measures ranged from null to small. These results thus confirm that variables well known to differentiate insomnia sufferers and good sleepers show a strong effect, whereas timerelated measures do not. Ancillary Measures and Time-Estimation Measures Exploratory Analyses Insomnia Severity and Sleep Efficiency Pearson correlation coefficients were computed between selfreport measures of insomnia severity on the ISI and ratios of mean intertap intervals over the objective duration. Results of the correlational analyses used for the total sample showed that the presence of a more severe insomnia complaint was not significantly associated with overestimation of the 3 durations of the temporal intervals, namely the 500-millisecond interval, (r 19 =.28, p =.22), the 1500-millisecond interval, (r 19 =.19, p =.41), and, finally, the 4000-millisecond interval (r 19 =.22, p =.35). In general, the correlations between insomnia severity and time-estimation data tended to be lower and not significant. Similarly, Pearson correlation coefficients were computed between the sleep efficiency derived from the sleep diaries and ratios of mean intertap intervals over the objective duration. Likewise, the results of the correlational analyses revealed that the presence of a low sleep efficiency was not significantly related with overestimation of the 3 durations of temporal intervals, that is the 500-millisecond interval (r 19 = -.34, p =.13), the 1500-millisecond interval (r 19 = -.21, p =.36), and, lastly, the 4000-millisecond interval (r 19 = -.35, p =.12). Altogether, the correlations between the sleep efficiency data and time-estimation measures tended to be lower and not significant. Depressive and Anxiety Symptoms Pearson correlation coefficients were also computed between self-report measures of depression and anxiety, and ratios of mean intertap intervals over the objective duration. The results of the correlational analyses used for the entire sample revealed that the presence of more depressive symptoms was not significantly related with overestimation of the 3 durations of the temporal intervals, that is the 500-ms interval (r 19 =.12, p =.61), the millisecond interval (r 19 =.21, p =.37), and the 4000-millisecond interval, (r 19 =.33, p =.15). Furthermore, the results showed that the presence of more anxiety symptoms was not significantly correlated with the 3 durations of the temporal intervals, namely the 500-millisecond interval, (r 19 = -.29, p =.21), the 1500-millisecond interval, (r 19 = -.001, p = 1.00), and, in the end, the 4000-millisecond interval, (r 19 = -.04, p =.86). Altogether, the correlations between the psychological data and time-estimation measures tended to be lower and not significant. DISCUSSION This study compared the performance of insomnia sufferers and of good sleepers on a time-estimation task. The insomnia group was as accurate as the good-sleeper group and was not more prone to overestimate time intervals. Standard deviations and coefficients of variation did not seem to reflect greater timing inaccuracy and variability among insomnia sufferers. In addition, no significant relationships were found between the severity of insomnia complaint, sleep efficiency, depressive and anxiety symptoms, and time-estimation performance. Despite the rationale supporting our assumptions, there is no evidence of time-estimation impairment in the insomnia group. It is thus not possible to conclude that time estimation, per se, as measured with the task used in the present study, is affected in insomnia sufferers nor is it possible to attribute the observed discrepancies between reported and recorded sleep to serious deficits in estimation of time. Moreover, in the present study, time estimation does not seem to be related to the severity of the insomnia complaint. Even if the time-estimation task was performed in the evening, when the degree of arousal among insomnia sufferers is supposed to be higher, 51 results from the present study do not support the contention that insomnia sufferers are poor estimators of time. These findings are consistent with other studies conducted with insomnia sufferers. Of the 3 studies conducted with insomnia sufferers, 2 showed that time estimation of relatively short as well as of long intervals was not affected by insomnia, 17,20 whereas the other found that only the duration of 1 prospective long interval was overestimated by the insomnia sufferers group. 18 Although Tang and Harvey 20 reported that a relationship between arousal levels and time misestimation is present, groups did not differ on general time-estimation measures. The absence of significant impairment in time estimation among insomnia sufferers is also consistent with findings of some studies conducted in patients with mood disorders. Indeed, several authors noticed that time estimation was not affected by depression The present findings are also in agreement with those of Moore and her colleagues, 17 who reported no significant relationship between anxiety scores and time-estimation performance. Our results suggest that factors other than altered time estimation could explain the typical discrepancies between subjective and objective sleep measurements in insomnia sufferers. Some authors have raised the possibility that insomnia sufferers may misperceive their state of consciousness. For instance, insomnia sufferers are more likely than good sleepers to report being awake when awakened from stage 2 sleep. 16,55-57 Related to this issue, Downey and Bonnet 15 showed that sufferers of chronic subjective insomnia can learn to discriminate sleep from wakefulness and, 490 Time Estimation and Insomnia Rioux et al

6 therefore, decrease their overestimations of sleep-onset latency. Moreover, the degree of the misestimation of the duration of sleep and the amount of time awake seems to be linked to the inaccurate discrimination of their state of consciousness. 57 Perhaps these issues are more relevant than is time-estimation impairment in understanding the discrepancies between reported and recorded sleep in insomnia sufferers. On the other hand, the sole fact of waiting for an event to occur (e.g., waiting to fall asleep) may lead to a misestimation of time. Indeed, some authors argue that elapsed time seems longer when one is engaged in an unpleasant, aversive, or distressing situation and, as a consequence, overestimation of time occurs. Conversely, elapsed time seems shorter when a person is engaged in a pleasant or relaxing situation, and, as a result, there is a tendency to underestimate time. 10,43,58,59 During the presleep period, individuals suffering from insomnia display unpleasant intrusive thoughts and an excessive negatively toned cognitive activity It is possible that this unpleasant and distressing situation around sleep onset and during nightly awakenings in insomnia sufferers yields misestimation of time. Insomnia sufferers may also devote more attention to time around the sleep-onset period in trying to achieve sleep, which leads to the overestimation of their sleepwake parameters. In fact, when individuals with insomnia are asked to monitor the clock, overestimation of their sleep-onset latencies occurs. 63 As pointed out by Tang and Harvey, 20 it might be possible that arousal levels increase as time to go to bed approaches, and that misestimation between groups and deficits in time estimation might be more evident during the period of time surrounding the onset of sleep when the estimation of time to fall asleep takes place. These authors also mentioned that misestimation might be pronounced because estimated intervals more closely reflect the time estimated to fall asleep or nighttime awakening (e.g., 30 minutes), with these time intervals corresponding to insomnia cut-off criteria. We thus agree with these authors that the period of time surrounding the onset of sleep might be a better-suited period to evaluate the extent of time-estimation deficits in insomniacs. Furthermore, because arousal (i.e., both cognitive and physiological) might persist or vary after sleep onset, estimation of time intervals during nocturnal awakenings might further circumscribe time misestimation in insomnia sufferers. It is also possible that the impairment of time estimation in insomnia sufferers is limited to retrospective judgments. Indeed, measures used to assess subjective sleep quality are often completed upon arising in morning. On this point, 1 study conducted with insomnia sufferers, relative to good sleepers, showed that they overestimate their sleep-onset latency both in the morning and after being awakened after the first sleep spindle. Nevertheless, both insomnia sufferers and good sleepers provide less accurate judgments of their sleep-onset latency in the morning. 64 In addition, several authors believe that retrospective time judgments are more variable and less accurate than are prospective ones. 25,33,34 Moreover, overestimation of elapsed duration is not uncommon with the verbal or written method estimation. 22 Inaccurate estimates of sleep-wake parameters in individuals with insomnia could thus reflect a difficulty in making accurate judgments on a retrospective basis. Some psychological characteristics may also lead to overestimation of sleep disturbance among insomnia sufferers. In that regard, individuals suffering from insomnia associated with depression may be more prone to magnify sleep disturbances. 36 In addition, cognitive rumination, physiologic symptoms of tension and anxiety, faulty sleep expectations, and catastrophic expectations about the impact of insomnia may also influence the degree of congruence between subjective and objective sleep-wake parameters. 37,65 Although our results did not show any relation between anxiety and depressive symptoms and time estimation, it may be helpful to further examine the impact of psychological factors on the estimation of sleep-wake parameters. Finally, this study presents some limitations. First, polysomnography was not used. Although insomnia refers to a subjective complaint of sleep disturbances, it is nonetheless possible that perceived sleep disturbances are magnified or disproportionate in relation to objective sleep disturbances in insomnia sufferers and good sleepers. Thus, replications of this study with the use of polysomnographic evaluations would be advisable. However, although polysomnography is often considered as the gold standard in the objective assessment of sleep, it might be that, in regard to time misestimation or misperception, our definition of sleep stages may not be sensitive enough to indicate the type of difficulty experienced by insomnia sufferers. One can thus ask the following question: Is the misestimation on the part of the insomnia sufferers, or on the part of our usual sleep-stage scoring or identification? Related to this issue, and also according to our usual polysomnography scoring, our sample did not differentiate between paradoxical and psychophysiologic insomniacs. As such, the use of more refine EEG techniques, such as sleep EEG spectral analysis, could also provide new insights for understanding discrepancies between subjective and objective measurements of sleep in insomnia sufferers. Given that the magnitude of the discrepancies between subjective and objective sleep measures is significantly higher among individuals suffering from paradoxical insomnia and that paradoxical insomniacs display more fastfrequency activity (i.e., probably more physiologic and cognitive arousal) than psychophysiologic insomniacs both at sleep-onset and during sleep, 66 it is possible to believe that time-estimation impairment may be a cardinal feature of this primary insomnia subtype. Given insomniacs psychological characteristics and different brain states observed during daytime and nighttime, the use of the present procedure at different times of day, and especially at the period of time surrounding the onset of sleep or after an experimental awakening, might also shed some light on the misestimation phenomenon. In summary, the present results do not confirm the hypothesis related to real time-estimation impairment in insomnia sufferers. The origin of insomnia sufferer s magnification of sleep problems remains perplexing, and additional research is needed to explain the tendency to overestimate sleep disturbances in insomnia sufferers, as well as the implication of this tendency in the management of chronic primary insomnia. ACKNOWLEDGEMENTS This research was supported in part by a Grant from the Fonds de Recherche en Santé du Québec (FRSQ; 50833) and Canadian Institutes of Health Research (CIHR, 49500), and by an FRSQ scholarship to IR. We are grateful to Charles M. Morin, Claudette Fortin, R. Rousseau, and Émilie Fortier-Brochu for their suggestions and their critical comments on an earlier draft of the paper. 491 Time Estimation and Insomnia Rioux et al

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