Dysfunctional Cognitions about Sleep in Psychiatric Patients

The optimal management of sleep problems is a significant challenge, particularly in patients with psychiatric illness, because disturbed sleep is a known risk factor for relapse. This study used the short Dysfunctional Beliefs and Attitudes Scale to assess beliefs about sleep in adults with acute psychiatric disorders (N = 100) recruited from inpatient and outpatient clinics. The subjects showed highly dysfunctional beliefs and attitudes about sleep and held diverse opinions about, but had low confidence in, their own capacity for optimal sleep management. They did not report excessive daytime sleepiness. We conclude that individuals with acute psychiatric illness worry significantly about their sleep and hold more dysfunctional beliefs about sleep than people without psychiatric illness. The absence of excessive daytime sleepiness in this sample, although counterintuitive, is consistent with findings in other studies. Given that two thirds of the sample expressed interest in non-pharmacological strategies to better manage their sleep problems, cognitive reshaping therapies appear to have clinical potential as alternatives to hypnosedative medication once a comprehensive sleep workup has excluded a physical sleep disorder such as obstructive sleep apnea. Dysfunctional beliefs and high concern about sleep offer potential targets for psychotherapy. (Journal of Psychiatric Practice 2014;20:188–195) KEY WORDS: sleep, insomnia, attitudes, beliefs, psychiatric, medication, excessive daytime sleepiness, therapy management, CBT

“Blessed is the person who is too busy to worry in the daytime and too sleepy to worry at night.” ~ Author Unknown Patients with psychiatric disorders commonly complain of sleep disturbances, and sleep normalization is often a key indicator of recovery from a psychiatric

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MARK HUTHWAITE, MB HELEN MILLER, MBChB JUDITH MCCARTNEY, BPharm SARAH ROMANS, MD

episode.1 The various pharmacological approaches to managing sleep disturbances are each associated with potential problems, especially when used longterm. These include physical dependence on benzodiazepines and non-benzodiazepine hypnosedative drugs,2,3 sedation and anticholinergic side effects from tricyclic antidepressants,4,5 and metabolic syndrome with sedative atypical antipsychotic drugs used off-label as hypnosedatives.6,7 Yet a psychiatric patient’s complaint about poor sleep cannot be ignored, as both the psychiatrist and patient know that insomnia is one potential precipitant of relapse in a wide range of conditions and is often noted on the patient’s list of early warning signs.1 Attitudes about sleep and about the consequences of not “getting enough sleep” may initiate and maintain insomnia.8 Conceptual models of how psychological processes maintain insomnia suggest that excessive rumination about poor sleep and its daytime consequences maintain sleep difficulties. Although some psychological or medical factors may trigger the initial disruption of the sleep/wake cycle, dysfunctional thoughts may then maintain the ongoing psychologically based sleep disturbances.9 Little has been written about the views of patients with psychiatric illness toward their sleep and the extent to which dysfunctional beliefs and attitudes may play a role in the maintenance of sleep disturbances in this particular population. The DysfuncHUTHWAITE, MILLER, MCCARTNEY, and ROMANS: University of Otago School of Medicine, Wellington, New Zealand. Copyright ©2014 Lippincott Williams & Wilkins Inc. Please send correspondence to: Prof Sarah Romans, Department of Psychological Medicine, School of Medicine and Health Sciences, University of Otago, Wellington, PO Box 7343, Wellington, 6242, New Zealand. [email protected] The Wellington Medical Research Foundation, Inc. supported this research. It was conducted with the assistance of Capital and Coast District Health Board, whose staff facilitated the data collection. We thank the 100 people who participated in this study. We would also like to acknowledge the statistical assistance and guidance of Dr James Stanley (medical biostatistician) from the University of Otago. The authors declare no conflicts of interest. DOI: 10.1097/01.pra.0000450318.14236.36

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DYSFUNCTIONAL COGNITIONS ABOUT SLEEP IN PSYCHIATRIC PATIENTS

tional Beliefs and Attitudes about Sleep (DBAS) scale was developed to assess sleep cognitions, expectations, and perceptions.10 It has been used in studies of populations of “good sleepers,” as well as in populations of patients with insomnia, and it has good psychometric properties.11 Most published work using the DBAS has used volunteer samples recruited by advertisement. Excessive daytime sleepiness (EDS) can also be a symptom of psychiatric illness, particularly depression,1,12,13 and it can also be associated with treatment for depression.14 EDS also may further undermine patients’ confidence in their ability both to sleep easily and well and to be alert during the day. Although the range of pathophysiological mechanisms underlying EDS are not fully understood,15,16 many sufferers believe EDS indicates that the previous night’s sleep was poor (e.g., too short, too light or fragmented). Pharmacodynamic principles and clinical opinion suggest that hypnosedative medication may contribute to EDS, although the research findings do not necessarily support this association.14,17

OBJECTIVE The aims of this study were to investigate beliefs about sleep in a sample of patients with a range of psychiatric illnesses using the DBAS and to see what role, if any, excessive daytime sleepiness played in causing concerns the patients had about their sleep.

METHOD Participants This study used a cross-sectional survey method and sampled from the greater Wellington region in New Zealand. Participants were recruited from one inpatient site and two community mental health clinics operated by the regional publically funded health organization, Capital and Coast District Health Board. Most referrals to these services come from primary care physicians and the service is free at point of service delivery. Patients were eligible for inclusion if they were 18–65 years of age and able to participate. This recruitment strategy meant that participants were experiencing an acute psychiatric illness, for which they were receiving active treatment. Exclusion criteria were inability to speak/ understand English, intellectual handicap to the

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extent that the patient could not follow the questionnaire, being judged by their health care team as too unwell on the day to participate, and acute intoxication or inability for other reasons to give written informed consent. We endeavored to recruit a consecutive series of all patients (including both new patients and returning patients who had been re-referred to the psychiatric service) from December 1, 2010 to January 14, 2011. Informed consent was obtained from all participants. Two research assistants collected data from each participant using a semi-structured interview. While most of the information was obtained directly from participants, some demographic and related information was extracted from the patient’s clinical record (see below). The Central Regional Ethics Committee of the New Zealand Ministry of Health gave ethical approval to this study on December 1, 2010. Measures The data collection protocol involved four components: 1. Participants were asked whether they had any difficulties sleeping, if they were using a hypnosedative, how they thought their prescribed medications affected their sleep, and what strategies other than medication they used or knew about to manage sleep problems. 2. The abbreviated (16-item) Dysfunctional Beliefs and Attitudes Sleep Scale (DBAS-16) was developed from the original 30-item DBAS.10 The DBAS was developed to measure the intensity of sleep disruptive cognitions, and both versions have reasonable psychometric properties.10 The participants endorsed items using a Likert-type scale that ranged from 0 (strongly disagree), through 5 (neutral) to 10 (strongly agree).We were not able to find New Zealand normative data for the DBAS. 3. The Epworth Sleepiness Scale (ESS) is a subjective self-report index of sleepiness that was developed by Johns18 and is widely used to assess daytime sleepiness. It contains eight items each of which asks how likely the respondent is to fall asleep in certain situations (e.g., when watching TV, sitting inactive in public, in a car stopped for a few minutes in traffic). Each item is rated on a Likert-type Scale from 0 (never) to 3 (high likelihood). The ESS has good psychometric properties; the author vali-

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dated its use in a comparative study of three tests measuring daytime sleepiness and found that the ESS gave the most accurate and discriminating results over multiple situations. It has been used in a limited way in psychiatric populations and there is one general population study with New Zealand participants.19 4. Information was extracted from hospital charts including current psychiatric diagnosis, mental health act status (involuntary patient status), current medications, and associated general medical conditions. Data Management and Statistical Analysis The statistical analyses were performed using Microsoft Excel 2007, Epi-info (3.5.1), and SPSS-20 to calculate frequencies, contingency tables, means and standard deviations, as indicated by data type. The 16-item DBAS needed data reduction; we used the subsets generated by Morin and colleagues from their two factor analyses.10 We summed the items listed for each factor and divided by the number of items in the subset to give comparable means. Diagnoses, using ICD-10 categories, were collapsed into three groups: 1) schizophrenia and related nonaffective psychoses, 2) affective disorders including bipolar disorders and affective disorders with psychotic features, and 3) other diagnoses (5 of the 9 patients in this category were diagnosed with posttraumatic stress disorder). We evaluated the data for interactions between demographic (age, sex, inpatient versus community sample) variables, clinical variables (diagnosis, hypnosedative use), and DBAS and ESS items, using Pearson’s correlation, chisquare, t tests, and analysis of variance (ANOVA) as indicated by data type. Finally, we compared the DBAS results with the data on “good sleepers” from Carney and colleagues.20

RESULTS Participant Characteristics One hundred sixty-three potentially eligible subjects were invited to take part in the study. Of these 163 individuals, 18 (11%) were excluded (3 due to language difficulties, 2 due to low IQ, and 13 because they were judged too acutely unwell to participate) and 45 (28%) refused (reasons for refusal included

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“not interested” or “no time,” doubt about the purpose of the data collection, or most commonly no reason). Thus, 100 patients participated in the study for an overall participation rate of 61%. The sociodemographic and clinical characteristics of the sample are shown in Table 1. Most patients (80%) reported having at least one sleep complaint, the most common being “difficulty falling asleep.” Dysfunctional Beliefs and Attitudes about Sleep There were no statistical differences in DBAS mean scores based on gender (male/female), diagnosis (schizophrenia and other non-affective psychoses, affective disorders), length of illness, hypnosedative use (yes/no), community versus inpatient sites, age, or length of illness. The average total DBAS score for our sample was 88.6 (standard deviation [SD] 30.75, minimum 30.0 and maximum 160.0) and the average item score was 5.54 (SD 1.92). Results of the DBAS are shown in Table 2, which also compares the central tendency and variance from the Wellington sample with results from the data on “good sleepers” reported by Carney and colleagues.20 Scores on each item in the Wellington sample were statistically higher than those in these “control” results. There were no statistical associations between any of the sixteen DBAS items and patient’s age, gender, or diagnosis collapsed into three categories. The DBAS-16 has 4 item subsets: Consequences of Insomnia, Sleep Expectations, Worry about Sleep and Helplessness, and Medication. We obtained the following means and standard deviations for the DBAS subsets: Consequences mean 5.77 (SD 2.19), Expectations mean 6.64, (SD 2.52), WorryHelplessness mean 5.03 (SD 2.35), and Medication mean 5.13 (SD 2.67). There was a complex pattern of interrelationships among the four subsets. Consequences was significantly correlated with the three other subsets (r > 0.38 and p < 0.001 in each case). Expectations was correlated with the WorryHelplessness subset (r = 0.25, p = 0.02) but not with Medication. However, Worry-Helplessness was correlated with Medication (r = 0.566, p < 0.001). There was no statistical association between any DBAS subset and age, gender, or length of illness. For hypnosedative use (yes/no), one DBAS subset, Expectations, did differ between the two groups, with those taking a hypnosedative having a statistically

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DYSFUNCTIONAL COGNITIONS ABOUT SLEEP IN PSYCHIATRIC PATIENTS

Table 1. Demographic and clinical characteristics of participants Age Years, mean (SD) 37.6 (11.6) Range (years) 19–63 Gender, n (%) Male 54 (54%) Female 46 (46%) Main source of income, n (%) Invalids benefit (long-term government income support) 49 (51%) Sickness benefit (short-term government income support) 22 (23%) Other government assistance 10 (10%) Employment 10 (10%) Other (includes savings, family support) 3 (10%) None 3 (3%) Education, n (%) Secondary - Level 1 not achieved 16 (16%) Secondary - Level 1 or higher 32 (33%) Tertiary - university/technical institute 44 (45%) Trade qualification 5 (5%) Legal status, n (%) Under Mental Health Act (involuntary) 39 (39%) Duration of mental illness Years, mean (SD) 13.2 (12.0) Range (years) 0.3–47 Recruitment location, n (%) Community (outpatients) 69 (69%) Inpatients 31 (31%) ICD-10 diagnosis, n (%) F20–F29 Schizophrenia, schizotypal or delusional disorders 55 (55%) F30–F39 Mood (affective) disorders 45 (45%) F40–F49 Neurotic, stress-related and somatoform disorders 24 (24%) F50–F59 Behavioral syndromes associated with psychological disturbances and physical factors 2 (2%) F60–F69 Disorders of adult personality and behavior 15 (15%) F80–F89 Disorders of psychological development 3 (3%) F90–F98 Behavioral and emotional disorders with onset usually occurring in childhood or adolescence 3 (3%) *Frequency and percentage are the same since n = 100, except in cases where data on an item were not available for the full sample. SD: standard deviation; Level 1: refers to New Zealand’s National Certificate of Educational Achievement Level 1 qualification, or equivalent.

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significant higher score than those not taking a hypnosedative (Expectations score of 6.89 (SD 2.20) for those taking a hypnosedative compared with 5.41 (SD 3.46) for those not taking a hypnosedative, t = 2.12, p = 0.03). Only one subset was statistically linked to diagnosis. Patients with “other” diagnosis had a statistically higher scores on the subset Consequences than did patients with schizophrenia and affective diagnoses (ANOVA f 3.34, df 2 p = 0.04). Epworth Sleepiness Scale Results on individual ESS items are shown in Table 3. The average total ESS score was 6.10 (SD 4.16). Only a few patients (13 of the 74 with complete ESS data [17.6%]) scored higher than 10 on the ESS. Visual inspection suggested no differences between the Wellington ESS scores and the normative New Zealand data, in which the mean total score was 6.0 (SEM 0.07) for New Zealand participants.19 DBAS and ESS No significant correlations were found between the DBAS subset scores and the ESS mean score using either Pearson’s or Spearman’s bivariate correlations.

DISCUSSION The first finding of this study is that individuals with acute psychiatric illness showed dysfunctional beliefs and attitudes toward sleep as assessed with the DBAS scale. All of the 16 items were endorsed statistically more strongly than in a previous published set of data from “good sleepers.”20 For example, three-quarters of the participants agreed or strongly agreed with the items “Need 8 hours sleep” and “Mood disturbance is due to insomnia.” Another item on which the two samples differed strongly was “Better off taking sleeping pills.” The second finding is that people with acute psychiatric illness do not report excessive daytime sleepiness on the ESS. This might be counter to expectation given the sedative properties of many commonly used psychiatric medications (e.g., antipsychotic agents). Despite some difficulties that were encountered in interviewing patients with acute psychiatric illness, which led to a refusal rate of 28% and an exclusion rate of 11%, this study shows that research with this population is feasible. One value of conducting

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Table 2. DBAS responses from Wellington participants, with results from “good sleepers” shown for comparison

Median

IQR

Wellington sample mean (SD)

1. Need 8 hours of sleep (96)

8

5.5, 10

7.3 (2.82)

5.63 (2.94)

< 0.0001

2. Need to catch up on lost sleep (96)

7

4, 9

6.3 (3.19)

4.84 (2.83)

< 0.0001

3. Consequences of insomnia on physical health (93)

8

4, 10

6.5 (3.48)

4.62 (3.32)

< 0.0001

4. Fear of losing control of sleep (95)

5

0, 8

4.7 (3.57)

1.65 (2.22)

< 0.0001

5. Insomnia interferes with daytime functioning (95)

8

6, 10

7.4 (2.83)

5.36 (2.77)

< 0.0001

6. Better taking sleeping pills (92)

7

4, 10

6.1 (3.49)

1.78 (2.27)

< 0.0001

7. Mood disturbances due to insomnia (95)

6

5, 8

6.1 (2.84)

3.48 (2.66)

< 0.0001

8. One poor night disturbs whole week (96)

5

1, 7

4.2 (3.36)

1.73 (2.38)

< 0.0001

9. Cannot function without a good night (95)

5

3, 7

5.1 (3.01)

2.53 (2.39)

< 0.0001

10. Sleep is unpredictable (95)

6

4, 10

6.2 (3.34)

4.23 (3.09)

< 0.0001

11. Unable to manage consequences (93)

5

2, 8

5.3 (3.37)

3.70 (2.63)

< 0.0001

12. Lack of energy due to poor sleep (94)

6

4, 8

6.1 (2.98)

5.25 (2.67)

0.0137

13. Insomnia results from chemical imbalance (87)

5

2, 8

5.1 (3.32)

4.25 (2.05)

0.0248

14. Insomnia destroying life (90)

4

0, 7

3.9 (3.47)

2.43 (2.57)

0.0003

15. Medication as a solution (93)

3

0, 7

4.0 (3.57)

1.23 (1.85)

< 0.0001

16. Cancel obligations after poor sleep (94)

5

1, 7

4.6 (3.51)

1.67 (2.35)

< 0.0001

DBAS itema (number of responses)

Good sleepersb mean (SD)

pc

aParaphrasing

of questions taken from Morin et al. 200710 taken from Carney et al. report concerning self-reported “good sleepers”20 cp-value determined by t-test comparing the means for the two groups IQR = Inter-quartile range (25%, 75%); DBAS: Dysfunctional Beliefs and Attitudes Sleep Scale (range from 0 = strongly disagree to 5 = neutral to 10 = strongly agree); SD: standard deviation bData

research with acutely ill patients is that it allows researchers to capture current practical problems encountered by patients and their treating physicians without the bias of retrospective reporting. Previous work that has examined the DBAS scale in psychiatric patients has used samples recruited through advertising.21–23 Although these studies have made a valuable contribution concerning the role of cognitive therapies in people with dysfunctional sleep cognitions, their DBAS results may not be typical of psychiatric patients in general. Although modest in size, our study sample included a wide range of diagnostic categories and would seem to be typical of adult psychiatry practice. The

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DBAS and ESS are widely used instruments with good psychometric properties. Study limitations include the fact that the participants were all treated by public sector psychiatrists working for one health organization. We also did not gather information on symptom severity and functional disability at the time patients completed the questionnaires. The 16-item DBAS posed some difficulties for this particular clinical sample. Many participants found it difficult to respond to statement 13, which asks about the belief that “Insomnia results from chemical imbalance,” appearing to think it was a right/wrong answer designed to test their knowl-

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DYSFUNCTIONAL COGNITIONS ABOUT SLEEP IN PSYCHIATRIC PATIENTS

Table 3. Scores on the Epworth Sleepiness Scale (ESS) Situation

Wellington sample n Score (SD)

1. Sitting and reading

92

2. Watching TV

Range

Median

0.84 (0.91)

0–3

1

90

0.91 (0.94)

0–3

1

3. Sitting inactive in public (theater, meeting)

93

0.40 (0.73)

0–3

0

4. Passenger in a car for an hour without a break

92

1.04 (1.05)

0–3

1

5. Lying down to rest in the afternoon

92

1.72 (1.07)

0–3

2

6. Sitting talking to someone

95

0.27 (0.58)

0–3

0

7. Sitting after lunch (no alcohol)

95

0.65 (0.80)

0–3

0

8. In a car, stopped for a few minutes in traffic

82

0.11 (0.42)

0–3

0

Scale: from 1 = never to 3 = high likelihood

edge. Participants who had initially stated they did not have a sleep problem found it difficult to respond to DBAS statements that explicitly asked about their “insomnia.” A better approach for future studies would be to establish the presence/absence of insomnia prior to administering the DBAS and then not include those items asking about insomnia or else guide participants on how best to respond to those statements, perhaps by including a “not applicable” response option. The comparison of data from this New Zealand population with data from “good sleepers” from another country was not optimal, but it was necessary since there are not yet any New Zealand normative DBAS data available. It is possible that patients’ attitudes toward their sleep may be influenced by their psychiatric illness (e.g., depressive nihilism may generate more negative sleep expectations). This raises the issue of state versus trait for the DBAS and ESS and its intersection with psychiatric status. Johns has reported good test-retest stability for the ESS18 but this may not apply to people with psychiatric illness who are moving in and out of symptomatic episodes. It would be informative to track people with psychiatric illnesses longitudinally to study this question. The ESS scores in our sample were similar to those found in general population studies. The individual ESS items were highly correlated with each other, with the exception of item 8, falling asleep while a passenger in a car. A number of our participants commented that this was an inappropriate item for them, as they were rarely being driven in a

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car in such a manner. With the benefit of hindsight, we might have broadened the item to include traveling on public transport such as buses. The lack of a correlation between any of the DBAS subset scores and the ESS in our sample does not support one aspect of Harvey’s cognitive model of insomnia—i.e., selective attention to daytime sleepiness increasing worry and concern about sleep.9 We currently know little about subjective daytime sleepiness and its relationship to objective daytime sleepiness and the role of psychotropic drugs in each. Both the individual items and total scores on the DBAS and ESS are continuous variables which researchers often reduce to categories. However, there does not yet seem to be a consensus in the literature about the best way to analyze and present these data. If categories are being used (e.g., 0–10 versus > 10 for the ESS total score), we need to be sure that the best cut-off is being used. The optimum cut-off should be generated by comparing the screening tool’s performance against a “gold standard.” Unfortunately, it is not clear what would constitute a “gold standard” for either the DBAS or ESS. Analysis of the Worry/Helplessness subset of DBAS items could suggest that people who score highly on this subset find their sleep unpredictable and uncontrollable and tend to catastrophize (e.g.: “I feel insomnia is ruining my ability to enjoy life and prevents me from doing what I want”). High scorers on the Worry/Helplessness subset also tend to accept a biomedical view of their insomnia and its treatment (e.g. “I believe insomnia is essentially the result of a

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chemical imbalance” and “Medication is probably the only solution to sleeplessness”). By contrast, there was no statistical correlation between the subsets for Expectations (e.g., “I need 8 hours or more sleep to feel refreshed and function well during the day” and “When I don’t get a proper amount of sleep on a given night, I need to catch up the next day”) and Medication subset scores. Further consideration of these subset items may suggest domains for cognitive behavioral interventions.24 The findings described above are clinically significant because they identify key beliefs that could be addressed psychotherapeutically by the treating psychiatrist or through structured cognitive-behavioral therapy.22,25,26 Finding non-medication strategies that patients can adopt is desirable for many reasons, including minimizing the utilization of complex psychopharmacological regimens with likely drugdrug interactions and dependence as well as empowering people to manage their daily lives without reliance on their physicians and prescribed medications. To our knowledge, this study is the first of its kind to use a generalizable sample of people with acute psychiatric illnesses; its main focus was to elicit the participants’ attitudes concerning the efficacy of their sleep medications and also non-pharmacological strategies to manage sleep. Surprisingly, given its relevance for quality of life, almost nothing has been written about the subjective sleep experience of people with psychiatric illness. Among the sparse literature in this area, the authors of one previous research report commented that side effects of medication may have a detrimental effect on sleep quality.27 Enhanced awareness of sleep problems experienced by patients with current psychiatric illness can aid clinicians’ work, providing an improved understanding of the dysfunctional attitudes and beliefs about sleep often held by these patients, a more concise characterization of patients’ sleep problems, and a reminder to reflect when considering pharmacological or non-pharmacological strategies to manage these sleep disorders. This study further highlights the importance of targeting sleep-related cognitions in the management of insomnia.24 Better elucidation of sleep disorders in patients with psychiatric illness can identify those patients who would benefit from a comprehensive sleep medicine consultation and assessment. This review should be completed before a psychotherapeutic approach is adopted. Although we did not find

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an association between the length of illness and dysfunctional beliefs in our study, it would be of interest to know whether the dysfunctional beliefs arose prior to the onset of the patients’ psychiatric illness or subsequently as part of its unfolding impact on their lives in general.

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