This article was downloaded by: [University of Chicago Library]On: 20 November 2014, At: 06:02Publisher: RoutledgeInforma Ltd Registered in England and Wales Registered Number: 1072954Registered office: Mortimer House, 37-41 Mortimer Street, London W1T 3JH, UK

The Journal of Genetic Psychology:Research and Theory on HumanDevelopmentPublication details, including instructions for authors andsubscription information:http://www.tandfonline.com/loi/vgnt20

Worry and Sleep Length Revisited:Worry, Sleep Length, and SleepDisturbance Ascribed to WorryWilliam E. Kelly aa Department of Counseling , University of Nevada , LasVegasPublished online: 30 Mar 2010.

To cite this article: William E. Kelly (2002) Worry and Sleep Length Revisited: Worry,Sleep Length, and Sleep Disturbance Ascribed to Worry, The Journal of GeneticPsychology: Research and Theory on Human Development, 163:3, 296-304, DOI:10.1080/00221320209598685

To link to this article: http://dx.doi.org/10.1080/00221320209598685

PLEASE SCROLL DOWN FOR ARTICLE

Taylor & Francis makes every effort to ensure the accuracy of all the information(the “Content”) contained in the publications on our platform. However, Taylor& Francis, our agents, and our licensors make no representations or warrantieswhatsoever as to the accuracy, completeness, or suitability for any purpose of theContent. Any opinions and views expressed in this publication are the opinions andviews of the authors, and are not the views of or endorsed by Taylor & Francis. Theaccuracy of the Content should not be relied upon and should be independentlyverified with primary sources of information. Taylor and Francis shall not be liablefor any losses, actions, claims, proceedings, demands, costs, expenses, damages,and other liabilities whatsoever or howsoever caused arising directly or indirectly inconnection with, in relation to or arising out of the use of the Content.

This article may be used for research, teaching, and private study purposes. Anysubstantial or systematic reproduction, redistribution, reselling, loan, sub-licensing,systematic supply, or distribution in any form to anyone is expressly forbidden.

Terms & Conditions of access and use can be found at http://www.tandfonline.com/page/terms-and-conditions

Dow

nloa

ded

by [

Uni

vers

ity o

f C

hica

go L

ibra

ry]

at 0

6:02

20

Nov

embe

r 20

14

The Journul qj' Genetic. Psychologyv 2002. 163(3), 296-304

Worry and Sleep Length Revisited: Worry, Sleep Length, and Sleep Disturbance

Ascribed to Worry

WILLIAM E. KELLY Departttient of Counselitig

University of Nevada, Las Vegas

ABSTRACT. The author administered university students ( N = 222; I52 women, 70 men) the Worry Domains Questionnaire (F. Tallis, G. C. L. Davey, &A. Bond, 1994) and a newly constructed scale (the Sleep Disturbance Ascribed to Worry Scale) to measure sleep dis- turbance attributed to worry. To revisit previous studies (i.e.. E. Hartmann. F. Baekeland, & G. R. Zwilling, 1972; S. J . H. McCann & L. L. Stewin, 1988) that suggested that sleep length was positively related to worry. the author also asked the students a question about habitual sleep length. The results indicated that worry and sleep disturbance attributed to worry were negatively related to sleep length. A regression analysis revealed that worry was significantly negatively related to habitual sleep length irrespective of sleep distur- bance ascribed to worry.

Key words: sleep disturbance, sleep length, worry

RECENT STUDIES of individual differences i n sleep length have indicated that individuals who habitually sleep 6 hr or fewer every 24 hr (short sleepers), as compared with those who sleep 9 hr or more every 24 hr (long sleepers), are more likely to be neurotic, demonstrate less creativity, report more hallucinations, endorse more eating disorders, and perform more poorly academically (Hicks, Guista, Schretlen, & Pellegrini, 1980; Hicks & Rozette, 1986; Kelly, Kelly, & Clanton, 2001; Kumar & Vaidya, 1982; Soper, Kelly, & Von Bergen, 1997). Research has also been conducted on mood states associated with sleep length. Kumar and Vaidya (1984) administered an anxiety scale to 25 long sleepers and 25 short sleepers randomly selected from a sample of 500 undergraduate students. The results indicated that short sleepers reported significantly more anxiety than did long sleepers.

Address correspondence to Williarir I?. Kelly, ,tho 1.5 now at the Grorlrmtc~ Dqmrtrnent of Cotmseling, George Fox University, Portlond Center, 12753 S. W 68th Avenue, Portlund, OR 97223; rvkelly@gc,orRef~x.edu (i)-niuil).

296

Dow

nloa

ded

by [

Uni

vers

ity o

f C

hica

go L

ibra

ry]

at 0

6:02

20

Nov

embe

r 20

14

Kelly 297

It has been posited that the lower levels of cortical arousal of short sleep- ers may influence their psychological rnakeup and symptomatology (Skinner, 1983; Soper et al., 1997). Specifically, short sleepers may compensate for lower levels of cortical arousal with increased levels of cognitive activity. This sug- gestion has been partially supported by other research. Coursey, Buchsbaum, and Frankel (1975) found that short sleepers demonstrated lower levels of sen- sory response and performed worse on a perceptual-motor task, both of which suggested lower levels of cortical arousability (Banich, 1997). The brain appears to combat decreases in arousability by using compensatory strategies and plasticity, or flexibility (Banich; Howard, 1994: Salthouse, 1991). This point illustrates the resiliency of the human brain and its attempts to activate itself in instances of damage and lower levels of activity. It seems likely, then, that short sleepers would manifest cognitive symptoms to compensate for low cortical arousal. Soper et al. (1997) argued that their findings of increased hal- lucinations among short sleepers supported this hypothesis.

In addition to hallucinations, another potential cognitive symptom of lower cortical activity is worrying. It has been posited that worry serves as a stimu- lant during periods of decreased activity, such as boredom (Kelly & Markos, 2001). Moreover, worry has been associated with increased levels of cortical activity (Borkovec, Shadick, & Hopkins, 1991). Thus, i t is possible that short sleepers, who have decreased levels of cortical arousal, would show an increase in worry as their brain attempts to increase cortical activity. Interestingly, how- ever, previous researchers have found just the opposite-that worry, loosely defined, was reported more often by long sleepers.

Nearly 3 decades ago, Hartmann, Baekeland, and Zwilling (1972) con- ducted a pioneer study examining individual differences among 28 short sleep- ers and 24 long sleepers. One primary finding was that long sleepers were described as “worriers” and were psychologically less healthy, whereas short sleepers were psychologically healthy. The research reviewed previously using larger, more diverse samples, however, indicated the opposite: that short sleep- ers are psychologically less healthy than long sleepers. Only one subsequent study has been published examining sleep length and worry. McCann and Stewin (1988) administered to 101 undergraduate students a sleep-length pref- erence question and a Likert-type single-item assessment of individuals’ status as worriers. The results indicated a modest, but significant, positive correlation between worrier status and sleep preference.

Although there is some consistency between the Hartmann et al. (1972) and McCann and Stewin ( 1988) studies, there are methodological inconsis- tencies and problems with these studies. For instance, whereas Hartmann et al. found that long sleepers scored higher on a measure of nervousness and anx- iety, no definition or standardized measure of worry was used. Instead, the authors merely described nervousness and anxiety as worry. More recent find- ings, however, indicate that worry and anxiety are separate constructs (Davey,

Dow

nloa

ded

by [

Uni

vers

ity o

f C

hica

go L

ibra

ry]

at 0

6:02

20

Nov

embe

r 20

14

298 The Journul of Genetic Psychology

1992; Davey, Hampton, Farrell, & Davidson, 199 I ) . Furthermore, the partici- pants appear to have been limited to men recruited from newspaper advertise- ments, nearly half of whom were eliminated by the researchers prior to data analyses because of sleep irregularities, because they had been identified as average sleepers (sleeping between 6 and 9 hr per night), or because they had scored high on measures of psychopathology. Because of the quantity of par- ticipant deletions, however, i t is difficult to understand what population the results represent.

McCann and Stewin (1988) assessed worry using only a single-item assessment and reported data of a sleep-preference assessment as opposed to a habitual-sleep-length assessment. Hence, the samples and sleep-length assessments of these studies were not consistent. In addition, the samples of both studies were small. One potential methodological problem with both of these studies is the lack of a reliable, valid assessment of worry and a measure of sleep disturbance related to worry. Previous studies have implicated cogni- tive activity as a source of sleep disturbance, especially insomnia, and sleep reduction (Nicassio, Mendlowitz, Fussell, & Petras, 1985; Watts, Coyle, & East, 1994).

An important element in the discussion of sleep length and worry is the lack of a cause-effect relationship regarding whether worriers are at risk of developing sleep disturbances or having specific habitual sleep lengths, or whether individuals with sleep disturbances or certain habitual sleep lengths are more likely to worry. Thus, it could be argued that worriers report less sleep because they are often unable to sleep because of worrying, rather than that short sleepers tend to compensate for suboptimal cortical arousal by worrying. My purpose in the present study, therefore, was to clarify the relationship between worry and sleep length in a college-student population by investigat- ing further the relationship between a reliable, valid measure of worry and habitual sleep length and the possible effects on this relationship by sleep dis- turbance ascribed to worry. For the latter question, it was necessary to devise a scale to measure sleep disturbance attributed to worry. Therefore, I attempted to develop a brief scale to measure sleep disturbance ascribed to worry and to investigate the relationships among habitual sleep length, the Sleep Disturbance Ascribed to Worry Scale (SAW), and a measure of worry.

Because of possible methodological problems with the Hartmann et al. (1972) and McCann and Stewin (1988) studies, as well as the preponderance of research findings indicating that short sleepers are more anxious and less psychologically healthy (see previous review), I expected that high scores on a reliable, valid measure of worry would be reported more by short sleepers than by long sleepers. Considering the notion that short sleepers compensate for sub- optimal cortical arousal through cognitive activities, I expected that individu- als who worry more would endorse less sleep regardless of sleep difficulties related to worry.

Dow

nloa

ded

by [

Uni

vers

ity o

f C

hica

go L

ibra

ry]

at 0

6:02

20

Nov

embe

r 20

14

Kelly 299

Method

Participants

Participants included 222 students (152 women, 70 men) enrolled in under- graduate and graduate human services courses at a midsized U.S. university. The mean age of the sample was 24.4 years ( S D = 8.0), with ages ranging from 18 to 65 years. There was no significant difference between the genders on age, t (220) = .61, p = S 4 . The majority of participants identified themselves as Cau- casian (66%). Other ethnicities included African American (lo%), Latino (lo%), and Asian American ( 1 1%). Five (2%) identified their ethnicities as “other.” Two respondents ( 1 %) did not identify their ethnicities.

ltistriinients

The Sleep Disturbance Ascribed to Worry (SAW) Scale. Because no scales specif- ically measuring sleep disturbance related to worry could be located at the time of this study, I developed the SAW for the present study as a brief instrument to measure sleep disturbances ascribed to worry. Previous literature indicated that the predominant sleep disturbance associated with worry was insomnia (e.g.. Nicassio et al., 1985; Watts et al., 1994). Hence, insomnia was the primary sleep disturbance evaluated and used in developing this scale. I used the following pro- cedure to develop the SAW: After reviews of the criteria for insomnia in the Diagnostic and Statistical Manual of Mental Disorders (fourth edition; DSM-IV; American Psychiatric Association, 1994), the pertinent literature on sleep distur- bance and worry, and Coren’s (1988) Insomnia Scale, I developed 5 items assess- ing the attribution of sleep disturbance to worry, effects of worry on sleep, and frequency of sleep disturbance ascribed to worry. The result was a 5-item ques- tionnaire that I administered by asking participants to respond to each item using an 1 I-point anchored-response scale (0 = never, 10 = very o f e n ) . Higher scores on the SAW indicate more sleep disturbance ascribed to worry.

Worry Domains Questionnaire (WDQ). The original WDQ (Tallis, Eysenck, & Mathews, 1992) included 30 items assessing six domains of worry. However, one domain (social concerns) was found to be highly related to social desirability. Therefore, the 25-item WDQ presented by Tallis, Davey, and Bond (1994) was used for this study. The 25-item WDQ measures a tendency to worry across five general worry domains: (a) relationships, (b) lack of confidence, (c) aimless future, (d) work-related, and (e) financial. WDQ items were presented with a 5- point Likert-type scale on which individuals described the extent (not at all to extremely) to which their experience was in agreement with individual items. I summed responses from the appropriate items to create a total WDQ score. Higher scores denote more worry. Test-retest reliability ( r = .79 after 4 weeks),

Dow

nloa

ded

by [

Uni

vers

ity o

f C

hica

go L

ibra

ry]

at 0

6:02

20

Nov

embe

r 20

14

300 The Journul ut Genetic Psychology

internal consistency (a = .92), and validity of the WDQ have been found to be satisfactory (Tallis et al., 1994).

Sleep length. I provided sleep length estimates as a continuous variable by using the method of Kumar and Vaidya (1984), whereby participants are asked to write the amount of time, in hours and minutes, that they habitually sleep, on average, in every 24-hr period.

Procedure

After the participants gave informed consent, they were administered the WDQ, SAW, and sleep length question in random order. As a validity check for the SAW, 46 of the participants were also asked to respond to the following question: “Use the following scale to describe the general quality of your sleep.” The partic- ipants responded to this question on an 1 I-point Likert-type scale ranging from awful to great. A demographics survey that solicited information about the partic- ipants’ age, gender, and ethnicity was also completed. The participants completed the questionnaires in a group setting. Specific information regarding the nature of the study was not disclosed until the participants had returned the questionnaires.

Results

Properties of the SAW

To explore the factor structure of the 5 SAW items, I calculated a principal components factor analysis. This analysis resulted in a single factor accounting for 62.5% (eigenvalue = 3.12) of the systematic variance. SAW items, their respective factor loadings, and means and standard deviations are presented in Table I . The internal consistency of the SAW was also explored. The coefficient alpha of the 5 items was 3 5 . Age was not correlated with SAW scores; r = -.01, p = .79. There was a significant difference between the genders for SAW scores, t(220) = 3.03, p < .003, with women (M = 19.3) endorsing higher SAW scores than men (M = 14.8). A one-way analysis of variance (ANOVA) revealed no sig- nificant difference in SAW scores among ethnicities, F(5, 214) = 1.23, p = .29. The correlation between the quality of sleep question and SAW scores was sig- nificant, r = -.37, p < .01, indicating that sleep disturbance resulting from worry negatively affects quality of sleep.

WDQ, Sleep Length, and SAW Analyses

Pearson correlations among WDQ scores, SAW scores, and sleep length were calculated. Sleep length was significantly negatively related to both WDQ ( r = -.24, p < .01) and SAW scores ( r = -.20, p < .01). SAW scores and WDQ

Dow

nloa

ded

by [

Uni

vers

ity o

f C

hica

go L

ibra

ry]

at 0

6:02

20

Nov

embe

r 20

14

Kelly 301

TABLE 1 Means, Standard Deviations, and Factor Loadings for SAW Items

Item Factor

M SD loading

1. tiow often do you awaken early from your normal sleeping time and are completely unable to return to sleep because of worry'? 3.39 2.47 .79

2. How often are you unable to stop worrying at bedtime? 4.09 2.75 .71 3. How often can you not get to sleep for several

minutes because of worry'? 4.25 2.94 .74 4. How often do you awake from sleep worrying'? 2.81 2.59 .87 5. During your usual sleep time, how often do you

awaken and are unable to return to sleep for several minutes because of worry? 3.30 2.58 .83

Total scale 17.84 10.50 ~~

Nore N = 222 SAW = Sleep I)i\turbancu Aqcnbed to Worry Scdle

scores were also significantly related ( r = .42, p < .O I ) . Next, gender differences in WDQ scores and sleep length were explored. No significant gender differences were found for WDQ scores, t(220) = I .63, p = .12, or sleep length, t(220) = 1.29, p = .20. Also, no significant correlations were observed between age and sleep length ( r = -.0S. p = .42) or age and WDQ scores ( r = -.09, p = .18).

Because of the significant gender differences found for SAW scores, it was necessary to identify any significant Gender x SAW interactions on WDQ scores and sleep length prior to further analyses involving these variables. Hence, I used a median split to create a high and low group on the basis of SAW scores. I cal- culated two separate 2 (gender) x 2 (SAW group: high or low) ANOVAs to iden- tify significant interactions between gender and SAW scores on sleep length and WDQ scores. The first ANOVA revealed no significant interaction between SAW scores and gender for sleep length, F( 1, 2 18) = .82, p = 3 7 . The second ANOVA also did not reveal il significant Gender x SAW score interaction for WDQ scores, F( I , 2 18) = I .OS, p = .3 1 . Thus, subsequent analyses involving SAW scores, WDQ scores, and sleep length were analyzed irrespective of gender.

I calculated a simple regression using sleep length as the criterion and WDQ scores as the predictor variable to test the relationship between worry and habitual sleep length. WDQ scores accounted for 6% of the variance in sleep length, which was significant, F( I , 220) = 13.50, p < . o (X) I . An analysis of the beta weights indi- cated a negative relationship between worry and sleep length (p = -.24).

I calculated a multiple regression to explore the influences of SAW scores o n the relationship between worry and sleep length, using sleep length as the

Dow

nloa

ded

by [

Uni

vers

ity o

f C

hica

go L

ibra

ry]

at 0

6:02

20

Nov

embe

r 20

14

302 The Journul of Generic Psychologv

criterion and SAW and WDQ scores as predictor variables. To account for SAW variance in the relationship between sleep length and worry, I forced SAW scores to enter first in the equation. SAW scores accounted for 4% of the vari- ance in sleep length, which was significant, F( I , 220) = 9.02, p < .003. The beta weight indicated a negative relationship between sleep disturbance ascribed to worry and sleep length ( p = -.20). On Step 2, WDQ scores were entered and accounted for an additional 3% of the variance, which was also significant, F( 1, 219) = 7.02, p < ,009, and remained negative ( p = -. 19).

Discussion

The results of the present study indicate that worry is negatively related to habitual sleep length. In other words, individuals who sleep less tend to worry more often. This finding is not consistent with that of previous researchers (i.e., Hartmann et al., 1972; McCann & Stewin, 1988) who found that worry was pos- itively related to sleep length. However, the results of the present study are con- sistent with those of other researchers that indicated that individuals who habit- ually sleep less are less psychologically healthy and more anxious (Hicks & Rozette, 1986; Kumar & Vaidya, 1982, 1984; Soper et al., 1997).

It also appears that the negative relationship between sleep length and worry exists irrespective of sleep disturbances attributed to worry. Thus, the lower sleep lengths of worriers do not appear to be the result of only sleep disturbance due to worrying. As postulated by previous researchers (i.e., Skinner, 1983; Soper et al., 1997). it may be that the less active neural systems of short sleepers tend to stim- ulate themselves by creating additional sensory and cognitive activity through wor- rying, but not necessarily during times of sleep. Further research is needed to sub- stantiate this claim. Measures of excitement seeking and need for cognition as well as neuropsychological measures might help researchers explore the cortical arousal explanation of worry among short sleepers. Furthermore, the relatively low percentage of variance accounted for by SAW and WDQ scores suggests that addi- tional variables may be involved in determining habitual sleep length.

The significant relationships found between the SAW and the WDQ, sleep length, and the sleep quality question provide some initial evidence for the valid- ity of the SAW and, thus, provide some credence to the findings of this study involving the SAW. Nevertheless, future researchers who use the SAW to exam- ine sleep disturbance attributed to worry should include additional measures to validate the SAW. Furthermore, a distinction has been drawn between transient and chronic sleep disturbance (Giesecke, 1987). Hence, future researchers should collect test-retest data on the SAW to determine whether it measures transient or chronic sleep disturbance attributed to worry.

The discrepancy between the results of the present study and the results of McCann and Stewin (1988) suggest that habitual sleep length and sleep length preference are separate constructs. Researchers should, therefore, investigate both

Dow

nloa

ded

by [

Uni

vers

ity o

f C

hica

go L

ibra

ry]

at 0

6:02

20

Nov

embe

r 20

14

Kelly 303

of these constructs in relation to worry. In addition, future research should also include additional measures of worry. The WDQ is coined as a measure of non- pathological worry (Tallis et al., 1992). Hence, it might be useful for researchers to include a measure of worry such as the Penn State Worry Questionnaire (Meyer, Miller, Metzger, & Borkovec, 1990), designed to assess pathological worrying. There may be differences in sleep length among nonpathological and pathological worriers. Also, sleep diaries should be considered as a measure of sleep length in addition to single-item measures of habitual sleep length.

REFERENCES

American Psychiatric Association. ( 1994). Diagnostic and statistical manual of mental disorders (4th ed.). Washington, DC: Author.

Banich, M. T. (1997). Neuropsychology: The neurul bascs of mental function. New York: Houg h ton Mi ftl in.

Borkovec, T. D.. Shadick. R. N., & Hopkins, M. (1991). The nature of normal and patho- logical worry. In R. M. Rapee & D. H. Barlow (Eds.), Chronic anxiety: Generalized anxiefy disordcJr and mixed anxiery-depression (pp. 29-5 I ) . New York: Guilford Press.

Coren, S. ( 1 988). Prediction of insomnia from arousability predisposition scores: Scale development and cross-validation. Behaviour Rcwarch and Therapy, 26(5), 415-420.

Coursey. R. D.. Buchsbaum, M., & Frankel, B. L. ( 1 975). Personality measures and evoked response in chronic insomniacs. Journal qfADnonna1 Psychology, 84(3), 239-249.

Davey, G. C. L. (1992). A comparison of three worry questionnaires. Behaviour Research and Therapy, 3I(I). 51-56.

Davey, G. C. L., Hampton. J., Farrell, J., & Davidson. S . (1991). Some characteristics of worrying: Evidence for worrying and anxiety as separate constructs. Personality and Individual Differences, 13(2), 133-147.

Giesecke, M. E. (1987). The symptom of insomnia in university students. Journal ofAmer- ican College Health, 35(5), 2 15-22 1.

Hartmann. E.. Baekeland, I:., & Zwilling. G. R. (1972). Psychological differences between long and short sleepers. Archives of General P.ry-hiatn, 26, 463468.

Hicks, R. A,, Guista M., Schretlen, D., & Pellegrini, R. J. (1980). Habitual duration of sleep and divergent thinking. Psychologiciil Reports. 46, 426.

Hicks, R. A, , & Rozette, E. (1986). Habitual sleep duration and eating disorders in college students. Percqmal and Motor Skills, 62, 209-210.

Howard. P. J . (1994). The owner’s manual f o r the Drain: Evetyday applications from mind- brain research. Austin, ‘TX: Bard Press.

Kelly, W. E., Kelly, K. E., & Clanton, R. C. (2001). The relationship between sleep length and grade-point average among college students. College Student Journal, 35( 1 ), 84-86.

Kelly, W. E., & Markos, P. A. (2001). The role of boredom in worry: An empirical inves- tigation with implications for counsellors. Guidance and Counselling, 16(3), 8 1-85.

Kumar, A,, & Vaidya, A. K. (1982). Neuroticism in short and long sleepers. Perceptual and Motor Skills. 54, 962.

Kumar, A,, & Vaidya, A. K. (1984). Anxiety as a personality dimension of short and long sleepers. Journal of Clinical Psychology, 40, 197-198.

McCann, S. J . H., & Stewin. L. L. (1988). Worry, anxiety, and preferred sleep length. The Journal of Genetic Psychology, 149(3). 41 3418.

Meyer, T. J . . Miller. M. L., Metzger. R. L., & Borkovec, T. D. (1990). Development and validation of the Penn State Worry Questionnaire. Behaitiour Research and Therapy, 28, 481495.

Dow

nloa

ded

by [

Uni

vers

ity o

f C

hica

go L

ibra

ry]

at 0

6:02

20

Nov

embe

r 20

14

Nicassio, P. M., Mendlowitz, D. R., Fussell, J. J., & Petras. L. (1985). The phenomenolo- gy of the pre-sleep state: The development of the pre-sleep arousal scale. Behaviour Research and Therapy, 23(3), 263-27 1.

Salthouse, T. A. (1991). Expertise as the circumvention of human processing limitations. In K. A. Ericsson & J. Smith (Eds.), 7hward a general t h e o n ofexperrise: Prospects and limits (pp. 286-300). New York: Cambridge University Press.

Skinner, N. F. (1983). Neuroticism, extraversion, and sex differences in short and long sleepers. Psychological Reports, 53, 669-670.

Soper, B.. Kelly, W. E., & Von Bergen. C. W. (1997). A preliminary study of sleep length and hallucinations in a college student population. College Student Journal, 31(2),

Tallis, F., Davey, G. C. L., & Bond, A. (1994). The Worry Domains Questionnaire. In G. Davey & F. FdlhS (Eds.), Worning: Perspectives on theon, assesstnent and treatment (pp. 286297) . New York: Wiley.

Tallis, F., Eysenck, M., & Mathews, A. (1992). A questionnaire for the measurement of nonpathological worry. Personality and Individual Differences. 13. 161-1 68.

Watts, F. N., Coyle, K., & East, M. P. (1994). The contribution of worry to insomnia. Brirish Journal of Clinical Psychology, 33(2), 2 1 1-220.

272-275.

Received Ju1.v 5, 2001

Dow

nloa

ded

by [

Uni

vers

ity o

f C

hica

go L

ibra

ry]

at 0

6:02

20

Nov

embe

r 20

14