telephone validation of the quality of life in epilepsy inventory-89 (qolie-89)

Epilrpsiu. 40(l):Y7-106. l Y Y 9 Lippincot( Williams & Wilkina, Philadelphia 0 International League Against Epilepsy

Clinical Research

Telephone Validation of the Quality of Life in Epilepsy Inventory-89 (QOLIE- 89)

Nancy Kline Leidy, Anne Elixhauser, Anne M. Rentz, *Robert Beach, ?John Pellock, $Steven Schachter, and §Mary Kay Willian

Center for Health Outcomes Research, MEDTAP International, Inc., Bethesda, Maryland; *Department of Neurology at the University cf North Carolina Hospituls in Chapel Hill, North Carolina; f Comprehensive Epilepsy Institute at the Medical

College oj Virginia of Virginia Commonwealth University in Richmond, Virginia; $Comprehensive Epilepsy Center at Beth Isruel Deaconess Medical Center in Boston, Massachusetts; and SAstra Merck, Inc.

Summary: Purpose: To assess the psychometric properties of the Quality of Life in Epilepsy Inventory-89 (QOLIE-89) administered via telephone and to compare these properties with data gathered through self-administration.

Methods: A study of 139 patients with epilepsy was under- taken at three clinical sites in the United States. Patients participated in both telephone interview (T) and self-administration (S). Order effect was controlled through randomization (T-S and S-T). Twenty-eight S-T subjects participated in an assessment of the 2-week reproducibility of telephone interviews.

Results: Internal consistency and test-retest reliability levels of the QOLIE-89 overall score were very high across method of administration (T = 0.98; S = 0.98; ICC of T = 0.96). Scores

were significantly related to mood (Profile of Mood States, r = -0.76, for both methods, p < 0.001) and two indicators of epilepsy severity (seizure frequency in the past month, T: r = 0.52, p < 0.0001; S: r = 0.54, p < 0.0001; days since last seizure, T: r = 0.28, p < 0.001; S: r = 0.25, p < O.Ol), with no significant differences in coefficients by method of administration. Performance of the measure was consistent for patients with unimpaired and impaired memory, using the River- mead Behavioural Memory Test, and across level of education.

Conclusions: Results of this study indicate telephone interview is a viable option for evaluating HRQL in persons with epilepsy and support the reliability and validity of the QOLIE- 89 regardless of method of administration. Key Words: Epi- lepsy-Outcomes-Quality of life-Methodology .

The quality of life of people with epilepsy can be diminished by seizures, the side effects of antiepileptic drugs (AEDs), and the negative social consequences of the condition. To understand the impact and effectiveness of treatment alternatives on the lives of those with epilepsy, we must look beyond seizure frequency to patients’ physical, psychological, and social well-being, that is, their health-related quality of life (HRQL).

There are several viable options for evaluating HRQL in patients with epilepsy, including the Epilepsy Surgery Inventory-55 (ESI-55) (1); the Liverpool Assessment Battery (2), and the Quality of Life in Epilepsy Inventory (QOLIE-89, QOLIE-3 1, and QOLIE-10) (3), among oth- ers (4-6). The QOLIE-89 is particularly suited to descriptive studies and clinical trials for several reasons: First, it is a comprehensive instrument composed of domains and subscales that correspond to the multiple di-

Accepted June 25, 1998. Address correspondence and reprint requests to Dr. N. Kline Ixidy

at Center for Health Outcomes Research, MEDTAP International, lnc., 7101 Wisconsin Avenue, Suite 600, Bethesda, MD 20814, U.S.A.

mensions of HRQL. Second, the foundation of the instrument, the ESI-55, has a long history as a surgical outcome measure with strong evidence of reliability and validity. Third, the Medical Outcomes Study Short- Form-36 (SF-36), the instrument’s generic core, has demonstrated sensitivity to change in other patient populations (7). Inclusion of the SF-36 enables investigators to compare their sample data with published norms and interpret treatment effects in the context of published efficacy data for other disease states. Finally, the instrument summarizes HRQL in uniform subscale, domain, and overall scores, which standardizes the data collected across studies, simplifies interpretation, and facilitates comparisons across clinical trials (8).

Traditionally, HRQL data have been gathered through in-person interview and self-completed questionnaire. In-person interviews can be expensive, and the require- ment for clinic or home visit can be burdensome to patients and clinic staff. Self-completed questionnaires have disadvantages as well, including low response rates, unmonitored completion, and higher frequency of miss-

97

98 N. K. LEIDY ET AL.

ing data. Both methods require training, time, and com- mitment of clinic personnel to assure complete and ac- curate data.

Telephone administration of HRQL instruments has certain advantages, particularly in long-term prospective studies and clinical trials (8,9). It can offer greater con- trol over timing of administration, more precision through the use of fewer trained interviewers and direct monitoring, and reduced clinic and patient burden ( 10,ll) . Telephone-administered questionnaires also contain virtually no missing data (1 1,13).

Because method of administration can have an impact on the reliability and validity of an instrument (10-13), it is critical to validate a new method before its use in an investigational or clinical setting. The purpose of this study was to evaluate the psychometric properties of the Quality of Life in Epilepsy (QOLIE-89) Inventory administered by telephone and to compare these properties with data gathered through self-administration, as origi- nally designed and tested (3,14). Score consistency and internal consistency reliability across method of administration and 2-week reproducibility of responses ac- quired via telephone were assessed. Construct validity was evaluated in terms of the consistency of the instrument’s relation to indicators of mood and epilepsy severity. Because patients with epilepsy can have memory deficits, we compared the performance of the instrument in patients with unimpaired and impaired memory, and then compared mean scores across memory groups, hy- pothesizing that those with memory impairment would have significantly poorer HRQL. Finally, data were gathered on the time required for administration and subject preferences regarding mode of administration.

METHODS

Sample Patients were recruited through three epilepsy centers

in the United States, thus enhancing generalizability while facilitating enrollment rate. Convenience sampling was used, with eligible patients identified by clinic personnel through patient records and clinic visit. Patients were contacted and invited to participate in a study of life quality in persons with epilepsy.

To optimize comparability with the original QOLIE- 89 validation study, inclusion and exclusion criteria ap- proximated those of Devinsky et al. (3): 18 years of age or older; diagnosis of epilepsy for a minimum of 1 year; prescribed AED at the time of recruitment; and seizure free for 24 h or returned to baseline functioning at the time of the interview. Patients were excluded if they could not complete the instruments for reasons of blind- ness, hearing impairment, or other physical disability precluding participation; could not speak or read English sufficiently to complete the questionnaires; had neuro-

logic or psychiatric disorders that would impair judg- ment or affect quality of life beyond the effects caused by epilepsy (e.g., dementia, mental retardation, stroke, severe head injury, tremor, schizophrenia, current clinical depression); were taking any of the following medications known to affect the central nervous system (other than AEDs): anxiolytics, sedatives, hypnotics, antidepressants, antipsychotics, narcotics, and tranquilizers (excluding those taken on an “as needed” basis, such as sleeping medication); or had undergone any form of epilepsy surgery.

Measures

Quality of Lqe in Epilepsy Inventoi-y-89 The QOLIE-89 consists of 89 items that form 17 sub-

scales representing four dimensions or domains of HRQL (3,15,16). The Medical Outcomes Short Form-36 (SF-36), the generic core, is supplemented by 53 items reflecting the unique challenges facing adults with epilepsy. The QOLIE-89 has been subjected to previous psychometric testing, including assessments of internal consistency, reproducibility, content validity, and construct validity (1,3).

Standardized procedures are used to convert each item composing the QOLIE-89 to a 0-100 score, with higher scores indicating better HRQL. Subscale scores are computed by averaging across all items within the subscale, with the number of completed items serving as the divi- sor (17). The overall score is a weighted sum of the individual subscale scores (17). To calculate domain scores, the factor-based standardized regression coefficients, or weights (3) for subscales within a factor were summed. Each weight was divided by this sum to obtain a standardized weight. Each patient’s subscale score was multiplied by its respective standardized weight. The standardized weight scores were then summed across subscales composing the domain.

Profile of Mood States (POMS) It has been suggested that mood disturbance in persons

with epilepsy is related to impairment in HRQL, and conversely, that HRQL impairment may contribute to mood disturbance. It also has been suggested that mood, as an aspect of mental health, is a component of HRQL. Previous studies have found moderate to strong correlations between the POMS, the QOLIE-89 (3), and EST-55 (1). Thus moderate to strong correlations between the POMS and the QOLIE-89 across method of administration in this study would provide evidence of the consistency of the HRQL instrument’s validity.

The POMS is a widely used self-administered instrument with strong evidence of reliability and validity (1-3,18-20). The 65-item instrument assesses six dimensions: depressionldejection, tensionlanxiety, fatigue/ inertia, confusionhewilderment, angerlhostility, and

TELEPHONE VALIDATION OF THE QOLIE-89 99

vigorhctivity. I t e m are adjectives that describe various affective states over the past week. Patients are asked to rate the extent to which they have been experiencing each state on a 5-point Likert scale, from not at all to extremely. Scale scores are derived by summing across the appropriate items. With the exception of vigor, higher scores indicate greater mood disturbance. The total score is formed by summing across five subscale scores and subtracting the vigor score. The POMS was self-administered only, during the clinic visit. The internal consistency reliability estimates for the POMS scales in this study ranged from 0.77 to 0.94 and were similar to those reported for normative samples (1 8).

Rivermead Beliuvioural Memory Test (RBMT) Patients with epilepsy often experience memory prob-

lems that could contribute to poor HRQL and affect the capacity reliably and validly to complete a structured telephone interview. Thus the psychometric properties of the QOLIE-89 were examined by method of administration in patients with normal and impaired memory function, evaluated through the RBMT (21). The RBMT is administered by a trained clinical or lay interviewer and takes -20 min to complete. Subjects are asked to participate in 12 tasks, each reflecting different aspects of behavioral memory, including remembering names, ob- jects, appointments, faces, and prose. Tasks are scored on a scale of 0 to 2; a total score is derived by summing across all tasks, with higher scores indicating less memory impairment. The developers suggest cut points for grouping patients into four categories: severely impaired (0-9), moderately impaired (10-1 6), poor memory (17-21), and normal memory (22-24).

The RBMT was selected as the measure of behavioral memory function for several reasons. First, the objective of this aspect of the study was to evaluate whether patients with memory impairment could provide consistent and reliable responses to a telephone interview of HRQL. We were seeking an instrument with a generalized or dichotomous characterization of memory impairment, rather than a highly sensitive indicator of cognitive impairment. Second, the RBMT has been shown to be a valid and reliable indicator of memory impairment in other populations (22) and has been recommended for use in patients with epilepsy (23). Third, it is easy to administer and less costly than neuropsychological bat- teries. Finally, an intent of this study was to assess the performance of the QOLIE-89 in light of the day-to-day memory difficulties of patients with epilepsy, rather than against traditional neuropsychological tests (24,25).

An Americanized version, available from the developers, was used in this study. Clinical nurse coordinators at each site were trained to administer the RBMT, which was performed during the patient’s clinic visit. The in- terrater reliability for training interviewers in the RBMT

in this study was set at 0.90. The internal consistency reliability estimate for the RBMT in this study was 0.71.

In our sample, the mean and standard deviation of RBMT scores were between those of brain-damaged patients (including head injured, stroke, subarachnoid hem- orrhage), with a reported mean of 15.29 f 6.42 and “normal” controls (mean, 22.19 ? 1.92) (21). Just over half of the patients (57.2%) had normal or poor memory (17-24) and were assigned to the unimpaired group, whereas the remaining patients had severe to moderate impairment (0-1 6) and were assigned to the impaired group for the analyses.

Clinical indicators Study personnel at each site reviewed the medical rec-

ord to obtain information on seizure type, current AED regimen, other medications, and number of unsuccessful AEDs. Patients were asked to provide data on seizure history (age of onset, number of seizures in the past month, date of most recent seizure); history of treatment for depression; and presence of other comorbid conditions. Epilepsy severity was assessed by using four variables: number of AEDs that failed, number of current AEDs, number of days since last seizure, and number of seizures during the past 4 weeks.

Demographic information, patient preference, and length ofadministration

Patients were asked to provide demographic data and information regarding their preferences for mode of administration. Time required for administration was estimated based on start and stop times recorded by study personnel.

Study design All subjects completed both self (S)- and telephone

(T)-administered questionnaires and were randomized into one of two groups: telephone interview first, followed by self-administration in the clinic (T-S) or self- administration in the clinic first, followed by telephone interview (S-T). The two administrations occurred within 2 to 8 days (mean, 4 * 1.5). To evaluate reproducibility, half the S-T group was randomized to receive a second telephone interview (S-T-T) 2 weeks later (mean, 14 +- 1.5 days; range, 10-16 days).

No changes were made in the QOLIE-89 for purposes of telephone administration. All patients were given a booklet containing the response options specified in the self-administered instrument for use during telephone administration and were queried about the presence of the booklet before initiating the interview.’ All interviews were conducted by trained personnel at a central- ized professional survey research center. The research protocol was approved by the appropriate institutional

’ Booklet is available on request from the corresponding author.

Epilrpsia, Vol. 40, No I . 1999


review boards; subjects provided verbal informed consent at the time of telephone enrollment, with written consent obtained during the clinic visit. Patients were reimbursed $25.00 per interview for their time and travel-related expenses.

Statistical analyses

Descriptive statistics Sociodemographic and clinical characteristics were

compared for the two groups (T-S and S-T) by using t tests and x 2 , as appropriate. A series of multiple- regression procedures were used to assess the effect of method (self vs. telephone), order of administration, and study site on QOLIE-89 score. Method effect was also evaluated in isolation through a series of exploratory post hoc tests: matched t test, Pearson’s correlation, and intraclass correlation, with no adjustments for multiple tests (p < 0.05). Floor and ceiling effects were computed to assess the proportion of respondents with the lowest and highest possible score for the QOLIE-89 by method of administration. Data also were examined for systematic differences in missing data.

Reliability Subscale internal consistency reliability levels (Cron-

bach’s alpha) were estimated within method of administration by using Cronbach’s formula for coefficient alpha. Mosier’s method for weighted composites was used to estimate the reliability of the domain and total scores (26). Coefficients were compared across method by using the Feldt approach for related samples, where the test statistic W is equal to (1 - r,)/( 1 - r2), and is distributed as the product of two independent central F variables and approximates a single F with N , - 1 and N2 - 1 degrees of freedom (27-29). Because this distribution is dependent on the number of items, subsample estimates are subject to error and should be considered exploratory.

To assess reproducibility of telephone-administered instruments, intraclass correlation coefficients (one-way random effects models) were computed for patients in the (S)-T-T group for whom there were no significant intervening life events between the two telephone administrations. These results were supplemented by paired t test and Pearson’s correlation coefficients to describe the location and nature of any differences between the two observations.

Validity Pearson product-moment correlation coefficients

were used to describe the relation between the POMS and the QOLIE-89 and between clinical indicators of epilepsy severity and the epilepsy domain subscales, epilepsy domain, and overall scores of the QOLIE-89. To evaluate the stability of the relation across method of administration, coefficients were compared by using the

formula for inferences about px, - pxz by using dependent samples (30).

The stability of the relation between seizure frequency and QOLIE-89 by method of administration was tested by using analysis of variance (ANOVA) procedures in which the domain and overall telephone scores served as the dependent variable and seizure frequency (dichotomous: none to five seizures; six or more seizures in the past 4 weeks) and self-scores served as independent variables. The interaction tested whether the relation between seizure frequency and the QOLIE-89 score varied by method of administration. If the interaction term was not significant, it was removed from the equation, and the model was rerun to test for the main effect of seizure frequency on HRQL. A post hoc exploratory analysis also was performed to test the sensitivity of the epilepsy domain-seizure frequency relation with frequency categorized into four groups: 0, one to five, six to 30, a 3 0 in the past month.

The ANOVA procedures also were used to assess the stability of QOLIE-89 score by method of administration in patients with impaired and unimpaired memory. In this model, the interaction term tested whether the relation between self- and telephone-administration varied by level of memory impairment. A significant main effect for memory would indicate HRQL differed by level of memory impairment, as one would expect in a valid measure of HRQL.

Internal consistency reliability levels (Cronbach’s alpha) were estimated within behavioral memory group (unimpaired, impaired) by method of administration and compared across method by using the Feldt approach for related samples described previously. Correlation coefficients between the POMS and the QOLIE-89 also were compared across memory group.

Finally, ANOVA was used to assess the effect of education [high school graduate or less (n = 60) and some college or more (n = 76)], with the interaction term testing whether the relation between self- and telephone- administration varied by education. In this case, a significant main effect for education would suggest an un- derlying sociodemographic bias in the instrument.

RESULTS

Sample One-hundred forty-eight patients were enrolled in the

study; 139 completed at least two interviews. Half (n = 7 1 ; 5 1 %) were randomized into the group receiving telephone interviews first (T-S); half (n = 68; 49%) were assigned to the S-T group. Of the latter, 34 patients were randomized to receive a second telephone interview; 28 patients stated they experienced no significant life events between the two telephone interviews and were included in the reproducibility analyses. No significant differences

E p i k p w J . Vol. 40. No. 1. 1999

TELEPHONE VALIDATION OF THE QOLIE-89 I01

in sociodemographic or clinical characteristics were observed between the T-S and S-T groups (see Tables 1 and 2).

Descriptive statistics Descriptive statistics for the validation measures

(POMS and Rivermead) are shown in Table 3. Table 4 provides descriptive statistics for the subscales, domains, and overall scale scores of the QOLIE-89 by method of administration. No method or order effects were found in any subscale, domain, or overall scores. Statistically significant site effects were detected within the subscales of the mental health domain, consistent with the younger age and lower prevalence of a depression history for subjects at one of the sites. All subsequent analyses for method of administration were pooled across order and site.

Post hoc exploratory t tests comparing order of administration within method showed no statistically significant effects. Matched t tests comparing method of administration found two significant differences. Com- pared with the telephone-administered scores, health perceptions (a scale from the SF-36 with one item added)

TABLE 1. Sample demographic characteristics"

Characteri $tics

Age (Yr) Average income per person

in household ($) Gender

Male Female

Marital status Never married Married Separated, divorced, widowed

RaceEthnicity White Non-white

Educational attainment High school or less Some college or more

Employed full time Employed part time Not employed outside home

Yearly household income (n = 135)

Employment status

<$ 10,000 $1 0,000-$29,999 $30,000-$49,999 $50,000 or more

Current driver's license

Ever had a driver's license Driver's license revoked Insurance covers prescription

(n = 137)

drugs

S-T (n = 68)

T-S (n = 71)

38.4 (1 1.3) 15,346 (12,140)

24 (35.3) 44 (64.7)

27 (39.7) 31 (45.6) 10 ( 1 4.7)

58 (85.3) lO(14.7)

31 (45.6) 37 (54.4)

27 (39.7) 7 (10.3)

34 (50.0)

21 (31.8) 24 (36.4) lO(15.2) 11 (16.7) 31 (45.6)

20 (29.4) 13 (19.1) 51 (75.0)

38.5 (10.4) 15,880 ( 1 2,350)

15 (21.1) 56 (78.9)

36 (50.7) 25 (35.2) 10 (14.1)

53 (74.7) 18 (25.3)

30 (42.2) 41 (57.8)

22 (31.0) 13 (18.3) 36 (50.7)

21 (30.4)

13 (18.8) 12 (17.4)

23 (33.3)

35 (49.3)

16 (22.5) 14 (19.7) 54 (76.1)

Values expressed as means (SD) or number (%). " No significant differences at p < 0.05, using t tests and xz analysis,

as appropriate.

TABLE 2. Sample clinical characteristics" ~~

Characteristics

~~

S-T T-S (n = 68) (n = 71)

Age when epilepsy was diagnosed (yr) Number of AEDs taking currently Number of AEDs failed in the past Ever treated for depression (n = 138) Number of comorbidities

None One Two Three

4 weeks (n = 135) 0 seizures 1-5 seizures 6-30 seizures 3 I+ seizures

Number of seizures in the past

18.7 ( I 2.7) 1.9 (0.8) 3.4 (2.6) 20 (29.9)

48 (70.6) 9 (13.2)

6 (8.8) 5 (7.4)

21 (31.8) 23 (34.9) 16 (24.2) 6 (9.1)

17.4 (14.0) 2.0 (0.8) 3.9 (2.5) 18 (25.4)

52 (73.2) 4 (5.6) 8 ( I 1.3) l(9.9)

28 (40.6) 23 (33.3) 15 (21.7) 3 (4.4)

Values expressed as mean (SD) or number (To). AED, antiepileptic drug. 'I No significant differences at p < 0.05, using t tests and x2 analysis,

as appropriate.

was 2 points higher by self-administration (p = 0.04), and physical functioning (a scale taken directly from the SF-36) was 3 points lower (p = 0.03). Pearson's correlation coefficients and intraclass correlation coefficients between the telephone- and self-administered methods ranged from 0.67 to 0.92 for the individual subscales and domains and 0.94 for the overall QOLIE-89, indicating a high degree of correspondence between the two methods.

Floor and ceiling effects for the QOLIE-89 also are shown in Table 4. Ceiling effects ranged from 1 to 50% for self-administration and from 1 to 5 1 % for telephone administration. Across method of administration, most of the subscales with the largest ceiling effects (>25%) were generic SF-36 subscales: role limitations-emotional, role limitations-physical, physical function, and pain. A small portion of the sample scored the minimum, ranging from < 1 % to 9%. Fewer than 1 % scored the lowest and highest possible scores on the domains and the overall QOLIE-89.

The self-administered method resulted in at least one missing response for 54 of the 89 QOLIE items, whereas the telephone interview resulted in at least one missing response for only nine items. Item nonresponse was 0.9% for self-administered and 0.1 % for administration via telephone.

Reliability

Internal consistency reliability Table 5 presents information on the internal consis-

tency reliability of the QOLIE-89. There were three significant differences in internal consistency reliability between method of administration. Alpha (a) levels for the health discouragement and emotional well-being subscales were higher for telephone administration; for medication effects, the a was lower. There were no dif-

Epilepsia, Vol. 40, NO. I, 1999


TABLE 4. Descriptive stutistics and poor and ceiling effects for the QOLIE-89 by method .f administration

TABLE 3. Scores on mood and memory

Instrument Mean (SD)

Profile of Mood States" Tension-anxiety 32.7 (37.2) Depression-dejection 11.2 (7.4) Anger-hostility 12.0 (12.1 j Fatigue 9.0 (8.4) Confusion-bewilderment 9.4 (6.6) Vigor 9.1 (5.8) Total mood-disturbance score 16.9 (6.7)

Total standardized score 17.0 (4.1 j Unimpaired memory 79 (57.2) Impaired memory 59 (42.8)

" Cronbach's alpha for the total mood disturbance scale, 0.95. " Cronbach's alpha for the total standardized score, 0.71. N = 138; one patient chose not to complete the RBMT for reasons

unrelated to the study. Values expressed as mean (SD) or number (%),

Rivermead Behavioral Memory Testb

ferences by method of administration in the reliability of the domain or overall scales.

Reproducibility Table 5 also presents the results of analyses evaluating

the reproducibility of the QOLIE-89 administered by telephone. Intraclass correlation coefficients and Pearson coefficients were similar, varying by <0.009; there were no statistically significant differences in mean scores between the first and second telephone interviews.

Validity

Mood Pearson correlation coefficients between the POMS

total score and the QOLIE-89 subscales, domain, and

overall scores by method of administration are provided in Table 5. There were no significant differences by method of administration. The same held true for POMSl QOLIE-89 subscale-to-subscale correlations (not shown).

Epilepsy severity Correlation coefficients between clinical indicators of

epilepsy severity and QOLIE-89 scores by method of administration are provided in Table 6. Coefficients for telephone- and self-administered methods were not significantly different. The only subscale that correlated significantly with all epilepsy-severity indicators was the work-driving-social function subscale.

The interaction terms in the ANOVAs were not significant (F = 0.20; p = 0.66 for the overall score). Analyses without the interaction terms indicated that domain and overall scores were significantly lower for patients who had six or more seizures in the past 4 weeks compared with patients who had five or fewer seizures ( F = 291.1; p < 0.0001 for the overall score, see Ta- ble 7).

The post hoc exploratory analysis of the impact of seizure frequency on HRQL (QOLIE-89 telephone scores), with frequency categorized into four groups, re- vealed a ' 'dose-response" relation, with statistically significant differences between each seizure-frequency cat- egory (20.60; p < 0.000 1 ): patients who were seizure free in the past month had a mean epilepsy domain score of 77.2 ? 19.1; one to five seizures, a mean of 65.6 ? 22.2 (12 points lower); six to 30 seizures, 44.1 i 25.5 (33

QOLIE-89 Scale

Epilepsy domain Seizure worry Medication effects Health discouragement Wor!ddriving/social function

Language Attentiodconcentration Memory

Overall quality of life Emotional well-bejng Role limitations: emotional Social isolation Social support Energy/fatigue

Physical health domain Health perceptions Physical function Role limitations: physical Pain

Cognitive domain

Mental health domain

Overall QOLIE-89 Score

Descriptive statistics Floor and ceiling effects

Self (n = 68)

Telephone (n = 71)

Self (n = 68)

Mean SD Mean SD % at min % at max

Telephone (n = 71)

% at min % at max

62.5 25.7 58.6 30.8 60.9 31.1 69.3 30.0 62.7 26.8 66.6 22.3 7 I .5 23.7 69.2 23.9 58.3 26.0 67.3 17.9 66.3 19.1 70.0 19.6 71.0 34.7 72.9 25.5 70.0 24.2 56.9 21.0 69.5 20.2 64.9 21.7 80.0 24.7 63.9 38.5 73.5 26.1 66.7 19.1

62.4 26.0 59.6 30.2 61.7 29.6 68.0 30.8 61.6 28.1 67.9 22.2 74.0 22.1 69.6 23.7 59. I 26.4 68.0 18.5 66.4 19.1 70.5 20.2 73.4 34.3 72.2 27.0 71.3 23.5 57.2 21.9 69.6 19.9 62.7 22.3 83.4 22.9 61.7 38.1 73 0 25.7 67.0 19.8

0.7 2.9 3.6 12.9 5.0 20.9 4.3 24.6 0.7 5.0 0.7 1.4 0.7 8.6 0.7 3.6 0.7 3.6 0.7 0.7 0.7 3.6 0.7 2.9 8.6 49.6 0.7 24.8 1.4 14.5 0.7 0.7 0.7 1.4 0.7 5.0 0.7 3 I .I

14.4 44.6 1.4 26.6 0.7 0.7

0.7 0.7 4.3 9.4 5.0 18.0 5.0 24.4 0.7 2.2 0.7 I .4 1.4 10.1 0.7 5.0 1.4 5.0 0.7 0.7 0.7 2.9 0.7 3.6 7.2 51.1 2.2 28.1 0.7 15.1 0.7 0.7 0.7 1.4 0.7 0.7 0.7 37.4

15.1 39.6 1.4 23.7 0.7 0.7


TABLE 5. Reliability and validity of the QOLIE-89 by method of administration

Reliability

QOLIE-89 Scale

Internal Construct validity" consistency" Reproducibility' (POMS)

Self Telephone Telephone Self Telephone

Epilepsy domain 0.95 0.94 0.92 -0.61 -0.66 Seizure worry 0.88 0.87 0.92 -0.50 -0.57 Medication effects 0.85" 0.78 0.81 -0.47 -0.54 Health discouragement 0.87d 0.92 0.86 -0.57 -0.60 WorWdriving/social function 0.92 0.93 0.93 -0.59 -0.60

Cognitive domain 0.96 0.95 0.90 -0.75 -0.74 Language 0.88 0.86 0.69 -0.62 -0.65 Attention/concentration 0.93 0.93 0.89 -0.77 -0.76 Memory 0.9 1 0.91 0.92 -0.66 -0.66

Mental health domain 0.93 0.94 0.93 -0.77 -0.76 Overall quality of life 0.69 0.76 0.82 -0.65 -0.63 Emotional well-being 0.80d 0.86 0.89 -0.79 -0.78 Role limitations: emotional 0.82 0.84 0.84 -0.53 -0.60 Social isolation 0.83 0.85 0.89 -0.63 -0.62 Social support 0.84 0.84 0.76 -0.45 -0.4 I Energy/fatigue 0.81 0.84 0.83 -0.62 -0.65

Physical health domain 0.94 0.94 0.95 -0.49 -0.53 Health perceptions 0.80 0.82 0.92 -0.53 -0.55 Physical function 0.91 0.93 0.92 -0.27 -0.38 Role limitations: physical 0.86 0.85 0.75 -0.36 -0.39 Pain 0.85 0.84 0.85 -0.43 -0.40

Overall QOLIE-89 Score 0.98 0.98 0.96 -0.76 -0.76

" n = 131-139; Cronbach's alpha. " n = 28; patients without significant intervening life events; values shown are intraclass corrrelation coefficients, Pearson's correlation coefficients

' n = 133-136; Pearson's correlations between the QOLIE-89 and POMS total score; no significant differences by method of administration; varied by <0.009.

correlation coefficients within method are all significant (p < 0.001) with the exception of physical function by self-administration (p < 0.01). The difference in Cronbach's alpha between self and telephone is statistically significant (p < 0.05).

points lower than no seizures); and >30, 32.9 f 20.15 (44 points lower than seizure-free patients).

Be ha v io ral memory The interaction terms in the ANOVAs evaluating the

effect of behavioral memory (RBMT) on overall and

domain scores of the QOLIE-89 were not significant. The mean overall score for patients with impaired memory was 63.8 (+ 20.1) for telephone and 63.4 (+ 19.3) for self compared with 69.3 (+ 19.3) for telephone and 69.3 (+ 18.6) for self for those with unimpaired memory ( F = 0.75; p = 0.39 for the overall score).

TABLE 6. Pearson's correlation coefficients between the QOLIE-89 epilepsy-specific scales, epilepsy domain, and overull .score, self-administered and telephone-administered versions

QOLIE-89 and version" Number of AEDs Number of AEDs Number of days Number of seizures that failed in past taking currently since last seizure in past 4 weeks"

Seizure worry scale S T

Medication effects scale S T

Health discouragement scale S T

WorWdriving/social scale S T

Epilepsy domain S T

Overall QOIJE-89 score S T

-0.07 -0.04 -0.09 -0.12 -0.09 -0.12 -0.32" -0.3Id -0.14 -0.15 -0.14 -0. I6

-0.10 -0.10 -0.06 -0.13 -0.12 -0.21 -0.30" -0.3Id -0.15 -0.20 -0.19 -0.21

0.27' 0.26' 0.06 0 20 0.24' 0 25' 0.28' 0 37' 0.24' 0.30" 0.25' 0.28d

-0.49 -0.45' -0.33" -0.38' -0.46' -0.54" -0.60 -0.64" -0.53' -0.56' -0.54' -0.52'

~~~~ ~

Version: S, self-administered; T, telephone-administered. Ordinal variable: 0, 1-5, 6-30, 31+ seizures in past month.

' p < 0.01. " p < 0.001. f' p < 0.000 I .

Eprleps~a, Vul. 40, No. I , 199Y


TABLE 7. Construct validity of the QOLIE-89: mean (-c standard deviation) domain and overall .scoi-es (telephone-administered) by seizure frequency and behavioral memory impairment

QOLIE-89 Score

Number of seizures in the past 4 weeks

0-5 6+ (n = 95) (n = 40)

Behavioral memory

Unimpaired Impaired (n = 59) (n = 79)

Epilepry domain 71.6 k 21.4 41.7 f 24.9" 65.8 f 25.6 58.7 * 26.3" Cognitive domain 73.9 t 19.3 56.7 * 2 1.7" 71.9 k 21.0 62.9 f 22.8" Mental health domain 72.8 i 15.4 56.4 5 20.8" 67.9 t 18.9 67.3 t 18.2 Physical health domain 74.9 t 16.8 57.2 f 22.0" 72.2 f 17.9 66.4 f 22.0b Overall QOLIE-89 Score 73.5 t 16.3 5 I .4 k 18.9" 69.3 k 19.3 63.8 f 20.1"

" p < 0.001 " p < 0.01.

The main effect of memory on QOLIE-89 overall score was statistically significant ( F = 21.20; p < O.OOOl), as were the analyses for the epilepsy ( F =

16.67; p < 0.0001), cognitive ( F = 28.29; p < 0.0001), and physical health domains ( F = 12.87; p < 0.005), indicating that patients with impaired memory had significantly poorer HRQL. Only the mental health domain scores were not significantly different for the impaired and unimpaired groups ( F = 0.13; p = 0.72). Mean domain and overall scores (telephone-administered) by memory impairment are provided in Table 7.

The internal consistency reliability of the QOLIE-89 overall score for patients with impaired versus unimpaired behavioral memory was 0.98 regardless of the method of administration used. Subscale ar levels for the self-administered method ranged from 0.77 to 0.96 for patients with unimpaired memory and 0.75 to 0.95 for those with impaired memory. Telephone administration ranged from 0.72 to 0.96 for patients with impaired memory and from 0.65 to 0.95 for patients with unimpaired memory. Four significant differences in subscale ar levels were found in the impaired memory group: telephone was more reliable than self (p < 0.01) for health discouragement, emotional well-being, and physical function and less reliable for pain (p < 0.05). In the unimpaired memory group, self-administration was more reliable for physical function and pain (p < 0.05). Cor- relation coefficients between the POMS and the QOLIE- 89 subscales were consistent across the two memory groups.

In the test for educational bias, the interaction term in the model of the overall score was not significant ( F =

1.33; p = 0.25), indicating that the relation between self- and telephone-administered scores did not vary with level of education. Tests for main effects of educational attainment on overall score indicated that there were no significant differences between the two education groups ( F = 0.52; p - 0.47).

Length of administration and patient preference The mean length of time required for self-adminis-

tration of the QOLIE-89 was 21 (k9) min com-

pared with 19 (+7) min for the first telephone interview (p = 0.006) and 16 (56) min for the second telephone interview. Most (46%) patients stated that they had no preference for either method of administration; 30% preferred the self-administered method, and 24% preferred telephone interview. There was no significant relation between the order in which patients experienced the two methods and preference ratings.

DISCUSSION

The results of this study indicate that the psychometric performance of the QOLIE-89 is stable across method of administration. There were no systematic differences in mean score by method or order of administration. Post hoc exploratory analyses uncovered two statistically significant differences between telephone and self-administration: a 2-point difference in health perceptions and a 3-point difference in physical functioning, a scale from the SF-36. Although statistically significant, these differences are relatively small on the 0-100 scale, and, given the number of comparisons performed, are likely to be chance occurrences. There were no indications that the order in which instruments were administered had any effect on HRQL scores.

Mean subscale scores for this sample were comparable to those reported by Devinsky et al. (3), where scores ranged from 54.3 to 85.3. In fact, values for all but three subscales were within 5 points of one another. Floor effects were minimal, consistent across method of administration, and similar to those reported by Devinsky et al. (3). Relatively high ceiling effects were found in three subscales that correspond to the generic SF-36 (role-limitation, emotional role limitations, and physical function), suggesting these subscales may be less sensitive to change. The finding is consistent with the need for condition-specific indices to complement generic HRQL assessment in evaluating treatment outcomes.

Internal consistency reliability estimates found in this and previous studies attest to the stability of the mea- surement error in the QOLIE-89, regardless of how it is administered. With the exception of the overall quality of

Epilepsia, Vol. 40, N o . 1. 1999


life subscale by self-administration, all of the coefficients in this and Devinsky’s study exceeded Nunnally’s crite- rion of 0.70 for “modest” reliability; most exceeded 0.80, which is considered optimal for basic research and group comparisons (3 I) . The overall QOLIE-89 reliability coefficient of 0.98 in this study and 0.97 reported by Devinsky et al. (3 I ) exceed the reliability standard for individual decisions based on small score differences.

Results of the 2-week reproducibility evaluation indicate that data gathered through telephone administration are stable over time under stable conditions. The fact that levels in this study were generally higher than previously reported may be a function of timing. In this study, the second interview took place within 10 to 16 days of the first (14 days ?2), whereas in the original QOLIE-89 validation study (3), instruments were self-administered with 1-21 days between administrations (no mean provided).

As predicted, and consistent with previous studies, the QOLIE-89 was significantly correlated with the POMS, regardless of method of administration. Coefficients were generally higher than those reported previously (3,16); the correlation of -0.76 between the POMS and QOLIE-89 total scores (self and telephone) were comparable to the -0.70 reported by Devinsky et al. (3) and Perrine et al. (1 6). The results also provide evidence of convergent validity of the QOLIE-89 (the strongest correlations were between the emotional well-being scale and the POMS total score) as well as divergent validity (the weakest correlations were between the physical health scales and the POMS total score).

Patients reporting more frequent seizures also reported poorer HRQL regardless of method of administration. Significant relations also were found between the epilepsy-specific work-driving-social subscale and number of AEDs that failed, number of current AEDs, days since last seizure, and number of seizures in the past 4 weeks. Devinsky et al. (3) reported that this subscale was second only to the health discouragement subscale in validity, supporting its sensitivity to the HRQL effects of epilepsy.

The epilepsy domain and the overall QOLIE-89 scores were particularly sensitive to between-patient differences in seizure frequency, suggesting that they also may be responsive to within-patient change with treatment. The magnitude of the observed differences between groups provides insight into numeric values that may be clinically meaningful. Further research is needed to deter- mine the sensitivity of the QOLIE-89 to change and the subscale and total scale change scores that would be considered clinically significant.

Patients with memory impairment and patients with a high school education or less were able to provide reliable, valid responses on the QOLIE-89, regardless of how the instrument was administered. It should be noted

that patients with severe cognitive impairment were excluded from this study, and that memory impairment was defined within the context of everyday memory problems that interfere with normal daily functioning. Clearly these results cannot be extrapolated to patients with severe cognitive deficits. Nevertheless, this is the first study to evaluate the performance of a HRQL measure in light of the behavioral memory impairment commonly experienced by patients wtih epilepsy. The QOLIE-89 performed comparably in the two memory groups and was sensitive to the HRQL effects of day-to-day memory limitations: as expected, patients with impaired memory had significantly lower QOLIE-89 scores than did patients with unimpaired memory. On the other hand, the instrument was free of confounding education effects.

Finally, there were no substantive differences between the two methods of administration in either the time required or patient preference for data collection. More than two thirds of patients indicated no preference for method of administration or indicated they preferred the telephone interview. Preferences for telephone interview may be more apparent in longitudinal studies requiring repeated clinic visits for assessing HRQL.

In summary, the results of this study indicate that telephone administration is a viable alternative for evaluating HRQL outcomes in patients with epilepsy and attest to the reliability and validity of the QOLIE-89 regardless of method of administration. The fact that many patients are unable to drive makes telephone administration particularly useful and cost-effective for monitoring HRQL in rural communities and situations requiring long-term follow-up. This is also the preferred data-collection method in studies involving large, geographically diverse samples. Mean score values, internal consistency reliability, reproducibility, and correlations wtih mood were equivalent across method of administration and similar to values reported in the literature. Furthermore, patients with impaired behavioral memory were able to provide reliable and valid responses to the QOLIE-89, regardless of method of administration. Finally, the fact that seizure frequency and behavioral memory were significantly related to HRQL is not only consistent with the construct validity of the instrument, but also offers further empiric insight into the impact of these factors on HRQL in adults with epilepsy.

Acknowledgment: We gratefully acknowledge the assistance of Tracey Reardon, Sally Elliott, Kathy O’Hara, Sue Lannon, and Gaye Harris, who were the study coordinators; Diane Burkom and Rebecca Ebaugh at Battelle Survey Opera- tions for their work in coordinating the study sites and over- seeing the conduct of the telephone interviews; Chris Thomp- son for computer programming; and Anne Getz for assistance with the evaluation of the data. Thanks also to the Georgetown University Medical Center Clinical Research Center for facilitating pilot work and to Eugene Means, M.D., of Astra Merck, Inc.. for his comments on an earlier version of this article. This

EpIleprIu. V d . 40, N o . I , 1999

106 N . K. LEIDY ET AL.

project was funded by Astra Merck, Inc. (Wayne, PA, U.S.A.). The paper was presented at the Annual Meeting of the Ameri- can Epilepsy Society in Boston, December 1997.

characteristics of the Psychological General Well-Being Index with a new response scale. Quul Life Res 1996;5:419-25.

15. Perrine KR. A new quality-of-life inventory for epilepsy patients: interim results. Epilepsia 1993;34(suppl 4):S28-33.

1

2

3

4.

5.

6.

7.

8.

9.

10.

I I .

12.

13.

REFERENCES

Vickrey BG, Hays RD, Graber J, Rausch R, Engel J, Brook RH. A health-related quality of life instrument for patients evaluated for epilepsy surgery. Med Care 1992;30:299-3 19. Smith DF, Baker GA, Dewey M, Jacoby A, Chadwick DW. Sei- zure frequency, patient-perceived seizure severity and the psycho- social consequences of intractable epilepsy. Epilepsy Res 1991; 9:231-41. Devinsky 0, Vickrey BG, Cramer J, et al. Development of the Quality of Life in Epilepsy Inventory. Epilepsiu 199x36: 1089- 104. Kendrick AM, Trimble MR. Repertory grid in the assessment of quality of life in patients with epilepsy: The Quality of Life As- sessment Schedule. In: Trimble MR, Dodson WE, Epilepsy and quality ($life. New York Raven, 1994: 151-63. Gillham R, Baker G, Thompson P, Birbeck K, et al. Standardisa- tion of a self-report questionnaire for use in evaluating cognitive, affective and behavioral side-effects of anti-epileptic drug treat- ments. Epilepsy Res 1996;24:47-55. Kugoh T. Quality of life in adult patients with epilepsy. Epilepsia 1996;37(suppl 3):3740. Ware JE, Snow KK, Kosinski M, Gandek B. SF-36 Health Survey: manual and interpretation guide. Boston, MA: The Health Insti- tute, New England Medical Center, 1993. Leidy N K , Rentz AM, Grace EM. Evaluating health-related quality of life outcomes in clinical trials of anti-epileptic therapy. Epilep- siu 1998;39:965-77. Hillman AL, Schwartz JS, Willian MK, et al. The cost-effectiveness of terazocin and placebo in the treatment of moderate to severe benign prostatic hyperplasia. Urology 1996;47: 169-78. Simon GE, VonKorff M, Heiligenstein JH, et al. Initial antidepres- sant choice in primary care: effectiveness and cost of fluoxetine vs. tricyclic antidepressants. JAMA 1996;275: 1897-902. Weinberger M, Oddone EZ, Samsa GP, Landsman PB. Are health- related quality-of-life measures affected by the mode of administration? J Clin Epidemiol 1996;49: 13540. te Velde A, Sprangers MA, Aaronson NK. Feasibility. psychometric performance, and stability across modes of administration of the CARES-SF. Ann Oncol 1996;7(4):38 1-90. McHorney CA, Kosinski M, Ware JE. Comparisons of the costs and quality of norms for the SF-36 health survey collected by mail versus telephone interview: results from a national survey. Med Care 199413255 1-67.

. . .. 16. Perrine K, Hermann BP, Meador KJ, et al. The relationship of

neuropsychological functioning to quality of life in epilepsy. Arch Neurol 1995;52:997-1003.

17. Vickrey BG, Perrine KR, Hays RD, et al. Quality ofLife in Epi- lepsy, QOLIE-89 scoring manual and patient inventory. Santa Monica, CA: RAND, 1993.

18. McNair D, Lorr M, Droppleman L. POMS: profile of mood states. San Diego, CA: EdITSEducational and Industrial Testing Service, 1992.

19. Dodrill C, Arnett J, Sommerville K, Sussman N. Evaluation of the effects of vigabatrin on cognitive abilities and quality of life in epilepsy. Neurology 1993;43:2501-7.

20. Baker GA, Smith DF, Dewey M, Jacoby A, Chadwick DW. The initial development of a health-related quality of life model as an outcome measure in epilepsy. Epilepsy Res 1993; 16:65-8 I .

21. Wilson B, Cockbum J, Baddeley A, Hiorns R. The Rivermead Behavioural Memory Test, supplement two. Bury St. Edmunds: Thames Valley Test Company, 199 I .

22. Wilson BA, Cockburn J, Baddeley AD, Hiorns R. The development and validation of a test battery for detecting and monitoring everyday problems. J Clin Exp Neuropsychol 1989;11:855-70.

23. Wilkins AJ. Remembering to do things in the laboratory and everyday life. Acta Neurol Scand 1986;74(suppl 109):109-12.

24. Giovagnoli AR, Mascheroni S, Avanzini G. Self-reporting of everyday memory in patients with epilepsy: relation to neuropsychological, clinical, pathological and treatment factors. Epilepsy Res 1997;28:1 19-28.

25. Vermeulen J , Aldendkamp AP, Alpherts WCJ. Memory com- plaints in epilepsy: correlations with cognitive performance and neuroticism. Epiiepsy Res 1993; 15: 157-70.

26. Mosier C1. On the reliability of a weighted composite. Psy- chometrika 194323: 161-8.

27. Feldt L. A test of the hypothesis that Cronbach’s alpha or Kuder- Richardson coefficient twenty is the same for two tests. Psy- chometrika 1969;34:363-73.

28. Feldt L. A test of the hypothesis that Cronbach’s alpha reliability coefficient is the same for two tests administered to the same sample. Psychometrika 1980;45:99-105.

29. Feldt L, Woodruff D, Salih F. Statistical inference for coefficient alpha. Appl Psychol Meas 1987;11:93-103.

30. Glass G, Stanley J. Statistical methods in educationul psychology. Englewood Cliffs, NJ:Prentice-Hall, 1970.

3 1. Nunnally JC, Bemstein IH. Psychometric theory. New York: Mc- 14. Revicki DA, Leidy NK, Howland L. Evaluating the psychometric Graw-Hill, 1994

Epilc,p.sio. Vol. 40, NO I , 1999

telephone validation of the quality of life in epilepsy inventory-89 (qolie-89)

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