Quality of life after myocardial infarction

Pergamon J Clin Epideaniol Vol. 47, No. 1 I, 1287-1296, 1994 pp.

oW5-4356@4~7-0 Copyright 0 1994 Elsevier Science Ltd

Printed in Great Britain. All rights merved 0895-4356/94 $7.00 + 0.00

QUALITY OF LIFE AFTER MYOCARDIAL INFARCTION

THOMAS K. HILLERS, GORDON H. GUYATT,* NEIL OLDRIDGE, JEAN CROWE, ANDREW WILLAN, LAUREN GRIFFITH and DAVID FEENY

Departments of Medicine and Clinical Epidemiology and Biostatistics, McMaster University, Hamilton, Ontario, Canada

(Received 6 February 1994)

Abstract-The objective of this work was to develop and test a questionnaire to measure health-related quality of life for patients after myocardial infarction (MI). In a cross-sectional survey, 63 patients identified the most frequent and important problems following acute myocardial infarction. The Quality of Life after Myocardial Infarction (QLMI) instrument was developed on the basis of these most frequent and important problems. The QLMI was administered, along with instruments measuring health utilities, social function, and emotional function, in a randomized trial of rehabilitation versus conventional care. The most frequent and important problems fell into areas of symptoms, restriction, confidence, self-esteem, and emotions, each of which is rep- resented in the 264tem QLMI. Effect sizes of the overall QLMI in differentiating between rehabilitation and control groups (0.39, and in detecting improvement over 12 months (1.22) were comparable or larger than any other instrument. The Pearson’s correlation coefficient between QLMI administered at 8 and 12 months following AMI varied between 0.75 and 0.87 for the five domains and the overall score. We found substantial correlations of the QLMI with other measures with moderate concordance with predictions about how the instrument should behave if it is a valid measure of health-related quality of life. The QLMI demonstrates a high degree of reliability, and is more responsive than other questionnaires. Relations between the QLMI and other measures provide moderate to strong evidence of its validity in discriminating between patients following AM1 according to their health-related quality of life, and in measuring changes in health-related quality of life over time.

Quality of life Myocardial infarction Cardiac rehabilitation

INTRODU(ZTION abstract concepts of well-being to empirical

The measurement of health has evolved from indices. These indexes must measure the long-

assessing longevity and major morbidity, to term effects of chronic illness that are currently

evaluating physical, emotional, and social func- the primary focus of health care in western

tion. This complex notion of health requires society.

sophisticated measurement tools to link the This is specifically true for cardiovascular

disease where the goal of treatment is not only to prolong life, but to relieve symptoms and improve function. The assessment of clinical

*All correspondence should be addressed to: Dr Gordon Guyatt, Rm 2C12, McMaster University Health Science

effectiveness in cardiovascular disease must in-

Centre, 1200 Main Street West, Hamilton Ontario, elude an assessment of health-related quality of Canada L8N 325. life [I].

1287

1288 THOMAS K. HILLERS et al.

Health-related quality of life can be assessed using disease-specific or generic measures. The advantages of generic measures is that they address a wide variety of domains, thereby assessing both anticipated and unpredictable treatment effects, as well as adverse effects. The major limitation of these instruments is that they may not examine treatment or adverse effects in detail. Disease-specific instruments, which focus on the problems of a defined population at a specific point in a disease process, address this limitation. While disease-specific instruments cannot be used to compare populations with different illnesses or problems, they have an important role in elucidating areas of health-related quality of life impairment in patient groups of special interest [2].

This paper describes the development and testing of the Quality of Life after Myocardial Infarction Questionnaire (QLMI). We developed the QLMI to evaluate the effectiveness of a comprehensive cardiac rehabilitation program in improving the health-related quality of life in patients following acute myocardial infarction (AMI) who showed evidence of anxiety or depression [3]. The questionnaire was designed both to evaluate change in health-related quality of life within patients over time and to discriminate between patients following AM1 with respect to their health-related quality of life. Our goal was to develop a short, easy to use questionnaire that would address physical, emotional and social function, and prove reliable, valid, and responsive [4,5].

METHODS

Item selection and reduction

We interviewed physicians, nurses, and other allied health professionals with experience in cardiac rehabilitation and patients with myocardial infarction and reviewed the literature [6,7] to generate items of importance to patients recovering from AMI. We developed an item reduction questionnaire of 97 items which we administered to 63 patients following AM1 (57 males and 6 females; mean age 58.0 years [range 31-781; 59% < 3 months following AMI, 25% from 3 to 6 months; 10% from 7 to 12 months, and 6% > 12 months) who were recruited from (1) a cardiac rehabilitation program, (2) patients in three community hospitals and (3) volunteer patients from the community. Patients judged whether or not the 97 items were of concern to

them. For items which were of concern we asked patients how important each item was using a 5 point scale ranging from: 1 (not very important) to 5 (extremely important). Each item’s “impact score” was calculated by multiplying the number of subjects who decided an item was of concern by the mean importance for that item.

We used the results of the Item Reduction Questionnaire as a guide for construction of the final questionnaire. Criteria for choice of items for the final questionnaire included the impact of the item as judged by the patients and importance of an item to clinicians.

Study design

We tested the QLMI in the context of a randomized trial comparing conventional care following AM1 to a program involving both physical conditioning and behavioral coun- selling. We have previously reported the results of this study [3].

All patients with a diagnosis of MI in 6 local hospitals were screened for eligibility. We randomized 201 MI patients scoring greater than 5 on the short form of the Beck depression inventory, or greater than 42 on the Spielberger State-Anxiety Scale, or 41 on the Spielberger Trait-Anxiety Scale. Results on the Beck and Spielberger instruments constituted our criteria for evidence of depression and anxiety.

In addition to the QLMI, a battery of other questionnaires were administered at baseline, 8 weeks (at the conclusion of the cardiac rehabilitation program) and at 4 months, 8 months and 1 year. These included two utility measures which summarize health-related quality of life on a scale from 0 to 1: the Quality of Well-being questionnaire (QWB) which has been widely used and extensively validated [8], and the Time Trade-off (TTO) in which patients are asked how many years in their present health state they would be willing to trade off for a shorter number of years in full health [9]. The Katz [lo] instrument assesses social function, has been used in a broad spectrum of settings [I 11, and has undergone extensive assessment of reliability and validity [ 121. Emotional function questionnaires included the Beck, a 13-item test (short form) designed to measure the number of depressive symptoms [13]; the Profile of Mood States (POMS) [14] which has separate scores for tension (POMS-T) and depression (POMS- D), and the Spielberger StateTrait Anxiety Inventory (STAI) [15], a commonly used anxiety scale which is divided into a 20 item

Quality of Life After Myocardial Infarction 1289

Stat+Anxiety scale covering current apprehen- sion, tension, nervousness and worry and a Trait-Anxiety scale, which includes the same 20 statements, but related to how the patient feels generally.

In addition to the questionnaires, subjects also undertook a progressive symptom-limited exercise test at entry to the study, at 8 weeks, and at the final 1 -year followup. Exercise testing was performed on an electrically braked cycle ergometer using a standardized protocol. Patients pedalled at a constant velocity with power increments of 100 kpm/min each minute until a symptom-limited maximum was achieved. Exercise performance was defined as the duration of time the participant continued with the test.

Testing QLMI measurement properties

General approach. Health-related quality of life measurement instruments may have one (or more) purposes. A discriminative instrument is designed to discriminate between people at a single point in time. For instance, we may wish to identify patients experiencing moderate or severe depression and/or anxiety post MI. Such instruments require good reproducibility (between-subject to within-subject variance) and cross-sectional construct validity, demonstrat- ing good correlation between established rating scales and the instrument being tested. An evaluative instrument is designed to measure the magnitude of longitudinal change in an individual or group. Responsiveness and longitudinal construct validity are measurement properties required of an evaluative instrument [16, 171. We tested QLMI performance as both a discriminative and evaluative instrument.

Validity concerns how well a test measures what it is designed to measure. Validation of a measure is stronger if a priori predictions are made concerning the relationships one expects between measures. After considering the specific items in each instrument, their relation to the domains of the QLMI, and the apparent ability of patients to understand what was being asked of them, two of the authors (TH) and (JC) predicted the correlations we anticipated if the QLMI was really measuring disease-specific health-related quality of life. The correlations were based on extensive experience with admin- istration of the instruments (JC) and with pat- terns of correlations observed with other similar instruments. In validating health-related quality of life measures when there is no criterion

standard, correlations with related measures much greater than 0.5 are very seldom observed, and should not be expected. Categories for the correlations were: absent (less than 0.2), weak (0.2-0.34), moderate (0.35-0.5) and strong (greater than 0.5).

Evaluative properties

Responsiveness. Responsiveness refers to the instrument’s ability to detect any clinically important changes in health-related quality of life. It is well established that the natural history of patients in the first year after myocardial infarction is gradual improvement in physical and emotional function [18]. We anticipated that a responsive instrument would be able to detect within-subject change over this period. We therefore compared the responsiveness of the instruments by comparing the size of the effect (or effect size) seen over these 12 months. The effect size was calculated as the ratio between the change in subjects score between baseline and 1Zmonth visits (the signal) and the pooled standard deviation of change during this period (the noise) [19].

We interpreted the results of the study as showing a small difference in health-related quality of life attributable to the rehabilitation program which was evident in the evaluation conducted 8 weeks after randomization but which gradually disappeared over the subsequent year, gradually decreasing with each subsequent evaluation [3]. A responsive instrument should therefore be able to detect differences between treatment and control group at the 8 week evaluation. Therefore, we calculated a second effect size measure of instrument responsiveness. This ratio had as its numerator or signal the difference between change in score in the treatment group and change in score in the control group over 8 weeks. The denominator or noise was the pooled standard deviation in the two groups.

For both methods of measuring responsiveness, we calculated the statistical significance of differences in effect size between the questionnaires.

Validity. The evaluative validity was deter- mined by measuring the correlations between changes in scores of individual domains of the QLMI and changes in scores of the other health- related quality of life instruments. Each subject contributed 4 data points to this analysis: the first a correlation between changes in the two measures being compared from the first to the


second visit; the second the correlation between changes from the second to the third visit; the third the correlations between changes from the third to the fourth visit; and the fourth the correlation of changes from the fourth to the fifth visit.

Discriminative properties

The minimum score, maximum score, means and standard deviations for the five domains of the QLMI at the first visit were, respectively, as follows: Self-esteem 2.0, 7.0, 5.75 and 1.03; Restriction 1 .O, 7.0, 4.16 and 1.57; Fatigue 3.2, 7.0, 5.66 and 0.82; Emotional Function 2.3, 7.0, 5.17 and 0.99; Confidence 2.6, 7.0, 4.99 and 0.92.

Reproducibility. The reproducibility of a measurement can be conceptualized as its re- peatability, consistency or stability when taking independent measures on the same subject under the same conditions [20]. Because we expected minimal changes in patients’ health- related quality of life between the 8 and 12 month visits, we calculated Pearson’s correlation coefficients to measure reliability of the questionnaire over this period.

Validity. We assessed discriminative (cross- sectional) validity by calculating correlations between scores in each domain of the QLMI with the scores of the other instruments. Choice of any of the 5 visits for calculating the correlations would have been arbitrary. For this reason, and to minimize random error, we calculated the mean score for each subject over the 5 visits for each domain of the QLMI, and the mean score across the 5 visits for each subject for each of the other instruments. We then examined the correlation of these mean scores to assess discriminative validity.

Internal consistency

At the suggestion of a reviewer, we calculated the Internal Consistency of the items in the questionnaire.

RESULTS

Population

A total of 201 patients were randomized, 99 to rehabilitation and 102 to conventional community care. Of these 201 patients, 177 were male and the average age was 52 years. The rehabilitation and conventional care groups were comparable with regard to age, sex, MI

site, severity, presence of previous MI and the percentage of patients working prior to MI (Table 1).

Item selection and reduction

Table 2 presents, for the 10 items with the highest impact score, the proportion of subjects who chose the item, and the mean importance attributed to the item, and the total impact.

On the basis of their conceptual link to one another, we divided the items from the Item Reduction Questionnaire into five domains: symptoms, restrictions, confidence, self-esteem, and emotion. Emotion and self-esteem include 6 questions, confidence and symptoms 5 questions and restriction 4 questions for a total of 26 items.

The QLMI presents response options as seven-point scales which allow detection of relatively fine gradations of change. Seven-point scales require little training time, and therefore are easily understood by the respondents [21,22]. At follow-up visits, to improve instrument validity, subjects are informed of their prior responses to each question [23,24]. The structure and content of the questionnaire is presented in the Appendix. To calculate the score for each domain we add up scores on the individual items and then divide by the number of items. Thus, the possible score for each domain ranges from 1 to 7.

Evaluative properties

Responsiveness. Table 3 presents the effect sizes of each of the instruments in detecting differences between scores at 12 months and scores at baseline. Two of the QLMI domains, Restrictions and Confidence, and the overall QLMI score, proved substantially more responsive than any of the other instruments.

Table 4 presents the effect sizes of each of the instruments in detecting differences between

Table 1. Characteristics at baseline

Rehabilitation Conventional care Sex (Male) 87 (88%) 90 (89%)

MI Site Anterior Inferior Posterior Indefinite

36 (36%) 34 (33%) 55 (55%) 56 (55%) 3 (3%) 8 (8%) 5 (5%) 5 (5%)

Previous MI 17 (17%) 18 (17%) Working prior to MI 65 (65%) 74 (73%) CPK 1641 (1466.5)* 1540 (1290.6)* Age (yr) 52.9 (9.5)’ 52.7 (9.5)*

*Standard deviation.

Quality of Life ARer Myocardial Infarction 1291

Table 2. Results of item reduction auestionnaire

Low in energy Worn out Restricted in your life Usual social activities Returning to work/employment More dependent than before Dizzy Need to rest frequently Restless Don’t know how much exercise to do

Proportion of subjects Mean identifying item as problem importance

0.68 2.95’ 0.52 3.03 0.51 2.91 0.44 2.89 0.32 4.05 0.41 3.00 0.38 3.13 0.51 2.34 0.43 2.14 0.46 2.55

Total impact

2.02t 1.59 1.51 1.29 1.29 I .24 1.19 1.19 1.17 1.17

*Maximum of 5. TMaximum of 1.0 x 5 or 5.0.

treatment and control groups at 8 weeks. Five measures, including two of the QLMI domains, Confidence and Emotional Function, and the QLMI total, showed statistically significant differences favouring treatment over control populations at the 8-week follow up. The two most responsive QLMI domains and the QLMI total were comparable in their performance to the most responsive of the other instruments.

Validity. Table 5 presents a comparison between the predicted and observed correlations of the five QLMI domains and the other measures. Of the 20 predictions concerning the relations between the QLMI domains and the five emotional function questionnaires, 11 proved accurate. The remaining correlations were all one category lower than predicted.

Of the 14 predictions concerning the relations between the QLMI domains and the functional and utility measures, 3 proved accurate. The observed correlations were one category lower than those predicted for another 9 correlations, and 2 categories lower than predicted for the remaining two correlations.

Table 3. Effect sizes, 12 months vs baseline

QLMI--Symptoms 0.27 QLMI-Restrictions 1.34t QLMI-Confidence 1.43* QLMI-Self esteem 0.85 QLMI-Emotions 0.51 QLMI-Total 1.22$ Exercise tolerance 0.50

Beck Trait anxiety State anxiety PQMS T POMS D

0.49 1.06 I .20 0.28 0.58 0.40 0.61 0.35

*Effect size statistically significantly larger (p < 0.05) than all other non-QLMI effect sizes.

TEffect size statistically significantly larger (p < 0.05) than all other non-QLMI effect sizes except for Katz.

$Effect size statistically significantly larger (p c 0.05) than all other non-QLMI effect sizes except for Katz and QWB.

Discriminative properties

Reliability. The Pearson correlations of the results of 8- and 1Zmonth visits for the five QLMI domains and the overall score were as follows: Symptoms 0.83, Restrictions 0.75, Confidence 0.87, Self-esteem 0.85, Emotional Function and Total 0.86. The range of correlations for individual items in the five domains was as follows: Symptoms 0.66-0.85; Restric- tions 0584.83; Confidence 0.72-0.87; Self- esteem 0.68-0.87; and Emotional Function 0.65-0.82.

Validity. Table 6 presents a comparison between the predicted and observed correlations of the five QLMI domains and the other measures. Of the 20 predictions concerning the relations between the QLMI domains and the five emotional function questionnaires, 5 proved accurate. Of the remaining correlations, 9 were one category higher than predicted, while the other 6 were two categories higher than predicted.

Of the 14 predictions concerning the relations between the QLMI domains and the functional and utility measures, 4 proved accurate. Another 7 positions were within one category of the results observed. In 4 of these 7, the correlations were higher than predicted, and in 3 they were lower than predicted. Of the 3 correlations that were much lower than predicted, two related to exercise performance.

Table 4. Effect size, treatment vs control, 8 weeks

QLMI-Symptoms 0.19 G

0.07 QLMI-Restrictions 0.27 0.10 QLMI-Confidence 0.37* Katz 0.06 QLMI-Self-esteem 0.19 Beck 0.16 QLMI-Emotion 0.32* Trait anxiety 0.01 QLMI-Total 0.35* State anxiety 0.37* Exercise tolerance 0.29 PQMS T 0.08

PQMS D 0.32*

*Difference between treatment and control at 8 weeks statistically significant (p < 0.05).

1292 THOMAS K. HILLER~ et al.

Table 5. Evaluative validity of the five QLMI domains

(A) QLMI and emotional function measures Restriction Confidence Self-esteem Emotions

Beck 10.201 (0.201 0.30 1 10.351 (weak)? (weak) (mozate) (moderate)

Trait 0.15 1 0.15 1 10.261 0.27 1 anxiety (weak) (weak) (weak) (moderate)

State 0.19 1 10.231 (b.26) 0.32 1 anxiety (weak) (weak) (weak) (moderate)

POMS 10.201 10.271 ro.331 10.371 tension (weak) (weak) (weak) (moderate)

POMS 0.11 1 0.161 0.31 1 10.361 depression (weak) (weak) (moderate) (moderate)

(B) QLMI and functional and utility measures Symptoms Restriction Confidence Self-esteem Emotions

Exercise

TTO

QWB

Katz

0.18 11 (strong)

0.23 1 (moderate)

0.25 1 (moderate)

0.10 1 (weak)

0.25 1 (moderate)

0.29 1 (moderate)

0.29 J 1 (strong)

0.28 1 (moderate)

0.22 1 (moderate)

10.271 (weak)

0.27 J (mod) 10.291 (weak)

0.26 1 (mod) 10.211

(weak)

tThe word in brackets under the number indicates the strength of the correlation that we predicted.

10.201 Numbers presented such as this, boxed, indicate accurate predictions. t Actual correlation one category higher than predicted correlation. 1 7 Actual correlation two categories higher than predicted correlation. 1 Actual correlation one category lower than predicted correlation. 1 1 Actual correlation two categories lower than predicted correlation.

Table 6. Discriminative validity of the five QLMI domains

(A) QLMI and emotional function measures Restriction Confidence Self-esteem Emotions

Beck

Trait anxiety

State anxiety

POMS tension

POMS depression

10.331 6=-W lo.zsl (weak)

0.31 (WX) 10.311 (weak) (0.341 (weak)

0.49 r (weak) 0.52 T t (weak) 0.55 t r (weak) 0.57 t r (weak) 0.62 f t (weak)

0.60 T (moderate)

0.56 T t (weak) 0.54 t 1 (weak) 0.58 t t (weak) 0.70 t

(moderate)

0.58 r (moderate)

0.61 t (moderate)

0.61 t (moderate)

0.68 t (moderate)

0.70 t (moderate)

(B) QLMI and functional and utility measures Symptoms Restriction Confidence Self-esteem Emotions

Exercise 0.28 1 1 0.17 11 (strong) (moderate)

TTO [0.361 0.32 1 10.421 10.421 0.31 1. (moderate) (moderate) (moderate) (mod) (mod)

QWB 0.62 7 0.44 1 0.42 T 0.41 T 0.38 T (moderate) (strong) (weak) (weak) (weak)

Katz 10.28) 0.1411 (weak) (moderate)

tThe word in brackets under the number indicates the strength of the correlation that we predicted.

10.201 Numbers presented such as this, boxed, indicate accurate predictions. 7 Actual correlation one category higher than predicted correlation. 7 7 Actual correlation two categories higher than predicted correlation. 1 Actual correlation one category lower than predicted correlation. 1 1 Actual correlation two categories lower than predicted correlation.


Internal consistency

Cronbach’s coefficient alpha for the five domains was as follows: Symptoms 0.59, Restric- tions 0.73, Confidence 0.50, Self-esteem 0.78 and Emotions 0.83. We examined the relation of item 16 (lack of self-confidence) with the Confi- dence and Self-esteem domains. The correlation of item 16 with the mean of the items in the Confidence domain was 0.5 1 and with the mean of the other items in the self-esteem domain 0.65.

DISCUSSION

The need for a disease-specific measure for patients following AM1 arises because generic measures do not focus in sufficient detail on the unique problems encountered by these patients. Perhaps the most serious problem that might result from this lack of detail is failure to detect clinically important differences if those differences are small.

We studied the QLMI with respect to both its ability to discriminate between subject at a single point in time with respect to their health- related quality of life and its ability to detect changes in health-related quality of life over time. With respect to its function as a discriminative instrument, all five domains of the instrument, and the overall score, proved highly reliable. While the time period over which we measured reliability was long (4 months), vari- ability in score in patients whose quality of life is actually changing would, if anything, attenu- ate the relationship between scores at the two time points. Thus, our estimate of reliability is, if anything, conservative.

The content validity of the questionnaire is established as a result of the manner in which it was developed, all items being of demonstrative importance to patients following AMI. We do not believe there is a gold or criterion standard for what we are trying to measure with either the individual domains or the overall QLMI. In the absence of a gold standard, further evidence of the validity of the QLMI cannot come from comparing results to a single criterion measure, but comes instead through determining the extent to which the questionnaire behaves, in relation to a number of established measures, in the manner one would expect if it is really measuring health-related quality of life. One could argue that our instrument does not reflect all aspects of comprehensive frameworks of quality of life. The instrument has few questions

pertaining to daily activities, which one might have thought would be important to patients. Our item reduction questionnaire had, however, 97 items and was fully comprehensive. If items do not appear on the final questionnaire it is because patients did not label them as problems or, if they did, thought they were not important. Therefore, with one limitation, we are comfort- able with the content validity of the instrument. The limitation is the fact that only a small proportion of the respondents in the item reduction process were women, raising the question of the content validity of the questionnaire when administered to women.

In the empirical testing of construct validity the correlations between the QLMI domains and measures of emotional function were con- sistently higher than those we predicted. It is likely that, to a larger extent than we anticipated, the QLMI discriminates between patients following AM1 on the basis of differences in their emotional function. Moderate correlations with both utility measures, correlations that corresponded closely with those predicted, suggest that the QLMI succeeds in capturing the patients’ overall assessment of their health- related quality of life.

Traditionally, health-related quality of life measures are validated in observational studies prior to use in randomized trials. We chose to proceed directly to the randomized trial for two reasons. First, prior validation is an inefficient strategy, both in terms of time and resource utilization. We have used the methodology for instrument development which characterizes the QLMI for a number of other instruments, and in each case successfully developed a valid instrument. Not validating the QLMI before the trial was a gamble, but one which we felt was relatively low risk. A second reason for validating the instrument in the context of a randomized trial was that this is one setting, and perhaps the most important setting, in which we hope other investigators will use the instrument. Validation is always strongest if carried out in the specific context in which an instrument will be applied.

With respect to its evaluative function, the QLMI fulfilled expectations that it would be more responsive than other available measures. The overall QLMI score proved as or more responsive than all other measures both in its ability to detect improvements in health-related quality of life over the 12 months following AMI, and in its ability to detect differences

1294 THOMAS K. HILLERS ef al.

between those given intensive rehabilitation and those given routine community care.

Correlations between changes in QLMI and changes in other measures were systematically lower than cross-sectional correlations used in the validation of the QLMI as a discriminative measure. As a result, correlations with the utility measures were, in general, lower than predicted. Because we observed substantial change over time in both the QLMI and all other questionnaires, the lower correlations must be due to additional random error introduced by the measurement of change over time. The correlations are still sufficiently high that they provide reasonable confidence that the QLMI is able to measure longitudinal changes in health- related quality of life.

An argument could be made that, for discriminative purposes, the QLMI adds little to existing emotional function questionnaires. This would follow from the high cross-sectional correlations with the emotional function measures. The same argument could not be made, however, for the use of the QLMI as an evaluative measure. The correlations of change between the QLMI and the emotional function measures were lower and, more important, the QLMI was more responsive than existing instruments.

Our results are consistent with those reported in a randomized trial of secondary prevention after suspected myocardial infarction conducted in Australia [25,26]. These workers reported that a slightly modified version of the QLMI was acceptable, and responsive in that it was able to distinguish between treatment and control groups.

In conclusion, the QLMI is a reliable measure of health-related quality of life which is able to discriminate between patients following AM1 according to both their emotional function and their overall view of their life quality. In studies of interventions for patients following AMI, most notably cardiac rehabilitation programs, the QLMI will detect smaller treatment effects, and thus require smaller sample sizes, than other available measures.

Acknowledgements-We would like to express our appreci- ation to David Streiner, Lori Ebbesen, Norman Jones, Robert McKelvie, Joanne Runions and George Torrance for help in planning and conducting the study and David Streiner for helpful comments on the manuscript. This work was supported in part by the National Research and Development Program, Health and Welfare, Canada. Dr Guyatt is a Career Scientist of the Ontario Ministry of Health.

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APPENDIX

Quality of Life Questionnaire (QLMI)

This questionnaire is designed to find out how you have been feeling during the last 2 weeks. The questions that you will be asked all relate to problems or feelings that patients often have after a heart attack. You will be asked about some of the symptoms you may have experienced, how tired you have been feeling and how your mood has been.

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How much time during the last two weeks have you felt frustrated, impatient or angry? Please indicate how often you have felt frustrated, impatient or angry by choosing one of the following options: (BLUE CARD) How often during the last two weeks have you felt worthless or inadequate? (BLUE CARD) In the last two weeks, how much time did you feel very confident and sure that you could deal with your heart problem? (YELLOW CARD) In general how much of the time did you feel discour- aged or down in the dumps during the last two weeks? (BLUE CARD) How much of the time during the last two weeks did you feel relaxed and free of tension? (YELLOW CARD) How often during the last two weeks have you felt worn out or low in energy? (BLUE CARD) How happy, satisfied, or pleased have you been with your personal life during the past two weeks? (GRAY CARD) How often during the last two weeks have you felt restless, or as if you were having difficulty trying to calm down? (BLUE CARD) How much shortness of breath have you experienced during the last two weeks while doing your day-to-day physical activities? (GREEN CARD) How often during the last two weeks have you felt tearful, or like crying? (BLUE CARD) How often during the last two weeks have you felt as if you are more dependent than you were before the heart attack? fBLUE CARD) How often during the last two weeks have you felt you were unable to do your usual social activities, or social activities with vour familv? (BLUE CARD) How often during the lait two weeks have’you felt as if others no longer have the same confidence in you as they did before the heart attack? (BLUE CARD) How often during the last two weeks have you experienced chest pain while doing your day-to-day activities? (BLUE CARD) How often during the last two weeks have you felt your heart problem limited or interfered with sexual inter- course? (BLUE CARD) How often during the.last two weeks have you felt unsure of yourself or lacking in self-confidence? (BLUE CARD) How often during the last two weeks have you been bothered by aching or tired legs? (BLUE CARD)

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During the last two weeks how much have you been limited in doing sports or exercise as a result of your heart problem? (PINK CARD) How often during the last two weeks have you felt apprehensive or frightened? (BLUE CARD) How often during the last two weeks have you felt dizzy or lightheaded? (BLUE CARD) During the last two weeks how much have you been restricted or limited as a result of your heart problem (PINK CARD) How often during the last two weeks have you felt unsure as to how much exercise or physical activity you should be doing? (BLUE CARD) How often during the last two weeks have you felt as if you are no longer a real man/woman (BLUE CARD) How often during the last two weeks have you felt as if your family is being overprotective towards you? (BLUE CARD) How often during the last two weeks have you felt as if you were a burden on others? (BLUE CARD) How often during the last two weeks have you felt you could manage your chest pain or discomfort when, or if, it occurred? (YELLOW CARD)

Domains :

Symptoms: 6, 9, 14, 17, 20 Restriction: 12, 15, 18, 21 Confidence: 3, 19, 22, 24, 26 Self-esteem: 2, 11, 13, 16, 23, 25 Emotion: 1, 4, 5, 7, 8, 10

Response options

BLUE CARD

1 ALL OF THE TIME 2 MOST OF THE TIME 3 A GOOD BIT OF THE TIME 4 SOME OF THE TIME 5 LITTLE OF THE TIME 6 HARDLY ANY OF THE TIME 7 NONE OF THE TIME

YELLOW CARD

1 NONE OF THE TIME 2 A LITTLE OF THE TIME 3 SOME OF THE TIME 4 A GOOD BIT OF THE TIME 5 MOST OF THE TIME 6 ALMOST ALL OF THE TIME 7 ALL OF THE TIME

GRAY CARD

1 VERY DISSATISFIED. UNHAPPY MOST OF THE TIME 2 GENERALLY DISSATISFIED, UNHAPPY 3 SOMEWHAT DISSATISFIED, UNHAPPY 4 GENERALLY SATISFIED, PLEASED 5 HAPPY MOST OF THE TIME 6 VERY HAPPY MOST OF THE TIME 7 NONE OF THE TIME

GREEN CARD

EXTREME SHORTNESS OF BREATH VERY SHORT OF BREATH QUITE A BIT OF SHORTNESS OF BREATH MODERATE SHORTNESS OF BREATH SOME SHORTNESS OF BREATH A LITTLE SHORTNESS OF BREATH NO SHORTAGE OF BREATH


PINK CARD 3 LIMITED QUITE A BIT 4 MODERATELY LIMITED

I EXTREMELY LIMITED 5 SOMEWHAT LIMITED 6 LIMITED A LITTLE

2 VERY LIMITED 7 NOT LIMITED

Table Al. Summary of outcome measures

Questionnaire In hospital Baseline screen 8 weeks 4 months 8 months 12 months

Beck depression Spielberger Ex-testing QLMI Bush QWB TTO POMS

X X X X X X X X X X

X X X X X X X X X X X X X X X X X X X X X X X

Documents

Quality of life after myocardial infarction