Medical University of Lübeck, Department of Psychiatry and Psychotherapy, Research Group S:TEP (Substance Abuse: Treatment, Epidemiology, and Prevention), Lübeck and
1 University of Greifswald, Institute of Epidemiology and Social Medicine, Addiction Research Center, Greifswald, Germany
Received 29 December 2000; in revised form 7 September 2001; accepted 18 November 2001
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ABSTRACT |
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INTRODUCTION |
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Only a few studies have addressed the validity of screening questionnaires in the general population. The CAGE (Ewing, 1984; Mayfield et al., 1974
) (acronym based on its four items: Cut down on drinking, Annoyed by criticism, Guilty feelings, and Eye opener) revealed a lower sensitivity in the general population than in primary-care patients (Chan et al., 1994a
; Cherpitel, 1998
) and in an emergency room setting (Cherpitel, 1998
). Interestingly, among the general population sample of the latter study, the CAGE showed a tendency to perform better among individuals reporting an emergency room or primary-care visit in the previous 12 months and was significantly more sensitive in men with a previous emergency room visit in the last year (Cherpitel, 1999
). The lower validity of the CAGE in general population samples corresponds with findings from a large scale Canadian study (Bisson et al., 1999
). The Brief MAST (Pokorny et al., 1972
), a shortened version of the Michigan Alcoholism Screening Test (MAST; Selzer, 1971
), was also less sensitive in a general population sample compared with primary-care out-patients (Chan et al., 1994b
). For the TWEAK test (Russell et al., 1994
) (acronym based on its five items Tolerance, Worry about drinking, Eye opener, Amnesia (blackouts), and c(K)ut down on drinking), findings are not so clear. In one study, the sensitivity of the TWEAK was lower in the general population, compared to an emergency room sample, but higher compared to primary-care patients, in identifying alcohol dependence (Cherpitel, 1998
). In a second study, no differences in sensitivity were found between a general population and a primary-care sample in detecting heavy drinking (Chan et al., 1993
). Using alcohol dependence as gold standard, differences in sensitivity of the TWEAK between samples depended on two versions of the tolerance item. In summary, there is evidence that screening questionnaires show different psychometric properties in the general population, compared to samples drawn in medical settings. No data with respect to the validity in the general population could be found for three more recently developed instruments: the Alcohol Use Disorders Identification Test (AUDIT; Babor et al., 1989b
; Saunders et al., 1993
), the AUDIT Alcohol Consumption Questions (AUDIT-C; Bush et al., 1998
) and the Lübeck Alcohol Dependence and Abuse Screening Test (LAST; Rumpf et al., 1997
). The AUDIT has been used in the general population; however, data are restricted to subgroups (unemployed; Claussen and Aasland, 1993
) and do not give clear estimates of validity such as sensitivity and specificity based on a gold standard (Holmila, 1995
; Fleming, 1996
; Medina-Mora et al., 1998
).
The aims of the present study were: (1) to assess and compare the performance of the AUDIT, the AUDIT-C and the LAST in a general population sample; (2) to examine different cut-off points for the three instruments; (3) to analyse age and gender effects; (4) to test whether sensitivity and internal consistency varied in the subsamples of individuals reporting general hospital admissions or general practice visits in the previous 12 months.
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SUBJECTS AND METHODS |
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Sample
From 6447 addresses drawn from the office files, 618 (9.6%) were invalid for various reasons (e.g. the individual moved away, was not known in the household, deceased, or did not fulfil the inclusion criteria). Of the remaining 5829 valid addresses, 665 (11.4%) individuals were not available during the study period, 83 (1.4%) did not participate because of being ill, 979 (16.8%) refused to participate, and nine (0.2%) refused an interview other than by telephone or only partially completed the interview. This results in a response rate of 70.2%. Of these 4093 interviews, 18 could not be analysed mainly because of technical problems. Therefore, the sample consisted of 4075 respondents. Only individuals consuming alcohol within the last 12 months (n = 3641) were asked to fill out the AUDIT and the LAST. Seventy-nine individuals had at least one missing value in AUDIT or LAST and 11 had missing values with respect to the recency of the alcohol-related disorders or in quantityfrequency questions, and were thus excluded from the analysis, which resulted in a final sample of 3551 analysed subjects. Of this sample, 50.8% were male, 45% had up to 9 years of schooling, 32.8% 1011 years, and 22.1% 12 or more years. Mean (± SD) age was 41.2 ± 12.8 years. Of the sample, 59.6% were married, 28.5% never married, and 11.9% widowed, divorced or separated.
Diagnosis of alcohol-related disorders
Alcohol dependence according to DSM-IV (American Psychiatric Association, 1995) was assessed by the Munich Composite International Diagnostic Interview (M-CIDI; Wittchen et al., 1995
) the German version of the CIDI (Robins et al., 1988
). Interviewers were trained by World Health OrganizationCIDI trainers in a 1-week course. Five psychologists supervised and edited the interviews. Of the sample described above, 1.4% fulfilled DSM-IV criteria in the last 12 months for current alcohol dependence and 1.2% for current alcohol misuse according to M-CIDI. For alcohol use disorders according to M-CIDI, testretest reliability was found to be excellent (Wittchen et al., 1998
).
Following criteria of the British Medical Association (1995), at-risk drinking was defined as average daily consumption of at least 20 (women) or 30 (men) g of pure alcohol. Alcohol consumption was assessed by using the quantityfrequency questions of the M-CIDI. Individuals drinking alcohol more than 12 times in the last 12 months were defined as current drinkers. Among these individuals, frequency of alcohol consumption was assessed by using the following categories: almost daily, 34 times per week, 12 times per week, 13 times per month, less often than monthly. Quantity assessment was supported by a visual aid showing typical alcoholic beverages. One standard drink was converted into 9 g of pure alcohol. A quantityfrequency index was computed by using the mean of the categories. The quantityfrequency assessment of the M-CIDI showed excellent testretest reliability (Lachner et al., 1998). Among the sample described above, 5.4% fulfilled criteria for at-risk drinking.
These rates of at-risk drinking, alcohol dependence, and alcohol misuse are rather small compared to data from the USA and are lower than in other regions of Germany. This is due to distinct regional differences in alcohol consumption between federal states in Germany with rates of at-risk drinking ranging between 2.2 and 23% (mean: 13.5%). Lübeck belongs to the state with the second lowest rate of at-risk drinkers (Meyer et al., 1998).
Screening questionnaires
German versions of AUDIT and LAST were presented as self-administered questionnaires at the end of the interview. The English language version items and the scoring are presented in Table 1. The alcohol use disorders section of the M-CIDI was presented after the sections on sociodemographics, tobacco use, affective, anxiety, somatoform, and eating disorders. Between the alcohol section of the M-CIDI and the screening questionnaires, comprehensive questions not related to alcohol were presented including the CIDI sections on obsessivecompulsive disorder, illicit drugs, and post-traumatic stress disorder, followed by questions on health-care utilization and several self-administered questionnaires with 125 items on mental health, sense of coherence, satisfaction with life, social support, nutrition, and physical activities. In total, questions on mental health far outnumbered questions on alcohol use.
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The AUDIT-C (short for AUDIT consumption questions) includes the first three items of the original instrument (Bush et al., 1998). Using a cut-off of 3 points, the AUDIT-C revealed a sensitivity of 0.90 for active alcohol misuse or dependence and 0.98 for heavy drinking (>14 drinks a week or
5 drinks on one occasion) with a rather low specificity (0.60). A higher cut-off resulted in a sensitivity of 0.86 and a specificity of 0.72 of patients with heavy drinking or alcohol dependence or misuse. The AUDIT-C outperformed the full AUDIT when identifying heavy drinking, but was inferior for alcohol misuse or dependence. Findings are restricted to male subjects and, to date, no further validation is available. In our study, the AUDIT-C scores were calculated by using the first three items of the full AUDIT.
The LAST was developed in a general hospital sample by combining the instruments CAGE and MAST (Rumpf et al., 1997). This questionnaire consists of seven dichotomous items (two from the CAGE and five from the MAST) and is scored without using weightings, with 2 points as cut-off. The LAST revealed a higher sensitivity, compared to the CAGE and the 13-item Short Michigan Alcoholism Screening Test (SMAST; Selzer et al., 1975
) and showed no significant differences in sensitivity when compared to the more comprehensive MAST (Rumpf et al., 1997
). The sensitivity in the detection of patients with alcohol dependence or misuse ranged from 0.63 (general practice) to 0.87 (general hospital). The specificity ranged between 0.88 (general hospital) and 0.93 (general practice). Compared to AUDIT and AUDIT-C, the LAST incorporates two items with more clinical aspects (Have you ever been told you have liver trouble? Cirrhosis?, Have you ever been in a hospital because of drinking?).
Data analysis
The concurrent validity of the screening questionnaires was assessed by calculating sensitivity (rate of correctly identified individuals having the respective disorder) and specificity (rate of correctly identified individuals not having the respective disorder). Differences in sensitivity between tests were analysed using the non-parametric McNemar test for two related samples. Receiver-operating characteristics (ROC) curves were computed using SPSS 9.0; the area under the curve was used to compare the performance of the instruments by additional calculations (McClish, 1991). ROC curves allow the exploration of the entire range of sensitivities and specificities at each possible cut-off point by showing sensitivity at the y-axis and (1 specificity) at the x-axis. Cut-off point decisions were made on grounds of the ROC curves. Those cut-offs were chosen where concavities occurred, otherwise the closest distance of the curve to the upper left corner was sought, and the cut-point above this was chosen.
To compare the quantityfrequency assessment of AUDIT and M-CIDI as a measure of concurrent validity, a quantity frequency index was computed by using the mean of the categories of the AUDIT questions as multiplier (AUDIT 1: 0, 0.033, 0.1, 0.357, 0.786; AUDIT 2: 1.5, 3.5, 5.5, 8, 10) Logistic regression analyses were used to examine the impact of gender and previous health-care utilization on the sensitivity of the screeners. Cronbach's alpha was calculated to assess internal consistency.
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RESULTS |
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Table 4 displays differences in sensitivity and specificity between tests at cut-off points found to be appropriate in the present sample. For this comparison, the following cut-off points were used. For the AUDIT, 5 was used as a cut-off point in all subgroups, except for alcohol dependence (cut-off: 6). For the AUDIT-C, 5 was used as the cut-off point with regard to each criterion, and for the LAST, 1 point served as the threshold for all three criteria. The AUDIT performed best for at-risk drinking, showing significantly higher sensitivity, but specificity was lower compared to AUDIT-C and LAST. For current alcohol misuse and alcohol dependence, no significant differences in sensitivity were found between tests. The LAST outperforms both AUDIT versions in specificity for alcohol misuse and the AUDIT shows better specificity for alcohol dependence, compared to the other tests. Using any of the three criteria, the AUDIT outperforms AUDIT-C and LAST in sensitivity, whereas AUDIT-C and LAST show higher specificity.
Internal consistency
Cronbach's alpha was used as a measure of internal consistency. The AUDIT showed a moderate alpha of 0.75. The lowest corrected item-total correlation was found for item 1 (frequency of alcohol consumption: 0.28) and item 9 (injured as a result of drinking: 0.36), all other items ranged between 0.48 and 0.58. The AUDIT-C, having only three items, revealed low internal consistency with an alpha of 0.56. Corrected item-total correlations ranged from 0.30 (item 1: frequency) to 0.52 (item 3: 6 drinks on one occasion). The LAST showed a moderate Cronbach's alpha of 0.72. The lowest corrected item-total correlation was found for item 1 (always able to stop drinking: 0.28) and item 6 (been told of having liver problems: 0.36), all other item-total correlations ranged between 0.44 and 0.58.
Impact of previous general hospital admissions and general practice visits on sensitivity and internal consistency
To examine if questionnaires have different sensitivities for individuals with previous primary-care contacts, logistic regression analyses were performed separately for the three questionnaires. As dependent variable, the sensitivity of the respective test (0 = not identified; 1 = identified), separately for each of the three criterion groups, was used. As independent variable, two dichotomous variables were entered separately: any general hospital admission (n = 393) and any general practice visit (n = 2660) in the last 12 months. Results showed that general practice visits had no significant impact on predicting the sensitivity of any of the three instruments. A general hospital admission, however, increased the chance of being detected by the LAST for any criterion group [odds ratio (OR) = 2.03; CI = 1.033.99; P < 0.05], but not for the single groups. Using the number of doctor visits and the number of hospital admissions as independent variable revealed the following results. The number of doctor visits was related to higher odds ratios in detecting alcohol misuse by the AUDIT-C (OR = 1.95; CI = 1.063.58; P < 0.05); this relationship was close to significance for the AUDIT (P = 0.059). The number of general hospital admissions had an impact on the detection by the LAST (OR = 1.73; CI = 1.052.86; P < 0.05).
When calculating Cronbach's alpha for the subsample with primary-care utilization in the previous year, internal consistency increased for all questionnaires in those individuals with a general hospital admission in the previous 12 months (AUDIT: from 0.75 to 0.85; AUDIT-C: from 0.56 to 0.66; LAST: from 0.72 to 0.77).
Impact of age and gender on performance
Age showed no meaningful correlations (Spearman rho) with total scores of AUDIT (0.052), AUDIT-C (0.037), and LAST (0.015). The mean scores of the questionnaires were compared between male and female participants (t-test). The AUDIT showed higher scores for male (mean ± SD = 4.49 ± 3.63) than for female (2.71 ± 2.02) participants (t = 18.13; df = 2838.85; P < 0.001). The AUDIT-C also had higher scores for male (3.80 ± 1.62) than for female (2.51 ± 1.42) participants (t = 22.70; df = 3321.82; P < 0.001). The LAST showed higher scores for male (0.47 ± 01.03) than for female (0.20 ± 0.71) individuals (t = 8.96; df = 3215.16; P < 0.001).
As shown in Table 5, areas under the ROC curve differed between men and women. AUDIT and AUDIT-C revealed significantly larger areas for at-risk drinking and any criterion in women. Logistic regression analyses, using gender as dependent variable, revealed differences in sensitivity. Sensitivity was determined by using the adjusted lower cut-offs as described above. The AUDIT was less sensitive in women in detecting at-risk drinking (OR = 0.27; CI = 0.130.54; P < 0.001), alcohol misuse (OR = 0.09; CI = 0.010.88; P < 0.05), and any criterion (OR = 0.29; CI = 0.160.52; P < 0.0001). Results were similar for the AUDIT-C with respect to two diagnostic groups: at-risk drinking (OR = 0.26; CI = 0.130.50; P < 0.001) and any criterion (OR = 0.30; CI = 0.170.53; P < 0.0001); results were only close to significance for alcohol misuse (P = 0.06). The LAST showed less sensitivity in detecting any criterion group in women (OR = 0.54; CI = 0.320.91; P < 0.05).
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DISCUSSION |
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Comparing the validity measures of the questionnaires with the above-recommended cut-off scores revealed that AUDIT outperforms AUDIT-C and LAST with respect to sensitivity in detecting at-risk drinking. No significant differences in sensitivity between tests could be found for current alcohol dependence or misuse. It must be remembered that the latter groups have smaller sample sizes (n = 49 and 41, respectively), compared to the at-risk drinking group (n = 191). Therefore, differences between tests for alcohol dependence or misuse might reach significance when using larger sample sizes. On the other hand, only small differences in specificity reached significance, because of the respective large groups of individuals with no diagnosis.
The fact that the AUDIT-C, which is a pure alcohol consumption measure, is as good as the full AUDIT, which comprised additional items on negative consequences and signs of dependence, is surprising. However when comparing areas under the ROC curves, there was a tendency (P = 0.08) of the AUDIT to perform better in detecting alcohol dependence. Further research is necessary to confirm the performance of the AUDIT-C in detecting alcohol dependence or misuse. It is important to mention that the AUDIT-C was presented as part of the AUDIT in our study; the instrument might have performed differently if the questionnaire had been given without items 410 of the AUDIT.
Findings with respect to the performance of the screening questionnaires for individuals who did, and those who did not, report previous health-care utilization are not so clear cut. This corresponds with findings on the detection of alcohol dependence by AUDIT and TWEAK from an US general population sample (Cherpitel, 1998, 1999
). In our sample, a previous general hospital admission in the last year increased the chance of being detected by the LAST as having any criterion (at-risk drinking, alcohol misuse or alcohol dependence). Data suggest that the LAST reveals a higher sensitivity in general hospital patients. This is in line with the fact that this instrument was developed in a general hospital setting and incorporates items with the more clinical aspects (liver problems, hospital admission). The number of doctor visits corresponds only with a higher sensitivity in detecting alcohol misuse of the AUDIT-C and (as a tendency) for the AUDIT. The lack of uniform findings with respect to the impact of previous health-care utilization suggests that the relationship is more multi-faceted. One confounding variable might be found in the current influence of the setting on the disclosure of alcohol problems when visiting a doctor or being admitted to a hospital. Findings on an elevated readiness to change drinking behaviour of alcohol-dependent individuals in a general hospital, compared to alcohol-dependent subjects in the general population (Rumpf et al., 1999
), underpin this assumption. Hence, retrospective questions on health-care utilization cannot assess all relevant aspects, when simulating the setting specific performance of screening questionnaires in a general population sample. Assessment at a time other than during admission to a health-care facility may well result in different findings.
In our sample, AUDIT and LAST revealed moderate Cronbach's alpha (AUDIT: 0.75; LAST: 0.72). Although it has to be considered that Cronbach's alpha is related to the number of items, internal consistency for the AUDIT-C was quite poor (alpha = 0.56). The internal consistency for the AUDIT corresponds with the lower part of the range in five studies reviewed by Allen et al. (1997). Cronbach's alpha for the AUDIT ranged from 0.75 to 0.94 in different samples including primary care (Barry and Fleming, 1993; Schmidt et al., 1995
), college students (Fleming et al., 1991
), and individuals arrested for driving while intoxicated (Hays et al., 1995
). No data are available on the internal consistency of the AUDIT-C. Cronbach's alpha for the LAST was lower, compared to data from general hospital (0.77 to 0.81) and slightly higher compared to general practice data (0.69) (Rumpf et al., 1997
). Using only those individuals with previous general hospital admission in the last 12 months for analysis, increased alpha for all instruments. Our findings suggest that these screening instruments would all show higher reliability in clinical subsamples.
No age-related differences in the performance of the tests were found, but there were significant gender effects. In women, lower mean scores were observed for all three questionnaires, the areas under the ROC curves were larger for at-risk drinking and any criterion using AUDIT and AUDIT-C, and sensitivity was lower for some criterion groups in all instruments. Data suggest that lower cut-offs should be used in female subjects, which is in line with a review on alcohol screening questionnaires in women (Bradley et al., 1998). Moreover, it might be worthwhile to develop gender-specific questionnaires.
Some limitations of the present study have to be considered. The prevalence rates of alcohol-related disorders and at-risk drinking in our sample were quite low, due to drinking practices in the study area involved. The catchment area is in a state near the bottom of the range for Germany which has substantial regional variations in alcohol consumption (Meyer et al., 1998). Although this may have lowered the internal consistency of the questionnaires, we believe this did not substantially affect their validity. However, low prevalence rates have an impact on choosing a cut-off score. People living in areas with high rates of at-risk drinking might have lower scores on some items reflecting social norms of drinking. As a consequence, it might be necessary to change cut-off points. In addition, choosing a cut-off depends on prevalence rates. Given a fixed cut-off point, the probability of a positive screening result being true becomes lower, as the prevalence decreases (positive predictive value).
AUDIT followed by LAST were presented at the end of a comprehensive interview including the substance misuse module of the M-CIDI. Therefore, serial effects have to be considered. One study showed that the sensitivity of the CAGE was lower if alcohol consumption questions were asked first (Steinweg and Worth, 1993). The quantityfrequency assessment of the M-CIDI may have had a similar effect on AUDIT and LAST. However, comprehensive material not related to alcohol was presented between the alcohol use disorders section of the M-CIDI and both questionnaires. Moreover, the vast majority of questions of the entire interview were on mental health and not related to alcohol use. These facts make it rather unlikely that serial effects led to a significant bias in this study.
Our data underline previous findings that screening questionnaires show different validity measures in the general population. Moreover, results presented here suggest that screening instruments are less reliable in the general population, compared to clinical settings. Therefore, data of screening measures in the general population have to be interpreted carefully. To improve the accuracy of screening, the use of two or more complementary instruments should be considered (Rumpf et al., 1998b). Another way of improving screening might be to use simple criteria, such as gender or health-care utilization, to decide which instrument or which cut-off is most adequate. Finally, it is desirable to have a number of different or modified screeners available that perform best in specific settings such as general practice, general hospital, emergency room, work place or the general population.
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ACKNOWLEDGEMENTS |
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FOOTNOTES |
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