False negative reports of a general substance-related problem can include statements that the person did not take the substance when he or she had been using, admissions of use but denial of high levels of consumption or associated problems that occurred, or a person admitting to substance related difficulties but denying an overarching problem with the substance . For alcohol, the focus of the current analyses, the latter might be a form of denial that is especially problematic for clinicians who only ask general questions about substance use and problems rather than using standardized screening questionnaires, like the Alcohol Use Disorders Identification Test . In such situations, the clinician might ask questions like “How much do you drink?” or “How would you describe your drinking pattern?”. The answer they might receive from many individuals who fit the definition of an AUD could be something like “I’m a moderate social drinker”. Much of the literature on denial has focused on underlying mechanisms that contribute to false negative reports regarding SUDs. Possible mechanisms include deliberate and conscious lies to avoid negative views from others or consequences of the behaviors and false negative reports from cognitive difficulties in correctly appraising the dangers of the substance use . Other theories reflect psychodynamic defense mechanisms where persons facing substance-related psychological stressors subconsciously “defend” themselves by denying that the substance problem or adverse event occurred . It is likely that multiple factors contribute simultaneously to denial ,trimming tray and the literature suggests that the underlying mechanisms might differ with different drugs and for different situations . The current analyses focus on inaccurate denial of current AUDs in individuals who report themselves as light or moderate social drinkers. To prepare for the study we searched the literature for specific characteristics of individuals who evidence denial.
Regarding demography, the most consistent data were seen for race/ethnicity where a relatively scant literature indicated that a range of denial-related behaviors were more common for African American and Hispanic American subjects than for European Americans . Marital status and education level did not consistently relate to the probability of denial , although one study suggested more denial among lower educated individuals . Even more inconsistent results were seen for the relationship to denial for sex, age, socioeconomic status or income . We found no published studies regarding whether an individual’s report of specific AUD criteria items were more likely to relate to inaccurate recognition or reluctance to admit to an overall alcohol problem. Optimally, the impact of specific criteria should be evaluated while also considering the relationship of denial to drinking quantities, the number of alcohol problems, and whether an individual has alcohol abuse or dependence in DSM-IV. Our group recently reported a phenomenon that might overlap with denial. That paper searched for characteristics of San Diego Prospective Study probands with AUDs whose young-adult offspring erroneously reported no significant alcohol problems in that parent . The attributes of the person who denies their own overarching alcohol problem might be similar to characteristics related to lack of recognition of his alcohol-related difficulties by his offspring. Items associated with an offspring’s incorrect report of their father’s problems included the lack of endorsement of four specific AUD criterion items. These included probands denying spending a great deal of time to obtain, use, and/or recover from alcohol , not endorsing decreasing important activities due to alcohol , and not admitting to continuing to use alcohol despite physical and/or psychological problems or despite social and/or interpersonal problems . This paper uses data from two SDPS generations to evaluate characteristics associated with denial of global ratings of problem drinking in individuals who admitted to specific abuse or dependence criteria.
The analyses test five hypotheses: 1) Based on clinical experience and the literature we estimate 30%–50% of SDPS AUD subjects will not rate themselves as falling into problem drinking categories; 2) The lower the number of AUD criteria endorsed the greater the chance of denying having a general problem with alcohol; 3) The lower the maximum drinks endorsed the greater the probability of denying having a general problem with alcohol; 4) Individuals with alcohol abuse will be more likely than those with alcohol dependence to deny having a general problem with alcohol; and 5) The absence of the four criterion items that related to false negative reports by offspring of their proband father’s AUD will also relate to that father’s own denial of a general problem with alcohol including D5 ; D6 ; D7 ; and A4 . Following University of California, San Diego Institutional Review Board approval, randomly mailed questionnaires were used to recruit 453 SDPS probands as drinking 18-to-25-year-old male UCSD students who never met criteria for an AUD, SUD, bipolar disorder or schizophrenia and did not currently have a major depressive or anxiety disorder.Beginning in 1988, the 453 probands began participation in every five-year personal follow-ups using a semi-structured interview reviewing substance use and problems based on the Third-Revised and Fourth Diagnostic and Statistical Manuals . The questions were extracted from the Semi-Structured Assessment for the Genetics of Alcoholism. Fifteen-year follow-ups included the Self Report of the Effects of alcohol questionnaire, the Impulsiveness Subscale of the Karolinska Scales of Personality and the Zuckerman Sensation Seeking Scale . The SRE records numbers of standard drinks required for up to four effects including a first effect, feeling dizzy or slurring speech, unstable standing, and unplanned falling asleep. SRE-5 scores for the first five times of drinking and is generated by the total drinks in that period needed across effects divided by the number of effects endorsed. SRE-T scores reflect the average across first five, heaviest drinking period, and recent 3-month drinking. Higher average drinks needed for effects indicates lower response per drink and higher future risk for alcohol problems . As probands’ biological children reached age 18, they were personally interviewed every five-years using SSAGA-based questions. The first interview following their 18th birthday included the impulsivity and sensation seeking questionnaires, and, for those with experience with drinking, the SRE.
Analyses include all 94 AUD male probands and all 176 offspring who met AUD criteria in the five-years prior to the index interview and these participants were not chosen as proband-off spring pairs. Their SSAGA-like interviews queried their recent five-year quantities, frequencies and problems associated with substances, including all 11 DSM-IV substance-related criterion items. We added a final question to the alcohol section which asked: “Since your prior evaluation , how would you label your own drinking pattern overall?” The options included: 1) nondrinker/abstainer; 2) infrequent/occasional light social drinker; 3) moderate social drinker; 4) frequent/heavy social drinker; 5) problem drinker/alcoholic; and 6) recovering alcoholic. The follow-up rate in the SDPS was over 90 %, and maximum likelihood procedures were used to address missing data with Little’s MCAR test showing data missing completely at random . Tables 1,2,3, respectively, describe AUD proband and AUD offspring demography, personality, and substance-related variables for all relevant participants combined and then separately for subjects who rated themselves as falling into categories 1–3 regarding their drinking pattern overall versus those who rated themselves as categories 4–6 . The deniers were reporting categories that might indicate to clinicians that a patient does not have problems with alcohol. The first step, univariate comparisons of Groups 1 versus 2, used F-tests for continuous variables and x2 for categorical data. Tables 2 and 4 present our key results involving backwards elimination logistic regression analyses using variables that significantly differentiated between deniers and non-deniers in Tables 1 and 3. Finally regarding methods, for both probands and offspring data, multicollinearity was assed using both simple correlation matrixes among the variables and evaluating for variance inflation factors . For correlations, values greater than or equal to 0.80 and for VIF values greater than 5 indicate possible multicollinearity .Table 1 for probands and Table 3 for offspring each first present data for the entire relevant sample and then separately for Group 1 denier and Group 2 non-denier participants. Self-ratings of their general alcohol status among AUD probands included 0% nondrinkers, 12 % infrequent/occasional light social drinkers, 55 % moderate social drinkers, 25 % frequent/heavy social drinkers, 6% problematic drinkers/alcoholics and 2% recovering alcoholics. AUD offspring self-ratings were 0% non-drinkers, 24 % infrequent/occasional light social drinkers, 58 % moderate social drinkers, 13 % frequent/heavy social drinkers, 2% problematic drinkers/alcoholics and 3% recovering alcoholics. Table 1 demonstrates that overall most AUD probands were European American, had ever married, 70 % had children, and their average education was 17 years. On average, probands endorsed 2.5 AUD criteria and 52 % were alcohol dependent with the remainder meeting alcohol abuse. Thirty-one percent had used cannabis in the recent five-years, 4% met cannabis use disorder criteria, 17 % smoked cigarettes,10 % used other illicit drugs, including 2% who met SUD criteria on that substance. Among AUD probands, 67 % were classified as deniers of problematic drinking . Significant alcohol-related univariate comparisons between probands in Groups 1 and 2 revealed that deniers were less likely to have alcohol dependence, reported lower average maximum drinks,grow tent kit and were less likely to endorse five AUD criteria, including dependence criteria D4, D5, and D7, along with abuse criteria A1 and A4. These included three of the four criteria predicted in Hypothesis 5.
Deniers were also less likely to have SUDs for noncannabis drugs. While not noted in the table, the correlation between a false negative family report of a father with an AUD in the prior paper and an AUD father being a denier in the current analysis was 0.28 . Table 2 presents results predicting AUD proband denier status using a backwards elimination logistic regression analysis that included variables that differed significantly across deniers and non-deniers in Table 1. Four variables contributed significantly to the analysis including three of the criteria predicted in Hypothesis 5 along with a SUD on illicit drugs other than cannabis. Tables 3 and 4 focus on 176 AUD offspring who were primarily European American, 40 % of whom were women, 29 % had ever been married, and individuals who reported on average 15 years of education. Sixty-two percent met interval criteria for alcohol dependence, they reported on average 11 maximum drinks per occasion and endorsed an average of four AUD criteria. One in five smoked cigarettes in the prior 5 years, 80 % used cannabis,19 % had a cannabis use disorder, and 37 % had used other illicit drugs, including 3% who developed a SUD on those substances. Comparisons of Groups 1 and 2 revealed that the 82 % who were deniers were slightly younger and had lower proportions with alcohol dependence, lower average maximum drinks, and fewer AUD criteria endorsed compared to non-deniers. Group 1 deniers were also less likely to endorse every specific AUD criterion except for D3 . AUD offspring in Group 1 on average reported fewer drinks required for effects across the time frames , were less involved with other drugs and had lower scores on sensation seeking. Group 1 and 2 offspring comparisons were repeated for the 106- male offspring, 84 of whom were deniers. Here, results were generally consistent with those in Table 3. Analyses using the 70 female offspring alone could not be adequately interpreted because there were only 9 non-deniers. Table 4 describes the backwards elimination regression analysis predicting denial in AUD offspring using variables that differed significantly across Groups 1 and 2 in Table 3. Like Table 2, significant predictors of denial involved indicators of less intense alcohol involvement and less use and/or problems with other drugs. The five specific variables in Table 4 included only one that contributed to Table 2 and one variable noted in Hypothesis 5 , but D6 had not entered the regression analysis for probands. The three other variables included lower proportions of deniers who smoked, reported alcohol withdrawal, or met criteria for alcohol dependence. If regression analyses were limited to the 106 AUD males, denial remained associated with lower levels of both alcohol and drug related problems, but the specific items for male offspring included a lower average maximum drinks per occasion, lower cannabis use, and deniers had a lower average age. Within the same interview session 67 % of SDPS probands with current AUDs and 82 % of current AUD offspring endorsed enough alcohol problems to meet DSM-IV AUD criteria but denied having a general alcohol problem.