The (CAARS) Conners’ Adult ADHD Rating Scales, published by WPS for clinicians, educators and researchers, can be purchased online. Description: The Symptom Checklist is an instrument consisting of the eighteen DSM-IV-TR criteria. Six of the eighteen questions were found to be the most. All participants completed the Conners’ Adult ADHD Rating Scale (CAARS)—self -report version (Conners et al., ). Responses to this item scale yield.

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Few studies have examined concordance between raters qdhd ADHD symptoms in adults; there is less information on how well rating scales function in distinguishing adult ADHD from other disorders.

The sample included adults evaluated for attention problems. Correlations and kappa values were calculated using self- and observer-ratings of item-level symptoms; sensitivity, specificity, and discriminant validity of cluster scores in predicting clinician diagnoses were computed for participants. Item-level concordance rates ranged from slight to fair. Cluster scores demonstrated a poor balance of sensitivity and specificity in predicting ADHD diagnosis; a high percentage of participants with internalizing disorders had scores in the clinical range.

Self- and observer- ratings on the CAARS provide clinically relevant data about attention problems in adults, but the instrument does not effectively distinguish between ADHD and other adult psychiatric disorders.

Diagnosis of the disorder in adults may be complicated: Though current clinical practice guidelines suggest that diagnostic evaluation should include a comprehensive interview and self- and observer- rating scales, limited information is available on how best to integrate discrepant data AACAP, Specifically, few studies have examined concordance between different raters of ADHD symptoms in adults or the degree to which information provided by each rater contributes to differential diagnosis; there is even less information as to how well rating scales function in distinguishing adult ADHD from other commonly diagnosed adult disorders.

Conners’ Adult ADHD Rating Scale™ (CAARS™)

The most comprehensive study to date examined the reliability and validity of three adult ADHD rating scales in a sample of adult outpatients with ADHD recruited from a psychomedical center in the Netherlands Kooij et al. These finding have led researchers to conclude that different scales may be appropriate to different assessment situations, as each appeared to contribute unique information, but that the relationship between rating scale, informant, and symptom presentation in adult ADHD has yet to be disentangled Kooij et al.

Rating scales, in particular, may be limited in their ability to discriminate ADHD from other adult disorders. Clinicians diagnosed participants in this study based on a synthesis of information drawn from self-report, corroborating documents, and interviews of family members, and these diagnoses were compared to the results of three self-rating scales: Depending upon criterion cutoff scores, false positives on the questionnaires were This lack of discriminative validity between the two clinical groups was particularly pronounced in women Barkley et al.

In sum, clinical analysis and synthesis of the range of interview, self-report, and collateral data is critical for accurate differential diagnosis of ADHD in adults. Research to date suggests that self- and observer-rating scales may each contribute uniquely to the determination of diagnosis and impairment, yet limited data regarding the reliability and discriminative validity of these scales makes is difficult for clinicians to determine their most appropriate use in the diagnostic decision-making process.

As such, more data are needed not only on the association between self- and other-ratings of ADHD symptoms in adults, but also on the degree to which these symptoms are associated with clinician-determined symptoms and overall clinical diagnosis. To begin to address this gap in the literature, this investigation was designed to examine the following: This sample included adults ages 18—70 years referred to a medical center-affiliated ADHD clinic for evaluation for attentional difficulties.

College-age participants were over-represented in the sample: Gender data was not available for 8. A subset of adults underwent a thorough ADHD assessment by a doctoral-level clinician.

Diagnoses were determined through a synthesis of the following data: The primary diagnoses for these participants were as follows: Demographic data of this subsample were similar to the larger sample. Both the self- and observer-rating forms of the CAARS were used in this investigation; the two versions are identical except that they are normed separately.

Eight cluster scores are derived from these items. T -scores are calculated for each scale based on age and gender. This measure takes the form of a semi-structured interview that methodically and thoroughly records the age of onset, presence, persistence, and faars of each of the 18 potential ADHD symptoms.

Prior to the interview patients caxrs CAADID Part I, a questionnaire that collects developmental information; information about academic, family, occupational, and personal functioning; and psychiatric history. Part II is the interview portion, which is administered by a clinician; this section assesses each symptom of ADHD in adulthood and in childhood, asking about specific examples of symptom manifestation at the different developmental levels.

Pearson correlations and kappa values for self- and observer-ratings were calculated for items corresponding to DSM-IV symptoms. Separate Pearson correlations were calculated between self-ratings and those of each of the most frequently represented observers: Z -scores were calculated and compared to determine if significant differences existed in concordance rates between self-ratings and those of the three different groups of observers on each of the symptom-specific items.


Sensitivity reflects the proportion of cases in which the presence of the disorder is correctly identified; an index with a high sensitivity may be understood as having a low Type II error rate in detecting the disorder.

Specificity, on the other hand, reflects the proportion of cases in which the absence of the disorder is correctly identified; an index with a high specificity may be seen as having a low Type I error rate. Crosstabs analyses were used to identify the number of cases for which the cluster score was in the clinical range and for which the clinician ultimately diagnosed the patient with ADHD true positives ; and to identify the number of cases for which the cluster score was not in the clinical range and the clinician did not ultimately diagnoses the patient with ADHD true negatives.

Percentages were then calculated by dividing number of true positives sensitivity or the number of true negatives specificity by the total sample. As a second measure of convergent and discriminant validity, sensitivity, and specificity were also calculated using a cut-off score based on the DSM-IV symptom-specific items.

The ability of the cluster scores to discriminate between ADHD and other adult psychopathology was examined. Finally, mean scores within each of the three diagnosis afhd ADHD, mood disorders, and anxiety disorders were calculated for each cluster for self- and observer-ratings. ANOVA was used to compare among the three diagnostic groups on each cluster score for self- and observer-ratings, and post hoc Bonferroni tests were used for pair wise comparisons. Symptom ratings across reporters were high in this clinical sample.

Symptoms were more frequently rated adhr present by patients than by observers; clinician ratings were variable, and did not appear to be more consistent with either self or observer reports across items.

Frequency rankings were similar across patients caara observers, but clinician rankings differed somewhat from both groups.

The score distributions for all of the self- and observer-rated symptoms were roughly normally distributed, with the exception of observer ratings of Problems with Self Zdhd Consistent with the item-level frequency reporting, cluster scores based on self-ratings were generally xdhd than those based on observer-ratings; this was especially evident for the DSM-IV Inattentive Symptoms cluster and for the DSM-IV Index cluster.

Pearson correlations were also calculated for the three xaars frequently represented observers: Results are presented in Table 2. Concordance was higher at the level of symptom clusters.

However, these sensitivities were offset by the corresponding specificities: The combination of self- and observer-ratings reduced the sensitivity of the scales to between 0. As a second measure of convergent and discriminant validity, the number of symptoms rated as present on the CAARS was compared with diagnosis as determined by the clinician.

For these analyses ADHD was considered to be present even if it was not listed as the primary diagnosis; a mood disorder, anxiety adhf, or other disorder was identified as the primary diagnosis only in the absence of ADHD.

Results indicated that of individuals identified as having ADHD based on self-ratings of symptoms, In sum, adding observer data to self-report was most useful in diminishing the chance of incorrectly diagnosing a depressed individual with ADHD. We then recalculated these percentages for those with both self and observer cluster scores in the clinical range to examine the degree to adbd including collateral rating-scale data helped to specify the presence of ADHD.

Findings are presented in Table 4. Cluster scores based on self-ratings varied widely in their degree of specificity to ADHD diagnosis. When observer-ratings in the clinical range were included, the pattern of association was similar but the percentages were lower. Finally, examination of the mean cluster scores of individuals with ADHD, mood disorders, and anxiety disorders confirmed that these scales were not effective at differentiating between ADHD and mood disorders.

Whereas mean scores on self-ratings were significantly different between ADHD and primary anxiety disorder on four of the eight scales, there were no significant ahd between ADHD and primary mood disorders on any of the self-rated scales.

This investigation examined the reliability and construct validity of self- and observer-ratings on the CAARS using a large sample of adults referred to a university-affiliated ADHD clinic for assessment of attention problems. Our goal was adhv provide information that would help clinicians integrate data from multiple informants in the assessment of adult ADHD.

Measures of concordance between self- and observer-ratings on the CAARS were examined at the item-level and at the level of cluster scores. Finally, divergent validity was assessed by examining the rate at which item-level symptom counts and cluster T -scores in the wdhd range for ADHD were also observed in other psychological disorders. The majority of the participants in this sample Having a substantial percentage of our sample who presented for assessment of attention problems, but who were ultimately determined to have disorders other than ADHD, also allowed us to explore the discriminant validity of the CAARS within a sample of high-risk aadhd in an outpatient setting.

Among the different observers friends, spouses, and parentsthere was only one significant difference in agreement with self-ratings on symptom-specific items; this suggests that at least with respect to the csars symptoms, various observers are likely to provide equally relevant data.


Unfortunately there were too few supervisors or coaches represented in our sample of observers to address this issue. Participants generally reported greater symptomatology than did observers; this was reflected in a consistently higher frequency of DSM-IV symptom endorsement at the item-level, as well as in higher mean T -scores on all CAARS clusters.

On the other hand, the frequency ranking of symptoms was afhd consistent between self and observer. This consistency in frequency ranking was not preserved in clinician ratings of the DSM-IV items, however: This adhf that participants and observers may interpret the behaviors described on the rating scales similarly, and may be relatively close in the degree to which they believe these behaviors caqrs common in cqars general population.

Given that one of the difficulties in diagnosing ADHD lies in determining how extreme the behavior is in relation to developmental and cultural norms, these findings suggest that it may be critical for clinicians to elicit concrete examples of behaviors and clear ratings of their frequency i.

DSM-III-R criteria for ADHD were endorsed too frequently on both self- and observer-ratings scales to provide an adequate basis for discriminating between those with and without the disorder. Clinically-elevated cluster T -scores demonstrated a relatively poor balance of sensitivity and specificity in predicting ADHD diagnosis. On this index, even when both self- and observer-ratings were in the clinical range the specificity only improved to 0.

As such, clinically-elevated T -scores on the CAARS clusters are relatively limited in the information they contribute to differentiating ADHD from other psychiatric disorders that commonly manifest in adulthood.

This lack of sensitivity and specificity in detecting ADHD in individuals with attention problems was underscored by the high percentage of participants with mood or anxiety disorders who produced cluster T -scores in the clinical range. Finally, an examination of mean cluster scores in those with ADHD, primary mood disorders, and primary anxiety disorders demonstrated that individuals with mood disorders are especially likely to be indistinguishable from those with ADHD on the CAARS.

Taken together, these findings suggest that while the CAARS is appropriate for screening for the presence of attention problems to determine whether or not a more thorough evaluation is necessary Conners et al.

Specificity of the CAARS in Discriminating ADHD Symptoms in Adults From Other Axis I Symptoms.

This conclusion is supported by studies in smaller samples of adults with depression, anxiety, or substance use disorders that have reported cluster scores comparable to caard found in ADHD Belendiuk et al. Diagnosing ADHD in adults may require different clinical skills than diagnosing the disorder in children, both because the symptoms may manifest differently, and because attention problems are common to many disorders that peak in adolescence and adulthood.

On the other hand, it is possible that there is a subset of the items on the CAARS that would more effectively distinguish between ADHD and other adult psychiatric disorders. However, because individuals who are diagnosed with ADHD in adulthood are frequently clinically complex and often present with multiple comorbidities Barkley et al.

To begin to address this issue, we are currently in the process of conducting factor analyses using a portion of this data set to examine how ADHD in adulthood csars to the child form of the disorder.

CAARS® – Conners’ Adult ADHD Rating Scales | Multi Health Systems (MHS Inc.)

Overall these findings point to the need for caaars examination of self-reported symptoms of adult ADHD, and particularly of inattentive symptoms, in determining their relevance to a diagnosis. This is especially the case if information about childhood caard is unreliable because of lack of access to appropriate reporters, or because of patient difficulty in remembering details about childhood behaviors.

Individual symptoms may not be highly concordant across reporters, and the attributions made casrs inattentive or impulsive behaviors are likely to vary among observers as well as across time and situation. In sum, the CAARS is an invaluable tool for identifying clinically significant problems with attention, but should be followed by a thorough clinical evaluation to determine differential diagnoses in adults seeking evaluation for ADHD.

The findings reported here must be considered in light of several limitations. We therefore believe that our conclusions remain relevant to clinicians using this measure as a tool in clinical practice. Second, participants were drawn exclusively from referrals to a specialty ADHD clinic, and thus they may have been more likely to identify attention problems among their primary complaints than individuals recruited from a more general outpatient psychology or psychiatry setting. As such, our findings with respect to discriminant validity may be limited.

On the other hand, almost a third of our sample was not diagnosed with ADHD; among those cawrs were, just under half met criteria for at least one comorbid Axis I psychiatric caar other than nicotine dependence.

Another issue with respect to xdhd representativeness of our sample is related to our clinic billing practices: As with many specialty outpatient clinics, our services are necessarily limited to those with some resources i.