Children and adolescents with attention-deficit/hyperactivity disorder (ADHD) often have a co-occurring reading disorder (RD). The purpose of this research was to assess differences between children with ADHD without RD (ADHD-only) and those with ADHD and co-occurring RD (ADHD+RD).® Databases for the years 2005 through 2007, this analysis compared the medical records--including patient demographics, comorbidities, and medication use--of children (age < 18) with ADHD-only to those with ADHD+RD.Using data from the U.S. Thomson Reuter MarketscanPatients with ADHD+RD were significantly younger, more likely to have received a procedure code associated with formal psychological or non-psychological testing, and more likely to have been diagnosed with comorbid bipolar disorder, conduct disorder, or depression. They were no more likely to have received an antidepressant, anti-manic (bipolar), or antipsychotic, and were significantly less likely to have received a prescription for a stimulant medication.Relying on a claims database, there appear to be differences in the patient characteristics, comorbidities, and medication use when comparing children with ADHD-only to those with ADHD+RD. Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition (DSM-IV), defines reading disorder (RD) as: "[R]eading achievement  that falls substantially below that expected given the individual's chronological age, measured intelligence, and age-appropriate education [The American Psychiatric Association's ducation ." While ducation , up to nducation ,4. Reseaducation -11.Given the fact that ADHD and RD often co-occur, a growing body of research has examined shared pathophysiological pathways of ADHD and RD. This research has shown that the two disorders share genetic and environmental factors ,13, cognThe purpose of the present study was to better understand differences between ADHD patients with and without co-occurring RD, using two patient groups identified from a large managed care health care claims database. The primary objective was to compare these two groups on the basis of demographic characteristics, other comorbid disorders, and pharmacological treatments patterns. A secondary objective -- recognizing that use of medical billing records is a suboptimal means of identifying children with RD -- was to examine the prevalence of a coded diagnosis RD among ADHD patients and to compare this prevalence with other estimates of RD prevalence among ADHD patients from the literature.® Research Databases. These retrospective, claims databases are fully compliant with the Health Insurance and Portability Act (HIPAA) and capture person-specific clinical utilization, expenditures, and enrollment across inpatient, outpatient, prescription drug and carve-out services from a selection of large employers, health plans, and government and public organizations. The databases link paid claims and encounter data to detailed patient information across sites and types of providers over time and include private sector health data from approximately 100 payers and more than 500 million claim records. Data examined for this study spanned the years 2005 through 2007.Data for this study came from the U.S. Thomson Reuters MarketscanTo be included in this study an individual had to be identified as having either ADHD-only or ADHD+ RD. In both groups, patients had to be diagnosed with ADHD based upon the receipt of an ICD-9-CM diagnostic code of 314.00 or 314.01 in the 2006 calendar year, with the first such date identified as the index date. In addition, individuals were required to be younger than 18 at index date and to have continuous insurance coverage, including prescription benefit coverage from 12 months prior to the index date  through 12 months post index date . To enhance comparability between the ADHD only and ADHD+RD cohorts, all children with a diagnosis of mental retardation , pervasive development disorder (ICD-9-CM of 299.xx), or developmental delays  at any time from the start of the pre-period through the end of the post-period were excluded, as these diagnoses generally preclude or complicate a diagnosis of RD.Given the above criteria, patients were then categorized as ADHD-only or ADHD+RD. In the ADHD-only cohort, patients were excluded if they had a diagnosis of RD (based upon receipt of an ICD-9-CM diagnostic code of 315.0x) at any time from the start of the pre-period through the end of the post-period. A total of 97, 703 children met the criteria for inclusion in the ADHD-only cohort.For inclusion in the ADHD+RD cohort, individuals had to be diagnosed with ADHD and RD during the 2006 calendar year, with the first date of either diagnosis identified as the index date. Patients with an index diagnosis of ADHD were required to have at least one diagnosis of RD over the time period from the start of the pre-period through the end of the post-period. Similarly, those whose index diagnosis was for RD were required to have at least one diagnosis of ADHD from the start of the pre-period through the end of the post period. A total of 265 individuals were included in the ADHD+RD cohort.The analysis compared patient demographics, comorbidities, and medication use between individuals with ADHD-only and those with ADHD+RD. Patient demographics included age, sex, region of residence, type of insurance coverage, and type of ADHD (with or without hyperactivity), while comorbid conditions included a variety of neuropsychiatric and behavioral conditions. The analysis also examined both medication use and length of therapy for ADHD medications  and other classes of medication used to treat psychiatric disorders . Differences in continuous variables were examined using t-statistics, while differences in categorical variables were examined using chi-square statistics. All analyses were conducted using SAS, version 9.1, and findings of P values of < 0.05 were considered statistically significant. As analyses were exploratory in nature, no adjustment for multiple comparisons was undertaken.In this retrospective claims database, 0.27% of patients with ADHD were found to have a co-occurring RD. Patients in the ADHD-only cohort were older than those in the ADHD+RD cohort. For example, in the ADHD-only cohort, 49.1% of individuals were age 6-11 and 44.0% were age 12-17, while in the ADHD+RD cohort, these percentages were 63.8% and 33.6%, respectively. The majority of patients in both cohorts were male (71.4% and 67.5%), insured via a PPO (30.4% and 30.6%) or an HMO (30.6% and 32.8%), and diagnosed with ADHD with hyperactivity (70.5% and 70.9%). Patients in the ADHD+RD cohort were more likely to have received formal psychological testing (24.5% v 7.8%) or neuropsychological testing (5.7% v 0.9%) in a setting that is associated with insurance reimbursement, compared to patients with ADHD-only (see Table Comparing comorbid conditions (at the three digit ICD-9-CM level) revealed that individuals with ADHD+RD, compared to those with ADHD-only, were more likely to be diagnosed with bipolar disorder , conduct disorder , depression , and other learning disorders . Examining subcategories of these comorbidities  revealed that children with ADHD+RD were more likely to be diagnosed with oppositional-defiant disorder , major depressive disorder, recurrent episode , and the learning disorder of developmental speech or language disorder . There was no difference in the two cohorts with regard to frequency of anxiety disorders, psychotic disorders, seizure disorders, or sleep disorders  and methylphenidate (Concerta), while atypical antipsychotics and antidepressants were the non-ADHD psychiatric medications most commonly prescribed. Relative to those with ADHD-only, children with ADHD+RD were significantly less likely to have received any stimulant medication . They were less likely, in particular, to have received the long-acting stimulant   or a short-acting amphetamine . There were no differences between the two cohorts with regard to the frequency of prescribing of anti-depressants, anti-manic agents, antipsychotics, or anxiolytics . In contrast, the ADHD-only children were nearly equally distributed in the 6-11 year old and 12-17 year old groups (49.1% v 44.0%). This difference in age distribution may reflect the fact that RD is typically identified when reading instruction begins in school, i.e., either the end of kindergarten or the beginning of first grade , whereasA large body of literature has provided evidence of a neurological basis for RD -34. In tThis study also revealed significant differences between the ADHD+RD and ADHD-only cohorts relative to comorbidities and medication use. Consistent with previous research showing a strong association between ADHD+RD and antisocial behavioral disorders, including aggression, delinquency, oppositional defiant disorder ,37,38, aless likely to receive stimulant medication, which is also commonly prescribed for the treatment of ADHD [Notably, although the patients with ADHD+RD in this study were more likely to be diagnosed with depression, bipolar/mania, or conduct disorder, they were no more likely to be prescribed antidepressant, anti-manic (bipolar), antipsychotic, or any other type of medication. Neither were those with ADHD+RD more likely to be prescribed any of the following non-stimulant medications used in the treatment of ADHD: atomoxetine ,40, tric of ADHD . AlthougThe findings of this study should be interpreted in the context of the limitations of the study design. First, the use of diagnostic codes to identify individuals is not as rigorous as formal diagnostic assessments for identifying people with ADHD or RD. Because RD may be diagnosed outside of a medical system that is associated with insurance reimbursement claims, use of such a claims database may preclude capturing a large segment of the ADHD+RD population. As mentioned above, this analysis found that less than 1% of individuals with ADHD received a diagnosis of RD, while the literature suggests that RD may co-occur in 15-30% of ADHD patients . In addiAdditionally, the number of unique physician visits was not captured in this analysis. While it appears that children with ADHD + RD present with more medical conditions and psychiatric comorbidities compared to children with ADHD alone, this may be due in part to the fact that children with ill-defined or complex developmental disorders are seen by multiple physicians and may receive multiple "rule out" diagnoses before receiving an accurate and comprehensive assessment of their condition. Finally, the use of medical claims data precludes the use of patient assessments; as a result, the analysis could not examine quality of life, functioning, or any clinical outcomes.This retrospective, descriptive analysis revealed significant differences between children with ADHD+RD and those with ADHD-only. In this study, the cohort with ADHD+RD had a higher burden of comorbidity, including a greater likelihood of a comorbid diagnosis of bipolar/mania, conduct disturbance, oppositional defiant disorder, depression, and learning disorders. At the same time, the children with ADHD+RD were no more likely to have been prescribed antidepressant, anti-manic (bipolar), antipsychotic, or any other type of medication, and were less likely to have been prescribed stimulant medication. These findings indicate the need for further research into the epidemiology, treatment and associated outcomes for children with ADHD+RD. They also indicate that the burden of ADHD+RD is unique and substantial. The special characteristics of ADHD+RD should be considered when conducting clinical evaluations and targeted treatment approaches. All results should be interpreted cautiously given the limited ability to ascertain RD using claims data, and future research into RD should focus on developing and using more broadly representative datasets.The authors declare that they have no competing interests.PC made substantial contributions to study conception, study design, interpretation of data, drafting and revising of manuscript and has read and given approval of the final version to be published. TL made substantial contributions to study design, data analyses, interpretation of data, drafting and revising of manuscript and has read and given approval of the final version to be published. SW made substantial contributions to study design, drafting and revising of manuscript and has read and given approval of the final version to be published. JJ made substantial contributions to study conception, study design, interpretation of data, drafting and revising of manuscript and has read and given approval of the final version to be published.


Tourette Syndrome (TS) is a childhood onset disorder of motor and vocal tics. The neural networks underlying TS overlap with those of saccade eye movements. Thus, deviations on saccadic tasks can provide important information about psychopathology of TS. Tourette syndrome often coexists with Attention Deficit Hyperactivity Disorder (ADHD) and Obsessive Compulsive Disorder (OCD). Hence, we manipulated various components of a saccade task to measure its effects on saccades of children with TS-only, TS+ADHD, TS+ADHD+OCD and healthy controls. Children looked toward (prosaccade) or in the opposite direction (antisaccade) of a peripheral target as soon as it appeared. The prosaccade and antisaccade tasks were presented in three conditions. In the Gap200 condition, the fixation dot disappeared 200 ms prior to the appearance of the peripheral target, In the Gap800 condition, the fixation dot disappeared 800 ms prior to the appearance of the peripheral target and in Overlap200 the fixation dot disappeared 200 ms after the appearance of the peripheral target. Fixation-offset manipulations had different effects on each group's antisaccades. The TS+ADHD+OCD group's antisaccade latencies and error rates remained relatively unchanged in the three conditions and displayed a pattern of eye movements that can be interpreted as enhanced. Alternatively, the TS+ADHD group displayed an overall pattern of longer saccadic latencies. Findings corroborate the hypothesis that the combination of tic disorder and ADHD results in unique behavioral profiles. It is plausible that a subgroup of children with TS develop an adaptive ability to control their tics which generalizes to enhanced volitional control of saccadic behavior as well. Supporting evidence and other findings are discussed. Tourette Syndrome (TS) is a childhood onset disorder of motor control with the primary symptoms consisting of motor and vocal tics. A tic is a sudden and stereotypic motor movement or vocalization . Certain types of disorders such as Attention Deficit Hyperactivity Disorder (ADHD) and Obsessive Compulsive Disorder (OCD) are strongly linked to TS and may be an integral part of this disorder. ADHD is the most commonly encountered comorbid condition in TS, occurring in about 21–90% of this population , the limbic structures and areas of the frontal cortex to which the BG project through the thalamocortical pathways appear to be associated with TS Segawa, . PatientThe present study focused on saccadic eye movements. Saccades are fast eye movements that redirect the gaze to different scenes and scan the visual environment  and an overlap condition. In the present study we wished to examine whether the Gap-effect would still emerges if the duration of the Gap increases.Compare the same parameters as in (1) in sub-groups of children with TS, divided according to comorbidity status, relative to one another and relative to healthy children.The Gap-effect phenomenon has also been observed in healthy children  and 22 children with TS 8–16 years of age  participated in this study. The children with TS were separated into three subgroups: TS-only , TS+ADHD , and TS+ADHD+OCD . Many of the children with TS were receiving medication. These medications included Clonidine , Risperidone , Citalopram (TS+ADHD), Atomoxetine , Fluvoxamine , Quetiapine , Bupropion , Zoloft , Dextroamphetamine (1 TS+ADHD+OCD), Olanzapine, Amantadine, Pantoprazole sodium, Salbutamol, Fluticasone (1 TS+ADHD+OCD), Amantadine (1 TS+ADHD+OCD). For a full demographic and medication information of each participant, please see Tajik-Parvinchi and Sandor . Information about symptoms associated with TS and OCD were collected using self-report and family report based on the tic inventory and ordinal severity scales of the Yale Global Tic Severity Scale . The participants' ADHD symptom severities were assessed retrospectively using the Clinical Global Impression of ADHD symptoms (CGI) both for life time and at the time of data collection [for participants demographic and medication information see Tajik-Parvinchi and Sandor ]. The raData collection was not completed by 3/32 children: 1 child in the Control group , 2 children in the TS-only group  due to participant fatigue and technical difficulties with the system . Please note that these children were able to complete majority of the tasks and the data from the completed tasks were included in the analyses.Informed written consent was obtained from the parents of the children and informed written assent was attained from the children. This study was approved by the University Health Network Ethic's Board and complied with the tenets of the Declaration of Helsinki.Eye movements were measured with a video-based cornea/pupil tracking system  with a maximum resolution 0.1° of visual angle. This system is free of drifts and it has a linear range of greater than 30° horizontally and 25° vertically. Eye movements were sampled at 120 Hz. Participants were seated upright in a chair especially crafted to adjust to various heights, to ensure that all participants' eye levels were the same when viewing the stimuli presentations and pointed to the center of the screen. The head was stabilized with a chin-rest. The stimuli extended around 0.25° and consisted of a blue fixation dot and green/red dots representing the peripheral targets. The red dots were displayed for antisaccades and the green dots for prosaccades. The stimuli were back projected on a screen which was 200 cm from the seated participants. The eye tracker was calibrated for each participant prior to data collection. The eye movement data and the stimuli presentations were recorded by the same eye tracking system.Children were presented with two tasks, the prosaccade and the antisaccade task. Each task was presented in 3 conditions. Thus, each participant had to complete 6 experimental conditions: prosaccade Gap200, prosaccade Gap800, prosaccade Overlap200, antisaccade Gap200, antisaccade Gap800, and antisaccade Overlap200. Each experimental condition consisted of 25 trials and was presented in a randomized order.In the Gap200 condition, the fixation dot disappeared 200 ms prior to the onset of the peripheral stimulus; in the Gap800 condition, the fixation dot disappeared for 800 ms prior to the onset of the peripheral stimulus and in the Overlap200 condition, the fixation dot remained on for 200 ms at the onset of the peripheral stimulus. In the present study, the Gap200 condition served as a baseline condition relative to which saccadic alterations in Gap800 and Overlap200 were measured. Data on group differences in the Gap200 condition have been reported elsewhere  was carried. The dependent variables were: Antisaccade Latency, Prosaccade Latency and Antisaccade Error Rates. The factor Group  was entered as the between-subjects factor and Condition  was entered as the repeated measure factor, establishing a 4 × 3 mixed model. All pair-wise comparisons were corrected using the Bonferroni method.F = 96.225, p < 0.00, but there were no Group × Condition effect F = 0.716, p = 0.638. However, given our priori hypothesis that the Gap-effect will weaken when Gap duration is increased, we followed up the ANOVA with Bonferroni corrected pairwise comparisons  = 0.863, p = 0.472.The ANOVA did not reveal an effect for Group F = 39.366, p < 0.001 and a Group × Condition effect, F = 2.808, p = 0.02. However, the reversal of Gap-effect was not observed. All groups displayed shorter antisaccade latencies in the Gap800 condition relative to the Overlap200 condition  except for one group, the TS+ADHD+OCD where this latency difference was not significant. Overall, it appears that increasing the Gap duration does not reverse the antisaccadic Gap-effect in any of our groups , the TS+ADHD (p < 0.001) and the TS-only (p < 0.001) groups in the Overlap200 condition . These findings indicate a faster reaction time in the TS+ADHD+OCD group. In contrast, the TS+ADHD group exhibited significantly longer antisaccade latencies (slower reaction times) in the Gap800 condition relative to the Control group (p < 0.001). In the Gap800 condition, the difference between the TS+ADHD and those of the TS-only group did not reach significance (p = 0.06).In contrast to our expectations, the TS+ADHD+OCD group displayed significantly shorter antisaccade latencies relative to the Control  = 4.28, p = 0.02 and a Group × Condition interaction effect F = 3.1, p = 0.01. The Control group had the highest rate of antisaccade errors in the Gap200 condition relative to the Gap800 (p < 0.001) and the Overlap200 (p < 0.001) conditions  in the Gap800 and Gap200 conditions and both were significantly higher than those in the Overlap200 condition . In the TS+ADHD group, antisaccade errors were the highest in the Gap200 condition, which was significantly higher than those observed in the Gap800 condition (p = 0.01). The TS+ADHD+OCD group's antisaccade error rates did not alter across the three conditions   Figure . For morp = 0.02) in the Overlap200 condition. The TS+ADHD+OCD displayed significantly lower rates of antisaccade errors relative to those of the Control group (p < 0.001) and to those of the TS+ADHD (p < 0.001) in the Gap200 condition. These group differences in the Gap200 condition have been discussed in another report  = 0.510, p = 0.809; Group*Age, F = 1.176, p = 0.395; Condition*Age,  = 1.081, p = 0.423; and Group*Condition*Age, F = 0.994, p = 0.499. In the antisaccade error rate, the main effect of “Age” was not significant F = 1.688. Similarly, there were no significant effects of Group*Age F = 0.430, p = 0.903; Condition*Age F = 0.751, p = 0.706 or Group*Condition*Age F = 0.638, p = 0.832.The above results appear to suggest an enhanced antisaccade ability in the TS+ADHD+OCD group. However, given that this group was the oldest group, it is possible that they performed better due to their older age. In order to explore this possibility, two analyses were carried out. First, the main effect of Age and all possible interactions were examined. Two ANOVAs were run, one for “Antisaccade Latency” and one for “Antisaccade Error.” These two variables were selected given the significant group differences that were revealed here. In both analyses, the factor “Age,” “Group,” and “Condition” were entered as the between subjects factors. In antisaccade latency, there were no significant effects of Age M = 168 m, SD = 22.38, n = 8; TS-only: 143.8 m, SD = 11.2, n = 4; TS+ADHD: M = 164.6, n = 5, SD = 22.8, TS+ADHD+OCD: M = 169 m, SD = 18.9, n = 6). The above analyses were repeated on the age-adjusted groups.In order to further explore the contribution of “Age” to the enhanced saccadic ability displayed by the TS+ADHD+OCD group, each group was age-adjusted by the means of data exclusion of the youngest(s) or the oldest(s) participant(s) in order to close the gap between the average ages of the groups. The data of the two youngest participants in the Control and the TS-only groups, the four youngest participants in the TS+ADHD and the oldest participant in the TS+ADHD+OCD group were excluded  = 42.908, p < 0.001 and a significant interaction effect F = 2.538, p = 0.033. The TS+ADHD+OCD group still exhibited significantly shorter antisaccade latencies relative to those of the Control (p = 0.004), the TS-only (p = 0.006) and the TS+ADHD (P < 0.001) groups in the Overlap200 condition  = 3.189, p = 0.05 was still present. However, the Group × Condition interaction effect was no longer significant F = 1.245, p = 0.3. Nevertheless, the TS+ADHD+OCD group had significantly lower antisaccade errors relative to the Control group p = 0.001 and to the TS+ADHD group p = 0.03 in the Gap200 condition, but their antisaccade error was no longer significantly reduced relative to the TS-only group p = 0.06  = 0.847, p = 0.373 and the CGI-life-time F = 0.011, p = 0.918 were not significantly different between the TS+ADHD and the TS+ADHD+OCD groups. Thus, taken together, these results indicate that ADHD symptom severity and the factor “Age” did not play a key role in the enhanced pattern of performance observed in the TS+ADHD+OCD group.In order to determine whether a significant difference in ADHD symptom severity between the TS+ADHD+OCD and the TS+ADHD groups was contributing to the group differences, an ANOVA was carried out to examine the differences between CGI-at-time and CGI-life-time between these two groups. The CGI at time of data collection Univariate analyses of variances were carried out with Tic Severity as the independent variable and Antisaccade Error rate, Antisaccade latency and Prosaccade Latency as the dependent variables. These analyses did not reveal any significant effects of tic severity.The results of the present study have revealed several main observations. The Gap-effect was observed in both prosaccades and antisaccades of all of our groups consistent with earlier reports  relative to those of the Control group and in two conditions (antisaccade Gap800 and antisaccade Overlap200) relative to those of the TS+ADHD+OCD group. These findings and their implications will be discussed in the following paragraphs.The latency difference between Gap and Overlap conditions were greater for antisaccades than for prosaccades Table . This obAll groups displayed the Gap-effect Reversal Figure  for prosThe present study is the first to demonstrate that healthy children, children with TS-only and those with TS+ADHD+OCD do not display the Gap-effect Reversal for antisaccades at all. This finding is different from the prosaccade finding described above Figure  and alsoEarlier reports indicate that antisaccade error rates decrease in a long Gap condition (600–800 ms) relative to both a short Gap (200–300 ms) and an Overlap conditions  relative to the Overlap condition  the children who were medication-free comprised a very small portion of this population. This raises two important issues. First, the generalizability of data of a TS medication-free group would be highly limited since they appear to make up a small population within this patient group. Second, the medication-free child probably exhibits very mild symptoms which do not require medication intervention. Hence, findings emerging from a medication-free group with TS would have its own limitations.The results of many oculomotor studies have shown that antipsychotic medications did not alter their pattern of significant findings (Crawford et al., A study by Burke and Reveley  indicateAlthough medication effect on saccadic ability is a valid concern and our readers should exercise caution when interpreting the present findings, a medication effect cannot adequately explain our pattern of findings. This conclusion is supported by the findings of other researchers who have made similar observations and have reported enhanced motor abilities in some of the children with TS (Mueller et al., Also, the average ages of our groups were somewhat different. Although the age-adjusted groups exhibited an overall pattern of finding similar to that prior to age-adjustments, the average age of the TS-only group was still not well-matched with the other groups. Hence, the reader should exercise caution when interpreting the findings relevant to this group. While the factor “Age” is a relevant variable to control, in the present study the enhanced performance of the TS+ADHD+OCD group is independent of the factor “Age.”Lastly, the small size of our samples may have subjected our findings to Type-II errors. Although we cannot exclude the possibility that further significant effects may surface with larger sample sizes, the significant findings which have been detected in the present study were large enough to be captured by our sample sizes and are valid to report.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


Cimex lectularius L.) have resurged in the United States and globally. Bed bugs are hematophagous ectoparasites of humans and other animals, including domestic pets, chickens, and bats, and their blood feeding habits contribute to their potential as disease vectors. Several species of Bartonella are re-emergent bacterial pathogens that also affect humans, domestic pets, bats and a number of other wildlife species. Because reports of both bed bugs and Bartonella have been increasing in the U.S., and because their host ranges can overlap, we investigated whether the resurgences of these medically important pathogens and their potential vector might be linked, by screening for Bartonella spp. in bed bugs collected from geographic areas where these pathogens are prevalent and from bed bugs that have been in culture in the laboratory for several years. We screened a total of 331 bed bugs: 316 bed bugs from 36 unique collections in 29 geographic locations in 13 states, 10 bed bugs from two colonies maintained in the laboratory for 3 yr, and 5 bed bugs from a colony that has been in culture since before the recent resurgence of bed bugs. Bartonella spp. DNA was screened using a polymerase chain reaction assay targeting the 16S–23S rRNA intergenic transcribed spacer region. Bartonella DNA was not amplified from any bed bug, but five bed bugs from four different apartments of an elderly housing building in North Carolina contained DNA sequences that corresponded to Burkholderia multivorans, an important pathogen in nosocomial infections that was not previously linked to an arthropod vector.Bed bugs ( Cimex lectularius L.) are an important resurging pest in urban centers globally, including the U.S. Rickettsia parkeri, could last up to 2 wk in the insects Bed bugs , Carrion’s disease (Bartonella bacilliformis) and Trench fever (Bartonella quintana). In the U.S., cats are the main reservoir of B. henselae, humans and dogs are incidental hosts, and CSD is common with the highest B. henselae seroprevalence found in cats in warm and humid areas of the Southeast, Hawaii, coastal California, and the south central plains regions Ctenocephalides felis (Bouchè)) is the primary vector of B. henselae, but the pathogen can also be transmitted by cat bites and/or scratches contaminated with flea feces. Trench fever is also prevalent in the U.S. in homeless shelters; it is transmitted by the body louse (Pediculus humanus humanus L.), and humans are considered the main reservoir B. henselae or B. quintana in bed bugs from the U.S. would seem more probable than other less prevalent Bartonella species that occasionally infect humans.Bartonella, are few and relatively recent. Lowe and Romney Staphylococcus aureus and vancomycin resistant Enterococcus faecium. Richard et al. Rickettsia spp., Bartonella spp., and Anaplasma spp. These authors did not detect Rickettsia or Bartonella in the screened insects, but they found a single sample containing an Anaplasma-like bacterium “Candidatus Midichloria mitochondrii,” an endosymbiont of ticks Post-resurgence efforts to screen bed bugs for human pathogens, including Bartonella spp. have been detected in eastern bat bugs (Cimex adjunctus Barber) collected in two bat caves from the southeastern U.S. Cimex adjunctus is found in bat roosts, occasionally invading buildings in bat roosting sites C. lectularius and co-infestation of human-built structures by both species can sometimes occur BartonellaC. lectularius can occasionally feed on bats C. lectularius could also harbor bat-adapted Bartonella species. Given that both C. lectularius and several Bartonella species are resurgent in the U.S. in association with humans, bats, domestic pets, and wildlife, our objective was to investigate if the resurgence of bed bugs could represent a potential source of Bartonella transmission. We screened for Bartonella spp. in bed bug populations from geographic areas where B. henselae bacteremia is prevalent in feral and pet cat populations.Bartonella spp. in any of the 316 bed bugs freshly collected in the field between 2005 and 2010. Furthermore, we did not detect Bartonella spp. DNA in any of the bed bugs maintained in our cultures, including 10 bed bugs from two colonies maintained in the laboratory for 3 yr and five bed bugs from the Fort Dix (Harold Harlan) colony, which was originally collected in 1973, well before the recent resurgence. The endosymbiont Wolbachia is highly prevalent in bed bug populations Bartonella are due to absence of Bartonella DNA and not PCR interference. Our findings suggest that bed bugs are an unlikely vector of Bartonella spp. However, as Bartonella are emerging pathogens, adaptation to new hosts in conjunction with an expanding range of vectors suggests that vector biologists should remain vigilant to the possibility of Bartonella occurring in bed bugs in the future Bartonella and bed bugs may be dynamic and could have changed since our collections were completed. We targeted our collections to regions of the United States where B. henselae seroprevalence is high in cats due to frequent flea exposure , close to the Bartonella henselae control (604 bp). When these amplicons were sequenced, the alignments of the five sequences (Genebank accession numbers: KF286544-KF286548) with BlastX were 98% similar to a sequence of Burkholderia multivorans, accession number YP001949472.1. As these amplicons were generated using Bartonella 16S-23S intergenic spacer primers, it is possible that more specifically designed primers for B. multivorans may detect higher prevalence of this pathogen in bed bugs. B. multivorans is recognized as an important pathogen in nosocomial infections of patients with cystic fibrosis B. multivorans DNA from multiple bed bugs in multiple but nearby apartments suggests that this association should be investigated further to determine whether bed bugs are competent to vector B. multivorans between humans.We screened 99 bed bugs from 10 apartments of an elderly housing building in Raleigh, North Carolina . Five beBartonella spp. DNA, 2–10 bed bugs per collection  assay targeting the 16S–23S ribosomal RNA intergenic transcribed spacer (ITS). The 16S–23S rRNA ITS region has been successfully used for the molecular diagnostic of Bartonella spp. from blood-sucking arthropods, including ticks and lice 5′- GGTTTTCCGGTTTATCCCGGAGGGC-3′) and reverse primer 1100as (5′-GAACCGACGACCCCCTGCTTGCAAAGCA-3′) B. henselae. Bed bug DNA was spiked with 2.5 copies of B. henselae DNA to determine if PCR inhibitors would interfere with successful amplification. No PCR inhibitors were detected in bed bug DNA. Additionally, to ensure that we could amplify bacterial DNA from bed bug DNA samples, we randomly chose 10 bed bug DNA samples from 10 distinct geographic locations and amplified bacterial DNA using bacteria specific 16S rDNA universal primers: 27F (5′- AGAGTTTGATCMTGGCTCAG-3′) and 1492R (5′-TACGGYTACCTTGTTACGACTT-3′) Bed bugs were surface sterilized by rinsing them with sterile water and 95% ethanol, and they were processed individually throughout the entire screening process. Total genomic DNA was extracted from individual adult bed bugs using the phenol-chloroform methodology described by Taggart et al. Bartonella spp. PCR amplification was performed in a 25 µL final volume reaction containing 12.5 µL of Premix Ex Taq™ (Takara Bio Inc.) and 7.5 µL of molecular grade water . The reaction mixture was completed by adding 0.2 µL of forward and reverse primers (each at 30 µM) and 5 µL of either bed bug DNA template, positive control (with 2.5 copies of Bartonella DNA) or water (as PCR negative control). Amplification of the rRNA ITS region was performed under the following conditions: a hot start cycle of 94°C for 2 min, followed by 55 cycles of denaturing at 94°C for 15 s, annealing at 68°C for 15 s, and extension at 72°C for 18 s. Amplification was completed by an additional cycle of 72°C for 1 min to allow complete extension of PCR products. All amplification products were separated by electrophoresis in a 2% agarose gel and visualized under ultraviolet light with ethidium bromide. Positive and negative controls were used in all reactions and consisted of genomic DNA extracts of B. henselae, and molecular-grade sterile water, respectively. If a sample was found to be positive, the PCR reaction was purified using the QIAquick® PCR purification kit  and sent to an external laboratory for sequencing. Alignment of sequences was performed with the program BlastX in order to identify bacteria at the genus and species levels.


In their article “Lead and PCBs as Risk Factors for Attention Deficit/Hyperactivity Disorder” (ADHD), p < 0.01) associated with ADHD in case children (As children . The laschildren .p < 0.047) association with medical record information on postnatal BLL in a potentially biased 60.9% of subjects, and no association (p < 0.641) with umbilical cord BLL in 88.6% of subjects.In their Table 1, According to National Health and Nutrition Examination Survey (NHANES) data, the proportion of elevated BLLs (≥ 10 µg/dL) in U.S. children 1–5 years of age dropped from 77.8% in 1976–1980 to 0.9% in 2005–2008 . HoweverThe PCB literature The dearth of well-controlled studies leaves open Eubig et al.’s question whether lead or PCBs exert an effect on ADHD occurrence beyond that exerted by heritability. This question cannot be answered satisfactorily until researchers consistently impose adequate control in their studies and funding agencies consistently require such control in the research they support.


Working memory impairments are frequent in Attention Deficit/Hyperactivity Disorder (ADHD) and create problems along numerous functional dimensions. The present study utilized the Visual Serial Addition Task (VSAT) and functional magnetic resonance imaging (fMRI) to explore working memory processes in thirteen typically developing (TD) control and thirteen children with ADHD, Combined type. Analysis of Variance (ANOVA) was used to examine both main effects and interactions. Working memory-specific activity was found in TD children in the bilateral prefrontal cortex. In contrast the within-group map in ADHD did not reveal any working-memory specific regions. Main effects of condition suggested that the right middle frontal gyrus (BA6) and the right precuneus were engaged by both groups during working memory processing. Group differences were driven by significantly greater, non-working memory-specific, activation in the ADHD relative to TD group in the bilateral insula extending into basal ganglia and the medial prefrontal cortex. A region of interest analysis revealed a region in left middle frontal gyrus that was more active during working memory in TD controls. Thus, only the TD group appeared to display working memory-modulated brain activation. In conclusion, children with ADHD demonstrated reduced working memory task specific brain activation in comparison to their peers. These data suggest inefficiency in functional recruitment by individuals with ADHD represented by a poor match between task demands and appropriate levels of brain activity. Impairments in working memory create difficulties for individuals with ADHD in their cognitive, academic and social activities. Difficulties arising from impaired working memory and associated executive functioning deficits may interfere with maintenance of rules to govern behavior, moral reasoning and problem solving skills Working memory manipulation and maintenance is assumed to involve the prefrontal cortex (PFC) A core problem in ADHD beyond working memory processing is a failure to implement strategies and adjust brain activation to match particular demands, or modulate neural effort in response to task specific characteristics This current study tested working memory in children with ADHD, Combined subtype, in comparison to TD children as an extension of previous neuroimaging working memory studies Initial participants included 17 ADHD and 22 TD children between the ages 8 to 14 years. The final sample, selected to match the age, IQ, and SES of the ADHD group see  includedRecruitment strategies included advertising in newspapers, pediatric and ADHD clinics, support groups and websites. Parents gave written informed consent, participants 13 and older gave written assent and younger participants gave verbal assent for a protocol approved by the institution's review board.SD above the mean on the Total Scale of the DSM-IV ADHD Parent Conners' Rating Scale – Long Version (CPRS-R-L) SD or higher on WJ-III Calculation subtest for their age. All volunteers participated in all phases of the screening process.We only invited volunteers for the ADHD group if the participants met DSM-IV-TR criteria for ADHD, Combined Type to enhance our ability to identify brain activation alterations associated with individuals experiencing the combination of inattentive and hyperactive/impulsive symptoms. The ADHD diagnosis was based on the presence of ADHD via the Diagnostic Interview for Children and Adolescents DICA, , a folloParticipants with co-existing Axis I or II diagnoses (except for ADHD in the ADHD group), metal or prosthesis in the body or major medical conditions were excluded. Children with first-degree family members with a history of bipolar, schizophrenia, or obsessive-compulsive disorder and controls with first-degree family members with ADHD were excluded. Exclusions were identified via phone screens that reviewed inclusion and exclusion criteria; the DICA and a follow-up interview with a clinician regarding clinical conditions in the participants and family members; Conners' Rating Scales; medical history, metal and prosthesis questionnaire and a handedness scale modified for children We developed the Visual Serial Addition Task (VSAT) based on the Paced Auditory Serial Addition Task PASAT, , as an fThe VSAT presents single-digit random numbers with participants adding each number to the one on the preceding screen. The stimuli ranged from 1–7 and could sum to no more than 9. See  ParticipTwo tasks controlled for different levels of cognitive involvement. A match-to-sample task (MST), with its less demanding cognitive load Independent samples t-tests examined whether there were any differences between the TD and ADHD groups on IQ, achievement and behavioral measures or ADHD ratings. Repeated Measures ANOVA with Task  as a within-subjects condition and Group  as a between-subjects condition tested whether behavioral measures  would be affected by increasing task difficulty from the MST to AT to VSAT tasks. We have previously demonstrated an increase in intra-individual RT variability in all subjects with increasing task difficulty in this paradigm A 1.5T Philips Eclipse scanner  equipped with high performance gradients acquired 88 high-resolution T1-weighted axial slices . For five (three ADHD) participants, high-resolution structural scans were not acquired due to the child's request to terminate the scanning session early. Each functional run acquired 223 volumes  using single-shot, T2* weighted, echo-planar imaging sequences . Vision 2000 goggles from Resonance Technologies  were used to present the stimuli.http://afni.nimh.nih.gov/afni). Volumes were motion corrected and all images aligned to the eighth volume in the run acquired immediately preceding the structural scan. The first seven volumes as well as volumes displaying excessive motion (more than one voxel size or 5 mm) were excluded from further analysis. Data were smoothed (4 mm Gaussian FWHM) and converted to percent change scores using MST as the baseline and any activation outside the brain was set to zero.Data were preprocessed and analyzed using AFNI software 3).For each participant, data from all runs were concatenated together. Due to excessive movement, one run was not included for five ADHD children. To address this issue, analyses were conducted with matched runs between groups. To this end, we randomly chose 5 TD children and excluded their third run before conducting the contrasts. Ideal waveforms were created for AT and VSAT tasks by convolving a square-wave function with a hemodynamic response function; therefore, the MST task acted as the absolute baseline against which AT and VSAT activity was contrasted. Multiple regression analyses generated percent signal change for AT and VSAT relative to the MST baseline. Motion parameters were modeled as variables of no interest. Images corresponding to estimates of the parameters of interest were then warped into the standard Talairach space Analysis of variance procedures for repeated measures were used to analyze the data in a 2×2 mixed design with group as a between-subjects factor (ADHD vs. TD), and condition as a within-subjects factor (AT vs. VSAT). Post-hoc contrasts included within-group (VSAT versus AT) and between-group (TD versus ADHD) contrasts. Significance required a voxel-wise threshold of p≤0.005. As a correction for multiple comparisons we combined this voxel-wise threshold with a minimum cluster-size of 282 µl, determined by Monte Carlo simulations, resulting in an overall 0.05 probability of a significant cluster surviving by chance. As our primary interest for this study is working memory functioning, we focus on relevant contrasts of interest, that is, post-hoc within- and between-group comparisons on the VSAT task , resulting from the ANOVA. Activation maps were thresholded and corrected for multiple comparisons as described previously.To test our hypotheses of frontal hypoactivity in the ADHD group, we used a mask comprised of inferior and middle frontal gyri (MFG) and performed a region of interest (ROI) analysis. This mask was defined using a plugin within AFNI which defines specific anatomical regions of interest in Talairach space. We used small volume correction The average activation, per region, from each map  was calculated for each participant for each task (AT and VSAT). Bivariate correlation analyses tested the relationship between working memory task performance (correct RT) and activation within notable regions as defined by the ANOVA. Correlations also tested for a relationship between brain activity and omission errors in the ADHD group only as the TD did not exhibit sufficient variability in this measure.Additional whole-brain regressions tested for correlations between RT and activation in every voxel in the brain in both groups separately. Within the ADHD group, whole-brain regressions tested the relationship between brain activation and symptom severity from the Hyperactivity, Inattentiveness and Total ADHD score of the CPRS-L. Again, activation maps were thresholded and corrected for multiple comparisons as described previously.Analyses were conducted to ascertain whether gender or handedness inequality between the groups might have affected our results. These analyses revealed no significant differences in activation maps controlling for gender and handedness that were not explained by decreased power due to fewer participants per group. Therefore, we report only results including extra number of females and left-handed participants.Independent t-tests revealed that the groups did not differ across age, SES, or IQ see . There wIndependent t-tests revealed that the minimally-demanding MST resulted in no significant differences in response time, omission or commission errors between ADHD and TD groups. The ADHD group produced significantly more omission errors on the VSAT and AT paradigm, suggesting greater inattention on the more cognitively demanding tasks. Commission errors on the tasks did not differ between groups see .F = 3.19; P = 0.09).Examination of the motion parameters (in six planes), using repeated measures ANOVA, revealed no significant between-group differences in the mean motion  revealed significant activation in thirteen regions including the PFC (BA 9 and 6), ACC, basal ganglia, temporo-parietal junction, inferior parietal cortex, precuneus, post-central gyrus and middle occipital gyrus see . The maiThe TD within-group contrast map resulted in eighteen functionally-defined regions, including the MFG (BA 6 and 9), pre-central gyrus, ventro-medial PFC, putamen, and the temporal and parietal cortices see . Six of The ADHD within-group contrast map revealed nine regions, all more active in the AT compared to VSAT. These regions included the medial FG, occipital, parietal and temporal regions see .The TD VSAT vs. ADHD VSAT contrast revealed four regions all significantly more active in the ADHD compared to the TD control group, namely two regions in the right insula/claustrum, one extending into inferior frontal gyrus (IFG) and the other into putamen, left insula and left medial frontal gyrus see . PearsonThe between-group ROI analysis revealed one region within the left MFG (BA 6), which was more active in the TD compared to the ADHD group see . This reIn the TD group, correlations between RT and brain activation revealed 3 regions see .. The leCorrelations between brain activity and symptom severity identified a negative correlation between activity in the right inferior occipital gyrus extending into fusiform gyrus and the inattentive score see . Thus, cWorking memory-related activity was evident in the TD control group in the bilateral MFG (BA 6), right MFG (BA 9) extending into ACC, pre-central gyrus, bilateral post-central gyrus (BA 4) and the right cingulate. The within-group contrast in the ADHD group failed to reveal any working memory-specific regions. The between-group contrast revealed regions in the bilateral insula, right claustrum, IFG, putamen and in the left medial FG. The ADHD group activated all of these regions significantly more than controls. Additional ROI-based analysis revealed a region in the left MFG that was more active in the TD group. Therefore, these regions were areas that significantly differed between groups in the working memory task.TD participants activated a network of regions, including bilateral MFG, commonly activated in WM. The lateral PFC has been associated with working memory in a number of studies in adults Although the ADHD group as a whole failed to demonstrate any significant activity in the regions defined by the TD group, the between-group working memory contrast failed to show significant group differences in these regions with the exception of the left MFG. Thus, left MFG was a working memory-related region that was hypoactive in the ADHD compared to the TD group. Hypoactivity in the frontal cortex during cognitive control is a largely consistent finding in ADHD However, the lack of a between-group difference in the cingulate, motor regions and right MFG suggests that there was significant variability in these regions in the ADHD group, with some of the participants in the ADHD group activating these regions. In fact, correlations revealed that those ADHD subjects who successfully engaged bilateral MFG also displayed better performance. Two regions from the Main effect of Condition contrast overlapped with regions from the TD within-group map, namely the right MFG (BA 6) and the right precuneus, extending into post-central gyrus. Thus these regions are very likely to be engaged by both ADHD and TD groups during working memory processing.The within-group contrast in the ADHD group did not result in working memory-specific regions, even though the behavioral data suggested that difficulty increased in both groups from MST to AT to VSAT tasks. Furthermore, the main effect of Group only revealed regions that were more active in the ADHD over TD group and thus are more active in general in the ADHD group. In fact, three regions, two in the right claustrum/insula and one in the left insula extending into the IFG, overlapped with the ADHD regions in the working memory between-groups contrast. This suggests that the ADHD group may be less likely to engage brain regions specifically for working memory or for more cognitively-demanding tasks in general. Similarly, in our previous working memory-imaging study in adults with ADHD, we found the ADHD group was more likely to engage the cerebellar vermis than controls, regardless of the task demands or whether or not they were actively taking a stimulant medication per se.Compared to the TD group, the ADHD group engaged the bilateral insula extending into the basal ganglia and the medial PFC. Activation in the insula has been noted in working memory encoding, maintenance and retrieval in TD adults deactivation of this area in the TD group. Medial PFC has been associated with the default mode attention network, which is usually deactive during cognitive demand. Failure to suppress activity in the default network during cognitive demand has been associated with errors in performance and distractibility not only in individuals with ADHD but also in healthy controls Hyperactivity in the medial PFC in the ADHD compared to control group has previously been addressed in our examination of distractibility in ADHD, utilizing the same data set Whole-brain correlations revealed links between task performance and activation in the TD group in the middle and superior temporal lobes and in regions associated with working memory and attention in general, namely the inferior and superior parietal lobe. These correlations were absent in the ADHD group. Previous fMRI studies of working memory in ADHD found hypoactivity in parietal regions in adults with ADHD The relatively small sample size utilized in this study not only limited our ability to test for age or gender effects but may also have compromised our ability to identify additional between-group differences. Between-group differences in the left MFG were only detectable using an ROI approach which is most likely due to a lack of power to detect this difference at a whole-brain level. Other limitations of this study include above average IQs for both groups that may limit the generalizability of the results and varying degrees of exposure to stimulant medication in ADHD participants. It is possible that exposure to medication altered brain activation, however recent studies comparing stimulant-naive and stimulant-exposed pediatric participants


Attention Deficit Hyperactivity Disorder (ADHD) occurs in approximately 5% of the adult population and includes cardinal symptoms of hyperactivity, inattention, and impulsivity that may be difficult to identify with clinical routine methods. Continuous performance tests are objective measures of inattention and impulsivity that, combined with objective measures of motor activity, facilitate identification of ADHD among adults. The aim of the present study was to examine the sensitivity, specificity, and a composite measure of ADHD using objective measures of the ADHD-cardinal symptoms in adult participants with ADHD and non-ADHD normative participants. Cardinal symptoms were measured in 55 participants having ADHD, 202 non-ADHD normative participants, as well as 84 ADHD normative participants using the Quantified Behavior Test Plus. This test measures inattention and impulsivity using a continuous performance test, and hyperactivity using a motion-tracking system. A predictive variable for the detection of ADHD called Prediction of ADHD yielded 86% sensitivity and 83% specificity. A composite measure of ADHD cardinal symptoms was developed using a Weighed Core Symptoms scale that indicated the total amount of ADHD symptoms on a numeric scale from 0 to 100. The total amount of ADHD symptoms was measured on a scale and predicted with the categorical variable in a majority of the cases in the present study. Further studies are needed in order to confirm the results with regard to additional clinical and normative samples. Careful consideration of potential sex and diagnostic subtype differences are noteworthy aspects for future examinations of the new instruments. In the 1950s, Continuous Performance Tests (CPT) were originally used for testing the signal detectability of radar operators. Development intended for psychiatric care and research eventually began in human subjects with brain damage  for many of the parameters of inattention and impulsivity. A meta-analytic review of neuropsychological measures  pooled effect sizes for sustained attention (−0.52) on various CPTs, which placed them among the top discriminating measures of adult ADHD versus healthy controls.The paradigm has been developed with prime reference to children with ADHD, but is also administered frequently to adults with the disorder. As a result, a lack of sensitivity and ceiling effects have been documented when applying child norms to adult populations, particularly in cases with less severe symptomatology  and compare them with healthy and matched controls (N = 20) using the Quantified Behavior Test Plus (QbTest-Plus). This test combines a motion-tracking system (MTS) and a CPT on the computer. It was developed for the purpose of reducing ceiling effects and to measure the ADHD core symptoms among adults. The highest separation of the groups was reported for the MTS measures that included parameters called microevents , time active (amount of time with motor activity), distance (m), and area (m2). With regard to the CPT measures, significant group differences were found for omission errors only. Motor activity was associated with increased levels of cognitive impairment in the ADHD group only. Motor activity in the ADHD group was up to 3.5-fold higher than that of healthy controls during the 20 min of standardized testing. The group differences became more accentuated as the period prolonged. Lis et al. , the second were non-ADHD normative (N = 202), and the third were ADHD normative (N = 84).This study consisted of 341 participants, comprising three groups. The first were participants with ADHD  and the psychiatric division in the County Council of Värmland, Sweden (N = 19). Assessments included similar neuropsychological tests and procedures at both psychiatric clinics, such as tests of memory, attention, executive functioning, intelligence, interviews, observations, and somatic examinations. None of the participants used stimulants on the day of the QbTest-Plus, but 34 participants generally used stimulants. The approximate mean time from taking stimulant medication at the first minute of the QbTest-Plus was 30.55 hr . A total of 22 persons did not use psychotropic medication, while 33 persons used one (n = 19), two (n = 10), three (n = 1), four (n = 2), or five (n = 1) psychotropic medications. Medications included antidepressants (n = 26), antiepileptics (n = 13), anxiolytics (n = 10), neuroleptics (n = 7), and anticholinergics (n = 1). The approximate mean time from taking psychotropic medication at the first minute of the QbTest-Plus was 16.27 hr (SD = 15.11 hr). Statistical analyses  regarding age, education, Global Assessment of Functioning (GAF) total . For means and standard deviations, see Demographic data for the ADHD group are presented in N = 202) included 114 men and 88 women whose mean age was 31.06 years . The group was recruited from the general population in order to represent non-ADHD normative participants and they did not have a diagnosis of ADHD. Participants were screened for symptoms of ADHD using the adult ADHD Self-Report Scale . The mean total for the six items that were most predictive of ASRS, that is, the screener, was 8.90 (SD = 3.53), and the mean total overall was 24.56 (SD = 8.66). An independent samples t-test confirmed that the ASRS scores of the screener and the total were significantly different (ps < .001) from those of the ADHD group presented in t-test yielded no significant differences for men and women in the non-ADHD normative group with regard to age or ASRS (ps > .05).The second group of participants (N = 84) included 47 men and 37 women with ADHD whose mean age was 35.07 years (SD = 10.36 years). The participants had previously completed the QbTest-Plus as a part of a thorough neuropsychiatric assessment performed at the neuropsychiatric clinic, Cereb AB, in Stockholm, Sweden. Apart from the QbTest-Plus, the neuropsychiatric assessment also included tests of cognitive functioning, attention, intelligence, everyday functioning, and ADHD symptomatology.The third group of participants  and the Weighed Core Symptoms scale . For the PADHD, the ADHD normative data were employed to evaluate the levels of sensitivity and specificity. For the WCS, the ADHD normative data were employed in the assessment of core symptom manifestations and to examine the cut-off points on the scale. As this group was solely a normative reference group for ADHD in the present study, with the purpose of examining the PADHD and the WCS, findings from the group are not reported in the statistical analyses of the results section.The present study had a quantitative design. Statistical analyses of variance and a Fisher's exact test were conducted using the software program Statistical Package for the Social Sciences version 19.0 for Windows . The independent variables of the present study were Group  and Gender . There were 202 participants in the non-ADHD normative group and 55 participants in the ADHD group. The total number of men was 139 and the total number of women was 118. The dependent variables of the present study were the core ADHD symptoms of hyperactivity, inattention, and impulsivity, as well as the composite measure, the WCS scale. The categorical variable, PADHD, was analyzed using Fisher's exact test.The dependent variables were developed statistically from the core symptom measures from the QbTest-Plus, that is, hyperactivity measured in distance, inattention measured using omission errors, and impulsivity measured using commission errors. The Q-score (Qb-test raw score) of each core symptom was transformed into percentages, where 0% indicated the maximum quantity of the symptom and 100% indicated the complete absence of the symptom. The additional scale, WCS, was constructed using weighed Q-scores from the symptom scales. The WCS runs from 0, which indicates the maximum amount of ADHD symptoms, and 100, which indicates a complete absence of ADHD symptoms. The weighed Q-score principle was based on analyses of Receiver Operator Curves, in which hyperactivity was the most predictive item of ADHD and therefore multiplied by 3, inattention was the second most predictive item and multiplied by 2, and impulsivity was ascribed no additional weight because of its relatively low predictive value.p < .05) with the PADHD  and Group . For further information on how the PADHD was conducted see the instruments section.The categorical variable, PADHD , was also based on the raw scores from the measures of the QbTest-Plus (Q-scores), that is, hyperactivity measured in distance, inattention measured using omission errors, and impulsivity measured using commission errors. It was analyzed in the present study using Fisher's exact test .In this study, hyperactivity has been operationalized with the parameter called “distance,” that is, the length of the path describing the movement of the headband reflector during the test. Inattention has been operationalized on the basis of omission errors, that is, when no response is registered and the stimulus was a target. Finally, impulsivity has been operationalized on the basis of commission errors, that is, when a response was registered and the stimulus was a nontarget. A former study of the QbTest-Plus . In the present study, the WCS correlated (Pearson's r) with hyperactivity , inattention , and impulsivity , and those results were also approximately the same when correlations were computed only for the ADHD group or only for the non-ADHD normative group.In this study, the relative significance of the core symptoms was taken into consideration by the means of the WCS, which weighs the scales of the core symptoms into one measure. The WCS scale was derived from the ADHD group and the non-ADHD normative group of the present study, and was tested on the normative group with ADHD, as described in the participants section. The ADHD normative group was employed in the assessment of core symptom manifestations and to examine the cut-off points on the scale. The best model adjustment was found when the results of the core symptoms were summed after the results of hyperactivity had been multiplied by 3, the results of inattention had been multiplied by 2, and the results of impulsivity by 1. Then, the total results from the ADHD group of the present study, the ADHD normative group, as well as the non-ADHD normative group, were categorized using 10 cut-off points , was based on qualitative analyses of raw scores from the operationalized measures of the QbTest-Plus (Q-scores). Data were derived from the ADHD group and the non-ADHD normative group of the present study. The qualitative analyses included testing the effects of setting various cut-off points as well as combining and coordinating cut-off points from the core symptom measures of hyperactivity (distance), inattention (omission error), and impulsivity (commission errors). The effects of the cut-off points were evaluated in terms of sensitivity  and specificity  for the ADHD group and the non-ADHD normative group. Multiple cut-off points for each of the three core symptoms combined with the coordinated cut-off points from the other two core symptoms resulted in multiple pathways to either of the two categories of PADHD . Except for distance, omission errors, and commission errors, the other parameters from the QbTest-Plus were assessed in terms of sensitivity and specificity, but according to the aggregated assessment trials, the most efficient parameters for the identification of ADHD and separation from non-ADHD normative participants were the three parameters that were ultimately included in the PADHD. Apart from the coordinated cut-off points for distance, omission errors, and commission errors, the PADHD also included supplementary cut-off points from a parameter called the normalized variation Q-score (NVQ). This variable is a mathematical measure defined as the standard deviation of the reaction time divided by the reaction time. It was included in the PADHD because it improved the predictive power. The NVQ is not a principal parameter in the PADHD, but is a supplementary parameter for the three core symptom measures.p < .05) for Prediction of ADHD  and Group .In order to make sure that the PADHD was not simply an adjustment for the ADHD group and the non-ADHD normative group of the present study, the PADHD was evaluated in terms of sensitivity and specificity for the ADHD normative group described in the participants section of the present study. The level of sensitivity became somewhat higher for the ADHD normative group than the ADHD group of the present study. This gave credit to the PADHD as not being an adjustment to the ADHD group of the present study. After the PADHD had been conducted through qualitative analyses and evaluated on the ADHD normative group described in the participants section, it was analyzed statistically for the present study using Fisher's exact test  Scale . Each item has a cut-off point of either 2 (sometimes) or 3 (often), and a result of four or more items listed above the cut-off point in part A is used as an inclusion/exclusion criterion for clinical purposes and in research programs, such as in the normative sample of the Qbtest-Plus  is a screening instrument , and not meeting the diagnostic criteria for ADHD in the DSM-IV. The study-specific procedures were explained and information about withholding one's diagnostic and medical status from the researcher as well as withdrawing from central stimulant treatment 24 hr prior to participation were highlighted in particular. On the day before participation, the participants received a short message on their mobile phone that included a reminder of the day, time, and location of the study.Nurses and trained clinicians at the psychiatric centers screened psychiatric records and recruited participants via mail and telephone. The vital inclusion criteria for the ADHD group were an age of 18–65 years, a diagnosis of ADHD according to the -IV APA, , a descrWhen arriving at the psychiatric center, the participant was met by a researcher in the lobby and taken to the test room, where information about the study procedures was provided. The written consent form was then introduced, and a signed copy received from the participant. The ASRS and a medical form, regarding the paticipant's medical status and the last time that central stimulant treatment was used, were then filled out. The patient's diagnosis and status was unknown to the researcher during the whole process of experimental testing and assessment. Prior to testing, the participant was seated on a chair without armrests in order to ensure a nonreclining body position and also provided with the reflective head-band and the handheld button.n = 3) and because of not obtaining the diagnostic requirements regarding ADHD (n = 1), which resulted in a total number of 55 participants for this group.Instructions on how to do the QbTest-Plus were given first verbally and then by the means of a standardized video  were recruited with the assistance of students at the Department of Psychology at Karlstad University in Karlstad, Sweden. The remaining part of the group (n = 63) was recruited with the assistance of the Cognitive Neuroscience Centre for Psychiatry at the University of Giessen, Germany. In Karlstad, recruiting was performed using major employers in the fields of education (n = 48), transportation/industry (n = 44), as well as among students at the University (n = 47). In Giessen, all recruiting was performed via major music organizations. The inclusion criteria for the normative group were an age of 18–65 years and a willingness to sign the informed consent and complete the study-specific procedures. The exclusion criterion was any known psychiatric diagnosis. The QbTest-Plus was performed at the Universities of Karlstad and Giessen. The procedures for experimental testing with the QbTest-Plus were the same as described above for the ADHD group.A majority of the participants in the non-ADHD normative group  between the variables, indicating a vast majority for No in the non-ADHD normative group and a vast majority for Yes in the ADHD group, as well as a Yes minority in the non-ADHD normative group and a No minority in the ADHD-group. The effects of the sensitivity and specificity for the categorical variable of the present study are presented in Fisher's exact test (5% level) with group  and the categorical variable, PADHD , showed a strong significant connection  and for gender . However, the analysis did not show a significant main effect for the interaction of group and gender . The results from the univariate F-tests regarding group and gender are given below.A Pillai's MANOVA  was conducted with group  and gender  as independent variables, and hyperactivity, inattention, and impulsivity as dependent variables. The analysis revealed significant effects for group  = 31.53, p < .001, Inattention, F = 70.00, p < .001, and Impulsivity, F = 47.45, p < .001, where the non-ADHD normative group scored higher on all variables compared with the ADHD group. With regard to gender, univariate F-tests revealed a significant effect for inattention, F = 8.05, p = .005, but not for hyperactivity or impulsivity (ps > .05). Further analysis showed that women scored lower on inattention, indicating higher symptom levels, compared with men. For means and standard deviations see Univariate F = 77.10, p < .001, but not of gender or the interaction of group and gender (ps > .05). The descriptive analyses showed that the non-ADHD normative group scored higher on the WCS compared with the ADHD group. For means and standard deviations see As the WCS is a composite measure, it needed to be analyzed separately using a two-way ANOVA. The analyses showed a significant effect of group, p < .001, η2 = .51, power > .99. The results from the univariate F-tests are given below.Subsequent analyses were conducted using a one-way Pillai's MANOVA with the categorical variable, PADHD , to investigate the relations with hyperactivity, inattention, and impulsivity. The analysis revealed significant results with PADHD, F-tests revealed significant effects of hyperactivity, F = 72.30, p < .001, inattention, F = 144.93, p < .001, and Impulsivity, F = 64.37, p < .001, where the no ADHD group scored higher on all variables compared with the yes ADHD group. For means and standard deviations see Univariate F = 249.34, p < .001, and descriptive analyses also showed that the group which was not supposed to have ADHD, according to the prediction variable, scored higher on the WCS compared with the group that was predicted to have ADHD. For means and standard deviations see The WCS was again analyzed separately using a one-way ANOVA. The analyses showed a significant effect for PADHD, The aims of the present study were twofold. First, to examine the predictive power of the QbTest-Plus in terms of its sensitivity and specificity for ADHD in adult persons, and second, to develop a composite measure for the entire ADHD core symptom triad on the basis of the measures provided by the QbTest-Plus. Two psychometric measures were developed in the present study. The first measure was the WCS, which quantified the amount of ADHD cardinal symptoms. The second measure was PADHD, which correctly classified ADHD in a majority of the cases. In this section, the results of the present study will be discussed in relation to some of the existing literature. First, the results from the examination of the sensitivity and specificity will be discussed, followed by the composite measure, and finally the limitations of the present study will be considered.In line with another recent study of PADHD  than the participants without ADHD, who had higher scores on the WCS . The WCS was developed using Qb-Test raw scores from the cardinal symptom measures of hyperactivity, inattention, and impulsivity. The scale was transformed, using visual binning with ten cut-points, into percentages where 0 indicated the maximum amount of ADHD cardinal symptoms and 100 indicated the complete absence of the symptoms. Interestingly, hyperactivity was the measure with the most diagnostic specificity, occurring frequently and most exclusively in the ADHD group regardless of the diagnostic subtype. Inattention was the most common symptom for both groups, which gives this measure a particular significance for diagnostic sensitivity. Impulsivity is probably the measure with the least sensitivity. It occurred infrequently in the ADHD group, but when it did so, it was often in extreme forms and usually along with other cardinal symptoms, consequently not adding any exclusive information for the detection of ADHD, altogether rendering low specificity. This relative significance of the cardinal symptoms was emphasized when constructing the WCS, because symptoms were given various weights, which is in line with the literature on the implications of core symptoms for the clinical diagnosis of ADHD  and with the inattentive subtype in particular (n = 11), suggests that additional studies with more representative samples are needed in order to investigate the present results with regard to the diagnostic subtypes of the clinical population with ADHD in general. As the hyperactivity measure has been emphasized in the present study, it is vital to investigate the levels of sensitivity with regard to well-defined and clinically representative samples of the ADHD diagnostic subtypes.The present study did not intend to investigate the PADHD and the WCS across the diagnostic subtypes of ADHD. Thus, the sample was not selected to be representative of the clinical phenomenon with regard to its relative proportions of diagnostic subtypes. However, it is worth mentioning that the majority of the ADHD participants in the present study were correctly classified using the PADHD and marked as impaired on the WCS regardless of their diagnostic subtype. The proportion of the ADHD predominantly inattentive subtypes in the present study (22%) was, however, lower than the clinical prevalence in general, that is, 37% , whereas positive prediction was related to lower scores on the scales (indicating higher symptom levels). Consequently, measures of ADHD (the WCS) and prediction of ADHD (the PADHD) were associated with each other and with actual ADHD  in a majority of cases.The present study also developed three separate core symptom scales intended for the patient and the clinician to use when illustrating and discussing symptom severity, as well as for monitoring treatment programs and progression. The core symptoms scales and the composite scale represent dimensional approaches to ADHD diagnosis and treatment. The behavioral measures are in line with the current clinical perspectives on ADHD and enable quantification of symptom severity and validation of subjective behavior ratings made by patients and family members. Both from the empirical scientific quarter and from literature reviews of adult ADHD , and participants without ADHD had higher scores on the WCS . The predictive values were similar to or higher than traditional measures of ADHD, such as behavior rating scales and neuropsychological tests. The study had limitations concerning psychiatric comorbidity and psychotropic medication in the group with ADHD, and some demographic data was not available to facilitate the matching process of the non-ADHD normative group.