P=0.048), while ADHD children showed no difference in GABA+ in the subcortical voxel (P>0.1), resulting in a significant age by disorder interaction (P=0.026). Co-varying for age in an analysis of covariance model resulted in a nonsignificant age by disorder interaction (P=0.06). Glutamine levels were increased in children with ADHD (P=0.041), but there was no significant difference in adults (P>0.1). Glutamate showed no difference between controls and ADHD patients but demonstrated a strong effect of age across both groups (P<0.001). In conclusion, patients with ADHD show altered levels of GABA+ in a subcortical voxel which change with development. Further, we found increased glutamine levels in children with ADHD, but this difference normalized in adults. These observed imbalances in neurotransmitter levels are associated with ADHD symptomatology and lend new insight in the developmental trajectory and pathophysiology of ADHD.While the neurobiological basis and developmental course of attention-deficit/hyperactivity disorder (ADHD) have not yet been fully established, an imbalance between inhibitory/excitatory neurotransmitters is thought to have an important role in the pathophysiology of ADHD. This study examined the changes in cerebral levels of GABA+, glutamate and glutamine in children and adults with ADHD using edited magnetic resonance spectroscopy. We studied 89 participants  in a subcortical voxel (children and adults) and a frontal voxel (adults only). ADHD adults showed increased GABA+ levels relative to controls ( Further, GABA seems to be important for behavioral inhibition and self-control,7 as reduced GABA levels are associated with high impulsivity, less cognitive control and impaired response inhibition.GABA, the main inhibitory neurotransmitter in the human cerebral cortex is synthesized from neuronal glutamate (Glu), and converted back into Glu in astrocytes. The astrocytic Glu is then catalyzed into glutamine (Gln) and transported to the presynaptic neuron, where it is cycled back into Glu, some of which is then converted into GABA.3 and imbalances in Glu are believed to interfere with the gating of sensory information in striato-frontal pathways in patients with ADHD.3Glu, the major excitatory neurotransmitter, modulates the release of dopamine,10 right prefrontal cortex11 and left striatum11 relative to controls, although these differences did not reach significance in a recent meta-analysis.12 Treatment with stimulant medication has been reported to decrease Glx in the basal ganglia in children with ADHD.13 However, there are also studies reporting no significant Glx differences with stimulant treatment.16 In ADHD adults, on one hand increases in Glx have been observed in the basal ganglia3 and in the left cerebellar hemisphere.17 On the other hand, studies report a reduction in Glx in the right anterior cingulate cortex,18 in a left midfrontal region19 and in the basal ganglia20 in adults with ADHD compared with controls. As the magnetic resonance spectroscopy (MRS)-visible Glx signal includes contributions from the metabolic Glx pool as well as the neurotransmitter pool, the MRS Glx signal represents only a nonspecific marker for neurotransmitter Glu. However, since neurotransmitter Glu is converted into Gln in glial cells,21 some authors have suggested that Gln may represent a more specific marker for neurotransmitter Glu.24In children with ADHD, an increase in Glu+Gln (Glx) was observed in frontal areas,25 However, to date, GABA+ has not been assessed in the basal ganglia in ADHD, although structural and functional basal ganglia abnormalities appear to represent a core finding in the ADHD literature, as highlighted in recent meta-analyses.27 Further, no previous studies have investigated both inhibitory and excitatory neurotransmission in both children and adults with ADHD in a single study, and the developmental trajectories of neurotransmitter levels in ADHD remain unclear, despite the known developmental abnormalities observed in the basal ganglia.28In children with ADHD, only one previous study has investigated cerebral GABA+ concentrations, reporting reduced levels in the sensorimotor cortex.25 We also expected to find increased levels of Glu in children with ADHD.10The primary aim of this study was to investigate whether inhibitory (GABA) and excitatory (Glu/Gln) neurotransmitter levels in a subcortical voxel are altered in children and adults with ADHD. A secondary aim was to investigate the relationship between neurotransmitter levels and ADHD symptomatology and how GABA, Gln and Glu change with development. For the ADHD adults, we examined a left frontal region centered on the dorsolateral prefrontal cortex in addition to the subcortical voxel. We hypothesized that GABA+ levels would be reduced in ADHD patients in the subcortical and frontal voxels, based on a recent report of decreased GABA in the sensorimotor cortex in children with ADHD.The participant group consisted of 89 participants including 16 children with ADHD and 19 control children, 16 adults with ADHD and 38 control adults. Data were acquired as part of a large developmental study investigating ADHD-related differences in GABA, Glu and Gln in the context of the normal maturational changes in these neurotransmitter systems. For this reason, a larger control group was recruited, but the groups were matched for age, handedness and gender. One ADHD adult was excluded because of recreational drug use. All participants complied with magnetic resonance imaging (MRI) safety standards. The control participants did not report any current or previous neurologic or psychiatric diagnoses or any current use of psychoactive medications. All spectra were inspected visually to assess fit quality and the signal-to-noise ratio, leading to the exclusion of one further adult ADHD patient and one control child. One child was excluded from the control group due to elevated ADHD symptom scores to avoid a confound due to subclinical cases . Because29 was performed with all ADHD children to ensure the diagnosis of combined ADHD and to exclude participants with comorbidities. Participants taking stimulant medications were instructed to interrupt their medication at least 72 h before the MRI measurements. Antidepressant medication in six adult ADHD participants was not interrupted. A urine toxicology test was not performed before scanning.The ADHD adults were recruited from the Psychiatric University Clinic Zürich and screened for comorbidities. All the patients were diagnosed according to DSM-IV criteria, by a consultant psychiatrist specialising in ADHD. To ensure a representative ADHD sample, we included participants with current mild depressive symptoms, but excluded any patients with major depression or current severe Axis I or II disorder, substance use disorder, autism spectrum disorder, tic disorder or any other medical or neurological illness affecting brain function. The ADHD children were recruited by the Department of Child and Adolescent Psychiatry of the University of Zurich. The Kiddie-Sads-Present and Lifetime clinical interview30 and the German short form of the Wender-Utah Rating Scale.31 For children, we used the research version of the Conners-3D32 and the strengths and difficulties questionnaires in their German adaptations.33Symptom scores were assessed with the German version of the Conners' Adult ADHD Rating ScaleAfter complete description of the study to the subjects, written informed consent was obtained. For the ADHD and control children, written consent was obtained from the parents and assent was obtained from the children. The study was approved by the cantonal ethics committee of Zürich and was conducted in accordance with guidelines of the Declaration of Helsinki. The participants received 60 Swiss Francs in vouchers for participation in this study.3 voxel in a subcortical region centered on the left basal ganglia  from all the participants. An additional 25 × 40 × 30 mm3 voxel was acquired in the left frontal lobe, centered on the dorsolateral prefrontal cortex from the adult participants , using an eight-channel receive-only head coil. The MRI protocol included a T1-weighted spoiled gradient echo scan  for planning the positioning of the target voxels. GABA-edited MR spectra were acquired using the MEGA-PRESS method with TE=68 ms, TR=2000 ms, 320 averages (160 pairs) and an eight-step phase cycle. We acquired spectra from a 28 × 40 × 25 mmants see . The ass34The T1-weighted images were segmented in native space using SPM8 with the ‘New Segment' module  running in MATLAB 2012b  to correct the spectroscopy results for partial volume cerebrospinal fluid contamination and different water compartment relaxation times.35 The edited spectra were analyzed with a simulated basis set including basis spectra for GABA, glutathione, NAA, Gln, Glu and N-acetyl aspartyl glutamate. GABA+/H2O, Glu/H2O and Gln/H2O were quantified from the edited spectra, using the control parameter sptype=‘mega-press-2'. The edited spectra provided a similar fit quality compared with the edit OFF MEGA-PRESS subspectra for Glu/H2O, but a better fit quality for Gln/H2O compared with the edit OFF subspectra (Gln detected with Cramer–Rao lower bounds (CRLB) <30% in 73/89 edited spectra and 43/89 edit OFF subspectra). The CRLB for GABA ranged from 2–10% for all participants. An estimate of general fit quality across each spectrum was assessed from the CRLB of the NAA fit, both in the edited spectra and in the edit OFF subspectra .The spectra were coil combined with weighting factors derived from the first point of the free induction decay signal from the unsuppressed water lines acquired with each coil. Water scaled metabolite concentrations were derived with LCModel version 6.3-1B.37 Normality of the data was assessed using Quantile–Quantile plots of the analysis of variance (ANOVA) residuals. ADHD-related and developmental differences in subcortical GABA+ and Glu were assessed with a 2 × 2 ANOVA, including age group (adults and children) and diagnostic group (ADHD and control) as fixed factors. Post hoc t-tests were performed to clarify the group differences. As the Gln levels were not normally distributed, differences between ADHD and control participants were tested using a two-tailed Wilcoxon rank-sum test. Correction for multiple comparisons was performed with Benjamini and Hochberg correction, with a false discovery rate (FDR) of 0.1.38 A multiple regression model was used to investigate the relationship between metabolite levels and ADHD symptom scores from the Conners' inventory, age, methylphenidate dose and gender, using the normally distributed data. To construct the final model, we started with the full model including gender, age, dose, inattention/memory-score, hyperactivity-score, impulsivity-score and the self-concept-score, then removed correlated regressors and finally removed nonsignificant predictors in a stepwise manner until only significant predictors remained in the model.Statistical analysis was performed using R 3.1.1 ref.  and ggPlM=52%, s.d.=3%) and ADHD patients . However, there was a significant difference in gray matter content comparing adults  to children .The gray matter content of the subcortical voxel did not differ significantly between controls =5.11, P=0.026, ω2=0.04; Post hoc t-tests demonstrated that ADHD adults had higher GABA+/H2O values  compared with controls . This difference was significant, t(52)=2.03, P=0.048, d=0.56. ADHD children showed no significant differences in GABA+/H2O values in the subcortical voxel  compared with controls , t(33)=−1.25, P>0.1, d=0.43.Comparing GABA+/HP=0.021, ω2=0.06), but the comparison between GABA levels in ADHD adults and controls revealed only a trend level difference (t(30)=1.99, P=0.055, d=0.73), although the effect size was comparable to that observed in the full control group. Co-varying for age in an analysis of covariance model resulted in a nonsignificant age group by diagnostic group interaction in the full group =3.5, P=0.06) but was significant in the one by one matched group =5.4, P=0.023).The same analysis was repeated with the one by one matched adult control group, resulting in similar results for the interaction =5.56, P=0.017) and 0.35 (P=0.010) for self-concept with an adjusted R2 of 0.26.The multiple regression in adults yielded standardized betas of 0.33 for age  between the groups.2O differences in the subcortical voxel in children and adults in a 2 × 2 ANOVA revealed a significant main effect of age group, F=40.6, P<0.001, ω2=0.31. The post hoc t-test revealed that children have significantly increased Glu/H2O values, t(78)=−6.59, P<0.001, d=1.49 =0.07, P>0.1, d=0.02) or for children (t(33)=−0.45, P>0.1, d=0.16).Comparing Glu/H1.49 see  relative2O regression model in adults and children yielded no significant effect. There were no significant differences in fit errors between ADHD and controls for Glu. However, Glu fit errors were significantly higher in adults (Mdn=5.4%) compared with children (Mdn=3.8%), W=1477, P<0.001, r=0.49.The Glu/HP<0.001, ω2=0.33). The comparison between adults and children was still significant t(64)=−5.87, P<0.001, d=−1.47.The same analysis was repeated with the one by one matched adult control group, resulting in similar results for the age group effect =33.25, The CRLB for Gln were <30% in 15/19 control children (range 13–23%), 14/16 ADHD children (range 10–22%), 32/38 control adults (range 10–29%) and 12/16 ADHD adults (range 11–28%). Using a stricter cutoff of 20% would result in the exclusion of two additional control children, two ADHD children, 15 control adults and six ADHD adults.2O compared with control adults (Mdn=1.15), W=229.0, P>0.1, r=0.14. However, ADHD children (Mdn=1.46) showed a significantly higher Gln/H2O level than control children (Mdn=1.01), W=152.0, P=0.041, r=0.38, which remained significant after FDR correction for multiple comparisons. There was no significant difference in Gln levels between adults (Mdn=1.2) and children (Mdn=1.09), W=726.0, P>0.1, r=0.11.ADHD adults (Mdn=1.25) showed no significant difference in Gln/H2O regression model was not performed due to non-normality of the data. There were no significant differences in fit errors between ADHD and controls for Gln. However, Gln fit errors were significantly higher in adults (Mdn=19.5%) compared with children (Mdn=16.00%) W=918.0, P=0.006, r=0.32.The Gln/H2O compared with control adults (Mdn=1.22), W=84.0, P>0.1, r=0.06. There was no significant difference in Gln levels between adults (Mdn=1.25) and children (Mdn=1.09), W=449.0, P>0.1, r=0.2.The same analysis was repeated with the one by one matched adult control group, where ADHD adults (Mdn=1.25) showed no significant difference in Gln/HM=34%, s.d.=3%) and ADHD patients .The gray matter content of the frontal voxel did not differ significantly between controls  compared with controls , t(51)=0.95, P>0.1, d=0.26 (see t(30)=0.02, P>0.1; d=0.01).In the left frontal voxel, ADHD adults did not differ in GABA+/H0.26 see . This waP=0.003) and −0.37 (P=0.05) for hyperactivity with an adjusted R2 of 0.15. There were no significant differences in GABA+ fit errors between ADHD and controls (P>0.1).The multiple regression in adults yielded standardized betas of 0.58 for inattention/memory  compared with controls , t(51)=0.12, P>0.1, d=0.03. This was also the case for the one by one matched group (t(30)=−1.07, P>0.1; d=0.39).ADHD adults showed no difference in Glu/HP>0.1).The multiple regression analysis in adults yielded no significant effects. There were no significant differences in Glu fit errors between ADHD and controls  >30%  leaving in total 48 adults (13 patients) in the analysis.2O values in the frontal voxel (Mdn=0.85) compared with controls (Mdn=0.98), W=179.0, P>0.1, r=0.16. This was also the case for the one by one matched group .ADHD adults showed no difference in Gln/HP>0.1).The multiple regression analysis in adults was not performed due to non-normality of the data. There were no significant differences in Gln fit errors between ADHD and controls =3.5, P=0.06. In the one by one matched group, the interaction was significant in the ANOVA =5.56, P=0.021) and the analysis of covariance =5.43, P=0.023). However, the effect of age on GABA+ is not yet clear, as some studies report a decline of GABA+ with age,43 while others observed an increase of GABA+ with age.44 The reported increase of GABA+ has also been reported to be driven by an increase of the co-edited macromolecules with age and not GABA.44It is possible that the significant difference in GABA between ADHD adults and controls might be driven by age differences. When age was included as a covariate in the GABA+ ANOVA in adults, the age by disorder interaction altered from F=5.11, 45 but not in others.46 However, most previous studies investigated the ratio of Glx (the sum of Glu+Gln) to creatine,47 rather than concentrations of Glx or Glu. Ratios to creatine are simpler to derive since they do not require correction for partial volume effects arising from cerebrospinal fluid in the MRS voxel, but the assessment of Glx/Cr ratios may be confounded by alterations in striatal Cr levels, which have been reported both in children10 and adults20 with ADHD. To our knowledge, only two previous studies investigated Glx or Glu in the left basal ganglia or striatum in ADHD, reporting an increase of Glx and Glu in children aged 8 years,10 and a decrease in Glx in both medication naive and medicated adults.20 These two findings point towards a possible age interaction with Glu in the striatum, such that Glu may be increased in children with ADHD and decreased with age, resulting in lower Glu levels in adult ADHD patients. However, in the present study, we did not observe a significant interaction between subcortical Glu levels and age or a significant effect in the regression analysis, although we did observe a significant main effect of age for Glu/H2O in the subcortical voxel, with children showing higher Glu concentrations than adults. Our regression analysis also suggests that Glu/H2O decreases with age in children and adults, consistent with the age decrease of Glx/Cr reported by Gao et al.,43 although their results were derived from frontal and parietal regions.We did not find increased subcortical Glu levels in ADHD patients compared with controls, as found in some previous studies48 Two of these studies did not include a healthy comparison group45 and one did not report group means or effect sizes for Glx,48 but for the remaining seven studies, we calculated the effect size (Cohen's D) from the difference between group means (ADHD–control) and the pooled standard deviations for Glx/Cr or Glx. Where data were available for multiple cohorts , the effect sizes were calculated separately for each ADHD cohort relative to the control group. Effect size data are shown graphically in 11 For the Glx concentration, data are only available for a small number of studies, but children with ADHD tended to show positive effect sizes (increased Glx) while adults with ADHD show smaller positive or negative effect sizes (reduced Glx20), but further studies would be needed to corroborate and extend this finding.To put our results into context with those from the literature, we identified 10 previous studies investigating Glx or Glx/Cr in the left basal ganglia/striatum in ADHD children or adults.2O in the subcortical voxel in children with ADHD, but there were no significant differences in Gln/H2O between ADHD and control adults. As Gln contributes to the Glx signal, the increased Gln levels are consistent with results from a previous study reporting increased Glx levels in children with ADHD11 =4.7, P=0.06) or control adults =1.5, P=0.39). The handedness was also carefully balanced between groups but the inclusion of both left- and right-handed participants may also contribute to the group variance. Future multicenter or meta-analytic studies with larger group sizes, or groups of male, right-handed participants only may be able to elucidate further the developmental and ADHD effects observed in the present study.Although the developmental effects observed in subcortical GABA+ levels and the significant difference in Gln levels in children with ADHD relative to control children survived correction for multiple comparisons with a relatively lenient FDR threshold of 0.1, these results did not survive correction with a more stringent FDR threshold of 0.05. Given the sample size, the relatively modest significance levels are surprising, but may result from the large variance seen both within and across age and diagnostic groups . Alterna45 others showed no change in Glx between medicated and medication naive adults with ADHD.20 However, in addition to psychostimulant medication for ADHD, four adult participants also reported current or previous use of antidepressants within 1 month of the MRS measurement, for sleep problems. As antidepressants have been shown to alter Glx51 and GABA levels,52 to assess the potentially confounding effects of antidepressant treatment on the MRS results, the statistical comparisons were repeated after excluding all participants on antidepressants. In this smaller subsample, the developmental GABA+/H2O interaction was of borderline significance with a similar effect size =3.93, P=0.05, ω2=0.03) compared with F=5.11, P=0.026, ω2=0.04 in the full group. The differences in GABA+/H2O between ADHD and control adults were not significant anymore due to the smaller sample size, but showed a similar effect size (t(47)=1.58, P=0.1, d=0.46 compared with t(52)=2.03, P=0.048, d=0.56). Therefore, while the results do not appear to be driven by medication effects, the variability in medication status of the ADHD adults does represent a significant source of variance, and these results should be reproduced in a sample of medication naive patients.In addition, medication effects could introduce variance, even though participants taking stimulants were asked to withdraw from treatment for 72 h before the MRS session. While some studies have reported a decrease in Glx levels following stimulant treatment,54 but with the default settings the baseline fit can include a large fraction of the GABA peak, introducing an error into the estimated GABA concentrations. However, with the MEGA-PRESS-2 and MEGA-PRESS-3 control parameters (available from version 6.3 onwards), the default baseline fitting in LCModel is turned off and this error is reduced.LCModel offers improved reproducibility for GABA detection relative to alternative spectral analysis methods,W=112.0, P=0.137, r=0.30, compared with W=152.0, P=0.041, r=0.38 in the full group). However, as higher CRLB are expected for lower concentration metabolites, using a strict CRLB cutoff for low-concentration metabolites like Gln and GABA can introduce a systematic bias toward higher concentrations as lower concentrations are more likely to be excluded. This potential bias can confound the analysis of group differences and should be considered carefully when selecting a CRLB cutoff.Although the CRLB cutoff used for Gln was relatively lenient (30%), using a stricter cutoff of 20% resulted in the exclusion of four additional children (two ADHD children and two control children). In this smaller subset of participants, the group difference in Gln in children was no longer significant  which change with development. Children with ADHD also show increased Gln levels in the subcortical voxel, but this difference normalized in adults. These imbalances in neurotransmitter levels are associated with symptom scores and lend new insight in the development and pathophysiology of ADHD.


To the Editor:Bartonella spp. are gram-negative alphaproteobacteria that are transmitted between the reservoir and mammal host by hematophagous insects  in the Echarate District, La Convención Province. Traps had been set in intradomiciliary, peridomiciliary, and extradomiciliary settings. Spleens of animals were obtained, and DNA was isolated by using the Illustra Tissue and Cells Genomic Prep Mini Spin Kit .Bartonella spp. DNA by using a PCR and primers CS443f and CS1210r specific for a 767-bp fragment of the citrate synthase gene (pla) encoded by the Y. pestis–specific pPLA plasmid  (blastn) program (www.ncbi.nlm.nih.gov/Class/MLACourse/Modules/BLAST/nucleotide_blast.html). The χ2 test was used to determine statistical differences in the prevalence of both pathogens among host species and villages.New and published Y. pestis and Bartonella spp. were 17.9% and 21.4%, respectively . Rodents positive for Bartonella spp. were found in the 3 study villages, and prevalence for Aguas Calientes was higher than that for Alto Ivochote (p<0.001). One of 8 rodents trapped inside houses and 1 of 2 rodents trapped at peridomestic sites were positive for Bartonella spp.Overall prevalences for ectively . Co-infeBartonella genogroup A, which was obtained from Oryzomis palustris rats in the southeastern United States .We propose that the genotype of isolates B273 and B280 is variant A6 and the genotype of isolate B259 is variant A7. A previous study reported that the A, B, and C genogroups contain independent species  that had 98% and 99% sequence similarity to genotypic variant A3 of the undescribed pla amplicons (GenBank accession nos. KF214264–KF214266) had 98% sequence identity with Y. pestis reference sequences. Plague prevalence was higher in H. perenensis rats than in R. rattus rats (p<0.05). Infected rodents were found in all villages studied except Yomentoni, and prevalence in Aguas Calientes was higher than in Alto Ivochote (p<0.01). Two (25%) of 8 rodents trapped inside houses were infected with Y. pestis.The Bartonella spp. and Y. pestis are common and widespread throughout the Echarate District. It also shows the role of H. perenensis and Oecomys spp. rodents as reservoirs of both pathogens. This role was confirmed by amplifying the chromosomal ferric iron uptake regulation gene by using PCR primers Ypfur1 and Ypfur2, as described by Hinnebusch et al. (Bartonella spp. as a cause of disease in humans is emerging in the Americas. This role has been suggested by identification of a novel rodent-associated Bartonella strain causing febrile illness in the rural southwestern United States (B. elizabethae, a bacteria that can cause human endocarditis, in the Huayllacallán Valley in Peru (This study suggests that infections of rodents with Bartonella spp. have been reported as infectious agents for humans, our results should prompt public health concern. However, our findings require further investigation about the pathogenicity of these Bartonella genotypes. The detection of both pathogens in intradomestic and peridomestic areas where humans are in close contact with rodents could indicate that the incidence of both diseases in humans from Echarate District might be underestimated.Because most identified


Bartonella species are human pathogens but little is known about their epidemiology. We trapped rodents and shrews around human habitations at two sites in Kenya  to determine the prevalence of Bartonella infection. Bartonella were detected by culture in five of seven host species. In Kibera, 60% of Rattus rattus were positive, as compared to 13% in Asembo. Bartonella were also detected in C. olivieri (7%), Lemniscomys striatus (50%), Mastomys natalensis (43%) and R. norvegicus (50%). Partial sequencing of the citrate synthase (gltA) gene of isolates showed that Kibera strains were similar to reference isolates from Rattus trapped in Asia, America, and Europe, but that most strains from Asembo were less similar. Host species and trapping location were associated with differences in infection status but there was no evidence of associations between host age or sex and infection status. Acute febrile illness occurs at high incidence in both Asembo and Kibera but the etiology of many of these illnesses is unknown. Bartonella similar to known human pathogens were detected in small mammals at both sites and investigation of the ecological determinants of host infection status and of the public health significance of Bartonella infections at these locations is warranted.Several rodent-associated  Bartonella are bacteria that infect many different mammal species and can cause illness in people. Several Bartonella species carried by rodents cause disease in humans but little is known about their distribution or the importance of bartonellosis as a cause of human illness. Data from Africa are particularly scarce. This study involved trapping of rodents and other small mammals at two sites in Kenya: Asembo, a rural area in Western Kenya, and Kibera, an informal urban settlement in Nairobi. Blood samples were collected from trapped animals to detect and characterize the types of Bartonella carried. At the Kibera site over half of the trapped rats were infected with Bartonella very similar to human pathogenic strains isolated from rats from other global regions. In Asembo, Bartonella were detected in four of the five animal species trapped and these Bartonella were less similar to previously identified isolates. All of the small mammals included in this study were trapped in or around human habitations. The data from this study show that Bartonella that can cause human illness are carried by the small mammals at these two sites and indicate that the public health impacts of human bartonellosis should be investigated. Bartonella species are Gram-negative haemotrophic bacteria that infect mammalian erythrocytes and are transmitted between hosts by blood-sucking arthropods. Over 30 species of Bartonella have been described and members of this genus infect a broad range of mammalian hosts including rodents, bats, carnivores and ruminants [Bartonella has a global distribution. The Bartonella elizabethae complex includes several Bartonella genotypes and strains  that have been isolated from Rattus and Bandicota species around the world [Rattus species [uminants . Arthropuminants –4. The ghe world . Recent  species .Bartonella species are recognized as human pathogens that cause diverse clinical presentations [Bartonella species, B. elizabethae is a known cause of human endocarditis [B. tribocorum, B. vinsonii subsp. arupensis, B. washoensis and B. alsatica have been associated with a range of symptoms in humans including fatigue, muscle and joint pain, and serious complications, such as endocarditis and neurological signs, particularly in immunocompromised patients [Several ntations . Among rcarditis . Other rpatients ,9.Bartonella species have been identified as important causes of febrile illness in some settings. In two studies conducted in Thailand, 15% of febrile patients were diagnosed with confirmed Bartonella infection based on a four-fold rise in antibody titres, and six different Bartonella species were identified by culture from blood clots collected from febrile patients [Bartonella species may well be under-recognized as a cause of human disease [patients ,11. Non- disease . This is disease .Bartonella  in 4.5% of febrile patients [Bartonella bacteraemia was detected by PCR in 10% of HIV-positive patients in South Africa [Bartonella on human health on the African continent.In the Democratic Republic of Congo (DRC), a seroprevalence study identified IgG antibodies against patients . Bartoneh Africa . Apart fBartonella species have been detected in animal and ectoparasite populations in Africa. Considering rodents and small mammals specifically, B. elizabethae and two other Bartonella lineages were detected in Namaqua rock mice sampled in South Africa, where 44% of the 100 individuals sampled were positive by PCR for Bartonella species [B. elizabethae, B. tribocorum and a Bartonella species with intermediate species classification based on sequence data were detected in 28% of rodents and hedgehogs (n = 75) sampled in Algeria [B. elizabethae, B. tribocorum and novel Bartonella species were also detected in rodents sampled in the Democratic Republic of Congo (DRC) and Tanzania [Bartonella infection prevalence of 34% (n = 529) and were infected with multiple genotypes including genotypes very closely related to B. elizabethae [B. elizabethae has also been detected in invasive and indigenous rodents sampled in Uganda [B. rochalimae, B. grahamii and B. elizabethae have been detected in Mearn’s pouched mice studied in Kenya [Bartonella have also been detected in fleas collected in Egypt, Morocco, DRC and Uganda [A variety of  species . B. eliz Algeria . B. elizTanzania . Small mzabethae . B. elizn Uganda  and genoin Kenya . Bartoned Uganda ,22–24.Bartonella infections in small mammals trapped at rural and urban locations in Kenya. We also aimed to characterize the Bartonella isolates obtained using partial sequences of the citrate synthase (gltA) gene and to compare the Bartonella genotypes detected in these distinct Kenyan populations with each other and with Bartonella detected in small mammals in other parts of the world.The first objective of this study was to determine the presence and prevalence of Cross-sectional rodent trapping surveys were conducted within two locations: Asembo, a rural area on the northern shore of Lake Victoria in Nyanza Province western Kenya  and Kibera, an urban informal settlement in Nairobi City  gene. Crude DNA extracts were obtained from bacterial cultures by heating a heavy suspension of the microorganisms. Two oligonucleotides (BhCS.781.p and BhCS.1137.n) were used as PCR primers to generate a 379-bp amplicon of the Bartonella gltA gene [The identity of presumptive ltA gene . PCR progltA amplicons. Unique gltA sequences generated through this study were submitted to GenBank (accession numbers KM233484—KM233492). The Clustal V program within the MegAlign module of Lasergene was used to compare homologous Bartonella gltA sequences generated in this study with others available from the GenBank database. Phylogenetic trees were constructed using the neighbor-joining method with the Kimura’s 2-parameter distance model and bootstrap calculations were carried out with 1000 replicates. B. tamiae was used as the outgroup. A criterion of >96% homology was used to define similarity of study sequences to known Bartonella species [Sequences were analysed using Lasergene 12 Core Suite  to determine sequence consensus for the  species .Bartonella infection status (culture positive or negative for Bartonella) and host and environmental variables in R (Version 3.0.3) [Generalized linear models were used to examine associations between individual n 3.0.3) . BinomiaWritten informed consent for trapping was obtained from representatives of the study households. The protocols and consent forms were reviewed and approved by the Animal Care and Use and Ethical Review Boards of the Kenya Medical Research Institute (#1191). The study protocols were also approved by the Institutional Animal Care and Use Committee and Institutional Review Board of the U.S. Centers for Disease Control and Prevention (#5410) and complied with the Public Health Service Policy on Humane Care and Use of Laboratory Animals.Crocidura olivieri , and rodents of the species Lemniscomys striatus , Mastomys natalensis , Mus minutoides , and Rattus rattus . All of the rodents trapped in Kibera were Mus musculus , Rattus norvegicus  or Rattus rattus (n = 32)  .Bartonella, including: Crocidura olivieri ; Lemniscomys striatus ; Mastomys natalensis ; and Rattus rattus . Overall, 24 of the 220 (11%) animals trapped in Kibera were culture positive: including Rattus norvegicus  and R. rattus . None of the 178 samples collected from Mus musculus in Kibera were positive (Rattus species were trapped in four of the five trapping grids established at the Kibera site (Ten of the 49 (21%) animals trapped in Asembo were culture-positive for positive . Cultureera site .gltA sequences was obtained from all 34 culture-positive animals. The phylogenetic relationships between the isolates obtained in this study and previously described Bartonella species are shown in Figs Bartonella detected in one M. natalensis and two R. rattus trapped in Asembo belong to the B. elizabethae species complex based on the similarity of the gltA sequences  to reference strains of the Bartonella species described previously in Rattus species trapped elsewhere. The strain of Bartonella cultured from a C. olivieri was not very similar to any previously described Bartonella reference species but has 93.8% similarity B. birtlesii. Three pathogenic Bartonella species  were detected in the two Rattus species sampled at the Kibera site. The gltA sequences for all Bartonella strains from Kibera rodents were identical (≥ 96% sequence identity) to reference isolates that are typical of Bartonella detected in Rattus populations globally . Approximately half (24/49) of the small mammals trapped in Asembo were trapped outside  were trapped outside. There were no statistically significant associations between the probability of Bartonella infection and small mammal sex or mass within the Asembo population. At the Kibera location, there was a clear influence of genus upon infection probability. None of the 178 Mus trapped were Bartonella positive but 24/42 Rattus were positive indicating much higher infection probability in Rattus (OR = Infinite). Considering the data for Rattus individuals only, there were no statistically significant associations between the probability of Bartonella infection and rodent species, sex, or mass. The proportion of infected Rattus and proportion of infected rodents overall varied by trapping zone in Kibera  and more Bartonella isolates of several species were identified in these populations.At the Asembo location, there was a weak association between individual infection status and host species (likelihood ratio test p = 0.053) where infection probability was higher in  outside . None ofn Kibera . There w trapped , the rodee zones . In contBartonella strains from rodent and shrew species in Asembo and Kibera, Kenya. Bartonella strains were found in several small mammal species with variation observed in the infection prevalence and in the strains of Bartonella detected between host species and study sites. The majority of Bartonella isolates obtained from these Kenyan mammals are genetically similar to reference strains of known human pathogens.This study reports isolation of Bartonella infection in Rattus in Africa may be low in contrast to the frequently high prevalences observed in Asian Rattus populations [Rattus populations could be attributed to host escape during colonization [R. rattus from Asembo (13%). However, the high infection prevalence observed in Rattus trapped at the Kibera site (e.g. 50% R. norvegicus and 60% R. rattus) is more similar to prevalence values observed in studies of Asian Rattus populations than to other African populations [Rattus at these two sites. Phylogenetic analyses indicate that B. elizabethae complex strains originated in Southeast Asia and have been disseminated throughout Asia, Europe, Africa, Australia and the Americas through multiple dispersal events of commensal Rattus species [Rattus and their associated Bartonella species to this site [Rattus and their associated Bartonella at these sites specifically. The number of species trapped in Kibera was smaller than the number trapped in Asembo, indicating a simpler species composition at this site and these data could also suggest a possible dilution effect of the increased community complexity in Asembo on Bartonella prevalence [Bartonella infection prevalence [Rattus populations.Several recent studies indicate that the prevalence of ulations –20,32. Inization ,20, a phnization . Consistulations . There ahis site ,33. Furtevalence . Finallyevalence ,35. Thisevalence . It is tMus musculus trapped in Kibera despite a large number of tested animals and high infection prevalence observed in Rattus trapped in the same locations. Low-level Bartonella infection has been reported from Mus trapped in Ethiopia but the absence of Bartonella in Mus was also reported in a small-scale study from Nigeria [Notably, no bartonellae were detected in  Nigeria ,37.Bartonella. The two culture positive animals trapped in outbuildings were R. rattus and they were carrying Bartonella similar to the B. elizabethae reference strain  belong to the Bartonella elizabethae complex and many of the strains identified in invasive Rattus hosts particularly are closely related to known human pathogens. All of the Bartonella strains isolated from Kibera rodents have ≥ 96% sequence identity with strains that are common in Rattus species sampled in Asia and on several other continents [Rattus and were more similar to isolates gathered previously from Ugandan rodents, suggesting a longer history of circulation of these strains within these species at the Asembo site. The identification of similar B. tribocorum sequences in Mastomys and Lemniscomys individuals trapped in Asembo suggests an absence of strong host-pathogen associations in these populations.Many of the ntinents . In contBartonella species have been identified as important causes of human febrile illness in several global settings but there has been little investigation of the impact of bartonellosis upon human health in Africa particularly and it is conceivable that Bartonella may be an important cause of febrile illness in these study populations.There is a high incidence of acute febrile illness in people in both Asembo and Kibera . A varieBartonella infection in the same host (Rattus species) at the two sites; the prevalence of infection in different hosts trapped at the same sites; the abundance of different infected hosts between the two locations and also between trapping zones in Kibera; the strains of Bartonella detected and finally in the locations within communities where rodents overall and Bartonella infected rodents were trapped. The impact of this variation in rodent host community composition, infection prevalence, ectoparasite vector preferences, and other ecological factors need to be understood to evaluate human Bartonella infection risks at these sites. The data presented here suggest that investigations of the multi-host infection dynamics of Bartonella and the public health significance of Bartonella infections at these Kenyan locations and others where there are close associations between people and small mammals are warranted.The data presented from the Asembo and Kibera sites indicate clear differences in: the prevalence of S1 Table(XLS)Click here for additional data file.S2 Table(XLSX)Click here for additional data file.


The prevalence of citizens diagnosed with Attention Deficit Hyperactivity Disorder (ADHD) has risen dramatically over the past decades in many countries, however, with large variations. Countries such as Denmark with centrally organized well fare systems, free access to health services and individual tracking based on unique personal identification may in particular contribute to our understanding of the reasons for this increase. Based on Danish registers we aimed to examine the geographical patterns of the distribution of ADHD diagnosis and medication use and explore the association with access to diagnostic services, diagnostic culture, neighbourhood socioeconomic status and municipal spending on health care for children.We combined information on registered diagnosis of ICD-10 Hyperkinetic Disorder and ADHD medication use in a Danish register-based cohort of children born between 1990 and 2000. We mapped incidence proportions of diagnoses and medication use within the 98 Danish Municipalities. Global and local clustering of ADHD was identified using spatial analysis. Information on contextual factors in the municipalities was obtained from national registers. The associations between the incidence of ADHD and contextual factors were analysed using Bayesian spatial regression models.We found a considerable variation in the incidence of ADHD across the municipalities. Significant clustering of both high and low incidence of ADHD was identified and mapped using the local Moran’s I. Clustering of low incidence of diagnosis and medication use was observed in less populated areas with limited diagnostic resources and in contrast clustering of high incidence in densely populated areas and greater diagnostic resources. When considering the spatial autocorrelation between neighbouring municipalities, no significant associations were found between ADHD and access to diagnostic services, different diagnostic culture, socioeconomic status at municipality level or the municipal spending on health care for children.A large geographical variation of ADHD in the municipalities was observed despite tax-financed and free access to healthcare. Although not statistically significant, results indicate that accessibility to diagnostic resources might explain some of the variation in ADHD incidence. In contrast to US studies the observed variation was not statistically associated to contextual factors in terms of SES, municipal spending on health care for children or differences in diagnostic practices. Attention Deficit Hyperactivity Disorder (ADHD) is a behavioural disorder characterised by inattentiveness, hyperactivity and impulsiveness. In most countries it is the most commonly diagnosed childhood behavioural disorder with an estimated prevalence of 3–5 % among 6 to 12-year old children . The recIt has been debated whether this increase in diagnosis and treatment of childhood psychiatric disorders reflects a true increase in the incidence of mental health problems in children, changes in their impact or simply an increase in recognition and help-seeking behaviour. This increase in diagnosis and treatment of psychiatric disorders may be related to contextual changes in society and an improved understanding of the relative contribution of these factors has become of major public interest. A recent study found a reduction over time in parent and teacher perceived levels of behavioural problems in pre-adolescent children in Great Britain concurrent with the increase in diagnosis and treatment; this suggests that the increased prevalence may be due to contextual factors rather than an increase in behavioural problems .Contextual factors causing an increase in diagnosis and treatment could be related to changes in access to diagnostic facilities/number of specialists, diagnostic culture, community resources such as socioeconomic status (SES) and spending on primary health care for children; these factors have been suggested to be associated with geographical differences , 17–19. Studies of factors related to access to diagnostic facilities have found that having a diagnosis of ADHD or taking medication for ADHD was associated with the number, age, and specialisation profile of physicians within states and counties in the US , 17. In Psychiatric diagnoses are based on descriptive criteria, interviews and observations; any diagnosis in psychiatry includes an interpretation and decision-making by a professional . A recenAn association between family socioeconomic disadvantage and childhood ADHD has been established at the individual level , 18, 19,Most studies addressing the rise and geographical variation in prevalence of ADHD have been conducted in the US; few have addressed European contexts. The associations between ADHD and access to diagnostic facilities, diagnostic culture and community SES may be very different in a country with free access to qualified health care and economic equality.In the present study we performed exploratory spatial analysis to examine if the following contextual factors were associated with the risk of ADHD diagnosis or treatment: access to paediatric psychiatrists and psychiatric hospitals, average SES in the community, spending on primary health care for children and diagnostic culture in the public psychiatric hospitals. We used administrative data from Denmark to identify spatial patterns of ADHD that may drive the increase in recorded incidence.The total number of children with ADHD was 8218 of which 6798 children had a hospital diagnosis, 6693 children redeemed medication, and 1420 children redeemed medication but did not have a registered diagnosis (treated by private practicing paediatric psychiatrists). In all of 750,512 children were born in the period from 1990 to 2000 in Denmark  in the 1990 birth cohort to 2.58 %  in the 2000 birth cohort  than the incidence proportion in the 1990–1992 birth cohort resulting in a significant national increase in incidence. Figure All indicators of ADHD vary considerably across municipalities. The mean incidence proportion of overall ADHD was 1.19 %, ranging from 0 to 2.87 % in the municipalities Table .Table 3SFour maps were constructed based on the incidence proportion of ADHD in each municipality using the previously mentioned indicators of ADHD: (a) all children with a diagnosis, (b) all children redeeming medication, (c) children redeeming medication but without a registered diagnosis, (d) all children with a diagnosis and/or redeeming medication Fig. . The pubWithin 98 municipalities in Denmark, 12 paediatric psychiatric wards are placed in 12 different municipalities and 16 private paediatric psychiatrists are practicing in 12 different municipalities. In all, diagnostic facilities are available in 18 municipalities  and the clustering of high incidence is covering an area with an average population density of 175 per km2 (ranging from 84 to 403 people per km2).Figure p value = 0.045  of the incidence proportion of the different indicators of ADHD between municipalities. Significant spatial clustering (by Moran’s I) between municipalities was seen. Overdispersion can also be due to lack of important explanatory variables. This study shows that the variation in ADHD diagnoses and medication use in Denmark is not random as the incidence is highly correlated in the municipalities. One possible cause is confounding if an important spatially correlated covariate is either not measured or unknown .This study used aggregated data at municipal level since we hypothesized that the variation is due to structural factors at this level.This exploratory analysis produced maps of the incidence proportions of ADHD by municipality using different indicators. Large variations in the incidence were observed as well as considerable differences in the increase in incidence across municipalities. Significant clustering of both high and low values was identified and mapped using the local Moran’s I. The clustering of low incidence proportions was located in less populated areas with limited diagnostic resources and in contrast clustering of high incidence proportions in densely populated areas with greater diagnostic resources. A large geographical variation of ADHD in the municipalities was observed despite tax-financed and free access to healthcare. Although not statistically significant, results indicate that accessibility to diagnostic resources might explain some of the variation in ADHD incidence. In contrast to US studies the observed variation was not statistically associated to contextual factors in terms of SES, municipal spending on health care for children or differences in diagnostic practices.With complete follow-up of a whole country’s citizens this study shows that the variation in ADHD diagnosis and medication use is not random and the reasons for the increased incidence of ADHD are probably complex and diverse.There are likely unknown factors related to diagnostic processes, besides accessibility to diagnostic services that drive the diagnostic occurrence of ADHD.We included all children born in Denmark from 1 January 1990 to 31 December 2000. This cohort was extracted from the Danish Medical Birth Registry and consisted of 750,512 children. The Danish Medical Birth Registry comprises data on all live births and stillbirths among women with permanent residence in Denmark . All livAll children were followed from birth until the first diagnosis of ADHD, first use of ADHD medication, death, emigration, the age of 11 years, or 31 December 2011, whichever came first. All children were followed up to the age of 11 years to ensure the same follow-up time of all children as the geographic analysis rely on binomial regression. The last birth cohort in our analyses was born in 2000 as we were able to do a follow-up in 2011. A child was considered to have ADHD if receiving a confirmed diagnosis of ADHD after the age of 5 years or redeeming a prescription for ADHD medication. ADHD can be difficult to diagnose before the age of five therefore the child was only considered a case if registered with a hospital admission related to the diagnosis or redeemed medication after the age of 5 years. Information on ADHD medication was obtained from the Register of Medicinal Product Statistics . A childIn Denmark, citizens have the right to use privately practicing specialists free of charge if waiting time at public hospital services exceeds 1 month. However, privately practicing psychiatrists are not obligated to report diagnoses to the registries. Thus, we used ADHD medication prescriptions as a proxy for those children who did not have a hospital diagnosis of ADHD. In Denmark, only specialists in paediatric psychiatry are allowed to prescribe ADHD medication to children.Data were available at individual level. We assigned the cases to the municipality in which they were diagnosed or redeemed prescriptions, whichever came first, while the rest of the study population was assigned to their birth municipality. We performed a sensitivity analysis assigning all children to their birth municipality. The results did not differ from the initial analyses. For the purposes of this analysis we aggregated data and performed the analyses at municipality level. The aggregation was calculated as the incidence proportion for each municipality. The number of cases was divided by the number of children born in the municipality from 1990 to 2000.The study was approved by the Danish Data Protection Agency.Health care in Denmark is primarily tax-financed and free of charge at the point of service. Danish health care is divided into three political and administrative levels: government level, regional level and municipal level. There are five regions and 98 municipalities in Denmark. The responsibility for running the public health care services is decentralised and divided between the regions and municipalities. The running of secondary care  is the responsibility of the five regions. The 98 municipalities are responsible for primary care, public health care, school health service, child dental treatment, prevention and rehabilitation. Costs of most prescriptive medication, including ADHD medication can be reimbursed.The first phase of the spatial data analysis included mapping the distribution of the different indicators of ADHD incidence proportion; diagnosis, medication use, medication use in children without a registered diagnosis, and overall ADHD (both diagnosis and/or redeeming medication). The next phase included the use of two spatial statistics to determine the spatial clustering: the global and local Moran’s I. The global Moran’s I statistic is a global measure of spatial autocorrelation used to test whether values in a numeric variable are randomly distributed over the geographical area or whether neighbouring values tend to be more similar than non-neighbouring. Moran’s I shows the strength of spatial autocorrelation on a scale ranging from +1 to −1. A value of +1 indicates positive spatial autocorrelation where high values are proximal to other high values. Conversely, a value of −1 represents negative spatial autocorrelation where high values tend to be near low values. A value of zero indicates no spatial autocorrelation, i.e. data are randomly distributed within the studied geographical area. Since global indices of spatial autocorrelation summarize the phenomenon of interest in a single value, they are intended not so much for identifying spatial clusters, as for detecting the presence of a general tendency to clustering within the study area. The local Moran’s I statistic reveals whether and where any local clustering occurs. The local Moran’s I identifies individual clusters, or small regions of clusters that may not be evident within the global pattern .An analytic tool in STATA developed by Maurizio Pisati was used to calculate both the global and the local Moran’s I statistic and associated Z-score. This tool tests whether the homogeneity (or heterogeneity) in values between a municipality and its neighbouring municipalities is higher than would be expected by chance. A municipality with a high Moran’s I statistic indicates that its incidence proportion values are close in magnitude to those of the neighbouring municipality. We used the tool to draw cluster maps visualising what is also called “hot spots”  and “cold spots”  .std. The distance band was chosen to be 200 km as the median distance between the centroids in the municipalities was 141 km and the 3rd quartile distance was 200 km. We performed a sensitivity analysis with distance bands of 150 and 300 km; this did not significantly change the clusters. The only changes were the appearance of one municipality and the disappearance of another in clusters with low incidence proportions.The analysis of spatial autocorrelation requires a measurement of the degree of spatial proximity among the spatial objects of interest. Typically, the degree of spatial proximity among a given set of spatial objects is represented by a matrix called spatial weights matrix (W) . We usedA two sided p value of <0.05 was considered statistically significant.To examine access to diagnostic services, information on number and municipality of privately practicing paediatric psychiatrists was extracted from a national register on provision of privately practicing physicians in 2009. The variables concerning economic characteristics in the municipalities were derived from Statistics Denmark for 2010 providing information aggregated at municipality level. The measures of SES in the municipalities and the municipal spending on health care for children reflect the local resources spent in the municipalities. The municipal spending on primary health care for children is a measure of the services provided by health visitors and school nurses. These services are available for all Danish children and can be used as a measure of the capacity of paediatric health promotion and disease prevention at municipality level. The average annual household income was used as a proxy for municipality level SES and calculated as the sum of the main source of income. The average municipal spending on primary health care for children was calculated as the net operating costs per child aged 0–16 years per year including the average costs of primary care including school nurse and health visitor services. Differences in diagnostic culture were examined by studying variation in the incidence proportion of conduct disorders. A number of criteria for ADHD are also considered a sign of conduct disorder and there might be a difference in attitude to diagnosing. If the peadiatric psychiatrist diagnose a child with ADHD he accepts at the same time that the cause is primarily genetically causing biological dysfunctions in the brain and therefore the treatment is primarily medical. If instead the psychiatrist believes that the childs problems are mainly environmental he would think that the child is suffering from behavioral problems such as conduct disorder. We hypothesised that the incidence proportion of conduct disorders may be higher in municipalities with a lower ADHD incidence proportion reflecting the difference in the professional’s beliefs and decision-making. The distribution of the incidence proportions of the ICD-10 hospital diagnoses F.91 conduct disorders and F.92 mixed disorders of conduct and emotions served as a proxy for diagnostic culture.A non-spatial logistic regression analysis was initially performed to examine the associations between incidence proportions of children with diagnosis, medication use without a registered hospital diagnosis and overall ADHD and resources. The number of children with a diagnosis, medication use without a registered diagnosis and overall ADHD (both diagnosis and/or medication) were analysed separately. The number of children with diagnosis, medication use and ADHD, respectively, were outcomes. Absence of a hospital or paediatric psychiatrist in the municipality , household income, average municipal spending on primary health care for children and incidence proportion of conduct disorders (100 × (count F91 + count F92/N)) were included as fixed effects (explanatory variables). Pearson correlation analysis was performed to check multicolinearity of the explanatory variables. The assumption about linearity between each outcome and the explanatory variables of average yearly total household income, average municipal spending on primary health care for children and proportion of children with a conduct disorder diagnosis was evaluated by categorising the explanatory variables and examining if the estimates of the categorised variable indicated linearity. The explanatory variables were categorised in three and four groups, respectively. Furthermore, linearity was evaluated by including the explanatory variable as a continuous variable as linear and quadratic terms in the analysis. If the quadratic term was significant it indicated that the assumption about linearity was not confirmed. The assumption about linearity for the three outcomes was not confirmed and the three explanatory variables were each categorised into three equally sized groups .i = 1,…, n, and n = 98.The logistic regression model used was:i = low, medium, high.j = low, medium, high.k = low, medium, high.l = yes, no.Significance of explanatory variables was evaluated using a likelihood ratio test. Model fit was evaluated using Pearson dispersion parameter. Adjustment for over-dispersion was performed based on Pearson goodness-of-fit statistics. Overdispersion is the presence of greater variability in a data set than would be expected based on the statistical model.The logistic regression analyses were performed in Statistical Analysis Software package .jkth element is 1 if the municipalities j and k are sharing a common border, otherwise 0.Areal data typically exhibit spatial autocorrelation with observations from areal units close together tending to have similar values. A proportion of this spatial autocorrelation may be modelled by including known covariate risk factors in a regression model. It is, however, common for spatial structure to remain in the residuals after accounting for these covariate effects. This residual spatial autocorrelation can be induced by a number of factors, and violates the assumption of independence common in many regression models. Bayesian modelling produces parameter estimates for each individual analysis unit by borrowing information from all other analysis units . A BayesThe Bayesian CAR model used was:i = 1,…, n, and n = 98.2)) was specified for parameters of the explanatory variables.A weakly informative independent Gaussian prior  and 0 otherwise.The variance parameter Inference (parameter estimation) for this model was based on Markov chain Monte-Carlo (MCMC) simulation, using a combination of Gibbs sampling and Metropolis steps. A single chain was applied. Each model was estimated with 100,000 iterations for burn-in and 1,000,000 iterations with thinning = 100.Significance was assessed as non-zero parameter estimates using 95 % credible intervals.Residuals of the final model for each outcome were mapped to evaluate how well the models performed. Convergence was evaluated by plotting the samples of selected parameters. The spatial regression analyses were performed in R using the CARBayes package (R version 3.1.2).


Pharmacotherapy is an effective therapeutic option for attention deficit hyperactivity disorder (ADHD). Understanding the patterns of medication treatment is crucial for clinical practice. This study employed nationwide population-based data to elucidate the initiation and persistence of pharmacotherapy  for youths with ADHD in Taiwan.Patients first receiving an ADHD diagnosis at age 18 or younger between January 2000 and December 2009  were selected from Taiwan’s National Health Insurance database. All patients were monitored through December 31, 2011, with an average follow-up time of 5.8 years. The initiation of ADHD drug therapy was defined as the first patient prescription, and discontinuation was defined as the cessation of ADHD medication for 180 days or longer.Within the first year after ADHD diagnosis, 47.3%, 14.4%, and 0.8% of the patients were prescribed IR–MPH, OROS–MPH, and ATX, respectively. Regarding the patients prescribed IR–MPH, OROS–MPH, and ATX, 17.8%, 12.6%, and 18.8%, respectively, received the prescription only once and never returned for a drug refill, and 51.0%, 38.9%, and 58.8%, respectively, discontinued drug therapy within 1 year after the first prescription. Male sex and neuropsychiatric comorbidities were associated with higher probabilities of being prescribed one of the medications. An older age at first prescription and a higher daily dose of prescription were significant predictors of early discontinuation of ADHD medication.The current findings suggest that IR–MPH is the most frequently prescribed drug for ADHD treatment in Taiwan. Patients treated with OROS–MPH possessed the highest persistence rate, whereas those treated with ATX had the lowest persistence rate. The results provide insight into the delivery of pediatric mental health services and have crucial implications for ADHD medication treatment in real clinical settings. Attention deficit hyperactivity disorder (ADHD) is a common neurodevelopmental disorder that begins in childhood . It affeAlthough compelling evidence has demonstrated the effectiveness of ADHD pharmacotherapy , public ADHD medications in routine clinical care are effective only when drug therapy is administered to the patient persistently. Premature discontinuation of ADHD medication may result in inadequate treatment responses and negative long-term outcomes , 24. A pPrior to 2011 in Taiwan, immediate-release methylphenidate (IR–MPH), osmotic controlled-release formulation of methylphenidate (OROS–MPH), and atomoxetine (ATX) were the only three drugs approved for ADHD treatment . IR–MPH Therefore, this study employed nationwide population-based data to elucidate the prescription patterns (initiation and persistence) of pharmacotherapy  for youths with ADHD in Taiwan, and investigated the factors associated with these patterns.The protocol for this study conformed to the Helsinki Declaration, and was approved by the Institutional Review Board (IRB) of Chang Gung Memorial Hospital. Patient records/information was anonymized and de-identified prior to analysis, and the need for written informed consent was waived by the IRB.Data for this study were obtained from the ambulatory claims database of the National Health Insurance Research Database (NHIRD). Implemented in 1995, Taiwan’s National Health Insurance (NHI) program is a compulsory universal health insurance program. The Bureau of National Health Insurance is the single payer for healthcare services under the NHI, and has contracted 93% of all healthcare providers in Taiwan. More than 96% of insured people have used healthcare services at least once in contracted hospitals and clinics since 1995. Contracted medical care institutions must submit monthly medical expense-related claim documents electronically, comprising patient demographic data, medical institutions visited, diagnostic codes, dates of prescriptions, drugs prescribed, and claimed medical expenses. Validation studies have demonstrated that the coding in the NHIRD system is a valid resource for population research .We included all patients with records in the NHIRD who were aged 18 years or less and newly diagnosed with ADHD between January 2000 and December 2009. To reduce the possibility of misdiagnosis, an ADHD patient was defined as a patient having at least two NHI claim records in accordance with International Classification of Diseases, Ninth Revision, Clinical Modification (ICD-9-CM) code 314.00 (attention deficit disorder without mention of hyperactivity) or 314.01 (attention deficit disorder with hyperactivity). Finally, our study sample comprised 112,140 patients with ADHD. Patient NHIRD medical records were followed up through December 31, 2011; thus, patients had a follow-up period ranging from 2 to 12 years (mean duration: 5.8 ± 2.7 years).The following relevant neurodevelopmental disorders that are commonly comorbid with ADHD were examined in this study and grouped as follows: oppositional defiant disorder (ODD) or conduct disorder (CD) (ICD-9-CM code 313.81 or 312.X), autistic spectrum disorder (ASD) (ICD-9-CM code 299.X), tic disorder (ICD-9-CM code 307.2X), and intellectual disability (ICD-9-CM codes 317–319), anxiety disorders (ICD-9-CM codes 300.X) and depressive disorders .Pharmacotherapies for ADHD were identified using the anatomical therapeutic chemical classification system. According to the Food and Drug Administration of Taiwan, only three drugs were licensed for treating ADHD before 2011: IR–MPH (ATC code N06BA04), OROS–MPH (ATC code N06BA04), and ATX (ATC code N06BA09). IR–MPH entered the market in Taiwan on March 1, 1995; OROS–MPH entered the market on September 1, 2004; and ATX entered the market on May 1, 2007. Any prescription of IR–MPH, OROS–MPH, or ATX was recorded using an ambulatory care claim, pharmacy claim, or hospital care claim.The initiation of ADHD drug therapy was defined as first patient prescription of IR–MPH, OROS–MPH, or ATX. We defined the index date as the date that the ADHD medication was first prescribed, and patient NHIRD medical records were followed up through December 31, 2011 or until discontinuation of medication treatment. The discontinuation of ADHD medication was defined as cessation of IR–MPH, OROS–MPH, or ATX for 180 days or longer. We defined the discontinuation date as the date of the last prescription administered before drug cessation. The total follow-up duration was defined as the duration between the index date and the discontinuation date or December 31, 2011. The average daily doses of ADHD medications were calculated based on the defined daily dose suggested by the WHO Collaborating Centre for Drug Statistics Methodology .P value of < 0.05 indicated statistical significance. A chi-squared (χ2) test or t test was applied to compare the characteristics of the ADHD patients who were prescribed ADHD medications and those who were not.All statistical analyses were performed using the Statistical Package for Social Sciences (SPSS) Version 21.0 . Variables were expressed as mean (standard deviation), median (range), or frequency values. A two-tailed We employed a multivariate logistic regression model to estimate the potential factors associated with drug therapy initiation, adjusted for the year of ADHD diagnosis. The factors associated with treatment with IR–MPH, OROS–MPH, and ATX were analyzed separately. The adjusted odds ratios and 95% confidence intervals (CI) were calculated. Survival curves were employed to express the probability of initiating ADHD drug therapy over time.In addition, Cox regression models  were fitTable 1), the patients who received drug therapy were older (mean age at ADHD diagnosis: 8.3 ± 3.0 years), had a higher proportion of males (81.7%), and were more likely to have an ODD/CD (12.0%), tic disorder (6.8%), intellectual disability (15.1%) or anxiety disorder (31.8%) comorbidity. Of all the patients, 61.6%, 32.0%, and 4.7% were prescribed at least one dose of IR–MPH, OROS–MPH, and ATX during the study period, respectively.Of the 112,140 youths  included in this study, 63.9% were prescribed ADHD medication  at least once during the study period. Furthermore, 35.9%, 46.0%, 49.1%, and 54.0% of ADHD youths received treatment of any of the three drugs within 30 days, 180 days, 1 year, and 2 years of their ADHD diagnosis, respectively. Compared with the unmedicated ADHD patients , the age at first prescription was 9.0 ± 2.8, 10.3 ± 2.7, and 10.9 ± 2.9 years, respectively; the mean time from ADHD diagnosis to drug prescription was 286.5 ± 549.7, 760.3 ± 800.6, and 1289.7 ± 919.7 days, respectively. The proportions of users of a particular drug receiving corresponding prescriptions within 30 days, 180 days, 1 year, and 2 years after ADHD diagnosis were as follows: 55.6%, 71.7%, 76.8%, and 84.7% were prescribed IR–MPH; 15.4%, 35.1%, 44.9%, and 59.3% were prescribed OROS–MPH; and 4.2%, 10.5%, 17.5%, and 32.0% were prescribed ATX.For patients who were prescribed IR–MPH, OROS–MPH, or ATX (Table 3), male sex and comorbidity with ODD/CD, ASD, tic disorder, intellectual disability, or an anxiety disorder were collectively associated with a higher probability of being prescribed IR–MPH, OROS–MPH, or ATX. However, comorbidity with a depressive disorder was associated with a lower probability of being prescribed IR–MPH or OROS–MPH, but was associated with a higher probability of being prescribed ATX. Older age at ADHD diagnosis was associated with a higher probability of being prescribed IR–MPH or OROS–MPH; however, prescription of ATX was associated with younger age at ADHD diagnosis.Regarding the factors associated with initiation of ADHD drug therapy , 17.8%, 12.6%, and 18.8%, respectively, received prescriptions only once and never returned for drug refill; 57.8%, 70.3%, and 52.3%, respectively, remained in drug treatment 6 months after first prescription; 49.0%, 61.1%, and 41.2%, respectively, remained in treatment 1 year after first prescription; and 38.4%, 49.8%, and 33.4%, respectively, remained in treatment 2 years after first prescription. Among the patients who discontinued their treatment with IR–MPH, OROS–MPH, and ATX, the age at discontinuation was 10.6 ± 3.1 years, 12.0 ± 3.0 years, and 11.4 ± 2.9 years, respectively; the mean time between drug therapy initiation to discontinuation was 539.3 ± 714.9 days, 444.2 ± 507.7 days, and 150.7 ± 176.6 days, respectively.Table 4), female sex, older age at first prescription and higher daily dose of IR-MPH significantly predicted IR–MPH early discontinuation; whereas comorbidity for ODD/CD, ASD, tic disorder, intellectual disability, anxiety disorder, or an depressive disorder was correlated with continued IR–MPH treatment. Among the patients prescribed OROS–MPH, female sex, older age at first prescription, comorbidity with intellectual disability, and higher dose of OROS-MPH significantly predicted early discontinuation, and having ODD/CD, anxiety disorder, or a depressive disorder was correlated with persistence in drug treatment. For ATX users, older age at first prescription, depressive disorder and higher dose of ATX significantly predicted early discontinuation, and having ASD, tic disorder, intellectual disability, or an anxiety disorder was correlated with persistence in drug treatment.Among the patients who were prescribed IR–MPH  was not provided in the claims data. Therefore, we could not determine whether or how the aforementioned factors affected ADHD pharmacotherapy. Second, the three medications entered the market in Taiwan at various times: IR–MPH on March 1, 1995; OROS–MPH on September 1, 2004; and ATX on May 1, 2007. Therefore, the patients who discontinued IR–MPH treatment before 2004 did not have the opportunity switch to OROS–MPH or ATX. Moreover, a direct comparison of discontinuation factors for MPH and ATX may be unequal. Third, the study employed reimbursement data, and the diagnoses of ADHD were not validated using structural diagnostic instruments; they were identified on the basis of only ICD codes. In addition, the treatment gap  and combination therapy were not analyzed in this study . FurtherThis nationwide study revealed that IR–MPH was the most frequently prescribed drug for treating ADHD in Taiwan between January 2000 and December 2009. Drug therapy persistence was highest among OROS–MPH-treated patients and lowest among ATX-treated patients. Male sex and neuropsychiatric comorbidities were associated with being prescribed one of the medications. Older age at first prescription and higher doses of prescribed medications significantly predicted early discontinuation of drug therapy. The results provide insight into the delivery of pediatric mental health services and have crucial implications for ADHD medication treatment in real clinical settings. The underlying reasons and clinical outcomes associated with initiation and persistence of ADHD medication treatment warrant further investigation.


Attention is one of the key factors in both hypnotic processes and patients with ADHD. In addition, the brain areas associated with hypnosis and ADHD overlap in many respects. However, the use of hypnosis in ADHD patients has still received only minor attention in research. The main purpose of the present work was to investigate whether hypnosis and hypnotic suggestions influence the performance of adult ADHD (n = 27) and control participants (n = 31) in the continuous performance test (CPT). The hypnotic susceptibility of the participants was measured by the Harvard Group Scale of Hypnotic Susceptibility (HGSHS:A) and the attentional task was a three minute long auditory version of the CPT. The CPT task was administered four times: before hypnosis (CPT1), after a hypnotic induction (CPT2), after suggestions about speed and accuracy (CPT3), and after the termination of hypnosis (CPT4). The susceptibility of the groups measured by HGSHS:A did not differ. There was a statistically significant decrease in reaction times in both ADHD and control groups between CPT2 and CPT3. The differences between CPT1 and CPT2, even though non-significant, were different in the two groups: in the ADHD group reaction times decreased whereas in the control group they increased. Both groups made very few errors in the short CPT. This study indicates that hypnotic suggestions have an effect on reaction times in the sustained attention task both in adult ADHD patients and control subjects. The theoretical and clinical implications are discussed. Attention deficit hyperactivity disorder (ADHD) is a developmental neurobiological disability characterized by deficits in attention and executive functions and/or symptoms of hyperactivity and impulsivity . It emerAdult ADHD typically manifests as deficits in organizing, prioritizing, and activating oneself to work; focusing, sustaining, and shifting attention to tasks; regulating alertness, sustaining effort, and processing speed; managing frustration and modulating emotions; utilizing working memory and accessing recall; and/or monitoring and self-regulating action . Some, bHypnosis can be defined in the following way: “Operationally, hypnosis refers to a change in baseline mental activity after an induction procedure and typically experienced at a subjective level as an increase in absorption, focused attention, disattention to extraneous stimuli and a reduction in spontaneous thought” . AlthougAttention is a key factor in hypnotic processes ,20. The When a relevant event occurs at a relatively slow rate over a prolonged period there is a need for sustaining attention. The most commonly used tests in both clinical practice and research to study sustained attention are continuous performance tests (CPTs). CPTs are considered to be reliable and sensitive measures of attention and attentional system dysfunction ,30. TherIn the Kallio et al study  several The aim of this study was to test the influence of hypnosis, hypnotizability, and hypnotic suggestions on the performance of ADHD and control participants in the CPT. Attention is a common key factor in both hypnosis and ADHD and, furthermore, there is clear overlap of the significant brain areas  and alterations in functional networks . On the basis of previous studies we hypothesize that in controls the reaction times will be slower after induction  and faster after hypnotic suggestions. No predictions are made about between group differences (controls vs ADHD) due to the lack of previous studies.Participants were recruited through advertisement in an ADHD magazine, in an adult ADHD internet discussion forum and by informing local physicians and clinics specialized in treating ADHD in adults. The control participants were recruited as above and from an e-mail list of psychology students. The inclusion criteria were as follows: (1) 18–45 years of age, (2) no diagnosis of psychosis or bipolar disorder, and (3) no current severe depression. Those for the ADHD group should also have ADHD diagnosis made by a physician and those for control group should not have an ADHD diagnosis or ADHD symptoms.In total, 53 potential participants for the ADHD group and 36 for the control group contacted the researchers. Of the ADHD candidates, nine individuals were excluded for not meeting all the inclusion criteria, and 16 cancelled or discontinued participation. One participant did not respond behaviorally to given hypnotic suggestions in HGSHS:A and was excluded from the analysis. Of the control group, one candidate was excluded because she/he reported ADHD symptoms and three cancelled participation. We also excluded one participant from the analysis due to missing information in the CPT . Thus, there were a total of 27 participants in the ADHD group and 31 in the control group.χ2 (1) = 1.47, p = 0.25]. They differed, as analyzed by t-test or Chi-Square test/Fisher exact test in age , in education , in ASRS score , in SCL-90 sum score  and in number of participants having psychiatric comorbidity .Demographic data of the two groups are presented in The ADHD participants were requested—if possible—to be without ADHD medication during test sessions. 10 did not have any ADHD medication and 17 were medicated. Six of the medicated were unmedicated in both sessions. From the 11 medicated participants, seven of them took during first session methylphenidate, two took dextroamphetamine, one bupropioni and one methylphenidate and bupropioni. In the second session there were changes in two of them: one had ceased taking methylphenidate medication and one had changed methylphenidate to dextroamphetamine and bupropioni.The study was approved by the Ethics Committee of the Helsinki University Central Hospital, Finland, and performed in accordance with the ethical standards laid down in the 1964 Declaration of Helsinki. All participants gave their written informed consent prior to participating in the study.Questionnaire of background information. In this questionnaire participants reported detailed information about education, work, health and medication.World Health Organization's Adult ADHD Self-report Scale (ASRS) . To investigate whether the reaction times in the ADHD and control groups differed across test conditions, a 2x4 rmANOVA was carried out. The test showed that there was a significant test condition × group interaction in mean reaction times . The result implies that the reaction time profiles across test conditions were different in the two groups  = 0.49, p = 1.00, d = 0.09], which they did between test conditions CPT2 and CPT3 . The comparison between CPT1 and CPT3 resulted in a Bonferroni corrected p-value that approached statistical significance . However, the effect size was moderate, with the mean reaction times differing by half a standard deviation. It is of interest to note that the difference CPT2-CPT3 was statistically significant, whereas the difference CPT1-CPT3 was only nearly so. This was due to subjects reacting differently to being exposed to conditions CPT2 and CPT3. When comparing CPT3 with the baseline measurement CPT1, the reaction times of eight participants increased and those of the others decreased. When comparing CPT3 with CPT2, there was less variation in the pattern of differences, with less increase in reaction times from CPT2 to CPT3. This resulted in greater variance in the difference scores in the comparison CPT1-CPT3, reflected in the greater p-value and the slightly smaller effect size than in the comparison CPT2-CPT3.These reaction time patterns were investigated in further detail using paired samples t-tests separately in the ADHD and the control group. CPT1 was compared with CPT2, CPT3 and CPT4, and CPT2 with CPT3. In the ADHD group, the mean reaction times did not differ between test conditions CPT1 and CPT2 , whereas a statistically significant difference was noted between test conditions CPT1 and CPT3  and CPT2 and CPT3 . In both groups, the statistically significant difference between conditions CPT2 and CPT3 indicates that the hypnotic suggestions resulted in faster reaction times, over and above the effect of hypnotic induction.In the control group, the mean reaction times did not differ between test conditions CPT1 and CPT2  but was significant in the control group . The gain score analysis showed that the difference of CPT1-CPT4 was not statistically significantly different across groups .We also compared the two non-hypnotic conditions, that is, before induction and after termination of hypnosis. The difference between CPT1 and CPT4 was not significant in the ADHD group , with a regression coefficient of b = -1.39 . The result reflects the fact that, as a group, the ADHD subjects committed 14 errors and the control subjects 4 errors in the CPT. As can be seen from Looking at CPT2 (hypnotic induction), the likelihood ratio test approached statistical significance , with a regression coefficient of b = -2.15 . A subject belonging to the control group was thus expected to commit, on average, roughly only one ninth (e-2.15 = 0.12) of the errors of a subject belonging to the ADHD group.In CPT3 (hypnotic suggestion), the likelihood ratio test produced a significant result . However, there was a trend towards that HSIs improved their mean reaction times more (improvement: 88.9 ms (12.9%), sd: 96.6 ms) than LSIs (improvement: 19.3 ms (2.9%), sd: 76.7 ms). Note here, that the sample size of LSI group was quite small. Second, the suggestibility was treated as a continuous variable (HGSHS:A 0–12) and its correlation with reaction time improvement with the suggestions was calculated. Pearson’s correlation r was 0.23 between hypnotic suggestibility and mean reaction time improvement between conditions CPT2 and CPT3. The correlation coefficient was not statistically significant (p = 0.088). In the ADHD group, Pearson’s correlation r was 0.16 (p = 0.43) and in the control group Pearson’s correlation r was 0.39 (p = 0.03). Because of the small number of the errors, we did not analyze the effect of hypnotizability on the number of errors.To investigate the influence of hypnotizability on the reaction time decrease due to hypnotic suggestions, all participants were first divided into low, LSI,  and high, HSI,  suggestibility groups. The difference of the mean reaction times between CPT2 and CPT3 conditions by LSIs and HSIs did not differ statistically [The main purpose of this study was to investigate whether hypnosis and hypnotic suggestions influence the performance of ADHD and control participants in the continuous performance task and whether the effect is different in the two groups. There was a decrease in reaction times in both groups between neutral hypnosis and hypnosis with suggestion conditions. The performance profiles of the two groups, however, differed.There was a statistically significant decrease in reaction times in both the ADHD and control groups from CPT2  to CPT3 (after suggestions) indicating an influence of hypnotic suggestions on reaction times in the attention task. The difference between CPT1 (before hypnosis) and CPT3 was statistically significant in the control group and almost significant with moderate effect size in ADHD group. There are no previous studies about the influence of hypnotic suggestion on CPT.The results are, however, in line with previous studies with other kinds of attentional tasks. The reduction or elimination of Stroop effect after posthypnotic suggestions has been shown in several studies –24. AlsoIn these tasks, there are different kinds of conflict conditions, and suggestions shift the automatic processes to being under control. There is also preliminary data that more controlled processes, like motion perception and visual search, can be shifted to be more automatic with posthypnotic suggestions . All of In the baseline measurement, the reaction times of the control group and ADHD group did not differ. This is in line with most of the previous studies ,35,36, aThere was a statistically significant group × test condition interaction indicating different performance patterns across the groups. Thus, the reaction time profiles across CPT measurements were different in the two groups. In the ADHD group, mean reaction times were the longest in CPT1, followed by decrease in reaction times in both CPT2 and CPT3. In the control group, mean reaction times were the longest in CPT2, followed by a substantial reduction in reaction times in condition CPT3. Although the changes in reaction times from CPT1 to CPT2 were not statistically significant separately in either of the groups, there was a tendency for the reaction times in the control group to increase and for those in the ADHD group to decrease slightly. Thus, we found only suggestive, not statistical, support for our hypothesis about slowing of control participants which has been found in a previous study . The tenThe influence of suggestions on reaction times was slightly weaker in ADHD group (reduction from CPT2 to CPT3 7.5%) than in controls (16.2%). When compared to the baseline, the difference between the groups was smaller . Thus it seems that there is no great difference between the groups but it is possible that the influence of suggestions on reaction times is slightly greater in controls. However, marked individual differences exist, especially in the ADHD group.The comparison of conditions CPT1 and CPT3 revealed that after applying the conservative Bonferroni correction their difference was statistically significant in the control group but not in the ADHD group. However, the difference bordered on statistical significance also in the ADHD group and the effect size of the comparison was moderate. This finding can be interpreted as showing that, perhaps partly due to the smallish sample sizes, it remains a possibility that the difference was due to random variation in the ADHD group. Still, taking into account the moderate effect size, it seems at least equally plausible to consider the effect as genuine also in the ADHD group.When examining the profiles in the There was a difference between the non-hypnotic conditions CPT1 and CPT4 in the control group but no difference in the ADHD group. However the difference was not statistically significantly different across groups. It is possible that some posthypnotic inertia may occur –48 and aThere was no statistical difference in the number of errors in the baseline CPT task (CPT1) between the ADHD and control groups. In previous studies adults with ADHD have made more errors than controls ,32–36. TIn the ADHD group there was an increase in error rate after induction, but in other conditions the number of errors remained approximately the same . In the control group the error rate was very low in all conditions . According to the statistical analysis, the ADHD participants made more errors than the controls in the CPT3 condition, but the differences in the number of errors were very small, making it difficult to draw definite conclusions. There are no previous studies about the effects of suggestions with similar tasks but the results obtained here are in line with studies with other kind of attentional tasks, e.g. Flanker task  or SimonThe mean susceptibility measured with HGSHS:A was in both groups  in the same range as in Finnish norms , even tIn the current study, the effect of hypnotic suggestions on reaction times compared to neutral hypnosis did not statistically differ between LSIs and HSIs. Further, there were no significant correlations between reaction time improvements in all participants. However, there was a trend for the HSIs to improve more than the LSIs, and in the control group there was also a moderate correlation between hypnotizability and improvement of reaction times. In the studies with other kind of attentional tasks, the reduction of Stroop effect –24, FlanOur study has some limitations that should be considered when interpreting the results. Our version of the CPT took only three minutes, compared with a more usual situation when it might last for 10–30 minutes. We chose a short version of the task to avoid prolonging the hypnosis sessions unnecessarily. However, this may have resulted in fewer errors in the groups as mentioned earlier. Also, the other properties of the CPT task  might have an influence on the subjects’ performance. It is also possible for some kind of a learning effect to occur in this kind of task. However, the profiles see  do not sAnother methodological compromise was the lack of counterbalancing between different conditions as well as not including a non-hypnotic condition in our study. This decision was made due to several reasons. There is evidence that in addition to hypnotic suggestions, also non-hypnotic suggestions reduce the Stroop effect . The revIn this study, hypnotizability was measured once by using HGSHS:A. An individual assessment in addition to a group variant would have clearly given a better estimate of the participants’ hypnotizability. However, the use of the previously popular Stanford Hypnotic Susceptibility Scale, Form C (SHSS:C)  includesIt is also possible to explain the result by referring to demand characteristics produced by the hypnotic induction and suggestions. We tried to reduce this risk by measuring reaction times, since it is difficult to modulate them, at least intentionally, in tasks that require fast responding to a challenging attentional task.Oakley and Halligan  have sugThese previous studies were not directly targeted to the core cognitive symptoms of ADHD, such as problems of attention or working memory. In this study, we did not find any effects of hypnotic suggestions on the attention errors, probably because of the short attentional task. We, however, did find that hypnotic suggestions influenced the reaction times in a sustained attention task, so it seems that it is possible to influence the cognitive performance of ADHD patients by hypnotic suggestions. Despite the limitations of this study and the caution that must be exercised when interpreting the results, it is worthwhile in further research to study more the possibilities of hypnosis and hypnotherapy on the attention deficit and other core deficits of ADHD patients.This study indicates that hypnotic suggestions have an influence on the reaction times in a sustained attention task. This effect was found in both adults with ADHD and normal control participants. However, this result has to be verified in further studies also with non-hypnotic suggestions. This study, together with the pilot study of hypnotherapy in adults with ADHD ,60, sugg