Using Clinical Data to Predict Accurate ADHD Diagnoses Among Urban Children

Hyperactivity in ADHD: Friend or Foe?

BACKGROUND

Hyperactivity may play a functional role in upregulating prefrontal cortical hypoarousal and executive functioning in ADHD. This study investigated the neurocognitive impact of movement during executive functioning on children with ADHD.

METHODS

Twenty-four children with and without ADHD completed a Stroop task and self-efficacy ratings while remaining stationary (Stationary condition) and while desk cycling (Movement condition). Simultaneous functional near-infrared spectroscopy (fNIRS) recorded oxygenated and deoxygenated changes in hemoglobin within the left dorsolateral prefrontal cortex (DLPFC).

RESULTS

Among children with ADHD, the Movement condition produced superior Stroop reaction time compared to the Stationary condition (p = 0.046, d = 1.00). Self-efficacy improved in the Movement condition (p = 0.033, d = 0.41), whereas it did not in the Stationary condition (p = 0.323). Seventy-eight percent of participants showed greater oxygenation in the left DLPFC during the Movement condition vs. the Stationary condition. Among children without ADHD, there were no differences in Stroop or self-efficacy outcomes between Stationary and Movement conditions (ps > 0.085, ts < 1.45); 60% of participants showed greater oxygenation in the left DLPFC during the Movement vs. the Stationary condition.

CONCLUSIONS

This work provides supportive evidence that hyperactivity in ADHD may be a compensatory mechanism to upregulate PFC hypoarousal to support executive functioning and self-efficacy.

Individualized prediction models in ADHD: a systematic review and meta-regression

There have been increasing efforts to develop prediction models supporting personalised detection, prediction, or treatment of ADHD. We overviewed the current status of prediction science in ADHD by: (1) systematically reviewing and appraising available prediction models; (2) quantitatively assessing factors impacting the performance of published models. We did a PRISMA/CHARMS/TRIPOD-compliant systematic review (PROSPERO: CRD42023387502), searching, until 20/12/2023, studies reporting internally and/or externally validated diagnostic/prognostic/treatment-response prediction models in ADHD. Using meta-regressions, we explored the impact of factors affecting the area under the curve (AUC) of the models. We assessed the study risk of bias with the Prediction Model Risk of Bias Assessment Tool (PROBAST). From 7764 identified records, 100 prediction models were included (88% diagnostic, 5% prognostic, and 7% treatment-response). Of these, 96% and 7% were internally and externally validated, respectively. None was implemented in clinical practice. Only 8% of the models were deemed at low risk of bias; 67% were considered at high risk of bias. Clinical, neuroimaging, and cognitive predictors were used in 35%, 31%, and 27% of the studies, respectively. The performance of ADHD prediction models was increased in those models including, compared to those models not including, clinical predictors (β = 6.54, p = 0.007). Type of validation, age range, type of model, number of predictors, study quality, and other type of predictors did not alter the AUC. Several prediction models have been developed to support the diagnosis of ADHD. However, efforts to predict outcomes or treatment response have been limited, and none of the available models is ready for implementation into clinical practice. The use of clinical predictors, which may be combined with other type of predictors, seems to improve the performance of the models. A new generation of research should address these gaps by conducting high quality, replicable, and externally validated models, followed by implementation research.

A Nomogram for Predicting ADHD and ASD in Child and Adolescent Mental Health Services (CAMHS)

Objectives: To enhance the early detection of Attention Deficit/Hyperactivity Disorder (ADHD) and Autism Spectrum Disorder (ASD) by leveraging clinical variables collected at child and adolescent mental health services (CAMHS). Methods: This study included children diagnosed with ADHD and/or ASD (n = 857). Three logistic regression models were developed to predict the presence of ADHD, its subtypes, and ASD. The analysis began with univariate logistic regression, followed by a multicollinearity diagnostic. A backward logistic regression selection strategy was then employed to retain variables with p < 0.05. Ethical approval was obtained from the local ethics committee. The models' internal validity was evaluated based on their calibration and discriminative abilities. Results: The study produced models that are well-calibrated and validated for predicting ADHD (incorporating variables such as physical activity, history of bone fractures, and admissions to pediatric/psychiatric services) and ASD (including disability, gender, special education needs, and Axis V diagnoses, among others). Conclusions: Clinical variables can play a significant role in enhancing the early identification of ADHD and ASD.

Psychometric Properties of the Czech Version of the Vanderbilt ADHD Diagnostic Parent Rating Scale

This study examined the psychometric properties of the Czech translation of the Vanderbilt ADHD Diagnostic Parent Rating Scale (VADPRS), a tool used to assess ADHD symptoms. Data was collected online from parents of school-aged children and included questions related to their child's diagnosis or treatment. The results showed that while relying on professional judgment improved specificity and positive predictive value, it decreased negative predictive value. These findings indicate that the VADPRS scale is more accurate in identifying individuals with ADHD when professionals provide the diagnosis, but fewer true negatives are found. This is the first study attempting to describe the psychometric properties of this tool in the Czech Republic and assess its use as an additional tool for ADHD diagnosis. It is recommended that structured clinical interviews be used to increase the accuracy of ADHD diagnosis.

Effect of a parent agreement on return rates of Vanderbilt assessments and treatment adherence in pediatric attention-deficit/hyperactivity disorder patients

Objective

We implemented a parent–teacher Vanderbilt agreement program to increase return rates of Vanderbilt assessment scales for children in our primary care practice, and compared the assessment return rate before and after agreement signature.

Methods

We retrospectively reviewed children diagnosed with attention-deficit/hyperactivity disorder (ADHD) who had a signed Vanderbilt agreement and were under continuous care at our clinic. Return rates were compared 1 year before and 1 year after the agreement date.

Results

Among 195 children, prior to the agreement, 71% returned teacher assessments, and 59% returned parent forms; after the intervention, assessment rates were not significantly different (76%, p = .255; and 65%, p = .185, respectively). The median number of returned assessments increased after the agreement.

Conclusions

Lack of documented parent and teacher Vanderbilt assessments remain a barrier to appropriate management of ADHD. Improving the rate of assessments returned is an important outcome for treating ADHD in the primary care setting.