A Teleneuropsychology Consultation Service Model for Children with Neurodevelopmental and Acquired Disorders Residing in Rural State Regions

Use of Machine Learning Models to Differentiate Neurodevelopment Conditions Through Digitally Collected Data: Cross-Sectional Questionnaire Study

BACKGROUND

Diagnosis of child and adolescent psychopathologies involves a multifaceted approach, integrating clinical observations, behavioral assessments, medical history, cognitive testing, and familial context information. Digital technologies, especially internet-based platforms for administering caregiver-rated questionnaires, are increasingly used in this field, particularly during the screening phase. The ascent of digital platforms for data collection has propelled advanced psychopathology classification methods such as supervised machine learning (ML) into the forefront of both research and clinical environments. This shift, recently called psycho-informatics, has been facilitated by gradually incorporating computational devices into clinical workflows. However, an actual integration between telemedicine and the ML approach has yet to be fulfilled.

OBJECTIVE

Under these premises, exploring the potential of ML applications for analyzing digitally collected data may have significant implications for supporting the clinical practice of diagnosing early psychopathology. The purpose of this study was, therefore, to exploit ML models for the classification of attention-deficit/hyperactivity disorder (ADHD) and autism spectrum disorder (ASD) using internet-based parent-reported socio-anamnestic data, aiming at obtaining accurate predictive models for new help-seeking families.

METHODS

In this retrospective, single-center observational study, socio-anamnestic data were collected from 1688 children and adolescents referred for suspected neurodevelopmental conditions. The data included sociodemographic, clinical, environmental, and developmental factors, collected remotely through the first Italian internet-based screening tool for neurodevelopmental disorders, the Medea Information and Clinical Assessment On-Line (MedicalBIT). Random forest (RF), decision tree, and logistic regression models were developed and evaluated using classification accuracy, sensitivity, specificity, and importance of independent variables.

RESULTS

The RF model demonstrated robust accuracy, achieving 84% (95% CI 82-85; P<.001) for ADHD and 86% (95% CI 84-87; P<.001) for ASD classifications. Sensitivities were also high, with 93% for ADHD and 95% for ASD. In contrast, the DT and LR models exhibited lower accuracy (DT 74%, 95% CI 71-77; P<.001 for ADHD; DT 79%, 95% CI 77-82; P<.001 for ASD; LR 61%, 95% CI 57-64; P<.001 for ADHD; LR 63%, 95% CI 60-67; P<.001 for ASD) and sensitivities (DT: 82% for ADHD and 88% for ASD; LR: 62% for ADHD and 68% for ASD). The independent variables considered for classification differed in importance between the 2 models, reflecting the distinct characteristics of the 3 ML approaches.

CONCLUSIONS

This study highlights the potential of ML models, particularly RF, in enhancing the diagnostic process of child and adolescent psychopathology. Altogether, the current findings underscore the significance of leveraging digital platforms and computational techniques in the diagnostic process. While interpretability remains crucial, the developed approach might provide valuable screening tools for clinicians, highlighting the significance of embedding computational techniques in the diagnostic process.

Feasibility of Remote Administration of the Uniform Data Set-Version 3 for Assessment of Older Adults With Mild Cognitive Impairment and Alzheimer's Disease

OBJECTIVE

Assess the feasibility and concurrent validity of a modified Uniform Data Set version 3 (UDSv3) for remote administration for individuals with normal cognition (NC), mild cognitive impairment (MCI), and early dementia.

METHOD

Participants (N = 93) (age: 72.8 [8.9] years; education: 15.6 [2.5] years; 72% female; 84% White) were enrolled from the Wake Forest ADRC. Portions of the UDSv3 cognitive battery, plus the Rey Auditory Verbal Learning Test, were completed by telephone or video within ~6 months of participant's in-person visit. Adaptations for phone administration (e.g., Oral Trails for Trail Making Test [TMT] and Blind Montreal Cognitive Assessment [MoCA] for MoCA) were made. Participants reported on the pleasantness, difficulty, and preference for each modality. Staff provided validity ratings for assessments. Participants' remote data were adjudicated by cognitive experts blinded to the in person-diagnosis (NC [N = 44], MCI [N = 35], Dementia [N = 11], or other [N = 3]).

RESULTS

Remote assessments were rated as pleasant as in-person assessments by 74% of participants and equally difficult by 75%. Staff validity rating (video = 92%; phone = 87.5%) was good. Concordance between remote/in-person scores was generally moderate to good (r = .3 -.8; p < .05) except for TMT-A/OTMT-A (r = .3; p > .05). Agreement between remote/in-person adjudicated cognitive status was good (k = .61-.64).

CONCLUSIONS

We found preliminary evidence that older adults, including those with cognitive impairment, can be assessed remotely using a modified UDSv3 research battery. Adjudication of cognitive status that relies on remotely collected data is comparable to classifications using in-person assessments.

Tele-Neuropsychology: From Science to Policy to Practice

OBJECTIVE

The primary aim of this paper is to accelerate the number of randomized experimental studies of the reliability and validity in-home tele-neuropsychological testing (tele-np-t).

METHOD

We conducted a critical review of the tele-neuropsychology literature. We discuss this research in the context of the United States' public and private healthcare payer systems, including the Centers for Medicare & Medicaid Services (CMS) and Current Procedural Terminology (CPT) coding system's telehealth lists, and existing disparities in healthcare access.

RESULTS

The number of tele-np publications has been stagnant since the onset of the COVID-19 pandemic. There are less published experimental studies of tele-neuropsychology (tele-np), and particularly in-home tele-np-t, than other tele-np publications. There is strong foundational evidence of the acceptability, feasibility, and reliability of tele-np-t, but relatively few studies of the reliability and validity of in-home tele-np-t using randomization methodology.

CONCLUSIONS

More studies of the reliability and validity of in-home tele-np-t using randomization methodology are necessary to support inclusion of tele-np-t codes on the CMS and CPT telehealth lists, and subsequently, the integration and delivery of in-home tele-np-t services across providers and institutions. These actions are needed to maintain equitable reimbursement of in-home tele-np-t services and address the widespread disparities in healthcare access.

Exploring telediagnostic procedures in child neuropsychiatry: addressing ADHD diagnosis and autism symptoms through supervised machine learning

Recently, there has been an increase in telemedicine applied to child neuropsychiatry, such as the use of online platforms to collect remotely case histories and demographic and behavioral information. In the present proof-of-concept study, we aimed to understand to what extent information parents and teachers provide through online questionnaires overlaps with clinicians' diagnostic conclusions on attention-deficit/hyperactivity disorder (ADHD). Moreover, we intended to explore a possible role that autism spectrum disorders (ASD) symptoms played in this process. We examined parent- and teacher-rated questionnaires collected remotely and an on-site evaluation of intelligence quotients from 342 subjects (18% females), aged 3-16 years, and referred for suspected ADHD. An easily interpretable machine learning model-decision tree (DT)-was built to simulate the clinical process of classifying ADHD/non-ADHD based on collected data. Then, we tested the DT model's predictive accuracy through a cross-validation approach. The DT classifier's performance was compared with those that other machine learning models achieved, such as random forest and support vector machines. Differences in ASD symptoms in the DT-identified classes were tested to address their role in performing a diagnostic error using the DT model. The DT identified the decision rules clinicians adopt to classify an ADHD diagnosis with an 82% accuracy rate. Regarding the cross-validation experiment, our DT model reached a predictive accuracy of 74% that was similar to those of other classification algorithms. The caregiver-reported ADHD core symptom severity proved the most discriminative information for clinicians during the diagnostic decision process. However, ASD symptoms were a confounding factor when ADHD severity had to be established. Telehealth procedures proved effective in obtaining an automated output regarding a diagnostic risk, reducing the time delay between symptom detection and diagnosis. However, this should not be considered an alternative to on-site procedures but rather as automated support for clinical practice, enabling clinicians to allocate further resources to the most complex cases.

Comparing remote versus in-person assessment of learning skills in children with specific learning disabilities

Background

Interactive telemedicine applications have been progressively introduced in the assessment of cognitive and literacy skills. However, there is still a lack of research focusing on the validity of this methodology for the neuropsychological assessment of children with Specific Learning Disorder (SLD).

Methods

Seventy-nine children including 40 typically developing children (18 males, age 11.5 ± 1.06) and 39 children with SLD (24 males, age 12.3 ± 1.28) were recruited. Each participant underwent the same neuropsychological battery assessing reading accuracy, speed, and comprehension, writing, numerical processing, computation, and semantic numerical sense, twice (once during an in-person session (I) and once during a remote (R) home-based videoconference session). Four groups were subsequently defined based on the administration order. Repeated-measure-ANOVAs with assessment type (R vs. I testing) as within-subject factor and diagnosis (SLD vs. TR) and administration order (R-I vs. I-R) as between-subject factors, and between-group t-tests comparing the two assessment types within each time of administration, were run.

Results

No differences emerged between I and R assessments of reading accuracy and speed, numerical processing, and computation; on the contrary, potential biases against R assessment emerged when evaluating skills in writing, reading comprehension, and semantic numerical sense. However, regardless of the assessment type, the scores obtained with I and R assessments within the same administration time point overlapped.

Discussion

These results partially support the validity and reliability of the assessment of children's learning skills via a remote home-based videoconferencing system. Implementing telemedicine as an assessment tool may increase timely access to primary health care and to support research activity.

[Formula: see text] Optimizing neurodevelopmental outcomes following fetal diagnosis of congenital heart disease: a call for primary prevention neuropsychology

Critical congenital heart disease (CHD) presents a lasting threat to quality of life through its adverse impact on neurodevelopmental and psychosocial outcomes. As recognition of this threat has increased, so too has an appreciation for the role of pediatric neuropsychologists in supporting families affected by CHD. But there is more to offer these families than traditional neuropsychological services, which tend to focus on secondary/tertiary forms of prevention. Now that many children with CHD are diagnosed prenatally, it may be possible to begin mitigating CHD-related risks and promoting positive outcomes earlier than ever before. Through primary prevention-oriented fetal neuropsychological consultation, as well as close collaboration with allied specialists, pediatric neuropsychology has an opportunity to re-envision its typical borders and more familiar practice models; to forge early and enduring partnerships with families; and to help promote the best possible neurodevelopmental trajectories, beginning before children are even born. In this conceptual review, we survey and integrate evidence from developmental science, developmental origins of health and disease, maternal-fetal medicine, and cardiac neurodevelopmental literatures, along with current practice norms, arriving ultimately at two central conclusions: 1) there is an important role to fill on multidisciplinary teams for the pediatric neuropsychologist in fetal cardiac care and 2) role expansion (e.g., through valuing broader-based training, flexing more generalist skills) can likely improve neuropsychological outcomes earlier than has been standard for pediatric neuropsychologists. Such a reimagining of our practice may be considered primary prevention neuropsychology. Implications for care in various settings and pragmatic barriers to implementation are discussed.

A Systematic Review and a Latin American Clinical Model for Teleneuropsychological Assessment

OBJECTIVE

The objective of this study is to propose a TeleNP model for remote assessment and offer practical recommendations for clinical practice with patients in Mexico and Latin America, based on a systematic literature review and clinical experience.

METHOD

A systematic review of studies from 2011 to 2021 in English and Spanish used TeleNP, teleneuropsychology, telepsychology, online, assessment, teleneuropsicología, and evaluación for the search; the databases examined included PubMed, BiDi UNAM, ScienceDirect, Google Scholar, and Wiley One Library; the Oxford Centre for Evidence-Based Medicine system was used to grade the levels of evidence. The experience of the last two years of students and faculty in the Master's and Doctoral Programs in Psychology, Clinical Neuropsychology Residency Program, was also used as a basis for this guide.

RESULTS

We propose a clinical model for TeleNP assessment in Mexico and Latin America based on the review of 31 articles and the practice of professors and students of clinical neuropsychology.

CONCLUSION

The proposed model describes a procedure and adaptations for home-to-home clinical practice in the neuropsychological assessment of Mexican patients that could also be used in other Latin American countries. Its reliability remains to be assessed, but this model and the suggestions proposed could be used in future studies and clinical trials for Mexican and Latin American populations.

The Relationship between Health Literacy and Comfort with Teleneuropsychology in a Veteran Sample

OBJECTIVE

Health literacy is a strong psychosocial determinant of health disparities and has been found to relate to various aspects of health-related technology use. With the increased implementation of neuropsychological services performed via telehealth during the coronavirus disease 2019 pandemic, the relationship between health literacy and comfort with teleneuropsychology warrants further investigation.

METHOD

The present study examined 77 Veterans participating in neuropsychological evaluations as a part of standard clinical care. The sample was diverse in terms of age ethnicity, and psychiatric and neurocognitive diagnoses. In addition to a fixed-flexible neuropsychological battery, the Brief Health Literacy Screening Tool (BRIEF) was administered to evaluate health literacy. Self-reported comfort with the teleneuropsychological evaluation was assessed using an informal 10-point scale, and qualitative comfort responses were also recorded.

RESULTS

Independent samples t-tests revealed older adults were more likely to participate in the evaluation via telephone than with VA Video Connect. Although health literacy was not related to telehealth modality, it was correlated with comfort with the teleneuropsychological evaluation (r = .34, p < .01), although it is notable that average comfort levels were high across modalities (M = 8.16, SD = 2.50).

CONCLUSIONS

Findings support the notion that teleneuropsychological services may feasibly be implemented with a diverse group of patients, although flexibility with modality may be necessary. Those performing these services should also be aware that patients with lower health literacy may feel less comfortable with teleneuropsychology as they seek to build rapport and optimize evaluation engagement.

Integrating Telehealth Into Neurodevelopmental Assessment: A Model From the Cardiac Neurodevelopmental Outcome Collaborative

Objective

In the wake of the COVID-19 pandemic, psychologists were pushed to look beyond traditional in-person models of neurodevelopmental assessment to maintain continuity of care. A wealth of data demonstrates that telehealth is efficacious for pediatric behavioral intervention; however, best practices for incorporating telehealth into neurodevelopmental assessment are yet to be developed. In this topical review, we propose a conceptual model to demonstrate how telehealth can be incorporated into various components of neurodevelopmental assessment.

Methods

Harnessing existing literature and expertise from a multidisciplinary task force comprised of clinicians, researchers, and patient/parent representatives from the subspecialty of cardiac neurodevelopmental care, a conceptual framework for telehealth neurodevelopmental assessment was developed. Considerations for health equity and access to care are discussed, as well as general guidelines for clinical implementation and gaps in existing literature.

Results

There are opportunities to integrate telehealth within each stage of neurodevelopmental assessment, from intake to testing, through to follow-up care. Further research is needed to determine whether telehealth mitigates or exacerbates disparities in access to care for vulnerable populations as well as to provide evidence of validity for a wider range of neurodevelopmental measures to be administered via telehealth.

Conclusions

While many practices are returning to traditional, face-to-face neurodevelopmental assessment services, psychologists have a unique opportunity to harness the momentum for telehealth care initiated during the pandemic to optimize the use of clinical resources, broaden service delivery, and increase access to care for pediatric neurodevelopmental assessment.

Tele-assessment of cognitive functions in children: a systematic review

Cognitive Tele-Assessment approach (CTA) has been widely used in adults for clinical, research, and screening purposes. In the last decades, it has been considered a useful tool for evaluating child development in both clinical and educational settings and new instruments for CTA in children have been developed. In comparison to In Person Assessment (IPA), CTA can have several advantages, such as increasing accessibility, cutting waiting lists, reducing time and travel costs, and assisting with infection control by minimizing face-to-face contact in times of pandemic. Nevertheless, several issues related to the feasibility and reliability of using CTA to evaluate cognitive development are still open. The present systematic review has a twofold aim: 1. to describe the cognitive functions that are most frequently measured by CTA in children, the procedures used, and the characteristics of the samples investigated; 2. to investigate the agreement between CTA and IPA scores in children.In the present systematic review, 23 studies using CTA in children, with typical or atypical development, have been selected and analyzed. Results support the similarities in performance scores between IPA and CTA and good compliance by children and their families in participating in CTA. Nonetheless, most studies suggest that several methodological precautions must be taken to manage technical and procedural characteristics that may represent challenges for CTA of children. Suggestions for a correct use of CTA, factors affecting the validity of the results and directions for future research are discussed.