MétaCan
Menu
Back to cohort
Record W4390078186 · doi:10.1017/s1355617723001261

44 Finding the Onramp: Understanding Access to Neuropsychological Evaluation in New Onset Pediatric Epilepsy

2023· article· en· W4390078186 on OpenAlexaboutno aff
Thomas Tran, Sonya Swami, Elice Shin, Rebecca Slomowitz, Rosario DeLeon, Nancy L. Nussbaum, William A. Schraegle

Bibliographic record

VenueJournal of the International Neuropsychological Society · 2023
Typearticle
Languageen
FieldMedicine
TopicEpilepsy research and treatment
Canadian institutionsnot available
Fundersnot available
KeywordsEpilepsyNeuropsychologyRespondentNeuropsychological assessmentMedicineFamily medicineTelemedicinePsychologyPsychiatryClinical psychologyCognitionHealth care

Abstract

fetched live from OpenAlex

Objective: Approximately half of all children and adults newly diagnosed with epilepsy also show behavioral and/or cognitive difficulties upon evaluation. While neuropsychological screening is recommended as a routine part of care at seizure onset, in reality, access to care is often restricted by many factors. In order to better define the extent of the problem, we developed a survey to understand how frequently youth with new onset epilepsy currently undergo neuropsychological evaluation or screening and whether virtual assessment tools are used to extend access to care. Participants and Methods: We created an online survey to better understand new onset epilepsy care provided within neuropsychological practice settings in the United States and Canada. The survey was disseminated via multiple listservs (e.g., AACN listservs, APPCN, PERF neuropsychologists) and respondents included 45 neuropsychologists. Survey questions were grouped by the following domains: 1) location characteristics (e.g., urban versus rural location, type of practice, affiliation with comprehensive epilepsy center); 2) volume of new onset epilepsy patient cases (e.g., number of neuropsychologists within practice who see new onset patients, percentage of new onset cases who received neuropsychological evaluations/screeners, wait time), and 3) tele-neuropsychology procedures (e.g., use of virtual testing, frequency of virtual testing, frequency of virtual intakes/feedbacks). Results: Practice locations of the 45 respondents included academic medical center (n=34, 75.6%), community medical center (n=10, 22.2%), and private practice (n=1, 2.2%). All but one respondent practiced in an urban setting. Respondents were generally affiliated with Comprehensive Epilepsy Centers (level 3 or 4) (n=39, 86.7%). Practice settings typically included < 3 epilepsy neuropsychologists (n=29, 65.9%). Of interest, neuropsychological evaluation of new onset pediatric epilepsy patients generally ranged from 0-25% of cases (n=32, 71%; mode=11-25%). Reported barriers included: insurance, poor access to rural populations, interdisciplinary communication, departmental referral patterns, limited number of providers, and need to prioritize pre-surgical patients. In terms of access, neuropsychology waitlist times for patients with nonsurgical epilepsy ranged from <1 to 6 months (n=34, 75%) with an equal proportion of patients waiting 1-3 months (33%) and 4-6 months (33%). Telehealth was not frequently utilized in non-surgical epilepsy test administration (Do not use, n=39; 86.7%), but frequently incorporated for non-testing purposes (i.e., intakes, feedbacks) (n=40, 88.9%). Conclusions: Results of this provider survey indicate that children with new-onset epilepsy do not routinely undergo neuropsychological evaluation (< 25%). Barriers included prioritizing presurgical workups, referral patterns, access to care, and limited provider bandwidth. Clearly, there is a need to improve access to care. Possible solutions include developing more time efficient screening batteries with measures most sensitive to early cognitive and psychosocial deficits, and incorporating the use of virtual technology all in the service of improving the lives of children with epilepsy.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.013
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.086
Threshold uncertainty score0.171

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.013
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.002
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.236
GPT teacher head0.444
Teacher spread0.208 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations1
Published2023
Admission routes1
Has abstractyes

Explore more

Same venueJournal of the International Neuropsychological SocietySame topicEpilepsy research and treatmentFrench-language works237,207