Leveraging Cognitive and Speech Ecological Momentary Assessment in Individuals With Phenylketonuria: Development and Usability Study of Cognitive Fluctuations in a Rare Disease Population
Bibliographic record
Abstract
BACKGROUND: Phenylketonuria (PKU) is a rare, hereditary disease that causes disruption in phenylalanine (Phe) metabolism. Despite early intervention, individuals with PKU may have difficulty in several different cognitive domains, including verbal fluency, processing speed, and executive functioning. OBJECTIVE: The overarching goal of this study is to characterize the relationships among cognition, speech, mood, and blood-based biomarkers (Phe, tyrosine) in individuals with early treated PKU. We describe our initial optimization pilot results that are guiding this study while establishing the feasibility and reliability of using ecological momentary assessment (EMA) in this clinical population. METHODS: In total, 20 adults with PKU were enrolled in this study between December 2022 and March 2023 through the National PKU Alliance. Of the total, 18 participants completed an extended baseline assessment followed by 6 EMAs over 1 month. The EMAs included digital cognitive tests measuring processing speed, sustained attention, and executive functioning, as well as speech (semantic fluency) and mood measures. Participants had 60 minutes to complete the assessment. RESULTS: Completion rates of EMAs were above 70% (on average 4.78 out of 6 EMAs), with stable performances across baseline measures and EMAs. Between-person reliability (BPR) of the EMAs, representing the variance due to differences between individuals versus within individuals, is satisfactory with values close to (semantic fluency BPR: 0.7, sustained attention BPR: 0.72) or exceeding (processing speed: 0.93, executive functioning: 0.88) data collected from a large normative database (n=5039-10,703), as well as slightly below or matching a previous study using a clinical group (n=18). As applicable, within-person reliability was also computed; we demonstrated strong reliability for processing speed (0.87). A control analysis ensured that time of day (ie, morning, afternoon, and evening) did not impact performance; performance on tasks did not decrease if tested earlier versus later in the day (all P values >.09). Similarly, to assess variability in task performance over the course of all EMAs, the coefficient of variability was computed; 28% for the task measuring sustained attention, 37% for semantic fluency, 15.8% for the task measuring executive functioning, and 17.6% for processing speed. Performance appears more stable in tasks measuring processing speed and executive functioning than on tasks of sustained attention and semantic fluency. CONCLUSIONS: Preliminary results of this study demonstrate strong reliability of cognitive EMA, indicating that EMA is a promising tool for evaluating fluctuations in cognitive status in this population. Future work should refine and expand the utility of these digital tools, determine how variable EMA frequencies might better characterize changes in functioning as they relate to blood-based biomarkers, and validate a singular battery that could be rapidly administered at scale and in clinical trials to determine the progression of disease.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.007 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".