Previously submitted to: JMIR Medical Informatics (no longer under consideration since Apr 06, 2026)
Date Submitted: Mar 25, 2026
Open Peer Review Period: Apr 6, 2026 - Apr 6, 2026
(closed for review but you can still tweet)
NOTE: This is an unreviewed Preprint
Warning: This is a unreviewed preprint (What is a preprint?). Readers are warned that the document has not been peer-reviewed by expert/patient reviewers or an academic editor, may contain misleading claims, and is likely to undergo changes before final publication, if accepted, or may have been rejected/withdrawn (a note "no longer under consideration" will appear above).
Peer review me: Readers with interest and expertise are encouraged to sign up as peer-reviewer, if the paper is within an open peer-review period (in this case, a "Peer Review Me" button to sign up as reviewer is displayed above). All preprints currently open for review are listed here. Outside of the formal open peer-review period we encourage you to tweet about the preprint.
Citation: Please cite this preprint only for review purposes or for grant applications and CVs (if you are the author).
Final version: If our system detects a final peer-reviewed "version of record" (VoR) published in any journal, a link to that VoR will appear below. Readers are then encourage to cite the VoR instead of this preprint.
Settings: If you are the author, you can login and change the preprint display settings, but the preprint URL/DOI is supposed to be stable and citable, so it should not be removed once posted.
Submit: To post your own preprint, simply submit to any JMIR journal, and choose the appropriate settings to expose your submitted version as preprint.
Warning: This is an author submission that is not peer-reviewed or edited. Preprints - unless they show as "accepted" - should not be relied on to guide clinical practice or health-related behavior and should not be reported in news media as established information.
A Construct Aligned Informatics Pipeline for Clinically Interpretable Digital Endpoints in Neurodevelopmental Conditions
ABSTRACT
Background:
Continuous, multimodal digital data promise richer assessment in neurodevelopmental conditions, but many digital endpoints remain device centric, poorly interpretable, and difficult for regulators and clinicians to use in decision making¹⁻².
Objective:
Introduce the Construct Aligned Framework (CAF), a reproducible informatics pipeline that maps multimodal digital features to latent neurobehavioral constructs while explicitly modeling context and behavioral missingness⁵⁻⁶.
Methods:
CAF comprises five modular components: construct anchored variance partitioning⁹, behavioral missingness modeling⁵⁻⁶, latent construct fusion⁹, ecological contrast assessment¹⁰, and construct calibrated reliability⁸. We provide prescriptive algorithm choices, minimal data requirements, a synthetic worked example demonstrating end to end feasibility, and a reproducibility appendix with synthetic data and pseudocode.
Results:
In a synthetic cohort (30 participants, 28 days), CAF separated construct signal from device/context variance³⁻⁴, produced a latent social engagement score with clear modality loadings⁹, quantified clinic–home ecological contrast¹⁰, and yielded acceptable reliability (ICC ≈ 0.78)⁸. Behavioral missingness modeling improved interpretability by distinguishing avoidance from technical dropout⁵⁻⁶.
Conclusions:
CAF provides a reproducible informatics pipeline that enables clinically interpretable digital endpoints, supporting transparent endpoint derivation, auditability, and downstream clinical decision making. The pipeline operationalizes construct alignment for regulatory ready digital endpoints¹⁻² by combining theory driven measurement⁹ with transparent, reproducible algorithms.
Citation
Request queued. Please wait while the file is being generated. It may take some time.
Copyright
© The authors. All rights reserved. This is a privileged document currently under peer-review/community review (or an accepted/rejected manuscript). Authors have provided JMIR Publications with an exclusive license to publish this preprint on it's website for review and ahead-of-print citation purposes only. While the final peer-reviewed paper may be licensed under a cc-by license on publication, at this stage authors and publisher expressively prohibit redistribution of this draft paper other than for review purposes.