Integration of sex/gender and utilization of ecological Momentary assessment of cognition in clinical populations: A scoping review
Bibliographic record
Abstract
Objectives: We aimed to describe the methods of smartphone-based cognitive ecological momentary assessment designs in clinical populations, with an intention to evaluate how the role of sex and/or gender has been considered in the design and analyses, particularly including female-specific physiology. Methods: This scoping review was conducted based on JBI scoping review methodology. On March 2nd, 2023, we searched for literature across four databases. Screening of the results and data extraction were conducted in duplicate according to the a priori methods in the pre-registered protocol. Results: 31 articles were included in this review. Participants ranged in age from 15-85 years old with various clinical disorders. Prompts were given between 1-7 times per day for 7-84 days. Executive function was the most frequently assessed cognitive domain. Over half the studies (n = 17, 55%) did not investigate the effects of sex and/or gender, and only one study considered the impact of hormonal therapy. Many studies (n = 14, 45%) used sex and gender interchangeably or incorrectly. Conclusions: Studies varied in design, with heterogeneity in the reporting of methodological information. The lack of attention to sex/gender on neuropsychological outcomes can lead to confusion and contradiction regarding its potential impact on cognition in clinical populations. This may hinder the identification of effective interventions for those assigned female at birth who have been overlooked or considered indistinguishable from their male counterparts. Given the well-documented impact of sex/gender on cognition, it is essential that future neuropsychological research, especially EMA-based studies, prioritize investigating sex/gender to ensure better outcomes for all.
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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 | 0.032 | 0.153 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.007 |
| Bibliometrics | 0.023 | 0.018 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.007 | 0.005 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.004 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".