Development and Validation of a Cross-Device Platform for Anhedonia Trend Visualization by Using Ecological Momentary Assessment and Moving Averages (Part I): Protocol for a Methodological Pilot Study
Bibliographic record
Abstract
BACKGROUND: Anhedonia is a core symptom of depressive disorders. Although group-level cutoff points for the Snaith-Hamilton Pleasure Scale (SHAPS) are established, real-time, individual-level monitoring remains limited. Ecological momentary assessment (EMA) enables high-frequency sampling, and simple moving averages (SMA; 7/14/30 days) offer an interpretable way to smooth daily signals and surface early-warning trends. OBJECTIVE: The aim of this study was to develop and validate a cross-device platform that collects EMA-based SHAPS responses and visualizes SMA trends for individual anhedonia monitoring. This part I protocol focuses on platform design, feasibility, usability, data quality, and initial analytical validity to inform subsequent evaluation. METHODS: We will conduct a single-arm methodological pilot in approximately 24 adults, recruited from an outpatient psychiatry clinic (clinical cohort) and a university setting (nonclinical cohort). After baseline assessment, participants will complete 30 days of daily EMA-SHAPS. Primary outcomes are feasibility (adherence, missingness patterns, timing fidelity) and usability/face validity (eg, System Usability Scale, qualitative feedback). We will also describe expert content validity ratings for key visual elements and exploratory analytic checks of within-person variability and the descriptive behavior of 7/14/30-day moving averages; these analyses are not powered for confirmatory hypothesis testing. RESULTS: This protocol specifies the design-validate sequence, recruitment procedures, and predefined adherence and missing-data rules for computing moving averages. Recruitment for the year-1 feasibility pilot is scheduled to begin in March 2026 following institutional review board approval (approval 114006; approval date: June 10, 2025), with feasibility metrics, usability indices, and parameter estimates used to refine alert logic and power calculations for a planned part II evaluation. CONCLUSIONS: Combining EMA-SHAPS with SMA-based trend visualizations may provide an interpretable way to summarize daily anhedonia signals and generate candidate early-warning indicators. This methodological pilot will deliver feasibility, usability, and preliminary analytic parameters needed to support a subsequent controlled evaluation of the platform's clinical utility. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): PRR1-10.2196/84024.
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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 | 0.074 | 0.083 |
| Meta-epidemiology (narrow) | 0.003 | 0.003 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.004 | 0.003 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.028 | 0.009 |
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".