Daily and weekly mood ratings using a remote capture method in high‐risk offspring of bipolar parents: Compliance and symptom monitoring
Bibliographic record
Abstract
OBJECTIVES: To determine the compliance and clinical utility of weekly and daily electronic mood symptom monitoring in adolescents and young adults at risk for mood disorder. METHODS: Fifty emerging adult offspring of bipolar parents were recruited from the Flourish Canadian high-risk offspring cohort study along with 108 university student controls. Participants were assessed by KSADS/SADS-L semi-structured interviews and used a remote capture method to complete weekly and daily mood symptom ratings using validated scales for 90 consecutive days. Hazard models and generalized estimating equations were used to determine differences in summary scores and regularity of ratings. RESULTS: Seventy-eight and 77% of high-risk offspring and 97% and 93% of controls completed the first 30 days of weekly and daily ratings, respectively. There were no differences in drop-out rates between groups over 90 days (weekly P = 0.2149; daily P = 0.9792). There were no differences in mean summary scores or regularity of weekly anxiety, depressive or hypomanic symptom ratings between high-risk offspring and control groups. However, high-risk offspring compared to controls had daily ratings indicating lower positive affect, higher negative affect and lower self-esteem (P = 0.0317). High-risk offspring with remitted mood disorder compared to those without had more irregularity in weekly anxiety and depressive symptom ratings and daily ratings of lower positive affect, higher negative affect, and higher shame and self-doubt (P = 0.0365). CONCLUSIONS: Findings support that high-resolution electronic mood tracking may be a feasible and clinically useful approach in monitoring emerging psychopathology in young people at high-risk offspring of mood disorder onset or recurrence.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 teacher head, 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".