Narrowing the Patient–Physician Gap Based on Self-Reporting and Monthly Hepatologist Feedback for Patients With Alcohol-Related Liver Disease: Interventional Pilot Study Using a Journaling Smartphone App
Bibliographic record
Abstract
BACKGROUND: Screening and intervention for alcohol use disorders (AUDs) are recommended to improve the prognosis of patients with alcohol-related liver disease (ALD). Most patients' smartphone app diaries record drinking behavior for self-monitoring. A smartphone app can be expected to also be helpful for physicians because it can provide rich patient information to hepatologists, leading to suitable feedback. We conducted this prospective pilot study to assess the use of a smartphone app as a journaling tool and as a self-report-based feedback source for patients with ALD. OBJECTIVE: The aims of this study were assessment of whether journaling (self-report) and self-report-based feedback can help patients maintain abstinence and improve liver function data. METHODS: This pilot study used a newly developed smartphone journaling app for patients, with input data that physicians can review. After patients with ALD were screened for harmful alcohol use, some were invited to use the smartphone journaling app for 8 weeks. Their self-reported alcohol intake, symptoms, and laboratory data were recorded at entry, week 4, and week 8. Biomarkers for alcohol use included gamma glutamyl transferase (GGT), percentage of carbohydrate-deficient transferrin to transferrin (%CDT), and GGT-CDT (GGT-CDT= 0.8 × ln[GGT] + 1.3 × ln[%CDT]). At each visit, their recorded data were reviewed by a hepatologist to evaluate changes in alcohol consumption and laboratory data. The relation between those outcomes and app usage was also investigated. RESULTS: Of 14 patients agreeing to participate, 10 completed an 8-week follow-up, with diary input rates between 44% and 100% of the expected days. Of the 14 patients, 2 withdrew from clinical follow-up, and 2 additional patients never used the smartphone journaling app. Using the physician's view, a treating hepatologist gave feedback via comments to patients at each visit. Mean self-reported alcohol consumption dropped from baseline (100, SD 70 g) to week 4 (13, SD 25 g; P=.002) and remained lower at week 8 (13, SD 23 g; P=.007). During the study, 5 patients reported complete abstinence. No significant changes were found in mean GGT and mean %CDT alone, but the mean GGT-CDT combination dropped significantly from entry (5.2, SD 1.2) to the week 4 visit (4.8, SD 1.1; P=.02) and at week 8 (4.8, SD 1.0; P=.01). During the study period, decreases in mean total bilirubin (3.0, SD 2.4 mg/dL to 2.4, SD 1.9 mg/dL; P=.01) and increases in mean serum albumin (3.0, SD 0.9 g/dL to 3.3, SD 0.8 g/dL; P=.009) were recorded. CONCLUSIONS: These pilot study findings revealed that a short-term intervention with a smartphone journaling app used by both patients and treatment-administering hepatologists was associated with reduced drinking and improved liver function. TRIAL REGISTRATION: UMIN CTR UMIN000045285; http://tinyurl.com/yvvk38tj.
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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 | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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 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".