Efficacy of journaling in the management of mental illness: a systematic review and meta-analysis
Bibliographic record
Abstract
OBJECTIVES: Journaling is a common non-pharmacological tool in the management of mental illness, however, no clear evidence-based guideline exists informing primary care providers on its use. We seek here to present this synthesis that may begin to inform future research and eventual evidence-based guideline development. DESIGN: Of the 3797 articles retrieved from MEDLINE, EMBASE, PsycINFO, 20 peer-reviewed randomised control trials (31 outcomes) met inclusion criteria. These studies addressed the impact of a journaling intervention on PTSD, other anxiety disorders, depression or a combination of the aforementioned. ELIGIBILITY CRITERIA: Peer reviewed, randomised control trials on the impact of journaling on mental illness were included. INFORMATION SOURCES: MEDLINE, EMBASE and PsycINFO. RESULTS: of 83.8%) combined with a B-level Strength of Recommendation Taxonomy recommendation. It was additionally found that there is a significant pre-post psychometric scale difference between control (-0.01, 95% CI -0.03 to 0.00) and intervention arms (-0.06, 95% CI -0.09 to -0.03). This 5% difference between groups indicates that a journaling intervention resulted in a greater reduction in scores on patient health measures. Cohen's d effect size analysis of studies suggests a small to moderate benefit. CONCLUSION: Further studies are needed to better define the outcomes. Our review suggests that while there is some randomised control data to support the benefit of journaling, high degrees of heterogeneity and methodological flaws limit our ability to definitively draw conclusions about the benefit and effect size of journaling in a wide array of mental illnesses. Given the low risk of adverse effects, low resource requirement and emphasis on self-efficacy, primary care providers should consider this as an adjunct therapy to complement current evidence-based management.
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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 | 0.020 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.008 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| 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".