Evaluation of a Tablet-Based Emotion Regulation Intervention for Surrogate Decision-Makers of Patients With Critical Illness: Pilot Nonrandomized Trial
Bibliographic record
Abstract
BACKGROUND: Psychological distress among surrogate decision-makers (surrogates) for patients with critical illness is well documented. Existing interventions for supporting surrogates in their role often target surrogates' informational needs without directly addressing surrogates' acute emotional burden. Therefore, we developed the Reappraisal-Enhanced Foundation for Regulating Affect and Managing Emotions (REFRAME) intervention, a tablet-based app that empowers surrogates to manage their psychological distress with cognitive reappraisal. OBJECTIVE: We sought to (1) determine the feasibility, acceptability, and appropriateness of implementing REFRAME and (2) examine its preliminary effects on surrogates' psychological distress. METHODS: We conducted a pilot nonrandomized trial at a tertiary medical center in northeast Ohio. We recruited adult surrogates for incapacitated intensive care unit (ICU) patients (≥48 hours). The first 20 participants received usual care (UC); the next 28 received UC and REFRAME, consisting of 3 sequential 10- to 15-minute modules administered every 24 to 48 hours (T1-T3) post enrollment (T0). We evaluated implementation outcomes both quantitatively and qualitatively by describing enrollment and completion rates, surrogates' scores on the Acceptability of Intervention Measure and the Intervention Appropriateness Measure, and thematically analyzing feedback from each interventional module. We measured psychological distress with the Patient-Reported Outcomes Measurement Information System Anxiety and Depression short forms at enrollment (T0) and approximately 1-week post enrollment (T3). We used linear mixed-effects models to assess changes in anxiety and depression severity between groups from T0 to T3, adjusting for the surrogate's gender, patient relationship, prior decision-making experience, and perceived stress. RESULTS: Our analytic sample included 48 surrogates (UC=20; REFRAME=28). Two-thirds (19/28, 67.9%) of those assigned to REFRAME completed all 3 modules, with over 70% finding it acceptable and appropriate. Qualitative feedback indicated that surrogates appreciated the intervention's normalization of their emotions and provision of practical reappraisal strategies. Both groups showed reductions in psychological distress severity, with greater reductions in depressive symptoms reported by surrogates in the REFRAME group (d=0.68). CONCLUSIONS: REFRAME was feasible to implement, well-received by users, and considered relevant in the ICU setting. We observed preliminary improvement in depressive symptoms, though the effects on anxiety are less certain. Our findings indicate that incorporating brief cognitive reappraisal tools into routine ICU practice may support surrogates' psychological well-being. Larger, more diverse trials with longer follow-up are necessary to confirm these initial findings and assess their impact on shared decision-making.
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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 | 0.003 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.009 | 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".