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Record W4213339231 · doi:10.21203/rs.2.394/v1

Enhancing & Mobilizing the POtential for Wellness & Emotional Resilience Among Surrogate Decision-Makers of ICU Patients (EMPOWER): Study protocol for a randomized controlled trial

2019· preprint· en· W4213339231 on OpenAlexaff
Holly G. Prigerson, Martin Viola, Chris R. Brewin, Christopher E. Cox, Daniel Ouyang, Madeline Rogers, Cynthia X. Pan, Shayna Rabin, Jiehui Xu, Susan C. Vaughan, Janna S. Gordon-Elliot, David Berlin, Lindsay Lief, Wendy G. Lichtenthal

Bibliographic record

VenueResearch Square · 2019
Typepreprint
Languageen
FieldMedicine
TopicPalliative Care and End-of-Life Issues
Canadian institutionsColumbia College
FundersNational Cancer InstituteAmerican Cancer Society
KeywordsRandomized controlled trialMedicineQuality of life (healthcare)Mental healthComplicated griefDistressClinical psychologyExperiential avoidanceAnxietyPsychiatryPsychologyGriefNursing

Abstract

fetched live from OpenAlex

Abstract Background Critical illness increases the risk for poor mental health outcomes among both patients and their informal caregivers or surrogate decision-makers. Surrogates who must make life-and-death medical decisions on behalf of incapacitated patients may experience additional distress. EMPOWER (Enhancing & Mobilizing the POtential for Wellness & Emotional Resilience among Surrogate Decision-Makers of ICU Patients) is a novel cognitive-behavioral, acceptance-based intervention delivered in the intensive care unit (ICU) setting to surrogate decision-makers designed to improve both patients’ quality of life and death and dying as well as surrogates’ mental health. Methods Clinician stakeholder and surrogate participant feedback (n=15), as well as results from an open trial (n =10), will be used to refine the intervention, which will then be administered as a multisite randomized controlled trial (n = 60) to examine clinical superiority to usual care. Feasibility, tolerability, and acceptability of the intervention will be evaluated through self-report assessments. Hierarchical linear modeling will be used to adjust for clustering within interventionists to determine the effect of EMPOWER on surrogate differences in the primary outcome, peritraumatic stress. Secondary outcomes will include symptoms of posttraumatic stress disorder (PTSD), prolonged grief disorder (PGD) and experiential avoidance. Exploratory outcomes will include symptoms of anxiety, depression, and decision regret, all measured at one-month and three-months from baseline. Linear regression models will examine the effects of assignment to EMPOWER versus the enhanced usual care group on patient quality of life or quality of death and intensity of care the patient received during the indexed ICU stay assessed at the time of the post-intervention assessment on. Participant exit interviews will be conducted at the three-month assessment time point and will be analyzed using qualitative thematic data analysis methods. Discussion The EMPOWER study is unique in its application of evidence-based psychotherapy targeting peritraumatic stress to improve patient and caregiver outcomes in the setting of critical illness. The experimental intervention will be strengthened through the input of a variety of ICU stakeholders, including behavioral health clinicians, physicians, bereaved informal caregivers, and open trial participants. Results of the RCT will be submitted for publication in a peer-reviewed journal and serve as preliminary data for a larger, multisite RCT grant application. Trial registration: ClinicalTrials.gov Identifier NCT03276559 (Retrospectively registered September 8th, 2017)

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.046
metaresearch head score (Gemma)0.049
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Randomized trial · Consensus signal: Randomized trial
GenreCandidate signal: Protocol · Consensus signal: Protocol
Teacher disagreement score0.085
Threshold uncertainty score0.285

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0460.049
Meta-epidemiology (narrow)0.0080.004
Meta-epidemiology (broad)0.0150.006
Bibliometrics0.0040.005
Science and technology studies0.0040.005
Scholarly communication0.0060.005
Open science0.0040.003
Research integrity0.0080.009
Insufficient payload (model declined to judge)0.0850.014

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.

Opus teacher head0.124
GPT teacher head0.502
Teacher spread0.378 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designRandomized trial
Domainnot available
GenreProtocol

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".

Quick stats

Citations0
Published2019
Admission routes1
Has abstractyes

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