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Record W2889432298 · doi:10.1186/s12913-018-3483-1

Adaptation of Coping Together - a self-directed coping skills intervention for patients and caregivers in an outpatient hematopoietic stem cell transplantation setting: a study protocol

2018· article· en· W2889432298 on OpenAlexaff
Tammy Son, Sylvie Lambert, Ann A. Jakubowski, Barbara DiCicco‐Bloom, Carmen G. Loiselle

Bibliographic record

VenueBMC Health Services Research · 2018
Typearticle
Languageen
FieldMedicine
TopicCancer survivorship and care
Canadian institutionsJewish General HospitalMcGill University
FundersNational Cancer InstituteMedical Research CouncilMemorial Sloan-Kettering Cancer Center
KeywordsPsychological interventionMedicineCoping (psychology)TransplantationDistressNursing researchIntervention (counseling)Clinical psychologyNursingSurgery

Abstract

fetched live from OpenAlex

BACKGROUND: Despite numerous reports of significant distress and burden for hematopoietic stem cell transplantation (HSCT) patients and caregivers (CGs), HSCT-specific coping interventions remain rare. The few in use lack specificity and are often not easily accessible or cost-effective. Whereas the development of new interventions is resource-intensive, theory-informed adaptation of existing evidence-based interventions is promising. To date, no HSCT-specific intervention has relied on a formal adaptation approach. METHODS: Using the Center for Disease Control and Prevention's Map of Adaptation, this two-phase qualitative descriptive study seeks to understand the perceptions of HSCT patients, CGs, individually, and in dyads, and clinicians about Coping Together (CT) for the preliminary adaptation (Phase 1), and then explores perceptions of the modified intervention in additional mixed sample (Phase 2). Six to ten participants including outpatients, CGs and dyads and five to seven HSCT clinician participants will be recruited for Phase 1. For Phase 2, 14 to 16 participants including outpatients, CGs and dyads will be recruited. Individual and dyadic semi-structured interviews will take place between 100 and 130 days post-HSCT. Verbatim transcripts will be analyzed using content analysis. DISCUSSION: It is paramount to have HSCT-specific supportive interventions that address patients' and CGs' multidimensional and complex needs. The timely involvement of key stakeholders throughout the adaptation process is likely to optimize the relevance and uptake of such tailored intervention. TRIAL REGISTRATION: This study is registered on October 6, 2016 in ClinicalTrials.gov at (identifier number NCT02928185 ).

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)0.020
metaresearch head score (Gemma)0.012
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Protocol · Consensus signal: Protocol
Teacher disagreement score0.030
Threshold uncertainty score0.107

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0200.012
Meta-epidemiology (narrow)0.0030.003
Meta-epidemiology (broad)0.0040.003
Bibliometrics0.0020.002
Science and technology studies0.0050.002
Scholarly communication0.0030.002
Open science0.0050.003
Research integrity0.0040.005
Insufficient payload (model declined to judge)0.0300.004

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 head0.043
GPT teacher head0.411
Teacher spread0.368 · 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 designNot applicable
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

Citations6
Published2018
Admission routes1
Has abstractyes

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