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Record W4379093318 · doi:10.2196/46339

The Electronic Surviving Cancer Competently Intervention Program—a Psychosocial Digital Health Intervention for English- and Spanish-Speaking Parents of Children With Cancer: Protocol for Randomized Controlled Trial

2023· article· en· W4379093318 on OpenAlexvenueno aff
Kimberly S. Canter, Lee M. Ritterband, David R. Freyer, Martha A. Askins, Laura Bava, Caitlyn Loucas, Kamyar Arasteh, Wen You, Anne E. Kazak

Bibliographic record

VenueJMIR Research Protocols · 2023
Typearticle
Languageen
FieldMedicine
TopicChildhood Cancer Survivors' Quality of Life
Canadian institutionsnot available
FundersNational Cancer InstituteNational Institutes of Health
KeywordsPsychosocialTelehealthPsychological interventionMedicineRandomized controlled trialDistressIntervention (counseling)Digital healthAnxietyTelemedicineHealth careFamily medicineNursingClinical psychologyPsychiatry

Abstract

fetched live from OpenAlex

BACKGROUND: The psychosocial needs and risks of children with cancer and their families are well-documented including increased risk of parental distress, posttraumatic stress, and anxiety. There is a critical need to provide evidence-based psychosocial care to parents and caregivers of children with cancer. Digital health interventions are important to address many barriers to in-person intervention delivery but are not widely used in pediatric psychosocial cancer care. The COVID-19 pandemic has reinforced the need for flexible, acceptable, and accessible psychosocial digital health interventions. The Electronic Surviving Cancer Competently Intervention Program (eSCCIP) is an innovative digital health intervention for parents and caregivers of children with cancer, delivered through a combination of self-guided web-based content and supplemented by 3 telehealth follow-up sessions with a trained telehealth guide. A Spanish language adaptation of eSCCIP, El Programa Electronico de Intervencion para Superar Cancer Competentemente (eSCCIP-SP), has been developed. The self-guided web-based cores of eSCCIP/eSCCIP-SP are a mix of didactic video content, multifamily video discussion groups featuring parents of children with cancer, and hands-on web-based activities. OBJECTIVE: The objective of this study is to test eSCCIP/eSCCIP-SP in a multisite randomized controlled trial, compared to an internet-based education control condition consisting of information specifically focused on concerns relevant to parents and caregivers of children with cancer. METHODS: Using a randomized controlled clinical trial design, 350 eligible parents and caregivers of children with cancer will be randomly assigned to the intervention (eSCCIP/eSCCIP-SP) or an education control condition. Data will be collected at 3 time points: preintervention (prior to randomization), immediately post intervention (after 6 weeks), and at a 3-month follow-up (from baseline). Participants randomized to either condition will receive study material (eSCCIP/eSCCIP-SP intervention or education control website) in English or Spanish, based on the primary language spoken in the home and participant preference. RESULTS: The primary study end point is a reduction in acute distress from baseline to postintervention, with secondary end points focused on reductions in symptoms of posttraumatic stress and anxiety, and improvements in coping self-efficacy and cognitive coping. An additional exploratory aim will be focused on implementation strategies and potential costs and cost-savings of eSCCIP/eSCCIP-SP, laying the groundwork for future trials focused on dissemination and implementation, stepped-care models, and intervention refinement. CONCLUSIONS: This trial will provide necessary data to evaluate the efficacy of eSCCIP/eSCCIP-SP. This intervention has the potential to be an easily scalable and highly impactful psychosocial treatment option for parents and caregivers of children with cancer. TRIAL REGISTRATION: ClinicalTrials.gov NCT05294302; https://clinicaltrials.gov/ct2/show/NCT05294302. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): PRR1-10.2196/46339.

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

Direct model labels (unvalidated)

Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.

Model armCategoriesStudy designConfidence
gemmano category
Domain: not available · Genre: Protocol
About the Canadian research system: no · About a Canadian topic: no
Randomized triallow
gptno category
Domain: not available · Genre: Protocol
About the Canadian research system: no · About a Canadian topic: no
Randomized trialmedium
models agreeAgreement compares identical category sets and study designs across arms.

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)0.024
metaresearch head score (Gemma)0.022
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 score0.086
Threshold uncertainty score0.288

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0240.022
Meta-epidemiology (narrow)0.0070.004
Meta-epidemiology (broad)0.0150.006
Bibliometrics0.0040.004
Science and technology studies0.0040.004
Scholarly communication0.0050.004
Open science0.0040.002
Research integrity0.0080.009
Insufficient payload (model declined to judge)0.0860.011

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 head0.112
GPT teacher head0.549
Teacher spread0.436 · 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

Labeled directly by 2 models reading the full record.

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

Citations4
Published2023
Admission routes1
Has abstractyes

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