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Record W3022990604 · doi:10.2196/17561

A Novel Narrative E-Writing Intervention for Parents of Children With Chronic Life-Threatening Illnesses: Protocol for a Pilot, Open-Label Randomized Controlled Trial

2020· article· en· W3022990604 on OpenAlexvenueno aff
Andy Hau Yan Ho, Oindrila Dutta, Geraldine Tan-Ho, Toh Hsiang Benny Tan, Xinyi Casuarine Low, Sashikumar Ganapathy, Josip Car, Moon‐Ho Ringo Ho, Chun Yan Miao

Bibliographic record

VenueJMIR Research Protocols · 2020
Typearticle
Languageen
FieldPsychology
TopicGrief, Bereavement, and Mental Health
Canadian institutionsnot available
Fundersnot available
KeywordsRandomized controlled trialGriefPsychological interventionQuality of life (healthcare)Intervention (counseling)NarrativeAttritionMedicinePsychologyPalliative careCaregiver burdenClinical psychologyNursingPsychotherapist

Abstract

fetched live from OpenAlex

BACKGROUND: A novel evidence-based Narrative e-Writing Intervention (NeW-I) has been developed and tested in Singapore to advance psychosociospiritual support for parents of children with chronic life-threatening illnesses. NeW-I is informed by an international systematic review and a Singapore-based qualitative inquiry on the lived experience of parental bereavement and supported by literature on anticipatory grief interventions for improving the holistic well-being of parent caregivers of seriously ill children. OBJECTIVE: This study's aim was to provide an accessible platform, NeW-I-which is a strengths- and meaning-focused and therapist-facilitated mobile app and web-based counseling platform-that aims to enhance quality of life, spiritual well-being, hope, and perceived social support and reduce depressive symptoms, caregiver burden, and risk of complicated grief among parents of children with chronic life-threatening illnesses. METHODS: The NeW-I therapist-facilitated web-based platform comprises a mobile app and a website (both of which have the same content and functionality). NeW-I has been implemented in Singapore as a pilot open-label randomized controlled trial comprising intervention and control groups. Both primary and secondary outcomes will be self-reported by participants through questionnaires. In collaboration with leading pediatric palliative care providers in Singapore, the trial aims to enroll 36 participants in each group (N=72), so that when allowing for 30% attrition at follow-up, the sample size will be adequate to detect a small effect size of 0.2 in the primary outcome measure, with 90% power and two-sided significance level of at least .05. The potential effectiveness of NeW-I and the accessibility and feasibility of implementing and delivering the intervention will be assessed. RESULTS: Funding support and institutional review board approval for this study have been secured. Data collection started in January 2019 and is ongoing. CONCLUSIONS: NeW-I aspires to enhance holistic pediatric palliative care services through a structured web-based counseling platform that is sensitive to the unique cultural needs of Asian family caregivers who are uncomfortable with expressing emotion even during times of loss and separation. The findings of this pilot study will inform the development of a full-scale NeW-I protocol and further research to evaluate the efficacy of NeW-I in Singapore and in other Asian communities around the world. TRIAL REGISTRATION: ClinicalTrials.gov NCT03684382; https://clinicaltrials.gov/ct2/show/NCT03684382. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/17561.

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)0.024
metaresearch head score (Gemma)0.024
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 score0.066
Threshold uncertainty score0.220

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0240.024
Meta-epidemiology (narrow)0.0040.002
Meta-epidemiology (broad)0.0080.004
Bibliometrics0.0020.002
Science and technology studies0.0030.003
Scholarly communication0.0040.004
Open science0.0030.002
Research integrity0.0060.007
Insufficient payload (model declined to judge)0.0660.008

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 head0.333
GPT teacher head0.585
Teacher spread0.252 · 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

Citations9
Published2020
Admission routes1
Has abstractyes

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