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Record W6939353174 · doi:10.60692/hp0zn-fay39

Recruitment and retention challenges and strategies in randomized controlled trials of psychosocial interventions for children with cancer and their parents: a collective case study

2023· article· en· W6939353174 on OpenAlexaff

Bibliographic record

VenueGreater South Information System · 2023
Typearticle
Languageen
FieldMedicine
TopicEthics in Clinical Research
Canadian institutionsSickKids FoundationHospital for Sick Children
Fundersnot available
KeywordsPsychosocialPsychological interventionRandomized controlled trialIntervention (counseling)Protocol (science)Clinical trialMEDLINEConsistency (knowledge bases)

Abstract

fetched live from OpenAlex

Abstract Objective In pediatric oncology there are few examples of successful recruitment and retention strategies in psychosocial care research. This study aims to summarize experiences, challenges, and strategies for conducting randomized controlled trials (RCTs) from psychosocial intervention studies among children with cancer and their parent(s). Methods We conducted a collective case study. To identify the cases, Pubmed and two trial registries were searched for ongoing and finished RCTs of psychosocial intervention studies for children with cancer and their parents. Online semi-structured expert interviews discussing recruitment and retention challenges and strategies were performed with principal investigators and research staff members of the intervention studies. Results Nine studies were identified. Investigators and staff from seven studies participated, highlighting challenges and strategies within three major themes: eligibility, enrollment and retention. Regarding eligibility, collaborating constructively with healthcare professionals and involving them before the start of the study were essential. Being flexible, training the research staff, enabling alignment with the participants' situation, and providing consistency in contact between the research staff member and the families were important strategies for optimizing enrollment and retention. All studies followed a stepped process in recruitment. Conclusion Although recruitment and retention in some selected studies were successful, there is a paucity of evidence on experienced recruitment and retention challenges in pediatric psychosocial research and best practices on optimizing them. The strategies outlined in this study can help researchers optimize their protocol and trial-implementation, and contribute to better psychosocial care for children with cancer and their parents. Trial registration: this study is not a clinical trial.

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)0.787
metaresearch head score (Gemma)0.778
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesMetaresearch
DomainCandidate signal: Methods · Consensus signal: Methods
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.213
Threshold uncertainty score0.263

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.7870.778
Meta-epidemiology (narrow)0.0020.002
Meta-epidemiology (broad)0.0040.005
Bibliometrics0.0060.007
Science and technology studies0.0100.011
Scholarly communication0.0120.018
Open science0.0080.013
Research integrity0.0120.007
Insufficient payload (model declined to judge)0.0040.001

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.

Opus teacher head0.610
GPT teacher head0.520
Teacher spread0.089 · 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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.

Study designQualitative
DomainMethods
GenreEmpirical

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
Published2023
Admission routes1
Has abstractyes

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