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Record W4413050793 · doi:10.2196/64977

Companionship and Sharing Create Social Connections of an Online Community-Based Intervention for Patients with Cancer Receiving Outpatient Care: Pilot Study

2025· article· en· W4413050793 on OpenAlexvenueno aff
Yi He, Ying Pang, Zimeng Li, Yan Wang, Yening Zhang, Zhongge Su, Song Lili, Shuangzhi He, Bingmei Wang, Lili Tang

Bibliographic record

VenueJMIR Cancer · 2025
Typearticle
Languageen
FieldMedicine
TopicCancer survivorship and care
Canadian institutionsnot available
Fundersnot available
KeywordsIntervention (counseling)Quality of life (healthcare)MedicineOnline communityLoginBaseline (sea)CancerOutpatient clinicFamily medicinePhysical therapyPsychiatryNursingWorld Wide WebInternal medicine

Abstract

fetched live from OpenAlex

Background: Online communities, platforms that facilitate social connections, have gained attention in the medical field, particularly for their potential to support patients. However, there is currently no online community specifically designed for patients with cancer receiving outpatient care. This study introduces a customized online community aimed at providing companionship and sharing to enhance the quality of life (QOL) among these patients. Objective: The purpose of this study was to assess the feasibility and initial effectiveness of a newly developed online community app in improving the QOL of patients with cancer receiving outpatient care. Methods: This pilot intervention-only study involved patients with cancer participating in a 4-week online community intervention through a mobile app. Eligible patients were aged 18 years or older, diagnosed with cancer, with an Eastern Cooperative Oncology Group Performance Status score of ≤2. The feasibility of the intervention was evaluated by community task participation rate, community task completion rate, and community daily login rate. Patients completed a QOL questionnaire (European Organization for Research and Treatment of Cancer Quality of Life Questionnaire Core 30, QLQ-C30) at baseline (T0), week 2 (T1), and week 4 (T2). After the intervention, participants were free to answer 3 questions about their user experience. Results: Baseline assessments were conducted on 30 patients, with 25 patients assessed at T1 (83.3%) and 22 at T2 (73.3%). The 4-week average community daily login rate was 60.37% (18.11/30 on average), with community task participation and community task completion rates reaching 42.25% (12.68/30 on average) and 22.38% (6.7/30 on average), respectively. Notably, after the study ended, participants continued logging into the app and completing tasks. Patients who actively engaged in community activities demonstrated significant improvements in global health status (mean 11.04, SD 10.3 vs mean -6.56, SD 11.58; P=.004), emotional function (mean 17.7, SD 22.93 vs mean -2.89, SD 13.9; P=.04), and constipation (mean 11, SD 16.5 vs mean 14.67, SD 17.39; P=.005) at T2, compared to those less active. The intervention enhanced emotional functioning and overall health and alleviated insomnia symptoms among active participants. Conclusions: The online community intervention, emphasizing companionship and sharing, was well accepted by patients with cancer and demonstrated initial effectiveness in enhancing the QOL. The study findings suggest that such interventions can provide a supportive environment for patients to cope with psychological, social, and physical challenges. Future validation of its effectiveness will require well-designed randomized controlled trials, and continued optimization tailored to specific user groups will be crucial to meet the evolving needs of the community. The core value of the online community lies in companionship and sharing, which can serve as a foundation for future research and development in this area.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.227
Threshold uncertainty score0.977

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.079
GPT teacher head0.379
Teacher spread0.300 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
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
Published2025
Admission routes1
Has abstractyes

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