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Record W4387983460 · doi:10.2196/49735

Development of Quality of Life in Adolescents and Young Adults With Cancer Using a Patient Support Smartphone App: Prepost Interventional Study

2023· article· en· W4387983460 on OpenAlexvenueno aff
Line Bentsen, Signe Hanghøj, Maiken Hjerming, Mette Buur Bergmann, Marianne Thycosen, Anette Borup, Camilla Larsen, Helle Pappot

Bibliographic record

VenueJMIR Cancer · 2023
Typearticle
Languageen
FieldMedicine
TopicChildhood Cancer Survivors' Quality of Life
Canadian institutionsnot available
Fundersnot available
KeywordsPsychologyQuality of life (healthcare)Quality (philosophy)MedicinePsychotherapistPhilosophy

Abstract

fetched live from OpenAlex

BACKGROUND: Adolescents and young adults often experience existential concerns in addition to side effects during a cancer trajectory, which they often carry alone. Thus, cohesion with other adolescents and young adults with cancer is essential but difficult due to the relatively small, widely dispersed nationwide population. In cocreation, a smartphone app has been developed and includes an information bank, a symptom tracker, and a social community platform, aiming to improve the quality of life (QoL) in this patient group. OBJECTIVE: This nationwide, multicenter study aimed to investigate the QoL in adolescents and young adults undergoing a cancer trajectory as they used the app for 6 weeks. METHODS: Via youth support initiatives, participants were recruited from hospitals in all regions of Denmark. Inclusion criteria were patients with cancer aged 15-29 years who either initiated any cancer treatment or started follow-up after cancer treatment within 30 days. Participants used the adolescents and young adults cancer app for 6 weeks. Before and after the 6 weeks of app use, they completed the European Organization for Research and Treatment of Cancer Quality of Life Questionnaire Core 30 (EORTC QLQ-C30). The participants were divided into a treatment and a follow-up group for analysis. A high score for a functional scale or the global health or overall QoL represents a high or healthy level of functioning or high QoL, respectively; however, a high score for a symptom scale or item represents a high level of symptomatology. RESULTS: Overall, 81 participants were recruited. However, 4 participants did not answer the questionnaire and 6 participants did not use the app. In the treatment group (n=36), significant improvement was found in 2 domains: "Role functioning" (baseline median 33.33, IQR 16.67-83.33 vs 6 weeks median 66.67, IQR 33.33-83.33; P=.04) and "Pain" (baseline median 33.33, IQR 16.67-50.00 vs 6 weeks median 16.67, IQR 0.00-33.33; P=.04). The "Global health/Overall QoL" scale remained stable (baseline median 58.33, IQR 45.83-77.08 vs 6 weeks median 62.50, IQR 41.67-75.00; P=.25). In the follow-up group (n=35), significant improvement was found in 3 domains: "Physical functioning" (baseline median 79.23, IQR 73.33-93.33 vs 6 weeks median 82.86, IQR 73.33-100.00; P=.03), "Cognitive functioning" (baseline median 62.38, IQR 50.00-83.33 vs 6 weeks median 69.52, IQR 50.00-100.00; P=.02), and "Social functioning" (baseline median 76.19, IQR 50.00-100.00 vs 6 weeks median 85.71, IQR 83.33-100.00; P=.05), as well as in the "Global health/Overall QoL" scale (baseline median 57.14, IQR 83.33-100.00 vs 6 weeks median 75.0, IQR 62.91-85.73; P<.001). CONCLUSIONS: In this study, we found an improvement in specific QoL scales for both participants in treatment and follow-up when using the app for 6 weeks. The global health or overall QoL score improved significantly in the follow-up group. In the treatment group, it remained stable. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): RR2-10.2196/10098.

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)0.001
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 score0.037
Threshold uncertainty score0.994

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
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 head0.056
GPT teacher head0.376
Teacher spread0.320 · 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

Citations11
Published2023
Admission routes1
Has abstractyes

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