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Record W4286378295 · doi:10.2196/34851

Impact of a Personal Health Record Intervention Upon Surveillance Among Colorectal Cancer Survivors: Feasibility Study

2022· article· en· W4286378295 on OpenAlexvenueno aff
Éric Vachon, Bruce W. Robb, David A. Haggstrom

Bibliographic record

VenueJMIR Cancer · 2022
Typearticle
Languageen
FieldMedicine
TopicCancer survivorship and care
Canadian institutionsnot available
FundersNational Cancer InstituteNational Institutes of HealthHealth Services Research and DevelopmentOffice of Research and DevelopmentLivestrong FoundationU.S. Department of Veterans Affairs
KeywordsMedicineColorectal cancerPsychological interventionColonoscopyConfidence intervalInternal medicineCancerPhysical therapy

Abstract

fetched live from OpenAlex

BACKGROUND: There are currently an estimated 1.5 million individuals living in the United States with colorectal cancer (CRC), and although the 5-year survival rate has increased, survivors are at risk for recurrence, particularly within the first 2-3 years after treatment. National guidelines recommend continued surveillance after resection to identify recurrence early on. Adherence among survivors ranges from 23% to 94%. Novel interventions are needed to increase CRC survivors' knowledge and confidence in managing their cancer and thus to increase adherence to follow-up surveillance. OBJECTIVE: The objective of this study is to develop and test the feasibility and efficacy of a stand-alone, web-based personal health record (PHR) to increase surveillance adherence among CRC survivors, with patient beliefs about surveillance as secondary outcomes. METHODS: A pre- and postintervention feasibility trial was conducted testing the efficacy of the colorectal cancer survivor (CRCS)-PHR, which had been previously developed using an iterative, user-centered design approach. RESULTS: The average age of the sample was 58 (SD 9.9) years, with 57% (16/28) male and the majority married (20/28, 71%) and employed full-time (15/28, 54%). We observed a significant increase in adherence to colonoscopy (before: 11/21, 52% vs after: 18/21, 86%; P=.005) and CEA (14/21, 67% vs 20/21, 95%; P=.01), as well as a slight increase in CT scans (14/21, 67% vs 18/21, 86%; P=.10). The only significant impact on secondary outcome (patient beliefs) was benefits of CEA test (P=.04), as most of the beliefs were high at baseline. CONCLUSIONS: This feasibility study lays the groundwork for continued development of the CRCS-PHR to increase CRC surveillance. Patient-centered technologies, such as the CRCS-PHR, represent an important potential approach to improving the receipt of guideline-concordant care and follow-up surveillance, and not just for CRC survivors. Researchers should continue to develop patient-centered health technologies with clinician implementation in mind to increase patient self-efficacy and surveillance adherence.

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)0.014
metaresearch head score (Gemma)0.026
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.014
Threshold uncertainty score0.072

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0140.026
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.002
Research integrity0.0010.002
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 head0.032
GPT teacher head0.386
Teacher spread0.354 · 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 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

Citations7
Published2022
Admission routes1
Has abstractyes

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