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Record W4313430439 · doi:10.2196/33147

CareKnowDo—A Multichannel Digital and Telephone Support Program for People With Chronic Kidney Disease: Feasibility Randomized Controlled Trial

2023· article· en· W4313430439 on OpenAlexvenueno aff
Jonathan Reston, Fergus Caskey, Barnaby Hole, Udaya Udayaraj, John Weinman

Bibliographic record

VenueJMIR Formative Research · 2023
Typearticle
Languageen
FieldMedicine
TopicDialysis and Renal Disease Management
Canadian institutionsnot available
FundersNational Institute for Health and Care Research
KeywordsMedicineKidney diseaseRandomized controlled trialPhysical therapyPsychosocialBlood pressureAttritionDigital healthInternal medicineHealth care

Abstract

fetched live from OpenAlex

BACKGROUND: Chronic kidney disease (CKD) is a common, progressive condition. Lifestyle changes and antihypertensive medication can slow the progression to end-stage kidney disease, which requires renal replacement therapy. However, adherence to these recommendations is often low. OBJECTIVE: The aim of CareKnowDo was to assess the feasibility of rolling out a digital self-management support and adherence program integrated with a patient-facing electronic health record, Patient View (PV). METHODS: A 2-arm, parallel, individual-level pragmatic feasibility pilot randomized controlled trial was conducted at 2 National Health Service (NHS) sites in the United Kingdom. A total of 61 patients with CKD were randomized 1:1 into 2 groups and provided with either a new, tailored digital and telephone support program (CareKnowDo: 31/61, 51%) integrated with PV or standard care (PV alone: 30/61, 49%). Quantitative measures included clinical and psychosocial measures. The primary outcomes were feasibility based: recruitment rate, dropout, and the exploration of associations. RESULTS: Of the 1392 patients screened in local kidney clinics, 269 (19.32%) met the basic inclusion criteria; the first 22.7% (61/269) who met the eligibility criteria were recruited to participate in the study. Of the 69 patients, 23 (38%) patients completed the final 6-month follow-up web-based survey. Reasons for the attrition were explored. A higher belief in the ability of the treatment to control CKD was associated with lower blood pressure at baseline (r=0.52; P=.005), and a higher perceived understanding of CKD at baseline was associated with lower blood pressure at follow-up (r=0.66; P<.001). Beliefs about medicines at baseline were associated with blood pressure at baseline but not at follow-up. This was true for both concerns about medicines (r=0.58; P=.001) and perceived necessity of medicines (r=0.42; P=.03). CONCLUSIONS: A tailored digital and nurse call-based program to enhance support for patients with CKD was piloted in 2 NHS sites and found to be feasible and acceptable. However, to maximize the effectiveness of the intervention (and of future trials), consideration should be given to the target audience most likely to benefit, as well as how to help them access the program as quickly and easily as possible. TRIAL REGISTRATION: NHS Health Research Authority, IRAS ID 184206; https://www.hra.nhs.uk/planning-and-improving -research/application-summaries/research-summaries/careknowdo-pilot-version-1/.

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)0.003
metaresearch head score (Gemma)0.004
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: Empirical · Consensus signal: Empirical
Teacher disagreement score0.010
Threshold uncertainty score0.033

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.004
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0030.002
Insufficient payload (model declined to judge)0.0100.001

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 head0.390
Teacher spread0.358 · 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
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

Citations9
Published2023
Admission routes1
Has abstractyes

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