MétaCan
Menu
Back to cohort
Record W2587498825 · doi:10.24251/hicss.2017.449

Telemonitoring for Seniors with Chronic Heart Failure: Patient Self-Care, Empowerment, and Adoption Factors

2017· article· en· W2587498825 on OpenAlexaff
Mirou Jaana, Haitham Tamim, Heather Sherrard, Guy Paré

Bibliographic record

VenueProceedings of the ... Annual Hawaii International Conference on System Sciences/Proceedings of the Annual Hawaii International Conference on System Sciences · 2017
Typearticle
Languageen
FieldMedicine
TopicMedication Adherence and Compliance
Canadian institutionsAlgonquin CollegeUniversity of Ottawa
Fundersnot available
KeywordsPatient EmpowermentEmpowermentHeart failureMedicineRelevance (law)Self-managementSelf carePhysical therapyPsychologyHealth careGerontologyInternal medicineComputer science

Abstract

fetched live from OpenAlex

Telemonitoring (TM) represents a promising technology for the management of chronic diseases. It is of particular relevance to senior patients with heart failure (HF) condition. This study employs a longitudinal design, and involves three surveys of elderly HF patients (n=23) administered one week, three months, and six months after system adoption. The main constructs were assessed based on existing validated scales. The results show that senior patients perceived value in using TM, did not expect the technology to be difficult to use, and did not encounter barriers to adoption. The analysis of impacts on self-care revealed significant positive effects of TM on the confidence of senior patients in their self-care ability to evaluate their symptoms, address them, and evaluate the effectiveness of the measures they take. Significant positive effects were also observed on two measures of treatment implementation. TM may be leveraged to improve senior patients’ self-care skills, which will benefit their health condition.

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 categoriesMeta-epidemiology (narrow), Science and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.928
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0020.002
Scholarly communication0.0010.002
Open science0.0040.001
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 head0.041
GPT teacher head0.315
Teacher spread0.275 · 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.

Study designQualitative
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
Published2017
Admission routes1
Has abstractyes

Explore more

Same venueProceedings of the ... Annual Hawaii International Conference on System Sciences/Proceedings of the Annual Hawaii International Conference on System SciencesSame topicMedication Adherence and ComplianceFrench-language works237,207