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Record W2770869357 · doi:10.1177/2158244017742952

Instrument Refinement: The Patient’s Perception of Life on Hemodialysis Scale

2017· article· en· W2770869357 on OpenAlexaff
J. Creina Twomey, Christine Way, Patrick S. Parfrey, David Churchill, Brendan J. Barrett

Bibliographic record

VenueSAGE Open · 2017
Typearticle
Languageen
FieldMedicine
TopicDialysis and Renal Disease Management
Canadian institutionsMcMaster UniversityMemorial University of Newfoundland
Fundersnot available
KeywordsHemodialysisScale (ratio)PsychologyQuality of life (healthcare)PerceptionPsychological interventionClinical psychologyDescriptive statisticsPsychiatryStatisticsPsychotherapist

Abstract

fetched live from OpenAlex

The objective of this study is to refine the Patient’s Perception of Hemodialysis Scale and data quality and refine the Patient’s Perception of Life on Hemodialysis Scale (PPHS). Collecting data from a convenient sample ( N = 236), data were collected and a cross-sectional design survey design was used. Item inclusion was based on the item’s theoretical underpinning, examination of data quality, findings from a multi-trait/multi-item correlation matrix, and criteria for item and scale characteristics. Data indicators were close to normal in terms of distribution. High and low statistics suggest that the entire scope of the characteristic being measured were experienced. All criteria related to this examination supported the inclusion/exclusion of remaining items and subscales. Subscales are able to measure the main concepts. Findings from this research have been analyzed, and the PPHS now includes five subscales (36 items) and is deemed a valid indicator of the hemodialysis patients’ perceptions of life. Nephrology nurses will be able to assess the patient’s illness and treatment experience, their perception of formal social supports, adjustment to life on hemodialysis, and design interventions.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.954
Threshold uncertainty score1.000

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)0.0010.000

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 head0.028
GPT teacher head0.287
Teacher spread0.259 · 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 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

Citations1
Published2017
Admission routes1
Has abstractyes

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