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Record W3114778989 · doi:10.1145/3432218

Evaluating the Gradual Delivery of Knowledge-focused and Mindset-focused Messages for Facilitating the Acceptance of COPD

2020· article· en· W3114778989 on OpenAlexaff
Steven Y. Zeng, Robert Wu, Khai N. Truong, Fanny Chevalier

Bibliographic record

VenueProceedings of the ACM on Interactive Mobile Wearable and Ubiquitous Technologies · 2020
Typearticle
Languageen
FieldPsychology
TopicDigital Mental Health Interventions
Canadian institutionsUniversity Health NetworkUniversity of Toronto
Fundersnot available
KeywordsMindsetCOPDProcess (computing)Pulmonary diseaseMedicineIdentity (music)PsychologyFoundation (evidence)Computer sciencePsychiatryInternal medicine

Abstract

fetched live from OpenAlex

Chronic Obstructive Pulmonary Disease (COPD) is a terminal, progressive lung condition which mainly affects older adults. The onset of symptoms, obstacles, and impairments brought about by COPD often necessitates a grieving process for patients. Acceptance is the stage of the grieving process in which the patient has healthily integrated the condition into his or her lifestyle and identity. Because of the progressive nature of COPD, the process of acceptance is a perpetual journey in which patients must continuously shift their mindsets and lifestyles to adapt to the increasing severity of the condition. Using the health belief model as a theoretical foundation, we explore the usage of daily automated SMS messages as an engaging and accessible means of facilitating and maintaining a patient's acceptance of COPD. The results of our investigation show that SMS messages serve as an effective tool for improving patients' acceptance of COPD while also reducing patients' proclivities to the nonacceptance stages of the grieving process.

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)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.864
Threshold uncertainty score0.442

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.001
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 head0.082
GPT teacher head0.392
Teacher spread0.311 · 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 designBench or experimental
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

Citations8
Published2020
Admission routes1
Has abstractyes

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