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Record W3117516503 · doi:10.2196/25062

An Asynchronous, Mobile Text-Based Platform (XatJove Anoia) for Providing Health Services to Teenagers: Protocol for a Quasiexperimental Study

2020· article· en· W3117516503 on OpenAlexvenueno aff
Glòria Saüch Valmaña, Josep Vidal‐Alaball, Victoria Garcia Furió, Giorgia Testoni, Albert Espelt, Katarin Exposito, Francesc Saigí-Rubió, Núria Carré, Ikuska Sanz, Víctor Viçens

Bibliographic record

VenueJMIR Research Protocols · 2020
Typearticle
Languageen
FieldHealth Professions
TopicMobile Health and mHealth Applications
Canadian institutionsnot available
Fundersnot available
KeywordsProtocol (science)MedicineMedical educationHealth careFace-to-faceTelemedicineFamily medicineAsynchronous communicationNursingComputer scienceAlternative medicine

Abstract

fetched live from OpenAlex

BACKGROUND: Due to the COVID-19 pandemic, it is more essential than ever to implement protective measures in primary care centers to ensure patients' safety. This protocol describes a quasiexperimental study on the use of a mobile chat platform as a clinical consultation tool for adolescents and primary health care physicians. OBJECTIVE: The purpose of the quasiexperimental study is to demonstrate that the use of mobile phones and messaging apps increases the number of health consultations. The study will be performed as part of the Health and School program in the Anoia region. METHODS: The quasiexperimental study will compare the number of face-to-face consultations to the number of consultations conducted on XatJove Anoia, as part of the Health in Schools program in the Anoia region. The study will involve the use of a new communication platform (ie, XatJove Anoia) for health care professionals and adolescents, and data on the number of face-to-face consultations will be collected as part of the same program in another region. Data will be collected from secondary schools during the academic year 2020-2021. Statistical analyses will be performed on the data that users will enter in the registration form. These data will be collected by means of a questionnaire, which will be submitted once the questionnaire is closed. The questionnaire will consist of multiple-choice questions, which will allow numerical values to be assigned to various responses in order to carry out statistical analyses. RESULTS: The study is projected to start at the beginning of November 2020 and finish in June 2021, which is when data analysis is expected to start. CONCLUSIONS: The results of the quasiexperimental study may assist in the development and planning of school health programs. TRIAL REGISTRATION: ClinicalTrials.gov NCT04562350; https://clinicaltrials.gov/ct2/show/NCT04562350. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): PRR1-10.2196/25062.

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)0.041
metaresearch head score (Gemma)0.031
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Non-randomized trial · Consensus signal: none
GenreCandidate signal: Protocol · Consensus signal: Protocol
Teacher disagreement score0.055
Threshold uncertainty score0.218

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0410.031
Meta-epidemiology (narrow)0.0040.003
Meta-epidemiology (broad)0.0040.003
Bibliometrics0.0020.002
Science and technology studies0.0050.003
Scholarly communication0.0020.002
Open science0.0040.003
Research integrity0.0060.007
Insufficient payload (model declined to judge)0.0550.011

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 head0.448
GPT teacher head0.686
Teacher spread0.239 · 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 designNon-randomized trial
Domainnot available
GenreProtocol

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

Citations0
Published2020
Admission routes1
Has abstractyes

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