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Record W2765326979 · doi:10.1080/15332985.2017.1395782

Embracing technology: Use of text messaging with adolescent outpatients at a mood and anxiety program

2017· article· en· W2765326979 on OpenAlexaff
Carolyn Summerhurst, Michael Wammes, Justin Arcaro, Elizabeth Osuch

Bibliographic record

VenueSocial Work in Mental Health · 2017
Typearticle
Languageen
FieldPsychology
TopicDigital Mental Health Interventions
Canadian institutionsWestern UniversityLondon Health Sciences CentreLawson Health Research Institute
Fundersnot available
KeywordsText messagingShort Message ServiceAnxietyMoodMental healthText messagePsychologyPsychiatryMedicineClinical psychologyComputer scienceInternet privacy

Abstract

fetched live from OpenAlex

The aim of this study is to assess the use of text message communication with an adolescent (16–25) psychiatric outpatient program. Ninety percent of patients (633) provided a mobile number and agreed to communicate with the program via text. Text messages exchanged with patients from May 2013 to May 2015 (12344) were extracted and analyzed. Results of this study indicate that text messaging was used to communicate frequently and primarily for the scheduling of appointments (58.9%) and was very rarely (0.3%) used inappropriately. The ability of mental health service providers to use text messaging with adolescent outpatients could improve cost-effectiveness and efficiency.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.291
Threshold uncertainty score0.792

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 studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.042
GPT teacher head0.399
Teacher spread0.357 · 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 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

Citations7
Published2017
Admission routes1
Has abstractyes

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