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Record W3088818255 · doi:10.2196/22047

Implementation and Evaluation of a Text Message–Based Addiction Counseling Program (Text4Hope-Addiction Support): Protocol for a Questionnaire Study

2020· article· en· W3088818255 on OpenAlexafffundvenue
Vincent I. O. Agyapong, Marianne Hrabok, Wesley Vuong, April Gusnowski, Reham Shalaby, Shireen Surood, Andrew J. Greenshaw, Avininder Aulakh, Adam Abba‐Aji, Mohit Singh

Bibliographic record

VenueJMIR Research Protocols · 2020
Typearticle
Languageen
FieldPsychology
TopicDigital Mental Health Interventions
Canadian institutionsAlberta Health ServicesUniversity of CalgaryUniversity of Alberta
FundersAlberta Children's Hospital FoundationUniversity of AlbertaAlberta Cancer FoundationRoyal Alexandra Hospital FoundationChildren's Hospital FoundationAlberta Health Services
KeywordsAnxietyAddictionCravingMental healthPopulationPsychiatryIntervention (counseling)Brief interventionMedicineClinical psychologyPsychology

Abstract

fetched live from OpenAlex

BACKGROUND: With the emergence of the COVID-19 pandemic, providing counseling to people with drug or alcohol addiction while maintaining physical distance has been challenging. This protocol describes the use of text messaging (as used in the Text4Hope-Addiction Support program) as a convenient, evidence-based, cost-effective, and accessible population-level mental health intervention with high user satisfaction proven in prior research. OBJECTIVE: The project goal is to implement a program of daily supportive text messaging (Text4Hope-Addiction Support) to reduce drug or alcohol cravings as well as anxiety and depression, typically associated with alcohol and substance use disorders. The aim of this study is to evaluate the prevalence of cravings, anxiety, and depressive symptoms; demographic correlates of the same; and the outcomes of the Text4Hope-Addiction Support intervention in mitigating cravings, anxiety, and depressive symptoms. METHODS: Self-administered, anonymous, online questionnaires will be used to assess cravings for the primary substance of addiction (Brief Substance Craving Scale), anxiety (Generalized Anxiety Disorder-7), and depressive symptoms (Patient Health Questionnaire-9). Data will be collected at baseline (onset of receiving text messages), program midpoint (6 weeks), and program end (12 weeks). RESULTS: As of October 2020, data collection is in progress; and it is expected to be completed by fall 2021. Data analysis will include parametric and nonparametric techniques, focusing on primary outcomes (ie, cravings, anxiety, and depressive symptoms) and metrics of use, including the number of subscribers and user satisfaction. CONCLUSIONS: This Text4Hope-Addiction Support project will provide key information regarding the prevalence rates of cravings, anxiety, and depressive symptoms among persons with alcohol and substance use disorders; demographic correlates of cravings, anxiety, and depression; and outcome data related to this scalable population-level intervention. Information from this study will be valuable for addiction care practitioners; it will inform the policy and decision making regarding population-level addiction treatment and support during emergencies. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/22047.

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)0.049
metaresearch head score (Gemma)0.039
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Protocol · Consensus signal: Protocol
Teacher disagreement score0.054
Threshold uncertainty score0.262

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0490.039
Meta-epidemiology (narrow)0.0040.002
Meta-epidemiology (broad)0.0050.004
Bibliometrics0.0020.002
Science and technology studies0.0030.002
Scholarly communication0.0020.002
Open science0.0030.002
Research integrity0.0050.007
Insufficient payload (model declined to judge)0.0540.012

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 head0.436
GPT teacher head0.682
Teacher spread0.246 · 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 designObservational
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

Citations11
Published2020
Admission routes3
Has abstractyes

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