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Record W4405089248 · doi:10.2196/63819

A Web-Based Resource Informed by Cognitive Behavioral Therapy and Positive Psychology to Address Stress, Negative Affect, and Problematic Alcohol Use: A Usability and Descriptive Study

2024· article· en· W4405089248 on OpenAlexaffvenue
Ingrid Serck-Hanssen, Marit Solheim-Witt, Justin J. Anker, Dawn E. Sugarman

Bibliographic record

VenueJMIR Formative Research · 2024
Typearticle
Languageen
FieldMedicine
TopicSubstance Abuse Treatment and Outcomes
Canadian institutionsAlpha Technologies (Canada)
FundersNational Institute on Drug Abuse
KeywordsAffect (linguistics)UsabilityPsychologyPreprintClinical psychologyCognitionDescriptive researchResource (disambiguation)Applied psychologyDescriptive statisticsPsychotherapistPsychiatryWorld Wide WebComputer science

Abstract

fetched live from OpenAlex

BACKGROUND: Research documents that drinking to cope behavior can be disrupted by enhancing emotion regulation and coping skills related to the experience of stress and negative affect. The Alpha Element Self-Coaching Plan incorporates principles of positive psychology and cognitive behavioral therapy to redirect negative thinking and emotions and, therefore, has the potential to benefit individuals who use alcohol to cope with stress. OBJECTIVE: This study aimed to evaluate satisfaction and usability of the online Alpha Element Self-Coaching Plan in order to inform the development of an expanded digital platform based on the Alpha Element framework. METHODS: Participants enrolled in the online program as part of their clinical care were eligible to participate. Twenty individuals (14 women, 6 men) between ages 30-79 (mean 54.5; SD=14.14) completed online questionnaires to assess product performance in areas such as ease of technology use, quality of videos and handouts, and the value of the activities. Participants also completed the System Usability Scale (SUS) and background and demographic information, including alcohol use. RESULTS: Only one participant reported no alcohol use in the past year; 55% (n=11) of participants drank alcohol 2-4 times/month or less and 45% (n=9) reported drinking alcohol 2-3 times/week or more. The average SUS score of 76.38 (SD=17.85) is well above the commonly accepted threshold of 68, indicating high system usability. A majority of the sample (n=16;84%) agreed or strongly agreed that the activities in the program inspired behavioral changes; and most agreed or strongly agreed that the program was engaging (n=16;80%), well-organized (n=18;90%), and easy to follow (n=17;85%). Only two participants endorsed experiencing difficulty using the program on a smartphone. Suggestions for program improvements included expanding the platform, updating the web format, adding user interactivity, and enhancing navigation. CONCLUSIONS: These data suggest that participants were generally satisfied with the online Alpha Element Self-Coaching Plan, and rated usability of the program as favorable. Importantly, a significant portion of participants reported that the program inspired behavioral changes. More research is needed with a larger sample to obtain specific data about alcohol consumption and investigate associations between alcohol use and program components, as well as examine gender differences. Data collected from this study will be used to expand the platform and improve user experience.

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)0.004
metaresearch head score (Gemma)0.008
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: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.022

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.008
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0050.001

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 head0.142
GPT teacher head0.470
Teacher spread0.328 · 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
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
Published2024
Admission routes2
Has abstractyes

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