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Record W4389051124 · doi:10.2196/52804

Exploring the Number of Web-Based Behavioral Health Coaching Sessions Associated With Symptom Improvement in Youth: Observational Retrospective Analysis

2023· article· en· W4389051124 on OpenAlexvenueno aff
Darian Lawrence‐Sidebottom, Landry Goodgame Huffman, Aislinn Beam, Rachael Guerra, Amit Parikh, Monika Roots, Jennifer Huberty

Bibliographic record

VenueJMIR Formative Research · 2023
Typearticle
Languageen
FieldPsychology
TopicDigital Mental Health Interventions
Canadian institutionsnot available
Fundersnot available
KeywordsAnxietyCoachingMental healthPsychological interventionDepression (economics)Clinical psychologyPsychiatryPsychologyMedicinePsychotherapist

Abstract

fetched live from OpenAlex

BACKGROUND: Rates of anxiety and depression have been increasing among children and adolescents for the past decade; however, many young people do not receive adequate mental health care. Digital mental health interventions (DMHIs) that include web-based behavioral health coaching are widely accessible and can confer significant improvements in youth anxiety and depressive symptoms. However, more research is necessary to determine the number of web-based coaching sessions that confer clinically significant improvements in anxiety and depressive symptoms in youth. OBJECTIVE: This study uses data from a pediatric DMHI to explore the number of web-based coaching sessions required to confer symptom improvements among children and adolescents with moderate or moderately severe symptoms of anxiety and depression. METHODS: We used retrospective data from a pediatric DMHI that offered web-based behavioral health coaching in tandem with self-guided access to asynchronous chat with practitioners, digital mental health resources, and web-based mental health symptom assessments. Children and adolescents who engaged in 3 or more sessions of exclusive behavioral health coaching for moderate to moderately severe symptoms of anxiety (n=66) and depression (n=59) were included in the analyses. Analyses explored whether participants showed reliable change (a decrease in symptom scores that exceeds a clinically established threshold) and stable reliable change (at least 2 successive assessments of reliable change). Kaplan-Meier survival analyses were performed to determine the median number of coaching sessions when the first reliable change and stable reliable change occurred for anxiety and depressive symptoms. RESULTS: Reliable change in anxiety symptoms was observed after a median of 2 (95% CI 2-3) sessions, and stable reliable change in anxiety symptoms was observed after a median of 6 (95% CI 5-8) sessions. A reliable change in depressive symptoms was observed after a median of 2 (95% CI 1-3) sessions, and a stable reliable change in depressive symptoms was observed after a median of 6 (95% CI 5-7) sessions. Children improved 1-2 sessions earlier than adolescents. CONCLUSIONS: Findings from this study will inform caregivers and youth seeking mental health care by characterizing the typical time frame in which current participants show improvements in symptoms. Moreover, by suggesting that meaningful symptom improvement can occur within a relatively short time frame, these results bolster the growing body of research that indicates web-based behavioral health coaching is an effective form of mental health care for young people.

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)0.010
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.008
Threshold uncertainty score0.019

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.010
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.002
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.356
GPT teacher head0.531
Teacher spread0.175 · 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

Citations4
Published2023
Admission routes1
Has abstractyes

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