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Record W4229037404 · doi:10.1016/j.ridd.2022.104239

Mixed methods intervention studies in children and adolescents with emotional and behavioral disorders: A methodological review

2022· review· en· W4229037404 on OpenAlex
Sergi Fàbregues, Cristina Mumbardó‐Adam, Elsa Lucia Escalante‐Barrios, Quan Nha Hong, Dick Edelstein, Kathryn Vanderboll, Michael D. Fetters

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueResearch in Developmental Disabilities · 2022
Typereview
Languageen
FieldHealth Professions
TopicHealth Policy Implementation Science
Canadian institutionsUniversité de Montréal
Fundersnot available
KeywordsPsycINFOIntervention (counseling)PsychologyMEDLINEScopusClinical psychologyEmotional and behavioral disordersQualitative researchApplied psychologyPsychiatry

Abstract

fetched live from OpenAlex

BACKGROUND: Mixed methods intervention studies can improve the accuracy of interventional evaluations in the field of emotional and behavioral disorders by helping researchers gain a more nuanced understanding of how a particular intervention works. However, no studies to date have systematically examined the ways in which this type of studies have been carried out and reported. AIM: To examine the methodological features and reporting practices found in mixed methods intervention studies in children and adolescents with emotional and behavioral disorders. METHOD: Methodological review based on a systematic search from inception to July 2021 in Embase, Medline, PsycINFO, and SCOPUS, and a hand search in seven journals. RESULTS: We found 30 studies, most of them published since 2019. These studies reported several patterns of mixed methods use which illustrated the unique insights that researchers can gain by using this approach. We identified several ways that authors could more clearly report the justification for using a mixed methods approach, the description of the design used, and the evidence of integration of the quantitative and qualitative components. CONCLUSION: We make recommendations for improving the reporting quality of mixed methods intervention studies in the field of emotional and behavioral disorders.

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.

Direct model labels (unvalidated)

Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.

Model armCategoriesStudy designConfidence
gemmaMetaresearch
Domain: Methods · Genre: Review
About the Canadian research system: no · About a Canadian topic: no
Systematic reviewmedium
gptMetaresearch
Domain: Methods · Genre: Review
About the Canadian research system: no · About a Canadian topic: no
Other designhigh
models splitAgreement compares identical category sets and study designs across arms.

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)0.032
metaresearch head score (Gemma)0.011
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow)
Consensus categoriesMetaresearch
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.833
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0320.011
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0000.002
Research integrity0.0000.002
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 head0.953
GPT teacher head0.797
Teacher spread0.156 · 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