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Record W2759397041 · doi:10.1186/s12913-017-2632-2

Knowledge translation tools for parents on child health topics: a scoping review

2017· review· en· W2759397041 on OpenAlexaff
Lauren Albrecht, Shannon D. Scott, Lisa Hartling

Bibliographic record

VenueBMC Health Services Research · 2017
Typereview
Languageen
FieldHealth Professions
TopicHealth Policy Implementation Science
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsKnowledge translationMedicineNursing researchPublic healthHealth administrationChecklistHealth informaticsHealth services researchFamily medicineMEDLINEMedical educationNursingPsychologyKnowledge managementComputer science

Abstract

fetched live from OpenAlex

BACKGROUND: An emerging field of knowledge translation (KT) research has begun to focus on health consumers, particularly in child health. KT tools provide health consumers with research knowledge to inform health decision-making and may foster 'effective consumers'. Thus, the purpose of this scoping review was to describe the state of the field of previously published effectiveness research on child health-related KT tools for parents/caregivers to understand the evidence-base, identify gaps, and guide future research efforts. METHODS: A health research librarian developed and implemented search strategies in 8 databases. One reviewer conducted screening using pre-determined criteria. A second reviewer verified 10% of screening decisions. Data extraction was performed by one reviewer. A descriptive analysis was conducted and included patient-important outcome classification, WIDER Recommendation checklist, and methodological quality assessment. RESULTS: Seven thousand nine hundred fifty two independent titles and abstracts were reviewed, 2267 full-text studies were retrieved and reviewed, and 18 articles were included in the final data set. A variety of KT tools, including single- (n = 10) and multi-component tools (n = 10), were evaluated spanning acute (n = 4), chronic (n = 5) and public/population health (n = 9) child health topics. Study designs included: cross-sectional (n = 4), before-after (n = 1), controlled before-after (n = 2), cohort (n = 1), and RCTs (n = 10). The KT tools were evaluated via single primary outcome category (n = 11) and multiple primary outcome categories (n = 7). Two studies demonstrated significant positive effects on primary outcome categories; the remaining studies demonstrated mixed effects (n = 9) and no effect (n = 3). Overall, methodological quality was poor; studies lacked a priori protocols (n = 18) and sample size calculations (n = 13). Overall, intervention reporting was also poor; KT tools lacked description of theoretical underpinnings (n = 14), end-user engagement (n = 13), and preliminary research (n = 9) to inform the current effectiveness evaluation. CONCLUSIONS: A number of child health-related knowledge translation tools have been developed for parents/caregivers. However, numerous outcomes were used to assess impact and there is limited evidence demonstrating their effectiveness. Moreover, the methodological rigor and reporting of effectiveness studies is limited. Careful tool development involving end-users and preliminary research, including usability testing and mixed methods, prior to large-scale studies may be important to advance the science of KT for health consumers.

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)0.042
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow), Science and technology studies, Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.530
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0420.003
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0040.001
Bibliometrics0.0010.001
Science and technology studies0.0100.000
Scholarly communication0.0000.001
Open science0.0020.000
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0000.002

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 head0.949
GPT teacher head0.820
Teacher spread0.129 · 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.

Study designSystematic review
Domainnot available
GenreReview

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

Citations35
Published2017
Admission routes1
Has abstractyes

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