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Record W3176323171 · doi:10.1101/2021.06.17.21259118

The development and usability testing of two arts-based knowledge translation tools for pediatric procedural pain

2021· preprint· en· W3176323171 on OpenAlexafffundabout
Anne Le, Lisa Hartling, Shannon D. Scott

Bibliographic record

VenuemedRxiv · 2021
Typepreprint
Languageen
FieldMedicine
TopicPediatric Pain Management Techniques
Canadian institutionsUniversity of Alberta
FundersNetworks of Centres of Excellence of Canada
KeywordsUsabilityKnowledge translationBespokePsychologyInfographicExcellenceHealth careMedical educationApplied psychologyMedicineKnowledge managementComputer scienceBusinessAdvertising

Abstract

fetched live from OpenAlex

Abstract Procedures carried out in acute care settings, such as emergency departments (EDs), are among the most common sources of acute pain experienced by children. Such procedures may include intravenous insertions (IVs), venipuncture, and wound irrigation and repair. Inadequately managed procedural pain can cause negative short-term and long-term implications for children, ranging from anxiety to aversion to healthcare. Parents have repeatedly expressed that they do not have the necessary tools to comfort or distract their child during uncomfortable medical procedures. As such, the purpose of this study was to work with parents to develop and evaluate two digital tools for pediatric procedural pain. A whiteboard animation video and interactive infographic were developed following a systematic review and interview with parents. Prototypes were tested in five ED waiting rooms in two Canadian provinces. Sites included those in urban, rural, and remote settings. Overall, parents rated the tools highly, suggesting that engaging with parents to develop arts-based digital tools is a highly effective method in ensuring that parents can understand and utilize complex health information. Author Contributions This study was conducted under the supervision of Drs. Shannon D. Scott (SDS) and Lisa Hartling (LH), PIs for translation Evidence in Child Health to enhance Outcomes (ECHO) Research and the Alberta Research Centre for Health Evidence (ARCHE), respectively. Both PIs designed the research study and obtained research funding through Translating Emergency Knowledge for Kids (TREKK) Networks of Centres of Excellence of Canada (NCE). SDS designed and supervised all aspects of tool development and evaluation. LH co-designed and supervised the qualitative study involving interviews with parents and systematic review of parent experiences and information needs. Tony An developed the infographic. Kassi Shave conducted and analyzed qualitative interviews with parents. Anne Le (AL) conducted usability testing. AL analyzed usability data. All authors contributed to the writing of this technical report and provided substantial feedback. This work was funded by: Networks of Centres of Excellence Klassen, T., Hartling, L., Jabbour, M., Johnson, D., & Scott, S.D. (2015). Translating emergency knowledge for kids (TREKK). Networks of Centres of Excellence of Canada Knowledge Mobilization Renewal ($1,200,000). January 2016 – December 2019. Women and Children’s Health Research Institute (WCHRI) Scott, S.D & Hartling L. (2016). Translating Emergency Knowledge for Kids renewal. Women and Children’s Health Research Institute (matched dollars, $150,000). April 2016 – December 2019. This report should be cited as Le, A., Hartling, L., Scott, S.D. (2021). The development and usability testing of two arts-based knowledge translation tools for pediatric procedural pain. Technical Report. ECHO Research, University of Alberta. Available at: http://www.echokt.ca/research/technical-report s/

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)0.020
metaresearch head score (Gemma)0.043
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 score0.020
Threshold uncertainty score0.106

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0200.043
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0010.001
Scholarly communication0.0020.001
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.134
GPT teacher head0.365
Teacher spread0.231 · 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

Citations3
Published2021
Admission routes3
Has abstractyes

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