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Record W3107148750 · doi:10.1097/ncc.0000000000000905

A Motivational Interviewing Intervention to Promote CRC Screening

2020· article· en· W3107148750 on OpenAlexaff
Adebola Adegboyega, Mollie E. Aleshire, Amanda T. Wiggins, Kelly Palmer, Jennifer Hatcher

Bibliographic record

VenueCancer Nursing · 2020
Typearticle
Languageen
FieldMedicine
TopicColorectal Cancer Screening and Detection
Canadian institutionsHatch (Canada)
FundersNational Cancer Institute
KeywordsMedicineMotivational interviewingPsychological interventionIntervention (counseling)PopulationIncidence (geometry)Emergency departmentFamily medicinePhysical therapyInternal medicineNursingEnvironmental health

Abstract

fetched live from OpenAlex

BACKGROUND: Appalachian Kentuckians suffer a disproportionate incidence and mortality from colorectal cancer (CRC) and are screened at lower rates (35%) compared with 47% of Kentuckians. OBJECTIVE: The aim of this study was to evaluate the efficacy of a motivational interviewing intervention delivered by trained Lay Health Advisors on CRC screening. METHOD: Eligible participants recruited from an emergency department (ED) completed a baseline survey and were randomized to either the control or the motivational interviewing intervention provided by Lay Health Advisors. Follow-up surveys were administered 3 and 6 months after baseline. To evaluate potential differences in treatment and control groups, t tests, χ2, and Mann-Whitney U tests were used. RESULTS: At either the 3- or 6-month assessment, there was no difference in the CRC screening by group (χ2 = 0.13, P = .72). There was a significant main effect for the study group in the susceptibility to CRC model; regardless of time, those in the intervention group reported approximately 1-point higher perceived susceptibility to CRC, compared with controls (est. b = 0.68, P = .038). Age and financial adequacy had a significant effect related to CRC screening. Older participants (est. b = 0.09, P = .014) and those who reported financial inadequacy (est. b = 2.34, P = .002) reported more screening barriers. CONCLUSION: This pilot study elucidated important factors influencing the uptake of CRC for an ED transient population and this may be useful in the design of future interventions using motivational interviewing in EDs. IMPLICATIONS FOR PRACTICE: Nurses can provide information about CRC screening guidelines and provide referrals to appropriate screening resources in the community.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.979
Threshold uncertainty score0.444

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.074
GPT teacher head0.358
Teacher spread0.284 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designOther design
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

Citations6
Published2020
Admission routes1
Has abstractyes

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