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Record W2605659115 · doi:10.7860/jcdr/2017/24811.9419

Screening in Public Health and Clinical Care: Similarities and Differences in Definitions, Types, and Aims – A Systematic Review

2017· review· en· W2605659115 on OpenAlex

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

VenueJOURNAL OF CLINICAL AND DIAGNOSTIC RESEARCH · 2017
Typereview
Languageen
FieldMedicine
TopicHealth Promotion and Cardiovascular Prevention
Canadian institutionsWestern University
Fundersnot available
KeywordsTerminologyPublic healthEpidemiologyMedicineConfusionMEDLINEScopusFamily medicineHealth carePsychologyPolitical sciencePathology

Abstract

fetched live from OpenAlex

INTRODUCTION: The concept of screening can be many times misleading to many people. This may be partly due to the way screening is described and explained in textbooks and journal articles. AIM: To review prominent public health and epidemiology textbooks, dictionaries, and relevant journal publications for definitions and examples of screening, with the aim of identifying common usages and concepts, as well as sources of potential confusion. MATERIALS AND METHODS: Commonly available epidemiology and public health textbooks and peer reviewed journals were searched for definitions and examples of screening. The search located seven journal articles, 10 textbooks, and one dictionary. The search platforms used were Pubmed, BIOSIS, EMBASE, Medline-OVID and Scopus under the Epidemiology and Biostatics subject head listed with Life Sciences. RESULTS: Descriptions of screening give varying emphasis to whether it is a test or a program, the aims of screening, the setting in which it is conducted, eligibility criteria, who initiates and who is intended to benefit and whether the condition being screened is an infectious or chronic disease or a risk-elevated state. Four essentially different 'types' of screening are described, using seven terms and occasionally contradictory examples. The detection of asymptomatic infectious cases is gradually changing from screening to surveillance as part of infection control. CONCLUSION: Voluntary screening programs rely on high participation to be effective and support and trust of the public are essential for the continued success of the public health profession. Consistent terminology is important for patients, providers and policymakers to understand what screening is and is not. Clear definitions are needed if we are to evaluate and communicate the risks and benefits of screening in public health.

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.

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)0.059
metaresearch head score (Gemma)0.094
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Research integrity
Consensus categoriesMetaresearch
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.516
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0590.094
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0050.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.002
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 head0.781
GPT teacher head0.631
Teacher spread0.150 · 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