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Record W2621589897 · doi:10.1111/jgs.14979

The Geriatrics 5M's: A New Way of Communicating What We Do

2017· letter· en· W2621589897 on OpenAlexaffabout
Mary E. Tinetti, Allen Huang, Frank Molnar

Bibliographic record

VenueJournal of the American Geriatrics Society · 2017
Typeletter
Languageen
FieldMedicine
TopicDementia and Cognitive Impairment Research
Canadian institutionsOttawa HospitalUniversity of Ottawa
Fundersnot available
KeywordsMedicineGeriatricsGerontologyMEDLINEFamily medicineMedical educationPsychiatry

Abstract

fetched live from OpenAlex

Over the past few decades, specialists in geriatric medicine have created and disseminated evidence-based management approaches for an increasing number of health conditions. Geriatrics care models inform practice in all health settings. Many of these advances were first reported in the pages of this journal.1 Despite these significant successes, geriatrics remains unrecognized and underappreciated by our colleagues, health system leaders, and the public. It is likely that one factor accounting for our obscurity is our failure to define and communicate our value to society and ourselves. Those outside the field have difficulty understanding what geriatrics is and what geriatricians do. We contribute to this lack of clarity. We are experts in complexity but are often bad at communicating simply. Our well-intentioned efforts to be inclusive and comprehensive lead to the creation of long, complex descriptions of what we do that further compromises understanding while eroding interest in, and support of, our field. In 2013, Dr. George Heckman suggested that, rather than developing complex, comprehensive definitions, we focus on a few core competencies and package them in a manner that will resonate with the public and with decision-makers.2 Such an approach will not capture 100% of what geriatricians do, but it is likely that the “branding” of our specialty will improve its visibility while enhancing understanding of our unique contribution to health care. On April 21, 2017, Dr. Mary Tinetti gave the keynote address at the Canadian Geriatrics Society Annual meeting in Toronto, Canada. During that address, she presented the concept of the Geriatric 5Ms—a communication framework to describe core competencies in geriatrics in a manner that those inside and outside the field will understand and remember. The 5Ms represent a serendipitous convergence of two independent efforts: one which occurred in Ottawa, Canada in 2015 which resulted in the “4Ms” representing Mind, Mobility, Medications and Multicomplexity, and the other activities in the United States during 2016 through the Institute for Healthcare Improvement–led Age-Friendly Health System initiative, spearheaded and supported by the John A. Hartford Foundation.3 The consolidated Geriatric 5Ms (which not coincidentally can be counted on the fingers of one hand) are Mind, Mobility, Medications, Multicomplexity, and Matters Most to Me. To learn about them, go to www.geriatricsjournal.ca → Update: The Public Launch of the Geriatric 5Ms (April 28, 2017).4 The Geriatric 5Ms concept is a simply conveyed yet comprehensive training and communication tool that allows us to communicate our expertise in easily understood and remembered terms. We hope members of geriatrics associations around the world find the Geriatric 5Ms helpful in their advocacy, communication, and training efforts to enhance our visibility and forge a collective identity. Conflict of Interest: The authors declare no competing interests. Author Contributions: All authors contributed equally to the writing and editing of the manuscript. Sponsor's Role: There was no sponsor for this manuscript.

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)0.036
metaresearch head score (Gemma)0.071
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Editorial · Consensus signal: none
Teacher disagreement score0.036
Threshold uncertainty score0.190

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0360.071
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0050.002
Science and technology studies0.0160.028
Scholarly communication0.0180.043
Open science0.0050.023
Research integrity0.0190.043
Insufficient payload (model declined to judge)0.0140.005

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 head0.029
GPT teacher head0.332
Teacher spread0.303 · 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 designNot applicable
Domainnot available
GenreEditorial

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".

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Citations264
Published2017
Admission routes2
Has abstractyes

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