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Record W2187033939 · doi:10.1177/070674370404900701

Geriatric Psychiatry: A Subspecialty Whose Time Has Come

2004· editorial· en· W2187033939 on OpenAlexaffvenueabout
Nathan Herrmann

Bibliographic record

VenueThe Canadian Journal of Psychiatry · 2004
Typeeditorial
Languageen
FieldEconomics, Econometrics and Finance
TopicHealth Systems, Economic Evaluations, Quality of Life
Canadian institutionsHealth Sciences CentreUniversity of TorontoSunnybrook Health Science Centre
Fundersnot available
KeywordsSubspecialtyGeriatric psychiatryCognitionGeriatricsMedicineCompetence (human resources)PsychiatryPsychosocialModalitiesPsychology

Abstract

fetched live from OpenAlex

What is geriatric psychiatry? Simply put, it is the subspecialty dealing with the assessment and management of mental disorders occurring in late life—a period occasionally and somewhat arbitrarily defined as aged 65 years and over (1). This definition falsely simplifies what we do as geriatric psychiatrists and does not acknowledge the scope of practice and the specific skills requisite to this subspecialty. The following are just some of the necessary skills and requirements: an awareness of the physiology of aging and how it affects the pharmacokinetics and pharmacodynamics of psychotropic medications; updated knowledge on the chronic and acute physical illnesses of late life and how they affect cognition and behaviour; a familiarity with medications used to treat chronic medical conditions, in order to evaluate their effects on behaviour and cognition and to avoid potential drug interactions with psychotropics; an expert ability to assess cognitive function and to determine the etiology of cognitive impairment; the ability to work with family systems, using extensive knowledge of community support networks and familiarity with the range of evidence-based psychiatric therapeutic modalities; the capacity to assess competence; and the capacity to deal with the multiple medical or legal issues that arise with elderly patients. Although many of these skills are not the exclusive domain of geriatric psychiatrists, this subspeciality is unique in that the assessment and management of each patient requires these skills. In Canada, geriatric psychiatry is flourishing. The Canadian Academy of Geriatric Psychiatry (CAGP) has over 190 members. The Academy hosts an annual academic meeting and provides residency training and fellowship awards. The CAGP was instrumental in developing the Canadian Coalition for Seniors’ Mental Health (CCSMH)—an organization that includes health professionals, researchers, government officials, caregivers, and seniors’ organizations. The goal of the CCSMH is to support collaborative initiatives to facilitate mental health for seniors through innovation and dissemination of best practices. Canadian geriatric psychiatrists play important roles in international organizations such as Alzheimer’s Disease International, the International Psychogeriatric Association, and the American Association of Geriatric Psychiatry. In 1999, the CAGP cohosted and organized the ninth Congress of the International Psychogeriatric Association—arguably the largest and most successful academic geriatric psychiatry meeting to date. As Canadian geriatric psychiatrists, we hold numerous peer-reviewed research grants, publish in peer-reviewed journals, and sit on international editorial boards. The articles in this issue, covering topics related to depression, dementia, and health services, are only a small sample of our academic activities. We have organized numerous undergraduate and postgraduate training programs in psychiatry across Canada, and we have published widely on educational issues related to geriatric psychiatry (2–6).

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)0.009
metaresearch head score (Gemma)0.022
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 score0.020
Threshold uncertainty score0.068

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0090.022
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0020.002
Science and technology studies0.0070.010
Scholarly communication0.0100.022
Open science0.0020.009
Research integrity0.0150.023
Insufficient payload (model declined to judge)0.0200.010

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 head0.111
GPT teacher head0.351
Teacher spread0.240 · 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".

Quick stats

Citations3
Published2004
Admission routes3
Has abstractyes

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