MétaCan
Menu
Back to cohort
Record W3081978009 · doi:10.1080/07317115.2020.1808134

Risk Factors for Cannabis-Related Mental Health Harms in Older Adults: A Review

2020· review· en· W3081978009 on OpenAlexaff
Amanda Hudson, Pamela Hudson

Bibliographic record

VenueClinical Gerontologist · 2020
Typereview
Languageen
FieldMedicine
TopicCannabis and Cannabinoid Research
Canadian institutionsDalhousie UniversityUniversity of Prince Edward IslandHealth PEI
Fundersnot available
KeywordsCannabisPsychosocialMental healthPsychiatryPsychological interventionPopulationEffects of cannabisPsychologyMedicineClinical psychologyEnvironmental health

Abstract

fetched live from OpenAlex

Objectives: This paper reviews research on the topic of cannabis use and mental health harms in older adults and illustrates potential contributing factors and special clinical considerations for working with this population. Known risk factors for cannabis-related mental disorders and mental health problems are outlined, first for the general population and then specifically for older adults.Methods: Studies were identified through online databases using a variety of search words. Articles were included in the review if they were peer-reviewed or published by a reputable national organization, published in English, and were pertinent to the topic of mental health harms of cannabis use.Results: Risk factors that emerged from the literature review aligned with the following categories: (1) patterns of use (i.e., potency of product, frequency of use), (2) personal characteristics (i.e., age, sex, social demographics), (3) psychosocial constructs (motivations, perceptions), and (4) morbidities (mental health, medication interactions).Conclusions: Frequent use was associated with increased risk for mental health consequences related to cannabis use. Certain motives for use (i.e., using to cope, using as a sleep aid) may increase susceptibility to cannabis-related harms, although more empirical work is required. Mental health conditions may predispose to cannabis-related harms through a variety of mechanisms, including increased vulnerability for cannabis-related psychiatric disorders, poorer prognosis for preexisting psychiatric disorders, and possibility of cannabis-medication interactions. Personal characteristics (younger age, being male, lower socioeconomic status) predict more frequent cannabis use, which may dispose to adverse outcomes.Clinical Implications: Predictors of cannabis-related harms hold relevance for public health messaging, as well as clinical interventions. Understanding how cannabis interacts with sociodemographic factors, mental health morbidities, and medications is crucial in providing accurate guidance to patients about their recreational cannabis use and in informing prescriber decisions about medicinal cannabis.

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)0.003
metaresearch head score (Gemma)0.007
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Research integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.570
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.007
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0080.003
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.003
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 head0.119
GPT teacher head0.484
Teacher spread0.364 · 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.

Study designNot applicable
Domainnot available
GenreReview

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

Citations29
Published2020
Admission routes1
Has abstractyes

Explore more

Same venueClinical GerontologistSame topicCannabis and Cannabinoid ResearchFrench-language works237,207