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Record W3031269770 · doi:10.1097/md.0000000000020225

The process of obtaining informed consent to research in long term care facilities (LTCFs)

2020· article· en· W3031269770 on OpenAlexaff
Katerina Tori, Markos Kalligeros, Fadi Shehadeh, Rajamohammed Khader, Aman Nanda, Robertus van Aalst, Ayman Chit, Eleftherios Mylonakis

Bibliographic record

VenueMedicine · 2020
Typearticle
Languageen
FieldMedicine
TopicPalliative Care and End-of-Life Issues
Canadian institutionsUniversity of Toronto
FundersSanofi PasteurSanofi
KeywordsInformed consentMedicineLong-term careAutonomyObservational studyDementiaFamily medicineGerontologyNursingAlternative medicine

Abstract

fetched live from OpenAlex

We examined the process of obtaining informed consent (IC) for clinical research purposes in long-term care facilities (LTCFs) in Rhode Island (RI), USA. We assessed factors that were associated with resident ability to consent, such as Brief Interview for Mental Status scores. We used a self-administered questionnaire to further understand the effect of LTCF staff evaluation of ability to consent on residents' autonomy and control over their medical decision making.Observational clinical studyLong-term care setting.LTCF personnel provided us with residents' names, as well as their professional assessment of resident ability to consent. We used Brief Interview for Mental Status (BIMS) scores to assess the cognitive capacity of all residents to assess, and compare it to the assessment provided by LTCF personnel. A logistic regression analysis was performed to determine the relationship between LTCF assessment of resident ability to consent and BIMS score or confirmed diagnosis of dementia as seen from residents' medical charts. A self-administered questionnaire was filled out by the personnel of 10 LTCFs across RI, USA.LTCF personnel in 9 out of 10 recruited facilities reported that their assessment of resident ability to consent was based on subjective assessment of the resident as alert and oriented. There was a statistically significant relationship between the LTCF assessment of resident ability to consent and previously diagnosed dementia (OR: 0.211, 95% CI 0.107-0.415). Therefore, as BIMS scores increased, the likelihood that the resident would be deemed able to consent by LTCF personnel also increased. Furthermore, there was a statistically significant relationship between LTCF assessment of resident ability to consent and BIMS scores (OR: 1.430, 95% CI 1.274-1.605).There is no standard on obtaining IC for research studies conducted in LTCFs. We recommend that standardizing the process of obtaining IC in LTCFs can enhance the ability to perform research with LTCF residents.

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)0.387
metaresearch head score (Gemma)0.343
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesMetaresearch
DomainCandidate signal: Methods · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.613
Threshold uncertainty score0.756

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.3870.343
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0060.003
Science and technology studies0.0060.011
Scholarly communication0.0040.004
Open science0.0040.007
Research integrity0.0050.005
Insufficient payload (model declined to judge)0.0040.001

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 head0.366
GPT teacher head0.532
Teacher spread0.167 · 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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.

Study designQualitative
DomainMethods
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

Citations8
Published2020
Admission routes1
Has abstractyes

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