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Record W4386407130 · doi:10.1097/njh.0000000000000977

A Standard Practice Protocol for Addressing Depression in a Hospice Setting

2023· article· en· W4386407130 on OpenAlexaff
Beth Ann Williams, Carrie Cormack

Bibliographic record

VenueJournal of Hospice and Palliative Nursing · 2023
Typearticle
Languageen
FieldMedicine
TopicPalliative Care and End-of-Life Issues
Canadian institutionsRegistered Nurses' Association of Ontario
Fundersnot available
KeywordsDepression (economics)PsychosocialMedicineProtocol (science)ReferralLimitingMoodPsychiatryNursingAlternative medicine

Abstract

fetched live from OpenAlex

Depression can worsen physical suffering and psychiatric distresses in individuals with life-limiting illnesses and is associated with increased rates of pain, fatigue, dyspnea, and worse survival outcomes. Evidence supports protocol development to address depression in the hospice setting using validated screening tools and a process for referral and treatment. After protocol development and integration of validated screening tools into the electronic medical record, newly admitted patients meeting inclusion criteria were screened during the social workers' initial psychosocial assessment. Patients were referred for pharmacological and nonpharmacological treatment strategies based on the severity of depression detailed in the protocol. Of all patients who met inclusion criteria, 100% were screened using the Patient Health Questionnaire-2 with 52% being identified as having some severity of depression, 26% being appropriately referred for treatment, and 50% receiving a pharmacological strategy, whereas 26% received nonpharmacological strategies. There was a statistically significant difference in severity of depression found between those identified as having a depressed mood preintervention and those with some severity of depression using a validated screening tool postintervention. Implementing a standardized practice protocol to address depression in a hospice setting allowed for consistent evaluation through the use of validated screening tool(s) and increased recognition of those with symptoms of depression.

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)0.001
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.290
Threshold uncertainty score0.495

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.210
GPT teacher head0.548
Teacher spread0.338 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
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

Citations0
Published2023
Admission routes1
Has abstractyes

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