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Record W2619850541 · doi:10.1097/ncm.0000000000000225

Supporting the Support System

2017· article· en· W2619850541 on OpenAlexaff
Jane Harkey, Jared Young, Jolynne “Jo” Carter, Michael Demoratz

Bibliographic record

VenueProfessional Case Management · 2017
Typearticle
Languageen
FieldHealth Professions
TopicFamily and Patient Care in Intensive Care Units
Canadian institutionsNational Capital Commission
Fundersnot available
KeywordsComputer science

Abstract

fetched live from OpenAlex

PURPOSE/OBJECTIVE: The benefits of having a support system, such as social relationships with close friends and family, have been well documented for patients with serious health issues. As scientific evidence has shown, individuals who have the lowest level of involvement in social relationships face a greater mortality risk. Support systems, however, are not infallible. Relationship stress can have a negative impact on people-patient and caregiver alike-behaviorally, psychosocially, and physiologically. The purpose of this article is to encourage case managers who take a patient-centered approach to also consider the existence and extent of the support system, as well as any stresses or tensions that are observable within the support system. Although the case manager is ethically obliged to advocate for the individual receiving case management services, that advocacy can be extended to the support system for the good of all. PRIMARY PRACTICE SETTINGS: This discussion applies to numerous case management practices and work settings including (but not limited to) hospital-based case management, home health, geriatrics, catastrophic case management, mental health, palliative care, and end of life/hospice. FINDING/CONCLUSIONS: As part of the assessment phase of the case management process, case managers determine the extent of the patient's support system or social support network such as family and close friends. Although their advocacy is primarily for the patient receiving case management services, case managers also become aware of the needs of the support system members as they face their loved one's serious illness, severe injury, geriatric care demands, or end of life. Case managers can use their communication skills, especially motivational interviewing, with patients and their support systems to identify stresses and issues that can impact the pursuit of health goals. In addition, case managers ensure that individuals and their support systems are kept informed such as about the health condition, stage of disease, plan of care, treatment options, and care transition plan. IMPLICATIONS FOR CASE MANAGEMENT: Professional case managers expand their role as advocates, serving primarily the patients ("clients") who receive case management services and also members of the support system. By becoming more aware and sensitive to the needs of the support system, case managers help reduce stress on the support system, which can contribute to positive outcomes for patients ("clients").

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)0.005
metaresearch head score (Gemma)0.019
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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.047
Threshold uncertainty score0.156

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.019
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0040.002
Scholarly communication0.0070.004
Open science0.0020.007
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0470.010

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 head0.114
GPT teacher head0.469
Teacher spread0.355 · 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
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
Published2017
Admission routes1
Has abstractyes

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