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Record W2316931140 · doi:10.3928/00989134-20140325-01

The Impact of an Acute Psychiatry Environment on Older Patients and Their Families

2014· article· en· W2316931140 on OpenAlexaboutno aff
Lillian Hung, Elizabeth Loewen, Buffy Bindley, Debra L. McLaren, Travis Feist, Alison Phinney

Bibliographic record

VenueJournal of Gerontological Nursing · 2014
Typearticle
Languageen
FieldArts and Humanities
TopicMental Health and Psychiatry
Canadian institutionsnot available
Fundersnot available
KeywordsMental healthActivities of daily livingPsychologyMedicineEthnographyNursingGerontologyPsychiatrySociology

Abstract

fetched live from OpenAlex

<p>Ethnographic methods (observations and interviews) were used to investigate the physical environment of a geriatric psychiatry unit to understand how it meets the needs of patients with mental health conditions. Four interrelated themes of environmental qualities emerged as central in promoting healing: <i>therapeutic</i>, <i>supportive of functional independence</i>, <i>facilitative of social connections</i>, and <i>personal safety and security</i>. Therapeutic describes the existence of a home-like environment and quality sensory stimulations. Supportive of functional independence refers to the environmental features that make it easy for older adults to mobilize and perform activities of daily living. Facilitative of social connections indicates the provision of social spaces for patients, families, and staff to interact and engage in meaningful activities. Personal safety and security involves having staff in close proximity and minimizing disruptions from confused patients. The evidence suggests that the physical environment is important in making hospitals safe and supportive of healing for older adults with mental health conditions. [<i>Journal of Gerontological Nursing, 40</i>(9), 50–56.]</p><div class="ftAuthorNotes"><p>Ms. Hung is doctoral student and Clinical Nurse Specialist, Ms. Loewen and Ms. Bindley are Clinical Nurse Specialists, Ms. McLaren and Mr. Feist are Registered Psychiatric Nurses, Providence Health Care (PHC), and Dr. Phinney is Associate Professor, University of British Columbia, Vancouver, British Columbia, Canada.</p><p>The authors have disclosed no potential conflicts of interest, financial or otherwise. The authors thank PHC Research Challenge for funding this research.</p><p>Address correspondence to Lillian Hung, MA, RN, Clinical Nurse Specialist, University of British Columbia, School of Nursing, T201-2211 Wesbrook Mall, Vancouver, BC, Canada V6T 2B5; e-mail: lhung@providencehealth.bc.ca.</p></div><div class="ftHistory-received"> Received: October 04, 2013</div><div class="ftHistory-accepted"> Accepted: February 14, 2014</div><div class="ftPubDate"> Posted Online: March 31, 2014</div>

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.880
Threshold uncertainty score0.263

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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 head0.019
GPT teacher head0.287
Teacher spread0.268 · 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

Citations9
Published2014
Admission routes1
Has abstractyes

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