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Record W2745612583 · doi:10.1186/s12913-017-2481-z

Facilitators and barriers of change toward an elder-friendly surgical environment: perspectives of clinician stakeholder groups

2017· article· en· W2745612583 on OpenAlexafffund
Heather Hanson, Lindsey M. Warkentin, R. Douglas Wilson, Navtej K. Sandhu, Susan E. Slaughter, Rachel G. Khadaroo

Bibliographic record

VenueBMC Health Services Research · 2017
Typearticle
Languageen
FieldPsychology
TopicAging and Gerontology Research
Canadian institutionsUniversity of AlbertaAlberta HealthUniversity of Calgary
FundersUniversity of AlbertaAlberta InnovatesAlberta Innovates - Health Solutions
KeywordsFocus groupMedicineStaffingHealth administrationNursingStakeholderPsychological interventionNursing researchHealth informaticsVulnerability (computing)Public health

Abstract

fetched live from OpenAlex

BACKGROUND: Current acute care surgical practices do not focus on the unique needs of older adults. Adverse outcomes in older patients result from a complex interrelationship between baseline vulnerability and insults experienced during hospitalization. The purpose of this study is to assess the organizational readiness and the barriers and facilitators for the implementation of elder-friendly interventions in the acute care of unplanned abdominal surgery patients. METHODS: This cross-sectional mixed methods study included a convenience sample of clinician stakeholder groups. Eight focus groups were conducted with 33 surgical team members including: 10 health care aides, 6 licensed practical nurses, 6 registered nurses, 4 nurse managers and 7 surgeons, to identify barriers and facilitators to the implementation of an elder-friendly surgical unit. Audio recordings of the focus groups were transcribed verbatim and analysed using interpretive description techniques. Transcripts were coded along with explanatory memos to generate a detailed description of participant experiences. Themes were identified followed by refining the codes. Participants also completed the Organizational Readiness for Implementing Change questionnaire. Differences in organizational readiness scores across clinician stakeholder groups were assessed using Kruskal-Wallice tests. Mann-Whitney tests (Bonferroni's corrections for multiple comparisons) were conducted to assess pair-wise relationships. RESULTS: The focus group data were conceptualized to represent facilitators and barriers to change at two levels of care delivery. Readiness to change at the organizational level was evident in five categories that reflected the barriers and facilitators to implementing an elder-friendly surgical unit. These included education, environment, staffing, policies and other research projects. At the individual level barriers and facilitators were apparent in staff members' acceptance of new roles and duties with other staff, family and patients. Examples of these included communication, teamwork and leadership. The mean change commitment and change efficacy scores on the Organizational Readiness for Implementing Change Questionnaire were 3.7 (0.8) and 3.5 (0.9) respectively. No statistically significant differences were detected between the stakeholder groups. CONCLUSIONS: Staff are interested in contributing to improved care for elderly surgical patients; however, opportunities were identified to enhance facilitators and reduce barriers in advance of implementing the elder-friendly surgical unit intervention.

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)0.030
metaresearch head score (Gemma)0.048
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.030
Threshold uncertainty score0.159

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0300.048
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0080.005
Scholarly communication0.0050.004
Open science0.0010.006
Research integrity0.0030.003
Insufficient payload (model declined to judge)0.0020.000

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 head0.288
GPT teacher head0.501
Teacher spread0.213 · 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 designQualitative
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

Citations24
Published2017
Admission routes2
Has abstractyes

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