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Record W3091795038 · doi:10.1186/s12904-020-00659-1

Designing a Mission statement Mobile app for palliative care: an innovation project utilizing design-thinking methodology

2020· article· en· W3091795038 on OpenAlexafffund
Rakhshan Kamran, Arianna Dal Cin

Bibliographic record

VenueBMC Palliative Care · 2020
Typearticle
Languageen
FieldMedicine
TopicPalliative Care and End-of-Life Issues
Canadian institutionsMcMaster University
FundersMcMaster University
KeywordsPalliative careIntervention (counseling)Health careNursingAdvance care planningMedicinePsychologyPolitical science

Abstract

fetched live from OpenAlex

BACKGROUND: Eliciting individual values and preferences of patients is essential to delivering high quality palliative care and ensuring patient-centered advance care planning. Despite advance care planning conserving healthcare costs by up to 36%, reducing psychological distress of patients and caregivers, and ensuring palliative care delivery in line with patient wishes, less than 33% of adults engage in it. We aimed to develop a mobile application intervention to address the challenges related to advance care planning and improve the delivery of palliative care. METHODS: Design-thinking methodology was used to develop a mobile application, in response to issues prominently identified in current palliative care literature. RESULTS: Issues surrounding communication of patient values from both the patient and provider side is identified as a main issue in palliative care. We designed a mobile application intervention prototype to address this. CONCLUSIONS: Our "Mission Statement" mobile application will allow patients to create a mission statement identifying what they want their care team to know about them, as well as space to identify important values and preferences. Patients will be able to evolve their mission statement and values and preferences over the course of their palliative care journey through the application. Design-thinking methodology is an effective tool to drive healthcare innovation and bridge the gap between research findings and implementation.

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)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.384
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
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 head0.589
GPT teacher head0.523
Teacher spread0.066 · 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.

Study designQualitative
Domainnot available
GenreMethods

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

Citations18
Published2020
Admission routes2
Has abstractyes

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