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Record W7132917751

Multidimensional Experience of Pain in Adults with Advanced Liver Disease

2024· dissertation· W7132917751 on OpenAlexfundaboutno aff
Franklin Gorospe

Bibliographic record

VenueTSpace · 2024
Typedissertation
Language
FieldMedicine
TopicPain Management and Opioid Use
Canadian institutionsnot available
FundersUniversity of Toronto
KeywordsQualitative researchBrief Pain InventoryQuality of life (healthcare)Perspective (graphical)Liver diseaseDiseaseQualitative propertyHepatology
DOInot available

Abstract

fetched live from OpenAlex

BackgroundUnrelieved pain is a significant problem for adult patients living with advanced liver disease such as cirrhosis. Poorly managed pain can reduce the quality of living and dying among this growing population. The lack of research exploring the physical, psychological, and sociocultural dimensions of pain may contribute to insufficient pain appraisal and missed opportunities for treatment. Exploring the patient’s experience with pain, the implications of advanced liver disease severity on pain, and self-care pain management strategies will be instrumental in developing future interventional studies. Purpose The overall aim of this thesis is to examine pain from a multidimensional perspective for patients with advanced liver disease. Design A convergent parallel mixed methods design, comprised of a survey study and a semi-structured interview study, was conducted in a Toronto hepatology clinic between May and September 2021. Methods Following a scoping review study, a cross-sectional survey study was conducted for adult patients with advanced liver disease using convenience sampling. The Brief Pain Inventory (Short Form) was used to collect data on pain characteristics, self-care management, and pain interference data. The qualitative descriptive study of semi-structured interviews was conducted concurrently. Through convenience sampling, participants who completed the Brief Pain Inventory (Short Form) were invited to participate in the semi-structured interviews. The results from the survey and interview studies were integrated using a joint display table that aligned quantitative and qualitative findings according to the research questions. Comparison and synthesis was performed to identify data patterns of convergence or divergence. Findings The design of our cross-sectional and qualitative descriptive studies was shaped by a multidimensional framework that centered on the patient’s pain experience. In our cross-sectional survey of 118 participants, we found that the severity of liver disease was associated with pain intensity and pain interfered with general activity, walking, sleep, and normal work. Participants reported using acetaminophen as the primary pain management strategy. In the qualitative descriptive study, which included 15 participants, we found that pain is multidimensional, and pain interfered with the physical, psychological, and sociocultural domains of a person’s life. The participants described partial relief when using acetaminophen. We found mostly convergence in this mixed methods study where data from the cross-sectional survey study was congruent with the information from the qualitative descriptive study. Conclusion This thesis highlighted how common pain is for patients with advanced liver disease and the multidimensional nature of their pain. Despite the high prevalence and complexity of pain among these patients, effective pain relief remains a challenge for the majority. Understanding the pain experience of adult patients with advanced liver disease using multidimensional pain appraisal tools can inform the effective use of comprehensive pain management strategies to address the interconnected physical, psychological, and sociocultural dimensions of pain.

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)0.003
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.003
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0000.002
Research integrity0.0010.001
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 head0.009
GPT teacher head0.304
Teacher spread0.295 · 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 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
Published2024
Admission routes2
Has abstractyes

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