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Record W1991471365 · doi:10.1089/jpm.2006.9.948

Quality of Life of Patients with Advanced Cancer and Acquired Immune Deficiency Syndrome and their Family Caregivers

2006· article· en· W1991471365 on OpenAlexaboutno aff
Deborah Witt Sherman, Xiang Y. Ye, Christina McSherry, Miriam Calabrese, Maria Alice Fortes Gatto

Bibliographic record

VenueJournal of Palliative Medicine · 2006
Typearticle
Languageen
FieldMedicine
TopicCancer survivorship and care
Canadian institutionsnot available
FundersNational Cancer Institute
KeywordsMedicineQuality of life (healthcare)CancerPalliative careFamily caregiversConfoundingGerontologyInternal medicineNursing

Abstract

fetched live from OpenAlex

BACKGROUND: Although definitions of palliative care include quality of life as a central concern, little research has been published about both the quality of life of patients with advanced illness and their family members, and particularly the changes in their quality of life over time. OBJECTIVES: The aims of this prospective longitudinal pilot study were to: (1) establish the reliability of multidimensional quality of life instruments based on patients with acquired immune deficiency syndrome (AIDS) and patients with cancer and caregivers; (2) identify differences in quality of life between patients with advanced AIDS and cancer, and their family caregivers with consideration of mortality, attrition, and compliance rates; and (3) examine differences in demographic variables and their potential confounding effect when measuring quality of life. METHODS: The sample included 101 patients with advanced illness (63 patients with advanced AIDS and 38 with advanced cancer) and 81 family caregivers (43 caregivers for patients with AIDS and 38 caregivers for patients with cancer). Data collection involved the monthly completion of the McGill Quality of Life Questionnaire (MQOL) for patients, and the Quality of Life Scale (QLS) for family caregivers. RESULTS: Reliability of the MQOL and QLS were established for patients with AIDS and patients with cancer and caregivers. Based on the MQOL, patients with advanced AIDS reported a lower total quality of life, and lower psychological quality of life, and a higher physical quality of life compared to patients with advanced cancer. There were no significant differences between patient groups on the one-item physical well-being subscale, or the existential well-being, and support subscales. Based on the QLS, AIDS caregivers reported greater overall quality of life, greater psychological well-being, and greater spiritual well-be- ing than cancer caregivers. There were no significant differences between AIDS and cancer caregivers with respect to physical or social well-being. From baseline entry into the study to third month of participation, there were no significant changes in total quality of life scores for patient or caregiver groups, although trends indicated a moderately high total quality of life over time for all patient and caregiver groups. Fourteen of 63 (22%) patients with AIDS patients died, while 19 of 38 (50%) patients with advanced cancer died after enrollment. Forty-six of 63 (73%) patients with advanced AIDS withdrew for various reasons other than death at some point during the 12 month time frame of the study, while 15 of 38 (39%) patients with advanced cancer withdrew. There were significant differences on all demographic variables for patients with advanced cancer and AIDS. Only religious affiliation was significantly related to quality of life for patients with AIDS, while gender was the only variable associated with quality of life for patients with cancer. There were significant differences on all demographic variables between caregivers with the exception of gender and living arrangements. Only the relationship between patients and caregivers and marital status were significantly associated with quality of life for cancer caregivers. CONCLUSIONS: In palliative care research, the challenge is to design studies that will capture changes in the domains of quality of life over time, yet will minimize participant burden and subsequent attrition rates. By measuring quality of life as an outcome variable in palliative care, health professionals can identify changes in the domains of quality of life over time for various patient populations and their family caregivers, and respond with appropriate interventions, which promote or maintain their quality of life even as death approaches.

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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.022
Threshold uncertainty score0.378

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.020
GPT teacher head0.291
Teacher spread0.271 · 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

Citations31
Published2006
Admission routes1
Has abstractyes

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