Living with hope: developing a psychosocial supportive program for rural women caregivers of persons with advanced cancer
Bibliographic record
Abstract
BACKGROUND: Hope is defined by caregivers as the inner strength to achieve future good and to continue care giving. Pilot test findings of a Living with Hope Program (LWHP) suggested it is an acceptable and feasible intervention for use by family caregivers. Although it shows promise in potentially increasing hope and quality of life, further testing and development is needed. Questions remain as to: a) what are the mechanisms through which the LWHP affects outcomes and b) how long it is effective? The overall purpose of this time series mixed method study is the further development and testing of the LWHP by:a. Determining the mechanisms of the LWHP by testing a LWHP conceptual model in which self-efficacy, and loss/grief are hypothesized intermediary variables for changes in hope, and subsequently quality of life among rural women caring for persons with advanced cancer, and;b. Exploring the longitudinal effects of the LWHP on hope, quality of life and health services utilization among rural women caring for persons with advanced cancer. METHODS/DESIGN: Using a time-series embedded mixed method design, data will be collected from 200 rural women caregivers. Following the collection of baseline and outcome variables, the intervention (LWHP) is applied to all subjects. Subjects are followed over time with repeated measures of outcome variables (1 wk, 2 wk, 3, 6 and 12 months). The journals that are completed as part of the LWHP comprise the qualitative data. Health services utilization data will be collected from the Saskatchewan Health Administrative Database for all subjects one year prior and one year after study enrolment.Path analysis will be used to test the model post LWHP, at 1 and 2 weeks. Two-factor ANCOVA will determine patterns over time and Cortazzi's narrative analysis will be used to analyze subjects journals completed as part of the LWHP. DISCUSSION: Data Collection began January 2009 and is expected to be completed within 2 years time. Monthly meetings with data collectors and site collaborators have been instrumental in revisions to the original study protocol such as identifying and adding additional study sites. TRIAL REGISTRATION: Trial Registration; Clinical Trials.Gov. NCT01081301.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".