A Proof-of-Concept Investigation of an Energy Management Education Program to Improve Fatigue and Life Participation in Adults on Chronic Dialysis
Bibliographic record
Abstract
Background:Fatigue and its negative impact on life participation are top research priorities of people on chronic dialysis therapy. Energy management education (EME) is a fatigue management approach that teaches people to use practical strategies (eg, prioritizing, using efficient body postures, organizing home environments) to manage their energy expenditure during everyday life.Objective:The aim of this study is to explore whether EME is associated with improvements in fatigue and life participation in adults on chronic dialysis.Design:Five single-case interrupted time-series AB studies, and follow-up qualitative interviews.Setting:The hemodialysis and peritoneal dialysis units at an academic hospital in Toronto, Canada.Patients:In total, 5 patients on chronic dialysis therapy were purposively selected to represent diversity in age, gender, and modality.Measurements:Brief questionnaires assessing fatigue and life participation were administered weekly during the baseline and intervention periods. Additional validated questionnaires (the Fatigue Impact Scale, 36-Item Short-Form Health Survey [SF-36] Vitality Scale, and Canadian Occupational Performance Measure) were also administered at baseline and post-intervention.Methods:All participants underwent “The PEP Program,” a personalized, web-supported EME program designed to meet the needs of people on dialysis. During the program, participants complete 2 brief web modules about energy management, and then use energy management principles and a problem-solving framework to work on 3 life participation goals during sessions with a trained program administrator. Data were analyzed using visual analysis and the Tau-U statistic for the weekly time-series data, and thematic analysis for the qualitative interviews.Results:Three of 5 participants displayed a consistently positive response to the Personal Energy Planning (PEP) program across multiple measures of fatigue and life participation. Tau-U effect size estimates ranged from small to moderate, according to the time-series data. All 5 participants expressed that the program had benefited them in qualitative follow-up interviews, with the most common reported benefit being that the program made day-to-day activities easier. The format of the program was also said to be feasible and convenient.Limitations:An exploratory, proof-of-concept study that used a small set of participants and lacked an active control comparison.Conclusions:The PEP program might have potential for improving fatigue-related outcomes in people on chronic dialysis. Larger, controlled studies of the program are warranted.
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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 | 0.005 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".