Feasibility of a Reflexology and Guided Imagery Intervention During Chemotherapy: Results of a Quasi-Experimental Study
Bibliographic record
Abstract
PURPOSE/OBJECTIVES: To evaluate patient characteristics to predict selection and maintenance of a complementary therapy and the feasibility of a randomized clinical trial (RCT) of complementary therapies. DESIGN: Quasi-experimental, exploratory study, unblinded and nonrandomized. SETTING: A comprehensive cancer center in Michigan. SAMPLE: 96 patients undergoing chemotherapy, predominantly Caucasian women. METHODS: Consenting patients with caregivers could choose a reflexology, guided imagery, guided imagery plus reflexology, or interview-only group. Patients without caregivers were restricted to guided imagery or interview-only groups. Data on demographics, depression, anxiety, and functional status were collected using established instruments. MAIN RESEARCH VARIABLES: Quality of life (QOL) and patient characteristics in relation to complementary therapy choice. FINDINGS: Patients who chose a complementary therapy rather than an interview only tended to be older and in worse health and had higher percentages of lung cancer, late-stage cancers, higher anxiety, depressive symptoms, and physical limitations at baseline. Patients lost from the guided imagery and guided imagery plus reflexology groups had greater symptom severity, depressive symptoms and anxiety, and worse physical and emotional well-being than those lost from the reflexology group. CONCLUSIONS: Patient characteristics influence choice of complementary therapies, highlighting the need for RCTs to evaluate the true effect of complementary therapies on the QOL of patients with cancer. Further research on complementary therapies can help healthcare providers identify patients who are likely to benefit most by addressing nursing-sensitive outcomes. IMPLICATIONS FOR NURSING: An RCT of reflexology as a single therapy for females with breast cancer is most feasible compared to other complementary therapies.
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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 | 0.028 | 0.047 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".