The Process of Whole Person Healing: “Unstuckness” and Beyond
Bibliographic record
Abstract
OBJECTIVE: The purpose of the present study was to fully explore the descriptions of patients' experiences of change after receipt of whole systems of complementary and alternative medicine (CAM) treatment. The aim was to develop an understanding of "unstuckness," including characterization of states, processes, and modifying factors. DESIGN: This was a secondary descriptive qualitative analysis, using techniques borrowed from phenomenology and grounded theory. SETTING/LOCATION: Three existent datasets collected at two different universities in the United States and Canada were used in the secondary analysis. PARTICIPANTS: Patients with chronic illnesses (including cancer and multiple nonmalignant conditions) who were treated with different packages of care were interviewed for the primary three studies (n = 76 with over 150 interview sessions). Complete data sets from these participants were used in this secondary analysis. OUTCOME MEASURES/DATA COLLECTION TECHNIQUES: Original transcripts were coded asking specific research questions about the experience of change subsequent to whole systems treatments. RESULTS: Data clearly indicated experiential differences between stuckness, unsticking, and unstuckness. Descriptors and characteristics of each state were identified, as was an initial grounded theory of change or transformation that occurs as an outcome of whole medical systems of CAM. CONCLUSIONS: The results provide preliminary conceptualizations and descriptions of the impact that CAM whole systems interventions may have on the individual' s life courses. This constitutes a first step in the identification, measurement, and evaluation of whole systems outcomes in a clinical setting. The emerging conceptualization of the process from stuckness to transformation may also provide a link between clinical research and systems science theory.
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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 | 0.010 | 0.016 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.036 |
| Scholarly communication | 0.006 | 0.009 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.001 | 0.004 |
| 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".