The Effect of Spiritual Well‐Being on Hope Among Hemodialysis Patients: A Latent Profile Analysis
Bibliographic record
Abstract
ABSTRACT Introduction Spiritual well‐being was a critical component of quality of life for hemodialysis patients. However, existing research primarily concentrates on the overall level of spiritual well‐being and associated factors, often neglecting the heterogeneity within the hemodialysis patients regarding their patterns of spiritual well‐being. In addition, the effect of spiritual well‐being on hope levels in hemodialysis patients remains unclear. This study aimed to examine the latent profiles of spiritual well‐being among hemodialysis patients and to explore their effect on hope. Methods A convenience sampling method was employed between July 2023 and March 2024 to recruit hemodialysis patients from three teaching hospitals in Sichuan Province as study participants. All participants complied with a demographic questionnaire, the Functional Assessment of Chronic Illness Therapy‐Spiritual Well‐Being, and the Herth Hope Index. A latent profile analysis was adopted to identify the latent profiles of spiritual well‐being among hemodialysis patients, and hierarchical linear regression was conducted to examine their role in hope. Findings Two latent profiles of spiritual well‐being were identified based on the participants' responses, designated as “Spiritual burnout group”(n = 246, 74.4%) and “Spiritual fulfillment group” (n = 51, 25.6%). Different latent profiles of spiritual well‐being among hemodialysis patients have a significant positive effect on the level of hope (ΔR 2 = 0.224, p < 0.001). Discussion The spiritual well‐being of hemodialysis patients was identified as suboptimal and demonstrated a significant positive association with their level of hope. Healthcare providers could identify the different profiles of spiritual well‐being in HD patients and deliver targeted interventions to guide them to positively live in harmony with themselves, others, and the environment to improve their level of hope.
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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 | 0.004 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".