Bibliographic record
Abstract
AIM: Readiness is associated with change, yet there is little understanding of this construct. The purpose of this study was to examine readiness; its referents, associated factors and the resulting consequences. METHODS: In the course of nursing five clients living with multiple sclerosis over a 7-month period using a Reflective Practice Model, data were systematically gathered using open-ended and then more focused questioning. Data collected during 42 client encounters (28 face-to-face encounters; 14 telephone contacts) were analysed using Chinn and Kramer's concept analysis technique. Findings. The concept of readiness was inductively derived. Readiness is both a state and a process. Before clients can create change they need to become ready to change. A number of factors trigger readiness. These include when: (a) clients perceive that a health concern is not going to resolve, (b) a change in a client's physical condition takes on new significance, (c) clients feel better able to manage their stress, (d) clients have sufficient energy, (e) clients perceive that they have adequate support in undertaking change. When one or more of these factors is present clients become ready to consider change. The process of readiness involves recognizing the need to change, weighing the costs and benefits and, when benefits outweigh costs, planning for change. The desire to change and to take action determines clients' degree of readiness. When they experience a high degree of readiness they report less anger, less depression, and view their condition in a more positive light. In contrast, when they experience a low degree of readiness they report feeling depressed, afraid and vulnerable in the face of change. CONCLUSION: Nursing has an important role to play in creating conditions to support change. To fulfil this role, nurses need to be able to assess readiness for change and the factors that enable it and then to intervene in ways that facilitate readiness.
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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 | 0.006 | 0.021 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.010 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.004 | 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".