Coaching-in-Context With Informal Maternal Care Partners of Children With Spinal Cord Injury
Bibliographic record
Abstract
Background: Coaching-in-Context (CinC) is a conversation-based process for working with people that draws on the tenets of positive psychology, is solution-focused and strength-based, and uses evidence-informed coaching techniques that create opportunities for clients to be at their best when engaging in the roles and activities that are desired, required, or expected of them. Objectives: To explore the use of CinC with informal maternal care partners (mothers, grandmothers) of children with spinal cord injury (SCI). Methods: This study was a multicenter, single group, pre-post treatment design. Participants received up to 10 sessions of CinC over a 10-week period. The Canadian Occupational Performance Measure (COPM), Parenting Stress Index, Fourth Edition Short Form (PSI-4-SF), and Pediatric Measure of Participation Short Form (PMoP SF) were administered before and after coaching. The number of coaching sessions completed, missed, and rescheduled was recorded. Descriptive and nonparametric statistics were used to summarize sample characteristics and to evaluate changed COPM scores. PSI-4-SF stress percentiles were examined descriptively. Wilcoxon signed-rank test was used to determine whether there was a statistically significant change between baseline and postcoaching COPM and PMoP SF scores. Results: Nine caregivers enrolled in the study; two had face-to-face coaching, five had phone coaching, and two dropped out. The seven who completed were mothers with an average age of 37.14 (range, 32–45; SD = 5.15) years, with children an average age of 10 (range, 7–13; SD = 2.89) years with paraplegia ( n = 4) or tetraplegia ( n = 3) sustained an average of 6.71 (range, 2–13; SD = 3.73) years prior to the study. Fifty-five (average = 7.86, mode = 9; range, 3–10) coaching sessions were provided; two sessions were missed and nine were rescheduled. After coaching, mean COPM performance scores increased by 2.48 ( SD = 2.01) ( Z = −4.057, p < .001), mean COPM satisfaction scores increased by 2.81 ( SD = 1.33) ( Z = −4.812, p < .001), and PMoP self scores increased ( Z = −2.023, p < .043). Conclusion: This study provides preliminary support for CinC with informal care partners of children with SCI. It also highlights several factors that are important to consider when implementing a coaching program, namely mode of delivery and time commitment.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.002 |
| 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".