Self-Perceived Skills Confidence: An Investigative Study of Chiropractic Students in the Early Phases of a College's Clinic Program
Bibliographic record
Abstract
OBJECTIVE: This pilot study surveyed students at early stages of a chiropractic college's clinical curriculum, at the time when integration of patient evaluation and management begins to occur, for collecting data regarding perceived levels of confidence in their spinal analysis and adjusting (manipulation) skills. METHODS: An online, cross-sectional survey based on students' perceptions of their skills was conducted in a basic technique review class for 3 consecutive terms. Questions primarily focused on full-spine radiography (Gonstead-type) analysis, radiographic descriptive analysis, motion palpation analysis, and manual full-spine and diversified spinal manipulation. RESULTS: Of 226 eligible students, 108 participated. The respondents were overall more confident with their analysis skills in full-spine radiographs and descriptive listings than they were with their motion palpation analysis. Self-confidence with spinal manipulation skills followed a general pattern from confident to unconfident to unsure. Students were most confident with prone thoracic spinal manipulation and least confident with seated cervical spinal manipulation. With lumbar and pelvic manipulation, confidence levels varied between side posture pushes, side posture pulls, and prone setups. CONCLUSIONS: Considerably more than half of the respondents were confident enough with their skills to feel comfortable beginning the clinical experience.
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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 | 0.002 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".