Photos Sculpt the Stories of Youth: Using Photovoice to Holistically Capture the Lived Experiences and Pain of Youth Who Underwent Spinal Fusion Surgery
Bibliographic record
Abstract
Spinal fusion surgery is one of the most common major surgical procedures in youth. Adolescent idiopathic scoliosis (AIS) is the most frequent reason for corrective spinal fusion. AIS (∼25%–47% of cases) and spinal fusion surgeries are associated with pain, including the development of new onset chronic pain for up to 15% of youth. This research used photovoice approaches to explore the journeys of youth from before, during, and after spinal fusion surgery, to demonstrate their experiences both of and beyond pain. Twenty participants were recruited from a previous study conducted by the senior author’s lab. Participants captured photos/videos in their daily life (Phase 1); collected previously taken photos/videos from before/during/after their surgery (Phase 2); and participated in individual interviews to reflexively discuss the meaning behind photos/videos (Phase 3). Before interviews, a questionnaire was administered to assess pain characteristics. Nineteen girls/women with scoliosis and one boy/man with kyphosis (12–19 years old, M age = 16 years) participated; they identified as white (80%), other (15%), and Southeast Asian (5%). The researchers used a reflexive thematic analysis approach, which generated five themes: (1) body aesthetic versus machine; (2) expectations and anticipation of surgery/outcomes; (3) desire of normalcy and freedom; (4) navigating a hoped-for positive surgery experience; and (5) the journey sculpts identity formation and sense of self. Findings support youth advocacy, underscoring the need to validate youth concerns and inform healthcare professionals of the importance of individualized care. Youth perspectives highlighted opportunities for optimizing surgery/healthcare experiences and the psychosocial impacts of scoliosis on body image and appearance.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.124 | 0.037 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.002 | 0.004 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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; both teacher heads agree on what is shown here.
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".