Embodiment, identity formation, and psychological late effects in adolescent and emerging adult cancer survivors
Bibliographic record
Abstract
OBJECTIVE: A cancer experience may complicate how young survivors relate to their bodies. To enhance our understanding, it is necessary to move beyond a narrow focus on bodily appearance. The current study examines how the multidimensional construct of embodiment is related to the developmental trajectories of identity formation and psychological late effects in young survivors. METHODS: Survivors completed self-report questionnaires on embodiment at Timepoint 4 and on identity synthesis and confusion, posttraumatic stress symptoms (PTSS), cancer-related worries, and benefit finding at Timepoints 1-3. Using structural equation modeling, embodiment 3 years later was predicted by developmental trajectories of identity and psychological late effects of cancer. RESULTS: Higher initial levels of identity synthesis and lower initial levels of identity confusion, PTSS, and cancer-related worries were associated with higher levels of embodiment 3 years later. Increases in identity synthesis and decreases in identity confusion were associated with higher levels of embodiment 3 years later. CONCLUSIONS: This longitudinal study highlights the significant value of embodiment in understanding the bodily experiences of young survivors, and reveals how embodiment is related to identity development and psychological late effects of cancer.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".