Perceptions of Self-compassion in Undergraduate Women: A Photo Elicitation Study
Bibliographic record
Abstract
Introduction Self-compassion is broadly defined by researchers as compassion directed toward oneself, encompassing self-love, common humanity, and mindfulness. However, beyond specific groups such as adolescents, individuals with anxiety and depression, and female exercisers, how the general public defines and perceives self-compassion remains underexplored. It is important to understand how other individuals define and experience self-compassion so that interventions targeted toward increasing self-compassion are meaningful for participants. Objective The purpose of the present study was to examine perceptions of self-compassion among female university students aged 18 to 24. Methods Semi-structured interviews using photo-elicitation were conducted with nine women. Interviews were transcribed verbatim and analysed using reflective thematic analysis. Results Participants had difficulty defining self compassion. Three themes were generated from the data, including: 1) describing self-compassion as tricky, 2) understanding the self in self-compassion, and 3) self-compassion as a tool. Discussion Participants had difficulty defining self-compassion and often referred to examples of compassion directed towards and received from others to describe the concept. Participants described ways in which self-compassion was adaptive and how practicing self-compassion helped them overcome personal challenges. These findings highlight the importance of psychoeducation to continue to deconstruct misconceptions about self-compassion, and to address conceptual gaps between how self-compassion is defined in the literature and how it is understood by general populations. Conclusion Given the difficulty of defining self-compassion, researchers should focus on knowledge translation strategies to help foster self-compassion in young women.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| 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".