An Interpretive Phenomenological Analysis of Traumatic Experiences: Clarifying Meaning-making Theory
Bibliographic record
Abstract
When coping with a stressful event, some individuals attempt to alter the way in which the situation is understood or appraised to manage their negative emotions and promote adjustment. This is a form of coping known as meaning-making. Meaning-making has been discussed extensively in the coping research literature, however, the variability of terminology, theory, and measurement has hindered researchers’ ability to interpret, understand, and apply the concept. To address this issue, six individuals participated in in-depth semi-structured interviews to discuss their experience of using meaning to cope through a stressful event. Interpretive phenomenological analysis (IPA) was used to examine how meaning was used throughout their coping process and how meaning contributed to the outcomes of their experience. Emergent themes were discovered and compared to two dominant meaning-making theories to identify consistencies, discrepancies, and novel findings. An integrated theory of meaning-making is proposed. Theoretical, methodological, and practical implications of the study are discussed.
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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 | 0.024 | 0.027 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.009 | 0.022 |
| Scholarly communication | 0.009 | 0.010 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.002 | 0.003 |
| 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".