My Life Is a Roller Coaster: The Subjective Experience of Borderline Personality Disorder
Bibliographic record
Abstract
Abstract This chapter delves into the lived accounts of individuals diagnosed with borderline personality disorder (BPD), employing Interpretative Phenomenological Analysis (IPA) to uncover the intricate layers of their inner worlds. Drawing from in-depth interviews with ten participants, the chapter explores how individuals grapple with shifting moods, relational turmoil, and a pervasive sense of fragmentation. Rather than offering a purely diagnostic overview, it emphasizes personal narratives as rich sources of insight into the challenges and paradoxes of navigating everyday life with BPD. The chapter identifies key experiential domains, such as cognitive patterns, affective responses, interpersonal dynamics, and coping behaviors, while also analyzing how participants respond to their diagnoses and interactions with mental health systems. Special attention is given to the theme of emotional volatility, selected for further investigation through microphenomenological interviewing, highlighting the potential for nuanced and embodied access to emotional experience. The findings not only shed light on subjective suffering but also point toward strategies of adaptation, meaning-making, and resilience, offering a valuable contribution to clinical understanding and qualitative inquiry into complex emotional conditions.
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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 | 0.002 | 0.005 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".