Religious/Spiritual Abuse, Meaning-Making, and Posttraumatic Growth
Bibliographic record
Abstract
While religion and spirituality (R/S) have been broadly studied for their positive mental health impacts, instances of abuse within religious or spiritual contexts remain under-researched. This scoping review aims to elucidate how individuals experiencing such abuse navigate their trauma, find meaning, and foster posttraumatic growth (PTG). The research was conducted using a scoping review methodology as a guide, and 10 articles were selected based on predefined inclusion and exclusion criteria. Synthesizing these articles revealed the following three central themes: recognizing abuse, relaying one’s story, and redefining spirituality. Survivors often face disbelief and stigma, hindering their ability to process their experiences. However, narrative sharing enables many to reclaim agency and healing through validation and the integration of the narrative into one’s life story. Additionally, survivors often transform spirituality, shifting from rigid frameworks to more nuanced and flexible understandings of the Divine and self. These findings underscore the importance of trauma-informed, spiritually sensitive clinical approaches that validate survivors’ experiences, facilitate narrative sharing, and support spiritual redefining. Future research must address knowledge gaps, including the development of improved assessment tools, exploration of effective treatment strategies, and the unifying of terms to better support survivors’ healing journeys and promote meaning-making and PTG in the aftermath of R/S abuse.
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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 | 0.006 | 0.023 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| 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".