Material hardship is associated with posttraumatic stress disorder symptoms among low‐income Black women
Bibliographic record
Abstract
The link between socioeconomic status and posttraumatic stress disorder (PTSD) symptoms is well established. Given that Black women are disproportionately burdened by both poverty and PTSD symptoms, research focusing on these constructs among this population is needed. The current study assessed the association between material hardship (i.e., difficulty meeting basic needs) and PTSD symptoms among 227 low-income Black women in the United States. We explored several potential explanations for the association between poverty and PTSD symptoms (e.g., individuals living in poverty may experience higher levels of trauma exposure; individuals living in poverty may have less access to relevant protective resources, like social support; poverty itself may represent a traumatic stressor). Using robust negative binomial regression, a positive association between material hardship and PTSD symptoms emerged, B = 0.10, p = .009, SMD = 0.08. When trauma exposure was added to the model, it was positively associated with PTSD symptoms, B = 0.18, p < .001, SMD = 0.16, and material hardship remained positively associated with PTSD symptoms, B = 0.10, p =.019, SMD = 0.08. When social support indicators were added to the model, they were not associated with PTSD symptoms; however, material hardship remained significantly associated, B = 0.10, p = .021, SMD = 0.08. In the model with material hardship and trauma exposure, a significant interaction between material hardship and trauma exposure on PTSD symptoms emerged, B = -0.04, p = .027. These results demonstrate the importance of including material hardship in trauma research, assessment, and treatment.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".