Journalists covering the refugee and migration crisis are affected by moral injury not PTSD
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Objective To explore the emotional health of journalists covering the migrations of refugees across Europe. Design Descriptive. A secure website was established and participants were given their unique identifying number and password to access the site. Setting Newsrooms and in the field. Participants Responses were received from 80 (70.2%) of 114 journalists from nine news organisations. Main outcome measures Symptoms of PTSD (Impact of Events Scale-revised), depression (Beck Depression Inventory-Revised) and moral injury (Moral Injury Events Scale-revised). Results Symptoms of PTSD were not prominent, but those pertaining to moral injury and guilt were. Moral injury was associated with being a parent ( p = .031), working alone ( p = .02), a recent increase in workload ( p = .017), a belief that organisational support is lacking ( p = .046) and poor control over resources needed to report the story ( p = .027). A significant association was found between guilt and moral injury ( p = .01) with guilt more likely to occur in journalists who reported covering the migrant story close to home ( p = .011) and who divulged stepping outside their role as a journalist to assist migrants ( p = .014). Effect sizes ( d) ranged from .47 to .71. Conclusions On one level, the relatively low scores on conventional psychometric measures of PTSD and depression are reassuring. However, our data confirm that moral injury is a different construct from DSM-defined trauma response syndromes, one that potentially comes with its own set of long-term maladaptive behaviours and adjustment problems.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 it