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Enregistrement W4412686064 · doi:10.3389/frhs.2025.1663204

Editorial: Mental health services for occupational trauma: decreasing stigma and increasing access, volume 2

2025· editorial· en· W4412686064 sur OpenAlexaff
Warren N. Ponder, Natalie Mota, Shay‐Lee Bolton

Notice bibliographique

RevueFrontiers in Health Services · 2025
Typeeditorial
Langueen
DomainePsychology
ThématiqueMental Health Treatment and Access
Établissements canadiensUniversity of Manitoba
Organismes subventionnairesnon disponible
Mots-clésStigma (botany)Mental healthPsychologyPsychiatryMedicine

Résumé

récupéré en direct d'OpenAlex

burnout significantly mediated the relationship between work and family conflict and job satisfaction, but that social support moderated the impact of burnout on job satisfaction. This finding underscores the importance of a supportive relationship at work and at home in mitigating the deleterious effects of burnout. Social support is also key to other frontline healthcare professions, such as nursing. In a systematic review and meta-analysis, Chen et al. (2024) found an inverse relationship between social support and turnover intention, a measure assessing the likelihood that they would leave their jobs. These results may be useful as a guide for nurse managers, healthcare centers, and policy administrators with actionable items to help reduce turnover, by encouraging and promoting social support. Sim et al. (2024) used a sample of South Korean nurses to examine posttraumatic growth (PTG), burnout, and posttraumatic stress disorder (PTSD) during the COVID-19 pandemic. They Ponder et al. Editorial,2 found that purposeful rumination, emotional expression and cognitive emotional regulation (cognitive coping while not being overburdened by negative emotions), increased PTG. Furthermore, they showed that PTG was a protective factor both against burnout and persistent PTSD symptoms. Melander et al. (2024) investigated social support and PTSD in a sample of Danish ambulance personnel and found that social support predicted higher levels of PTSD symptoms, and that informal managerial and collegial support was preferential to formal social support (e.g., debriefing/defusing, formal training for peer support or a manager). Their sample also overwhelmingly preferred seeking out a family member or close friend for support. These studies further illustrated the importance of social support and protective factors against burnout.A sizable minority of U.S. first responders-between 17% and 28%-have prior military service (Baker et al., 2023b;Ponder et al., 2023), and there may be additional institutional (e.g., sensitivity, logistic, and not fitting in) and stigma-related barriers to care that should be considered (Ouimette et al., 2011). Ein et al. (2024) conducted a rapid review to understand barriers and facilitators related to mental health service utilization in veterans. Some examples of primary barriers included system navigation difficulties and negative attitudes toward mental health, while facilitators included mental health literacy and social support. If this population can overcome perceptions of stigma and potential negative impacts on career trajectory, recent research has recommended a transdiagnostic approach that focuses on emotion regulation (Schman et al., 2025). To help break down barriers to care, Meyer et al. (2025) sought to address stigma, logistical barriers, and lack of therapist cultural competency through implementation of the Unified Protocol in a sample of first responders. They found significant reductions in PTSD, depression, and generalized anxiety symptoms among first responders in this uncontrolled trial with treatment delivered by telehealth (Meyer et al., 2025). Ponder et al. Editorial,3 While this special issue fills some of the gaps in the literature, much more can be done.One of the most concerning consequences of burnout and untreated mental health symptoms is an increased risk of substance misuse as a coping mechanism, which can lead to serious career repercussions for members in these occupational roles, including legal consequences. To address this, Fort Worth, Texas created the first Public Safety Employees Treatment Court (PSETC), which gives first responders an opportunity for participation in a specialty diversion court program that, if successfully completed, could dismiss their case. The program typically takes 8to 24-months, and the participants have to adhere to an agreed upon collaborative treatment plan established at entrance into the program. In the initial study, there were reductions in suicidality, generalized anxiety, depression, emotional distress, and PTSD, while resilience was increased (Ponder et al., 2025).It is also important to continue to understand risk and protective factors for burnout and mental health in these populations by conducting additional international epidemiological studies. We propose that an interdisciplinary team of scholars and data analysts should leverage international samples using the same assessments for secondary data analytic comparative studies. This taskforce could function in a similar manner to what the National Vietnam Veterans Readjustment Study achieved for Vietnam veterans in the 1980s (Kulka et al., 1990). Using a nationally representative sample, findings from that study elucidated the scale of mental health problems among veterans and, in 1989, led to the first VA-established National Center for PTSD in Boston (Friedman, 2012). Since this time, the National Center has been at the forefront of the continued study of trauma in veterans and evidence-based solutions to alleviate suffering from posttraumatic stress. First responders deserve the same level of scholarly investigation. We hope this special issue contributes to a larger body of much-needed work in this area.

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Comment cette classification a été obtenuedéplier

Prédiction distillée sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.

score de la tête « metaresearch » (Codex)0,003
score de la tête « metaresearch » (Gemma)0,000
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesMéta-épidémiologie (sens strict), Études des sciences et des technologies, Intégrité de la recherche
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Sans objet · Signal consensuel: Sans objet
GenreSignal candidat: Éditorial · Signal consensuel: Éditorial
Score de désaccord entre enseignants0,084
Score d'incertitude au seuil1,000

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0030,000
Méta-épidémiologie (sens strict)0,0010,001
Méta-épidémiologie (sens large)0,0020,000
Bibliométrie0,0010,001
Études des sciences et des technologies0,0020,000
Communication savante0,0000,001
Science ouverte0,0010,000
Intégrité de la recherche0,0010,001
Charge utile insuffisante (le modèle a refusé de juger)0,0000,000

Scores machine (provisoires)

Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.

Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.

Tête enseignante Opus0,015
Tête enseignante GPT0,379
Écart entre enseignants0,364 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.

Devis d'étudeSans objet
Domainenon disponible
GenreÉditorial

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations0
Publié2025
Routes d'admission1
Résumé présentoui

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