Protocol for a national study on emergency response team officers' mental health and well-being: working with police services in Canada
Notice bibliographique
Résumé
Purpose The purpose of our article is to explicate how researchers in Canada can learn from our methodology to work in collaboration with police services and foster research collaborations with “hard-to-reach” groups. Police ERTs have been criticized for being “secretive,” “elite,” distrusting of popular media or outside research, and difficult to contact. Subsequently, researchers often struggle to form partnerships with police agencies to access information regarding ERT data – leading the large majority of research in Canada to rely on mixed samples or secondary data like Access to Information and Privacy Requests (ATIP) or Freedom of Information Requests (FOI) to make bold claims about the state of ERT work in Canada. As such, we provide insights into how we employed study tools and collaborative efforts, including virtual interviewing, which fosters disinhibition among participants to assist in sharing distressing realities, to reach ERTs on a national scale, forming one of the largest qualitative research designs involving ERT in Canada. Design/methodology/approach The current article is a methodological protocol article that explicates our qualitative approach, procedures and ethical decision-making tied to our national Canadian sample exploring the mental health and well-being of police emergency response team (ERT) officers. In the current protocol article, we explain our methodological and qualitative procedures for collecting interview data from part-time and full-time ERT members (n = 117) across a two-year data-collection period in Canada. Respondents come from 20 separate ERTs from 17 unique police services nationally. Thus, we lay out our processes in creating the potentially largest study of ERT in Canada, perhaps even internationally. Findings Because this is a methodological protocol article, no empirical findings were produced. However, we clearly explicate our best practices and methodological approaches to how we collected 117 semi-structured interviews with police services from across Canada. Particular focus is placed on our approach to fostering research collaborations with police services, including but not limited to our iterative ethical choices and pathways forward for research in the field. Our findings are earmarked for other qualitative researchers who are also interested in forming national research projects with police services, as we illuminate how we managed to formulate one of the largest qualitative research designs on ERTs in Canada. Originality/value The current study explicates our procedures in how we conducted one of the first, if not the first, research projects in Canada to qualitatively explicate how help-seeking and pathways to care are different, both good and bad, across provincial, municipal and federal tactical teams, inclusive of factors about workplace cultures, politics, material and human resourcing, access to psychological services, occupational, organizational and operational stress, and stigma. Our article provides pathways forward for other qualitative researchers on how to access, produce and manage a large-scale research project with hard-to-reach public safety personnel, including an emphasis on flexible data collection procedures.
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 machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,051 | 0,055 |
| Méta-épidémiologie (sens strict) | 0,002 | 0,003 |
| Méta-épidémiologie (sens large) | 0,003 | 0,003 |
| Bibliométrie | 0,004 | 0,006 |
| Études des sciences et des technologies | 0,019 | 0,004 |
| Communication savante | 0,007 | 0,003 |
| Science ouverte | 0,004 | 0,004 |
| Intégrité de la recherche | 0,003 | 0,008 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,094 | 0,012 |
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.
score_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 découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».