An Investigation into Attrition and Retention of Rehabilitation Professionals
Notice bibliographique
Résumé
Introduction: Health human resources are scarce worldwide. In occupational therapy (OT), physical therapy (PT), and speech-language pathology (S-LP), attrition and retention issues amplify this situation and contribute to the precarity of health systems. The overarching objective of this doctoral research was to investigate why OTs, PTs and S-LPs stayed in, or left their profession. Specific aims were to: 1) understand how educational and health care environments influence professionals’ decisions to stay in, or leave their profession; 2) investigate reasons for attrition across the three professions; 3) explore stakeholder perspectives on attrition and retention; and 4) explore stakeholder-informed retention strategies for OTs, PTs and S-LPs in Quebec (Canada). Methods: The research included three phases. Phase 1 was a scoping review to map the literature on attrition and retention in OT, PT and S-LP. Guided by cultural-historical activity theory (CHAT) as a theoretical scaffolding, phases 2 and 3 used interpretive description (ID) methodology including inductive and deductive analytical approaches and constant comparative techniques. Phase 2 involved interviews with 51 Quebec OTs, PTs and S-LPs. Phase 3 consisted of focus groups with 16 participants from 4 stakeholder groups: employers, professional educational programs, associations, and regulatory bodies. Results: Fifty-nine papers were included in the scoping review. Main findings highlighted push, pull, and stay factors that shaped professionals’ decisions to leave their profession. Based on the interviews, six themes related to professionals’ perceived factors contributing to attrition and retention, were developed: 1) characteristics of work that make it meaningful; 2) aspects of work that practitioners appreciate; 3) factors of daily work that weigh on a practitioner; 4) factors that contribute to managing work; 5) relationships with different stakeholders that shape daily work; and 6) perceptions of the profession. Through a combined analysis of phase 2 and 3 data, five sets of retention strategies were generated: 1) offering informal and formal benefits; 2) ensuring that work aligns with values; 3) improving alignment of work parameters with professionals’ needs and interests; 4) modifying physical, social, cultural, and structural aspects of a workplace; and 5) addressing how the profession is governed. Discussion: Push, pull and stay factors shape professionals’ decisions in terms of leaving their profession. Push factors (e.g., unsupportive environments) drive professionals out of their profession. Pull factors (e.g., career change) draw professionals away from their profession. In contrast, stay factors (e.g., positive impact on clients) support professionals to remain in their chosen profession. System-level factors (e.g., regulatory bodies’ expectations) influenced participants’ decision to stay in or leave their profession. Regarding retention strategies, professionals focused on improving public awareness of their profession while managers targeted individual-level retention strategies (e.g., providing support). Broader solutions were identified by professional educational programs (e.g., mentorship), associations and regulatory bodies (e.g., scope of practice). The data demonstrate that stakeholders need to adopt an intersectoral approach to designing multi-system retention strategies. Conclusion: This doctoral research makes an original and important contribution to knowledge around attrition and retention in OT, PT and S-LP. Using CHAT and ID, the research enriches concepts of attrition and retention, highlights the multi-level, contributing factors to attrition and retention and provides the first set of stakeholder-informed retention strategies. Designing multi-level strategies will be especially important to ensure the availability of professionals for present and future rehabilitation needs
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 | 0,036 | 0,091 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,007 | 0,011 |
| Études des sciences et des technologies | 0,008 | 0,004 |
| Communication savante | 0,006 | 0,003 |
| Science ouverte | 0,003 | 0,004 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,003 | 0,000 |
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.
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 ».