Taking the pulse of the health services research community: a cross-sectional survey of research impact, barriers and support
Notice bibliographique
Résumé
Objective This study reports on the characteristics of individuals conducting health service research (HSR) in Australia and New Zealand, the perceived accessibility of resources for HSR, the self-reported impact of HSR projects and perceived barriers to conducting HSR. Methods A sampling frame was compiled from funding announcements, trial registers and HSR organisation membership. Listed researchers were invited to complete online surveys. Close-ended survey items were analysed using basic descriptive statistics. Goodness of fit tests determined potential associations between researcher affiliation and access to resources for HSR. Open-ended survey items were analysed using thematic analysis. Results In all, 424 researchers participated in the study (22% response rate). Respondents held roles as health service researchers (76%), educators (34%) and health professionals (19%). Most were employed by a university (64%), and 57% held a permanent contract. Although 63% reported network support for HSR, smaller proportions reported executive (48%) or financial (26%) support. The least accessible resources were economists (52%), consumers (49%) and practice change experts (34%); researchers affiliated with health services were less likely to report access to statisticians (P<0.001), economists (P<0.001), librarians (P=0.02) and practice change experts (P=0.02) than university-affiliated researchers. Common impacts included conference presentations (94%), publication of peer-reviewed articles (87%) and health professional benefits (77%). Qualitative data emphasised barriers such as embedding research culture within services and engaging with policy makers. Conclusions The data highlight opportunities to sustain the HSR community through dedicated funding, improved access to methodological expertise and greater engagement with end-users. What is known about the topic? HSR faces several challenges, such as inequitable funding allocation and difficulties in quantifying the effects of HSR on changing health policy or practice. What does this paper add? Despite a vibrant and experienced HSR community, this study highlights some key barriers to realising a greater effect on the health and well-being of Australian and New Zealand communities through HSR. These barriers include limited financial resources, methodological expertise, organisational support and opportunities to engage with potential collaborators. What are the implications for practitioners? Funding is required to develop HSR infrastructure, support collaboration between health services and universities and combine knowledge of the system with research experience and expertise. Formal training programs for health service staff and researchers, from short courses to PhD programs, will support broader interest and involvement in HSR.
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 | 0,016 | 0,042 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,001 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,002 | 0,003 |
| Études des sciences et des technologies | 0,002 | 0,001 |
| Communication savante | 0,002 | 0,002 |
| Science ouverte | 0,001 | 0,002 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,002 | 0,001 |
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 ».