Nature and perceived benefits of patient-initiated consultations in community pharmacies: A population survey
Notice bibliographique
Résumé
The role of community pharmacists in enhancing patient care has received increased attention. However, there is a paucity of literature on the nature, frequency, and perceived impacts of patient-initiated consultations in community pharmacies. We aim to describe the profile of patients seeking advice from community pharmacists as well as the nature and impact of those consultations. A survey was conducted with Quebec adults who had consulted a pharmacist in the previous four weeks. Data was collected in 2017 and 1104 agreed to participate (25.3%). Of those, 93 were withdrawn due to incomplete data and 98 failed to meet the inclusion criteria. Sample representativeness was ensured by quota sampling (gender, age) after stratification by region. Among the 913 respondents, 46% had consulted a pharmacist more than once during the four weeks prior to the survey. Individuals with a university degree consulted less often than those without (1.97 vs. 2.17 times; t = 2.0; p < .05) and participants with one or several chronic diseases consulted more frequently than those having no chronic disease (2.18 vs. 1.94 times; t = 5.7; p < .05). Older adults (55+) consulted more often for themselves compared to younger (18–34) and middle-aged (35–54) adults (1.53 vs. 1.31 vs. 1.44 times; F = 4.0; p < .05). Concerning the consultations, 58% were related to medications and 33% to health problems. In terms of impacts, 81% of consultations were perceived to have prevented the use of other healthcare resources. Patient satisfaction with their consultations was high with an average score of 8.75 on a 10-point scale (SD = 1.63). Findings reveal that the reasons for consulting a community pharmacist are diverse, most being related to medications or health issues. Patients reported that pharmacists were able to manage most consultations without referring them to other health care resources or professionals, and their satisfaction with their consultation was high. Community pharmacy; counselling; patient satisfaction; primary health care; surveys and questionnaires.
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 enseignantsNi 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.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,007 | 0,002 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,001 |
| Études des sciences et des technologies | 0,001 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,004 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 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 tête enseignante, 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 ».