Commentary on Mäkelä<i>et al</i>. (2011): How many patients must be asked about alcohol before it is enough?
Notice bibliographique
Résumé
Patients want to discuss, and they expect clinicians to discuss, drinking patterns. Clinical good will result if this challenge is taken, but the public health effects might be less impressive than is sometimes suggested. Mäkelä, Seppä & Havio [1] raise several interesting and important questions, among them whether alcohol issues are sufficiently attended to in health-care settings (HCS). For convenience, I will discuss this topic under the name ‘screening and brief intervention’ (SBI). The authors point to a number of vital issues, such as the general population's desire to discuss alcohol issues in HCS, and that fewer than 40% of those with heavy episodic drinking were advised about their drinking habits. There are a number of possible treatment barriers. For instance, Mäkeläet al. show that different groups in (Finnish) society are asked about alcohol in PHC at different rates; e.g. people with lower education are more seldom asked. This violates everyone's equal right to treatment. This can, to my mind, be due to class differences between patient and provider, perhaps mediated by language barriers. In order to promote SBI the authors propose increased alcohol education in the basic training of health-care staff. That is necessary, but not enough; unequal rights to treatment are just as important an issue to target in the training. Also, prevention in general needs to be given a stronger place in the curriculum, and this teaching should probably be integrated into the whole curriculum [2]. The authors argue rightly for more interventions on alcohol. There are at least two reasons to raise the alcohol issue in the consultations: (i) there may be a clinical impact of alcohol in the individual case; and (ii) alcohol is a public health issue. In a clinical case with (possible) alcohol involvement, it is difficult to excuse that alcohol is overlooked. However, the public health issue of SBI is more complicated. When HCS also focuses on risky consumption, before possible problems have developed, it takes on a public health perspective which is in accordance with the Ottawa Charter for Health Promotion [3]. In accordance with this intention, the world has seen an increased focus on life-style issues in health care, such as SBI. In Mäkeläet al.'s paper, the respondents were asked about their attitudes towards being asked about alcohol in HCS, and the issue is discussed from a public health perspective (or ‘population perspective’, as the authors refer to it). All measures undertaken in treatment, including SBI, are subject to priority discussions. SBI have some weaknesses. One can argue that SBI, although proven effective, have been difficult to implement, and as an individual-level policy SBI is a less effective strategy than population-level alcohol policies in preventing alcohol-related ill-health [4]; nor are SBI among the cheapest methods to reach that target. Following these observations, I doubt that SBI ever will have any major public health impact. Nevertheless, it should be implemented in HCS, but primarily for other reasons. An important question raised by this study is what proportion of patients should be screened. Is one-third enough or too few? How can we tell? Perhaps a more reasonable way to look at this issue is to ask ‘What is enough?’. Most would agree that 100% would be a waste of consultation time. Risky alcohol use is only one of many problems that HCS has to attend to, and it would not be feasible to ask all patients about everything. Figures of risky drinking vary around 10–15% in both the general population and in primary health care, so perhaps 30% is a useful figure; I believe it is good enough. As this comment is on science, should we not also question what that figure, a third, stands for? First, what does it say? When ranking what patients and doctors considered important with health encounters, offering preventive work was listed in 17th and 16th place, respectively [5]. This is not very high. Secondly, we know that it is difficult to recall remote alcohol intake. Perhaps it is equally difficult to recall what a doctor or nurse asked several months ago. In the Mäkelä study only the general population was studied. Perhaps a more elucidative result can be reached if both the patients and the doctors/nurses are asked, as also has been carried out [6]. If more patients wish to discuss the alcohol issue, one can assume that in many cases they could also do so. Missed opportunities cannot always be attributed to the care provider. I value greatly the ‘R’ in the FRAMES concept [7]. FRAMES is an acronym for Feed-back, Responsibility, Advice, Menu, Empathy and Self-efficacy, all vital components of a successful brief intervention activity. The ‘R’ emphasizes that the patient/client has responsibility for changing his/her life-style. Patient responsibility is well captured in the following sentences: ‘Asking questions and voicing your concerns’ and ‘Watching for problems and getting help solving them’[8]. There are several ways to increase the SBI activity in HCS. As a complement to stimulate care providers to pay attention to the issue, one could also assist patients (empowerment) to raise the subject of alcohol in the consultation with a doctor or a nurse, access an e-based intervention such as ‘Thrive’[9] or make a telephone call to a help-line. From a public health perspective, it could benefit SBI to stimulate citizens as well as patient organizations to request such service. Ass. Professor Spak receives funding from a university professorship.
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 | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,004 | 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; les deux têtes enseignantes s’accordent sur ce qui est montré ici.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».