Informed patients: legal fiction or reality?
Notice bibliographique
Résumé
Background: Shared decision making is based on the assumption that it is acceptable, even important and probably favourable to involve patients in the decision-making process. To achieve this goal, patients need to be informed about the content and the aim of the treatment, alternative treatments, possible side-effects and risks. In the Netherlands and Finland, the right of informed consent is protected by the ‘Law on Medical Treatment’. In Belgium such a law secondary is being prepared, while in the United Kingdom and Germany guidelines were developed. Aim: The aim of the presentation is to investigate (1) the importance patients attach to LMT-items; (2) the extent to which general practitioners put the LMT-items into practice; and (3) the contribution of information-giving about medical and therapeutical issues to shared decision making. Methods: Data was derived from the video-observation study being part of the Second Dutch National Survey of General Practice. In 86 practices video-recordings of consultations were made of 142 GPs and 2784 patients. Patients filled in questionnaires before and just after their visit. Doctor-patient communication of 15 patients per GP was rated by observers by means of Roter’s Interactional Analysis System (RIAS), who also registered - among others - data on LMT-items. Only patients of 18 years and older were included (N=1787). Data were analysed by t-tests, Pearson’s correlation coefficient and logistic regression analysis. Results: Patients attach much importance to be informed about the treatment and its side-effects, alternative treatments, and shared decision making (75-90%). However, three quarter of the patients liked to leave the final decision to the GP. In the patients’ eyes, agreement about relevance and performance of the LMT-items was high for treatment information, but less for information about side-effects and alternatives. The (more objective) video-observers, however, rated lower percentages. Many patients who wanted shared decision making were involved indeed, but still 30% was not. In 72% of the consultations the GP took the final decision. Male and lowly educated patients liked to leave the decision to the GP, whereas highly educated patients wanted shared decision making. GPs gave room to and encouraged older patients more than younger ones to shared decision making. Information about medical/therapeutic issues (as rated by RIAS) appeared not to be related to shared decision making (taking into account relevant characteristics). Conclusions: Relevance and performance of LMT-items do not always agree, but perhaps information is not always required or desired. Patients seem to have a positive picture of GPs’ performance of the TML-items. Not all patients want shared decision making, but those who do are often involved in the decision process. More research into the decision making process is recommended. (aut. ref.)
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 | 0,034 | 0,139 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,001 | 0,003 |
| Études des sciences et des technologies | 0,005 | 0,042 |
| Communication savante | 0,007 | 0,011 |
| Science ouverte | 0,002 | 0,005 |
| Intégrité de la recherche | 0,007 | 0,011 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,006 | 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 ».