Occupational therapy contributions to people with neurological conditions: Time to set research priorities
Notice bibliographique
Résumé
People with neurological conditions experience many challenges in their daily lives, ranging from basic activities of daily living through to more complex occupations such as driving a car, maintaining paid employment, or going on vacation with family or friends. Challenges evolve over time for many reasons – progression of the condition (in some cases), normal aging, new responsibilities at home or work, residential moves, or shifts in social or financial circumstances, just to name a few. The potential for occupational therapists to make a positive impact on the lives of people with neurological conditions is high, given our focus on enabling occupation. But what does the evidence say? A quick search of the Cochrane Library using the term ‘occupational therapy’ uncovered a total of 49 reviews, five of which explicitly addressed the effectiveness of occupational therapy for people with neurological conditions (multiple sclerosis, stroke, Parkinson’s disease). Only one review, which focused on people with stroke (Legg et al., 2006), offered a positive conclusion about occupational therapy interventions. The authors found that ‘for every 11 (95%, CI 7 to 30) patients receiving an occupational therapy intervention to facilitate personal activities of daily living, one patient was spared a poor outcome’ (Legg et al., 2006: 2). The four remaining Cochrane reviews all concluded that there was insufficient evidence to support occupational therapy interventions for the specific population targeted (that is, people with multiple sclerosis, people with stroke in care homes, people with cognitive impairment from stroke, people with Parkinson’s disease). Each group of authors noted the lack of high-quality randomized trials for inclusion in the review process. There may be many reasons that occupational therapy researchers are not conducting these trials, but it is clear that the time has come to address them. One option is to model the research priority setting meetings hosted by the National Multiple Sclerosis Society in the United States (National Multiple Sclerosis Society, 2015), which are used to set a path forward for researchers and funders around a specific area of concern. Of note is that these meetings include people with the condition, researchers, funders, and other key stakeholders from around the world. Two other quick searches were conducted to identify sources of synthesized evidence about occupational therapy for people with neurological conditions – one in the Campbell Collaboration Library (www.campbellcollaboration.org) and one in OTseeker (www.otseeker.com). What was interesting about the findings from both of these sources was that the relevant reviews were about specific interventions occupational therapists might employ (for example, electronic assistive technology) rather than about occupational therapy per se. Several reviews concluded that the intervention was effective. The conclusions focused on the intervention rather than the delivering discipline. The findings from these three simple searches point to the need for more focused efforts to set research priorities about occupational therapy for people with neurological conditions. In addition, the differences across the three searches raise some interesting questions about the ways in which evidence is summarized and communicated, and what the implications might be for different stakeholders. Should we be examining the effectiveness of the discipline (which presumably uses a range of interventions) or the effectiveness of a specific intervention (which might be employed by several different disciplines treating people with neurological conditions)? To what extent should we be comparing the outcomes of specific interventions delivered by occupational therapists with the outcomes of other disciplines using the same intervention – if the evidence is
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 | 0,001 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 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 | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,004 | 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 ».