Notice bibliographique
Résumé
The aim of this book is to provide an updated synthesis of the scientific evidence linking exercise training to health outcomes in chronic disease. Editor John Saxton, a professor of clinical exercise physiology, has contributed the introduction and co-authored one chapter; the remaining 16 chapters, each focusing on a specific chronic disease, are contributed by international health care professionals, researchers, and research groups. The introduction highlights key questions to consider when assessing the efficacy of exercise training, provides definitions of exercise terminology, describes levels of evidence, and discusses dose–response issues. Several common chronic diseases are discussed, including cardiovascular and metabolic conditions (coronary heart disease, hypertension, stroke, peripheral arterial disease/intermittent claudication, type 2 diabetes); respiratory diseases (chronic obstructive lung disease, asthma); musculoskeletal and rheumatic disorders (osteoarthritis, osteoporosis, rheumatoid arthritis, ankylosing spondylitis, chronic fatigue syndrome, fibromyalgia syndrome); neurological conditions (multiple sclerosis, Parkinson disease); cancer (colorectal, breast, and prostate); and obesity. Kidney disease, despite being listed as a prevalent chronic disease in the introduction, is not covered elsewhere in the volume. Evidence for exercise training, including both narrative and systematic reviews, is reported from a variety of study designs, with a particular focus on randomized controlled trials. Each chapter contains an extensive reference list that includes studies published up to 2010. Strong, comprehensive scientific evidence for exercise training is available for some chronic diseases, showing improvements in mortality and modification of the disease process and risk factors, while less rigorous and/or preliminary evidence supports exercise training for other chronic conditions. In addition to physiologic factors such as cardiorespiratory fitness, skeletal muscle function, and body composition, the authors discuss psychosocial outcomes, such as anxiety and depression, that commonly affect people with chronic disease. Functional outcomes, measures of quality of life, and disease-specific outcomes such as pain, bone-mineral density, spinal mobility, gait velocity, motor function, and fatigue are included where relevant. The chapters vary with respect to structure, organization, format of exercise prescription recommendations, and presentation of research studies. Aerobic and resistance training and safety are discussed consistently, however, and several chapters discuss hospital training versus community and home exercise. Issues repeatedly identified as warranting future research include clarifying the response to and efficacy of exercise training for specific sub-groups of patients (considering disease severity, symptoms and phase of treatment); determining optimal prescription parameters; and addressing adherence issues. Because people with chronic disease often present with comorbidities, the disease-specific chapter format provides a helpful resource to address the multiple needs of the chronic disease population. I would recommend this book to clinicians to support evidence-based clinical practice, as well as to clinical researchers interested in investigating the effects of exercise as an adjunct treatment in chronic disease. Overall, Exercise and Chronic Disease: An Evidence-Based Approach provides a useful framework for examining existing and emerging evidence, summarizes current evidence to support clinical practice and inform clinical decision making, and emphasizes future research priorities and opportunities.
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) | 0,000 | 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) | 0,001 | 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 ».