Notice bibliographique
Résumé
International contributions to this issue of JAPA cover a diverse range of topics including the effects of respiratory resistance training, understanding physical activity patterns of the emerging "Boomer" cohort, the influence of physical inactivity on chronic disease, validation of a new telephone-based physical activity assessment tool, the "Phone-FITT," investigation of factors associated with nonparticipation by older adults in physical activity, and an examination of the 6-min walk test employed under different test conditions.In keeping with JAPA's international flavor, this issue includes authors from Australia, Netherlands, Greece, Canada, and the United States.Although all seven contributions to this issue of JAPA make a substantive contribution to the growing body of physical activity and aging literature, three articles in our opinion should be highlighted.Participants new to exercise often complain that they are "winded" and uncomfortable, especially when exercising at intensities (moderate to vigorous) required to engender fitness and health (Paterson, Jones, & Rice, 2007).Progressive respiratorymuscle conditioning, as described by Watsford and Murphy, reduced subjective perceived exertion and submaximal exercise heart rate and improved ventilation and treadmill performance time in older women.What makes this study unique is the progressive training regimen and the fact that the authors chose to evaluate change based on performance outcomes that challenge respiratory function, rather than less intense activities.This exercise strategy might benefit both healthy older adults and those undergoing respiratory rehabilitation.As gerontologists we have for some time heralded the coming tide of older adults, dubbed the "Boomer" generation (Wister, 2005).Swan and colleagues provide us with some insight into the physical activity characteristics of this emerging cohort.Moderate physical activity levels are similar across 10-year age cohorts, and significant declines are only observed in the oldest old, suggesting that Boomers continue to be as physically active as younger adult groups, at least for moderate-intensity activities.The authors point out that this is likely influenced by the fact that Boomers enjoy more leisure time, a result of retirement; higher socioeconomic status; and better health and health care than older "traditional" aging cohorts.Unfortunately, vigorous and strengthening activities, both being very important components of fitness, do not follow the same trajectory but decline with increasing age.Although this analysis was limited to 3 years, this article should help generate discussion among health promoters on how to more effectively target physical activity interventions in the future.Most physical activity questionnaires neglect to capture the frequency, intensity, and duration (time) of physical activity performed.This is especially true of physical activity tools specific to older adults, which often have limited evidence to support their suitability, as was evident in a systematic review previously published in JAPA (Jørstad-Stein et al., 2005).Gill, Jones, Zou, and Speechley have taken the next step with the development and testing of the Phone-FITT questionnaire.The Phone-FITT generates a score based on the frequency, intensity, and duration
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 | 0,002 | 0,008 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,002 | 0,001 |
| Études des sciences et des technologies | 0,002 | 0,001 |
| Communication savante | 0,007 | 0,003 |
| Science ouverte | 0,001 | 0,002 |
| Intégrité de la recherche | 0,004 | 0,004 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,268 | 0,141 |
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 ».