Access to Health Services: Experiences of Women with Neurological Disabilities
Notice bibliographique
Résumé
Health is essential to the quality of life of an individual and consists of three domains: physical, psychological and social (Krotoski, Nosek, & Turk, 1996). The physical domain refers to the wellbeing in an individual's body. The psychological domain refers to wellbeing in a person's mind and emotions. And, the social domain refers to an individual's satisfaction with one's social relationships and participation in social activities. People with disabilities often encountered challenges to maintaining overall due to society's physical and attitudinal barriers (Donnelly et al., 2007; Neri & Kroll, 2003; Nosek, 2000; Putnam et al., 2003; Scherer & Dicowden, 2008; Shigaki, Hagglund, Clark, & Conforti, 2002). Several national and statewide surveys indicated that people with disabilities had limited access to healthcare compared to people without disabilities (Chevarley, Thierry, Gill, Ryerson, & Nosek, 2006; Hagglund Clark, Conforti, & Shigaki, 1999; Minden, Frankel, Hadden, & Hoaglin, 2007). This lack of access to primary care then led to recurrent, but often preventable, problems which, in turn, affected education, employment, and quality of life of people with disabilities (Iezzoni, Davis, Soukup, & O'Day, 2002; Nosek, 2000; Shigaki et al., 2002; Thierry & Cyril, 2004; US Department of Health & Human Services, 2000). Minden et al. (2007) examined the data obtained from the Sonya Slitka Longitudinal Multiple Sclerosis Study. They reported that substantial numbers of people with multiple sclerosis (MS) had (a) limited access to specialists, (b) restricted choice of hospitals/providers, and (c) problems obtaining mental services. Shigaki et al., (2002) studied access to healthcare among people with rehabilitation needs receiving Medicaid in Missouri. They found that individuals with spinal cord injuries (SCI) reported the most frequent difficulties accessing healthcare services. The National Healthcare Disparities Report of 2005 (U.S. Department of Health and Human Services, 2005) indicates that are observed across many clinical conditions including mental health and subpopulations including ethnic minorities, women, and individuals with According to the Bureau of the Census (2008), approximately 1 in 5 women had a disability in the U.S. in 2002, and American women have a higher disability incident rate compared to American men. Despite the number of women with disabilities there have been limited studies on access to healthcare among women with disabilities. A few national investigations indicated that women with disabilities were not well served by the healthcare and rehabilitation systems compared to women without disabilities (Chevarley et al, 2006; Hughes, 2006; Parish & Huh, 2006; Parish & Ellison-Martin, 2007; Nosek, Howland, Rintala, & Young, 2001; Smith, 2008; Smith & Ruiz, 2009). Based on an analysis of the 2004 data from the Behavioral Risk Factor Surveillance System, Smith and Ruiz (2009) reported that women with disabilities experienced disparities more than women without disabilities and men with disabilities in that they were less likely to see a doctor due to cost. Through longitudinal analyses of 1999-2002 Medical Expenditure Survey, Wei, Findley, and Sambamoorthi (2006) found that women with disabilities were less likely to receive mammography and Pap smears within the recommended intervals compared to women without disabilities. Murphy, Molnar, and Lankasky (1995) surveyed 101 adults with cerebral palsy in San Francisco and found that 90% of women with cerebral palsy in their sample did not have regular Pap smears, pelvic examinations, or breast examinations. In a survey study of preventive healthcare among 220 women with MS, Shabas and Weinrebs (2000) found that 50% of the women did not get regular medical preventive checkups. Nosek et al. (2001) indicated that routine screening for breast cancer with mammography was difficult for many women in wheelchairs because of the inaccessibility of the facility (e. …
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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 | 0,002 | 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) | 0,002 | 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 ».