Validity and Reliability of the General Well-Being Schedule with Northern Plains American Indians Diagnosed with Type 2 Diabetes Mellitus

2003 ◽  
Vol 93 (1) ◽  
pp. 49-58 ◽  
Author(s):  
Gary R. Leonardson ◽  
Mark C. Daniels ◽  
Frederick K. Ness ◽  
Erica Kemper ◽  
Joni L. Mihura ◽  
...  

The General Well-being Schedule is a brief indicator of subjective feelings of psychological well-being and distress. It is easy to administer, reliable, and valid, although its validity with American Indians has not been established. This study then assessed reliability, validity, and factor structure for a sample of 88 diabetic American Indians, who sought care for diabetes at an Indian Health Service hospital. Cronbach alpha was .89. A factor analysis indicated four dimensions. Adequate concurrent and divergent validity were noted in association with scores on the Beck Depression Inventory-Second Edition, the depression scale on the Symptom Checklist-90-Revised, and Family-Adaptation, Partnership, Growth, Affection, & Resolve. These results suggest that the General Well-being Schedule is a reliable and valid measure of general well-being for this population of American Indians.

2005 ◽  
Vol 97 (1) ◽  
pp. 161-166 ◽  
Author(s):  
Gary R. Leonardson ◽  
Frederick K. Ness ◽  
Mark C. Daniels ◽  
Erica Kemper ◽  
Brett A. Koplin ◽  
...  

According to the Indian Health Service, substance abuse and Type 2 diabetes are serious problems among Native Americans. To assess substance use in a medical setting, valid screening tests are needed so the Alcohol Use Disorders Identification Test (AUDIT), a simple brief screen for excessive drinking, and the CAGE-adapted to Include Drugs (CAGE-AID) for identifying primary care patients with alcohol and drug disorders were given 50 Northern Plains American Indians with diabetes. Both are short, easy to administer, have good sensitivity and specificity, and can be easily incorporated into a medical history protocol or intake procedure. Reliability coefficients were above .90 and appeared to have sufficient concurrent and divergent validity indicated by moderate correlations with the General Well-being Schedule ( rs = –.39 and –.36), the Family-Adaptation, Partnership, Growth, Affection, & Resolve ( r = –.47 and –.36), and the Beck Depression Inventory-II ( r = .36 and .29).


1999 ◽  
Vol 27 (2) ◽  
pp. 5-11
Author(s):  
Apanakhi Buckley

This paper describes a qualitative study of how indigenous people experience medical school in the United States. Nine American Indians and Alaska Natives participated in the study: five women and four men. They came from eight different tribes, but they have asked me to protect their confidentiality, so I will not identify their tribes. Their ages ranged from 27 to 39. Five of them had children. Two of them were unmarried.In the United States, the need for indigenous physicians is great. Twice as many American Indians die from homicide and suicide as non-Indians in the United States (Wallace, Kirk, Houston, Amnest, and Emrich, 1993); three times as many die from accidents and more than four times as many die from alcoholism (Indian Health Service, 1996). Diabetes is rampant among American Indians and Alaska Natives. Women are the hardest hit (Gilliland, Gilliland, and Carter; 1997). More than five times as many American Indian and Alaska Native women die from diabetes than non-Latina white women.


1992 ◽  
Vol 84 (19) ◽  
pp. 1500-1505 ◽  
Author(s):  
D. M. Bleed ◽  
D. R. Risser ◽  
S. Sperry ◽  
D. Hellhake ◽  
S. D. Helgerson

2018 ◽  
Vol 149 (1) ◽  
pp. 89-92 ◽  
Author(s):  
Lauren E. Dockery ◽  
Anita Motwani ◽  
Kai Ding ◽  
Mark Doescher ◽  
Justin D. Dvorak ◽  
...  

2019 ◽  
Vol 6 (1) ◽  
Author(s):  
Amanda A. Honeycutt ◽  
Olga Khavjou ◽  
Simon J. Neuwahl ◽  
Grant A. King ◽  
Meredith Anderson ◽  
...  

Abstract Background In the United States, the mortality burden of injury is higher among American Indians and Alaska Natives (AI/AN) than any other racial/ethnic group, and injury contributes to considerable medical costs, years of potential life lost (YPLL), and productivity loss among AI/AN. This study assessed the economic burden of injuries for AI/AN who are eligible for services through Indian Health Service, analyzing direct medical costs of injury for Indian Health Service’s users and years of potential life lost (YPLL) and the value of productivity losses from injury deaths for AI/AN in the Indian Health Service population. Methods Injury-related lifetime medical costs were estimated for Indian Health Service users with medically treated injuries using data from the 2011–2015 National Data Warehouse. Productivity costs and YPLL were estimated using data on injury-related deaths among AI/AN in Indian Health Service’s 2008–2010 service population. Costs were reported in 2017 U.S. dollars. Results The total estimated costs of injuries per year, including injuries among Indian Health Service users and productivity losses from injury-related deaths, were estimated at $4.5 billion. Lifetime medical costs to treat annual injuries among Indian Health Service users were estimated at $549 million, with the largest share ($131 million) going toward falls, the most frequent injury cause. Total estimated YPLL from AI/AN injury deaths in Indian Health Service’s service population were 106,400. YPLL from injury deaths for men (74,000) were 2.2 times YPLL for women (33,000). Productivity losses from all injury-related deaths were $3.9 billion per year. The highest combined lifetime medical and mortality costs were for motor vehicle/traffic injuries, with an estimated cost of $1.6 billion per year. Conclusions Findings suggest that targeted injury prevention efforts by Indian Health Service likely contributed to lower rates of injury among AI/AN, particularly for motor vehicle/traffic injuries. However, because of remaining disparities in injury-related outcomes between AI/AN and all races in the United States, Indian Health Service should continue to monitor changes in injury incidence and costs over time, evaluate the impacts of previous injury prevention investments on current incidence and costs, and identify additional injury prevention investment needs.


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