2,791 research outputs found
Correlated physical and mental health summary scores for the SF-36 and SF-12 Health Survey, V.1
<p>Abstract</p> <p>Background</p> <p>The SF-36 and SF-12 summary scores were derived using an uncorrelated (orthogonal) factor solution. We estimate SF-36 and SF-12 summary scores using a correlated (oblique) physical and mental health factor model.</p> <p>Methods</p> <p>We administered the SF-36 to 7,093 patients who received medical care from an independent association of 48 physician groups in the western United States. Correlated physical health (PCS<sub>c</sub>) and mental health (MCS<sub>c</sub>) scores were constructed by multiplying each SF-36 scale z-score by its respective scoring coefficient from the obliquely rotated two factor solution. PCS<sub>c</sub>-12 and MCS<sub>c</sub>-12 scores were estimated using an approach similar to the one used to derive the original SF-12 summary scores.</p> <p>Results</p> <p>The estimated correlation between SF-36 PCS<sub>c </sub>and MCS<sub>c </sub>scores was 0.62. There were far fewer negative factor scoring coefficients for the oblique factor solution compared to the factor scoring coefficients produced by the standard orthogonal factor solution. Similar results were found for PCS<sub>c</sub>-12, and MCS<sub>c</sub>-12 summary scores.</p> <p>Conclusion</p> <p>Correlated physical and mental health summary scores for the SF-36 and SF-12 derived from an obliquely rotated factor solution should be used along with the uncorrelated summary scores. The new scoring algorithm can reduce inconsistent results between the SF-36 scale scores and physical and mental health summary scores reported in some prior studies.</p> <p>(Subscripts C = correlated and UC = uncorrelated)</p
PWM4: THE RELATIONSHIP BETWEEN NOTTINGHAM HEALTH PROFILE DOMAINS AND CLINICAL CHARACTERISTICS OF WOMEN WITH ESTABLISHED POSTMENOPAUSAL OSTEOPOROSIS
Recommended from our members
Developing Children's Oral Health Assessment Toolkits Using Machine Learning Algorithm.
ObjectivesEvaluating children's oral health status and treatment needs is challenging. We aim to build oral health assessment toolkits to predict Children's Oral Health Status Index (COHSI) score and referral for treatment needs (RFTN) of oral health. Parent and Child toolkits consist of short-form survey items (12 for children and 8 for parents) with and without children's demographic information (7 questions) to predict the child's oral health status and need for treatment.MethodsData were collected from 12 dental practices in Los Angeles County from 2015 to 2016. We predicted COHSI score and RFTN using random Bootstrap samples with manually introduced Gaussian noise together with machine learning algorithms, such as Extreme Gradient Boosting and Naive Bayesian algorithms (using R). The toolkits predicted the probability of treatment needs and the COHSI score with percentile (ranking). The performance of the toolkits was evaluated internally and externally by residual mean square error (RMSE), correlation, sensitivity and specificity.ResultsThe toolkits were developed based on survey responses from 545 families with children aged 2 to 17 y. The sensitivity and specificity for predicting RFTN were 93% and 49% respectively with the external data. The correlation(s) between predicted and clinically determined COHSI was 0.88 (and 0.91 for its percentile). The RMSEs of the COHSI toolkit were 4.2 for COHSI (and 1.3 for its percentile).ConclusionsSurvey responses from children and their parents/guardians are predictive for clinical outcomes. The toolkits can be used by oral health programs at baseline among school populations. The toolkits can also be used to quantify differences between pre- and post-dental care program implementation. The toolkits' predicted oral health scores can be used to stratify samples in oral health research.Knowledge transfer statementThis study creates the oral health toolkits that combine self- and proxy- reported short forms with children's demographic characteristics to predict children's oral health and treatment needs using Machine Learning algorithms. The toolkits can be used by oral health programs at baseline among school populations to quantify differences between pre and post dental care program implementation. The toolkits can also be used to stratify samples according to the treatment needs and oral health status
U.S. General Population Estimate for “Excellent” to “Poor” Self-Rated Health Item
BACKGROUND: The most commonly used self-reported health question asks people to rate their general health from excellent to poor. This is one of the Patient-Reported Outcomes Measurement Information System (PROMIS) global health items. Four other items are used for scoring on the PROMIS global physical health scale. Because the single item is used on the majority of large national health surveys in the U.S., it is useful to construct scores that can be compared to U.S. general population norms. OBJECTIVE: To estimate the PROMIS global physical health scale score from the responses to the single excellent to poor self-rated health question for use in public health surveillance, research, and clinical assessment. DESIGN: A cross-sectional survey of 21,133 individuals, weighted to be representative of the U.S. general population. PARTICIPANTS: The PROMIS items were administered via a Web-based survey to 19,601 persons in a national panel and 1,532 subjects from PROMIS research sites. The average age of individuals in the sample was 53 years, 52 % were female, 80 % were non-Hispanic white, and 19 % had a high school degree or lower level of education. MAIN OUTCOME MEASURES: PROMIS global physical health scale. KEY RESULTS: The product–moment correlation of the single item with the PROMIS global physical health scale score was 0.81. The estimated scale score based on responses to the single item ranged from 29 (poor self-rated health, 2.1 SDs worse than the general population mean) to 62 (excellent self-rated health, 1.2 SDs better than the general population mean) on a T-score metric (mean of 50). CONCLUSIONS: This item can be used to estimate scores for the PROMIS global physical health scale for use in monitoring population health and achieving public health objectives. The item may also be used for individual assessment, but its reliability (0.52) is lower than that of the PROMIS global health scale (0.81)
Does modafinil enhance activity of patients with myotonic dystrophy?: A double-blind placebo-controlled crossover study
We performed a double-blind placebo-controlled crossover study in 13 patients with myotonic dystrophy to address the question whether modafinil, known to improve hypersomnolence in myotonic dystrophy, may improve levels of activity as well. We used the Epworth Sleepiness Scale as a measure of hypersomnolence and a structured interview of the patient and the partner or housemate as a measure of activity. We additionally used a restricted form of the RAND-36 to relate a possible improvement of activity to perceived general health. We confirmed earlier positive findings of modafinil regarding reduced somnolence (p = 0.015), but no significant effects were seen regarding activity levels (p = 0.2 for patients’ self-reports and 0.5 for partners’ reports)
Health state preferences are equivalent in the United States and Trinidad and Tobago
To derive preference weights in Trinidad and Tobago for Quality of Well-being Scale (QWB) health states in order to calculate QWB scores that can be compared to scores calculated from US-derived preference weights. The comparison was to determine whether the QWB scores from these different preference weights would lead to similar conclusions.
We conducted in-person household interviews to elicit preferences for 65 health states using a probability sample of 235 adults from Port of Spain, Chaguanas and San Fernando, Trinidad and Tobago. A regression model with correction for within-person clustering of observations was used to obtain preference weights based on case judgments on a 0 (dead) to 10 (“perfect health”) scale. The independent variables were the components of the QWB entered as indicator (0, 1) variables.
One hundred and nineteen (51%) respondents provided ratings. The respondents that provided ratings were demographically no different from those that did not. The QWB response patterns were very similar using Trinidad and US weights. The mean (SD) QWB score was 0.750 (0.130) for female respondents and 0.784 (0.125) for male respondents using Trinidad coefficients (t
2, 233 = −2.05, P = 0.04) and 0.747 (0.131) for female respondents and 0.783 (0.126) for male respondents using US weights (t
2, 233 = −2.17, P = 0.03).
Overall, we found the US and Trinidad and Tobago weights were highly similar and that the choice of either set of weights would lead to similar conclusions
Development and preliminary evaluation of a quality of life measure targeted at dementia caregivers
<p>Abstract</p> <p>Background</p> <p>Providing care for individuals with a progressive, debilitating condition such as dementia can adversely impact the quality of life (QOL) of informal caregivers. To date, there is no existing caregiver quality of life measure for dementia caregivers with breadth of coverage or that is applicable to caregivers of diverse ethnic backgrounds. The purpose of this study was to develop and evaluate a caregiver-targeted quality-of-life measure (CGQOL) for informal caregivers of persons with dementia that can be used with caregivers from a variety of ethnicities.</p> <p>Methods</p> <p>91 items were field tested by telephone interviews with 179 English-speaking and 21 monolingual Spanish-speaking caregivers of persons with dementia. Repeat interviews were conducted with 71 caregivers. Administration time, scale score distributions, item-scale correlations, reliability, and associations of scales with patient and caregiver demographic and caregiving characteristics were estimated. Structure of associations among scales was examined using exploratory factor analysis.</p> <p>Results</p> <p>Item analysis yielded 80 items distributed across 10 scales, with median administration time of 17 minutes [IQR 13.5–22 minutes] and minimal missing data. There were few floor or ceiling effects in scale score distributions. Internal consistency reliability was ≥ 0.78 for all scales; test-retest reliability (intraclass correlation) estimates exceeded 0.70 for 6 scales. More hours weekly spent in caregiving was uniquely associated with worse quality of life on 8 scales (p's ≤ 0.05). Three higher-order dimensions of caregiving assistance, emotional and social concerns, and spirituality and benefits were identified.</p> <p>Conclusion</p> <p>These preliminary results support subsequent evaluation of test-retest reliability, construct validity, and responsiveness to change of this quality-of-life measure for caregivers from diverse ethnicities.</p
Reliability and validity of the ESRD Symptom Checklist – Transplantation Module in Norwegian kidney transplant recipients
BACKGROUND: The aim of the study was to validate the Norwegian version of a self-administered 43-item questionnaire designed to assess quality of life in kidney transplant recipients, the End-Stage Renal Disease Symptom Checklist – Transplantation Module (ESRD-SCL). METHODS: In total, 53 kidney transplant recipients from one university-affiliated hospital responded to a questionnaire including the ESRD-SCL and the Short Form 36 (SF-36). We assessed internal consistency reliability and test-retest reliability with 2 weeks between assessments. Construct validity was assessed by correlations of the ESRD-SCL subscales with related and unrelated SF-36 scales, demographic, and clinical characteristics. RESULTS: Subscales of the ESRD-SCL showed good internal consistency reliability (Cronbach's = 0.72–0.81) and for the aggregate total scale α was 0.94. Test-retest reliability median 14 days apart was excellent with intraclass coefficients ranging from 0.87 to 0.95. The pattern of correlations of the ESRD-SCL scales with related and unrelated scales SF-36 scales and demographic and clinical characteristics gave support to the construct validity of the ESRD-SCL. CONCLUSION: The Norwegian translation of the ESRD-SCL showed satisfactory internal consistency reliability, test-retest reliability and construct validity, at the level of the original German version
Validation of the Kidney Disease Quality of Life-Short Form: a cross-sectional study of a dialysis-targeted health measure in Singapore
<p>Abstract</p> <p>Background</p> <p>In Singapore, the prevalence of end-stage renal disease (ESRD) and the number of people on dialysis is increasing. The impact of ESRD on patient quality of life has been recognized as an important outcome measure. The Kidney Disease Quality Of Life-Short Form (KDQOL-SF™) has been validated and is widely used as a measure of quality of life in dialysis patients in many countries, but not in Singapore. We aimed to determine the reliability and validity of the KDQOL-SF™ for haemodialysis patients in Singapore.</p> <p>Methods</p> <p>From December 2006 through January 2007, this cross-sectional study gathered data on patients ≥21 years old, who were undergoing haemodialysis at National Kidney Foundation in Singapore. We used exploratory factor analysis to determine construct validity of the eight KDQOL-SF™ sub-scales, Cronbach's alpha coefficient to determine internal consistency reliability, correlation of the overall health rating with kidney disease-targeted scales to confirm validity, and correlation of the eight sub-scales with age, income and education to determine convergent and divergent validity.</p> <p>Results</p> <p>Of 1980 haemodialysis patients, 1180 (59%) completed the KDQOL-SF™. Full information was available for 980 participants, with a mean age of 56 years. The sample was representative of the total dialysis population in Singapore, except Indian ethnicity that was over-represented. The instrument designers' proposed eight sub-scales were confirmed, which together accounted for 68.4% of the variance. All sub-scales had a Cronbach's α above the recommended minimum value of 0.7 to indicate good reliability (range: 0.72 to 0.95), except for Social function (0.66). Correlation of items within subscales was higher than correlation of items outside subscales in 90% of the cases. The overall health rating positively correlated with kidney disease-targeted scales, confirming validity. General health subscales were found to have significant associations with age, income and education, confirming convergent and divergent validity.</p> <p>Conclusions</p> <p>The psychometric properties of the KDQOL-SF™ resulting from this first-time administration of the instrument support the validity and reliability of the KDQOL-SF™ as a measure of quality of life of haemodialysis patients in Singapore. It is, however, necessary to determine the test-retest reliability of the KDQOL-SF™ among the haemodialysis population of Singapore.</p
Minimal changes in health status questionnaires: distinction between minimally detectable change and minimally important change
Changes in scores on health status questionnaires are difficult to interpret. Several methods to determine minimally important changes (MICs) have been proposed which can broadly be divided in distribution-based and anchor-based methods. Comparisons of these methods have led to insight into essential differences between these approaches. Some authors have tried to come to a uniform measure for the MIC, such as 0.5 standard deviation and the value of one standard error of measurement (SEM). Others have emphasized the diversity of MIC values, depending on the type of anchor, the definition of minimal importance on the anchor, and characteristics of the disease under study. A closer look makes clear that some distribution-based methods have been merely focused on minimally detectable changes. For assessing minimally important changes, anchor-based methods are preferred, as they include a definition of what is minimally important. Acknowledging the distinction between minimally detectable and minimally important changes is useful, not only to avoid confusion among MIC methods, but also to gain information on two important benchmarks on the scale of a health status measurement instrument. Appreciating the distinction, it becomes possible to judge whether the minimally detectable change of a measurement instrument is sufficiently small to detect minimally important changes
- …