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PubMed2000

Assessing body composition and changes in body composition. Another look at dual-energy X-ray absorptiometry.

Dual-energy X-ray absorptiometry (DXA) is selected with increasing frequency as a method for both assessing body composition and measuring the changes in body composition. Issues have been raised about hydration, software version, hardware (fan beam vs. pencil beam), and the subject population in relation to the validity of DXA-derived estimates of body composition. This paper reviews validation studies of DXA to assess the impact of recent developments in its technology. Studies by Prior et al., Kohrt et al., Salamone et al., Going et al., and Pietrobelli et al. demonstrate the effectiveness of DXA estimates of changes in body composition. By contrast, Clasey et al., Nelson et al., and Friedl et al. found limitations in DXA estimates of body composition and its changes. These contradictory conclusions were explored for threats to internal validity in each research study. From this analysis, two validation guidelines are recommended for use when evaluating estimates of body composition. When multicomponent models are used, it is essential that estimates of body water as a fraction of fat-free mass fall in the expected range (71 to 75%) and have a relatively small standard deviation (2 to 3%). For measuring changes in body composition, DXA estimates of total body mass must accurately reflect both baseline and posttreatment scale body weight estimates. Failure to meet these guidelines threatens the internal validity of the study and raises the likelihood of methodological discrepancies. Applying these criteria to DXA studies of body composition under review accounts for much of the contradictory conclusions among investigations.

Absorptiometry, Photon↗

PubMed1998

[Is the randomized controlled trial overvalued as a basis for clinical decision-making? A review with comments].

The randomized controlled trial (RCT) may have considerable limitations in clinical research. Lacking the possibility of blinding impairs the internal validity of the trials. The external validity is often impaired, as results of RCTs obtained in an ideal situation, may be difficult to generalize to a clinical routine situation. Pragmatic randomized trials move from ideal situations towards routine situations, and by modifying the design it is possible to reduce selection bias due to patient and physician preferences. Quasi-experimental studies have varying degrees of problems with internal validity but are necessary contributions to our knowledge of the effect of treatment in clinical routine situations. Limitations of the usefulness of RCTs as well as pragmatic and quasi-experimental studies in clinical research make it necessary to recognise that different methods complement one another. Research in development of RCTs and new methods in clinical research should be encouraged.

Decision Making↗

PubMed2006

Postasphyxial hypoxic-ischemic encephalopathy in neonates: outcome prediction rule within 4 hours of birth.

OBJECTIVES: To construct and validate a model and derive a simple rule that is usable in any birth location for the prediction of outcome of term infants with severe asphyxia. DESIGN: Retrospective cohort study. SETTING: Regional outborn neonatal intensive care unit. PARTICIPANTS: Infants with postintrapartum asphyxial hypoxic-ischemic encephalopathy (n = 375). MAIN EXPOSURES: Clinical and laboratory predictors available at age 4 hours. MAIN OUTCOME MEASURES: A logistic regression model was developed and internally validated (with random sampling and based on the year of birth) for severe adverse outcome, which was defined as death or severe disability (severe cerebral palsy, severe developmental delay, sensorineural deafness, or cortical blindness singly or in combination). A simple prediction rule was derived from 3 variables. RESULTS: Complete data were available for 302 (92%) of the 345 infants with known outcomes (204 infants with severe adverse outcome). Six independent predictors of outcomes were identified. Using the 3 most significant predictors (chest compressions, age at onset of respiration, and base deficit), severe adverse outcome rates were 46% (95% confidence interval, 33%-58%) with none of the 3 predictors, 64% (95% confidence interval, 54%-73%) with any 1 predictor, 76% (95% confidence interval, 66%-85%) with any 2 predictors, and 93% (95% confidence interval, 81%-99%) with all of the 3 predictors present. The internal validations revealed a robust model. CONCLUSIONS: This predictive model for neonatal hypoxic-ischemic encephalopathy provides a sliding scale of probabilities that could be used for prognostication and to design eligibility criteria for decision making including neuroprotective therapy.

Age Factors↗

PubMed2000

['Informed consent' and prerandomization].

The usual procedure in randomised controlled trials is to obtain informed consent first, after which participants can be randomised. The reversal of the order, first randomisation and then informed consent, is called pre-randomisation (Zelen design). In the Netherlands, there is discussion as to whether pre-randomisation should be allowed in medical research. Full informed consent regarding the design of the investigation may lead to unwanted loss of distinction between the experimental and control groups, thus reducing the internal validity of the investigation. A possible solution could be to include, in the informed consent procedure, the statement that certain information has been withheld because revealing it now would make the investigation useless, but that it will be revealed to all participants afterwards and that the study design was approved by the medical ethics committee. In this way, the advantage of the enhanced internal validity of the pre-randomisation design is retained while simultaneously keeping intact the sequence of first informed consent and then randomisation.

Humans↗

PubMed2005

Chemotherapy-induced anaemia during adjuvant treatment for breast cancer: development of a prediction model.

BACKGROUND: At present, oncologists prescribe chemotherapy according to standard dose schedules, and as a result many patients develop serious, dose-limiting toxic effects such as anaemia. We aimed to develop a prediction model for anaemia in patients with breast cancer who were receiving adjuvant chemotherapy. METHODS: We reviewed medical records of 331 patients who had received adjuvant chemotherapy for breast cancer. Patients were divided randomly into a derivation sample (n=221) and internal-validation sample (n=110). An external sample of 119 patients enrolled onto the control group of a randomised trial of epoetin alfa was used to validate the model further. Multivariable logistic regression was applied to develop the initial model. We then developed a risk-scoring system, ranging from 0 (low risk) to 50 (high risk), based on the final regression variables. A receiver operating characteristic (ROC) curve analysis was done to measure the accuracy of the scoring system when applied to both validation samples. FINDINGS: The risk of anaemia increased as the pretreatment haemoglobin concentration decreased and was reduced with successive chemotherapy cycles. Risk was also predicted by a platelet count of 200x10(9) cells/L or less before chemotherapy, age 65 years or older, type of adjuvant chemotherapy, and use of prophylactic antibiotics. ROC analysis had acceptable areas under the curve of 0.88 for the internal-validation sample and 0.84 for the external validation sample. A risk score of > or = 24 to < 25 before chemotherapy was identified as the optimum cut-off for maximum sensitivity (83.5%) and specificity (92.3%) of the prediction model. INTERPRETATION: The application and continued refinement of this prediction model will help oncologists to identify patients at risk of developing anaemia during chemotherapy for breast cancer, and might enhance patient-centred care by the application of anaemia treatment in a proactive and appropriate way.

Aged↗

PubMed2003

The validity of the depression rating scales in discriminating between citalopram and placebo in depression recurrence in the maintenance therapy of elderly unipolar patients with major depression.

The World Federation of Societies of Biological Psychiatry guidelines for treatment of unipolar major depression has recommended three depression rating scales for evaluating outcome: The Hamilton Depression Rating Scale (HAM-D), the Montgomery-Asberg Depression Rating Scale (MADRS), and the Bech-Rafaelsen Melancholia Scale (MES). In this study we evaluated the ability of these scales to differentiate between citalopram and placebo in the recurrence prevention of unipolar depression. The study is a psychometric reexamination of a trial on the efficacy of citalopram versus placebo in the maintenance therapy of elderly patients with unipolar depression. Internal validity (the Cronbach coefficient alpha, the Loevinger coefficient of homogeneity, and factor analysis) of the three scales has been examined to evaluate their unidimensionality. In the outcome analysis for depression recurrence, the conventional cutoff scores of the three scales are used. In total, 60 patients received citalopram and 61 patients received placebo in the maintenance phase of 48 weeks. The results showed that the internal validity was higher for MES and MADRS than for HAM-D. Using the MADRS, 67.2 % of the patients on placebo and 31.6 % of the patients on citalopram developed a depression recurrence (ratio 2.12); using HAM-D17, 42.6 % on placebo and 13.3 % on citalopram developed a depression recurrence (ratio 3.20); and using the MES, 34.4 % on placebo and 11.7 % on citalopram developed a depression recurrence (ratio 2.94). The conventional cutoff scores of HAM-D17 and MES for depression recurrence indicated a ratio between citalopram and placebo of around 3, while the conventional cutoff scores of MADRS for depression recurrence indicated a ratio of only around 2. In future trials on the recurrence prevention of unipolar depression, a cutoff score of 25 rather than 22 on the MADRS is recommended.

Aged↗

PubMed2026

Machine learning-guided risk stratification in elderly AML based on genomic, immunophenotypic and therapeutic profiles.

BACKGROUND: Elderly patients with acute myeloid leukemia (AML) exhibit considerable biological and clinical heterogeneity, hindering precise prognosis. Existing prognostic systems inadequately capture the complexity of elderly AML due to their reliance on data from younger cohorts and omission of key factors like immunophenotypic markers and therapeutic profiles. This study aimed to develop and internally validate a machine learning-based prognostic model specifically tailored to elderly AML patients. METHODS: A total of 156 patients were analyzed using a two-stage modeling strategy. Clinical and genomic variables were modeled first, followed by independent analysis of immunophenotypic features. Feature selection was performed using multilayer perceptron (MLP) and random forest (RF), while multivariate Cox regression was used for final model construction. Internal validation was conducted using 1000 bootstrap iterations to assess model stability and performance. RESULTS: The model demonstrated strong predictive performance, with a concordance index (C-index) of 0.702. Time-dependent area under the curve (AUC) and calibration plots confirmed accurate prediction of 1-, 3-, and 5-year overall survival. Decision curve analysis indicated favorable net benefit across a range of threshold probabilities. Key independent prognostic factors identified included TP53 mutations, high CD13 expression, and IDH2 mutations. CONCLUSION: This model provides a robust and interpretable tool for individualized risk stratification in elderly AML. By integrating genomic, immunophenotypic, and therapeutic variables, it may help optimize treatment decisions and improve outcomes for this vulnerable population. Future efforts should focus on external validation and integration of dynamic biomarkers.

Humans↗

PubMed2000

Observation procedures characterizing occupational physical activities: critical review.

The first objective of this paper is to compare the observation procedures proposed to characterize physical work. The second objective is to examine the following 3 methodological issues: reliability, observer training, and internal validity. Seventy-two papers were reviewed, 38 of which proposed a new or modified observation grid. The observation variables identified were broken down into 7 categories as follows: posture, exertion, load handled, work environment, use of feet, use of hands, and activities or tasks performed. The review revealed the variability of existing procedures. The examination of methodological issues showed that observation data can be reliable and can present an adequate internal validity. However, little information about the conditions necessary to achieve good reliability was available.

Canada↗

PubMed1999

Malingering and mild brain injury: how low is too low.

The purpose of this study was to investigate potential validity markers for 4 commonly used neuropsychological tests. Participants were divided into 5 groups: moderate/severe brain injury (n = 27), mild brain injury--nonlitigating (n = 35), normal controls (n = 30), mild brain injury--litigating (n = 49), and malingering "actors" (n = 20). Participants completed a flexible neuropsychological battery that included the 4 tests of interest (Judgment of Line Orientation, Token Test, Dichotic Listening, and 20-item forced choice). Results demonstrated cutoff levels on all 4 tests below which people with mild brain injury would not be expected to fall. The fact that some litigants, but no nonlitigants, fell below these cutoff levels suggests these tests and their cutoff levels may be used appropriately as internal validity markers. There was 100% specificity and 95% sensitivity found when all 4 tests were used together (1-test criteria) to separate litigants, nonlitigants, and actors. It is suggested that further examination of these tests and other neuropsychological tests, be completed so that, eventually, all neuropsychological tests will have internal validity markers.

Adult↗

PubMed2026

Risk Factors and Predictive Model for Postoperative High Myopia in Children Undergoing Congenital Cataract Surgery With Intraocular Lens Implantation.

PURPOSE: To identify risk factors associated with the development of high myopia following congenital cataract surgery and to establish a robust predictive model. DESIGN: Retrospective clinical cohort study. SUBJECTS: This retrospective study included 106 pediatric patients who underwent congenital cataract surgery with primary IOL implantation (mean follow-up 8.19 years). The model was externally validated in an independent cohort of 72 patients with a mean follow-up of 7.83 years. METHODS: Preoperative and postoperative ocular biometric parameters were collected. Risk factors for postoperative high myopia were analyzed using Cox proportional hazards regression, which served as the basis for model construction. The predictive performance of the model was rigorously evaluated for discrimination and calibration. Discriminative ability was quantified using Harrell's C-index and the area under the receiver operating characteristic curve (AUC). Model calibration was assessed via calibration plots by comparing predicted probabilities with actual observed outcomes. Internal validation was performed using a bootstrapping method (500 iterations) to ensure model stability and adjust for potential overfitting. RESULTS: An initial postoperative refraction of <+0.75D, and a higher IOL Power to Axial length Ratio (IOL/AL ratio) were identified as significant risk factors for the development of postoperative high myopia. Shorter preoperative axial length was associated with a greater magnitude of postoperative myopic shift. The predictive model demonstrated robust performance, achieving a C-index of 0.711 (internal validation C-index: 0.713). The area under the receiver operating characteristic curve (AUC) values for predicting high myopia at 5 and 10 years were 0.858 and 0.745, respectively. Furthermore, calibration curves demonstrated excellent agreement between the predicted and observed outcomes throughout the follow-up period. In external validation, the model achieved a C-index of 0.825, 5-year AUC of 0.833, and 10-year AUC of 0.713. CONCLUSIONS: Our analysis established that initial postoperative refraction <+0.75D, and an elevated IOL/AL ratio are key determinants of high myopia risk following surgery. Shorter preoperative axial length was associated with a greater magnitude of postoperative myopic shift. This predictive framework provides clinicians with a practical tool to optimize preoperative IOL selection and identify high-risk infants who require vigilant myopia prevention and balanced amblyopia management.

Humans↗

PubMed2005

GenClust: a genetic algorithm for clustering gene expression data.

BACKGROUND: Clustering is a key step in the analysis of gene expression data, and in fact, many classical clustering algorithms are used, or more innovative ones have been designed and validated for the task. Despite the widespread use of artificial intelligence techniques in bioinformatics and, more generally, data analysis, there are very few clustering algorithms based on the genetic paradigm, yet that paradigm has great potential in finding good heuristic solutions to a difficult optimization problem such as clustering. RESULTS: GenClust is a new genetic algorithm for clustering gene expression data. It has two key features: (a) a novel coding of the search space that is simple, compact and easy to update; (b) it can be used naturally in conjunction with data driven internal validation methods. We have experimented with the FOM methodology, specifically conceived for validating clusters of gene expression data. The validity of GenClust has been assessed experimentally on real data sets, both with the use of validation measures and in comparison with other algorithms, i.e., Average Link, Cast, Click and K-means. CONCLUSION: Experiments show that none of the algorithms we have used is markedly superior to the others across data sets and validation measures; i.e., in many cases the observed differences between the worst and best performing algorithm may be statistically insignificant and they could be considered equivalent. However, there are cases in which an algorithm may be better than others and therefore worthwhile. In particular, experiments for GenClust show that, although simple in its data representation, it converges very rapidly to a local optimum and that its ability to identify meaningful clusters is comparable, and sometimes superior, to that of more sophisticated algorithms. In addition, it is well suited for use in conjunction with data driven internal validation measures and, in particular, the FOM methodology.

Algorithms↗

PubMed2005

A prediction rule for selective screening of Chlamydia trachomatis infection.

BACKGROUND: Screening for Chlamydia trachomatis infections is aimed at the reduction of these infections and subsequent complications. Selective screening may increase the cost effectiveness of a screening programme. Few population based systematic screening programmes have been carried out and attempts to validate selective screening criteria have shown poor performance. This study describes the development of a prediction rule for estimating the risk of chlamydial infection as a basis for selective screening. METHODS: A population based chlamydia screening study was performed in the Netherlands by inviting 21,000 15-29 year old women and men in urban and rural areas for home based urine testing. Multivariable logistic regression was used to identify risk factors for chlamydial infection among 6303 sexually active participants, and the discriminative ability was measured by the area under the receiver operating characteristic curve (AUC). Internal validity was assessed with bootstrap resampling techniques. RESULTS: The prevalence of C trachomatis (CT) infection was 2.6% (95% CI 2.2 to 3.2) in women and 2.0% (95% CI 1.4 to 2.7) in men. Chlamydial infection was associated with high level of urbanisation, young age, Surinam/Antillian ethnicity, low/intermediate education, multiple lifetime partners, a new contact in the previous two months, no condom use at last sexual contact, and complaints of (post)coital bleeding in women and frequent urination in men. A prediction model with these risk factors showed adequate discriminative ability at internal validation (AUC 0.78). CONCLUSION: The prediction rule has the potential to guide individuals in their choice of participation when offered chlamydia screening and is a promising tool for selective CT screening at population level.

Adolescent↗

PubMed2006

A prediction rule to identify low-risk patients with pulmonary embolism.

BACKGROUND: A simple prognostic model could help identify patients with pulmonary embolism who are at low risk of death and are candidates for outpatient treatment. METHODS: We randomly allocated 15,531 retrospectively identified inpatients who had a discharge diagnosis of pulmonary embolism from 186 Pennsylvania hospitals to derivation (67%) and internal validation (33%) samples. We derived our rule to predict 30-day mortality using classification tree analysis and patient data routinely available at initial examination as potential predictor variables. We used data from a European prospective study to externally validate the rule among 221 inpatients with pulmonary embolism. We determined mortality and nonfatal adverse medical outcomes across derivation and validation samples. RESULTS: Our final model consisted of 10 patient factors (age > or = 70 years; history of cancer, heart failure, chronic lung disease, chronic renal disease, and cerebrovascular disease; and clinical variables of pulse rate > or = 110 beats/min, systolic blood pressure < 100 mm Hg, altered mental status, and arterial oxygen saturation < 90%). Patients with none of these factors were defined as low risk. The 30-day mortality rates for low-risk patients were 0.6%, 1.5%, and 0% in the derivation, internal validation, and external validation samples, respectively. The rates of nonfatal adverse medical outcomes were less than 1% among low-risk patients across all study samples. CONCLUSIONS: This simple prediction rule accurately identifies patients with pulmonary embolism who are at low risk of short-term mortality and other adverse medical outcomes. Prospective validation of this rule is important before its implementation as a decision aid for outpatient treatment.

Age Factors↗

PubMed2026

Cross-Platform Proteomics and Machine Learning Algorithms Nominate Plasma Biomarkers of Stroke Diagnosis.

BACKGROUND: Blood-based biomarkers for stroke subtyping could improve triage in emergency settings. We used cross-platform proteomics to identify plasma biomarkers differentiating major stroke diagnostic groups. METHODS: We conducted a case-control study using 2 biorepositories. Plasma was collected in the emergency department from adults with suspected stroke before therapeutic intervention. Differentially enriched proteins were identified across acute ischemic stroke, intracerebral hemorrhage, transient ischemic attack, and stroke mimics using SomaScan discovery proteomics (Grady). Differentially enriched proteins were nominated using pairwise and multigroup comparisons and adjusted for clinical covariates. Protein panels were created using least absolute shrinkage and selection operator logistic regression. Internal validation used repeated nested cross-validation (rCV) and targeted mass spectrometry (MS), while external validation used data-independent acquisition  mass spectrometry in an independent cohort (Yale). RESULTS: We included 100 subjects (40 with acute ischemic stroke, 20 with intracerebral hemorrhage, 20 with transient ischemic attack, 20 with stroke mimics) in discovery and 80 subjects (20 per group) in external validation cohorts. SomaScan quantified 7307 proteins, of which 61 differentiated stroke subtypes. We identified 7 protein classifiers for acute ischemic stroke (rCV-area under the curve, 0.82 [95% CI, 0.78-0.86]), 6 for intracerebral hemorrhage (rCV-area under the curve, 0.70 [95% CI, 0.64-0.76]), 8 for transient ischemic attack (rCV-area under the curve, 0.78 [95% CI, 0.73-0.84]), and 7 for stroke mimics (rCV-area under the curve, 0.81 [95% CI, 0.77-0.86]). Targeted proteomics internally validated 11 proteins, and data-independent acquisition-mass spectrometry externally validated 32 proteins, including VTN (vitronectin), PLG (plasminogen), and S100A9 as top stroke mimics, transient ischemic attack, and intracerebral hemorrhage classifiers. CONCLUSIONS: This study highlights plasma proteomics as a valuable tool for discovering protein biomarkers of stroke diagnosis. These findings support further validation in larger, multicenter cohorts to facilitate biomarker-guided stroke diagnosis in acute care.

Humans↗

PubMed2004

Validation of internal control genes for gene expression analysis in diabetic glomerulosclerosis.

BACKGROUND: Gene expression analysis is an invaluable tool in the study of diabetic glomerulosclerosis. The necessary denominator for the quantitative expression of a specific gene is the expression level of a second gene that is presumed to remain unchanged. Thus, it is critical that the stability of this housekeeping gene in diabetic glomeruli or in cultured glomerular cells is not altered by the disease or a high glucose environment, respectively. Although gene expression quantification, achieved by Northern blot analysis or real-time reverse transcription-polymerase chain reaction (RT-PCR) has been extensively applied in diabetic renal tissue in vivo and in vitro, there are no studies validating the use of any specific endogenous control gene in these measurements. METHODS: We performed real-time RT-PCR using RNA from microdissected diabetic glomeruli and from mesangial cells cultured in high glucose concentration to investigate gene expression stability of beta-actin, glyceraldehyde-3-phosphate dehydrogenase (GADPH), phospholipase A2, beta2-microglobulin, acidic ribosomal protein 36B4, and cyclophilin A. RESULTS: Using an analysis method which is independent of gene abundance and compares the pair-wise variation of a given housekeeping gene with all other control genes, beta-actin and phospholipase A2, were found to be the most stable genes in diabetic glomeruli and in primary mesangial cells exposed to 20 mmol/L glucose. CONCLUSION: It is proposed that the expression level of these genes is the best reference to evaluate relative changes in gene activity in diabetic/high glucose exposed glomerular tissues.

Actins↗

PubMed2001

The royal free interview for spiritual and religious beliefs: development and validation of a self-report version.

BACKGROUND: Spiritual beliefs are rarely considered in psychological or medical publications. We recently published the psychometric properties of an interview designed to measure religious and spiritual belief. In this study, we aimed to develop this instrument further as a self-report questionnaire and to make it more comprehensive by including measurement of spiritual experiences in addition to faith or intellectual assent. METHODS: Based on extensive discussion with colleagues, advice from users of the interview and comments from respondents, a self-report format was designed. We then evaluated the final format of the questionnaire in terms of (1) patterns of response and demographic predictors of beliefs; (2) test-retest reliability and internal consistency; (3) criterion and internal validity; and (4) the nature of spiritual experiences and their relationship to beliefs and strength of beliefs. RESULTS: Two hundred and ninety-seven people took part in the validity and reliability tests of the questionnaire. Criterion validity, predictive validity, internal consistency and test-retest reliability were acceptably high. The instrument consistently differentiated between people with high and low spiritual beliefs. CONCLUSIONS: This instrument is brief and simple to complete. We would recommend that measures of religious and/or spiritual belief like this be more widely applied in health services research as they evaluate aspects of people's lives that go somewhat further than health status or quality of life.

Adult↗

PubMed2004

A clinical and echocardiographic score for assigning risk of major events after dobutamine echocardiograms.

OBJECTIVES: We sought to develop and validate a risk score combining both clinical and dobutamine echocardiographic (DbE) features in 4890 patients who underwent DbE at three expert laboratories and were followed for death or myocardial infarction for up to five years. BACKGROUND: In contrast to exercise scores, no score exists to combine clinical, stress, and echocardiographic findings with DbE. METHODS: Dobutamine echocardiography was performed for evaluation of known or suspected coronary artery disease in 3156 patients at two sites in the U.S. After exclusion of patients with incomplete follow-up, 1456 DbEs were randomly selected to develop a multivariate model for prediction of events. After simplification of each model for clinical use, the models were internally validated in the remaining DbE patients in the same series and externally validated in 1733 patients in an independent series. RESULTS: The following score was derived from regression models in the modeling group (160 events): DbE risk = (age.0.02) + (heart failure + rate-pressure product <15000).0.4 + (ischemia + scar).0.6. The presence of each variable was scored as 1 and its absence scored as 0, except for age (continuous variable). Using cutoff values of 1.2 and 2.6, patients were classified into groups with five-year event-free survivals >95%, 75% to 95%, and <75%. Application of the score in the internal validation group (265 events) gave equivalent results, as did its application in the external validation group (494 events, C index = 0.72). CONCLUSIONS: A risk score based on clinical and echocardiographic data may be used to quantify the risk of events in patients undergoing DbE.

Cardiotonic Agents↗

PubMed1995

Measuring sexual functioning in premenopausal women.

OBJECTIVE: To assess the validity and reliability of a measure of sexual function for premenopausal women. DESIGN: A self-administered sexual function questionnaire, derived from the Sabbatsberg Sexual Self-Rating Scale, and other health measures were given to women who were randomly sampled from the community health index. SUBJECTS: One hundred and forty-eight premenopausal women aged between 45 and 49 years. MAIN OUTCOME MEASURES: The content validity, internal consistency and construct validity of the revised sexual rating scale. RESULTS: One hundred and thirty-seven women (92%) responded to the main questionnaire and 89 (60%) completed the sexual rating scale, which possessed a high level of internal consistency; scores on the sexual rating scale, which possessed a high level of internal consistency; scores on the sexual ratings scale had small to moderate correlations with the measures of health, two of which (depression and role limitations attributable to emotional problems) were sufficient to explain 25% of the variation in the sexual functioning scores. CONCLUSION: Questions derived from the Sabbatsberg sexual self-rating scale have been used to construct a simple, acceptable, valid and reliable measure of sexual functioning for women in the 45 to 49 years of age group. Such a measure could be widely used as an adjunct to clinical and more general measures of health in order to assess the impact of interventions on sexual functioning within clinical trials.

Female↗