Degenerative temporomandibular joint diseases and their relation with sleep and emotional disturbance

G*Power (Erdfelder, Faul, & Buchner, 1996) was designed as a general stand-alone power analysis program for statistical tests commonly used in social and behavioral research. G*Power 3 is a major extension of, and improvement over, the previous versions. It runs on widely used computer platforms (i.e., Windows XP, Windows Vista, and Mac OS X 10.4) and covers many different statistical tests of the t, F, and chi2 test families. In addition, it includes power analyses for z tests and some exact tests. G*Power 3 provides improved effect size calculators and graphic options, supports both distribution-based and design-based input modes, and offers all types of power analyses in which users might be interested. Like its predecessors, G*Power 3 is free. Show more

To test the construct validity of the short-form version of the Depression anxiety and stress scale (DASS-21), and in particular, to assess whether stress as indexed by this measure is synonymous with negative affectivity (NA) or whether it represents a related, but distinct, construct. To provide normative data for the general adult population. Cross-sectional, correlational and confirmatory factor analysis (CFA). The DASS-21 was administered to a non-clinical sample, broadly representative of the general adult UK population (N = 1,794). Competing models of the latent structure of the DASS-21 were evaluated using CFA. The model with optimal fit (RCFI = 0.94) had a quadripartite structure, and consisted of a general factor of psychological distress plus orthogonal specific factors of depression, anxiety, and stress. This model was a significantly better fit than a competing model that tested the possibility that the Stress scale simply measures NA. The DASS-21 subscales can validly be used to measure the dimensions of depression, anxiety, and stress. However, each of these subscales also taps a more general dimension of psychological distress or NA. The utility of the measure is enhanced by the provision of normative data based on a large sample. Show more

As with other fields, medical sciences are subject to different sources of bias. While understanding sources of bias is a key element for drawing valid conclusions, bias in health research continues to be a very sensitive issue that can affect the focus and outcome of investigations. Information bias, otherwise known as misclassification, is one of the most common sources of bias that affects the validity of health research. It originates from the approach that is utilized to obtain or confirm study measurements. This paper seeks to raise awareness of information bias in observational and experimental research study designs as well as to enrich discussions concerning bias problems. Specifying the types of bias can be essential to limit its effects and, the use of adjustment methods might serve to improve clinical evaluation and health care practice. Show more