19 research outputs found
Biomarkers of systemic inflammation and depression and fatigue in moderate clinically stable COPD
<p>Abstract</p> <p>Introduction</p> <p>COPD is an inflammatory disease with major co-morbidities. It has recently been suggested that depression may be the result of systemic inflammation. We aimed to explore the association between systemic inflammation and symptoms of depression and fatigue in patients with mainly moderate and clinically stable COPD using a range of inflammatory biomarkers, 2 depression and 2 fatigue scales.</p> <p>Method</p> <p>We assessed 120 patients with moderate COPD (FEV<sub>1</sub>% 52, men 62%, age 66). Depression was assessed using the BASDEC and CES-D scales. Fatigue was assessed using the Manchester COPD-fatigue scale (MCFS) and the Borg scale before and after 6MWT. We measured systemic TNF-α, CRP, TNF-α-R1, TNF-α-R2 and IL-6.</p> <p>Results</p> <p>A multivariate linear model of all biomarkers showed that TNF-α only had a positive correlation with BASDEC depression score (p = 0.007). TNF-α remained positively correlated with depression (p = 0.024) after further adjusting for TNF-α-R1, TNF-α-R2, 6MWD, FEV<sub>1</sub>%, and pack-years. Even after adding the MCFS score, body mass and body composition to the model TNF-α was still associated with the BASDEC score (p = 0.044). Furthermore, patients with higher TNF-α level (> 3 pg/ml, n = 7) had higher mean CES-D depression score than the rest of the sample (p = 0.03). Borg fatigue score at baseline were weakly correlated with TNF-α and CRP, and with TNF-α only after 6MWT. Patients with higher TNF-α had more fatigue after 6MWD (p = 0.054).</p> <p>Conclusion</p> <p>This study indicates a possible association between TNF-α and two frequent and major co-morbidities in COPD; i.e., depression and fatigue.</p
Evidence-based Kernels: Fundamental Units of Behavioral Influence
This paper describes evidence-based kernels, fundamental units of behavioral influence that appear to underlie effective prevention and treatment for children, adults, and families. A kernel is a behavior–influence procedure shown through experimental analysis to affect a specific behavior and that is indivisible in the sense that removing any of its components would render it inert. Existing evidence shows that a variety of kernels can influence behavior in context, and some evidence suggests that frequent use or sufficient use of some kernels may produce longer lasting behavioral shifts. The analysis of kernels could contribute to an empirically based theory of behavioral influence, augment existing prevention or treatment efforts, facilitate the dissemination of effective prevention and treatment practices, clarify the active ingredients in existing interventions, and contribute to efficiently developing interventions that are more effective. Kernels involve one or more of the following mechanisms of behavior influence: reinforcement, altering antecedents, changing verbal relational responding, or changing physiological states directly. The paper describes 52 of these kernels, and details practical, theoretical, and research implications, including calling for a national database of kernels that influence human behavior