The Attentional Control Scale (ACS; Derryberry & Reed, 2002) has been used to assess executive control over attention in numerous studies, but no published data have examined the factor structure of the English version. The current studies addressed this need and tested the predictive and convergent validity of the ACS subscales. In Study 1, exploratory factor analysis yielded a two-factor model with Focusing and Shifting subscales. In Study 2, confirmatory factor analysis supported this model and suggested superior fit compared to the factor structure of the Icelandic version (Ólafsson et al., 2011). Study 3 examined correlations between the ACS subscales and measures of working memory, anxiety, and cognitive control. Study 4 examined correlations between the subscales and reaction times on a mixed-antisaccade task, revealing positive correlations for antisaccade performance and prosaccade latency with Focusing scores and between switch trial performance and Shifting scores. Additionally, the findings partially supported unique relationships between Focusing and trait anxiety and between Shifting and depression that have been noted in recent research. Although the results generally support the validity of the ACS, additional research using performance-based tasks is needed.
Purpose Significant cancer-related distress affects 30-60% of women diagnosed with breast cancer. Fewer than 30% of distressed patients receive psychosocial care. Unaddressed distress is associated with poor treatment adherence, reduced quality of life, and increased healthcare costs. This study aimed to evaluate the preliminary efficacy of a new web-based, psychoeducational distress self-management program, CaringGuidance™ After Breast Cancer Diagnosis, on newly diagnosed women's reported distress.Methods One-hundred women, in five states, diagnosed with breast cancer within the prior 3 months, were randomized to 12 weeks of independent use of CaringGuidance™ plus usual care or usual care alone. The primary multidimensional outcome, distress, was measured with the Distress Thermometer (DT), the Center for Epidemiologic Studies Depression Scale (CES-D), and the Impact of Events Scale (IES) at baseline and months 1, 2, and 3. Intervention usage was continually monitored by the data analytic system imbedded within CaringGuidance™. Results Although multilevel models showed no significant overall effects, post hoc analysis showed significant group differences in slopes occurring between study months 2 and 3 on distress (F(1,70) = 4.91, p = .03, η 2 = .065) measured by the DT, and depressive symptoms (F(1, 76) = 4.25, p = .043, η 2 = .053) favoring the intervention. Conclusions Results provide preliminary support for the potential efficacy of CaringGuidance™ plus usual care over usual care alone on distress in women newly diagnosed with breast cancer. This analysis supports and informs future study of this selfmanagement program aimed at filling gaps in clinical distress management.
The pursuit of appropriate, biocompatible materials is one of the primary challenges in translational bioprinting. The requirement to refine a biomaterial into a bioink places additional demands on the criteria for candidate biomaterials. The material must enable extrusion as a liquid bioink and yet be capable of maintaining its shape in the post-printing phase to yield viable tissues, organs and biological materials. Plant-derived biomaterials show great promise in harnessing both the natural strength of plant microarchitecture combined with their natural biological roles as supporters of cell growth. The aim of this review article is to outline the most widely used biomaterials derived from land plants and marine algae: nanocellulose, pectin, starch, alginate, agarose, fucoidan, and carrageenan, with an in-depth focus on nanocellulose and alginate. The properties that render these materials as promising bioinks for three dimensional bioprinting is herein discussed alongside their potential in 3D bioprinting for tissue engineering, drug delivery, wound healing, and implantable medical devices.
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