THE RELATIVE SIGNIFICANCE OF SYNTACTIC KNOWLEDGE AND VOCABULARY KNOWLEDGE IN SECOND LANGUAGE LISTENING COMPREHENSION

The main purpose of the current study was to examine the role of vocabulary knowledge (VK) and syntactic knowledge (SK) in L2 listening comprehension, as well as their relative significance. Unlike previous studies, the current project employed assessment tasks to measure aural and proceduralized VK and SK. In terms of VK, to avoid under-representing the construct, measures of both breadth (VB) and depth (VD) were included. Additionally, the current study examined the role of VK and SK by accounting for individual differences in two important cognitive factors in L2 listening: metacognitive knowledge (MK) and working memory (WM). Also, to explore the role of VK and SK more fully, the current study accounted for the negative impact of anxiety on WM and L2 listening. The study was carried out in an English as a Foreign Language (EFL) context, and participants were 263 Iranian learners at a wide range of English proficiency from lower-intermediate to advanced. Participants took a battery of ten linguistic, cognitive and affective measures. Then, the collected data were subjected to several preliminary analyses, but structural equation modeling (SEM) was then used as the primary analysis method to answer the study research questions. Results of the preliminary analyses revealed that MK and WM were significant predictors of L2 listening ability; thus, they were kept in the main SEM analyses. The significant role of WM was only observed when the negative effect of anxiety on WM was accounted for. Preliminary analyses also showed that VB and VD were not distinct measures of VK. However, the results also showed that if VB and VD were considered separate, VD was a better predictor of L2 listening success. The main analyses of the current study revealed a significant role for both VK and SK in explaining success in L2 listening comprehension, which differs from findings from previous empirical studies. However, SEM analysis did not reveal a statistically significant difference in terms of the predictive power of the two linguistic factors. Descriptive results of the SEM analysis, along with results from regression analysis, indicated to a more significant role for VK.

Predictors of Patient Activation Among Underserved Patients in a Nurse-managed Health Center: A Pilot Study

The concept of patient activation has gained traction as the term referring to patients who understand their role in the care process and have “the knowledge, skills and confidence” necessary to manage their illness over time (Hibbard & Mahoney, 2010). Improving health outcomes for vulnerable and underserved populations who bear a disproportionate burden of health disparities presents unique challenges for nurse practitioners who provide primary care in nurse-managed health centers. Evidence that activation improves patient self-management is prompting the search for theory-based self-management support interventions to activate patients for self-management, improve health outcomes, and sustain long-term gains. Yet, no previous studies investigated the relationship between Self-determination Theory (SDT; Deci & Ryan, 2000) and activation. The major purpose of this study, guided by the Triple Aim (Berwick, Nolan, & Whittington, 2008) and nested in the Chronic Care Model (Wagner et al., 2001), was to examine the degree to which two constructs– Autonomy Support and Autonomous Motivation– independently predicted Patient Activation, controlling for covariates. For this study, 130 nurse-managed health center patients completed an on-line 38-item survey onsite. The two independent measures were the 6-item Modified Health Care Climate Questionnaire (mHCCQ; Williams, McGregor, King, Nelson, & Glasgow, 2005; Cronbach’s alpha =0.89) and the 8-item adapted Treatment Self-Regulation Questionnaire (TSRQ; Williams, Freedman, & Deci, 1998; Cronbach’s alpha = 0.80). The Patient Activation Measure (PAM-13; Hibbard, Mahoney, Stock, & Tusler, 2005; Cronbach’s alpha = 0.89) was the dependent measure. Autonomy Support was the only significant predictor, explaining 19.1% of the variance in patient activation. Five of six autonomy support survey items regressed on activation were significant, illustrating autonomy supportive communication styles contributing to activation. These results suggest theory-based patient, provider, and system level interventions to enhance self-management in primary care and educational and professional development curricula. Future investigations should examine additional sources of autonomy support and different measurements of autonomous motivation to improve the predictive power of the model. Longitudinal analyses should be conducted to further understand the relationship between autonomy support and autonomous motivation with patient activation, based on the premise that patient activation will sustain behavior change.