Structural equation modeling of the relationship between nursing students' quality of life and academic resilience.

Objective: Across the Middle Eastern countries, there is a lack of studies exploring the connection between the quality of life (QoL) and academic resilience of nursing students. This study determines the association between nursing students' profile variables and their QoL and academic resilience (AR). Methods: A descriptive cross-sectional design with structural equation modeling (SEM) was adopted. This study was conducted at the College of Nursing at the University of Ha'il, KSA. Survey questionnaires using the 12-item Brunnsviken Brief Quality of Life Scale (BBQ) and 30-item Academic Resilience Scale (ARS-30) were utilised to collect data from nursing students (n = 384). SEM via latent variable analysis (lavaan) software version 0.6-7 was used for statistical derivation and analysis. Results: SEM revealed no correlation with QoL and AR when compared using the participants' profile variables (gender, year level, and enrolled units). There was a correlation between the grade point average (GPA) and QoL. However, no association was found between QoL and AR. Conclusion: GPA exhibited a positive correlation with QoL; thus, nursing students with higher GPA have a more stable and desirable QoL. Additionally, our findings illustrate the individuality of nursing students despite their shared characteristics.

An Empirical Q-Matrix Validation Method for the Polytomous G-DINA Model.

A number of empirically based Q-matrix validation methods are available in the literature, all of which were developed for cognitive diagnosis models (CDMs) involving dichotomous attributes. However, in many applications, it is more instructionally relevant to classify students into more than two categories (e.g., no mastery, basic mastery, and advanced mastery). To extend the practical utility of CDMs, methods for validating the Q-matrix for CDMs that measure polytomous attributes are needed. This study focuses on validating the Q-matrix of the generalized deterministic input, noisy, "and" gate model for polytomous attributes (pG-DINA). The pGDI, an extension of the G-DINA model discrimination index, is proposed for polytomous attributes. The pGDI serves as the basis of a validation method that can be used not only to identify potential misspecified q-entries, but also to suggest more appropriate attribute-level specifications. The theoretical properties of the pGDI are underpinned by several mathematical proofs, whereas its practical viability is examined using simulation studies covering various conditions. The results show that the method can accurately identify misspecified q-entries and suggest the correct attribute-level specifications, particularly when high-quality items are involved. The pGDI is applied to a proportional reasoning test that measures several polytomous attributes.

Risk factors for locoregional metastasis, distant metastasis and persistent disease in micropapillary thyroid cancer among Filipinos

BACKGROUND: Micropapillary Thyroid Cancer (MPTC) is defined as papillary thyroid cancer measuring less than one centimeter in size. Although there have been many studies involving MPTC, there is still a gap in the understanding of the behavior of MPTC in the Filipino population. OBJECTIVES: This study aims to determine risk factors and prevalence of locoregional and distant metastasis upon diagnosis and the risk factors for persistent disease after thyroidectomy among patients with MPTC. METHODS: This is a retrospective study that included all patients with histopathology result of MPTC from January 1, 2004 to December 31, 2012. Patients who had accompanying well differentiated thyroid tumors other than MPTC and those patients with a diagnosis of MPTC with no follow up after the surgery were excluded. RESULTS: A total of 109 patients were eligible for the study. The mean age was 46.06 years with majority being female (96.3%). The average tumor size was 0.502 cm. Seventy-five  (68.81%) received Radioactive Iodine Therapy (RAI) after thyroidectomy. Nineteen patients (17.92%) had multifocal disease while 11 (10.09%) had multicentric disease. Fifteen patients (13.76%) had locoregional metastasis while eight (7.34%) had distant metastasis on diagnosis. Out of the 91 patients included for analysis of persistent disease, eight patients (8.79%) had persistent disease. Exact logistic regression showed that locoregional metastasis (p=0.0044) is a risk factor for distant metastasis at diagnosis. Age, sex, tumor size, multifocality, multicentricity, RAI, and extent of surgery did not reach statistical significance as independent risk factor for locoregional, distant metastasis on diagnosis, and persistent disease. CONCLUSION: Although MPTC is considered an indolent type of well differentiated thyroid cancer, there are certain patients who may present with metastasis at diagnosis. Our data showed that locoregional metastasis is a risk factor for distant metastasis on diagnosis in patients having MPTC.