A scoping review of Q methodology nursing education studies

Perspectives on advance care planning and related end-of-life care in people with heart failure: A Q methodology study

Negative perspectives around advance care planning (ACP) prevent people with heart failure (HF) from preparing their end-of-life (EOL) effectively. A Q methodology study was conducted to identify types of ACP perspectives in Koreans with HF. The Q sample (31 statements representing ACP perspectives) was constructed through an extensive literature review and in-depth qualitative interview. The P sample (individuals with HF) completed each grid with a statement on the Q sorting table. The data were analyzed using the PQ program. Individuals with HF have both different and common perspectives on ACP. Three types of perspectives were identified: "positive acceptance," "contemplative support," and "hesitancy in acceptance." Common perspectives across types indicated that people with HF had positive attitudes toward ACP and emphasized their autonomy in EOL decisions. Clinicians need to consider these different and common perspectives on ACP to facilitate patients' engagement and provide relevant support.

Identifying, classifying and prioritizing factors affecting human errors in the mine design process: A mixed methods research

BACKGROUND: Mines are often home to many dangers with a high rate of accidents and occupational diseases. One of the most effective ways to prevent these adverse incidents is to identify and control the influential factors causing human error in design and the ensuing negative consequences. OBJECTIVE: This study aimed to explore, categorize and prioritize factors affecting human errors in the mine design process. METHODS: The study has a mixed-method design combining qualitative and quantitative data. In the qualitative phase, the required data were collected by conducting semi-structured interviews with 12 surface mine designers. The causes of errors were extracted and categorized by the latent content analysis using MAXQDA2022 software. The identified causes in the qualitative phase were sent to expert designers in Q tables, and the data were analyzed by factor analysis. RESULTS: Of the identified codes in the qualitative phase, 40 main themes in five different categories (individual, organizational, external, task, and environmental factors) were determined as causes. The results of the quantitative phase suggest the existence of four different mental patterns regarding the causes of design errors (DEs). The data analysis also shows that organizational and personal factors, particularly supervision and inspection, experience, and technical knowledge, were the strongest causes of DEs and environmental (hotness, coldness, indoor air quality, and noise) and external (work-family conflict) factors being the weakest ones. CONCLUSION: This study not only identifies and categorizes the causes of design errors in the mining industry but also suggests some control strategies for these errors based on the mental patterns of the experts.