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BackgroundGlobally, the nursing profession faces shortages, high turnover, and inequitable distribution. These problems are particularly acute in South East Asia. The present paper describes the design and initial findings of the Thai Nurse Cohort Study (TNCS).MethodsThe TNCS is a longitudinal prospective cohort study comprising multiple age cohorts, initiated in 2009 and expected to run until 2027. Cohorts comprise registered nurses (RN) holding professional licenses granted by the Thailand Nursing and Midwifery Council. Follow-up is at 3-year intervals, with new (younger) TNCS cohorts introduced and older, no-longer eligible members checked out. This maintains the cohort size as representative of the Thai RN population. The first survey round (2009) used a self-administered mailed questionnaire. The second round (2012) provided follow-up of the initial cohort and formed the baseline survey of new entries.ResultsThe sampling frame for the first round was 142,699 licensed RN; 50,200 age-stratified participants were randomly selected and mailed the questionnaire, and 18,198 questionnaires were returned owing to incorrect addresses. Of the remaining 32,002 participants, 18,756 (58.6 %) responded (average age 43.7 ± 9.8 years). About 15.4 % (equivalent to 20,000 of the current RN population), reported an intention to leave their nursing career. The second round achieved a follow-up rate of 60.2 %. This round included 3020 participants randomly selected from 6402 new RN (response rate, 38.3 %; mean age 23.1 ± 3.5 years). In this round, 11.2 % reported they intended to leave nursing in the next 2 years.ConclusionsThese two survey rounds have highlighted that Thailand is facing critical nurse shortages. A high rate of nurses expressed an intention to leave the profession; the capacity to replace these potential losses is much lower.

The findings add to increasing international evidence that favourable nurse working conditions, low nurse-to-patient ratio and richer skill mix result in positive patient outcomes. Health systems can foster nurses to perform high-quality care by improving work conditions, and providing sufficient nurses and resources.

Binge drinking, an extreme drinking pattern and the most common form of hazardous alcohol consumption among university students, has remained a public health concern with physical, psychological, academic, and social problems. Tracking multiple factors is needed to find ways to deal with such hazardous drinking patterns and their adverse consequences. In Thailand, the particular factors leading to binge drinking patterns among university students are still not recognized. Four hundred thirteen university students in Northern Thailand self-administered a Web-based survey about the causal factors. The survey was based on a hypothesized model from the Social Ecological Model and from empirical studies. There were four factors that were hypothesized to directly increase binge drinking behavior: attitudes toward drinking, peer influence, physical environments of drinking, and alcohol advertisements. However, there were another four factors that were hypothesized to directly decrease binge drinking behavior: drinking refusal self-efficacy, university alcohol regulations, alcohol public policies, and knowledge. Through testing of the hypothesized model by Structural Equation Modeling, the causal model of binge drinking among Thai university students revealed “binge drinking refusal self-efficacy” (β = −.22, p < .001) and “peer influence” (β = −.14, p < .05) as significant negative factors and “physical environments” (β = .18, p < .001) as a positive predictor regarding binge drinking. The study shows how healthcare providers may be able to lessen binge drinking by designing effective prevention programs centering on an intrapersonal factor (binge drinking refusal self-efficacy), an interpersonal factor (peer influence), and a community factor (physical environments).

Decisions about nurse staffing levels in intensive care units (ICUs) should be guided by research to ensure optimal outcomes. This descriptive correlational study in a large Thai hospital was designed to evaluate the effect of nurse staffing levels on the costs of care, in terms of medical care cost per patient day and health personnel cost per patient day, in ICUs. The costing data were collected prospectively from the records of 242 critically ill patients while the nurse staffing levels were extracted from hospital management reports. The findings showed that a nurse staffing model with a higher number of registered nurses (RNs) led to an increase in the health personnel cost per patient day. However, a greater number of RNs was associated with improved patient safety and efficiency, thereby reducing the length of stay and the costs of care in the long term. This study provides evidence to support decisions by hospital administrators concerning RN staffing levels.