Development and validation of the Health Promoting Behaviour for Bloating (HPBBloat) scale

© 2021 Abdullah et al. Background Health management strategies may help patients with abdominal bloating (AB), but there are currently no tools that measure behaviour and awareness. This study aimed to validate and verify the dimensionality of the newly-developed Health Promoting Behaviour for Bloating (HPB-Bloat) scale. Methods Based on previous literature, expert input, and in-depth interviews, we generated new items for the HPB-Bloat. Its content validity was assessed by experts and pre-tested across 30 individuals with AB. Construct validity and dimensionality were first determined using exploratory factor analysis (EFA) and Promax rotation analysis, and then using confirmatory factor analysis (CFA). Results During the development stage, 35 items were generated for the HPB-Bloat, and were maintained following content validity assessment and pre-testing. One hundred and fifty-two participants (mean age of 31.27 years, 68.3% female) and 323 participants (mean age of 27.69 years, 59.4% male) completed the scale for EFA and CFA, respectively. Using EFA, we identified 20 items that we divided into five factors: diet (five items), health awareness (four items), physical activity (three items), stress management (four items), and treatment (four items). The total variance explained by the EFA model was 56.7%. The Cronbach alpha values of the five factors ranged between 0.52 and 0.81. In the CFA model, one problematic latent variable (treatment) was identified and three items were removed. In the final measurement model, four factors and 17 items fit the data well based on several fit indices (root mean square error of approximation (RMSEA) = 0.044 and standardized root mean squared residual (SRMR) = 0.052). The composite reliability of all factors in the final measurement model was above 0.60, indicating acceptable construct reliability. Conclusion The newly developed HPB-Bloat scale is valid and reliable when assessing the awareness of health-promoting behaviours across patients with AB. Further validation is needed across different languages and populations.Universiti Sains Malaysia: 1001.PPSP.801225

Prevalence, associated factors and outcomes of pressure injuries in adult intensive care unit patients: the DecubICUs study

Funder: European Society of Intensive Care Medicine; doi: http://dx.doi.org/10.13039/501100013347Funder: Flemish Society for Critical Care NursesAbstract: Purpose: Intensive care unit (ICU) patients are particularly susceptible to developing pressure injuries. Epidemiologic data is however unavailable. We aimed to provide an international picture of the extent of pressure injuries and factors associated with ICU-acquired pressure injuries in adult ICU patients. Methods: International 1-day point-prevalence study; follow-up for outcome assessment until hospital discharge (maximum 12 weeks). Factors associated with ICU-acquired pressure injury and hospital mortality were assessed by generalised linear mixed-effects regression analysis. Results: Data from 13,254 patients in 1117 ICUs (90 countries) revealed 6747 pressure injuries; 3997 (59.2%) were ICU-acquired. Overall prevalence was 26.6% (95% confidence interval [CI] 25.9–27.3). ICU-acquired prevalence was 16.2% (95% CI 15.6–16.8). Sacrum (37%) and heels (19.5%) were most affected. Factors independently associated with ICU-acquired pressure injuries were older age, male sex, being underweight, emergency surgery, higher Simplified Acute Physiology Score II, Braden score 3 days, comorbidities (chronic obstructive pulmonary disease, immunodeficiency), organ support (renal replacement, mechanical ventilation on ICU admission), and being in a low or lower-middle income-economy. Gradually increasing associations with mortality were identified for increasing severity of pressure injury: stage I (odds ratio [OR] 1.5; 95% CI 1.2–1.8), stage II (OR 1.6; 95% CI 1.4–1.9), and stage III or worse (OR 2.8; 95% CI 2.3–3.3). Conclusion: Pressure injuries are common in adult ICU patients. ICU-acquired pressure injuries are associated with mainly intrinsic factors and mortality. Optimal care standards, increased awareness, appropriate resource allocation, and further research into optimal prevention are pivotal to tackle this important patient safety threat

Correction to: Prevalence, associated factors and outcomes of pressure injuries in adult intensive care unit patients: the DecubICUs study

The original version of this article unfortunately contained a mistake

Prevalence, associated factors and outcomes of pressure injuries in adult intensive care unit patients: the DecubICUs study

Funder: European Society of Intensive Care Medicine; doi: http://dx.doi.org/10.13039/501100013347Funder: Flemish Society for Critical Care NursesAbstract: Purpose: Intensive care unit (ICU) patients are particularly susceptible to developing pressure injuries. Epidemiologic data is however unavailable. We aimed to provide an international picture of the extent of pressure injuries and factors associated with ICU-acquired pressure injuries in adult ICU patients. Methods: International 1-day point-prevalence study; follow-up for outcome assessment until hospital discharge (maximum 12 weeks). Factors associated with ICU-acquired pressure injury and hospital mortality were assessed by generalised linear mixed-effects regression analysis. Results: Data from 13,254 patients in 1117 ICUs (90 countries) revealed 6747 pressure injuries; 3997 (59.2%) were ICU-acquired. Overall prevalence was 26.6% (95% confidence interval [CI] 25.9–27.3). ICU-acquired prevalence was 16.2% (95% CI 15.6–16.8). Sacrum (37%) and heels (19.5%) were most affected. Factors independently associated with ICU-acquired pressure injuries were older age, male sex, being underweight, emergency surgery, higher Simplified Acute Physiology Score II, Braden score 3 days, comorbidities (chronic obstructive pulmonary disease, immunodeficiency), organ support (renal replacement, mechanical ventilation on ICU admission), and being in a low or lower-middle income-economy. Gradually increasing associations with mortality were identified for increasing severity of pressure injury: stage I (odds ratio [OR] 1.5; 95% CI 1.2–1.8), stage II (OR 1.6; 95% CI 1.4–1.9), and stage III or worse (OR 2.8; 95% CI 2.3–3.3). Conclusion: Pressure injuries are common in adult ICU patients. ICU-acquired pressure injuries are associated with mainly intrinsic factors and mortality. Optimal care standards, increased awareness, appropriate resource allocation, and further research into optimal prevention are pivotal to tackle this important patient safety threat

Mathematical models for vector-borne infectious disease mapping with application to Dengue disease in Malaysia

Few publications consider the estimation of relative risk for vector borne infectious diseases.Most of these articles involve exploratory analysis that includes the study of covariates andtheir effects on disease distribution and the study of geographic information systems tointegrate patient-related information. The aim of this research is to introduce an alternativemethod of relative risk estimation based on stochastic SIR-SI models (susceptible-infectiverecoveredfor human populations; susceptible-infective for vector populations) for thetransmission of vector borne infectious diseases, particularly dengue disease.Firstly, we describe deterministic compartmental SIR-SI models that are suitable for denguedisease transmission. We then adapt these to develop corresponding stochastic SIR-SImodels using 'discrete time, discrete space' and 'continuous time, discrete space' data. Ourfirst type of stochastic models comprises extensions of the discrete time stochastic SIRmodel proposed by Lawson (2006) and involves the theoretical construction and iterativeevaluation of SIR-SI difference equations. Our second type of stochastic models involvescontinuous extensions of the first type of models and involves the theoretical constructionand numerical analysis of SIR-SI differential equations. Determining solutions for the lattermodels involves investigating their asymptotic properties and applying simple computationalalgorithms for solving the SIR-SI system of ordinary differential equations. Furtherdiscussion on modelling continuous space data regardless of the measurement scale of timesis also presented in this thesis.Finally, an alternative method of estimating the relative risk for dengue disease mappingbased on these stochastic SIR-SI models is developed and applied to analyse dengue datafrom Malaysia. This new approach offers better models for estimating relative risks fordengue disease mapping compared to the other common approaches, because it takes intoaccount the transmission process of the disease while allowing for covariates and spatialcorrelation between risks in adjacent regions. Although the SIR-SI model for dengue diseaseis the focus of this research, the methods extend readily to apply more generally to othervector borne infectious diseases

Vector borne infectious disease mapping with stochastic difference equations : an analysis of dengue disease in Malaysia

Few publications consider the estimation of relative risk for vector borne infectious diseases. Most of these articles involve exploratory analysis that includes the study of covariates and their effects on disease distribution and the study of geographic information systems to integrate patient-related information. The aim of this paper is to introduce an alternative method of relative risk estimation based on discrete time-space stochastic SIR-SI models (susceptible-infective-recovered for human populations; susceptible-infective for vector populations) for the transmission of vector borne infectious diseases, particularly dengue disease. Firstly, we describe deterministic compartmental SIR-SI models that are suitable for dengue disease transmission. We then adapt these to develop corresponding discrete timespace stochastic SIR-SI models. Finally, we develop an alternative method of estimating the relative risk for dengue disease mapping based on these models and apply them to analyse dengue data from Malaysia. This new approach offers a better model for estimating the relative risk for dengue disease mapping compared to the other common approaches, because it takes into account the transmission process of the disease while allowing for covariates and spatial correlation between risks in adjacent regions

Numerical analysis of the SIR-SI differential equations with application to dengue disease mapping in Kuala Lumpur, Malaysia

The main aim of this study is to describe and introduce a method of numerical analysis in obtaining approximate solutions for the SIR-SI differential equations (susceptible-infective-recovered for human populations; susceptible-infective for vector populations) that represent a model for dengue disease transmission. Firstly, we describe the ordinary differential equations for the SIR-SI disease transmission models. Then, we introduce the numerical analysis of solutions of this continuous time, discrete space SIR-SI model by simplifying the continuous time scale to a densely populated, discrete time scale. This is followed by the application of this numerical analysis of solutions of the SIR-SI differential equations to the estimation of relative risk using continuous time, discrete space dengue data of Kuala Lumpur, Malaysia. Finally, we present the results of the analysis, comparing and displaying the results in graphs, table and maps. Results of the numerical analysis of solutions that we implemented offers a useful and potentially superior model for estimating relative risks based on continuous time, discrete space data for vector borne infectious diseases specifically for dengue disease