Being honest with causal language in writing for publication

The misleading use of causal language in publication is problematic for authors, reviewers and consumers of the information. Published research in quality journals has important knowledge implications and it is, therefore, contingent on authors to use language that is accurate and appropriate to their work. Language implying unsupported causal relationships may overstate the evidence-base, especially if accepted by uncritical readers or unwitting members of the general public who may not understand how to interpret inferential statistics

Exploratory factor analysis and principal component analysis in clinical studies: Which one should you use?

Factor analysis covers a range of multivariate methods used to explain how underlying factors influence a set of observed variables. When research aims to identify these underlying factors, exploratory factor analysis (EFA) is used. In contrast, when the aim is to test whether a set of observed variables represents the underlying factors, in accordance with an existing conceptual basis, confirmatory factor analysis is performed. EFA has many similarities with a commonly used data reduction technique called principal component analysis (PCA). These similarities, along with using the related terms factor and component interchangeably, contribute to confusion in analysis. The difficulty in identifying the appropriate use of statistical methods and their application and interpretation impacts clinical and research implications (Beavers et al., 2013; Tabachnick & Fidell, 2001). We acknowledge previous articles in nursing journals offering guidance on the use of factor analysis (Gaskin & Happell, 2014; Watson & Thompson, 2006)

Using risk and odds ratios to assess effect size for meta-analysis outcome measures

Best practice is built on the principle of aggregating all available evidence on a topic to make a clinical decision on the most appropriate intervention for the situation at hand. Systematic reviews and meta-analyses are powerful tools that summarize the evidence for current best practice guidelines for the available interventions for a particular problem (Moher, Liberati, Tetzlaff, & Altman, 2009). Meta-analysis combines the results of multiple studies to produce an aggregated and more precise estimates of the benefits of the interventions. Meta-analysis of high-quality randomized trials is considered the highest level of evidence to inform practice

Effect of angiotensin-converting enzyme inhibitor and angiotensin receptor blocker initiation on organ support-free days in patients hospitalized with COVID-19

IMPORTANCE Overactivation of the renin-angiotensin system (RAS) may contribute to poor clinical outcomes in patients with COVID-19. Objective To determine whether angiotensin-converting enzyme (ACE) inhibitor or angiotensin receptor blocker (ARB) initiation improves outcomes in patients hospitalized for COVID-19. DESIGN, SETTING, AND PARTICIPANTS In an ongoing, adaptive platform randomized clinical trial, 721 critically ill and 58 non–critically ill hospitalized adults were randomized to receive an RAS inhibitor or control between March 16, 2021, and February 25, 2022, at 69 sites in 7 countries (final follow-up on June 1, 2022). INTERVENTIONS Patients were randomized to receive open-label initiation of an ACE inhibitor (n = 257), ARB (n = 248), ARB in combination with DMX-200 (a chemokine receptor-2 inhibitor; n = 10), or no RAS inhibitor (control; n = 264) for up to 10 days. MAIN OUTCOMES AND MEASURES The primary outcome was organ support–free days, a composite of hospital survival and days alive without cardiovascular or respiratory organ support through 21 days. The primary analysis was a bayesian cumulative logistic model. Odds ratios (ORs) greater than 1 represent improved outcomes. RESULTS On February 25, 2022, enrollment was discontinued due to safety concerns. Among 679 critically ill patients with available primary outcome data, the median age was 56 years and 239 participants (35.2%) were women. Median (IQR) organ support–free days among critically ill patients was 10 (–1 to 16) in the ACE inhibitor group (n = 231), 8 (–1 to 17) in the ARB group (n = 217), and 12 (0 to 17) in the control group (n = 231) (median adjusted odds ratios of 0.77 [95% bayesian credible interval, 0.58-1.06] for improvement for ACE inhibitor and 0.76 [95% credible interval, 0.56-1.05] for ARB compared with control). The posterior probabilities that ACE inhibitors and ARBs worsened organ support–free days compared with control were 94.9% and 95.4%, respectively. Hospital survival occurred in 166 of 231 critically ill participants (71.9%) in the ACE inhibitor group, 152 of 217 (70.0%) in the ARB group, and 182 of 231 (78.8%) in the control group (posterior probabilities that ACE inhibitor and ARB worsened hospital survival compared with control were 95.3% and 98.1%, respectively). CONCLUSIONS AND RELEVANCE In this trial, among critically ill adults with COVID-19, initiation of an ACE inhibitor or ARB did not improve, and likely worsened, clinical outcomes. TRIAL REGISTRATION ClinicalTrials.gov Identifier: NCT0273570

Motivation for a successful health career

It has been said that the greatest motivators are those which the person values but does not currently possess (Wiley, 1997), with motivation integral to the concept of achievement. Motivation has direct links to behaviour (Nicholson et al., 1995) and thus focussing on what we want can encourage us to change our behaviours and undertake that which enhances performance. Motivation cannot stand alone, but rather should be in lockstep with other attributes such as self-initiative and self-organisation to support positive behaviours (Marques et al., 2019)

Climate and mental health

Extreme and unpredictable climatic conditions can have significant impacts on health and wellbeing. While attention to date has addressed threats to physical health and safety, mental health and wellbeing can also be seriously affected by climatic conditions and weather events such as extreme heat and cold, bushfires, hurricanes, and floods. With rising concern about both climate and mental health, it is timely to consider the relationship between the two and the possible implications for health professionals. This column focuses on how nurses can take a key role in improving responses to emerging and increasing mental health challenges linked to climate

Nursing daily routine activities: A considered response or coping mechanism?

Routine activities have important roles in the daily work-place. Routine provides a sense of coordination, organisation and stability and its very regularity demonstrates its important place in the everyday (Aldrich & Dickie, 2013; Zisberg et al., 2007). A routine can be a rule, such as the ideal routine, as well as a behaviour, where the routine is expressed as a pattern (Feldman & Pentland, 2003; Pentland & Feldman, 2005). Routine can be viewed both positively and negatively. Perceptions of routinisation may consider it rigid and hence stifling creativity (Aldrich & Dickie, 2013) and perpetuating monotony of repetition (Rytterstr€om et al., 2011). It can be viewed as an unconsidered, automated-like response, suppressing more considered approaches. Alternatively, routine can present a constructed approach to tasks, and provides a negotiation between the needs of the situation and our personal capabilities (Aldrich & Dickie, 2013)

Small business ownership and mental health

Small businesses contribute greatly to economic activity and provide employment for large proportions of people worldwide. While the definition of a small business, or a small to medium enterprise (SME), varies across countries, the significant economic contribution made by entrepreneurial activity is consistent. In Australia, businesses with less than 20 workers employed approximately 4.8 million people in 2017, comprising 44% of the workforce (Gilfillan, 2018). Similarly, there are over 4.5 million such business in the USA employing over 20 million people (United States Census Bureau, 2019)

The earnestness of being important: Reporting non-significant statistical results

Quantitative research relies on assessing statistical significance, most commonly expressed in the form of a probability value research hypotheses, however, many studies provide results that are not statistically significant. The literature provides many examples of erroneous reporting and misguided presentation and description of such results (Parsons, Price, Hiskens, Achten, & Costa, 2012

When the problem is ‘global’ but the response is not: inequities in mental health services in low-and middle-income countries

The impact on those who experience mental illness and the consequences for their families and societies knows no geographic or racial boundaries. While there is important geographic variance in the prevalence and prognosis of some mental health conditions, such conditions exist in every culture and country with similar patterns including early onset and their chronic nature (Andlin-Sobocki, Jonsson, Wittchen, & Olesen, 2005)