Symptoms in Patients Receiving Noninvasive Ventilation in the Intensive Care Unit

Background Although a multitude of studies have demonstrated the effectiveness of noninvasive ventilation (NIV) for treatment of respiratory insufficiency, there have been few investigations of patients’ experiences while receiving this common treatment. Identification of the presence, intensity, and distress of symptoms during NIV will inform the development and testing of interventions to best manage them and improve patients’ intensive care unit (ICU) experiences. Objective The objectives of this study were (a) to identify the presence, intensity, and distress of symptoms in patients receiving NIV in the ICU using a modified version of the Edmonton Symptom Assessment Scale (MESAS) and (b) to describe the most common and distressing symptoms experienced by patients. Methods A cross-sectional descriptive design was used with a convenience sample of 114 participants enrolled from three ICUs at one Midwestern medical center. Participants were approached if they were English-speaking, were 18 years old or older, and had an active order for NIV; exclusions included use of personal NIV equipment, severe cognitive impairment, or problems communicating. Demographic and clinical data were obtained from the electronic health record. Presence, intensity, and distress of patient-reported symptoms were obtained once using a modified, 11-item version of the MESAS. Results The mean age of participants was 68 years old, and 54.4% were male. The primary type of NIV was bi-level positive airway pressure; a nasal/oral mask was most frequently used. The symptoms experienced by most of the participants were thirst, anxiety, tiredness, and restlessness; these symptoms were rated as moderate or severe in both intensity and distress by most participants experiencing the symptoms. Discussion Patients in the ICU experience both intense and distressful symptoms that can be severe while undergoing treatment with NIV. Future research is warranted to determine these symptoms’ interrelatedness and develop interventions to effectively manage patient-reported symptoms.

Realist Approach to Qualitative Data Analysis

Background A realist approach has gained popularity in evaluation research, particularly in understanding causal explanations of how a program works (or not), the circumstances, and the observed outcomes. In qualitative inquiry, the approach has contributed to better theoretically based explanations regarding causal interactions. Objective The aim of this study was to discuss how we conducted a realist-informed data analysis to explore the causal interactions within qualitative data. Methods We demonstrated a four-step realist approach of retroductive theorizing in qualitative data analysis using a concrete example from our empirical research rooted in the critical realism philosophical stance. These steps include (a) category identification, (b) elaboration of context-mechanism-outcome configuration, (c) demi-regularities identification, and (d) generative mechanism refinement. Results The four-step qualitative realist data analysis underpins the causal interactions of important factors and reveals the underlying mechanisms. The steps produce comprehensive causal explanations that can be used by related parties—especially when making complex decisions that may affect wide communities. Discussion The core process of realist data analysis is retroductive theorizing. The four-step qualitative realist data analysis facilitates this theorizing by allowing the researcher to identify (a) patterns, (b) fluctuation of patterns, (c) mechanisms from collected data, and (d) to confirm proposed mechanisms.