Objectives: To develop a valid, reliable measure that reflected the environment of respectfulness within the ICU setting. Design: We developed a preliminary survey instrument based on conceptual domains of respect identified through prior qualitative analyses of ICU patient, family member, and clinician perspectives. The initial instrument consisted of 21 items. After five cognitive interviews and 16 pilot surveys, we revised the instrument to include 23 items. We used standard psychometric methods to analyze the instrument. Settings: Eight ICUs serving adult patients affiliated with a large university health system. Subjects: ICU clinicians. Interventions: None. Measurements and Main Results: Based on 249 responses, we identified three factors and created subscales: General Respect, Respectful Behaviors, and Disrespectful Behaviors. The General Respect subscale had seven items (α = 0.932) and reflected how often patients in the ICU are treated with respect, in a dignified manner, as an individual, equally to all other patients, on the “same level” as the ICU team, as a person, and as you yourself would want to be treated. The Respectful Behaviors subscale had 10 items (α = 0.926) and reflected how often the ICU team responds to patient and/or family anxiety, makes an effort to get to know the patient and family as people, listens carefully, explains things thoroughly, gives the opportunity to provide input into care, protects patient modesty, greets when entering room, and talks to sedated patients. The subscale measuring disrespect has four items (α = 0.702) and reflects how often the ICU team dismisses family concerns, talks down to patients and families, speaks disrespectfully behind their backs, and gets frustrated with patients and families. Conclusions: We created a reliable set of scales to measure the climate of respectfulness in intensive care settings. These measures can be used for ongoing quality improvement that aim to enhance the experience of ICU patients and their families. Study data were collected and managed using Research Electronic Data Capture (REDCap) electronic data capture tools hosted at Johns Hopkins University. REDCap is a secure, web-based application designed to support data capture for research studies, providing 1) an intuitive interface for validated data entry, 2) audit trails for tracking data manipulation and export procedures, 3) automated export procedures for seamless data downloads to common statistical packages, and 4) procedures for importing data from external sources. Supplemental digital content is available for this article. Direct URL citations appear in the printed text and are provided in the HTML and PDF versions of this article on the journal’s website (http://ift.tt/29S62lw). Supported, in part, by the National Institutes of Health (NIH) George and Betty Moore Foundation. Dr. Beach’s, Ms. Topazian’s, and Drs. Sugarman’s and Geller’s institutions received funding from the George and Betty Moore Foundation. Dr. Beach’s institution also received funding from the National Institutes of Health (NIH) (K24 Grant) and the Greenwall Foundation; and she received support for article research from the NIH. Dr. Sugarman disclosed that he serves on the Merck KGaA Bioethics Advisory Panel and Stem Cell Research Oversight Committee, Quintiles’ Ethics Advisory Panel, and he has consulted with Novartis on a bioethics issue (none of which are related to the content of this article). Dr. Geller received support for article research from the Gordon and Betty Moore Foundation. Dr. Chan has disclosed that she does not have any potential conflicts of interest. For information regarding this article, E-mail: mcbeach@jhmi.edu Copyright © by 2018 by the Society of Critical Care Medicine and Wolters Kluwer Health, Inc. All Rights Reserved.
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