Background: Improving sleep for hospitalized patients is an essential clinical need. Compared to the traditional "one-size-fits-all" interventions designed by clinicians for all patients, an individualized strategy engaging patients to identify salient sleep disruptors and seek their input how to address these disruptors are more likely to succeed. Followed by our work of developing the Factors Affecting Inpatient Sleep (FAIS) scale, in this report we developed a set of icons illustrating 14 common sleep disruptors on the FAIS scale, and proposed behavioral sleep promotion tips addressing each sleep disruptor. The set of icons and sleep promotion tips were built into the mobile health (mHealth) tool SLEEPKit, which was the start of our endeavor using mHealth technology to support individualized sleep promotion.
Methods: A participatory iterative approach including feedbacks from patients, family members, and clinicians was used to develop and refine the icons and sleep promotion tips. Focus groups were used to inform the initial development and to brainstorm for the refinement of the icons. Individual interviews with patients and clinicians were conducted to validate each version of the icons using a standardized Content Validity Index (CVI) on a 4-point Likert scale, and offered comments and suggestions for improvement. Strategies of sleep promotion were first identified by the literature review, and then enriched by the summary of data from our previous work. Focus groups were conducted in order to learn empirically if the sleep promotion tips on the current version were acceptable to both patients and clinicians, and how they could be improved.
Results: Six focus groups were conducted and achieved saturation in suggestions for improvement. A total of 5 patients and 3 family members who served on the Patient/ Family Advisory Council, and 42 nurses who served on the interdisciplinary professional practice committees participated in the focus groups. A total of 75 patients and 50 clinicians offered individual feedback and the CVI test for the icons. Successive two or four phases of iterative icon evaluation and refinement were carried out until the average CVI ratings for each icon achieved 3 and above. The sleep promotion tips were created to demonstrate a collaborative effort between patients and clinicians. To empower patients for bedside communication related to their sleep, examples of communication starters ("Try saying") were included in the tips for patients.
Conclusions: By using the participatory iterative approach, these icons for common sleep disturbing factors were understandable by both patients and clinicians, and the sleep promotion tips were perceived to be feasible and effective in the acute care hospital setting. This work moved the individualized sleep promotion forward, and supported the development of a novel mHealth tool for inpatient sleep promotion tailored to individual patient's needs.
Keywords: Sleep promotion; acute care; hospitalized patients; mobile health (mHealth).
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