Objective:An easy to administer tool is needed for clinical assessment of sleep quality by healthcare providers. This study compared two brief, validated sleep questionnaires in order to identify an appropriate tool for clinical assessment. Methods:Women (N = 121) between the ages of 25-89 years (60.3 ± 15.9 years) completed the Richards-Campbell Sleep Questionnaire, the Restorative Sleep Questionnaire, and associated measures of quality of life, well-being, stress, and physical activity. Results:There were no differences in sleep quality assessments between the two questionnaires for sleep last night (daily), during the past 7 days (weekly), or during the past 4 weeks (monthly). Overall, participants reported good daily, weekly, and monthly sleep quality (mean scores 71.1-75.3 out of 100), although both questionnaires assessed significantly better (p ≤ 0.002) daily sleep quality compared to weekly and monthly. There were no floor effects for either questionnaire, but ceiling effects were noted for the Richards-Campbell Sleep Questionnaire daily and weekly versions. When participants were grouped by sleep quality, very good sleepers reported better quality of life (p˂ 0.05) and well-being (p˂ 0.001), and less stress (p˂ 0.05) compared to poor sleepers for all versions of the Restorative Sleep Questionnaire and for the Richards-Campbell Sleep Questionnaire daily and weekly versions. Conclusions:For overall identification and assessment of good versus poor sleep quality, clinicians can choose either the Richards-Campbell Sleep Questionnaire or the Restorative Sleep Questionnaire. However, caution may be needed for short-term (daily, weekly) assessment for which the Restorative Sleep Questionnaire may be more appropriate due to fewer ceiling effects.
Background:Trust building is essential for effective healthcare, including care delivered using digital health technologies (DHTs). This analysis aimed to develop an understanding of the mechanisms of trust building in relation to DHTs for diabetes using tracking and measuring tools. Methods:This was a multimethod qualitative analysis conducted in Germany, Spain, and the United States, using a behavioral science approach. Interviews were conducted with different groups of participants from June 2022 to August 2022. The interviews consisted of one-on-one interviews (90 min) with experts in the diabetes support system, online dyad interviews (120 min), and online homework (120 min) with adults with type 2 diabetes (T2D) with different mind states (struggling, juggling, and controlling) and their caregivers. Focus group discussions were conducted with healthcare professionals (HCPs; each 150 min), including general physicians, specialists, and nurses, representing a conservative or innovator persona. Results:Nine interviews were conducted with experts (n=9), 28 dyad interviews were conducted with people with T2D (n=38) and caregivers (n=18), and 15 focus group discussions were conducted with 59 HCPs. Building trust in DHTs appeared to be created differently from building trust in medications, and requires activating, motivating, and sustaining desired behavior change. DHT trust builds systematically in three levels: trust in individual's own role in diabetes management (self-efficacy), trust in data as a tool to create empowerment, and trust in viability of sustained behavior change. Conclusion:People who had built trust on all three levels felt in control of their diabetes and were motivated and engaged in DHTs. Focus on trust building is important for digital healthcare launch strategies, particularly in user conversion from consideration phase to actual initiation of use of DHTs.
