Caryl Lynn Gay

Post-stroke fatigue affects rehabilitation, daily activities, and quality of life. Its relationship with sleep remains unclear. We aimed in the acute stroke phase to (a) describe fatigue and sleep using self-reported and objective sleep measures, (b) describe sleep apnoea and (c) explore the associations between sleep measures and post-stroke fatigue. This cross-sectional study examined Norwegian adults within 14 days of first ischaemic stroke. Fatigue was assessed with the Fatigue Severity Scale. Self-reported sleep factors (Pittsburgh Sleep Quality Index [PSQI], Epworth Sleepiness Scale) and objective WatchPAT measures (apnoea-hypopnea, sleep time, efficiency, REM/deep sleep) served as exposure variables. Multivariable regression models, adjusted for age, sex, mRS, and depression or anxiety symptoms, were used to examine associations between sleep and fatigue. Participants (n = 107, mean age 65 (SD14) years, n = 65(61%) male) had a mean NIHSS score of 2.5 [SD3.3], Fatigue Severity Scale score of 3.11 [SD1.82], and n = 71 (66%) scored as having disturbed sleep (PSQI). Mean total sleep time (n = 81) was 7.04 [SD1.46] hours and 54 (71%) had sleep apnoea. In the final multivariable model, only poor sleep quality (b = 0.45, p = 0.010) was associated with post-stroke fatigue. Addressing sleep quality in the acute stroke phase may benefit post-stroke fatigue.

Background/Objectives: Despite the importance of parent mental health for child health, there are no global prevalence data on parental mental health symptoms when children are hospitalized. We aimed to describe depression and anxiety symptom prevalence and associated factors among parents of hospitalized children. Methods: We conducted this 14-country prospective cohort survey with parents/primary caregivers staying at a nearby Ronald McDonald House^® during their child’s hospital treatment. We used the Hospital Anxiety and Depression Scale to measure depression and anxiety symptoms and validated scales and theory-based questions to measure parent, family, and child covariates. We calculated the prevalence of clinically significant or concerning symptoms of depression and anxiety, and used multivariable regression analyses to examine associations between covariates and outcomes. Results: Among 3350 participants, 1789 (49.7%) reported depression symptoms and 2286 (69.0%) reported anxiety symptoms. Worry about housing and poorer ratings of their child’s health were associated with increased risk of depression symptoms. Poorer rating of the child’s health, living with a partner, and discrimination in daily life were associated with increased risk of anxiety symptoms. Higher levels of self-care, hospital family-centered care, and social support were associated with reduced risk of depression symptoms. Higher levels of self-care and social support were associated with reduced risk of anxiety symptoms. Conclusions: Clinically significant or concerning depression and anxiety symptoms are common among parents of hospitalized children globally. Hospitals should consider offering routine mental health symptom screening and preventative mental health and support services to all parents.

Background: Digital health technologies play a pivotal role in stroke prevention and rehabilitation. However, variations in digital health literacy (DHL) among stroke survivors may impede effective use of these tools. Understanding DHL-profiles and their influencing factors is essential for tailoring interventions. Aim: This study aimed to identify DHL-profiles among stroke survivors and possible associations with sociodemographic and clinical characteristics. Methods: We conducted a cross-sectional study with 177 first-time stroke patients (2021–2022) from the Norwegian stroke registry. DHL was measured using the eHealth Literacy Questionnaire. Cluster analysis identified DHL profiles, and multinomial regression explored associations with sociodemographic and clinical variables. Results: Three distinct DHL-profiles emerged: Novices (26%), Cautious users (57%), and Navigators (17%). Novices exhibited notable DHL limitations, cautious users demonstrated moderate proficiency, and navigators displayed a high level of proficiency. Participants aged ≥67 years were five times more likely to be Novices compared to Cautious users. Lower education and cognitive functioning increased novice likelihood, whereas living alone decreased the chance of being a Navigator. Conclusions: Diverse DHL-profiles among stroke survivors highlight the need for personalized digital health services. Tailored interventions, developed through co-design and addressing specific DHL challenges, may improve equitable access and enhance usability, ultimately promoting health equity.

Objective: To qualitatively explore healthcare personnel’s (HCP) experiences with health literacy sensitivity in relation to work satisfaction and stress. Being HL sensitive means that HCP have adequate knowledge, skills, and attitudes to follow up on patients’ HL needs. Methods: Four focus group interviews were conducted with 30 hCP from a medium-sized general hospital in Oslo, Norway. We used inductive thematic analysis developed by Braun & Clark. NVivo v12 software assisted data analysis. Results: Three main themes were identified: (1) HCP experiences with HL (2) HCP experience barriers with HL sensitivity, and (3) HCP collaboration and communication are essential for HL. Variability in HL understanding among HCP may lead to challenges in providing patient-centered care. Factors such as heavy workloads, cultural barriers, and organizational limitations hinder HL sensitivity and can cause frustration and stress among HCP. Conclusion: Targeted interventions and organizational support are essential to address HCP’s obstacles with HL sensitivity. Utilizing improved communication techniques and HL tools may help reduce stress and frustration. Practice Implications: To optimize HL sensitivity, it is imperative to prioritize HCP needs. Organizations should strive to facilitate HL in a way that does not impose additional stress on HCP.

Background: Symptom assessment is key to effective symptom management and palliative care for patients with advanced cancer. Symptom prevalence and severity estimates vary widely, possibly dependent on the assessment tool used. Are symptoms specifically asked about or must the patients add them as additional symptoms? This study compared the prevalence and severity of patient-reported symptoms in two different versions of a multi-symptom assessment tool. In one version, three symptoms dry mouth, constipation, sleep problems were among those systematically assessed, while in the other, these symptoms had to be added as an “Other problem”. Methods: This retrospective cross-sectional study included adult patients with advanced cancer at an inpatient palliative care unit. Data were collected from two versions of the Edmonton Symptom Assessment System (ESAS): modified (ESAS-m) listed 11 symptoms and revised (ESAS-r) listed 9 and allowed patients to add one “Other problem”. Seven similar symptoms were listed in both versions. Results: In 2013, 184 patients completed ESAS-m, and in 2017, 156 completed ESAS-r. Prevalence and severity of symptoms listed in both versions did not differ. In ESAS-m, 83% reported dry mouth, 73% constipation, and 71% sleep problems, but on ESAS-r, these symptoms were reported by only 3%, 15% and < 1%, respectively. Although ESAS-r severity scores for these three symptoms were higher than on ESAS-m, differences did not reach statistical significance. Conclusion: We identified significant differences in patient symptom reporting based on whether symptoms like dry mouth, obstipation and sleep problems were specifically assessed or had to be added by patients as an “Other problem”.