PurposeThis study aimed to explore support for mothers and fathers in single-family rooms (SFRs) of a NICU.DesignA qualitative descriptive design was employed.SampleA convenience sample of 15 parents (nine mothers, six fathers) were recruited from a Level III NICU.MethodDuring their infants' hospitalization, each parent recorded their thoughts and feelings regarding support whenever appropriate over a period of 48 hours using Handy Application to Promote Preterm infant happY-life (HAPPY), an android recording application.ResultsParents felt supported when staff facilitated their learning in a collaborative manner, fostered their optimism, and provided situational assistance. Continuity and consistency of care and presence were important characteristics of supportive nursing care. Though SFRs offered privacy for parents to learn and to be with their infants, the design limited parental access to nursing and medical staff, which sometimes prevented parents from receiving adequate support and partaking in decision making concerning their infants' care.

Aim To identify generic measures used to measure quality of life (QoL) in pediatric multiple sclerosis research, estimate an overall score of children and adolescents with pediatric multiple sclerosis, and compare the scores to scores of typically developing children and adolescents. Method A systematic search was conducted on four databases. All studies were included if: the sample was children with pediatric demyelinating disorders; self‐reported QoL/health‐related quality of life (HRQoL) measures or results were reported; and the mean age of the sample was below 21 years. Quality of the included articles was appraised using the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) checklist and the Mixed Methods Appraisal Tool checklist. A meta‐analysis was also conducted. Results A total of 12 full‐text articles were included. Content analysis showed that many components of QoL were not included in the measures. Seven studies were included in the meta‐analysis. The meta‐analyzed score was 75.7 (95% confidence interval 71.2–80.3) with a pooled standard deviation of 16.6. Scores of typically developing children and children with pediatric multiple sclerosis were similar. Interpretation Most measures assessed HRQoL and not QoL. Development of a condition‐specific measure of QoL for children and adolescents with pediatric multiple sclerosis would make an important contribution to the field. Health‐related quality of life (HRQoL) measures were used to measure quality of life in pediatric multiple sclerosis. HRQoL scores in pediatric multiple sclerosis were similar to typically developing children and adolescents.

No abstract

Background: Goal setting is a crucial element in self-management of chronic diseases. Personalized outcome feedback is needed for goal setting, a requirement for behavior change. This study contributes to the understanding of the specificity of patient-formulated self-management goals by testing the effectiveness of a personalized health outcome profile. Objective: To estimate among people living with HIV, to what extent providing feedback on their health outcomes, compared to no feedback, will affect number and specificity of patient-formulated self-management goals. Methods: A personalized health outcome profile has been produced for individuals enrolled in a Canadian HIV Brain Health Now cohort study at cohort entry and at the last recorded visit. Participants will be randomized to receive or not “My Personal Brain Health Dashboard” prior to a goal setting exercise. Self-defined goals in free text will be collected through an online platform. Intervention and control groups will receive instructions on goal setting and tips to improve brain health. A total of 420 participants are needed to detect a rate ratio (number of specific words/numbers of person-goals, intervention:control) of 1.5. Text mining techniques will be used to quantify goal specificity based on word matches with a goal-setting lexicon. The expectation is that the intervention group will set more goals and have more words matching the developed lexical than the control group. The total number of words per person-goals will be calculated for each group and Poisson regression will be used to estimate the rate ratio and 95% confidence intervals and compare rate ratios between men and women using an interaction term. Conclusions: This study will contribute to growing evidence for the value of person-reported health outcomes in tailoring interventions, and will provide a thorough understanding of the quality of person-defined goals using text mining. Trial registration: Clinical Trials NCT04175795, registered on 25th November 2019.

No abstract

Purpose To estimate among people living with chronic HIV, to what extent providing feedback on their health outcomes will affect the number and specificity of patient-formulated self-management goals. Methods A personalized feedback profile was produced for individuals enrolled in a Canadian HIV Brain Health Now study. Goal specificity was measured by total number of specific words (matched to a domain-specific developed lexicon) per person-words using text mining techniques. Results Of 176 participants enrolled and randomly assigned to feedback and control groups, 110 responses were received. The average number of goals was similar for both groups (3.7 vs 3.9). The number of specific words used in the goals formulated by the feedback and control group were 642 and 739, respectively. Specific nouns and actionable verbs were present to some extent and “measurable” and “time-bound” words were mainly missing. Negative binomial regression showed no difference in goal specificity among groups (RR = 0.93, 95% CI 0.78–1.10). Goals set by both groups overlapped in 8 areas and had little difference in rank. Conclusion Personalized feedback profile did not help with formulation of high-quality goals. Text mining has the potential to help with difficulties of goal evaluation outside of the face-to-face setting. With more data and use of learning models automated answers could be generated to provide a more dynamic platform. Supplementary Information The online version contains supplementary material available at 10.1007/s11136-022-03245-5.

No abstract

No abstract