Prognosis of shoulder pain in those with and without a psychological disorder: A prospective cohort study with a six-month follow-up.

BACKGROUND: Because shoulder pain can have an unfavorable prognosis, it is important to have a better understanding of factors that may influence recovery. OBJECTIVE: To determine the association between recovery from shoulder pain and the presence of depression, anxiety, and pain catastrophizing. METHODS: In a prospective cohort study with a six months follow-up, we included patients visiting an orthopaedic department with shoulder pain. Primary outcome was recovery from shoulder pain measured with the Shoulder Pain and Disability Index at three and six months. Information about depression and anxiety (Hospital Anxiety and Depression Scale), pain catastrophizing (Pain Catastrophizing Scale), and demographic and clinical factors were collected at baseline. A linear mixed model was used to estimate the effects of depression, anxiety, pain catastrophizing, and underlying shoulder disorders on recovery. RESULTS: We included 190 patients. There were no statistically significant associations between the presence of depression, anxiety, and pain catastrophizing, and three- and six-month recovery. Also between the underlying shoulder disorders and recovery at three and six months, there were no statistically significant associations. CONCLUSIONS: We could not prove that depression, anxiety, and pain catastrophizing, as well as underlying shoulder disorders, were associated with recovery of shoulder pain at six months.

Asynchronous mHealth Interventions in Rheumatoid Arthritis: Systematic Scoping Review.

BACKGROUND: Mobile devices such as smartphones and tablets have surged in popularity in recent years, generating numerous possibilities for their use in health care as mobile health (mHealth) tools. One advantage of mHealth is that it can be provided asynchronously, signifying that health care providers and patients are not communicating in real time. The integration of asynchronous mHealth into daily clinical practice might therefore help to make health care more efficient for patients with rheumatoid arthritis (RA). The benefits have been reviewed in various medical conditions, such as diabetes and asthma, with promising results. However, to date, it is unclear what evidence exists for the use of asynchronous mHealth in the field of RA. OBJECTIVE: The objective of this study was to map the different asynchronous mHealth interventions tested in clinical trials in patients with RA and to summarize the effects of the interventions. METHODS: A systematic search of Pubmed, Scopus, Cochrane, and PsycINFO was performed following the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) guidelines. Studies were initially screened and later assessed by two independent researchers. Disagreements on inclusion or exclusion of studies were resolved by discussion. RESULTS: The literature search yielded 1752 abstracts. After deduplication and screening, 10 controlled intervention studies were included. All studies were assessed to be at risk for bias in at least one domain of the Cochrane risk-of-bias tool. In the 10 selected studies, 4 different types of mHealth interventions were used: SMS reminders (to increase medication adherence or physical activity; n=3), web apps (for disease monitoring and/or to provide medical information; n=5), smartphone apps (for disease monitoring; n=1), and pedometers (to increase and track steps; n=1). Measured outcomes varied widely between studies; improvements were seen in terms of medication compliance (SMS reminders), reaching rapid remission (web app), various domains of physical activity (pedometer, SMS reminders, and web apps), patient-physician interaction (web apps), and self-efficacy (smartphone app). CONCLUSIONS: SMS reminders, web apps, smartphone apps, and pedometers have been evaluated in intervention studies in patients with RA. These interventions have been used to monitor patients or to support them in their health behavior. The use of asynchronous mHealth led to desirable outcomes in nearly all studies. However, since all studies were at risk of bias and methods used were very heterogeneous, high-quality research is warranted to corroborate these promising results.