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The progressive nature of Parkinson’s disease, its complex treatment regimens and the high rates of comorbid conditions make self-management and treatment adherence a challenge. Clinicians have limited face-to-face consultation time with Parkinson’s disease patients, making it difficult to comprehensively address non-adherence. Here we share the results from a multi-centre (seven centres) randomised controlled trial conducted in England and Scotland to assess the impact of using a smartphone-based Parkinson’s tracker app to promote patient self-management, enhance treatment adherence and quality of clinical consultation. Eligible Parkinson’s disease patients were randomised using a 1:1 ratio according to a computer-generated random sequence, stratified by centre and using blocks of variable size, to intervention Parkinson’s Tracker App or control (Treatment as Usual). Primary outcome was the self-reported score of adherence to treatment (Morisky medication adherence scale −8) at 16 weeks. Secondary outcomes were Quality of Life (Parkinson’s disease questionnaire −39), quality of consultation for Parkinson’s disease patients (Patient-centred questionnaire for Parkinson’s disease), impact on non-motor symptoms (Non-motor symptoms questionnaire), depression and anxiety (Hospital anxiety and depression scale) and beliefs about medication (Beliefs about Medication Questionnaire) at 16 weeks. Primary and secondary endpoints were analysed using a generalised linear model with treatment as the fixed effect and baseline measurement as the covariate. 158 patients completed the study (Parkinson’s tracker app = 68 and TAU = 90). At 16 weeks Parkinson’s tracker app significantly improved adherence, compared to treatment as usual (mean difference: 0.39, 95%CI 0.04–0.74; p = 0.0304) with no confounding effects of gender, number of comorbidities and age. Among secondary outcomes, Parkinson’s tracker app significantly improved patients’ perception of quality of consultation (0.15, 95% CI 0.03 to 0.27; p = 0.0110). The change in non-motor symptoms was −0.82 (95% CI −1.75 to 0.10; p = 0.0822). 72% of participants in the Parkinson’s tracker app group continued to use and engage with the application throughout the 16-week trial period. The Parkinson’s tracker app can be an effective and novel way of enhancing self-reported medication adherence and quality of clinical consultation by supporting self-management in Parkinson’s disease in patients owning smartphones. Further work is recommended to determine whether the benefits of the intervention are maintained beyond the 16 week study period.

BackgroundMaternal common mental disorders are prevalent in low-resource settings and have far-reaching consequences for maternal and child health. We assessed the prevalence and predictors of psychological distress as a proxy for common mental disorders among mothers in rural Jharkhand and Orissa, eastern India, where over 40% of the population live below the poverty line and access to reproductive and mental health services is low.MethodWe screened 5801 mothers around 6 weeks after delivery using the Kessler-10 item scale, and identified predictors of distress using multiple hierarchical logistic regression.Results11.5% (95% CI: 10.7–12.3) of mothers had symptoms of distress (K10 score > 15). High maternal age, low asset ownership, health problems in the antepartum, delivery or postpartum periods, caesarean section, an unwanted pregnancy for the mother, small perceived infant size and a stillbirth or neonatal death were all independently associated with an increased risk of distress. The loss of an infant or an unwanted pregnancy increased the risk of distress considerably (AORs: 7.06 95% CI: 5.51–9.04 and 1.49, 95% CI: 1.12–1.97, respectively).LimitationsWe did not collect data on antepartum depression, domestic violence or a mother's past birth history, and were therefore unable to examine the importance of these factors as predictors of psychological distress.ConclusionsMothers living in underserved areas of India who experience infant loss, an unwanted pregnancy, health problems in the perinatal and postpartum periods and socio-economic disadvantage are at increased risk of distress and require access to reproductive healthcare with integrated mental health interventions.

BackgroundThe huge increase in smartphone use heralds an enormous opportunity for epidemiology research, but there is limited evidence regarding long-term engagement and attrition in mobile health (mHealth) studies.ObjectiveThe objective of this study was to examine how representative the Cloudy with a Chance of Pain study population is of wider chronic-pain populations and to explore patterns of engagement among participants during the first 6 months of the study.MethodsParticipants in the United Kingdom who had chronic pain (≥3 months) and enrolled between January 20, 2016 and January 29, 2016 were eligible if they were aged ≥17 years and used the study app to report any of 10 pain-related symptoms during the study period. Participant characteristics were compared with data from the Health Survey for England (HSE) 2011. Distinct clusters of engagement over time were determined using first-order hidden Markov models, and participant characteristics were compared between the clusters.ResultsCompared with the data from the HSE, our sample comprised a higher proportion of women (80.51%, 5129/6370 vs 55.61%, 4782/8599) and fewer persons at the extremes of age (16-34 and 75+). Four clusters of engagement were identified: high (13.60%, 865/6370), moderate (21.76%, 1384/6370), low (39.35%, 2503/6370), and tourists (25.44%, 1618/6370), between which median days of data entry ranged from 1 (interquartile range; IQR: 1-1; tourist) to 149 (124-163; high). Those in the high-engagement cluster were typically older, whereas those in the tourist cluster were mostly male. Few other differences distinguished the clusters.ConclusionsCloudy with a Chance of Pain demonstrates a rapid and successful recruitment of a large, representative, and engaged sample of people with chronic pain and provides strong evidence to suggest that smartphones could provide a viable alternative to traditional data collection methods.

BackgroundThe increasing ownership of smartphones provides major opportunities for epidemiological research through self-reported and passively collected data.ObjectiveThis pilot study aimed to codesign a smartphone app to assess associations between weather and joint pain in patients with rheumatoid arthritis (RA) and to study the success of daily self-reported data entry over a 60-day period and the enablers of and barriers to data collection.MethodsA patient and public involvement group (n=5) and 2 focus groups of patients with RA (n=9) supported the codesign of the app collecting self-reported symptoms. A separate “capture app” was designed to collect global positioning system (GPS) and continuous raw accelerometer data, with the GPS-linking providing local weather data. A total of 20 patients with RA were then recruited to collect daily data for 60 days, with entry and exit interviews. Of these, 17 were loaned an Android smartphone, whereas 3 used their own Android smartphones.ResultsOf the 20 patients, 6 (30%) withdrew from the study: 4 because of technical challenges and 2 for health reasons. The mean completion of daily entries was 68% over 2 months. Patients entered data at least five times per week 65% of the time. Reasons for successful engagement included a simple graphical user interface, automated reminders, visualization of data, and eagerness to contribute to this easily understood research question. The main barrier to continuing engagement was impaired battery life due to the accelerometer data capture app. For some, successful engagement required ongoing support in using the smartphones.ConclusionsThis successful pilot study has demonstrated that daily data collection using smartphones for health research is feasible and achievable with high levels of ongoing engagement over 2 months. This result opens important opportunities for large-scale longitudinal epidemiological research.

BackgroundThe aim of the STRIPES trial was to assess the effectiveness of providing supplementary, remedial teaching and learning materials (and an additional ‘kit’ of materials for girls) on a composite of language and mathematics test scores for children in classes two, three and four in public primary schools in villages in the Nagarkurnool division of Andhra Pradesh, India.MethodsSTRIPES was a cluster randomised trial in which 214 villages were allocated either to the supplementary teaching intervention (n = 107) or to serve as controls (n = 107). 54 of the intervention villages were further randomly allocated to receive additional kit for girls. The study was not blinded. Analysis was conducted on the intention to treat principle, allowing for clustering.ResultsComposite test scores were significantly higher in the intervention group (107 villages; 2364 children) than in the control group (106 villages; 2014 children) at the end of the trial (mean difference on a percentage scale 15.8; 95% CI 13.1 to 18.6; p<0.001; 0.75 Standard Deviation (SD) difference). Composite test scores were not significantly different in the 54 villages (614 girls) with the additional kits for girls compared to the 53 villages (636 girls) without these kits at the end of the trial (mean difference on a percentage scale 0.5; 95% CI -4.34 to 5.4; p = 0.84). The cost per 0.1 SD increase in composite test score for intervention without kits is Rs. 382.97 (£4.45, $7.13), and Rs.480.59 (£5.58, $8.94) for the intervention with kits.ConclusionsA 18 month programme of supplementary remedial teaching and learning materials had a substantial impact on language and mathematics scores of primary school students in rural Andhra Pradesh, yet providing a ‘kit’ of materials to girls in these villages did not lead to any measured additional benefit.Trial RegistrationControlled-Trials.com ISRCTN69951502

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BackgroundNonadherence to treatment leads to suboptimal treatment outcomes and enormous costs to the economy. This is especially important in Parkinson’s disease (PD). The progressive nature of the degenerative process, the complex treatment regimens and the high rates of comorbid conditions make treatment adherence in PD a challenge. Clinicians have limited face-to-face consultation time with PD patients, making it difficult to comprehensively address non-adherence. The rapid growth of digital technologies provides an opportunity to improve adherence and the quality of decision-making during consultation. The aim of this randomised controlled trial (RCT) is to evaluate the impact of using a smartphone and web applications to promote patient self-management as a tool to increase treatment adherence and working with the data collected to enhance the quality of clinical consultation.Methods/DesignA 4-month multicentre RCT with 222 patients will be conducted to compare use of a smartphone- and internet-enabled Parkinson’s tracker smartphone app with treatment as usual for patients with PD and/or their carers. The study investigators will compare the two groups immediately after intervention. Seven centres across England (6) and Scotland (1) will be involved. The primary objective of this trial is to assess whether patients with PD who use the app show improved medication adherence compared to those receiving treatment as usual alone. The secondary objectives are to investigate whether patients who receive the app and those who receive treatment as usual differ in terms of quality of life, quality of clinical consultation, overall disease state and activities of daily living. We also aim to investigate the experience of those receiving the intervention by conducting qualitative interviews with a sample of participants and clinicians, which will be administered by independent researchers.Trial registrationISRCTN45824264 (registered 5 November 2013)Electronic supplementary materialThe online version of this article (doi:10.1186/1745-6215-15-374) contains supplementary material, which is available to authorized users.