Patient-Driven Innovation for Mobile Mental Health Technology: Case Report of Symptom Tracking in Schizophrenia.
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SUBMITTER: Torous J
PROVIDER: S-EPMC5519827 | biostudies-other | 2017 Jul
REPOSITORIES: biostudies-other
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| S-EPMC5481265 | biostudies-literature
Project description:BackgroundPediatric blood and marrow transplant (PBMT) patients experience significant symptom distress. Mobile health (mHealth) technologies can be leveraged to improve understanding of the patient's symptom experience by providing continuous, real-time, in situ, patient-generated symptom data. This rich data stream can subsequently enhance symptom management strategies. However, limited research has been conducted in this area.ObjectivesThis pilot study seeks to (a) explore the feasibility of integrating mHealth technologies to monitor symptom data for PBMT patients and (b) evaluate the study design, measures, and procedures.MethodsAn exploratory longitudinal design was employed to assess the feasibility of monitoring 10 PBMT patients' symptoms using data from two mHealth technologies: (a) a smartphone mHealth application (app) to collect symptom data and (b) a wearable tracking device (Apple watch) to collect physiological data. Feasibility was measured as usability and acceptability. Monthly patient interviews and an end-of-study feasibility survey were employed and analyzed to further understand reasons for sustained interest in and attrition from the study.ResultsOverall usability of the wearable was 51%, and app was 56%. Children reported devices were easy to use and acceptable. The study demonstrated acceptability with an enrollment rate of 83% and an attrition rate of 30%, with 70% of the children remaining in the study for at least 40 days.DiscussionThis pilot study is among the first to explore the feasibility of using mobile technologies to longitudinally obtain patient-generated symptom data to enhance understanding of the PBMT symptom experience. In addition, it will improve our understanding of how these data present, interact, and cluster together throughout the posttransplant period.
| S-EPMC7256218 | biostudies-literature
Project description:ObjectiveIn the field of global mental health, there is a need for identifying core values and competencies to guide training programs in professional practice as well as in academia. This paper presents the results of interdisciplinary discussions fostered during an annual meeting of the Society for the Study of Psychiatry and Culture to develop recommendations for value-driven innovation in global mental health training.MethodsParticipants (n = 48), who registered for a dedicated workshop on global mental health training advertised in conference proceedings, included both established faculty and current students engaged in learning, practice, and research. They proffered recommendations in five areas of training curriculum: values, competencies, training experiences, resources, and evaluation.ResultsPriority values included humility, ethical awareness of power differentials, collaborative action, and "deep accountability" when working in low-resource settings in low- and middle-income countries and high-income countries. Competencies included flexibility and tolerating ambiguity when working across diverse settings, the ability to systematically evaluate personal biases, historical and linguistic proficiency, and evaluation skills across a range of stakeholders. Training experiences included didactics, language training, self-awareness, and supervision in immersive activities related to professional or academic work. Resources included connections with diverse faculty such as social scientists and mentors in addition to medical practitioners, institutional commitment through protected time and funding, and sustainable collaborations with partners in low resource settings. Finally, evaluation skills built upon community-based participatory methods, 360-degree feedback from partners in low-resource settings, and observed structured clinical evaluations (OSCEs) with people of different cultural backgrounds.ConclusionsGlobal mental health training, as envisioned in this workshop, exemplifies an ethos of working through power differentials across clinical, professional, and social contexts in order to form longstanding collaborations. If incorporated into the ACGME/ABPN Psychiatry Milestone Project, such recommendations will improve training gained through international experiences as well as the everyday training of mental health professionals, global health practitioners, and social scientists.
| S-EPMC4938758 | biostudies-literature
Project description:BackgroundSmartphones offer the possibility of assessing recovery of mobility after total hip or knee arthroplasty (THA or TKA) passively and reliably, as well as facilitating the collection of patient-reported outcome measures (PROMs) with greater frequency.Questions/purposesWe investigated the feasibility of using mobile technology to collect daily step data and biweekly PROMs to track recovery after total joint arthroplasty.MethodsPre- and post-operative daily steps were recorded in prospectively enrolled patients (128 THA and 139 TKA) via an app, which uses the phone's accelerometer. During 6-month follow-up, patients also completed PROMs (the pain numeric rating scale, the Hip Disability and Osteoarthritis Outcome Score Joint Replacement [HOOS JR] and the Knee Injury and Osteoarthritis Outcome Score Joint Replacement [KOOS JR]), and HOOS or KOOS JR quality of life domain via a mobile-enabled web link.ResultsAt least 6 months of follow-up was completed by 65% for THA and 68% for TKA patients. Reasons for non-completion included time commitment, phone battery, app issues, and health complications. Responses from 78% of requested PROMs were returned with 96% of patients returning at least one post-operative PROM. Step data were available from 92% of days from male patients and 86% of days from female patients. The most robust recovery occurred early, within the first 2 months. The groups with higher pre-operative steps were more likely to recover their maximum daily steps at an earlier time point. Correlations between step counts and PROMs scores were modest.ConclusionAssessing large amounts of post-TKA and post-THA step data using mobile technology is feasible. Completion rates were good, making the technology very useful for collecting frequent PROMs. Being unable to ensure that patients always carried their phones limited our analysis of the step counts.
| S-EPMC7749883 | biostudies-literature
Project description:This pilot study aims to investigate the relationships between consumers' weight status, energy density of food and visual attention towards food during unplanned purchase behavior in a real-world environment. After more than a decade of intensive experimental eye tracking research on food perception, this pilot study attempts to link experimental and field research in this area. Shopping trips of participants with different weight status were recorded with mobile eye tracking devices and their unplanned purchase behavior was identified and analyzed. Different eye movement measurements for initial orientation and maintained attention were analyzed. Differences in visual attention caused by energy density of food were found. There was a tendency across all participants to look at low energy density food longer and more often.
| S-EPMC7932502 | biostudies-literature
Project description:Mobile sensing data processed using machine learning models can passively and remotely assess mental health symptoms from the context of patients' lives. Prior work has trained models using data from single longitudinal studies, collected from demographically homogeneous populations, over short time periods, using a single data collection platform or mobile application. The generalizability of model performance across studies has not been assessed. This study presents a first analysis to understand if models trained using combined longitudinal study data to predict mental health symptoms generalize across current publicly available data. We combined data from the CrossCheck (individuals living with schizophrenia) and StudentLife (university students) studies. In addition to assessing generalizability, we explored if personalizing models to align mobile sensing data, and oversampling less-represented severe symptoms, improved model performance. Leave-one-subject-out cross-validation (LOSO-CV) results were reported. Two symptoms (sleep quality and stress) had similar question-response structures across studies and were used as outcomes to explore cross-dataset prediction. Models trained with combined data were more likely to be predictive (significant improvement over predicting training data mean) than models trained with single-study data. Expected model performance improved if the distance between training and validation feature distributions decreased using combined versus single-study data. Personalization aligned each LOSO-CV participant with training data, but only improved predicting CrossCheck stress. Oversampling significantly improved severe symptom classification sensitivity and positive predictive value, but decreased model specificity. Taken together, these results show that machine learning models trained on combined longitudinal study data may generalize across heterogeneous datasets. We encourage researchers to disseminate collected de-identified mobile sensing and mental health symptom data, and further standardize data types collected across studies to enable better assessment of model generalizability.
| S-EPMC9045602 | biostudies-literature
Project description:BackgroundThe amount of information needed by doctors has exploded. The nature of knowledge (explicit and tacit) and processes of knowledge acquisition and participation are complex. Aiming to assist workplace learning, Wales Deanery funded "iDoc", a project offering trainee doctors a Smartphone library of medical textbooks.MethodsData on trainee doctors' (Foundation Year 2) workplace information seeking practice was collected by questionnaire in 2011 (n = 260). iDoc baseline questionnaires (n = 193) collected data on Smartphone usage alongside other workplace information sources. Case reports (n = 117) detail specific instances of Smartphone use.ResultsMost frequently (daily) used information sources in the workplace: senior medical staff (80% F2 survey; 79% iDoc baseline); peers (70%; 58%); and other medical/nursing team staff (53% both datasets). Smartphones were used more frequently by males (p < 0.01). Foundation Year 1 (newly qualified) was judged the most useful time to have a Smartphone library because of increased responsibility and lack of knowledge/experience.Preferred information source varied by question type: hard copy texts for information-based questions; varied resources for skills queries; and seniors for more complex problems. Case reports showed mobile technology used for simple (information-based), complex (problem-based) clinical questions and clinical procedures (skills-based scenarios). From thematic analysis, the Smartphone library assisted: teaching and learning from observation; transition from medical student to new doctor; trainee doctors' discussions with seniors; independent practice; patient care; and this 'just-in-time' access to reliable information supported confident and efficient decision-making.ConclusionA variety of information sources are used regularly in the workplace. Colleagues are used daily but seniors are not always available. During transitions, constant access to the electronic library was valued. It helped prepare trainee doctors for discussions with their seniors, assisting the interchange between explicit and tacit knowledge.By supporting accurate prescribing and treatment planning, the electronic library contributed to enhanced patient care. Trainees were more rapidly able to medicate patients to reduce pain and more quickly call for specific assessments. However, clinical decision-making often requires dialogue: what Smartphone technology can do is augment, not replace, discussion with their colleagues in the community of practice.
| S-EPMC3552772 | biostudies-literature
Project description:The article presented an integrated data on talent management practices and innovation performance of academic staff in a technology-driven private university in Nigeria. The study adopted a quantitative approach with a survey research design to establish the major determinants of talent management practices. The population of this study included academic staff and the use of questionnaire was adopted to elicit from the study population. Data was analysed with the use of structural equation modelling and the field data set is made widely accessible to enable critical or a more comprehensive investigation. The findings identified talent development and retention strategies as predictors for facilitating innovation performance in the sample University. It was recommended that management of the sampled university will consistently need to adopt reliable range of strategies to attract and retain people for excellence performance.
| S-EPMC6139485 | biostudies-literature
Project description:BACKGROUND:The objective of this study was to develop and validate a short form of the Patient Health Questionnaire-9 (PHQ-9), a self-report questionnaire for assessing depressive symptomatology, using objective criteria. METHODS:Responses on the PHQ-9 were obtained from 7,850 English-speaking participants enrolled in 20 primary diagnostic test accuracy studies. PHQ unidimensionality was verified using confirmatory factor analysis, and an item response theory model was fit. Optimal test assembly (OTA) methods identified a maximally precise short form for each possible length between one and eight items, including and excluding the ninth item. The final short form was selected based on prespecified validity, reliability, and diagnostic accuracy criteria. RESULTS:A four-item short form of the PHQ (PHQ-Dep-4) was selected. The PHQ-Dep-4 had a Cronbach's alpha of 0.805. Sensitivity and specificity of the PHQ-Dep-4 were 0.788 and 0.837, respectively, and were statistically equivalent to the PHQ-9 (sensitivity = 0.761, specificity = 0.866). The correlation of total scores with the full PHQ-9 was high (r = 0.919). CONCLUSION:The PHQ-Dep-4 is a valid short form with minimal loss of information of scores when compared to the full-length PHQ-9. Although OTA methods have been used to shorten patient-reported outcome measures based on objective, prespecified criteria, further studies are required to validate this general procedure for broader use in health research. Furthermore, due to unexamined heterogeneity, there is a need to replicate the results of this study in different patient populations.
| S-EPMC6321766 | biostudies-literature
Project description:BACKGROUND:Despite the growth of and media hype about mobile health (mHealth), there is a paucity of literature supporting the effectiveness of widespread implementation of mHealth technologies. OBJECTIVE:This study aimed to assess whether an innovative mHealth technology system with several overlapping purposes can impact (1) clinical outcomes (ie, readmission rates, revisit rates, and length of stay) and (2) patient-centered care outcomes (ie, patient engagement, patient experience, and patient satisfaction). METHODS:We compared all patients (2059 patients) of participating orthopedic surgeons using mHealth technology with all patients of nonparticipating orthopedic surgeons (2554 patients). The analyses included Wilcoxon rank-sum tests, Kruskal-Wallis tests for continuous variables, and chi-square tests for categorical variables. Logistic regression models were performed on categorical outcomes and a gamma-distributed model for continuous variables. All models were adjusted for patient demographics and comorbidities. RESULTS:The inpatient readmission rates for the nonparticipating group when compared with the participating group were higher and demonstrated higher odds ratios (ORs) for 30-day inpatient readmissions (nonparticipating group 106/2636, 4.02% and participating group 54/2048, 2.64%; OR 1.48, 95% CI 1.03 to 2.13; P=.04), 60-day inpatient readmissions (nonparticipating group 194/2636, 7.36% and participating group 85/2048, 4.15%; OR 1.79, 95% CI 1.32 to 2.39; P<.001), and 90-day inpatient readmissions (nonparticipating group 261/2636, 9.90% and participating group 115/2048, 5.62%; OR 1.81, 95% CI 1.40 to 2.34; P<.001). The length of stay for the nonparticipating cohort was longer at 1.90 days, whereas the length of stay for the participating cohort was 1.50 days (mean 1.87, SD 2 vs mean 1.50, SD 1.37; P<.001). Patients treated by participating surgeons received and read text messages using mHealth 83% of the time and read emails 84% of the time. Patients responded to 60% of the text messages and 53% of the email surveys. Patients were least responsive to digital monitoring questions when the hospital asked them to do something, and they were most engaged with emails that did not require action, including informational content. A total of 96% (558/580) of patients indicated high satisfaction with using mHealth technology to support their care. Only 0.40% (75/2059) patients opted-out of the mHealth technology program after enrollment. CONCLUSIONS:A novel, multicomponent, pathway-driven, patient-facing mHealth technology can positively impact patient outcomes and patient-reported experiences. These technologies can empower patients to play a more active and meaningful role in improving their outcomes. There is a deep need, however, for a better understanding of the interactions between patients, technology, and health care providers. Future research is needed to (1) help identify, address, and improve technology usability and effectiveness; (2) understand patient and provider attributes that support adoption, uptake, and sustainability; and (3) understand the factors that contribute to barriers of technology adoption and how best to overcome them.
| S-EPMC7381069 | biostudies-literature