Flooderiksson3019

In this Viewpoint, we share our perspective on the current trends and progress of serious games for prosthetic training.

Opioid overdose (OD) and related deaths have significantly increased in the United States over the last 2 decades. Existing studies have mostly focused on demographic and clinical risk factors in noncritical care settings. Social and behavioral determinants of health (SBDH) are infrequently coded in the electronic health record (EHR) and usually buried in unstructured EHR notes, reflecting possible gaps in clinical care and observational research. Therefore, SBDH often receive less attention despite being important risk factors for OD. Natural language processing (NLP) can alleviate this problem.

The objectives of this study were two-fold First, we examined the usefulness of NLP for SBDH extraction from unstructured EHR text, and second, for intensive care unit (ICU) admissions, we investigated risk factors including SBDH for nonfatal OD.

We performed a cross-sectional analysis of admission data from the EHR of patients in the ICU of Beth Israel Deaconess Medical Center between 2001 and 2012. We used pae first study to analyze the risk factors for nonfatal OD in an ICU setting using NLP-extracted SBDH from EHR notes. We found several risk factors associated with nonfatal OD including SBDH. SBDH are richly described in EHR notes, supporting the importance of integrating NLP-derived SBDH into OD risk assessment. More studies in ICU settings can help health care systems better understand and respond to the opioid epidemic.

Among the general public, there appears to be a growing need and interest in receiving digital mental health and well-being support. In response to this, mental health apps (MHapps) are becoming available for monitoring, managing, and promoting positive mental health and well-being. Thus far, evidence supports favorable outcomes when users engage with MHapps, yet there is a relative paucity of reviews on apps that support positive mental health and well-being.

We aimed to systematically review the available research on MHapps that promote emotion regulation, positive mental health, and well-being in the general population aged 18-45 years. More specifically, the review aimed at providing a systematic description of the theoretical background and features of MHapps while evaluating any potential effectiveness.

A comprehensive literature search of key databases, including MEDLINE (via Ovid), EMBASE (via Ovid), PsycINFO (via Ovid), Web of Science, and the Cochrane Register of Controlled Trials (CENTRAL), w warranted to inform the development and testing of evidence-based programs.

The emerging evidence for MHapps that promote positive mental health and well-being suggests promising outcomes. Despite a wide range of MHapps, few apps specifically promote emotion regulation. However, our findings may position emotion regulation as an important mechanism for inclusion in future MHapps. A fair proportion of the included studies were pilot or feasibility trials (k=17, 33%), and full-scale RCTs reported high attrition rates and nondiverse samples. Given the number and pace at which MHapps are being released, further robust research is warranted to inform the development and testing of evidence-based programs.

The misuse of opioid medications among adolescents is a serious problem in the United States. Serious games (SGs) are a novel way to promote safe and responsible management of opioid medications among adolescents, thereby reducing the number of adolescent opioid misuse cases reported annually.

This study aimed to examine the effect of the SG MedSMA℞T Adventures in PharmaCity on adolescents' opioid safety knowledge, awareness, behavioral intent, and self-efficacy.

A nationally representative sample of adolescents age 12 to 18 years old were recruited online through Qualtrics panels from October to November 2020. Data collection consisted of a pre-game survey, 30 minutes of gameplay, and a post-game survey. The pre- and post-game survey included 66 items examining participants' baseline opioid knowledge, safety, and use, and demographic information. The post-game survey had 25 additional questions regarding the MedSMA℞T game. Gameplay scenarios included five levels intended to mimic adolescents' daily lifr participants who were non-white or Hispanic had higher improvement than non-Hispanic white participants (non-white mean (SD) = 1.10 (1.06), white = 0.75 (0.91), p = 0.026). Older grades were associated with greater improvement in opioid knowledge (correlation coefficient -0.23 (95% CI -0.40 to -0.05), p = 0.012). There were 28 (23.9%) participants who played all 5 levels of the game and had better improvement in opioid use self-efficacy.

Findings suggest MedSMA℞T Adventures in PharmaCity can be used as an effective tool to educate adolescents on the safe and responsible use of prescribed opioid medications. Future testing of the effectiveness of this SG should involve a randomized control trial. Additionally, the feasibility of implementing and disseminating MedSMA℞T Adventures in PharmaCity in schools and healthcare settings, such as adolescent health or primary care clinics, emergency departments, and pharmacies, should be investigated.

Privacy is of increasing interest in the present big data era, particularly the privacy of medical data. Specifically, differential privacy has emerged as the standard method for preservation of privacy during data analysis and publishing.

Using machine learning techniques, we applied differential privacy to medical data with diverse parameters and checked the feasibility of our algorithms with synthetic data as well as the balance between data privacy and utility.

All data were normalized to a range between -1 and 1, and the bounded Laplacian method was applied to prevent the generation of out-of-bound values after applying the differential privacy algorithm. To preserve the cardinality of the categorical variables, we performed postprocessing via discretization. The algorithm was evaluated using both synthetic and real-world data (from the eICU Collaborative Research Database). We evaluated the difference between the original data and the perturbated data using misclassification rates and the mean squ appropriate degree of noise for data perturbation to balance privacy and utility depending on specific situations.

We applied local differential privacy to medical domain data, which are diverse and high dimensional. Higher noise may offer enhanced privacy, but it simultaneously hinders utility. We should choose an appropriate degree of noise for data perturbation to balance privacy and utility depending on specific situations.

Secure patient portals are widely available, and patients use them to view their electronic health records, including their clinical notes. We conducted experiments asking them to cogenerate notes with their clinicians, an intervention called OurNotes.

This study aims to assess patient and provider experiences and attitudes after 12 months of a pilot intervention.

Before scheduled primary care visits, patients were asked to submit a word-constrained, unstructured interval history and an agenda for what they would like to discuss at the visit. Using site-specific methods, their providers were invited to incorporate the submissions into notes documenting the visits. Sites served urban, suburban, and rural patients in primary care practices in 4 academic health centers in Boston (Massachusetts), Lebanon (New Hampshire), Denver (Colorado), and Seattle (Washington). Each practice offered electronic access to visit notes (open notes) to its patients for several years. A mixed methods evaluation used tracking t.

OurNotes interests patients, and providers experience it as a positive intervention. Participation by patients, care partners, clinicians, and electronic health record experts will facilitate further development.

Medication nonadherence is a costly problem that is common in clinical use and clinical trials alike, with significant adverse consequences. Digital pill systems have proved to be effective and safe solutions to the challenges of nonadherence, with documented success in improving adherence and health outcomes.

The aim of this human factors validation study is to evaluate a novel digital pill system, the ID-Cap System from etectRx, for usability among patient users in a simulated real-world use environment.

A total of 17 patients with diverse backgrounds who regularly take oral prescription medications were recruited. After training and a period of training decay, the participants were asked to complete 12 patient-use scenarios during which errors or difficulties were logged. The participants were also interviewed about their experiences with the ID-Cap System.

The participants ranged in age from 27 to 74 years (mean 51 years, SD 13.8 years), and they were heterogeneous in other demographic factors as well, such as education level, handedness, and sex. In this human factors validation study, the patient users completed 97.5% (196/201) of the total use scenarios successfully; 75.1% (151/201) were completed without any failures or errors. The participants found the ID-Cap System easy to use, and they were able to accurately and proficiently record ingestion events using the device.

The participants demonstrated the ability to safely and effectively use the ID-Cap System for its intended use. The ID-Cap System has great potential as a useful tool for encouraging medication adherence and can be easily implemented by patient users.

The participants demonstrated the ability to safely and effectively use the ID-Cap System for its intended use. The ID-Cap System has great potential as a useful tool for encouraging medication adherence and can be easily implemented by patient users.

There is scant insight into the presence of nuclear medicine (NM) and nuclear radiology (NR) programs on social media.

Our purpose was to assess Twitter engagement by academic NM/NR programs in the United States.

We measured Twitter engagement by the academic NM/NR community, accounting for various NM/NR certification pathways. The Twitter presence of NM/NR programs at both the department and program director level was identified. Tweets by programs were cross-referenced against potential high-yield NM- or NR-related hashtags, and tabulated at a binary level. Axitinib mouse A brief survey was done to identify obstacles and benefits to Twitter use by academic NM/NR faculty.

For 2019-2020, 88 unique programs in the United States offered NM/NR certification pathways. Of these, 52% (46/88) had Twitter accounts and 24% (21/88) had at least one post related to NM/NR. Only three radiology departments had unique Twitter accounts for the NM/molecular imaging division. Of the other 103 diagnostic radiology residency programs,adiologists' overall positive views of social media's usefulness, scant social media engagement by the NM community may represent a missed opportunity. More Twitter engagement and further research by trainees and colleagues should be encouraged, as well as the streamlined use of unique hashtags.

The internet has been widely accessible and well accepted by young people; however, there is a limited understanding of the internet usage patterns and characteristics on issues related to health problems. The contents posted on online health communities (OHCs) are valuable resources to learn about youth's health information needs.

In this study, we concurrently exploited statistical analysis and topic analysis of online health information needs to explore the distribution, impact factors, and topics of interest relevant to Chinese young people.

We collected 60,478 health-related data sets posted by young people from a well-known Chinese OHC named xywy.com. Descriptive statistical analysis and correlation analysis were applied to find the distribution and influence factors of the information needs of Chinese young people. Furthermore, a general 4-step topic mining strategy was presented for sparse short texts, which included sentence vectorization, dimension reduction, clustering, and keyword generation.