Autonomy in Video Games and Gamification

In the past decade, gamification (using game elements in non-gaming tasks to enhance motivation and engagement) has become a popular concept in many industries, but few studies have explored the principles under which it works. Self-determination theory suggests three psychological needs that gamification fulfills: competence, relatedness, and autonomy. Autonomy, a person\u27s perception that they have the ability to act however they choose, has emerged as an important, yet less-studied aspect in gamification. Inclusion of autonomy in gamification should foster engagement, enjoyment, and better performance. An experiment inspired by the above was carried out in which a sample of college students (N = 57) played a video game called Super Mario Bros. Crossover with either the choice to customize the aesthetics of their character and background (autonomy-supportive) or no choice of aesthetics (non-supportive). It was hypothesized that conditions involving more choice would lead to higher perceived autonomy and performance, and that perceived autonomy would be positively correlated with engagement, enjoyment, and performance. The manipulation resulted in no significant difference in perceived autonomy or performance, and perceived autonomy was only significantly positively correlated with enjoyment. Prior Super Mario Bros. experience was also found to positively correlate with perceived autonomy in the autonomy-supportive condition. The choice of aesthetics does not appear to have been sufficiently strong enough to increase perceived autonomy in this context

Designing a System for Patients Controlling Providers’ Access to their Electronic Health Records: Organizational and Technical Challenges

BACKGROUND Electronic health records (EHRs) are proliferating, and financial incentives encourage their use. Applying Fair Information Practice principles to EHRs necessitates balancing patients’ rights to control their personal information with providers’ data needs to deliver safe, high-quality care. We describe the technical and organizational challenges faced in capturing patients’ preferences for patient-controlled EHR access and applying those preferences to an existing EHR. METHODS We established an online system for capturing patients’ preferences for who could view their EHRs (listing all participating clinic providers individually and categorically—physicians, nurses, other staff) and what data to redact (none, all, or by specific categories of sensitive data or patient age). We then modified existing data-viewing software serving a state-wide health information exchange and a large urban health system and its primary care clinics to allow patients’ preferences to guide data displays to providers. RESULTS Patients could allow or restrict data displays to all clinicians and staff in a demonstration primary care clinic, categories of providers (physicians, nurses, others), or individual providers. They could also restrict access to all EHR data or any or all of five categories of sensitive data (mental and reproductive health, sexually transmitted diseases, HIV/AIDS, and substance abuse) and for specific patient ages. The EHR viewer displayed data via reports, data flowsheets, and coded and free text data displayed by Google-like searches. Unless patients recorded restrictions, by default all requested data were displayed to all providers. Data patients wanted restricted were not displayed, with no indication they were redacted. Technical barriers prevented redacting restricted information in free textnotes. The program allowed providers to hit a “Break the Glass” button to override patients’ restrictions, recording the date, time, and next screen viewed. Establishing patient-control over EHR data displays was complex and required ethical, clinical, database, and programming expertise and difficult choices to overcome technical and health system constraints. CONCLUSIONS Assessing patients’ preferences for access to their EHRs and applying them in clinical practice requires wide-ranging technical, clinical, and bioethical expertise, to make tough choices to overcome significant technical and organization challenges

Intentional and unintentional medication non-adherence in psoriasis: The role of patients’ medication beliefs and habit strength

Medication non-adherence is a missed opportunity for therapeutic benefit. We assessed “real-world” levels of self-reported non-adherence to conventional and biologic systemic therapies used for psoriasis and evaluated psychological and biomedical factors associated with non-adherence using multivariable analyses. Latent profile analysis was used to investigate whether patients can be categorized into groups with similar medication beliefs. Latent profile analysis categorizes individuals with similar profiles on a set of continuous variables into discrete groups represented by a categorical latent variable. Eight hundred and eleven patients enrolled in the British Association of Dermatologists Biologic Interventions Register were included. Six hundred and seventeen patients were using a self-administered systemic therapy; 22.4% were classified as “non-adherent” (12% intentionally and 10.9% unintentionally). Patients using an oral conventional systemic agent were more likely to be non-adherent compared to those using etanercept or adalimumab (29.2% vs. 16.4%; P ≤ 0.001). Latent profile analysis supported a three-group model; all groups held strong beliefs about their need for systemic therapy but differed in levels of medication concerns. Group 1 (26.4% of the sample) reported the strongest concerns, followed by Group 2 (61%), with Group 3 (12.6%) reporting the weakest concerns. Group 1 membership was associated with intentional non-adherence (odds ratio = 2.27, 95% confidence interval = 1.16−4.47) and weaker medication-taking routine or habit strength was associated with unintentional non-adherence (odds ratio = 0.92, 95% confidence interval = 0.89−0.96). Medication beliefs and habit strength are modifiable targets for strategies to improve adherence in psoriasis

Individual common variants exert weak effects on the risk for autism spectrum disorders.

While it is apparent that rare variation can play an important role in the genetic architecture of autism spectrum disorders (ASDs), the contribution of common variation to the risk of developing ASD is less clear. To produce a more comprehensive picture, we report Stage 2 of the Autism Genome Project genome-wide association study, adding 1301 ASD families and bringing the total to 2705 families analysed (Stages 1 and 2). In addition to evaluating the association of individual single nucleotide polymorphisms (SNPs), we also sought evidence that common variants, en masse, might affect the risk. Despite genotyping over a million SNPs covering the genome, no single SNP shows significant association with ASD or selected phenotypes at a genome-wide level. The SNP that achieves the smallest P-value from secondary analyses is rs1718101. It falls in CNTNAP2, a gene previously implicated in susceptibility for ASD. This SNP also shows modest association with age of word/phrase acquisition in ASD subjects, of interest because features of language development are also associated with other variation in CNTNAP2. In contrast, allele scores derived from the transmission of common alleles to Stage 1 cases significantly predict case status in the independent Stage 2 sample. Despite being significant, the variance explained by these allele scores was small (Vm< 1%). Based on results from individual SNPs and their en masse effect on risk, as inferred from the allele score results, it is reasonable to conclude that common variants affect the risk for ASD but their individual effects are modest

Predictive Modeling of Hypoglycemia for Clinical Decision Support in Evaluating Outpatients with Diabetes Mellitus

Objective: Hypoglycemia occurs in 20–60% of patients with diabetes mellitus. Identifying at-risk patients can facilitate interventions to lower risk. We sought to develop a hypoglycemia prediction model. Methods: In this retrospective cohort study, urban adults prescribed a diabetes drug between 2004 and 2013 were identified. Demographic and clinical data were extracted from an electronic medical record (EMR). Laboratory tests, diagnostic codes and natural language processing (NLP) identified hypoglycemia. We compared multiple logistic regression, classification and regression trees (CART), and random forest. Models were evaluated on an independent test set or through cross-validation. Results: The 38,780 patients had mean age 57 years; 56% were female, 40% African-American and 39% uninsured. Hypoglycemia occurred in 8128 (539 identified only by NLP). In logistic regression, factors positively associated with hypoglycemia included infection, non-long-acting insulin, dementia and recent hypoglycemia. Negatively associated factors included long-acting insulin plus sulfonylurea, and age 75 or older. The models’ area under curve was similar (logistic regression, 89%; CART, 88%; random forest, 90%, with ten-fold cross-validation). Conclusions: NLP improved identification of hypoglycemia. Non-long-acting insulin was an important risk factor. Decreased risk with age may reflect treatment or diminished awareness of hypoglycemia. More complex models did not improve prediction

Comparative Analysis of Acid Sphingomyelinase Distribution in the CNS of Rats and Mice Following Intracerebroventricular Delivery

Niemann-Pick A (NPA) disease is a lysosomal storage disorder (LSD) caused by a deficiency in acid sphingomyelinase (ASM) activity. Previously, we reported that biochemical and functional abnormalities observed in ASM knockout (ASMKO) mice could be partially alleviated by intracerebroventricular (ICV) infusion of hASM. We now show that this route of delivery also results in widespread enzyme distribution throughout the rat brain and spinal cord. However, enzyme diffusion into CNS parenchyma did not occur in a linear dose-dependent fashion. Moreover, although the levels of hASM detected in the rat CNS were determined to be within the range shown to be therapeutic in ASMKO mice, the absolute amounts represented less than 1% of the total dose administered. Finally, our results also showed that similar levels of enzyme distribution are achieved across rodent species when the dose is normalized to CNS weight as opposed to whole body weight. Collectively, these data suggest that the efficacy observed following ICV delivery of hASM in ASMKO mice could be scaled to CNS of the rat

Nomenclature for kidney function and disease: report of a Kidney Disease:Improving Global Outcomes (KDIGO) Consensus Conference

The worldwide burden of kidney disease is rising, but public awareness remains limited, underscoring the need for more effective communication by stakeholders in the kidney health community. Despite this need for clarity, the nomenclature for describing kidney function and disease lacks uniformity. In June 2019, Kidney Disease: Improving Global Outcomes (KDIGO) convened a Consensus Conference with the goal of standardizing and refining the nomenclature used in the English language to describe kidney function and disease, and of developing a glossary that could be used in scientific publications. Guiding principles of the conference were that the revised nomenclature should be patient-centered, precise, and consistent with nomenclature used in the KDIGO guidelines. Conference attendees reached general consensus on the following recommendations: (i) to use "kidney" rather than "renal" or "nephro-" when referring to kidney disease and kidney function; (ii) to use "kidney failure" with appropriate descriptions of presence or absence of symptoms, signs, and treatment, rather than "end-stage kidney disease"; (iii) to use the KDIGO definition and classification of acute kidney diseases and disorders (AKD) and acute kidney injury (AKI), rather than alternative descriptions, to define and classify severity of AKD and AKI; (iv) to use the KDIGO definition and classification of chronic kidney disease (CKD) rather than alternative descriptions to define and classify severity of CKD; and (v) to use specific kidney measures, such as albuminuria or decreased glomerular filtration rate (GFR), rather than "abnormal" or "reduced" kidney function to describe alterations in kidney structure and function. A proposed 5-part glossary contains specific items for which there was general agreement. Conference attendees acknowledged limitations of the recommendations and glossary, but they considered standardization of scientific nomenclature to be essential for improving communication