Balanced difficulty task finder: an adaptive recommendation method for learning tasks based on the concept of state of flow.

An adaptive task difficulty assignment method which we reckon as balanced difficulty task finder (BDTF) is proposed in this paper. The aim is to recommend tasks to a learner using a trade-off between skills of the learner and difficulty of the tasks such that the learner experiences a state of flow during the learning. Flow is a mental state that psychologists refer to when someone is completely immersed in an activity. Flow state is a multidisciplinary field of research and has been studied not only in psychology, but also neuroscience, education, sport, and games. The idea behind this paper is to try to achieve a flow state in a similar way as Elo's chess skill rating (Glickman in Am Chess J 3:59-102) and TrueSkill (Herbrich et al. in Advances in neural information processing systems, 2006) for matching game players, where "matched players" should possess similar capabilities and skills in order to maintain the level of motivation and involvement in the game. The BDTF draws analogy between choosing an appropriate opponent or appropriate game level and automatically choosing an appropriate difficulty level of a learning task. This method, as an intelligent tutoring system, could be used in a wide range of applications from online learning environments and e-learning, to learning and remembering techniques in traditional methods such as adjusting delayed matching to sample and spaced retrieval training that can be used for people with memory problems such as people with dementia.

Associations Between Immigration-Related User Factors and eHealth Activities for Self-Care: Case of First-Generation Immigrants From Pakistan in the Oslo Area, Norway.

BACKGROUND: Immigrant populations are often disproportionally affected by chronic diseases, such as type 2 diabetes mellitus (T2DM). Use of information and communication technology (ICT) is one promising approach for better self-care of T2DM to mitigate the social health inequalities, if designed for a wider population. However, knowledge is scarce about immigrant populations' diverse electronic health (eHealth) activities for self-care, especially in European countries. OBJECTIVE: With a target group of first-generation immigrants from Pakistan in the Oslo area, Norway, we aimed to understand their diverse eHealth activities for T2DM self-care in relation to immigration-related user factors specific to this target group: proficiency in relevant languages (Urdu, Norwegian, English), length of residence in Norway, and diagnosis of T2DM compared with general user factors (age, gender, education and digital skills, and self-rated health status). METHODS: Data were from a survey among the target population (N=176) conducted in 2015-2016. Using logistic regression, we analyzed associations between user factors and experiences of each of the following eHealth activities for T2DM self-care in the last 12 months: first, information seeking by (1) search engines and (2) Web portals or email subscriptions; second, communication and consultation (1) by closed conversation with a few acquaintances using ICT and (2) on social network services; and third, active decision making by using apps for (1) tracking health information and (2) self-assessment of health status. Using Poisson regression, we also assessed the relationship between user factors and variety of eHealth activities experienced. The Bonferroni correction was used to address the multiple testing problem. RESULTS: Regression analyses yielded the following significantly positive associations: between Urdu literacy and (1) information seeking by Web portals or email subscriptions (odds ratio [OR] 2.155, 95% CI 1.388-3.344), (2) communication and consultation on social network services (OR 5.697, 95% CI 2.487-13.053), and (3) variety (estimate=0.350, 95% CI 0.148-0.552); between length of residence in Norway and (1) communication and consultation by closed conversation with a few acquaintances using ICT (OR 1.728, 95% CI 1.193-2.503), (2) communication and consultation on social network services (OR 2.098, 95% CI 1.265-3.480), and (3) variety (estimate=0.270, 95% CI 0.117-0.424); between Norwegian language proficiency and active decision making by using apps for self-assessment of health status (OR 2.285, 95% CI 1.294-4.036); between education and digital skills and active decision making by using apps for tracking health information (OR 3.930, 95% CI 1.627-9.492); and between being a female and communication and consultation by closed conversation with a few acquaintances using ICT (OR 2.883, 95% CI 1.335-6.227). CONCLUSIONS: This study implies immigration-related factors may confound associations between general user factors and eHealth activities. Further studies are needed to explore the influence of immigration-related user factors for eHealth activities in other immigrant groups and countries. INTERNATIONAL REGISTERED REPORT: RR2-DOI 10.2196/resprot.5468.

Correction: The Association Between Commonly Investigated User Factors and Various Types of eHealth Use for Self-Care of Type 2 Diabetes: Case of First-Generation Immigrants From Pakistan in the Oslo Area, Norway.

[This corrects the article DOI: 10.2196/publichealth.7009.].

The Association Between Commonly Investigated User Factors and Various Types of eHealth Use for Self-Care of Type 2 Diabetes: Case of First-Generation Immigrants From Pakistan in the Oslo Area, Norway.

BACKGROUND: Sociodemographic and health-related factors are often investigated for their association with the active use of electronic health (eHealth). The importance of such factors has been found to vary, depending on the purpose or means of eHealth and the target user groups. Pakistanis are one of the biggest immigrant groups in the Oslo area, Norway. Due to an especially high risk of developing type 2 diabetes (T2D) among this population, knowledge about their use of eHealth for T2D self-management and prevention (self-care) will be valuable for both understanding this vulnerable group and for developing effective eHealth services. OBJECTIVE: The aim of this study was to examine how commonly were the nine types of eHealth for T2D self-care being used among our target group, the first-generation Pakistani immigrants living in the Oslo area. The nine types of eHealth use are divided into three broad categories based on their purpose: information seeking, communication, and active self-care. We also aimed to investigate how sociodemographic factors, as well as self-assessment of health status and digital skills are associated with the use of eHealth in this group. METHODS: A survey was carried out in the form of individual structured interviews from September 2015 to January 2016 (N=176). For this study, dichotomous data about whether or not an informant had used each of the nine types of eHealth in the last 12 months and the total number of positive answers were used as dependent variables in a regression analysis. The independent variables were age, gender, total years of education, digital skills (represented by frequency of asking for help when using information and communication technology [ICT]), and self-assessment of health status. Principal component analyses were applied to make categories of independent variables to avoid multicollinearity. RESULTS: Principal component analysis yielded three components: knowledge, comprising total years of education and digital skills; health, comprising age and self-assessment of health status; and gender, as being a female. With the exception of closed conversation with a few specific acquaintances about self-care of T2D (negatively associated, P=.02) and the use of ICT for relevant information-seeking by using search engines (not associated, P=.18), the knowledge component was positively associated with all the other dependent variables. The health component was negatively associated with the use of ICT for closed conversation with a few specific acquaintances about self-care of T2D (P=.01) but not associated with the other dependent variables. Gender component showed no association with any of the dependent variables. CONCLUSIONS: In our sample, knowledge, as a composite measure of education and digital skills, was found to be the main factor associated with eHealth use regarding T2D self-care. Enhancing digital skills would encourage and support more active use of eHealth for T2D self-care.