Explore the vast range of titles available.

Globally, mobile phones have achieved wide reach at an unprecedented rate, and mobile phone apps have become increasingly prevalent among users. The number of health-related apps that were published on the two leading platforms (iOS and Android) reached more than 100,000 in 2014. However, there is a lack of synthesized evidence regarding the effectiveness of mobile phone apps in changing people's health-related behaviors. The aim was to examine the effectiveness of mobile phone apps in achieving health-related behavior change in a broader range of interventions and the quality of the reported studies. We conducted a comprehensive bibliographic search of articles on health behavior change using mobile phone apps in peer-reviewed journals published between January 1, 2010 and June 1, 2015. Databases searched included Medline, PreMedline, PsycINFO, Embase, Health Technology Assessment, Education Resource Information Center (ERIC), and Cumulative Index to Nursing and Allied Health Literature (CINAHL). Articles published in the Journal of Medical Internet Research during that same period were hand-searched on the journal's website. Behavior change mechanisms were coded and analyzed. The quality of each included study was assessed by the Cochrane Risk of Bias Assessment Tool. A total of 23 articles met the inclusion criteria, arranged under 11 themes according to their target behaviors. All studies were conducted in high-income countries. Of these, 17 studies reported statistically significant effects in the direction of targeted behavior change; 19 studies included in this analysis had a 65% or greater retention rate in the intervention group (range 60%-100%); 6 studies reported using behavior change theories with the theory of planned behavior being the most commonly used (in 3 studies). Self-monitoring was the most common behavior change technique applied (in 12 studies). The studies suggest that some features improve the effectiveness of apps, such as less time consumption, user-friendly design, real-time feedback, individualized elements, detailed information, and health professional involvement. All studies were assessed as having some risk of bias. Our results provide a snapshot of the current evidence of effectiveness for a range of health-related apps. Large sample, high-quality, adequately powered, randomized controlled trials are required. In light of the bias evident in the included studies, better reporting of health-related app interventions is also required. The widespread adoption of mobile phones highlights a significant opportunity to impact health behaviors globally, particularly in low- and middle-income countries.

Using data from 138 independent samples, we meta-analytically examined three research questions concerning the roles of personality and network position in organizations. First, how do different personality characteristics—self-monitoring and the Big Five personality traits—relate to indegree centrality and brokerage, the two most studied structurally advantageous positions in organizational networks? Second, how do indegree centrality and brokerage compare in explaining job performance and career success? Third, how do these personality variables and network positions relate to work outcomes? Our results show that self-monitoring predicted indegree centrality (across expressive and instrumental networks) and brokerage (in expressive networks) after controlling for the Big Five traits. Self-monitoring, therefore, was especially relevant for understanding why people differ in their acquisition of advantageous positions in social networks. But the total variance explained by personality ranged between 3% and 5%. Surprisingly, we found that indegree centrality was more strongly related to job performance and career success than brokerage. We also found that personality predicted job performance and career success above and beyond network position and that network position partially mediated the effects of certain personality variables on work outcomes. This paper provides an integrated view of how an individual’s personality and network position combine to influence job performance and career success.

Background: Digital interventions have tremendous potential to improve well-being and health care conveyance by improving adequacy, proficiency, availability, and personalization. They have gained acknowledgment in interventions for the management of a healthy lifestyle. Therefore, we are reviewing existing conceptual frameworks, digital intervention approaches, and associated methods to identify the impact of digital intervention on adopting a healthier lifestyle. Objective: This study aims to evaluate the impact of digital interventions on weight management in maintaining a healthy lifestyle (eg, regular physical activity, healthy habits, and proper dietary patterns). Methods: We conducted a systematic literature review to search the scientific databases (Nature, SpringerLink, Elsevier, IEEE Xplore, and PubMed) that included digital interventions on healthy lifestyle, focusing on preventing obesity and being overweight as a prime objective. Peer-reviewed articles published between 2015 and 2020 were included. We used the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines and a framework for an evidence-based systematic review. Furthermore, we improved the review process by adopting the Rayyan tool and the Scale for the Assessment of Narrative Review Articles. Results: Our initial searches identified 780 potential studies through electronic and manual searches; however, 107 articles in the final stage were cited following the specified inclusion and exclusion criteria. The identified methods for a successful digital intervention to promote a healthy lifestyle are self-monitoring, self-motivation, goal setting, personalized feedback, participant engagement, psychological empowerment, persuasion, digital literacy, efficacy, and credibility. In this study, we identified existing conceptual frameworks for digital interventions, different approaches to provide digital interventions, associated methods, and execution challenges and their impact on the promotion of healthy lifestyle management. Conclusions: This systematic literature review selected intervention principles (rules), theories, design features, ways to determine efficient interventions, and weaknesses in healthy lifestyle management from established digital intervention approaches. The results help us understand how digital interventions influence lifestyle management and overcome the existing shortcomings. It serves as a basis for further research with a focus on designing, developing, testing, and evaluating the generation of personalized lifestyle recommendations as a part of digital health interventions.

The error-related negativity (ERN) is a negative waveform that arises over the front of the scalp immediately after a participant makes a detectable error. The goal of this short article is to describe my serendipitous encounter with this brain signal in 1993–1994 and to briefly review the operation of the underlying error-monitoring system. Recent work suggests that the ERN reflects an internal comparison, by the anterior cingulate cortex, of two signals: an unconscious representation of the ongoing action and a conscious representation of the intended one.

Low infection and case-fatality rates have been thus far observed in Taiwan. One of the reasons for this major success is better use of big data analytics in efficient contact tracing and management and surveillance of those who require quarantine and isolation. We present here a unique application of big data analytics among Taiwanese people who had contact with more than 3000 passengers that disembarked at Keelung harbor in Taiwan for a 1-day tour on January 31, 2020, 5 days before the outbreak of coronavirus disease (COVID-19) on the Diamond Princess cruise ship on February 5, 2020, after an index case was identified on January 20, 2020. The smart contact tracing-based mobile sensor data, cross-validated by other big sensor surveillance data, were analyzed by the mobile geopositioning method and rapid analysis to identify 627,386 potential contact-persons. Information on self-monitoring and self-quarantine was provided via SMS, and severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) tests were offered for symptomatic contacts. National Health Insurance claims big data were linked, to follow-up on the outcome related to COVID-19 among those who were hospitalized due to pneumonia and advised to undergo screening for SARS-CoV-2. As of February 29, a total of 67 contacts who were tested by reverse transcription-polymerase chain reaction were all negative and no confirmed COVID-19 cases were found. Less cases of respiratory syndrome and pneumonia were found after the follow-up of the contact population compared with the general population until March 10, 2020. Big data analytics with smart contact tracing, automated alert messaging for self-restriction, and follow-up of the outcome related to COVID-19 using health insurance data could curtail the resources required for conventional epidemiological contact tracing.

The present study assessed the associations among higher-order thinking skills (reflective thinking, critical thinking) and self-monitoring that contribute to academic achievement among university students. The sample consisted of 196 Iranian university students (mean age = 22.05, SD = 3.06; 112 females; 75 males) who were administered three questionnaires. To gauge reflective thinking, the \"Reflective Thinking Questionnaire\" designed by Kember et al. (Assess Eval High Educ 25(4):380-395, 2000) was utilized. It includes 16 items measuring four types of reflective thinking (habitual action, understanding, reflection, and critical reflection). To assess critical thinking, the \"Watson-Glaser Critical Thinking Appraisal\"(2002) was utilized. It comprises 80 items and consists of 5 subtests (inference, recognizing unstated assumptions, deduction, interpretation, and evaluation). Self-monitoring was measured via 8 items of the self-regulation trait questionnaire designed by O'Neil and Herl (Paper presented at the annual meeting of the American Educational Research Association, San Diego, CA, 1998). The results demonstrated that critical thinking and all components of reflective thinking positively and significantly predicted achievement with habitual action having the lowest impact and reflection exhibiting the highest influence. Self-monitoring indirectly exerted a positive influence on achievement via understanding and reflection. It was also found that among the four subscales of reflective thinking, reflection and critical reflection predicted critical thinking positively and significantly. Self-monitoring had a positive and significant impact on critical thinking. It also significantly and positively influenced understanding as well as reflection. (HRK / Abstract übernommen).

Due to easy access and low cost, Internet-delivered therapies offer an attractive alternative to improving health. Although numerous websites contain health-related information, finding evidence-based programs (as demonstrated through randomized controlled trials, RCTs) can be challenging. We sought to bridge the divide between the knowledge gained from RCTs and communication of the results by conducting a global systematic review and analyzing the availability of evidence-based Internet health programs. The study aimed to (1) discover the range of health-related topics that are addressed through Internet-delivered interventions, (2) generate a list of current websites used in the trials which demonstrate a health benefit, and (3) identify gaps in the research that may have hindered dissemination. Our focus was on Internet-delivered self-guided health interventions that did not require real-time clinical support. A systematic review of meta-analyses was conducted using Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines (PROSPERO Registration Number CRD42016041258). MEDLINE via Ovid, PsycINFO, Embase, Cochrane Database of Systematic Reviews, and the Cumulative Index to Nursing and Allied Health Literature (CINAHL) were searched. Inclusion criteria included (1) meta-analyses of RCTs, (2) at least one Internet-delivered intervention that measured a health-related outcome, and (3) use of at least one self-guided intervention. We excluded group-based therapies. There were no language restrictions. Of the 363 records identified through the search, 71 meta-analyses met inclusion criteria. Within the 71 meta-analyses, there were 1733 studies that contained 268 unique RCTs which tested self-help interventions. On review of the 268 studies, 21.3% (57/268) had functional websites. These included evidence-based Web programs on substance abuse (alcohol, tobacco, cannabis), mental health (depression, anxiety, post-traumatic stress disorder [PTSD], phobias, panic disorders, obsessive compulsive disorder [OCD]), and on diet and physical activity. There were also evidence-based programs on insomnia, chronic pain, cardiovascular risk, and childhood health problems. These programs tended to be intensive, requiring weeks to months of engagement by the user, often including interaction, personalized and normative feedback, and self-monitoring. English was the most common language, although some were available in Spanish, French, Portuguese, Dutch, German, Norwegian, Finnish, Swedish, and Mandarin. There were several interventions with numbers needed to treat of <5; these included painACTION, Mental Health Online for panic disorders, Deprexis, Triple P Online (TPOL), and U Can POOP Too. Hyperlinks of the sites have been listed. A wide range of evidence-based Internet programs are currently available for health-related behaviors, as well as disease prevention and treatment. However, the majority of Internet-delivered health interventions found to be efficacious in RCTs do not have websites for general use. Increased efforts to provide mechanisms to host \"interventions that work\" on the Web and to assist the public in locating these sites are necessary.

Depression treatment might be enhanced by ecological momentary interventions (EMI) based on self-monitoring and person-specific feedback. This study is the first to examine the efficacy of two different EMI modules for depression in routine clinical practice. Outpatients starting depression treatment at secondary mental health services (N = 161; MIDS-DEPRESSION = 35.9, s.d. = 10.7; MAGE = 32.8, s.d. = 12.1; 46% male) participated in a pragmatic randomized controlled trial with three arms. Two experimental groups engaged in 28 days of systematic self-monitoring (5 times per day), and received weekly feedback on either positive affect and activities (Do-module) or negative affect and thinking patterns (Think-module). The control group received no additional intervention. Participants completed questionnaires on depressive symptoms (primary outcome), social functioning, and empowerment before and after the intervention period, and at four measurements during a 6-month follow-up period. Of the 90 (out of 110) participants who completed the intervention, 86% would recommend it. However, the experimental groups did not show significantly more or faster changes over time than the control group in terms of depressive symptoms, social functioning, and empowerment. Furthermore, the trajectories of the two EMI modules were very similar. We did not find statistical evidence that this type of EMI augments the efficacy of regular depression treatment, regardless of module content. We cannot rule out that EMIs have a positive impact on other domains or provide a more efficient way of delivering care. Nonetheless, EMI's promise of effectiveness has not materialized yet.

Electronic activity monitors (such as those manufactured by Fitbit, Jawbone, and Nike) improve on standard pedometers by providing automated feedback and interactive behavior change tools via mobile device or personal computer. These monitors are commercially popular and show promise for use in public health interventions. However, little is known about the content of their feedback applications and how individual monitors may differ from one another. The purpose of this study was to describe the behavior change techniques implemented in commercially available electronic activity monitors. Electronic activity monitors (N=13) were systematically identified and tested by 3 trained coders for at least 1 week each. All monitors measured lifestyle physical activity and provided feedback via an app (computer or mobile). Coding was based on a hierarchical list of 93 behavior change techniques. Further coding of potentially effective techniques and adherence to theory-based recommendations were based on findings from meta-analyses and meta-regressions in the research literature. All monitors provided tools for self-monitoring, feedback, and environmental change by definition. The next most prevalent techniques (13 out of 13 monitors) were goal-setting and emphasizing discrepancy between current and goal behavior. Review of behavioral goals, social support, social comparison, prompts/cues, rewards, and a focus on past success were found in more than half of the systems. The monitors included a range of 5-10 of 14 total techniques identified from the research literature as potentially effective. Most of the monitors included goal-setting, self-monitoring, and feedback content that closely matched recommendations from social cognitive theory. Electronic activity monitors contain a wide range of behavior change techniques typically used in clinical behavioral interventions. Thus, the monitors may represent a medium by which these interventions could be translated for widespread use. This technology has broad applications for use in clinical, public health, and rehabilitation settings.

[This corrects the article DOI: 10.2196/jmir.8890.].