Incidence of coronary heart disease among remote workers: a nationwide web-based cohort study.

Coronary heart disease (CHD) risk is influenced by socioeconomic status-related parameters, particularly occupation. We investigated occupational gaps in CHD risk and how the introduction of remote work moderated the observed occupational differences in CHD risk during the coronavirus disease 2019 pandemic in Japan. Data from a web-based, nationwide cohort study, comprising 17,640 workers (aged 20-65 years) with baseline data from December 2020, were analyzed. Participants were grouped by occupation as upper-level nonmanual workers (managers/professionals) and others (reference group). The primary outcome was CHD (angina pectoris/myocardial infarction) onset retrospectively confirmed at the 1-year follow-up survey. Upper-level nonmanual workers exhibited a higher CHD incidence than others (2.3% vs. 1.7%). This association was pronounced in the younger (20-49 years) population, with a significant CHD risk (adjusted risk ratio = 1.88). Upper-level nonmanual workers exhibited nearly 15% higher remote work prevalence, with a significant remote work-related CHD risk (adjusted risk ratio = 1.92). The mediating effects of remote work explained an overall disparity of 32% among the younger population. Occupational gaps in CHD incidence in Japan differ from those in Western countries, where upper-level nonmanual workers have lower cardiovascular risk. In Japan, remote work can mediate CHD risk in the younger population of upper-level nonmanual workers.

The Effects of Problematic Internet Use and Emotional Connotation on Internet Slang Processing: Evidence from a Lexical Decision Task.

Young people use slang for identifying themselves with a particular social group, gaining social recognition and respect from that group, and expressing their emotional state. One feature of Internet slang is its active use by youth in online communication, which, under certain conditions, may cause problematic Internet use (PIU). We conducted two studies in young Russian speakers (n1 = 115, n2 = 106). In study 1, participants were asked to rate a set of slang and common words using Self-Assessment Manikin. The study revealed that the most reliable predictor of higher emotional ratings was word familiarity. There were no significant effects of slang vs. common words or word frequency. In study 2, we used a dual lexical decision task to reveal the effects of word characteristics and propensity for PIU on reaction time (RT) for Internet slang words in pairs with semantically related vs. unrelated common words. Study 2 did not reveal any significant semantic priming effect. Word frequency was a significant predictor of lexical decision facilitation. Common, but not slang, word valence and dominance significantly affected RT in the opposite direction. Individuals with higher cognitive preoccupation with the Internet responded significantly faster, while those more likely to use online communication for mood regulation responded significantly slower to the stimuli. Apparently, on explicit and implicit levels, in-depth knowledge of Internet slang can be one the PIU markers. The results are discussed in line with Davis' approach to determining the general pathological Internet use.

ENIGMA: A Web Application for Running Online Artificial Grammar Learning Experiments.

Artificial grammar learning (AGL) is an experimental paradigm frequently adopted to investigate the unconscious and conscious learning and application of linguistic knowledge. This paper will introduce ENIGMA ( https://enigma-lang.org ) as a free, flexible, and lightweight Web-based tool for running online AGL experiments. The application is optimized for desktop and mobile devices with a user-friendly interface, which can present visual and aural stimuli and elicit judgment responses with RT measures. Without limits in time and space, ENIGMA could help collect more data from participants with diverse personal and language backgrounds and variable cognitive skills. Such data are essential to explain complex factors influencing learners' performance in AGL experiments and answer various research questions regarding L1/L2 acquisition. The introduction of the core features in ENIGMA is followed by an example study that partially replicated Chen (Lang Acquis 27(3):331-361, 2020) to illustrate possible experimental designs and examine the quality of the collected data.

The Impact of Video-Based Microinterventions on Attitudes Toward Mental Health and Help Seeking in Youth: Web-Based Randomized Controlled Trial.

BACKGROUND: Mental health (MH) problems in youth are prevalent, burdening, and frequently persistent. Despite the existence of effective treatment, the uptake of professional help is low, particularly due to attitudinal barriers. OBJECTIVE: This study evaluated the effectiveness and acceptability of 2 video-based microinterventions aimed at reducing barriers to MH treatment and increasing the likelihood of seeking professional help in young people. METHODS: This study was entirely web based and open access. The interventions addressed 5 MH problems: generalized anxiety disorder, depression, bulimia, nonsuicidal self-injury, and problematic alcohol use. Intervention 1 aimed to destigmatize and improve MH literacy, whereas intervention 2 aimed to induce positive outcome expectancies regarding professional help seeking. Of the 2435 participants who commenced the study, a final sample of 1394 (57.25%) participants aged 14 to 29 years with complete data and sufficient durations of stay on the video pages were randomized in a fully automated manner to 1 of the 5 MH problems and 1 of 3 conditions (control, intervention 1, and intervention 2) in a permuted block design. After the presentation of a video vignette, no further videos were shown to the control group, whereas a second, short intervention video was presented to the intervention 1 and 2 groups. Intervention effects on self-reported potential professional help seeking (primary outcome), stigma, and attitudes toward help seeking were examined using analyses of covariance across and within the 5 MH problems. Furthermore, we assessed video acceptability. RESULTS: No significant group effects on potential professional help seeking were found in the total sample (F2,1385=0.99; P=.37). However, the groups differed significantly with regard to stigma outcomes and the likelihood of seeking informal help (F2,1385=3.75; P=.02). Furthermore, separate analyses indicated substantial differences in intervention effects among the 5 MH problems. CONCLUSIONS: Interventions to promote help seeking for MH problems may require disorder-specific approaches. The study results can inform future research and public health campaigns addressing adolescents and young adults. TRIAL REGISTRATION: German Clinical Trials Register DRKS00023110; https://drks.de/search/de/trial/DRKS00023110.

Pharmacokinetics Profiler (PhaKinPro): Model Development, Validation, and Implementation as a Web Tool for Triaging Compounds with Undesired Pharmacokinetics Profiles.

Computational models that predict pharmacokinetic properties are critical to deprioritize drug candidates that emerge as hits in high-throughput screening campaigns. We collected, curated, and integrated a database of compounds tested in 12 major end points comprising over 10,000 unique molecules. We then employed these data to build and validate binary quantitative structure-activity relationship (QSAR) models. All trained models achieved a correct classification rate above 0.60 and a positive predictive value above 0.50. To illustrate their utility in drug discovery, we used these models to predict the pharmacokinetic properties for drugs in the NCATS Inxight Drugs database. In addition, we employed the developed models to predict the pharmacokinetic properties of all compounds in the DrugBank. All models described in this paper have been integrated and made publicly available via the PhaKinPro Web-portal that can be accessed at https://phakinpro.mml.unc.edu/.

Against the odds: exploring individuals' pushback mechanisms against commercialized football gambling.

Introduction: The need for money, the pursuit of pleasure, and the liberalized access to gambling have been documented in several pieces of literature as the drivers of gambling. Such drivers are predicated on commercialized gambling, leading to the growth of the gambling industry and constituting a structural influence that normalizes the activity among young people. Methods: Through a qualitative inquiry, this study investigates the social agentic factors of individuals who are susceptible to gambling. Fifteen non-gamblers were recruited across three commercial cities in Africa, namely Nairobi, Lagos, and Johannesburg. We first established the gambling susceptibility of the participants: their need for money, their passion for football, ownership of a smartphone, access to the internet, and exposure to football gambling marketing. Results: Consequently, we probed for their agency, which is indicative of why they do not gamble, despite being susceptible to engaging in the activity. Four major agentic factors were identified from the participants; knowledge of the industry's business model, conserving the integrity of football, identity of self, morality and/or religion model. Discussion: As such, these factors may be utilized to develop an intervention program for gamblers within the geographical context.

Effect of Prosocial Behaviors on e-Consultations in a Web-Based Health Care Community: Panel Data Analysis.

BACKGROUND: Patients using web-based health care communities for e-consultation services have the option to choose their service providers from an extensive digital market. To stand out in this crowded field, doctors in web-based health care communities often engage in prosocial behaviors, such as proactive and reactive actions, to attract more users. However, the effect of these behaviors on the volume of e-consultations remains unclear and warrants further exploration. OBJECTIVE: This study investigates the impact of various prosocial behaviors on doctors' e-consultation volume in web-based health care communities and the moderating effects of doctors' digital and offline reputations. METHODS: A panel data set containing information on 2880 doctors over a 22-month period was obtained from one of the largest web-based health care communities in China. Data analysis was conducted using a 2-way fixed effects model with robust clustered SEs. A series of robustness checks were also performed, including alternative measurements of independent variables and estimation methods. RESULTS: Results indicated that both types of doctors' prosocial behaviors, namely, proactive and reactive actions, positively impacted their e-consultation volume. In terms of the moderating effects of external reputation, doctors' offline professional titles were found to negatively moderate the relationship between their proactive behaviors and their e-consultation volume. However, these titles did not significantly affect the relationship between doctors' reactive behaviors and their e-consultation volume (P=.45). Additionally, doctors' digital recommendations from patients negatively moderated both the relationship between doctors' proactive behaviors and e-consultation volume and the relationship between doctors' reactive behaviors and e-consultation volume. CONCLUSIONS: Drawing upon functional motives theory and social exchange theory, this study categorizes doctors' prosocial behaviors into proactive and reactive actions. It provides empirical evidence that prosocial behaviors can lead to an increase in e-consultation volume. This study also illuminates the moderating roles doctors' digital and offline reputations play in the relationships between prosocial behaviors and e-consultation volume.

Internet-based eHealth technology for emotional well-being among the older adults with a family cancer history: full mediation effects of health information self-efficacy and cancer fatalism.

BACKGROUND: Older adults with a family cancer history (FCH) face an increased cancer risk, which may adversely impact their emotional well-being. Internet-based eHealth technologies (IETs) provide a potential solution to this challenge. This study examines the influence of using IETs on the emotional well-being of older adults with FCH. It also delves into the mediating pathways through health information self-efficacy and cancer fatalism. METHODS: This study conducted a mediation analysis using data from the Health Information National Trends Survey (HINTS 6) collected from March 2022 to November 2022, focusing on older adults with FCH who had previously searched for cancer-related information (N = 1,280). RESULTS: In the mediation model, no positive direct associations between IETs usage and emotional well-being were found. Only health information self-efficacy and cancer fatalism were found to mediate the relationship between IETs usage and emotional well-being serially (ß = 0.007, 95% CI [0.003, 0.012]). CONCLUSIONS: The findings inform health information professionals and healthcare practitioners on enhancing the impact of IETs usage on individual health information self-efficacy, which mitigates cancer fatalism, contributing to better emotional well-being in the digital era.

An online survey on public awareness of drug clinical trials in inland cities of northern China.

Objective: The aims of this survey were to investigate the public awareness of drug clinical trials (DCTs) and willingness to participate the DCTs, and provide references for propaganda and science popularization of DCTs. Methods: A self-designed questionnaire named "an online survey questionnaire on public awareness of DCTs" was used to conduct an online survey from January to March 2022. The demographic characteristics and the response of participants to the awareness and willingness to participate the DCTs were collected. The factors affecting the public awareness of DCTs were analyzed by single factor and binary logistic regression analysis. Results: One thousand three hundred eighty valid questionnaires were collected, and the respondents' awareness rate of DCTs was 61.1%. Thirteen demographic characteristics including age, gender, education, occupation, work fields, household type, marital status, city type, income, medical insurance, medical expenditure, pressure to seek medical care, financial pressure, both significantly affected the qualified rate of participants' awareness of DCTs (p < 0.001) by single factor analysis. Binary logistic regression analysis indicated that education level, work fields, city type, medical insurance, and medical expenditure affected independently the participants' awareness rate of DCTs (p < 0.001). 52.9% of the participants were willing to take part in DCTs. "to promote medical progress" (54.4%) or "believe doctors" (31.1%) were the most frequent reasons for subjects participating in DCTs. Conclusion: The public awareness rate of DCTs and the willingness to participate in drug clinical were significantly affected by the demographic characteristics of subjects. Thus, targeting the needs of the public, propaganda, and science popularization of DCTs should be carried out and served public health.

Evaluating a web-based training curriculum for disseminating best practices for the care of newborns with neonatal opioid withdrawal syndrome in a rural hospital, the NOWS-NM Program.

BACKGROUND: The incidence of neonatal opiate withdrawal syndrome (NOWS) in the US has grown dramatically over the past two decades. Many rural hospitals not equipped to manage these patients transfer them to hospitals in bigger cities. METHODS: We created a curriculum, the NOWS-NM Program, a web-based curriculum training in best practices. To evaluate the curriculum, we conducted pre- and post-surveys of NOWS knowledge, attitudes, and care practices, plus post-curriculum interviews and focus groups. RESULTS: Fourteen participants completed both pre- and post-curriculum surveys. They indicated an increase in knowledge and care practices. A small number of respondents expressed negative attitudes about parents of infants with NOWS at pre-test, the training curriculum appeared to have no impact on such attitudes at post-test. Sixteen participants participated in focus groups or interviews. Qualitative data reinforced the positive quantitative results and contradicted the negative survey results, respondents reported that the program did reduce stigma and improve provider/staff interactions with patients. CONCLUSIONS: This curriculum demonstrated positive impacts on NOWS knowledge and care practices. Incorporating focus on core concepts of trauma-informed care and self-regulation in future iterations of the curriculum may strengthen the opportunity to change attitudes and address the needs expressed by participants and improve care of families and babies with NOWS.

GSB: GNGS and SAG-BiGRU network for malware dynamic detection.

With the rapid development of the Internet, the continuous increase of malware and its variants have brought greatly challenges for cyber security. Due to the imbalance of the data distribution, the research on malware detection focuses on the accuracy of the whole data sample, while ignoring the detection rate of the minority categories' malware. In the dataset sample, the normal data samples account for the majority, while the attacks' malware accounts for the minority. However, the minority categories' attacks will bring great losses to countries, enterprises, or individuals. For solving the problem, this study proposed the GNGS algorithm to construct a new balance dataset for the model algorithm to pay more attention to the feature learning of the minority attacks' malware to improve the detection rate of attacks' malware. The traditional malware detection method is highly dependent on professional knowledge and static analysis, so we used the Self-Attention with Gate mechanism (SAG) based on the Transformer to carry out feature extraction between the local and global features and filter irrelevant noise information, then extracted the long-distance dependency temporal sequence features by the BiGRU network, and obtained the classification results through the SoftMax classifier. In the study, we used the Alibaba Cloud dataset for malware multi-classification. Compared the GSB deep learning network model with other current studies, the experimental results showed that the Gaussian noise generation strategy (GNGS) could solve the unbalanced distribution of minority categories' malware and the SAG-BiGRU algorithm obtained the accuracy rate of 88.7% on the eight-classification, which has better performance than other existing algorithms, and the GSB model also has a good effect on the NSL-KDD dataset, which showed the GSB model is effective for other network intrusion detection.

Therapeutic education of patients with coronary heart disease: Impact of digital platform monitoring in preventing major cardiovascular events in Tunisia: Study protocol.

BACKGROUND: Faced with the increase in the number of chronic diseases with the aging of the population, and with the observation of the insufficiency of therapeutic control, a new need has emerged, that of having a patient as a partner in care. METHODS: This study is a randomized controlled trial. Patients with coronary heart disease will be recruited from one clinical site and randomly assigned into two groups: the intervention group and the control group. All participants will be followed up for a total of one year (with three-time points for data collection). Patients who are assigned to the intervention group will receive therapeutic education at first. The digital platform will then allow healthcare providers to accompany them outside the hospital walls. The primary outcome is the incidence of major cardiovascular events within one year of discharge. Main secondary outcomes include changes in health behaviors, medication adherence, and quality of life score. The digital platform is a multi-professional telemonitoring platform that allows care teams to accompany the patient outside the hospital walls. It allows the collection and transmits information from the patient's home to the therapeutic education team. All data will be secured at a certified host. The patient application provides data on compliance, adherence to physical activity (number of steps taken per day), adequate diet (weight gain, food consumed during the meal, compliance with low-salt or salt-free diet, diabetic diet), smoking cessation, as well as medication adherence. Access to educational tools (digital media) is provided to all initial program participants. These tools will be updated annually by the rehabilitation team on the recommendations. The platform also offers the possibility of organizing an individual or group remote educational session (videoconference modules allowing group and individual sessions), a secure integrated caregiver-patient messaging system. The control group will receive the usual controls at the hospital. DISCUSSION: To offer a complete solution of care to our patients, we have thought of setting up a digital platform that aims to monitor the patient and strengthen their abilities to manage their condition daily. This pilot experience could be generalized to several services and disciplines. It could be used in several research works. TRIAL REGISTRATION: Trial registered with the Pan African Clinical Trial Registry (PACTR202307694422939). URL: https://pactr.samrc.ac.za/TrialDisplay.aspx?TrialID=24247.

A model study of teaching method reform of computer laboratory course integrating internet of things technology.

The Internet of Things (IoT) is gradually changing the way teaching and learning take place in on-campus programs. In particular, face capture services improve student concentration to create an efficient classroom atmosphere by using face recognition algorithms that support end devices. However, reducing response latency and executing face analysis services effectively in real-time is still challenging. For this reason, this paper proposed a pedagogical model of face recognition for IoT devices based on edge computing (TFREC). Specifically, this research first proposed an IoT service-based face capture algorithm to optimize the accuracy of face recognition. In addition, the service deployment method based on edge computing is proposed in this paper to obtain the best deployment strategy and reduce the latency of the algorithm. Finally, the comparative experimental results demonstrate that TFREC has 98.3% accuracy in face recognition and 72 milliseconds in terms of service response time. This research is significant for advancing the optimization of teaching methods in school-based courses, meanwhile, providing beneficial insights for the application of face recognition and edge computing in the field of education.

The effect of internet-administered support (carer eSupport) on preparedness for caregiving in informal caregivers of patients with head and neck cancer compared with support as usual: a study protocol for a randomized controlled trial.

BACKGROUND: Informal caregivers (ICs) of patients with cancer provide essential and mainly uncompensated care. A self-perceived preparedness to care for the patient is associated with a lower caregiver burden, described as the extent to which caregiving is perceived as having adverse effects on IC functioning and well-being. ICs' well-being is associated with patient-perceived quality of care, suggesting that interventions to optimize ICs' health are essential in order to improve patient care. Head and neck cancer (HNC) is the seventh most common malignant disease in the world. The disease and its treatment have a significant negative impact on the patient's health and quality of life. Symptoms usually interfere with swallowing, food and fluid intake, breathing, speaking, and communication. ICs frequently manage patients' symptoms and side effects, especially problems related to nutrition and oral pain, without being properly prepared. Carer eSupport is an Internet-administered intervention, based on focus group discussions with ICs, developed in collaboration with ICs and healthcare professionals, tested for feasibility, and deemed feasible. This study protocol outlines the methods of investigating the effects of Carer eSupport plus support as usual (SAU) on self-reported preparedness for caregiving, caregiver burden, and well-being in the ICs of patients with HNC, compared with ICs receiving SAU only. METHODS AND ANALYSIS: In this randomized controlled trial, 110 ICs of patients with HNC, undergoing radiotherapy combined with surgery and/or medical oncological treatment, will be randomized (1:1) to Carer eSupport plus SAU or SAU only. Data will be collected at baseline (before randomization), post-intervention (after 18 weeks), and 3 months after post-intervention. The primary outcome is self-reported preparedness for caregiving. Secondary outcomes are self-reported caregiver burden, anxiety, depression, and health-related quality of life. The effect of Carer eSupport plus SAU on preparedness for caregiving and secondary outcomes, compared with SAU only, will be evaluated by intention to treat analyses using linear regression models, mixed-model regression, or analysis of covariance. DISCUSSION: If proven effective, Carer eSupport has the potential to significantly improve ICs' preparedness for caregiving and their wellbeing, thereby improving patient-perceived quality of care and patient wellbeing. TRIAL REGISTRATION: ClinicalTrials.gov; NCT06307418, registered 12.03.2024 (https://clinicaltrials.gov/search? term=NCT06307418).

Individuals' attitudes toward digital mental health apps and implications for adoption in Portugal: web-based survey.

BACKGROUND: The literature is consensual regarding the academic community exhibiting higher levels of mental disorder prevalence than the general population. The potential of digital mental health apps for improving access to resources to cope with these issues is ample. However, studies have yet to be performed in Portugal on individuals' attitudes and perceptions toward digital mental health applications or their preferences and decision drivers on obtaining mental health care, self-assessment, or treatment. OBJECTIVE: This study aims to understand the determinants of digital mental health applications use in the Portuguese academic community of Porto, along with potential adoption barriers and enablers. METHODS: A cross-sectional, web-based survey was delivered via dynamic email to the University of Porto's academic community. Data collection occurred between September 20 and October 20, 2022. We used structural equation modeling to build three models, replicating a peer-reviewed and published study and producing a newly full mediation model shaped by the collected data. We tested the relationships between use of digital mental health apps and perceived stress, perceived need to seek help for mental health, perceived stigma, past use of mental health services, privacy concerns, and social influence. RESULTS: Of the 539 participants, 169 (31.4%) reported having used digital mental health apps. Perceived stress and a latent variable, comprising perceptions of mental health problems and coping strategies, were positively associated with mental health app use, while privacy concerns regarding one's information being accessible to others were negatively associated. Perceived stigma, need to seek help, and close relationships did not have a statistically significant direct effect. CONCLUSIONS: These findings can inform product and policy development of new, better-targeted digital mental health app interventions, with implications for researchers and academia, industry, and policymakers. Our study concludes that, to maximize adherence to these apps, they should have low to no financial charges, demonstrate evidence of their helpfulness and focus on the timely delivery of care. We also conclude that to foster digital mental health app use, there is a need to improve mental health literacy, namely regarding self-awareness of one's conditions, acceptable stress levels, and overall behavior towards mental health. TRIAL REGISTRATION: RR2-10.2196/41040.

Usability of an Automated System for Real-Time Monitoring of Shared Decision-Making for Surgery: Mixed Methods Evaluation.

BACKGROUND: Improving shared decision-making (SDM) for patients has become a health policy priority in many countries. Achieving high-quality SDM is particularly important for approximately 313 million surgical treatment decisions patients make globally every year. Large-scale monitoring of surgical patients' experience of SDM in real time is needed to identify the failings of SDM before surgery is performed. We developed a novel approach to automating real-time data collection using an electronic measurement system to address this. Examining usability will facilitate its optimization and wider implementation to inform interventions aimed at improving SDM. OBJECTIVE: This study examined the usability of an electronic real-time measurement system to monitor surgical patients' experience of SDM. We aimed to evaluate the metrics and indicators relevant to system effectiveness, system efficiency, and user satisfaction. METHODS: We performed a mixed methods usability evaluation using multiple participant cohorts. The measurement system was implemented in a large UK hospital to measure patients' experience of SDM electronically before surgery using 2 validated measures (CollaboRATE and SDM-Q-9). Quantitative data (collected between April 1 and December 31, 2021) provided measurement system metrics to assess system effectiveness and efficiency. We included adult patients booked for urgent and elective surgery across 7 specialties and excluded patients without the capacity to consent for medical procedures, those without access to an internet-enabled device, and those undergoing emergency or endoscopic procedures. Additional groups of service users (group 1: public members who had not engaged with the system; group 2: a subset of patients who completed the measurement system) completed user-testing sessions and semistructured interviews to assess system effectiveness and user satisfaction. We conducted quantitative data analysis using descriptive statistics and calculated the task completion rate and survey response rate (system effectiveness) as well as the task completion time, task efficiency, and relative efficiency (system efficiency). Qualitative thematic analysis identified indicators of and barriers to good usability (user satisfaction). RESULTS: A total of 2254 completed surveys were returned to the measurement system. A total of 25 service users (group 1: n=9; group 2: n=16) participated in user-testing sessions and interviews. The task completion rate was high (169/171, 98.8%) and the survey response rate was good (2254/5794, 38.9%). The median task completion time was 3 (IQR 2-13) minutes, suggesting good system efficiency and effectiveness. The qualitative findings emphasized good user satisfaction. The identified themes suggested that the measurement system is acceptable, easy to use, and easy to access. Service users identified potential barriers and solutions to acceptability and ease of access. CONCLUSIONS: A mixed methods evaluation of an electronic measurement system for automated, real-time monitoring of patients' experience of SDM showed that usability among patients was high. Future pilot work will optimize the system for wider implementation to ultimately inform intervention development to improve SDM. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): RR2-10.1136/bmjopen-2023-079155.

Effectiveness of a Web-Based Individual Coping and Alcohol Intervention Program for Children of Parents With Alcohol Use Problems: Randomized Controlled Trial.

BACKGROUND: Children whose parents have alcohol use problems are at an increased risk of several negative consequences, such as poor school performance, an earlier onset of substance use, and poor mental health. Many would benefit from support programs, but the figures reveal that only a small proportion is reached by existing support. Digital interventions can provide readily accessible support and potentially reach a large number of children. Research on digital interventions aimed at this target group is scarce. We have developed a novel digital therapist-assisted self-management intervention targeting adolescents whose parents had alcohol use problems. This program aims to strengthen coping behaviors, improve mental health, and decrease alcohol consumption in adolescents. OBJECTIVE: This study aims to examine the effectiveness of a novel web-based therapist-assisted self-management intervention for adolescents whose parents have alcohol use problems. METHODS: Participants were recruited on the internet from social media and websites containing health-related information about adolescents. Possible participants were screened using the short version of the Children of Alcoholics Screening Test-6. Eligible participants were randomly allocated to either the intervention group (n=101) or the waitlist control group (n=103), and they were unblinded to the condition. The assessments, all self-assessed, consisted of a baseline and 2 follow-ups after 2 and 6 months. The primary outcome was the Coping With Parents Abuse Questionnaire (CPAQ), and secondary outcomes were the Center for Epidemiological Studies Depression Scale, Alcohol Use Disorders Identification Test (AUDIT-C), and Ladder of Life (LoL). RESULTS: For the primary outcome, CPAQ, a small but inconclusive treatment effect was observed (Cohen d=-0.05 at both follow-up time points). The intervention group scored 38% and 46% lower than the control group on the continuous part of the AUDIT-C at the 2- and 6-month follow-up, respectively. All other between-group comparisons were inconclusive at either follow-up time point. Adherence was low, as only 24% (24/101) of the participants in the intervention group completed the intervention. CONCLUSIONS: The findings were inconclusive for the primary outcome but demonstrate that a digital therapist-assisted self-management intervention may contribute to a reduction in alcohol consumption. These results highlight the potential for digital interventions to reach a vulnerable, hard-to-reach group of adolescents but underscore the need to develop more engaging support interventions to increase adherence. TRIAL REGISTRATION: ISRCTN Registry ISRCTN41545712; https://www.isrctn.com/ISRCTN41545712?q=ISRCTN41545712. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): RR2-10.1186/1471-2458-12-35.

PsiOvi Staging Model for Schizophrenia (PsiOvi SMS): A New Internet Tool for Staging Patients with Schizophrenia.

BACKGROUND: One of the challenges of psychiatry is the staging of patients, especially those with severe mental disorders. Therefore, we aim to develop an empirical staging model for schizophrenia. METHODS: Data were obtained from 212 stable outpatients with schizophrenia: demographic, clinical, psychometric (PANSS, CAINS, CDSS, OSQ, CGI-S, PSP, MATRICS), inflammatory peripheral blood markers (C-reactive protein, interleukins-1RA and 6, and platelet/lymphocyte [PLR], neutrophil/lymphocyte [NLR], and monocyte/lymphocyte [MLR] ratios). We used machine learning techniques to develop the model (genetic algorithms, support vector machines) and applied a fitness function to measure the model's accuracy (% agreement between patient classification of our model and the CGI-S). RESULTS: Our model includes 12 variables from 5 dimensions: 1) psychopathology: positive, negative, depressive, general psychopathology symptoms; 2) clinical features: number of hospitalizations; 3) cognition: processing speed, visual learning, social cognition; 4) biomarkers: PLR, NLR, MLR; and 5) functioning: PSP total score. Accuracy was 62% (SD = 5.3), and sensitivity values were appropriate for mild, moderate, and marked severity (from 0.62106 to 0.6728). DISCUSSION: We present a multidimensional, accessible, and easy-to-apply model that goes beyond simply categorizing patients according to CGI-S score. It provides clinicians with a multifaceted patient profile that facilitates the design of personalized intervention plans.

Dissociation of prepotent response inhibition and interference control in problematic internet use: evidence from the Go/No-Go and Flanker tasks.

BACKGROUND: Problematic Internet Use (PIU), characterized by failures to control the overuse of internet, is associated with a range of functional impairments. However, there is limited research on the specific impact of PIU on inhibitory control functions, particularly in terms of differentiating between prepotent response inhibition and interference control. Therefore, the main objective of this study is to investigate these two components of inhibitory control in individuals with PIU. METHODS: Thirty participants who met the PIU criteria and 30 control participants were included in the present study. All participants completed the Go/No-Go and Flanker tasks, in which internet-related images and words were used as task stimuli. RESULTS: In the Go/No-Go task, all participants exhibited poorer performance in inhibiting internet-related stimuli compared to internet-unrelated stimuli, during the No-Go trials. In the Flanker task, results revealed a three-way interaction of Group, Stimulus type and Congruency. Specifically, in the incongruent condition, participants with PIU exhibited slower responses for internet-unrelated targets compared to internet-related targets, whereas no similar effect was observed among individuals with low internet use. CONCLUSIONS: The findings suggest that difficulties in controlling the interference effect of internet-related information represent a key dysfunction in inhibitory control of PIU.