A Technology-Assisted Language Intervention for Children Who Are Deaf or Hard of Hearing: A Randomized Clinical Trial.

BACKGROUND AND OBJECTIVES: Children who are deaf or hard of hearing (DHH) often have persistent language delays despite early identification and interventions. The technology-assisted language intervention (TALI), which incorporates augmentative and alternative communication technology into a speech-language therapy model, was designed to support language learning. The study objective was to evaluate the impact of the TALI on spoken language outcomes in DHH children. METHODS: Children aged 3 to 12 years with mild to profound bilateral hearing loss were enrolled in a single-site randomized controlled trial. Children were randomly assigned to receive the TALI or treatment as usual (TAU) (with no change in current care) and were followed for 24 weeks. Primary outcomes included spoken language measures elicited from language samples. Secondary outcomes included standardized assessments. Intention-to-treat analyses were used. RESULTS: Analyses focused on 41 children randomly assigned to TALI (n = 21) or TAU (n = 20). Among all participants, mean age was 6.3 years (SD 2.5). Over 24 weeks, children in the TALI group, compared with those in the TAU group, had significantly greater increases in the length of phrases they used to express themselves (ß = .91 vs .15, respectively; P< .0001). Similar findings were seen with conversational turn-taking and number of different words spoken. CONCLUSIONS: Providing visual supports for language concepts that are typically challenging for DHH children to acquire allowed children to process and comprehend spoken language more fully. Such strategies can mitigate persistent language delays with the goal of improving lifelong outcomes and independence across settings.

Development and Feasibility of MindChip™: A Social Emotional Telehealth Intervention for Autistic Adults.

The study aims to develop and pilot a telehealth social emotional program, MindChip™ delivered with a computer based interventions (CBI) (Mind Reading©) for autistic adults. MindChip™ combined four theoretical perspectives and community feedback underpinning the essential mechanisms for targeting the social emotional understanding of autistic adults. A randomised pragmatic pilot trial (N = 25) was conducted to explore the feasibility of MindChip™ (n = 11) and to understand the preliminary efficacy of combining it with CBI compared to CBI only (n = 14). The use of MindChip™ and CBI combined demonstrated partial feasibility, with preliminary efficacy findings revealing increased emotion recognition generalisation outcomes compared to CBI only. Further research is required to improve the engagement and personalisation of the intervention for autistic adults.

Pilot trial of a transdiagnostic computerized anxiety sensitivity intervention among VA primary care patients.

People in need of mental health treatment do not access care at high rates or in a timely manner, inclusive of Veterans at Department of Veteran's Affairs (VA) medical centers. Barriers to care have been identified, and one potential solution is the use of technology-based interventions within primary care. This study evaluated the Cognitive Anxiety Sensitivity Treatment (CAST), a previously developed computerized treatment that has shown efficacy in community samples for mental health symptoms including: anxiety, depression, post-traumatic stress, and suicidal ideation. VA primary care patients with elevated anxiety sensitivity (N = 25) were recruited to participate in a mixed-method open pilot to examine acceptability, usability, and preliminary effectiveness in a VA primary care setting. Participants completed an initial visit, that included the intervention, and a one-month follow-up. Veterans found CAST to be generally acceptable, with strong usability ratings. Qualitative analyses identified areas of strength and areas for improvement for use with VA primary care Veterans. Repeated measures ANCOVAs revealed significant effects for symptoms of anxiety, depression, traumatic-stress, and suicidal ideation. CAST could potentially have a large public health impact if deployed across VA medical centers as a first-step intervention for a range of mental health presenting concerns.

Artificial intelligence: a disruptive tool for a smarter medicine.

OBJECTIVE: Although highly successful, the medical R&D model is failing at improving people's health due to a series of flaws and defects inherent to the model itself. A new collective intelligence, incorporating human and artificial intelligence (AI) could overcome these obstacles. Because AI will play a key role in this new collective intelligence, it is necessary that those involved in healthcare have a general knowledge of how these technologies work. With this comprehensive review, we intend to provide it. MATERIALS AND METHODS: A broad-ranging search has been undertaken on institutional and non-institutional websites in order to identify relevant papers, comments and reports. RESULTS: We firstly describe the flaws and defects of the current R&D biomedical model and how the generation of a new collective intelligence will result in a better and wiser medicine through a truly personalized and holistic approach. We, then, discuss the new forms of data collection and data processing and the different types of artificial learning and their specific algorithms. Finally, we review the current uses and applications of AI in the biomedical field and how these can be expanded, as well as the limitations and challenges of applying these new technologies in the medical field. CONCLUSIONS: This colossal common effort based on a new collective intelligence will exponentially improve the quality of medical research, resulting in a radical change for the better in the healthcare model. AI, without replacing us, is here to help us achieve the ambitious goal set by the WHO in the Alma Ata declaration of 1978: "Health for All".

Machine Learning in Cardiology-Ensuring Clinical Impact Lives Up to the Hype.

Despite substantial advances in the study, treatment, and prevention of cardiovascular disease, numerous challenges relating to optimally screening, diagnosing, and managing patients remain. Simultaneous improvements in computing power, data storage, and data analytics have led to the development of new techniques to address these challenges. One powerful tool to this end is machine learning (ML), which aims to algorithmically identify and represent structure within data. Machine learning's ability to efficiently analyze large and highly complex data sets make it a desirable investigative approach in modern biomedical research. Despite this potential and enormous public and private sector investment, few prospective studies have demonstrated improved clinical outcomes from this technology. This is particularly true in cardiology, despite its emphasis on objective, data-driven results. This threatens to stifle ML's growth and use in mainstream medicine. We outline the current state of ML in cardiology and outline methods through which impactful and sustainable ML research can occur. Following these steps can ensure ML reaches its potential as a transformative technology in medicine.

Big data-driven precision medicine: Starting the custom-made era of iatrology.

Precision medicine is a new therapeutic concept and method emerging in recent years. The rapid development of precision medicine is driven by the development of omics related technology, biological information and big data science. Precision medicine is provided to implement precise and personalized treatment for diseases and specific patients. Precision medicine is commonly used in the diagnosis, treatment and prevention of various diseases. This review introduces the application of precision medicine in eight systematic diseases of the human body, and systematically presenting the current situation of precision medicine. At the same time, the shortcomings and limitations of precision medicine are pointed out. Finally, we prospect the development of precision medicine.

Short- and long-term changes in substance-related coping as mediators of in-person and computerized CBT for alcohol and drug use disorders.

BACKGROUND: No studies have examined long-term changes in substance-related coping skills as a statistical mediator of cognitive-behavioral therapy (CBT) for substance use disorders (SUD). METHODS: We tested both short- and long-term changes in coping as mediators of treatment effects in two trials of in-person and/or computerized CBT for SUD. The first trial included 137 individuals (75 % male; 65.7 % non-White; mean age = 35.9) with drug and/or alcohol use disorders randomized to one of the following: in-person CBT, computer-delivered CBT (CBT4CBT) plus brief monitoring, or treatment-as-usual (TAU). The second trial included 68 individuals (65 % male; 66.2 % non-white; mean age = 42.7) with an alcohol use disorder randomized to one of the following: CBT4CBT plus brief monitoring, CBT4CBT plus TAU, or TAU only. Coping was assessed with the Coping Strategies Scale. Latent growth curve mediational models were conducted, with both short-term (baseline through end-of-treatment) and long-term (baseline through 3-month post-treatment follow-up) changes in coping. RESULTS: There were no mediation effects for short-term changes in coping. However, in both trials, there were significant mediation effects for long-term changes in coping: In trial 1, the effect of CBT4CBT vs. TAU on substance use at the 6-month follow-up was mediated by long-term increases in coping. This same mediation effect was not found for in-person CBT vs. TAU. In trial 2, the effect of CBT4CBT vs. not receiving CBT4CBT on heavy drinking at the 6-month follow-up was mediated by long-term increases in coping. CONCLUSIONS: Long-term increases in coping may be a mechanism of change in computerized CBT for SUD.

Treatment and management of cognitive dysfunction in patients with multiple sclerosis.

Cognitive impairment is a common and devastating manifestation of multiple sclerosis (MS). Although disease-modifying therapies have been efficacious for reducing relapse rates in MS, such treatments are ineffective for treating cognitive dysfunction. Alternative treatment approaches for mitigating cognitive problems are greatly needed in this population. To date, cognitive rehabilitation and exercise training have been identified as possible candidates for treating MS-related cognitive impairment; however, cognitive dysfunction is still often considered to be poorly managed in patients with MS. This Review provides a comprehensive overview of recent developments in the treatment and management of cognitive impairment in people with MS. We describe the theoretical rationales, current states of the science, field-wide challenges and recent advances in cognitive rehabilitation and exercise training for treating MS-related cognitive impairment. We also discuss future directions for research into the treatment of cognitive impairment in MS that should set the stage for the inclusion of cognitive rehabilitation and exercise training into clinical practice within the next decade.

Descriptive Norms but not Harm Reduction Strategies as a Mediator of Personalized Boosters After a Computerized College Drinking Intervention.

BACKGROUND: Computer-delivered programs to reduce college drinking have strong appeal but are sometimes less efficacious than their in-person counterparts. Boosters may be an ideal way to strengthen and extend the effects of computerized interventions while maintaining low cost and easy dissemination. However, little is known about how they work. Consequently, the current study aimed to explore descriptive perceived drinking norms and use of protective behavioral strategies (PBS) as potential mediators of booster effects. We also examined norms and PBS as mediators of the main intervention. The present study was a follow-up analysis of data from a randomized controlled trial (Alcohol Clin Exp Res 42, 2018, 1735) testing the efficacy of emailed boosters containing personalized feedback after a computerized alcohol intervention. METHODS: Participants were 537 (67.4% women) emerging adult college drinkers (M age = 19.65, SD = 1.67). They were randomly assigned to one of 3 conditions: general health education, alcohol intervention only, or alcohol intervention plus booster email. Participants completed assessments at baseline and follow-ups through 9 months. RESULTS: Descriptive norms were a mediator of booster efficacy where receiving the booster yielded stronger reductions in alcohol use through reduced concurrent norms; however, fully longitudinal models did not reach significance. There was also an indirect effect for the intervention where those who received the intervention experienced an increase in drinking through increased concurrent norms. However, a stronger direct effect was found where those who received the intervention experienced a stronger decrease in drinking after controlling for norms. There was no support for PBS as a mediator of booster or intervention efficacy. CONCLUSIONS: The present study was the first, to our knowledge, to demonstrate a potential mechanism of change in booster interventions. A simple, succinct reminder via email led to reductions in perceptions of how much peers drink, and this led to reductions in alcohol consumption. Our findings support the promise of utilizing brief and easily implemented targeted messaging to enhance the potency of computerized interventions for college drinkers.

Trends in and factors associated with the adoption of digital aids for smoking cessation and alcohol reduction: A population survey in England.

BACKGROUND: Digital smoking cessation and alcohol reduction aids are widely available in England. To estimate their public health impact, researchers need to consider their adoption in the target population. We assessed adoption rates, and characteristics of adopters, of digital smoking cessation and alcohol reduction aids in England. METHODS: 3655 smokers and 2998 high-risk drinkers (defined as a score of >4 on the Alcohol Use Disorders Identification Test-Consumption; AUDIT-C) who had made a past-year quit/reduction attempt were surveyed as part of the Smoking and Alcohol Toolkit Studies between January 2015-October 2018. Respondents provided information on socio-demographic characteristics and whether they had used a digital aid in a recent quit/reduction attempt. RESULTS: 2.7 % (95 % CI 2.2%-3.0%) of smokers and 3.6 % (95 % CI 2.9%-4.0%) of drinkers who had made a past-year quit/reduction attempt (26.9 % and 15.3 %, respectively) had used a digital aid. Survey year was not significantly associated with use in smokers or drinkers. None of the baseline characteristics were significantly associated with the use of a digital aid in smokers. Drinkers with high motivation to reduce alcohol consumption (ORadj = 2.49, 95 % CI 1.63-3.77, p < .001) and higher AUDIT scores (ORadj = 1.07, 95 % CI 1.03-1.11, p < .001) had greater odds of adoption. CONCLUSIONS: Digital smoking cessation and alcohol reduction aids are rarely used by smokers or high-risk drinkers attempting to quit/cut down in England, indicating that most of the target population is not being reached. Despite overall digital access improving, adoption rates remained similarly low between 2015-2018.

Facilitating the Delivery of Cognitive Remediation in First-Episode Psychosis: Pilot Study of a Home-Delivered Web-Based Intervention.

We explored the adherence to a home-delivered, computer-based, cognitive remediation protocol in a first-episode psychosis outpatient cohort. Seventeen patients underwent a cognitive training protocol for 6 months using an online platform accessible from their home under the supervision of a qualified neuropsychologist. Neuropsychological, psychopathological, and functional data were collected at baseline and postintervention, whereas qualitative appraisal of the intervention was assessed monthly. Overall, participants' evaluation of the program was positive. This was reflected in a good adherence rate with 12 (70%) of 17 patients completing 80% of the prescribed sessions. Exploratory analysis revealed significant improvements in sustained attention (p = 0.020) and verbal memory (p = 0.018). A decrease in negative symptoms and an improvement on the Clinical Global Impression were also found (p = 0.009). We believe these are encouraging results to further explore the adopted delivery approach, which could facilitate access to cognitive training earlier and to a larger group of patients.

Pilot Test of a Computer-Based System to Help Family Caregivers of Dementia Patients.

BACKGROUND: Family members absorb much of the care of dementia patients. The burden of care substantially impacts caregivers' health, further straining our healthcare system. By 2050, the incidence of Alzheimer's disease will more than double, increasing the numbers of family caregivers proportionally. Interventions that reduce their burden are needed to preserve their health as well as the viability of the healthcare system. OBJECTIVE: This paper reports on the development and feasibility testing of a computer-based system intended to improve the lives of caregivers. D-CHESS (Dementia-Comprehensive Health Enhancement Support System) allows users to obtain information, communicate with other caregivers, get help with care decisions, and share information with experts. METHOD: Thirty-one caregivers were randomly assigned to an intervention group receiving D-CHESS for 6 months or to a control group receiving a caregiving book. Surveys at 0, 2, 4, and 6 months evaluated caregiver burden, family conflict, satisfaction with decisions, social support, loneliness, anxiety, depression, and coping competence. RESULTS: Survey findings suggest D-CHESS participants may perform better on measures of social support, anxiety, loneliness, and coping competence; the groups were equivalent on caregiver burden, decision satisfaction, and depression, and the control group reported less family conflict than the intervention. D-CHESS use data suggested enhancements to system design and content to increase awareness and use of various features. CONCLUSION: This study suggests that D-CHESS has potential to positively impact family caregivers and that the system merits further development and investigation with a full-scale clinical trial.

Predictors of overall and mental health-related internet use in adults with psychosis.

As digital interventions are beginning to be developed to support self-management of psychosis, it is important to understand how illness-related and individual factors may affect internet use and engagement with digital mental health resources among people with psychotic disorders. This study aimed to identify demographic, clinical, and personal variables associated with overall and mental health-related internet use in a sample of 189 adult community mental health service users with nonaffective and affective psychotic disorders. Among participants who regularly used the internet (87.3%), most (67.9%) reported using the internet for mental health information. Higher frequency of overall internet use was predicted by younger age, completion of post-secondary education, and less severe negative symptoms. Internet use for mental health information was predicted by younger age, higher levels of overall internet use, current productive employment, and higher loneliness. This study is the first to quantitatively examine how clinical and personal measures relate to overall and mental health-related internet use in people with psychosis. Although cognitive difficulties and negative symptoms impacted overall internet use, these disorder-related difficulties did not further impact internet use for mental health information. Digital mental health resources should be designed to optimise engagement for this population.

Preliminary evidence that computerized approach avoidance training is not associated with changes in fMRI cannabis cue reactivity in non-treatment-seeking adolescent cannabis users.

BACKGROUND: Cognitive Bias Modification (CBM) has garnered interest as a potential addiction treatment. CBM interventions such as Approach Avoidance Training (AAT) are designed to alter automatic tendencies to approach drugs or drug-related cues. In our previous work, the cannabis AAT (CAAT) reduced cannabis approach bias, which was related to reduced cannabis use, among 80 non-treatment-seeking cannabis-using youth (Jacobus et al., 2018). In this preliminary examination, a subsample of these youth underwent neuroimaging to explore CAAT's effect on cannabis cue-related neural activation. METHODS: Sub-study participants were 41 cannabis-using youth ages 17-21 (mean age = 18.83; 47.5% female). Participants completed a cannabis cue-reactivity task during a functional MRI scan pre- and post CAAT-training or CAAT-sham to examine CAAT-related neural changes. RESULTS: Thirty-seven youth completed all six CAAT (n = 19) or CAAT-sham (n = 18) training sessions and had usable neuroimaging data. The group*time interaction on cannabis approach bias reached trend-level significance (p = .055). Change in approach bias slopes from pre-to post-treatment was positive for CAAT-sham (increased approach bias) and negative for CAAT-training (change to avoidance bias), consistent with the larger study. No significant changes emerged for cannabis cue-induced activation following CAAT-training or CAAT-sham in whole brain or region of interest analyses. However, active CAAT-training was associated with small-to-medium decreases in amygdala (Cohen's dz = 0.36) and medial prefrontal cortex (Cohen's dz = 0.48) activation to cannabis cues. CONCLUSIONS: Despite reducing cannabis use in the larger sample, CAAT-training did not alter neural cannabis cue-reactivity in the sub-study compared to CAAT-sham. More research is needed to understand neural mechanisms underlying AAT-related changes in substance use.

Moderators of the efficacy of a web-based stress management intervention for college students.

High levels of stress are common among college students. Web-based interventions may be one way to teach students stress management skills. Although previous research has demonstrated the overall efficacy of web-based stress management interventions, little attention has been paid to who might benefit most from these interventions. In this study, we analyzed data from 3 prior studies (N = 782) to examine moderators of the efficacy of a web-based stress management intervention that focused on increasing perceived present control (i.e., aspects of stressors that are controllable in the present). Specific moderators assessed in regression analyses were baseline scores on outcome measures (perceived stress, stress symptoms, anxiety, depression) and the putative mechanism (perceived present control) of the intervention. Baseline symptom levels moderated the effects of the intervention on all outcomes, such that the intervention was more effective for students with more baseline symptoms. Baseline levels of present control had less consistent moderating effects, but significant interactions indicated that the intervention was more effective for those with lower levels of present control. The novel Johnson-Neyman technique was used to identify specific cutoff scores on these measures, below which the effect of the intervention was not significant, and scores on the measures associated with varying effect sizes. Findings from the Johnson-Neyman analyses can inform the development of screening criteria for future research and clinical application. Because the intervention was more effective for students with higher levels of baseline distress, it may be better suited for an indicated rather than universal prevention approach. (PsycINFO Database Record (c) 2019 APA, all rights reserved).

Recruitment of Older Veterans with Diabetes Risk for Alzheimer's Disease for a Randomized Clinical Trial of Computerized Cognitive Training.

BACKGROUND: Type 2 diabetes mellitus (T2DM) is prevalent in the general United States population, and in the veteran population. T2DM has consistently been linked to increased risk for cognitive impairment, dementia, and Alzheimer's disease. Computerized cognitive training (CCT) is practical and inexpensive cognitive interventions that is an alternative to medication. OBJECTIVE: To report the recruitment methods and challenges to date in an ongoing two-site randomized controlled trial (RCT) of CCT on cognitive function and T2DM management in an older non-demented veteran population. METHODS: Veterans are recruited primarily by targeted mailings or by direct contact at clinics and presentations. RESULTS: From 1,459 original contacts, 437 expressed initial interest, 111 provided informed consent, and 97 completed baseline assessments. Participants from the two VA Medical Centers differed in demographics and baseline characteristics. Comparing recruitment methods, the proportion of individuals contacted who were ultimately consented was significantly less from mailings (5%) than other sources (20%), primarily face- to-face clinic visits (χ2 (1) = 38.331, p < 0.001). CONCLUSIONS: Mailings are cost-effective, but direct contact improved recruitment. Not using or lacking access to computers and ineligibility were major reasons for non-participation. Within-site comparisons of demographically diverse sites can address confounding of demographic and other site differences.