Perforating lichen nitidus in the setting of atopic dermatitis.

Perforating lichen nitidus is a rare subtype of lichen nitidus, with approximately 11 cases reported worldwide. Lesions typically present in young male patients at sites prone to mechanical irritation, including the hands, feet, forearms, elbows, and knees. Classic histopathologic features of perforating lichen nitidus show a lymphohistiocytic infiltrate within the papillary dermis between hyperplastic rete ridges with transepidermal elimination of dermal contents. Very few cases are reported in the literature of lichen nitidus and its association with atopic dermatitis. This is the first case describing perforating lichen nitidus in a patient with a history of atopic dermatitis being treated with dupilumab injections. Lesions of perforating lichen nitidus worsened with successful treatment of atopic dermatitis. These findings suggest a unique pathophysiology of perforating lichen nitidus lesions.

Using Machine Learning of Online Expression to Explain Recovery Trajectories: Content Analytic Approach to Studying a Substance Use Disorder Forum.

BACKGROUND: Smartphone-based apps are increasingly used to prevent relapse among those with substance use disorders (SUDs). These systems collect a wealth of data from participants, including the content of messages exchanged in peer-to-peer support forums. How individuals self-disclose and exchange social support in these forums may provide insight into their recovery course, but a manual review of a large corpus of text by human coders is inefficient. OBJECTIVE: The study sought to evaluate the feasibility of applying supervised machine learning (ML) to perform large-scale content analysis of an online peer-to-peer discussion forum. Machine-coded data were also used to understand how communication styles relate to writers' substance use and well-being outcomes. METHODS: Data were collected from a smartphone app that connects patients with SUDs to online peer support via a discussion forum. Overall, 268 adult patients with SUD diagnoses were recruited from 3 federally qualified health centers in the United States beginning in 2014. Two waves of survey data were collected to measure demographic characteristics and study outcomes: at baseline (before accessing the app) and after 6 months of using the app. Messages were downloaded from the peer-to-peer forum and subjected to manual content analysis. These data were used to train supervised ML algorithms using features extracted from the Linguistic Inquiry and Word Count (LIWC) system to automatically identify the types of expression relevant to peer-to-peer support. Regression analyses examined how each expression type was associated with recovery outcomes. RESULTS: Our manual content analysis identified 7 expression types relevant to the recovery process (emotional support, informational support, negative affect, change talk, insightful disclosure, gratitude, and universality disclosure). Over 6 months of app use, 86.2% (231/268) of participants posted on the app's support forum. Of these participants, 93.5% (216/231) posted at least 1 message in the content categories of interest, generating 10,503 messages. Supervised ML algorithms were trained on the hand-coded data, achieving F1-scores ranging from 0.57 to 0.85. Regression analyses revealed that a greater proportion of the messages giving emotional support to peers was related to reduced substance use. For self-disclosure, a greater proportion of the messages expressing universality was related to improved quality of life, whereas a greater proportion of the negative affect expressions was negatively related to quality of life and mood. CONCLUSIONS: This study highlights a method of natural language processing with potential to provide real-time insights into peer-to-peer communication dynamics. First, we found that our ML approach allowed for large-scale content coding while retaining moderate-to-high levels of accuracy. Second, individuals' expression styles were associated with recovery outcomes. The expression types of emotional support, universality disclosure, and negative affect were significantly related to recovery outcomes, and attending to these dynamics may be important for appropriate intervention.

Effect of an eHealth intervention on older adults' quality of life and health-related outcomes: a randomized clinical trial.

BACKGROUND: By 2030, the number of US adults age ≥65 will exceed 70 million. Their quality of life has been declared a national priority by the US government. OBJECTIVE: Assess effects of an eHealth intervention for older adults on quality of life, independence, and related outcomes. DESIGN: Multi-site, 2-arm (1:1), non-blinded randomized clinical trial. Recruitment November 2013 to May 2015; data collection through November 2016. SETTING: Three Wisconsin communities (urban, suburban, and rural). PARTICIPANTS: Purposive community-based sample, 390 adults age ≥65 with health challenges. EXCLUSIONS: long-term care, inability to get out of bed/chair unassisted. INTERVENTION: Access (vs. no access) to interactive website (ElderTree) designed to improve quality of life, social connection, and independence. MEASURES: Primary outcome: quality of life (PROMIS Global Health). Secondary: independence (Instrumental Activities of Daily Living); social support (MOS Social Support); depression (Patient Health Questionnaire-8); falls prevention (Falls Behavioral Scale). Moderation: healthcare use (Medical Services Utilization). Both groups completed all measures at baseline, 6, and 12 months. RESULTS: Three hundred ten participants (79%) completed the 12-month survey. There were no main effects of ElderTree over time. Moderation analyses indicated that among participants with high primary care use, ElderTree (vs. control) led to better trajectories for mental quality of life (OR=0.32, 95% CI 0.10-0.54, P=0.005), social support received (OR=0.17, 95% CI 0.05-0.29, P=0.007), social support provided (OR=0.29, 95% CI 0.13-0.45, P<0.001), and depression (OR= -0.20, 95% CI -0.39 to -0.01, P=0.034). Supplemental analyses suggested ElderTree may be more effective among people with multiple (vs. 0 or 1) chronic conditions. LIMITATIONS: Once randomized, participants were not blind to the condition; self-reports may be subject to memory bias. CONCLUSION: Interventions like ET may help improve quality of life and socio-emotional outcomes among older adults with more illness burden. Our next study focuses on this population. TRIAL REGISTRATION: ClinicalTrials.gov ; registration ID number: NCT02128789.

Behavioral healthcare organizations' experiences related to use of telehealth as a result of the COVID-19 pandemic: an exploratory study.

BACKGROUND: Due to the COVID-19 pandemic, healthcare providers were forced to shift many services quickly from in-person to virtual, including substance use disorder (SUD) and mental health (MH) treatment services. This led to a sharp increase in telehealth services, with health systems seeing patients virtually at hundreds of times the rate as before the onset of the COVID-19 pandemic. By analyzing qualitative data about SUD and MH care organizations' experiences using telehealth, this study aims to elucidate emergent themes related to telehealth use by the front-line behavioral health workforce. METHODS: This study uses qualitative data from large-scale web surveys distributed to SUD and MH organizations between May and August 2020. At the end of these surveys, the following question was posed in free-response form: "Is there anything else you would like to say about use of telehealth during or after the COVID-19 pandemic?" Respondents were asked to answer on behalf of their organizations. The 391 responses to this question were analyzed for emergent themes using a conventional approach to content analysis. RESULTS: Three major themes emerged: COVID-specific experiences with telehealth, general experiences with telehealth, and recommendations to continue telehealth delivery. Convenience, access to new populations, and lack of commute were frequently cited advantages of telehealth, while perceived ineffectiveness of and limited access to technology were frequently cited disadvantages. Also commonly mentioned was the relaxation of reimbursement regulations. Respondents supported continuation of relaxed regulations, increased institutional support, and using a combination of telehealth and in-person care in their practices. CONCLUSIONS: This study advanced our knowledge of how the behavioral health workforce experiences telehealth delivery. Further longitudinal research comparing treatment outcomes of those receiving in-person and virtual services will be necessary to undergird organizations' financial support, and perhaps also legislative support, for virtual SUD and MH services.

Intraindividual, Dyadic, and Network Communication in a Digital Health Intervention: Distinguishing Message Exposure from Message Production.

Communicating within digital health interventions involves a range of behaviors that may contribute to the management of chronic illnesses in different ways. This study examines whether communication within a smartphone-based application for addiction recovery produces distinct effects depending on 1) the "level" of communication, defined as intraindividual communication (e.g., journal entries to oneself); dyadic communication (e.g., private messaging to other individuals); or network communication (e.g., discussion forum posts to all group members), and 2) whether individuals produce or are exposed to messages. We operationalize these communication levels and behaviors based on system use logs as the number of clicks dedicated to each activity and assess how each category of system use relates to changes in group bonding and substance use after 6 months with the mobile intervention. Our findings show that (1) intraindividual exposure to one's own past posts marginally predicts decreased drug use; (2) dyadic production predicts greater perceived bonding; while dyadic exposure marginally predicts reduced drug use; (3) network production predicts decreased risky drinking. Implications for digital health interventions are discussed.

Potential Influences of the COVID-19 Pandemic on Drug Use and HIV Care Among People Living with HIV and Substance Use Disorders: Experience from a Pilot mHealth Intervention.

People living with HIV (PLWH) and substance use disorder (SUD) are particularly vulnerable to harmful health consequences of the global COVID-19 pandemic. The health and social consequences of the pandemic may exacerbate substance misuse and poor management of HIV among this population. This study compares substance use and HIV care before and during the pandemic using data collected weekly through an opioid relapse prevention and HIV management mobile-health intervention. We found that during the pandemic, PLWH and SUD have increased illicit substance use and contact with other substance-using individuals and decreased their confidence to stay sober and attend recovery meetings. The proportion of people missing their HIV medications also increased, and confidence to attend HIV follow-up appointments decreased. Optimal support for PLWH and SUD is critical during pandemics like COVID-19, as drug-related and HIV antiretroviral therapy (ART) non-adherence risks such as overdose, unsafe sexual behaviors, and transmission of infectious diseases may unfold.

RESUMEN: Personas con VIH y con trastornos por abuso de sustancias son más vulnerable a las consecuencias de la pandemia: COVID-19. Dentro estas poblaciones, las consecuencias sociales y de la salud, causadas por la pandemia, pueden exacerbar el mal uso de las sustancias, y la adherencia a los antiretrovirales. Este estudio compara el abuso de sustancias y el cuidado del VIH, antes y durante la pandemia, usando datos colectados semanal de otro programa que también investigo la prevención entre personas que han recaído con el uso de opioides y que tienen VIH. Nuestro análisis encuentra, que durante la pandemia, incrementaron el uso de sustancias ilícitas, y contacto con otras personas que usan sustancias, y perdieron la capacidad de mantenerse sobrios, y tambien dejaron de asistir reuniones de recuperación/apoyo. También, el porcentaje de personas con VIH no siguiendo con sus planes de tratamiento de VIH, incrementó; perdieron su motivacion en mantener sus citas médicos. Es muy crítico, durante una pandemia como COVID-19, tener recursos para personas que pertenecen a estas poblaciones, si no, casos de sobredosis, sexo sin protección y la transmisión de enfermedades infecciosas van a prevaler.

Exploring the Role of Social Support in Promoting Patient Participation in Health Care among Women with Breast Cancer.

Scholars have adopted Street's (2003) ecological model of communication in medical encounters to investigate the factors promoting patient participation in health care. However, factors demonstrated in the ecological model were bounded in the context of medical care primarily focusing on health care providers and patients. Social factors, such as patients' relationships and supportive communication with others outside the context of health care remain relatively unexplored. To expand the purview of our understanding of factors that influence patient participation, this research integrated social support literature into the research on physician-patient communication and proposed a model which described a process through which social support can enhance patient participation in health care. The data analyzed in this study were a part of two larger clinical trials in which 661 women with breast cancer were recruited from three cancer institutions in the United States. The results from structural equation modeling analysis from cross-sectional and longitudinal data provided strong evidence for the hypotheses predicting that perceived social support was positively associated with health information competence, which in turn fully mediated the association between social support and patient participation in health care. Theoretical and practical implications are discussed.

Effects of Web-Based Social Connectedness on Older Adults' Depressive Symptoms: A Two-Wave Cross-Lagged Panel Study.

BACKGROUND: Depressive symptoms are the most prevalent mental health concern among older adults (possibly heightened during the COVID-19 pandemic), which raises questions about how such symptoms can be lowered in this population. Existing research shows that offline social connectedness is a protective factor against depression in older adults; however, it is unknown whether web-based social connectedness can have similar effects. OBJECTIVE: This study investigates whether social connectedness on a support website protects older adults against depressive symptoms over the course of a year, above and beyond the protective effect of offline social connectedness. The secondary aim is to determine whether older adults with increased depressive symptoms are more likely to engage in social connectedness on this website. Thus, we examine depressive symptoms as both an outcome and predictor of web-based social connectedness to fully understand the chain of causality among these variables. Finally, we compare web-based social connectedness with offline social connectedness in their ability to lower depressive symptoms among older adults. METHODS: A total of 197 adults aged 65 years or older were given access to a social support website, where they were able to communicate with each other via a discussion forum for a year. Participants' social connectedness on the web-based platform, conceptualized as message production and consumption, was measured using behavioral log data as the number of messages participants wrote and read, respectively, during the first 6 months (t1) and the following 6 months (t2) of the study. Participants self-reported their offline social connectedness as the number of people in their support networks, and they reported their depressive symptoms using the Patient Health Questionnaire-8 both at baseline (t1) and at 12-month follow-up (t2). To ascertain the flow of causality between these variables, we employed a cross-lagged panel design, in which all variables were measured at t1 and t2. RESULTS: After controlling for the effect of offline support networks at t1, web-based message consumption at t1 decreased older adults' depressive symptoms at t2 (ß=-.11; P=.02), but web-based message production at t1 did not impact t2 depressive symptoms (ß=.12; P=.34). Web-based message consumption had a larger effect (ß=-.11; P=.02) than offline support networks (ß=-.08; P=.03) in reducing older adults' depressive symptoms over time. Higher baseline depressive symptoms did not predict increased web-based message consumption (ß=.12; P=.36) or production (ß=.02; P=.43) over time. CONCLUSIONS: The more messages older adults read on the web-based forum for the first 6 months of the study, the less depressed they felt at the 1-year follow-up, above and beyond the availability of offline support networks at baseline. This pinpoints the substantial potential of web-based communication to combat depressive symptoms in this vulnerable population. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): RR2-10.1186/s13063-015-0713-2.

Understanding how e-health interventions meet psychosocial needs of breast cancer patients: The pathways of influence on quality of life and cancer concerns.

OBJECTIVE: This investigation explores how using different e-health interventions facilitates positive psychosocial changes and how these changes reduce cancer concerns and improve quality of life in breast cancer patients over time. METHODS: A total of 326 breast cancer patients were randomly assigned to one of three e-health interventions: (a) Internet only, (b) the Comprehensive Health Enhancement Support System information and support services (CHESS-IS), or (c) CHESS with mentor. Proximal health outcomes such as information overload, emotional functioning, and social support were measured alongside distal outcomes like cancer concerns and quality of life. Participants completed surveys at four time points: pretest as a baseline, 6 weeks, 3 months, and 6 months. RESULTS: Both interventions were effective in improving patient health beyond Internet only but they differed in type of change mechanism and clinical benefit. The CHESS-IS enhanced proximal outcomes at 3 months through improved information competence. The CHESS with mentor intervention reduced breast cancer concerns at 6 months, mediated mainly by emotional-social competence and emotional functioning. CONCLUSIONS: Using e-health interventions like CHESS can help patients improve cancer information management skills and emotional functioning, contributing to better short-term health outcomes. Adding a human mentor can enhance the benefits of CHESS use, extending the experience among breast cancer patients. Theoretical, practical, and clinical implications of the study results are discussed.

A Longitudinal Investigation of Empathic Exchanges in Online Cancer Support Groups: Message Reception and Expression Effects on Patients' Psychosocial Health Outcomes.

Recent studies have devoted attention to the effects of both expression and reception in communication process. However, there remain both theoretical and methodological complexities concerning whether and under what condition message expression and reception play significant but different roles in explaining various psychosocial health outcomes. Relying on theoretical insights from the social support literature and methodological innovations offered by computational social science, this study aims to examine the effects of empathic exchanges on cancer patient's short- and long-term psychosocial health outcomes. Our findings suggest that both empathy expression and reception are crucial to attaining benefits for cancer patients, each predicting differential cognitive and affective health outcomes. Further, our finding supports the stress-buffering hypothesis such that empathy reception provides a beneficial effect for patients who experienced a higher degree of depression associated with their cancer diagnosis and follow-up treatments.

Interactivity, Presence, and Targeted Patient Care: Mapping e-Health Intervention Effects Over Time for Cancer Patients with Depression.

This study examined the interplay of depression and different types of e-health interventions on breast cancer patients' perceived healthcare competence, emotional processing, and social well-being over time. The three e-health interventions--Internet Only as a control condition, CHESS (Comprehensive Health Enhancement Support System) Only, and CHESS with a Human Mentor, a cancer information specialist--provided varying degrees of interactivity and presence. A total of 328 women with breast cancer participated in one of the three interventions for a 6-month period. Women were further split into two groups based on reported levels of depression. For perceived healthcare competence and social well-being, results revealed significant interaction effects for intervention type by depression over time, such that breast cancer patients with higher levels of depression benefited most from the CHESS with Mentor intervention over the 6-month study period. For emotional processing, depressed cancer patients benefited more from the CHESS with Mentor than the other two interventions, regardless of time. These findings have (a) theoretical implications on how mental health factors can intersect with interactivity and presence to influence psychosocial outcomes, (b) conceptual implications for the role of human interaction within e-health systems, and (c) practical implications for the development of e-health interventions for cancer patients with depression.

An Outcome Study of the CASA-CHESS Smartphone Relapse Prevention Tool for Latinx Spanish-Speakers with Substance Use Disorders.

Background: Hispanic/Latinx persons with alcohol and other drug disorders (AOD) have limited access to culturally competent continuity of care. To address this, the evidence-based smartphone recovery application Addiction-Comprehensive Health Enhancement Support System (A-CHESS) was translated and adapted for Latinx Spanish-speakers with AOD, developing CASA-CHESS. Objectives: This study examined the AOD and mental health outcomes for Latinx Spanish-speaking clients using the CASA-CHESS smartphone tool over a 6-month period, post-residential treatment. This single group, pre-post study design included seventy-nine male and female Spanish-speaking Latinx clients, equipped with CASA-CHESS as they completed residential AOD treatment. Primary outcome measures at baseline and 6-month follow-up included substance use and other mental health symptoms. Results: While over 70% of the sample reported past heroin use and alcohol use, clients had low baseline rates of substance use, depression and anxiety and elevated social support scores as they graduated from residential treatment. Overall participants maintained their relatively low baseline rates during the 6-month post-residential period while using the CASA-CHESS relapse prevention tool. Those who discontinued using CASA-CHESS within the first 4 months after leaving residential treatment reported higher rates of substance use as well as anxiety and depression symptoms than those using it for 4 or more months, suggesting that continued use of CASA-CHESS may contribute to maintenance of successes gained in treatment. Conclusions/Importance: CASA-CHESS may reduce the risk of relapse for Latinx Spanish-speakers following residential services and extend needed access to culturally and linguistically competent aftercare services for those with AOD.

What Do You Say Before You Relapse? How Language Use in a Peer-to-peer Online Discussion Forum Predicts Risky Drinking among Those in Recovery.

Increasingly, individuals with alcohol use disorder (AUD) seek and provide support for relapse prevention in text-based online environments such as discussion forums. This paper investigates whether language use within a peer-to-peer discussion forum can predict future relapse among individuals treated for AUD. A total of 104 AUD sufferers who had completed residential treatment participated in a mobile phone-based relapse-prevention program, where they communicated via an online forum over the course of a year. We extracted patterns of language use on the forum within the first four months on study using Linguistic Inquiry and Word Count (LIWC), a dictionary-based text analysis program. Participants reported their incidence of risky drinking via a survey at 4, 8, and 12 months. A logistic regression model was built to predict the likelihood that individuals would engage in risky drinking within a year based on their language use, while controlling for baseline characteristics and rates of utilizing the mobile system. Results show that all baseline characteristics and system use factors explained just 13% of the variance in relapse, whereas a small number of linguistic cues, including swearing and cognitive mechanism words, accounted for an additional 32% of the total 45% of variance in relapse explained by the model. Effective models for predicting relapse are needed. Messages exchanged on AUD forums could provide an unobtrusive and cost-effective window into the future health outcomes of AUD sufferers, and their psychological underpinnings. As online communication expands, models that leverage user-submitted text toward predicting relapse will be increasingly scalable and actionable.

Detecting Recovery Problems Just in Time: Application of Automated Linguistic Analysis and Supervised Machine Learning to an Online Substance Abuse Forum.

BACKGROUND: Online discussion forums allow those in addiction recovery to seek help through text-based messages, including when facing triggers to drink or use drugs. Trained staff (or "moderators") may participate within these forums to offer guidance and support when participants are struggling but must expend considerable effort to continually review new content. Demands on moderators limit the scalability of evidence-based digital health interventions. OBJECTIVE: Automated identification of recovery problems could allow moderators to engage in more timely and efficient ways with participants who are struggling. This paper aimed to investigate whether computational linguistics and supervised machine learning can be applied to successfully flag, in real time, those discussion forum messages that moderators find most concerning. METHODS: Training data came from a trial of a mobile phone-based health intervention for individuals in recovery from alcohol use disorder, with human coders labeling discussion forum messages according to whether or not authors mentioned problems in their recovery process. Linguistic features of these messages were extracted via several computational techniques: (1) a Bag-of-Words approach, (2) the dictionary-based Linguistic Inquiry and Word Count program, and (3) a hybrid approach combining the most important features from both Bag-of-Words and Linguistic Inquiry and Word Count. These features were applied within binary classifiers leveraging several methods of supervised machine learning: support vector machines, decision trees, and boosted decision trees. Classifiers were evaluated in data from a later deployment of the recovery support intervention. RESULTS: To distinguish recovery problem disclosures, the Bag-of-Words approach relied on domain-specific language, including words explicitly linked to substance use and mental health ("drink," "relapse," "depression," and so on), whereas the Linguistic Inquiry and Word Count approach relied on language characteristics such as tone, affect, insight, and presence of quantifiers and time references, as well as pronouns. A boosted decision tree classifier, utilizing features from both Bag-of-Words and Linguistic Inquiry and Word Count performed best in identifying problems disclosed within the discussion forum, achieving 88% sensitivity and 82% specificity in a separate cohort of patients in recovery. CONCLUSIONS: Differences in language use can distinguish messages disclosing recovery problems from other message types. Incorporating machine learning models based on language use allows real-time flagging of concerning content such that trained staff may engage more efficiently and focus their attention on time-sensitive issues.

Implementing a Mobile Health System to Integrate the Treatment of Addiction Into Primary Care: A Hybrid Implementation-Effectiveness Study.

BACKGROUND: Despite the near ubiquity of mobile phones, little research has been conducted on the implementation of mobile health (mHealth) apps to treat patients in primary care. Although primary care clinicians routinely treat chronic conditions such as asthma and diabetes, they rarely treat addiction, a common chronic condition. Instead, addiction is most often treated in the US health care system, if it is treated at all, in a separate behavioral health system. mHealth could help integrate addiction treatment in primary care. OBJECTIVE: The objective of this paper was to report the effects of implementing an mHealth system for addiction in primary care on both patients and clinicians. METHODS: In this implementation research trial, an evidence-based mHealth system named Seva was introduced sequentially over 36 months to a maximum of 100 patients with substance use disorders (SUDs) in each of three federally qualified health centers (FQHCs; primary care clinics that serve patients regardless of their ability to pay). This paper reports on patient and clinician outcomes organized according to the Reach, Effectiveness, Adoption, Implementation, and Maintenance (RE-AIM) framework. RESULTS: The outcomes according to the RE-AIM framework are as follows: Reach-Seva reached 8.31% (268/3226) of appropriate patients. Reach was limited by our ability to pay for phones and data plans for a maximum of 100 patients per clinic. Effectiveness-Patients who were given Seva had significant improvements in their risky drinking days (44% reduction, (0.7-1.25)/1.25, P=.04), illicit drug-use days (34% reduction, (2.14-3.22)/3.22, P=.01), quality of life, human immunodeficiency virus screening rates, and number of hospitalizations. Through Seva, patients also provided peer support to one another in ways that are novel in primary care settings. Adoption-Patients sustained high levels of Seva use-between 53% and 60% of the patients at the 3 sites accessed Seva during the last week of the 12-month implementation period. Among clinicians, use of the technology was less robust than use by patients, with only a handful of clinicians using Seva in each clinic and behavioral health providers making most referrals to Seva in 2 of the 3 clinics. Implementation-At 2 sites, implementation plans were realized successfully; they were delayed in the third. Maintenance-Use of Seva dropped when grant funding stopped paying for the mobile phones and data plans. Two of the 3 clinics wanted to maintain the use of Seva, but they struggled to find funding to support this. CONCLUSIONS: Implementing an mHealth system can improve care among primary care patients with SUDs, and patients using the system can support one another in their recovery. Among clinicians, however, implementation requires figuring out how information from the mHealth system will be used and making mHealth data available in the electronic health (eHealth) record. In addition, paying for an mHealth system remains a challenge.

How Cancer Patients Use and Benefit from an Interactive Cancer Communication System.

Despite the mounting evidence of efficacy of eHealth interventions, their mechanisms of action remain unknown. The current study analyzed patient log data as each patient engaged in an eHealth system called the Comprehensive Health Enhancement Support System (CHESS) and reports on how patients engage with different combinations of eHealth services over time. Newly diagnosed breast cancer patients (N = 443) were given access for 6 months to one of four different configurations of CHESS: (1) Information, (2) Information and Support, (3) Information, Support, and Coaching (Full CHESS), and (4) Full CHESS and Mentor. Besides a baseline survey, three follow-up posttests were administered. Action log data on how patients engaged with the CHESS were also collected and merged with surveys to examine how patients benefit during the cancer experience. The findings suggest that usage patterns were not competitive, implying that cancer patients' access to more complex tools generates more use with their time spreading out over the diverse services. Despite overall decline in usage rates, it was less severe in Full CHESS and Mentor condition, suggesting that communication functions drive long-term engagement with the system. Notably, the strongest relation between use and cancer information competence appeared late in the follow-up period.

Offline Social Relationships and Online Cancer Communication: Effects of Social and Family Support on Online Social Network Building.

This study investigates how social support and family relationship perceptions influence breast cancer patients' online communication networks in a computer-mediated social support (CMSS) group. To examine social interactions in the CMSS group, we identified two types of online social networks: open and targeted communication networks. The open communication network reflects group communication behaviors (i.e., one-to-many or "broadcast" communication) in which the intended audience is not specified; in contrast, the targeted communication network reflects interpersonal discourses (i.e., one-to-one or directed communication) in which the audience for the message is specified. The communication networks were constructed by tracking CMSS group usage data of 237 breast cancer patients who participated in one of two National Cancer Institute-funded randomized clinical trials. Eligible subjects were within 2 months of a diagnosis of primary breast cancer or recurrence at the time of recruitment. Findings reveal that breast cancer patients who perceived less availability of offline social support had a larger social network size in the open communication network. In contrast, those who perceived less family cohesion had a larger targeted communication network in the CMSS group, meaning they were inclined to use the CMSS group for developing interpersonal relationships.

Reducing Symptom Distress in Patients With Advanced Cancer Using an e-Alert System for Caregivers: Pooled Analysis of Two Randomized Clinical Trials.

BACKGROUND: Symptom distress in patients toward the end of life can change rapidly. Family caregivers have the potential to help patients manage those symptoms, as well as their own stress, if they are equipped with the proper resources. Electronic health (eHealth) systems may be able to provide those resources. Very sick patients may not be able to use such systems themselves to report their symptoms but family caregivers could. OBJECTIVE: The aim of this paper was to assess the effects on cancer patient symptom distress of an eHealth system that alerts clinicians to significant changes in the patient's symptoms, as reported by a family caregiver. METHODS: A pooled analysis from two randomized clinical trials (NCT00214162 and NCT00365963) compared outcomes at 12 months for two unblinded groups: a control group (Comprehensive Health Enhancement Support System [CHESS]-Only) that gave caregivers access to CHESS, an online support system, and an experimental group (CHESS+CR [Clinician Report]), which also had CHESS but with a CR that automatically alerted clinicians if symptoms exceeded a predetermined threshold of severity. Participants were dyads (n=235) of patients with advanced lung, breast, or prostate cancer and their respective family caregivers from 5 oncology clinics in the United States of America. The proportion of improved patient threshold symptoms was compared between groups using area-under-the-curve analysis and binomial proportion tests. The proportion of threshold symptoms out of all reported symptoms was also examined. RESULTS: When severe caregiver-reported symptoms were shared with clinicians, the symptoms were more likely to be subsequently reported as improved than when the symptoms were not shared with clinicians (P<.001). Fewer symptom reports were completed in the group of caregivers whose reports went to clinicians than in the CHESS-Only group (P<.001), perhaps because caregivers, knowing their reports might be sent to a doctor, feared they might be bothering the clinician. CONCLUSIONS: This study suggests that an eHealth system designed for caregivers that alerts clinicians to worrisome changes in patient health status may lead to reduced patient distress. TRIAL REGISTRATION: Clinicaltrials.gov NCT00214162; https://clinicaltrials.gov/ct2/show/NCT00214162 (Archived by WebCite at http://www.webcitation.org/6nmgdGfuD) and Clinicaltrials.gov NCT00365963; https://clinicaltrials.gov/ct2/show/NCT00365963 (Archived by WebCite at http://www.webcitation.org/6nmh0U8VP).

Use of a Smartphone Recovery Tool for Latinos with Co-Occurring Alcohol and Other Drug Disorders and Mental Disorders.

OBJECTIVE: Addressing alcohol and other drug disorders and other mental disorders among adult Hispanics/Latinos is of critical concern, as they are one of the fastest-growing ethnic groups with a disproportionate rate of disease, mental disorders, and poverty. Although improvement in outcomes is associated with sustained participation in ongoing treatment for co-occurring alcohol and other drug disorders/mental disorders, continuing care is rare for these chronic conditions, especially for Latinos with more limited access to culturally and linguistically competent services. METHODS: The evidence-based smartphone recovery application Addiction-Comprehensive Health Enhancement Support System (A-CHESS) was translated and adapted for Spanish-speaking Latinos with alcohol and other drug disorders/mental disorders, thus developing CASA-CHESS to address a high level of need for services, high rates of relapse, and lack of existing culturally competent services for Latinos. RESULTS: Of the 79 Latino clients who completed residential treatment and received a smartphone equipped with CASA-CHESS, 26.6% discontinued using CASA-CHESS and 73.4% remained active for four or more months. CASA-CHESS usage was sustained over the four months across all three tenets of self-determination theory (competence, relatedness, and autonomy), with the most commonly utilized services being relevant to relatedness (e.g., messaging, discussion boards). CASA-CHESS clients demonstrated a similar pattern of usage to A-CHESS clients. CONCLUSIONS: Findings illustrate that Spanish-speaking Latinos with alcohol and other drug disorders/mental disorders will use a smartphone application to assist with their recovery, continuing their access to resources, case management, and quality information after leaving residential treatment. Consistent with previous findings, our results also emphasize the importance of social support during the four months post-discharge. Such evidence-based, theory-driven digital interventions may extend access to culturally and linguistically competent services.

Breast Cancer Survivors' Contribution to Psychosocial Adjustment of Newly Diagnosed Breast Cancer Patients in a Computer-Mediated Social Support Group.

This study investigated the role of breast cancer survivors in a computer-mediated social support (CMSS) group for women with breast cancer. Applying a computer-aided content analytic method, the present study examined the differences in support provision between survivors and newly diagnosed patients. This study further investigated the impacts of survivor-provided social support on psychosocial adjustment of newly diagnosed patients. The results revealed that, compared with newly diagnosed patients, breast cancer survivors provided more emotional and informational support. Receiving emotional support from survivors contributed to an improvement in the quality of life and the depression of patients. The effects of survivor-provided informational support were not significant.