Adherence Promotion With Tailored Motivational Messages: Proof of Concept and Message Preferences in Older Adults.

This study examined the feasibility of using tailored text messages to promote adherence to longitudinal protocols and determined what facets of text message tone influence motivation. Forty-three older adults (Mage = 73.21, SD = 5.37) were recruited to engage in video-game-based cognitive training for 10 consecutive days. Participants received encouraging text messages each morning that matched their highest or lowest ranking reasons for participating in the study, after which they rated how effective each message was in motivating them to play the games that day. After 10 days, participants rated all possible messages and participated in semi-structured interviews to elicit their preferences for these messages. Results showed that messages matching participants' reasons for participating were more motivating than mismatched messages. Further, participants preferred messages that were personalized (i.e., use second person voice) and in formal tones. Messages consistent with these preferences were also rated as more motivating. These findings establish the feasibility of using message tailoring to promote adherence to longitudinal protocols and the relevance of tailoring messages to be personal and formal.

Terms of Engagement: Understanding the Motivations, Preferences, and Attitudes of Older Adults Toward Mobile Cognitive Assessment and Training.

BACKGROUND AND OBJECTIVES: The future of cognitive assessment is likely to involve mobile applications for smartphones and tablets; cognitive training is also often delivered in these formats. Unfortunately, low adherence to these programs can hinder efforts at the early detection of cognitive decline and interfere with examining cognitive training efficacy in clinical trials. We explored factors that increase adherence to these programs among older adults. RESEARCH DESIGN AND METHODS: Focus groups were conducted with older adults (N = 21) and a younger adult comparison group (N = 21). Data were processed using reflexive thematic analysis with an inductive, bottom-up approach. RESULTS: Three primary themes related to adherence were developed from the focus group data. Switches of engagement reflects factors that must be present; without them, engagement is unlikely. Dials of engagement reflects a cost-benefit analysis that users undergo, the outcome of which determines whether a person will be more or less likely to engage. Bracers of engagement reflects factors that nudge users toward engagement by minimizing barriers associated with the other themes. Older adults in general were more sensitive to opportunity costs, preferred more cooperative interactions, and were more likely to mention technology barriers. DISCUSSION AND IMPLICATIONS: Our results are important for informing the design of mobile cognitive assessment and training apps for older adults. These themes provide guidance about ways apps could be modified to increase engagement and adherence, which in turn can more effectively facilitate the early detection of cognitive impairment and the evaluation of cognitive training efficacy.

Engaging Adolescent Heart Transplant Recipients Through In-App Messaging During Mobile Health Intervention.

Introduction: Adolescents heart transplant recipients experience difficulty with adherence to immunosuppressive medication leading to increased risk of organ rejection, hospitalization, and mortality. Few interventions have been successful to promote medication adherence in adolescent heart transplant patients as most fail to engage the patient in the behavioral change process and support patient-provider communication. The purpose of this study was to explore the nature and degree of in-app communication between adolescent heart transplant recipients and nursing staff during an asynchronous mobile video directly observed therapy intervention. Methods: A content analysis of 894 in-app messages exchanged between 10 adolescent patients and nurses during a 12-week mobile-based intervention was conducted. Two authors used an inductive, iterative process to guide a thematic analysis of the asynchronous in-app messages with high interrater reliability ranging from 81.5% to 100%. Findings: In-app messages fell under 3 broad content categories: (1) interpersonal support and rapport-building, (2) medically related questions and information, or (3) functional information about the intervention and the mHealth app. Results demonstrated the degree to which interpersonal engagement occurred during the intervention, the nature of these exchanges, and their relationship to medication adherence. Conclusions: The study provided insights into the feasibility and benefits of 2-way communication features of the directly observed therapy intervention in promoting engagement and in improving medication adherence among adolescent heart transplant patients. Continued research and clinical focus on patient engagement and impactful aspects of interpersonal communication could aid in the translation of this intervention into standard clinical care at pediatric transplant centers.

Annotation and Information Extraction of Consumer-Friendly Health Articles for Enhancing Laboratory Test Reporting.

Viewing laboratory test results is patients' most frequent activity when accessing patient portals, but lab results can be very confusing for patients. Previous research has explored various ways to present lab results, but few have attempted to provide tailored information support based on individual patient's medical context. In this study, we collected and annotated interpretations of textual lab result in 251 health articles about laboratory tests from AHealthyMe.com. Then we evaluated transformer-based language models including BioBERT, ClinicalBERT, RoBERTa, and PubMedBERT for recognizing key terms and their types. Using BioPortal's term search API, we mapped the annotated terms to concepts in major controlled terminologies. Results showed that PubMedBERT achieved the best F1 on both strict and lenient matching criteria. SNOMED CT had the best coverage of the terms, followed by LOINC and ICD-10-CM. This work lays the foundation for enhancing the presentation of lab results in patient portals by providing patients with contextualized interpretations of their lab results and individualized question prompts that they can, in turn, refer to during physician consults.

Deep learning-based predictions of older adults' adherence to cognitive training to support training efficacy.

As the population ages, the number of older adults experiencing mild cognitive impairment (MCI), Alzheimer's disease, and other forms of dementia will increase dramatically over the next few decades. Unfortunately, cognitive changes associated with these conditions threaten independence and quality of life. To address this, researchers have developed promising cognitive training interventions to help prevent or reverse cognitive decline and cognitive impairment. However, the promise of these interventions will not be realized unless older adults regularly engage with them over the long term, and like many health behaviors, adherence to cognitive training interventions can often be poor. To maximize training benefits, it would be useful to be able to predict when adherence lapses for each individual, so that support systems can be personalized to bolster adherence and intervention engagement at optimal time points. The current research uses data from a technology-based cognitive intervention study to recognize patterns in participants' adherence levels and predict their future adherence to the training program. We leveraged the feature learning capabilities of deep neural networks to predict patterns of adherence for a given participant, based on their past behavior. A separate, personalized model was trained for each participant to capture individualistic features of adherence. We posed the adherence prediction as a binary classification problem and exploited multivariate time series analysis using an adaptive window size for model training. Further, data augmentation techniques were used to overcome the challenge of limited training data and enhance the size of the dataset. To the best of our knowledge, this is the first research effort to use advanced machine learning techniques to predict older adults' daily adherence to cognitive training programs. Experimental evaluations corroborated the promise and potential of deep learning models for adherence prediction, which furnished highest mean F-scores of 75.5, 75.5, and 74.6% for the Convolution Neural Network (CNN), Long Short-Term Memory (LSTM) network, and CNN-LSTM models respectively.

A Machine-Learning Based Approach for Predicting Older Adults' Adherence to Technology-Based Cognitive Training.

Adequate adherence is a necessary condition for success with any intervention, including for computerized cognitive training designed to mitigate age-related cognitive decline. Tailored prompting systems offer promise for promoting adherence and facilitating intervention success. However, developing adherence support systems capable of just-in-time adaptive reminders requires understanding the factors that predict adherence, particularly an imminent adherence lapse. In this study we built machine learning models to predict participants' adherence at different levels (overall and weekly) using data collected from a previous cognitive training intervention. We then built machine learning models to predict adherence using a variety of baseline measures (demographic, attitudinal, and cognitive ability variables), as well as deep learning models to predict the next week's adherence using variables derived from training interactions in the previous week. Logistic regression models with selected baseline variables were able to predict overall adherence with moderate accuracy (AUROC: 0.71), while some recurrent neural network models were able to predict weekly adherence with high accuracy (AUROC: 0.84-0.86) based on daily interactions. Analysis of the post hoc explanation of machine learning models revealed that general self-efficacy, objective memory measures, and technology self-efficacy were most predictive of participants' overall adherence, while time of training, sessions played, and game outcomes were predictive of the next week's adherence. Machine-learning based approaches revealed that both individual difference characteristics and previous intervention interactions provide useful information for predicting adherence, and these insights can provide initial clues as to who to target with adherence support strategies and when to provide support. This information will inform the development of a technology-based, just-in-time adherence support systems.

Directly observed therapy to promote medication adherence in adolescent heart transplant recipients.

PURPOSE: HT recipients experience high levels of medication non-adherence during adolescence. This pilot study examined the acceptability and feasibility of an asynchronous DOT mHealth application among adolescent HT recipients. The app facilitates tracking of patients' dose-by-dose adherence and enables transplant team members to engage patients. The DOT application allows patients to self-record videos while taking their medication and submit for review. Transplant staff review the videos and communicate with patients to engage and encourage medication adherence. METHODS: Ten adolescent HT recipients with poor adherence were enrolled into a single-group, 12-week pilot study examining the impact of DOT on adherence. Secondary outcomes included self-report measures from patients and parents concerning HRQOL and adherence barriers. Long-term health outcomes assessed included AR and hospitalization 6 months following DOT. FINDINGS: Among 14 adolescent HT patients approached, 10 initiated the DOT intervention. Of these, 8 completed the 12-week intervention. Patients and caregivers reported high perceptions of acceptability and accessibility. Patients submitted 90.1% of possible videos demonstrating medication doses taken. MLVI values for the 10 patients initiating DOT decreased from 6 months prior to the intervention (2.86 ± 1.83) to 6 months following their involvement (2.08 ± 0.87) representing a 21.7% decrease in non-adherence, though not statistically significant given the small sample size. CONCLUSIONS: Result of this pilot study provides promising insights regarding the feasibility, acceptability, and potential impact of DOT for adolescent HT recipients. Further randomized studies are required to confirm these observations.

Motivation to Engage in Aging Research: Are There Typologies and Predictors?

BACKGROUND AND OBJECTIVES: Study recruitment and retention of older adults in research studies is a major challenge. Enhancing understanding of individual differences in motivations to participate, and predictors of motivators, can serve the dual aims of facilitating the recruitment and retention of older adults, benefiting study validity, economy, and power. RESEARCH DESIGN AND METHODS: Older adults (N = 472) past and potential participants were surveyed about motivations to participate in research, demographic, and individual difference measures (e.g., health status, cognitive difficulties). Latent class and clustering analyses explored motivation typologies, followed by regression models predicting individual motivators and typologies. RESULTS: Older adults endorsed a diversity of research motivations, some of which could be predicted by individual difference measures (e.g., older participants were more motivated by the desire to learn new technology, participants without a college education were more motivated by financial compensation, and participants with greater self-reported cognitive problems were more likely to participate to gain cognitive benefit). Clustering analysis revealed 4 motivation typologies: brain health advocates, research helpers, fun seekers, and multiple motivation enthusiasts. Cognitive difficulties, age, employment status, and previous participation predicted membership in these categories. DISCUSSION AND IMPLICATIONS: Results provide an understanding of different participant motivations beyond differences between younger and older adults and begin to identify different classes of older adults motivated to participate in research studies. Results can provide guidance for targeted recruitment and retention strategies based on individual differences in stated or predicted motivations.

An Informatics Framework to Assess Consumer Health Language Complexity Differences: Proof-of-Concept Study.

BACKGROUND: The language gap between health consumers and health professionals has been long recognized as the main hindrance to effective health information comprehension. Although providing health information access in consumer health language (CHL) is widely accepted as the solution to the problem, health consumers are found to have varying health language preferences and proficiencies. To simplify health documents for heterogeneous consumer groups, it is important to quantify how CHLs are different in terms of complexity among various consumer groups. OBJECTIVE: This study aimed to propose an informatics framework (consumer health language complexity [CHELC]) to assess the complexity differences of CHL using syntax-level, text-level, term-level, and semantic-level complexity metrics. Specifically, we identified 8 language complexity metrics validated in previous literature and combined them into a 4-faceted framework. Through a rank-based algorithm, we developed unifying scores (CHELC scores [CHELCS]) to quantify syntax-level, text-level, term-level, semantic-level, and overall CHL complexity. We applied CHELCS to compare posts of each individual on online health forums designed for (1) the general public, (2) deaf and hearing-impaired people, and (3) people with autism spectrum disorder (ASD). METHODS: We examined posts with more than 4 sentences of each user from 3 health forums to understand CHL complexity differences among these groups: 12,560 posts from 3756 users in Yahoo! Answers, 25,545 posts from 1623 users in AllDeaf, and 26,484 posts from 2751 users in Wrong Planet. We calculated CHELCS for each user and compared the scores of 3 user groups (ie, deaf and hearing-impaired people, people with ASD, and the public) through 2-sample Kolmogorov-Smirnov tests and analysis of covariance tests. RESULTS: The results suggest that users in the public forum used more complex CHL, particularly more diverse semantics and more complex health terms compared with users in the ASD and deaf and hearing-impaired user forums. However, between the latter 2 groups, people with ASD used more complex words, and deaf and hearing-impaired users used more complex syntax. CONCLUSIONS: Our results show that the users in 3 online forums had significantly different CHL complexities in different facets. The proposed framework and detailed measurements help to quantify these CHL complexity differences comprehensively. The results emphasize the importance of tailoring health-related content for different consumer groups with varying CHL complexities.

Perceived Active Control over Online Health Information: Underlying Mechanisms of Mode Tailoring Effects on Website Attitude and Information Recall.

Previous tailoring research has traditionally studied effects of system-initiated message content to match individual characteristics. Recently scholars have explored how tailoring health information to individual modality preferences and processing styles can increase message effectiveness. Using a web-based experiment among a representative sample of Internet users (N = 392; 25-86 years), this study investigated the underlying mechanisms that might explain the effects of mode tailoring on website attitudes and recall of online health information. Results from structural equation modeling showed that mode tailoring - enabling users to self-customize a health website's presentation mode (via textual, visual, audiovisual information) - increased users' perceived active control, which in turn contributed to higher perceived relevance and website engagement, and reduced cognitive load. Positive indirect effects of mode tailoring (vs. no tailoring) through these mechanisms were found for both website attitude and information recall. The findings suggest that perceived active control is the key driver of mode tailoring effects. Mode tailoring can be a promising and novel strategy to maximize the effectiveness of tailored health communications. The authors discuss the implications for theory and design of digital health information.

Systematic review of the information and communication technology features of web- and mobile-based psychoeducational interventions for depression.

OBJECTIVE: To examine the information and communication technology (ICT) features of psychoeducational interventions for depression delivered via the Internet or via mobile technology. METHODS: Web- and mobile-based psychoeducational intervention studies published from 2004 to 2014 were selected and reviewed by two independent coders. RESULTS: A total of 55 unique studies satisfied the selection criteria. The review revealed a diverse range of ICTs used to support the psychoeducational programs. Most interventions used websites as their main mode of delivery and reported greater use of communication tools compared to effective approaches like tailoring or interactive technologies games, videos, and self-monitoring tools. Many of the studies relied on medium levels of clinician involvement and only a few were entirely self-guided. CONCLUSION: Programs that reported higher levels of clinician involvement also reported using more communication tools, and reported greater compliance to treatment. Future experimental studies may help unpack the effects of technology features and reveal new ways to automate aspects of clinician input. PRACTICAL IMPLICATIONS: There is a need to further examine ways ICTs can be optimized to reduce the burden on clinicians whilst enhancing the delivery of proven effective therapeutic approaches.

A model of tailoring effects: A randomized controlled trial examining the mechanisms of tailoring in a web-based STD screening intervention.

OBJECTIVE: This study explores the mechanisms of tailoring within the context of RU@Risk a brief Web-based intervention designed to promote sexually transmitted disease (STD) testing among young adults. This is one of a few studies to empirically examine theorized message processing mechanisms of tailoring and persuasion outcomes in a single model. METHOD: Sexually active college students (N = 1065) completed a pretest, were randomly assigned to explore a tailored or nontailored website, completed a posttest, and were offered the opportunity to order a free at-home STD test kit. As intervention effects were hypothesized to work via increases in perceived risk, change in perceived risk from pretest to posttest by condition was examined. Hypothesized mechanisms of tailoring (perceived personal relevance, attention, and elaboration) were examined using structural equation modeling (SEM). All analyses controlled for demographic variables and sexual history. RESULTS: As predicted, perceived risk of STDs increased from pretest to posttest, but only in the tailored condition. Results revealed that exposure to the tailored (vs. nontailored) website increased perceived personal relevance, attention to, and elaboration of the message. These effects in turn were associated with greater perceived risk of STDs and intentions to get tested. Additionally, participants in the tailored condition were more likely to order a test kit. CONCLUSIONS: Findings provide insight into the mechanisms of tailoring with important implications for optimizing message design. (PsycINFO Database Record

Predictors of provider recommendation for HPV vaccine among young adult men and women: findings from a cross-sectional survey.

BACKGROUND: Although physician recommendation is one of the strongest predictors of human papillomavirus (HPV) vaccination, it is unclear for whom physicians are recommending the vaccine. To help guide intervention efforts, this study investigated predictors of participant-reported physician recommendation for HPV vaccine among young adults in the USA. METHODS: Women and men (N=223) aged 18-26 years were recruited online through Craigslist, a popular classified advertisements website. Ads were posted in the 25 largest US cities from September 2013 to March 2014. Participants completed a survey that assessed demographic and sociopolitical characteristics, sexual history, HPV vaccination history, and whether they had ever received a recommendation for HPV vaccine from a physician or healthcare provider. RESULTS: Fifty-three per cent reported receiving a recommendation for HPV vaccine and 45% had received ≥1 dose of HPV vaccine. Participants who received a recommendation were over 35 times more likely to receive ≥1 dose of HPV vaccine relative to participants without a recommendation. Bivariable and multivariable correlates of provider recommendation were identified. Results from the multivariable model indicated that younger (aged 18-21 years), female, White participants with health insurance (ie, employer-sponsored or some other type such as military-sponsored) were more likely to report receiving a recommendation for HPV vaccine. CONCLUSIONS: Results suggest that physician recommendation practices for HPV vaccination vary by characteristics of the patient. Findings underscore the key role of the healthcare provider in promoting HPV vaccination and have important implications for future HPV vaccine interventions with young adults.

A meta-analysis of web-delivered tailored health behavior change interventions.

Web-based tailored intervention programs show considerable promise in effecting health-promoting behaviors and improving health outcomes across a variety of medical conditions and patient populations. This meta-analysis compares the effects of tailored versus nontailored web-based interventions on health behaviors and explores the influence of key moderators on treatment outcomes. Forty experimental and quasi-experimental studies (N =20,180) met criteria for inclusion and were analyzed using meta-analytic procedures. The findings indicated that web-based tailored interventions effected significantly greater improvement in health outcomes as compared with control conditions both at posttesting, d =.139 (95% CI = .111, .166, p <.001, k =40) and at follow-up, d =.158 (95% CI = .124, .192, p <.001, k =21). The authors found no evidence of publication bias. These results provided further support for the differential benefits of tailored web-based interventions over nontailored approaches. Analysis of participant/descriptive, intervention, and methodological moderators shed some light on factors that may be important to the success of tailored interventions. Implications of these findings and directions for future research are discussed.

Increasing human papillomavirus vaccine acceptability by tailoring messages to young adult women's perceived barriers.

BACKGROUND: Human papillomavirus (HPV) vaccination is a safe and effective primary prevention strategy for cervical cancer. Despite the need for effective HPV vaccination interventions, relatively few have been tested. Moreover, existing interventions have tended to use a one-size-fits-all educational approach. We investigated whether tailoring intervention materials to young adult women's perceived barriers to HPV vaccination-a known psychosocial predictor of vaccine uptake-would increase women's intentions to receive the HPV vaccine. METHODS: Young adult women (N = 94; aged 18-26 years) who had not been vaccinated against HPV were randomly assigned to read either a nontailored message about HPV vaccination or a message that was individually tailored to participants' perceived barriers to HPV vaccine uptake (e.g., safety concerns, cost, and not sexually active). Participants' intentions to receive the HPV vaccine in the next year were assessed before and after delivery of the intervention and served as the primary outcome variable. RESULTS: The most commonly selected barrier and primary reason for not getting vaccinated was concern about vaccine adverse effects (endorsed by 55%). Knowledge about HPV vaccination increased after exposure to the intervention but did not differ by experimental condition. Although HPV vaccination intentions increased from pretest to posttest in both conditions, participants in the tailored condition reported greater increases in intentions than did participants in the nontailored condition (F1,90 = 4.02, P = 0.048, partial η = 0.043). CONCLUSIONS: Findings suggest that tailoring intervention materials to women's individual barriers is a potentially promising strategy for increasing HPV vaccination among young adult women.

Exploring digital divides: an examination of eHealth technology use in health information seeking, communication and personal health information management in the USA.

Recent government initiatives to deploy health information technology in the USA, coupled with a growing body of scholarly evidence linking online heath information and positive health-related behaviors, indicate a widespread belief that access to health information and health information technologies can help reduce healthcare inequalities. However, it is less clear whether the benefits of greater access to online health information and health information technologies is equitably distributed across population groups, particularly to those who are underserved. To examine this issue, this article employs the 2007 Health Information National Trends Survey (HINTS) to investigate relationships between a variety of socio-economic variables and the use of the web-based technologies for health information seeking, personal health information management and patient-provider communication within the context of the USA. This study reveals interesting patterns in technology adoption, some of which are in line with previous studies, while others are less clear. Whether these patterns indicate early evidence of a narrowing divide in eHealth technology use across population groups as a result of the narrowing divide in Internet access and computer ownership warrants further exploration. In particular, the findings emphasize the need to explore differences in the use of eHealth tools by medically underserved and disadvantaged groups. In so doing, it will be important to explore other psychosocial variables, such as health literacy, that may be better predictors of health consumers' eHealth technology adoption.

Assessing the Relationship Between Perceived Message Sensation Value and Perceived Message Effectiveness: Analysis of PSAs From an Effective Campaign.

The current study is an analysis of public service announcements (PSAs) from an effective safer sex campaign that utilized a sensation-seeking targeting (SENTAR) approach. Two random samples of heterosexually active young adults (sample one N = 1,463, sample two N = 895) viewed different sets of safer sex PSAs on a laptop computer and answered questions about their perceived sensation value and perceived effectiveness. Multiple regression analyses examined the impact of (a) demographic, (b) individual difference, (c) sexual context, and (d) message variables including perceived message sensation value (PMSV) on the perceived message effectiveness (PME) of the PSAs. Results indicated that females, African Americans, condom users, and those with less education viewed the PSAs as slightly more effective than males, Caucasians, non-condom users, and those with more education. PMSV and personal utility emerged as the strongest predictors of PME, even after controlling for all of the aforementioned variables. Implications for further research on PMSV and perceived and actual effectiveness of PSAs are offered.

Computer-tailored health interventions delivered over the Web: review and analysis of key components.

OBJECTIVE: This systematic review explores how computer-tailored, behavioral interventions implemented and delivered via the Web have been operationalized in a variety of settings. METHODS: Computer-tailored, online behavioral intervention studies published from 1996 to early 2007 were selected and reviewed by two independent coders. RESULTS: Of 503 studies screened, 30 satisfied the selection criteria. The level of sophistication of these interventions varied from immediate risk/health assessment, tailored web content to full-blown customized health programs. The most common variables for tailoring content were health behaviors and stages of change. Message tailoring was achieved through a combination mechanisms including: feedback, personalization and adaptation. CONCLUSIONS: Tailored, self-guided health interventions delivered via the Web to date have involved a great diversity of features and formats. While some programs have been relatively brief and simple, others have involved complex, theory-based tailoring with iterative assessment, tools for development of self-regulatory skills, and various mechanisms for providing feedback. PRACTICE IMPLICATIONS: Our ability to fully optimize the use of computer-assisted tailoring will depend on the development of empirically based guidelines for tailoring across populations, health foci, health behaviors and situations. Further outcome research is needed to enhance our understanding of how and under what conditions computer-tailoring leads to positive health outcomes in online behavioral interventions.

Predictors of online information seeking by international students when disaster strikes their countries.

This study explores factors influencing international students' likelihood of using the Internet to seek disaster-related information should a disaster affect their countries. A cross-sectional survey was conducted in two universities in America between August 1 and September 30, 2005. Two hundred twenty-nine (n = 229) students completed the self-administered questionnaires. ANOVA analyses found that respondents' Internet self-efficacy had no significant impact on their intentions to seek disaster-related information on the Internet. However, respondents' Internet dependency and attitude toward seeking information online were found to have a significant effect on such intentions.