JMIR Publications

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  Demographics of Users, Social &...

  Oct 18, 2018

  Preferences for Health Information Technologies Among US Adults: Analysis of the Health Information National Trends Survey

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  Authors List:

  • Onur Asan  
  • Farion Cooper II  
  • Sneha Nagavally  
  • Rebekah J Walker  
  • Joni S Williams  
  • Mukoso N Ozieh  
  • Leonard E Egede  

  Abstract:

  Background: Emerging health technologies are increasingly being used in health care for communication, data collection, patient monitoring, education, and facilitating adherence to chronic disease management. However, there is a lack of studies on differences in the preference for using information exchange technologies between patients with chronic and nonchronic diseases and factors affecting these differences. Objective: The purpose of this paper is to understand the preferences and use of information technology for information exchange among a nationally representative sample of adults with and without 3 chronic disease conditions (ie, cardiovascular disease [CVD], diabetes, and hypertension) and to assess whether these preferences differ according to varying demographic variables. Methods: We utilized data from the 2012 and 2014 iteration of the Health Information National Trends Survey (N=7307). We used multiple logistic regressions, adjusting for relevant demographic covariates, to identify the independent factors associated with lower odds of using health information technology (HIT), thus, identifying targets for awareness. Analyses were weighted for the US population and adjusted for the sociodemographic variables of age, gender, race, and US census region. Results: Of 7307 participants, 3529 reported CVD, diabetes, or hypertension. In the unadjusted models, individuals with diabetes, CVD, or hypertension were more likely to report using email to exchange medical information with their provider and less likely to not use any of the technology in health information exchange, as well as more likely to say it was not important for them to access personal medical information electronically. In the unadjusted model, additional significant odds ratio (OR) values were observed. However, after adjustment, most relationships regarding the use and interest in exchanging information with the provider were no longer significant. In the adjusted model, individuals with CVD, diabetes, or hypertension were more likely to access Web-based personal health information through a website or app. Furthermore, we assessed adjusted ORs for demographic variables. Those aged >65 years and Hispanic people were more likely to report no use of email to exchange medical information with their provider. Minorities (Hispanic, non-Hispanic black, and Asian people) were less likely to indicate they had no interest in exchanging general health tips with a provider electronically. Conclusions: The analysis did not show any significant association among those with comorbidities and their proclivity toward health information, possibly implying that HIT-related interventions, particularly design of information technologies, should focus more on demographic factors, including race, age, and region, than on comorbidities or chronic disease status to increase the likelihood of use. Future research is needed to understand and explore more patient-friendly use and design of information technologies, which can be utilized by diverse age, race, and education or health literacy groups efficiently to further bridge the patient-provider communication gap.

  • J Med Internet Res 2018;20(10):e277

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  Demographics of Users, Social &...

  Oct 18, 2018

  Assessment of Personal Health Care Management and Chronic Disease Prevalence: Comparative Analysis of Demographic, Socioeconomic, and Health-Related Variables

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  Authors List:

  • Ryan H Sandefer  
  • Bonnie L Westra  
  • Saif S Khairat  
  • David S Pieczkiewicz  
  • Stuart M Speedie  

  Abstract:

  Background: The use of personal health care management (PHM) is increasing rapidly within the United States because of implementation of health technology across the health care continuum and increased regulatory requirements for health care providers and organizations promoting the use of PHM, particularly the use of text messaging (short message service), Web-based scheduling, and Web-based requests for prescription renewals. Limited research has been conducted comparing PHM use across groups based on chronic conditions. Objective: This study aimed to describe the overall utilization of PHM and compare individual characteristics associated with PHM in groups with no reported chronic conditions, with 1 chronic condition, and with 2 or more such conditions. Methods: Datasets drawn from the National Health Interview Survey were analyzed using multiple logistic regression to determine the level of PHM use in relation to demographic, socioeconomic, or health-related factors. Data from 47,814 individuals were analyzed using logistic regression. Results: Approximately 12.19% (5737/47,814) of respondents reported using PHM, but higher rates of use were reported by individuals with higher levels of education and income. The overall rate of PHM remained stable between 2009 and 2014, despite increased focus on the promotion of patient engagement initiatives. Demographic factors predictive of PHM use included people who were younger, non-Hispanic, and who lived in the western region of the United States. There were also differences in PHM use based on socioeconomic factors. Respondents with college-level education were over 2.5 times more likely to use PHM than respondents without college-level education. Health-related factors were also predictive of PHM use. Individuals with health insurance and a usual place for health care were more likely to use PHM than individuals with no health insurance and no usual place for health care. Individuals reporting a single chronic condition or multiple chronic conditions reported slightly higher levels of PHM use than individuals reporting no chronic conditions. Individuals with no chronic conditions who did not experience barriers to accessing health care were more likely to use PHM than individuals with 1 or more chronic conditions. Conclusions: The findings of this study illustrated the disparities in PHM use based on the number of chronic conditions and that multiple factors influence the use of PHM, including economics and education. These findings provide evidence of the challenge associated with engaging patients using electronic health information as the health care industry continues to evolve.

  • J Med Internet Res 2018;20(10):e276

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  New Methods

  Oct 17, 2018

  Skin Cancer Classification Using Convolutional Neural Networks: Systematic Review

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  Authors List:

  • Titus Josef Brinker  
  • Achim Hekler  
  • Jochen Sven Utikal  
  • Niels Grabe  
  • Dirk Schadendorf  
  • Joachim Klode  
  • Carola Berking  
  • Theresa Steeb  
  • Alexander H Enk  
  • Christof von Kalle  

  Abstract:

  Background: State-of-the-art classifiers based on convolutional neural networks (CNNs) were shown to classify images of skin cancer on par with dermatologists and could enable lifesaving and fast diagnoses, even outside the hospital via installation of apps on mobile devices. To our knowledge, at present there is no review of the current work in this research area. Objective: This study presents the first systematic review of the state-of-the-art research on classifying skin lesions with CNNs. We limit our review to skin lesion classifiers. In particular, methods that apply a CNN only for segmentation or for the classification of dermoscopic patterns are not considered here. Furthermore, this study discusses why the comparability of the presented procedures is very difficult and which challenges must be addressed in the future. Methods: We searched the Google Scholar, PubMed, Medline, ScienceDirect, and Web of Science databases for systematic reviews and original research articles published in English. Only papers that reported sufficient scientific proceedings are included in this review. Results: We found 13 papers that classified skin lesions using CNNs. In principle, classification methods can be differentiated according to three principles. Approaches that use a CNN already trained by means of another large dataset and then optimize its parameters to the classification of skin lesions are the most common ones used and they display the best performance with the currently available limited datasets. Conclusions: CNNs display a high performance as state-of-the-art skin lesion classifiers. Unfortunately, it is difficult to compare different classification methods because some approaches use nonpublic datasets for training and/or testing, thereby making reproducibility difficult. Future publications should use publicly available benchmarks and fully disclose methods used for training to allow comparability.

  • J Med Internet Res 2018;20(10):e11936

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  Medicine 2.0: Social Media, Open,...

  Oct 16, 2018

  Nature and Diffusion of Gynecologic Cancer–Related Misinformation on Social Media: Analysis of Tweets

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  Authors List:

  • Liang Chen  
  • Xiaohui Wang  
  • Tai-Quan Peng  

  Abstract:

  Background: Over the last two decades, the incidence and mortality rates of gynecologic cancers have increased at a constant rate in China. Gynecologic cancers have become one of the most serious threats to women’s health in China. With the widespread use of social media, an increasing number of individuals have employed social media to produce, seek, and share cancer-related information. However, health information on social media is not always accurate. Health, and especially cancer-related, misinformation has been widely spread on social media, which can affect individuals’ attitudinal and behavioral responses to cancer. Objective: The aim of this study was to examine the nature and diffusion of gynecologic cancer–related misinformation on Weibo, the Chinese equivalent of Twitter. Methods: A total of 2691 tweets related to 2 gynecologic cancers—breast cancer and cervical cancer—posted on Weibo from June 2015 to June 2016 were extracted using the Python Web Crawler. Two medical school graduate students with expertise in gynecologic diseases were recruited to code the tweets to differentiate between true information and misinformation as well as to identify the types of falsehoods. The diffusion characteristics of gynecologic cancer–related misinformation were compared with those of the true information. Results: While most of the gynecologic cancer–related tweets provided medically accurate information, approximately 30% of them were found to contain misinformation. Furthermore, it was found that tweets about cancer treatment contained a higher percentage of misinformation than prevention-related tweets. Nevertheless, the prevention-related misinformation diffused significantly more broadly and deeply than true information on social media. Conclusions: The findings of this study suggest the need for controlling and reducing the cancer-related misinformation on social media with the efforts from both service providers and medical professionals. More specifically, it is important to correct falsehoods related to the prevention of gynecologic cancers on social media and increase individuals’ capacity to assess the veracity of Web-based information to curb the spread and thus minimize the consequences of cancer-related misinformation.

  • J Med Internet Res 2018;20(10):e11515

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  Clinical Informatics

  Oct 15, 2018

  Web-Based Information Infrastructure Increases the Interrater Reliability of Medical Coders: Quasi-Experimental Study

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  Authors List:

  • Julian Varghese  
  • Sarah Sandmann  
  • Martin Dugas  

  Abstract:

  Background: Medical coding is essential for standardized communication and integration of clinical data. The Unified Medical Language System by the National Library of Medicine is the largest clinical terminology system for medical coders and Natural Language Processing tools. However, the abundance of ambiguous codes leads to low rates of uniform coding among different coders. Objective: The objective of our study was to measure uniform coding among different medical experts in terms of interrater reliability and analyze the effect on interrater reliability using an expert- and Web-based code suggestion system. Methods: We conducted a quasi-experimental study in which 6 medical experts coded 602 medical items from structured quality assurance forms or free-text eligibility criteria of 20 different clinical trials. The medical item content was selected on the basis of mortality-leading diseases according to World Health Organization data. The intervention comprised using a semiautomatic code suggestion tool that is linked to a European information infrastructure providing a large medical text corpus of >300,000 medical form items with expert-assigned semantic codes. Krippendorff alpha (Kalpha) with bootstrap analysis was used for the interrater reliability analysis, and coding times were measured before and after the intervention. Results: The intervention improved interrater reliability in structured quality assurance form items (from Kalpha=0.50, 95% CI 0.43-0.57 to Kalpha=0.62 95% CI 0.55-0.69) and free-text eligibility criteria (from Kalpha=0.19, 95% CI 0.14-0.24 to Kalpha=0.43, 95% CI 0.37-0.50) while preserving or slightly reducing the mean coding time per item for all 6 coders. Regardless of the intervention, precoordination and structured items were associated with significantly high interrater reliability, but the proportion of items that were precoordinated significantly increased after intervention (eligibility criteria: OR 4.92, 95% CI 2.78-8.72; quality assurance: OR 1.96, 95% CI 1.19-3.25). Conclusions: The Web-based code suggestion mechanism improved interrater reliability toward moderate or even substantial intercoder agreement. Precoordination and the use of structured versus free-text data elements are key drivers of higher interrater reliability.

  • J Med Internet Res 2018;20(10):e274

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  Clinical Informatics

  Oct 15, 2018

  Investigating the Perceptions of Primary Care Dietitians on the Potential for Information Technology in the Workplace: Qualitative Study

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  Authors List:

  • Aimee Jones  
  • Lana J Mitchell  
  • Rochelle O'Connor  
  • Megan E Rollo  
  • Katherine Slater  
  • Lauren T Williams  
  • Lauren Ball  

  Abstract:

  Background: Chronic diseases are the leading cause of morbidity and mortality worldwide. The primary health care setting is an effective avenue for the management and prevention of chronic diseases. Dietitians working in this setting assist with the management of modifiable risk factors of chronic diseases. However, health care professionals report challenges in providing care in this setting because of time and financial constraints. Information technology offers the potential to improve health care quality, safety, efficiency, and cost-efficiency, but there exists limited understanding of dietitians’ application of technology in this setting. Objective: The objective of this study was to explore the perceptions of primary care dietitians about using information technology in their workplace. Methods: We recruited 20 Australian primary care dietitians using purposive and snowball sampling for semistructured telephonic interviews. Interview questions aimed to gain an understanding of dietitians’ perceptions about sharing patient outcomes through a national database and the benefits, disadvantages, feasibility, and barriers of using information technology. Interviews were audiorecorded, transcribed verbatim, and thematically analyzed for emerging themes and subthemes. Finally, the technologies used by participants were collated by name and researched for their key attributes. Results: The following 4 distinct themes emerged from the data: information technology improving the efficiency of practice tasks, experiencing barriers to using information technology in practice, information technology enhancing outcomes through education and monitoring, and information technology for sharing information with others. Participants identified several advantages and disadvantages of using technology and expressed willingness to share patient outcomes using a Web-based database. Conclusions: This study suggests that information technology is perceived to have benefits to dietitians and patients in primary health care. However, to achieve the optimal benefit, support is required to overcome barriers to integrate information technology into practice better. Further development of patient management systems and standardized Web-based data collection systems are needed to support better usage by dietitians.

  • J Med Internet Res 2018;20(10):e265

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  Infodemiology and Infoveillance

  Oct 12, 2018

  Using Twitter to Examine Web-Based Patient Experience Sentiments in the United States: Longitudinal Study

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  Authors List:

  • Kara C Sewalk  
  • Gaurav Tuli  
  • Yulin Hswen  
  • John S Brownstein  
  • Jared B Hawkins  

  Abstract:

  Background: There are documented differences in access to health care across the United States. Previous research indicates that Web-based data regarding patient experiences and opinions of health care are available from Twitter. Sentiment analyses of Twitter data can be used to examine differences in patient views of health care across the United States. Objective: The objective of our study was to provide a characterization of patient experience sentiments across the United States on Twitter over a 4-year period. Methods: Using data from Twitter, we developed a set of 4 software components to automatically label and examine a database of tweets discussing patient experience. The set includes a classifier to determine patient experience tweets, a geolocation inference engine for social data, a modified sentiment classifier, and an engine to determine if the tweet is from a metropolitan or nonmetropolitan area in the United States. Using the information retrieved, we conducted spatial and temporal examinations of tweet sentiments at national and regional levels. We examined trends in the time of the day and that of the week when tweets were posted. Statistical analyses were conducted to determine if any differences existed between the discussions of patient experience in metropolitan and nonmetropolitan areas. Results: We collected 27.3 million tweets between February 1, 2013 and February 28, 2017, using a set of patient experience-related keywords; the classifier was able to identify 2,759,257 tweets labeled as patient experience. We identified the approximate location of 31.76% (876,384/2,759,257) patient experience tweets using a geolocation classifier to conduct spatial analyses. At the national level, we observed 27.83% (243,903/876,384) positive patient experience tweets, 36.22% (317,445/876,384) neutral patient experience tweets, and 35.95% (315,036/876,384) negative patient experience tweets. There were slight differences in tweet sentiments across all regions of the United States during the 4-year study period. We found the average sentiment polarity shifted toward less negative over the study period across all the regions of the United States. We observed the sentiment of tweets to have a lower negative fraction during daytime hours, whereas the sentiment of tweets posted between 8 pm and 10 am had a higher negative fraction. Nationally, sentiment scores for tweets in metropolitan areas were found to be more extremely negative and mildly positive compared with tweets in nonmetropolitan areas. This result is statistically significant (P<.001). Tweets with extremely negative sentiments had a medium effect size (d=0.34) at the national level. Conclusions: This study presents methodologies for a deeper understanding of Web-based discussion related to patient experience across space and time and demonstrates how Twitter can provide a unique and unsolicited perspective from users on the health care they receive in the United States.

  • J Med Internet Res 2018;20(10):e10043

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  Cost-Effectiveness and Economics

  Oct 11, 2018

  Tailored, Therapist-Guided Internet-Based Cognitive Behavioral Therapy Compared to Care as Usual for Patients With Rheumatoid Arthritis: Economic Evaluation...

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  Authors List:

  • Maaike Ferwerda  
  • Sylvia van Beugen  
  • Henriët van Middendorp  
  • Henk Visser  
  • Harald Vonkeman  
  • Marjonne Creemers  
  • Piet van Riel  
  • Wietske Kievit  
  • Andrea Evers  

  Abstract:

  Background: Internet-based cognitive behavioral therapy can aid patients with rheumatoid arthritis with elevated levels of distress to enhance their quality of life. However, implementation is currently lacking and there is little evidence available on the (cost-) effectiveness of different treatment strategies. Objective: Cost-benefit ratios are necessary for informing stakeholders and motivating them to implement effective treatment strategies for improving health-related quality of life (HRQoL) of patients with rheumatoid arthritis. A cost-effectiveness study from a societal perspective was conducted alongside a randomized controlled trial on a tailored, therapist-guided internet-based cognitive behavioral therapy (ICBT) intervention for patients with rheumatoid arthritis with elevated levels of distress as an addition to care as usual (CAU). Methods: Data were collected at baseline or preintervention, 6 months or postintervention, and every 3 months thereafter during the 1-year follow-up. Effects were measured in terms of quality-adjusted life years (QALYs) and costs from a societal perspective, including health care sector costs (health care use, medication, and intervention costs), patient travel costs for health care use, and costs associated with loss of labor. Results: The intervention improved the quality of life compared with only CAU (Δ QALYs=0.059), but at a higher cost (Δ=€4211). However, this increased cost substantially reduced when medication costs were left out of the equation (Δ=€1863). Of all, 93% (930/1000) of the simulated incremental cost-effectiveness ratios were in the north-east quadrant, indicating a high probability that the intervention was effective in improving HRQoL, but at a greater monetary cost for society compared with only CAU. Conclusions: A tailored and guided ICBT intervention as an addition to CAU for patients with rheumatoid arthritis with elevated levels of distress was effective in improving quality of life. Consequently, implementation of ICBT into standard health care for patients with rheumatoid arthritis is recommended. However, further studies on cost reductions in this population are warranted. Trial Registration: Nederlands Trial Register NTR2100; http://www.trialregister.nl/trialreg/admin/rctview.asp?TC=2100 (Archived by WebCite at http://www.webcitation.org/724t9pvr2)

  • J Med Internet Res 2018;20(10):e260

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  Patient-Reported Outcome Measures...

  Oct 11, 2018

  Eliciting the Impact of Digital Consulting for Young People Living With Long-Term Conditions (LYNC Study): Cognitive Interviews to Assess the Face and...

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  Authors List:

  • Jackie Sturt  
  • Thandiwe Rebecca Dliwayo  
  • Vera Forjaz  
  • Kathryn Hamilton  
  • Carol Bryce  
  • Joseph Fraser  
  • Frances Griffiths  

  Abstract:

  Background: Digital consulting, using email, text, and Skype, is increasingly offered to young people accessing specialist care for long-term conditions. No patient-reported outcome measures (PROMs) have been evaluated for assessing outcomes of digital consulting. Systematic and scoping reviews, alongside patient involvement, revealed 2 candidate PROMs for this purpose: the patient activation measure (PAM) and the physician’s humanistic behaviors questionnaire (PHBQ). PAM measures knowledge, beliefs, and skills that enable people to manage their long-term conditions. PHBQ assesses the presence of behaviors that are important to patients in their physician-patient interactions. Objective: This study aimed to assess the face and content validity of PAM and PHBQ to explore whether they elicit important outcomes of digital consulting and whether the PROMs can isolate the digital consultation component of care. Methods: Participants were drawn from 5 clinics providing specialist National Health Service care to 16- to 24-year-olds with long-term health conditions participating in the wider LYNC (Long-Term Conditions, Young People, Networked Communications) study. Overall, 14 people undertook a cognitive interview in this substudy. Of these, 7 participants were young people with either inflammatory bowel disease, cystic fibrosis, or cancer. The remaining 7 participants were clinicians who were convenience sampled. These included a clinical psychologist, 2 nurses, 3 consultant physicians, and a community youth worker practicing in cancer, diabetes, cystic fibrosis, and liver disease. Cognitive interviews were transcribed and analyzed, and a spreadsheet recorded the participants’ PROM item appraisals. Illustrative quotes were extracted verbatim from the interviews for all participants. Results: Young people found 11 of the PAM 13 items and 7 of the additional 8 PAM 22 items to be relevant to digital consulting. They were only able to provide spontaneous examples of digital consulting for 50% (11/22) of the items. Of the 7 clinicians, 4 appraised all PAM 13 items and 20 of the PAM 22 items to be relevant to evaluating digital consulting and articulated operationalization of the items with reference to their own digital consulting practice with greater ease than the young people. Appraising the PHBQ, in 14 of the 25 items, two-thirds of the young people’s appraisals offered digital consulting examples with ease, suggesting that young people can detect and discern humanistic clinician behaviors via digital as well as face-to-face communication channels. Moreover, 17 of the 25 items were appraised as relevant by the young people. This finding was mirrored in the clinician appraisals. Both young people and the clinicians found the research task complex. Young participants required considerably more researcher prompting to elicit examples related to digital consulting rather than their face-to-face care. Conclusions: PAM and PHBQ have satisfactory face and content validity for evaluating digital consulting to warrant proceeding to psychometric evaluation. Completion instructions require revision to differentiate between digital and face-to-face consultations.

  • J Med Internet Res 2018;20(10):e268

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  Medicine 2.0: Social Media, Open,...

  Oct 11, 2018

  Drug Repositioning to Accelerate Drug Development Using Social Media Data: Computational Study on Parkinson Disease

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  Authors List:

  • Mengnan Zhao  
  • Christopher C Yang  

  Abstract:

  Background: Due to the high cost and low success rate in new drug development, systematic drug repositioning methods are exploited to find new indications for existing drugs. Objective: We sought to propose a new computational drug repositioning method to identify repositioning drugs for Parkinson disease (PD). Methods: We developed a novel heterogeneous network mining repositioning method that constructed a 3-layer network of disease, drug, and adverse drug reaction and involved user-generated data from online health communities to identify potential candidate drugs for PD. Results: We identified 44 non-Parkinson drugs by using the proposed approach, with data collected from both pharmaceutical databases and online health communities. Based on the further literature analysis, we found literature evidence for 28 drugs. Conclusions: In summary, the proposed heterogeneous network mining repositioning approach is promising for identifying repositioning candidates for PD. It shows that adverse drug reactions are potential intermediaries to reveal relationships between disease and drug.

  • J Med Internet Res 2018;20(10):e271

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  Web-based and Mobile Health...

  Oct 10, 2018

  Combining Technology and Research to Prevent Scald Injuries (the Cool Runnings Intervention): Randomized Controlled Trial

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  Authors List:

  • Jacqueline Burgess  
  • Kerrianne Watt  
  • Roy M Kimble  
  • Cate M Cameron  

  Abstract:

  Background: New technologies, internet accessibility, social media, and increased smartphone ownership provide new opportunities for health researchers to communicate and engage target audiences. An innovative burn prevention intervention was developed using these channels. Objective: The aim of this study was to evaluate the efficacy of Cool Runnings, an app-based intervention to increase knowledge of childhood burn risk (specifically hot beverage scalds) and correct burn first aid among mothers of young children. Methods: This was a 2-group, parallel, single-blinded randomized controlled trial (RCT). Participants were women aged 18 years and above, living in Queensland, Australia, with at least 1 child aged 5-12 months at time of enrollment. The primary outcome measures were change in knowledge about risk of burns and correct burn first aid assessed via 2 methods: (1) overall score and (2) categorized as adequate (score=4) versus inadequate (score<4). Efficacy of gamification techniques was also assessed. Results: In total, 498 participants were recruited via social media and enrolled. At the 6-month follow-up, 244 participants completed the posttest questionnaire. Attrition rates in both groups were similar. Participants who remained in the study did not differ from those lost to follow-up on any characteristics except education level. Although similar at baseline, intervention group participants achieved significantly greater improvement in overall knowledge posttest than control group participants on both primary outcome measures (overall knowledge intervention: mean [SD] of overall knowledge 2.68 [SD 1.00] for intervention vs 2.13 [SD 1.03] for control; 20.7% [25/121] adequate in intervention vs 7.3% [2/123] in control). Consequently, the number needed to treat was 7.46. Logistic regression showed participants exposed to the highest level of disadvantage had 7.3 times higher odds of improved overall knowledge scores than participants in other levels of disadvantage. There were also significant correlations between gamification techniques and knowledge change (P<.001). In addition, odds of knowledge improvement between baseline and 6-month follow-up was higher in participants with low-moderate app activity compared with no app activity (odds ratio [OR] 8.59, 95% CI 2.9-25.02) and much higher in participants with high app activity (OR 18.26, 95% CI 7.1-46.8). Conclusions: Despite substantial loss to follow-up, this RCT demonstrates the Cool Runnings app was an effective intervention for improving knowledge about risks of hot beverage scalds and burn first aid in mothers of young children. The benefits of combining gamification elements in the intervention were also highlighted. Given the low cost and large reach of smartphone apps to deliver content to and engage with targeted populations, the results from this RCT provide important information on how smartphone apps can be used for widespread injury prevention campaigns and public health campaigns generally. Trial Registration: Australian New Zealand Clinical Trials Registry ACTRN12616000019404; https://www.anzctr.org.au/Trial/Registration/TrialReview.aspx?id=369745&showOriginal=true&isReview=true (Archived by WebCite at http://www.webcitation.org/72b1E8gTW)

  • J Med Internet Res 2018;20(10):e10361

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  Web-based and Mobile Health...

  Oct 10, 2018

  Predicting Adherence to Internet-Delivered Psychotherapy for Symptoms of Depression and Anxiety After Myocardial Infarction: Machine Learning Insights From...

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  Authors List:

  • John Wallert  
  • Emelie Gustafson  
  • Claes Held  
  • Guy Madison  
  • Fredrika Norlund  
  • Louise von Essen  
  • Erik Martin Gustaf Olsson  

  Abstract:

  Background: Low adherence to recommended treatments is a multifactorial problem for patients in rehabilitation after myocardial infarction (MI). In a nationwide trial of internet-delivered cognitive behavior therapy (iCBT) for the high-risk subgroup of patients with MI also reporting symptoms of anxiety, depression, or both (MI-ANXDEP), adherence was low. Since low adherence to psychotherapy leads to a waste of therapeutic resources and risky treatment abortion in MI-ANXDEP patients, identifying early predictors for adherence is potentially valuable for effective targeted care. Objectives: The goal of the research was to use supervised machine learning to investigate both established and novel predictors for iCBT adherence in MI-ANXDEP patients. Methods: Data were from 90 MI-ANXDEP patients recruited from 25 hospitals in Sweden and randomized to treatment in the iCBT trial Uppsala University Psychosocial Care Programme (U-CARE) Heart study. Time point of prediction was at completion of the first homework assignment. Adherence was defined as having completed more than 2 homework assignments within the 14-week treatment period. A supervised machine learning procedure was applied to identify the most potent predictors for adherence available at the first treatment session from a range of demographic, clinical, psychometric, and linguistic predictors. The internal binary classifier was a random forest model within a 3×10–fold cross-validated recursive feature elimination (RFE) resampling which selected the final predictor subset that best differentiated adherers versus nonadherers. Results: Patient mean age was 58.4 years (SD 9.4), 62% (56/90) were men, and 48% (43/90) were adherent. Out of the 34 potential predictors for adherence, RFE selected an optimal subset of 56% (19/34; Accuracy 0.64, 95% CI 0.61-0.68, P<.001). The strongest predictors for adherence were, in order of importance, (1) self-assessed cardiac-related fear, (2) sex, and (3) the number of words the patient used to answer the first homework assignment. Conclusions: For developing and testing effective iCBT interventions, investigating factors that predict adherence is important. Adherence to iCBT for MI-ANXDEP patients in the U-CARE Heart trial was best predicted by cardiac-related fear and sex, consistent with previous research, but also by novel linguistic predictors from written patient behavior which conceivably indicate verbal ability or therapeutic alliance. Future research should investigate potential causal mechanisms and seek to determine what underlying constructs the linguistic predictors tap into. Whether these findings replicate for other interventions outside of Sweden, in larger samples, and for patients with other conditions who are offered iCBT should also be investigated. Trial registration: ClinicalTrials.gov NCT01504191; https://clinicaltrials.gov/ct2/show/NCT01504191 (Archived at Webcite at http://www.webcitation.org/6xWWSEQ22)

  • J Med Internet Res 2018;20(10):e10754

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