bluuebunny/crossref_metadata_2025 huggingface dataset:
Codeine Addiction and Internet Forum Use and Support: Qualitative Netnographic Study (Preprint)
Authors: Lee Eleanor , Cooper Richard J
Published: October 2018

BACKGROUND

The use of codeine as an analgesic is well-recognized, but there are increasing concerns that for some individuals continued use may lead to misuse, dependence, and fatalities. Research suggests that those affected may represent a hard-to-reach group who do not engage with formal treatment services.

OBJECTIVE

This study sought to explore the experiences of people with self-reported addiction to codeine and, specifically, how a social media forum is used to communicate with others about this issue.

METHODS

Using a qualitative netnographic methodology, the social media forum Mumsnet was used, with permission, and searches were undertaken in 2016 of any posts that related to codeine and addiction. A total of 95 relevant posts were identified; a purposive sample of 25 posts was selected to undertake subsequent six-stage thematic analysis and development of emerging themes. These 25 posts were posted between 2003 and 2016 and comprised 757 individual posts.

RESULTS

Individuals created posts to actively request help in relation to usually their own, but occasionally their partner’s or relative’s, problems relating to codeine use and self-reported “addiction.” Varying levels of detail were provided in narratives of problematic codeine use. There were both positive and negative descriptions of side effects emerging, problems experiencing withdrawal, and failed attempts to discontinue codeine use. Mainly positive and supportive responses to posts were identified from those with either self-reported health profession experience or lay respondents, who often drew on their own experiences of similar problems. Treatment advice emerged in two main ways, either as signposting to formal health services or to informal approaches and often anecdotal advice about how to taper or use cold turkey techniques. Some posts were more critical of the original poster, and arguments and challenges to advice were not uncommon. Shame and stigma were often associated with users’ posts and, while there was a desire to receive support and treatment advice in this forum, users often wanted to keep their codeine use hidden in other aspects of their lives. Distinctly different views emerged as to whether responsibility lay with prescribers or patients. Some users expressed anger toward doctors and their prescribing practices.

CONCLUSIONS

This study provides a unique insight into how a public internet forum is used by individuals to confirm and seek support about problematic codeine use and of the ways others respond. The pseudonymous use of internet forums for such information and variation in treatment options suggested by often lay respondents suggest that increased formal support and awareness about codeine addiction are needed. There may be opportunities for providing further support directly on such online forums. Improvements in prescribing codeine and in the over-the-counter supply of codeine are required to prevent problematic use from occurring.
Health Information Engagement Factors: A Content Analysis of Facebook of Ministry of Health, Malaysia. (Preprint)
Authors: A Rahim Afiq Izzudin , A Salim Faizul Nizam , Ariffin Mohd Ariff Ikram , Ibrahim Mohd Ismail
Published: October 2018

BACKGROUND

Health organizations have widely adopted social media for health promotion, public health communication conveyance and organizational, promotional activities. However, limited information is available on the factors that facilitate the health information diffusion in Malaysia, an Asia country with different socio-economic, cultural events and average internet penetration rate compared to Western countries.

OBJECTIVE

This study aims to look at factors associated with good engagement rates among netizens using Facebook (FB) Page of the Ministry of Health (MOH) Malaysia.

METHODS

Two thousand one hundred twenty-three FB posts randomly selected in the cross-sectional study design. The sample was determined based on the study objective using two proportion formula. Data gathered from Facebook Insight of MOH’s FB Page from November 2016 to October 2017. The logistic regression model was applied to identify factors associated with good engagement rate.

RESULTS

The most prevalent type of health information was the organizational promotion (n=766) while the majority of posts were posted between midnight till early morning (n=870) and the most frequent types of the post was the photo (n=1366). This study found that good engagement rate significantly associated with health education post (AOR 3.80, 95% CI 3.02, 4.78, P<0.001), risk communication post (AOR 1.77, 95% CI 1.39, 2.26, P<0.001), post in afternoon (AOR 1.76, 95% CI 1.34, 2.31, P<0.001), or in evening (AOR: 1.48, 95% CI 1.20, 1.82, P<0.001) and video post (AOR: 3.74, 95% CI 1.44, 9.71, P= 0.007). The engagement was negatively associated with FB post at morning, and utilization of different FB type of post namely link, share video or photo.

CONCLUSIONS

Understanding of engagement factors on social media such as Facebook may improve the dissemination of health information among netizens by health organizations.
Toward an Objective Assessment of Implementation Processes for Innovations in Health Care: Psychometric Evaluation of the Normalization Measure Development (NoMAD) Questionnaire Among Mental Health Care Professionals (Preprint)
Authors: Vis Christiaan , Ruwaard Jeroen , Finch Tracy , Rapley Tim , de Beurs Derek , van Stel Henk , van Lettow Britt , Mol Mayke , Kleiboer Annet , Riper Heleen , Smit Jan
Published: October 2018

BACKGROUND

Successfully implementing eMental health (eMH) interventions in routine mental health care constitutes a major challenge. Reliable instruments to assess implementation progress are essential. The Normalization MeAsure Development (NoMAD) study developed a brief self-report questionnaire that could be helpful in measuring implementation progress. Based on the Normalization Process Theory, this instrument focuses on 4 generative mechanisms involved in implementation processes: coherence, cognitive participation, collective action, and reflexive monitoring.

OBJECTIVE

The aim of this study was to translate the NoMAD questionnaire to Dutch and to confirm the factor structure in Dutch mental health care settings.

METHODS

Dutch mental health care professionals involved in eMH implementation were invited to complete the translated NoMAD questionnaire. Confirmatory factor analysis (CFA) was conducted to verify interpretability of scale scores for 3 models: (1) the theoretical 4-factor structure, (2) a unidimensional model, and (3) a hierarchical model. Potential improvements were explored, and correlated scale scores with 3 control questions were used to assess convergent validity.

RESULTS

A total of 262 professionals from mental health care settings in the Netherlands completed the questionnaire (female: 81.7%; mean age: 45 [SD=11]). The internal consistency of the 20-item questionnaire was acceptable (.62≤alpha≤.85). The theorized 4-factor model fitted the data slightly better in the CFA than the hierarchical model (Comparative Fit Index=0.90, Tucker Lewis Index=0.88, Root Mean Square Error of Approximation=0.10, Standardized Root Mean Square Residual=0.12, χ22=22.5, P≤.05). However, the difference is small and possibly not outweighing the practical relevance of a total score and subscale scores combined in one hierarchical model. One item was identified as weak (λCA.2=0.10). A moderate-to-strong convergent validity with 3 control questions was found for the Collective Participation scale (.47≤r≤.54, P≤.05).

CONCLUSIONS

NoMAD’s theoretical factor structure was confirmed in Dutch mental health settings to acceptable standards but with room for improvement. The hierarchical model might prove useful in increasing the practical utility of the NoMAD questionnaire by combining a total score with information on the 4 generative mechanisms. Future research should assess the predictive value and responsiveness over time and elucidate the conceptual interpretability of NoMAD in eMH implementation practices.
Quality of Life Among Informal Caregivers of Patients With Degenerative Cervical Myelopathy: Cross-Sectional Questionnaire Study (Preprint)
Authors: Mowforth Oliver Daniel , Davies Benjamin Marshall , Kotter Mark Reinhard
Published: October 2018

BACKGROUND

Degenerative cervical myelopathy (DCM) is a common, chronic neurological condition that severely affects individuals by causing a range of disabling symptoms, frequently at a time around the peak of their careers. Subsequently, individuals with DCM often become dependent on informal care arrangements. The significant economic contribution of informal care and its burden on care providers are becoming increasingly recognized.

OBJECTIVE

This study aimed to measure the quality of life of DCM informal caregivers and provide preliminary insight into possible contributing factors.

METHODS

Carers of individuals with DCM completed a Web-based survey hosted by Myelopathy.org, an international DCM charity. Carer quality of life was assessed in the form of caregiver happiness and 7 dimensions of carer burden using the Care-Related Quality of Life (CarerQol) instrument. The relationships between patient disease severity, patient pain, and carer quality of life were investigated. Differences in carer quality of life were assessed across patient and carer demographic groups, including between UK and US carers.

RESULTS

DCM caregivers experienced substantial burden as a result of their caregiving (mean CarerQol-7D=64.1; 95% CI 58.8-69.5) and low happiness (mean CarerQol-VAS [Visual Analog Scale]=6.3; 95% CI 5.7-6.9). Burden was high and happiness was low in DCM carers when compared with a large, mixed-disease study of adult informal carers where CarerQol-7D was 79.1 and CarerQol-VAS was 7.1. No significant relationship was found between DCM carer quality of life and patient disease severity and pain scores. DCM carer quality of life appeared uniform across all patient and carer demographic groups.

CONCLUSIONS

Caring for individuals with DCM is associated with reduced quality of life in the form of significant burden and reduced happiness. Reductions appear greater in DCM than in other diseases investigated. However, no simple relationship was identified between individual patient or carer factors and carer quality of life.
Flu Outbreak Prediction Using Twitter Posts Classification and Linear Regression With Historical Centers for Disease Control and Prevention Reports: Prediction Framework Study (Preprint)
Authors: Alessa Ali , Faezipour Miad
Published: October 2018

BACKGROUND

Social networking sites (SNSs) such as Twitter are widely used by diverse demographic populations. The amount of data within SNSs has created an efficient resource for real-time analysis. Thus, data from SNSs can be used effectively to track disease outbreaks and provide necessary warnings. Current SNS-based flu detection and prediction frameworks apply conventional machine learning approaches that require lengthy training and testing, which is not the optimal solution for new outbreaks with new signs and symptoms.

OBJECTIVE

The objective of this study was to propose an efficient and accurate framework that uses data from SNSs to track disease outbreaks and provide early warnings, even for newest outbreaks, accurately.

METHODS

We present a framework of outbreak prediction that included 3 main modules: text classification, mapping, and linear regression for weekly flu rate predictions. The text classification module used the features of sentiment analysis and predefined keyword occurrences. Various classifiers, including FastText (FT) and 6 conventional machine learning algorithms, were evaluated to identify the most efficient and accurate one for the proposed framework. The text classifiers were trained and tested using a prelabeled dataset of flu-related and unrelated Twitter postings. The selected text classifier was then used to classify over 8,400,000 tweet documents. The flu-related documents were then mapped on a weekly basis using a mapping module. Finally, the mapped results were passed together with historical Centers for Disease Control and Prevention (CDC) data to a linear regression module for weekly flu rate predictions.

RESULTS

The evaluation of flu tweet classification showed that FT, together with the extracted features, achieved accurate results with an F-measure value of 89.9% in addition to its efficiency. Therefore, FT was chosen to be the classification module to work together with the other modules in the proposed framework, including a regression-based estimator, for flu trend predictions. The estimator was evaluated using several regression models. Regression results show that the linear regression–based estimator achieved the highest accuracy results using the measure of Pearson correlation. Thus, the linear regression model was used for the module of weekly flu rate estimation. The prediction results were compared with the available recent data from CDC as the ground truth and showed a strong correlation of 96.29% .

CONCLUSIONS

The results demonstrated the efficiency and the accuracy of the proposed framework that can be used even for new outbreaks with new signs and symptoms. The classification results demonstrated that the FT-based framework improves the accuracy and the efficiency of flu disease surveillance systems that use unstructured data such as data from SNSs.
Electronic Health Self-Management Interventions for Patients With Chronic Kidney Disease: Systematic Review of Quantitative and Qualitative Evidence (Preprint)
Authors: Shen Hongxia , van der Kleij Rianne MJJ , van der Boog Paul JM , Chang Xinwei , Chavannes Niels H
Published: October 2018

BACKGROUND

Chronic kidney disease (CKD) poses a major challenge to public health. In CKD patients, adequate disease self-management has been shown to improve both proximal and distal outcomes. Currently, electronic health (eHealth) interventions are increasingly used to optimize patients’ self-management skills.

OBJECTIVE

This study aimed to systematically review the existing evidence regarding the implementation and effectiveness of eHealth self-management interventions for patients with CKD.

METHODS

Following a search in 8 databases (up to November 2017), quantitative and qualitative data on process and effect outcomes were extracted from relevant studies. Quality was appraised using the Crowe Critical Appraisal Tool; narrative synthesis was performed to analyze the data extracted.

RESULTS

Of the 3307 articles retrieved, 24 (comprising 23 studies) were included in this review; of these, almost half were appraised to be of low to moderate quality. There was considerable heterogeneity in the types of interventions used and the outcomes measured. A total of 10 effect and 9 process outcome indicators were identified. The most frequently reported effect outcome indicators were specific laboratory tests and blood pressure (BP), whereas satisfaction was the most frequently reported process outcome indicator. Positive effects were found for proximal outcomes (eg, BP control and medication adherence), and mixed effects were found for more distal outcomes (eg, quality of life). High feasibility, usability, and acceptability of and satisfaction with eHealth self-management interventions were reported. The determinant ability of health care professionals to monitor and, if necessary, anticipate on patient measurements online was mostly cited to influence patients’ adherence to interventions.

CONCLUSIONS

eHealth self-management interventions have the potential to improve disease management and health outcomes. To broaden the evidence base and facilitate intervention upscaling, more detailed descriptions and thorough analysis of the intervention components used are required. In addition, our review reveals that outcomes closely related to the scope and duration of the intervention implemented are most likely to be impacted. For instance, if a 4-week Web-based training to optimize disease management skills is implemented, the outcome perceived control would more likely be affected than kidney function. Although this seems obvious, most studies evaluate only distal outcomes and thereby fail to capture intervention effects that might contribute to long-term health improvement. We advise future researchers to carefully consider their choice of outcomes based on their sensitivity for change. In this way, we ensure that relevant effects are captured and legitimate conclusions are drawn.
Toward Developing a Standardized Core Set of Outcome Measures in Mobile Health Interventions for Tuberculosis Management: Systematic Review (Preprint)
Authors: Lee Seohyun , Lee Youngji , Lee Sangmi , Islam Sheikh Mohammed Shariful , Kim Sun-Young
Published: October 2018

BACKGROUND

Tuberculosis (TB) management can be challenging in low- and middle-income countries (LMICs) not only because of its high burden but also the prolonged treatment period involving multiple drugs. With rapid development in mobile technology, mobile health (mHealth) interventions or using a mobile device for TB management has gained popularity. Despite the potential usefulness of mHealth interventions for TB, few studies have quantitatively synthesized evidence on its effectiveness, presumably because of variability in outcome measures reported in the literature.

OBJECTIVE

The aim of this systematic review was to evaluate the outcome measures reported in TB mHealth literature in LMICs.

METHODS

MEDLINE, EMBASE, and the Cochrane Database of Systematic Reviews were searched to identify mHealth intervention studies for TB (published up to May 2018) that reported any type of outcome measures. The extracted information included the study setting, types of mHealth technology used, target population, study design, and categories of outcome measures. Outcomes were classified into 13 categories including treatment outcome, adherence, process measure, perception, technical outcome, and so on. The qualitative synthesis of evidence focused on the categories of outcome measures reported by the type of mHealth interventions.

RESULTS

A total of 27 studies were included for the qualitative synthesis of evidence. The study designs varied widely, ranging from randomized controlled trials to economic evaluations. A total of 12 studies adopted short message service (SMS), whereas 5 studies used SMS in combination with additional technologies or mobile apps. The study populations were also diverse, including patients with TB, patients with TB/HIV, health care workers, and general patients attending a clinic. There was a wide range of variations in the definition of outcome measures across the studies. Among the diverse categories of outcome measures, treatment outcomes have been reported in 14 studies, but only 6 of them measured the outcome according to the standard TB treatment definitions by the World Health Organization.

CONCLUSIONS

This critical evaluation of outcomes reported in mHealth studies for TB management suggests that substantial variability exists in reporting outcome measures. To overcome the challenges in evidence synthesis for mHealth interventions, this study can provide insights into the development of a core set of outcome measures by intervention type and study design.
Augmenting Flexnerism Via Twitterism: Need for Integrating Social Media Application in Blueprinting Pedagogical Strategies for Undergraduate Medical Education (Preprint)
Authors: Banerjee Yajnavalka , Tambi Richa , Gholami Mandana , Alsheikh-Ali Alawi , Bayoumi Riad , Lansberg Peter
Published: October 2018

BACKGROUND

Flexnerism, or “competency-based medical education,” advocates that formal analytic reasoning, the kind of rational thinking fundamental to the basic sciences, especially the natural sciences, should be the foundation of physicians’ intellectual training. The complexity of 21st century health care requires rethinking of current (medical) educational paradigms. In this “Millennial Era,” promulgation of the tenets of Flexnerism in undergraduate medical education requires a design and blueprint of innovative pedagogical strategies, as the targeted learners are millennials (designated as generation-Y medical students).

OBJECTIVE

The aim of this proof-of-concept study was to identify the specific social media app platforms that are selectively preferred by generation-Y medical students in undergraduate medical education. In addition, we aimed to explore if these preferred social media apps can be used to design an effective pedagogical strategy in order to disseminate course learning objectives in the preclinical phase of a spiral curriculum.

METHODS

A cross-sectional survey was conducted by distributing a 17-item questionnaire among the first- and second-year medical students in the preclinical phase at the Mohammed Bin Rashid University of Medicine and Health Science.

RESULTS

The study identified YouTube and WhatsApp as the social media app platforms preferred by generation-Y medical students in undergraduate medical education. This study also identified the differences between female and male generation-Y medical students in terms of the use of social media apps in medical education, which we believe will assist instructors in designing pedagogical strategies to integrate social media apps. In addition, we determined the perceptions of generation-Y medical students on the implementation of social media apps in medical education. The pedagogical strategy designed using social media apps and implemented in the Biochemistry course was well accepted by generation-Y medical students and can be translated to any course in the preclinical phase of the medical curriculum. Moreover, the identified limitations of this study provide an understanding of the gaps in research in the integration of social media apps in a medical curriculum catering to generation-Y medical students.

CONCLUSIONS

21st century medical education requires effective use of social media app platforms to augment competency-based medical education: Augmentation of Flexnerism in the current scenario is possible only by the adaptation of Twitterism.
Mobile App Use for Insomnia Self-Management: Pilot Findings on Sleep Outcomes in Veterans (Preprint)
Authors: Reilly Erin D , Robinson Stephanie A , Petrakis Beth Ann , Kuhn Eric , Pigeon Wilfred R , Wiener Renda Soylemez , McInnes D Keith , Quigley Karen S
Published: October 2018

BACKGROUND

Sleep disturbance is a major health concern among US veterans who have served since 2001 in a combat theater in Iraq or Afghanistan. We report subjective and objective sleep results from a pilot trial assessing self-management–guided use of a mobile app (CBT-i Coach, which is based on cognitive behavioral therapy for insomnia) as an intervention for insomnia in military veterans.

OBJECTIVE

The primary aim of this study was to evaluate changes in subjective and objective sleep outcomes from pre to postintervention.

METHODS

Subjective outcomes included the Insomnia Severity Index, the Pittsburgh Sleep Quality Inventory, and sleep-related functional status. A wearable sleep monitor (WatchPAT) measured objective sleep outcomes, including sleep efficiency, percent rapid eye movement (REM) during sleep, sleep time, and sleep apnea. A total of 38 participants were enrolled in the study, with 18 participants being withdrawn per the protocol because of moderate or severe sleep apnea and 9 others who dropped out or withdrew. Thus, 11 participants completed the full 6-week CBT-i Coach self-management intervention (ie, completers).

RESULTS

Completer results indicated significant changes in subjective sleep measures, including reduced reports of insomnia (Z=–2.68, P=.007) from pre (mean 16.63, SD 5.55) to postintervention (mean 12.82, SD 3.74), improved sleep quality (Z=–2.37, P=.02) from pre (mean 12.82, SD 4.60) to postintervention (mean 10.73, SD 3.32), and sleep-related functioning (Z=2.675, P=.007) from pre (mean 13.86, SD 3.69) to postintervention (mean 15.379, SD 2.94). Among the objective measures, unexpectedly, objective sleep time significantly decreased from pre to postintervention (χ22=7.8, P=.02). There were no significant changes in percent REM sleep or sleep efficiency.

CONCLUSIONS

These findings suggest that the CBT-i Coach app can improve subjective sleep and that incorporating objective sleep measures into future, larger clinical trials or clinical practice may yield important information, particularly by detecting previously undetected sleep apnea.

CLINICALTRIAL

ClinicalTrials.gov NCT02392000; http://clinicaltrials.gov/ct2/show/NCT02392000
Evaluation of a Technology-Based Peer-Support Intervention Program for Preventing Postnatal Depression (Part 1): Randomized Controlled Trial (Preprint)
Authors: Shorey Shefaly , Chee Cornelia Yin Ing , Ng Esperanza Debby , Lau Ying , Dennis Cindy-Lee , Chan Yiong Huak
Published: October 2018

BACKGROUND

The frenzy of postbirth events often takes a toll on mothers’ mental well-being, leaving them susceptible to postpartum psychological disorders such as postnatal depression (PND). Social support has been found to be effective in restoring the emotional well-being of new mothers. Therefore, mothers need to be supported during the crucial postpartum period to buffer the negative after effects of childbirth and to promote healthier maternal well-being.

OBJECTIVE

This study aimed to evaluate the effectiveness of a technology-based peer-support intervention program (PIP) on maternal outcomes during the early postpartum period.

METHODS

A randomized, parallel-armed controlled trial was conducted. The study recruited 138 mothers (69 in intervention group, 69 in control group) at risk of PND from a tertiary hospital in Singapore. To support these mothers, 20 peer volunteers were recruited by word of mouth and trained by a psychiatrist in social support skills before the intervention commenced. The 4-week–long intervention included a weekly follow-up with a peer volunteer through phone calls or text messages. The intervention group received peer support in addition to the standard care offered by the hospital. The control group only received postnatal standard care. Maternal outcomes (PND, postnatal anxiety [PNA], loneliness, and perceived social support) were measured with reliable and valid instruments. Data were collected immediately postpartum, at 1 month postpartum and at 3 months postpartum. The general linear model was used to compare the groups for postpartum percentage changes in the outcome variables at first and third months, and the linear mixed model was used to compare the trend over the study period.

RESULTS

There was a statistically significant difference in Edinburgh Postnatal Depression Scale scores (d=–2.11; 95% CI −4.0 to −0.3; P=.03) between the intervention and control groups at 3 months postpartum after adjusting for covariates. The intervention group had a significant change over time compared with the control group.

CONCLUSIONS

The technology-based PIP was found to be effective in reducing the risk of PND among new mothers and showed a generally positive trend in reducing PNA and loneliness and increasing perceived social support. This study highlights the importance of training paraprofessionals to provide needed support for new mothers postpartum. A further long-term evaluation of the PIP on maternal and family outcomes and its cost-effectiveness is needed to inform clinical practices.

CLINICALTRIAL

ISRCTN Registry ISRCTN14864807; https://www.isrctn.com/ISRCTN14864807

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID)

RR2-10.2196/resprot.9416
Effective Engagement of Adolescent Asthma Patients With Mobile Health–Supporting Medication Adherence (Preprint)
Authors: Kosse Richelle C , Bouvy Marcel L , Belitser Svetlana V , de Vries Tjalling W , van der Wal Piet S , Koster Ellen S
Published: October 2018

BACKGROUND

Mobile health (mHealth) apps have the potential to support patients’ medication use and are therefore increasingly used. Apps with broad functionality are suggested to be more effective; however, not much is known about the actual use of different functionalities and the effective engagement.

OBJECTIVE

The aim of this study was to explore the use and the effective engagement of adolescents (aged 12 to 18 years) with the Adolescent Adherence Patient Tool (ADAPT).

METHODS

The ADAPT intervention consisted of an app for patients, which was connected to a management system for their pharmacist. The aim of the ADAPT intervention was to improve medication adherence and, therefore, the app contained multiple functionalities: questionnaires to monitor symptoms and adherence, medication reminders, short movies, pharmacist chat, and peer chat. For this study, data of the ADAPT study and a cluster randomized controlled trial were used. Adolescents with asthma had 6 months’ access to the ADAPT intervention, and all app usage was securely registered in a log file.

RESULTS

In total, 86 adolescents (mean age 15.0, SD 2.0 years) used the ADAPT app 17 times (range 1-113) per person. Females used the app more often than males (P=.01) and for a longer period of time (P=.03). On average, 3 different functionalities were used, and 13% of the adolescents used all functionalities of the app. The questionnaires to monitor symptoms and adherence were used by most adolescents. The total app use did not affect adherence; however, activity in the pharmacist chat positively affected medication adherence (P=.03), in particular, if patients sent messages to their pharmacist (P=.01).

CONCLUSIONS

mHealth apps for adolescents with asthma should contain different functionalities to serve the diverging needs and preferences of individual patients. Suggested key functionalities to promote use and effectiveness in adolescents with asthma are questionnaires to monitor symptoms and a health care provider chat.
Assessment of Use and Preferences Regarding Internet-Based Health Care Delivery: Cross-Sectional Questionnaire Study (Preprint)
Authors: Paslakis Georgios , Fischer-Jacobs Josefine , Pape Lars , Schiffer Mario , Gertges Raoul , Tegtbur Uwe , Zimmermann Tanja , Nöhre Mariel , de Zwaan Martina
Published: October 2018

BACKGROUND

There has been an incremental increase in the use of technology in health care delivery. Feasibility, acceptability, and efficacy of interventions based on internet technologies are supported by a growing body of evidence.

OBJECTIVE

The aim of this study was to investigate use and preferences in the general adult population in Germany for remote, internet-based interaction (eg, email, videoconferencing, electronic medical records, apps).

METHODS

A nationwide cross-sectional questionnaire survey in adults that was representative in terms of age, sex and educational level was carried out.

RESULTS

A total of 22.16% (538/2428) of survey participants reported not using the internet for work or private use. The nonuser phenotype can be described as being older, having lower educational and income status, and living in less populated areas. The majority of participants within the cohort of internet users reported that they would not consider using electronic medical records (973/1849, 52.62%), apps (988/1854, 53.29%), or emails to report symptoms (1040/1838, 56.58%); teleconference with one (1185/1852, 63.98%) or more experts (1239/1853, 66.86%); or participate in video psychotherapy (1476/1853, 79.65%) for the purpose of medical consultation or treatment. Older age and lower educational level were the most robust predictors of assumed future denial of use.

CONCLUSIONS

Our results point toward low use and preference rates among the general population for the use of telemedicine. It also seems that those who might benefit from telemedical interventions the most, are, in fact, those who are most hesitating. These low use and preference rates of eHealth should be considered prior to designing and providing future telemedical care, supporting the need for easy-to-use, data secure solutions.
Framing Mental Health Within Digital Games: An Exploratory Case Study of Hellblade (Preprint)
Authors: Fordham Joseph , Ball Christopher
Published: October 2018

BACKGROUND

Researchers and therapists have increasingly turned to digital games for new forms of treatments and interventions for people suffering from a variety of mental health issues. Yet, the depiction of mental illness within digital games typically promotes stigmatized versions of those with mental health concerns. Recently, more games have attempted to implement more realistic and respectful depictions of mental health conditions.

OBJECTIVE

This paper presents an exploratory analysis of a contemporary game that has the potential to change the way researchers, practitioners, and game designers approach topics of mental health within the context of gaming.

METHODS

A case study of Hellblade: Senua's Sacrifice was conducted using frame analysis to show how key design choices for this game present the potential for new ways of approaching games and mental health.

RESULTS

A case study of Hellblade’s development shows how research-informed collaborative design with mental health practitioners, scientists, and individuals with mental health problems can lead to a realistic depiction of mental illness in games. Furthermore, the use of frame analysis demonstrates how to harness narrative, mechanics, and technology to create embodied experiences of mental health, which has the potential to promote empathetic understanding.

CONCLUSIONS

This paper highlights an exemplary case of collaborative commercial game design for entertainment purposes in relation to mental health. Understanding the success of Hellblade's depiction of psychosis can improve serious games research and design. Further research must continue to provide deeper analysis of not only games that depict mental illness, but also the design process behind them.
A Stroke Risk Detection: Improving Hybrid Feature Selection Method (Preprint)
Authors: Zhang Yonglai , Zhou Yaojian , Zhang Dongsong , Song Wenai
Published: October 2018

BACKGROUND

Stroke is one of the most common diseases that cause mortality. Detecting the risk of stroke for individuals is critical yet challenging because of a large number of risk factors for stroke.

OBJECTIVE

This study aimed to address the limitation of ineffective feature selection in existing research on stroke risk detection. We have proposed a new feature selection method called weighting- and ranking-based hybrid feature selection (WRHFS) to select important risk factors for detecting ischemic stroke.

METHODS

WRHFS integrates the strengths of various filter algorithms by following the principle of a wrapper approach. We employed a variety of filter-based feature selection models as the candidate set, including standard deviation, Pearson correlation coefficient, Fisher score, information gain, Relief algorithm, and chi-square test and used sensitivity, specificity, accuracy, and Youden index as performance metrics to evaluate the proposed method.

RESULTS

This study chose 792 samples from the electronic records of 13,421 patients in a community hospital. Each sample included 28 features (24 blood test features and 4 demographic features). The results of evaluation showed that the proposed method selected 9 important features out of the original 28 features and significantly outperformed baseline methods. Their cumulative contribution was 0.51. The WRHFS method achieved a sensitivity of 82.7% (329/398), specificity of 80.4% (317/394), classification accuracy of 81.5% (645/792), and Youden index of 0.63 using only the top 9 features. We have also presented a chart for visualizing the risk of having ischemic strokes.

CONCLUSIONS

This study has proposed, developed, and evaluated a new feature selection method for identifying the most important features for building effective and parsimonious models for stroke risk detection. The findings of this research provide several novel research contributions and practical implications.
Identifying Key Target Audiences for Public Health Campaigns: Leveraging Machine Learning in the Case of Hookah Tobacco Smoking (Preprint)
Authors: Chu Kar-Hai , Colditz Jason , Malik Momin , Yates Tabitha , Primack Brian
Published: October 2018

BACKGROUND

Hookah tobacco smoking (HTS) is a particularly important issue for public health professionals to address owing to its prevalence and deleterious health effects. Social media sites can be a valuable tool for public health officials to conduct informational health campaigns. Current social media platforms provide researchers with opportunities to better identify and target specific audiences and even individuals. However, we are not aware of systematic research attempting to identify audiences with mixed or ambivalent views toward HTS.

OBJECTIVE

The objective of this study was to (1) confirm previous research showing positively skewed HTS sentiment on Twitter using a larger dataset by leveraging machine learning techniques and (2) systematically identify individuals who exhibit mixed opinions about HTS via the Twitter platform and therefore represent key audiences for intervention.

METHODS

We prospectively collected tweets related to HTS from January to June 2016. We double-coded sentiment for a subset of approximately 5000 randomly sampled tweets for sentiment toward HTS and used these data to train a machine learning classifier to assess the remaining approximately 556,000 HTS-related Twitter posts. Natural language processing software was used to extract linguistic features (ie, language-based covariates). The data were processed by machine learning tools and algorithms using R. Finally, we used the results to identify individuals who, because they had consistently posted both positive and negative content, might be ambivalent toward HTS and represent an ideal audience for intervention.

RESULTS

There were 561,960 HTS-related tweets: 373,911 were classified as positive and 183,139 were classified as negative. A set of 12,861 users met a priori criteria indicating that they posted both positive and negative tweets about HTS.

CONCLUSIONS

Sentiment analysis can allow researchers to identify audience segments on social media that demonstrate ambiguity toward key public health issues, such as HTS, and therefore represent ideal populations for intervention. Using large social media datasets can help public health officials to preemptively identify specific audience segments that would be most receptive to targeted campaigns.
Estimation of the Population Size of Men Who Have Sex With Men in Vietnam: Social App Multiplier Method (Preprint)
Authors: Son Vo Hai , Safarnejad Ali , Nga Nguyen Thien , Linh Vu Manh , Tu Le Thi Cam , Manh Pham Duc , Long Nguyen Hoang , Abdul-Quader Abu
Published: October 2018

BACKGROUND

Although the prevalence of HIV among men who have sex with men (MSM) in Vietnam has been increasing in recent years, there are no estimates of the population size of MSM based on tested empirical methods.

OBJECTIVE

This study aimed to estimate the size of the MSM population in 12 provinces in Vietnam and extrapolate from those areas to generate a national population estimate of MSM. A secondary aim of this study was to compare the feasibility of obtaining the number of users of a mobile social (chat and dating) app for MSM using 3 different approaches.

METHODS

This study used the social app multiplier method to estimate the size of MSM populations in 12 provinces using the count of users on a social app popular with MSM in Vietnam as the first data source and a questionnaire propagated through the MSM community using respondent-driven sampling as the second data source. A national estimation of the MSM population is extrapolated from the results in the study provinces, and the percentage of MSM reachable through online social networks is clarified.

RESULTS

The highest MSM population size among the 12 provinces is estimated in Hanoi and the lowest is estimated in Binh Dinh. On average, 37% of MSM in the provinces surveyed had used the social app Jack’d in the last 30 days (95% CI 27-48). Extrapolation of the results from the study provinces with reliable estimations results in an estimated national population of 178,000 MSM (95% CI 122,000-512,000) aged 15 to 49 years in Vietnam. The percentage of MSM among adult males aged 15 to 49 years in Vietnam is 0.68% (95% CI 0.46-1.95).

CONCLUSIONS

This study is the first attempt to empirically estimate the population of MSM in Vietnam and highlights the feasibility of reaching a large proportion of MSM through a social app. The estimation reported in this study is within the bounds suggested by the Joint United Nations Programme on HIV/AIDS. This study provides valuable information on MSM population sizes in provinces where reliable estimates were obtained, which they can begin to work with in program planning and resource allocation.
Feasibility of a Sleep Self-Management Intervention in Pregnancy Using a Personalized Health Monitoring Device: Protocol for a Pilot Randomized Controlled Trial (Preprint)
Authors: Hawkins Marquis , Iradukunda Favorite , Paterno Mary
Published: October 2018

BACKGROUND

Sleep disruptions are common during pregnancy and associated with increased risk of adverse maternal outcomes such as preeclampsia, gestational diabetes, prolonged labor, and cesarean birth. Given the morbidity associated with poor sleep, cost-effective approaches to improving sleep that can be disseminated in community or clinical settings are needed. Personal health monitor (PHM) devices offer an opportunity to promote behavior change, but their acceptability and efficacy at improving sleep in pregnant women are unknown.

OBJECTIVE

The goal of the paper is to describe the protocol for an ongoing pilot randomized controlled trial that aims to establish the feasibility, acceptability, and preliminary efficacy of using a PHM device (Shine 2, Misfit) to promote sleep during pregnancy.

METHODS

The proposed pilot study is a 12-week, parallel arm, randomized controlled trial. Pregnant women, at 24 weeks gestation, will be randomized at a 1:1 ratio to a 12-week sleep education plus PHM device group or a sleep education alone comparison group. The primary outcomes will be measures of feasibility (ie, recruitment, enrollment, adherence) and acceptability (ie, participant satisfaction). The secondary outcomes will be self-reported sleep quality and duration, excessive daytime sleepiness, fatigue, and depressive symptoms.

RESULTS

Recruitment for this study began in September 2017 and ended in March 2018. Data collection for the primary and secondary aims was completed in August 2018. We anticipate that the data analysis for primary and secondary aims will be completed by December 2019. The results from this trial will inform the development of a larger National Institutes of Health grant application to test the efficacy of an enhanced version of the sleep intervention that we plan to submit in the year 2020.

CONCLUSIONS

This study will be the first to apply a PHM device as a tool for promoting self-management of sleep among pregnant women. PHM devices have the potential to facilitate behavioral interventions because they include theory-driven, self-regulatory techniques such as behavioral self-monitoring. The results of the study will inform the development of a sleep health intervention for pregnant women.

CLINICALTRIAL

ClinicalTrials.gov NCT03783663; https://clinicaltrials.gov/ct2/show/NCT03783663 (Archived by WebCite at http://www.webcitation.org/779Ou8hon)

INTERNATIONAL REGISTERED REPOR

DERR1-10.2196/12455
Relating Instructional Design Components to the Effectiveness of Internet-Based Mindfulness Interventions: A Critical Interpretive Synthesis (Preprint)
Authors: Lippmann Marie , Laudel Helena , Heinzle Marlene , Narciss Susanne
Published: October 2018

BACKGROUND

Internet-based mindfulness interventions are a promising approach to address challenges in the dissemination and implementation of mindfulness interventions, but it is unclear how the instructional design components of such interventions are associated with intervention effectiveness.

OBJECTIVE

The objective of this study was to identify the instructional design components of the internet-based mindfulness interventions and provide a framework for the classification of those components relative to the intervention effectiveness.

METHODS

The critical interpretive synthesis method was applied. In phase 1, a strategic literature review was conducted to generate hypotheses for the relationship between the effectiveness of internet-based mindfulness interventions and the instructional design components of those interventions. In phase 2, the literature review was extended to systematically explore and revise the hypotheses from phase 1.

RESULTS

A total of 18 studies were identified in phase 1; 14 additional studies were identified in phase 2. Of the 32 internet-based mindfulness interventions, 18 were classified as more effective, 11 as less effective, and only 3 as ineffective. The effectiveness of the interventions increased with the level of support provided by the instructional design components. The main difference between effective and ineffective interventions was the presence of just-in-time information in the form of reminders. More effective interventions included more supportive information (scores: 1.91 in phases 1 and 2) than less effective interventions (scores: 1.00 in phase 1 and 1.80 in phase 2), more part-task practice (scores: 1.18 in phase 1 and 1.60 in phase 2) than less effective interventions (scores: 0.33 in phase 1 and 1.40 in phase 2), and provided more just-in-time information (scores: 1.35 in phase 1 and 1.67 in phase 2) than less effective interventions (scores: 0.83 in phase 1 and 1.60 in phase 2). The average duration of more effective, less effective, and ineffective interventions differed for the studies of phase 1, with more effective interventions taking up more time (7.45 weeks) than less effective (4.58 weeks) or ineffective interventions (3 weeks). However, this difference did not extend to the studies of phase 2, with comparable average durations of effective (5.86 weeks), less effective (5.6 weeks), and ineffective (7 weeks) interventions.

CONCLUSIONS

Our results suggest that to be effective, internet-based mindfulness interventions must contain 4 instructional design components: formal learning tasks, supportive information, part-task practice, and just-in-time information. The effectiveness of the interventions increases with the level of support provided by each of these instructional design components.