Collection and visualization of dietary behavior and reasons for eating using Twitter

AI nutritionist: Intelligent software as the next generation pioneer of precision nutrition

With the rapid development of information technology and artificial intelligence (AI), people have acquired the abilities and are encouraged to develop intelligent tools and software, which begins to shed light on intelligent and precise food nutrition. Despite the rapid development of such software, disparities still exist in terms of methodology, contents, and implementation strategies. Hence, a set of panoramic profiles is urgently needed to elucidate their values and guide their future development. Here a comprehensive review was conducted aiming to summarize and compare the objects, contents, intelligent algorithms, and functions realized by the already released software in current research. Consequently, 177 AI nutritionists in recent years were collected and analyzed. The advantages, limitations, and trends concerning their application scenarios were analyzed. It was found that AI nutritionists have been gradually advancing the production modes and efficiency of food recognition, dietary recording/monitoring, nutritional assessment, and nutrient/recipe recommendation. Most AI nutritionists have a relatively low level of intelligence. However, new trends combining advanced AI algorithms, intelligent sensors and big data are coming with new applications in real-time and precision nutrition. AI models concerning molecular-level behaviors are becoming the new focus to drive AI nutritionists. Multi-center and multi-level studies have also gradually been realized to be necessary.

Who We Seek and What We Eat? Sources of Food Choice Inspirations and Their Associations with Adult Dietary Patterns before and during the COVID-19 Lockdown in New Zealand

Research shows the shaping of food choices often occurs at home, with the family widely recognised as significant in food decisions. However, in this digital age, our eating habits and decision-making processes are also determined by smartphone apps, celebrity chefs, and social media. The ‘COVID Kai Survey’ online questionnaire assessed cooking and shopping behaviours among New Zealanders during the 2020 COVID-19 ‘lockdown’ using a cross-sectional study design. This paper examines how sources of food choice inspirations (cooking-related advice and the reasons for recipe selection) are related to dietary patterns before and during the lockdown. Of the 2977 participants, those influenced by nutrition and health experts (50.9% before; 53.9% during the lockdown) scored higher for the healthy dietary pattern. Participants influenced by family and friends (35% before; 29% during the lockdown) had significantly higher scores for the healthy and the meat dietary patterns, whereas participants influenced by celebrity cooks (3.8% before; 5.2% during the lockdown) had significantly higher scores in the meat dietary pattern. There was no evidence that associations differed before and during the lockdown. The lockdown was related to modified food choice inspiration sources, notably an increase in ‘comforting’ recipes as a reason for recipe selection (75.8%), associated with higher scoring in the unhealthy dietary pattern during the lockdown. The lockdown in New Zealand saw an average decrease in nutritional quality of diets in the ‘COVID Kai Survey’, which could be partly explained by changes in food choice inspiration sources.

Bystander Prevention for Sexual Violence: #HowIWillChange and Gaps in Twitter Discourse

Twitter has rapidly gained popularity as a space for the public to discuss sexual violence (SV) prevention due to a number of high-profile SV cases. This study aimed to examine Twitter discourse on SV prevention through the hashtag #HowIWillChange, which encouraged Twitter users to come forward and report plans to engage in bystander prevention. We analyzed 1,493 #HowIWillChange tweets from October 2017 through a directed content analysis approach rooted in an evidence-based framework for the continuum of bystander intervention. We assessed emergent themes around how Twitter users discuss SV to identify gaps and misinformation in public Twitter discourse. Although Twitter users discussed a range of prevention strategies, misinformation was also spread, including perpetuation of the myth that only strangers commit rape, that only male children need lessons on consent, and that SV prevention vilifies men. These results can inform health promotion programs aiming to educate the public on bystander prevention.

Efficacy and acceptability of a web platform to teach nutrition education to children

Introduction

Introduction: Nutrition Education (NE) has been identified as a key factor to prevent children obesity. Teachers and dietitians are the professionals in charge of transmitting this knowledge to children; however, it has been identified that they do not possess either proper training, or the proper tools to perform this activity. Objectives: to evaluate the acceptability and usability of a NE Internet platform and its two "Serious Games" (SGs) among a sample of elementary school teachers, dietitians, and education students. In addition, to evaluate the efficacy of this platform to teach NE in a sample of children aged 9 to 12 years. Methods: a total of 66 NE professionals and 135 children participated. Usability and acceptability questionnaires of the platform and an instrument to measure the acceptability, immersion, and playability of the SGs were administered to the professionals. The children fulfilled a questionnaire on nutritional knowledge. Descriptive statistics analyzed the main responses of the professionals involved, and an ANOVA compared the differences observed. For the children´s data a t-test of repeated samples and a repeated-measures ANOVA were performed. Results: dietitians and education students responded with a favorable opinion about the platform; however, the scores given by all professionals to the SGs ranged from low to moderate. Children increased their nutritional knowledge from pre to post evaluation (p < 0.001). This increase was observed in 10-year-old children and in children with 11 to 12 years of age, but not in 9-year-olds. Conclusions: this platform proved to be an effective tool to increase children's nutritional knowledge. Professionals expressed a medium level in terms of acceptability and usability for this platform, but also effectiveness in providing NE to children.

Tailored smartphone intervention to promote healthy eating among Brazilian adolescents: a randomised controlled trial protocol

INTRODUCTION

Adolescent eating patterns are characterised by high consumption of unhealthy foods, which has resulted in an increasing prevalence of overweight and chronic diseases. It is crucial to promote healthy eating habits, and nutritional interventions based on the transtheoretical model have been found to be especially effective. Mobile health strategies also seem promising for adolescents. This study aims to outline a smartphone intervention via WhatsApp for adolescents to promote healthy eating consumption, better nutritional knowledge, self-efficacy in the adoption of healthy practices and progress through the stages of change.

METHODS AND ANALYSIS

There will be three distinct groups in this randomised study: a general intervention group (GG), in which the participants will receive the same healthy eating messages, based on the Brazilian food guide; a tailored intervention group (TG), in which the participants will receive healthy eating messages based on their stage of change; and a control group (CG), in which participants will receive messages on a different theme. Possession of a smartphone, use of WhatsApp and being a senior student (16-19 years) from a public school of the Federal District of Brazil will be the study's inclusion criteria. Rural schools will be excluded. The sample size estimated is 390 individuals: 38 in the GG, 314 in the TG and 38 in the CG. The intervention will last 6 weeks, with a daily message sent to the students. We will investigate nutritional knowledge, self-efficacy in the adoption of healthy eating practices, food consumption and stages of change using preintervention and postintervention questionnaires. Memorisation of the messages will be also assessed.

ETHICS AND DISSEMINATION

The study was approved by the University of Brasília, School of Health Sciences and Research Ethics Committee. At the end of the study, the participating schools will receive a printed report with the main results of the intervention.

TRIAL REGISTRATION NUMBER

RBR-5b9jk7.

Sharing the pain: an observational analysis of Twitter and pain in Ireland

INTRODUCTION

Studies involving Twitter and chronic pain can provide highly valuable patient-generated information. The aim of this paper was to examine pain-related tweets in Ireland over a 2-week period from 22 June 2017 to 5 July 2017 using pain-related keywords. We wished to identify Twitter user gender profile; most common discussion topics; sentiment analysis; and dissemination of tweets.

METHODS

A third-party data analytics company conducted a Twitter social media analysis over a randomly chosen 14-day period between the dates 22 June and 5 July 2017. All relevant keywords were included in the search. Author group consensus yielded 24 terms. Geographical location was restricted to Ireland. A computational sentiment dictionary was used to provide a rating of the emotional properties of the text on a 9-point scale from -5 to +4 of negative to positive sentiment. Dissemination was calculated by the number of times the tweet was displayed ('impressions').

RESULTS

There were 941 tweets identified during the study from 715 contributors. These generated 2.88 million impressions. The most frequently occurring keywords were headache (n=321); migraine (n=147); back pain (n=123); cannabis (n=114); and chronic pain (n=85). There were 1.94 times as many tweets from females as males. The highest proportion of tweets from female users was in the fibromyalgia (83%) and migraine (60%) categories; and from males in the sciatica (35%), chronic pain (34%) and back pain (32%) categories. Cannabis-related tweets reflected mostly non-personal content (90%), with a highly positive sentiment, and the highest number of impressions per tweet. The largest amount of advice was offered in the back pain category. Reposting of other users' content ('retweets') was more likely to contain a positive sentiment.

CONCLUSION

A substantial discussion of pain-related topics took place on Twitter during our study period. This provided real-time, dynamic information from individuals on discussion topics in pain medicine. This can be used to gain a greater understanding of the pain experience. As patients are increasingly acquiring healthcare information through online sources, high-quality information from approved sources should be promoted on such platforms.

Usability of Food Size Aids in Mobile Dietary Reporting Apps for Young Adults: Randomized Controlled Trial

Background

Young adults are more likely to use self-managed dietary reporting apps. However, there is scant research examining the user experience of different measurement approaches for mobile dietary reporting apps when dealing with a wide variety of food shapes and container sizes.

Objective

Field user experience testing was conducted under actual meal conditions to assess the accuracy, efficiency, and subjective reaction of three food portion measurement methods embedded in a developed mobile app. Key-in–based aid (KBA), commonly used in many current apps, relies on the user’s ability to key in volumes or weights. Photo-based aid (PBA) extends traditional assessment methods, allowing users to scroll, observe, and select a reduced-size image from a set of options. Gesture-based aid (GBA) is a new experimental approach in which the user makes finger movements on the screen to roughly describe food portion boundaries accompanied by a background reference.

Methods

A group of 124 young adults aged 19 to 26 years was recruited for a head-to-head randomized comparison and divided into 3 groups: a KBA (n=42) control group and PBA (n=41) and GBA (n=41) experimental groups. In total, 3 meals (ie, breakfast, lunch, and dinner) were served in a university cafeteria. Participants were provided with 25 dishes and beverages for selection, with a variety of food shapes and containers that reflect everyday life conditions. The accuracy of and time spent on realistic interaction during food portion estimation and the subjective reaction of each aid were recorded and analyzed.

Results

Participants in the KBA group provided the highest accuracy in terms of hash brown weight (P=.004) and outperformed PBA or GBA for many soft drinks in cups. PBA had the best results for a cylindrical hot dog (P<.001), irregularly shaped pork chop (P<.001), and green tea beverage (660 mL; P<.001). GBA outperformed PBA for most drinks, and GBA outperformed KBA for some vegetables. The GBA group spent significantly more time assessing food items than the KBA and PBA groups. For each aid, the overall subjective reaction based on the score of the System Usability Scale was not significantly different.

Conclusions

Experimental results show that each aid had some distinguishing advantages. In terms of user acceptance, participants considered all 3 aids to be usable. Furthermore, users’ subjective opinions regarding measurement accuracy contradicted the empirical findings. Future work will consider the use of each aid based on food or container shape and integrate the various advantages of the 3 different aids for better results. Our findings on the use of portion size aids are based on realistic and diverse food items, providing a useful reference for future app improvement of an effective, evidence-based, and acceptable feature.

Trial Registration

International Standard Randomized Controlled Trial Registry ISRCTN36710750; http://www.controlled-trials.com/ISRCTN36710750.

A Systematic Review of Ecological Momentary Assessment of Diet: Implications and Perspectives for Nutritional Epidemiology

The ecological momentary assessment (EMA) of eating behaviors represents an innovative, detailed and valid approach to capture the complexity of food intake and to overcome limitations of traditional dietary assessment methods. Moreover, EMA studies might generate a large variety of data (e.g., dietary, behavioral, physical, sociopsychological, and contextual information), thereby enabling to examine concurrent exposures and events. Due to the increasing number of studies in this field of research, here we systematically reviewed EMA methods for the assessment of dietary intake in epidemiological studies, and discussed implications and perspectives for future research. Our study summarized several protocols and platforms that may be applied to assess diet in terms of eating frequency, choices, and habits. Nearly 38% of studies used an event-contingent strategy by asking participants to report foods and beverages consumed in real-time at each eating occasion. Instead, approximately 55% of studies used a signal-contingent prompting approach that notified the participants to record their dietary consumption. The remaining studies used a combination of event- and signal-contingent protocols to compare their accuracy or to improve the assessment of dietary data. Although both approaches might improve the accuracy and ecological validity of dietary assessment—also reducing the burden for participants—some limitations should nevertheless be considered. Despite these limitations, our systematic review pointed out that EMA can be applied in various fields of nutritional epidemiology, from the identification of determinants of dietary habits in healthy people to the management of patients with eating or metabolic disorders. However, more efforts should be encouraged to improve the validity and the reliability of EMA and to provide further technological innovations for public health research and interventions.

Mobile Ecological Momentary Diet Assessment Methods for Behavioral Research: Systematic Review

BACKGROUND

New methods for assessing diet in research are being developed to address the limitations of traditional dietary assessment methods. Mobile device-assisted ecological momentary diet assessment (mEMDA) is a new dietary assessment method that has not yet been optimized and has the potential to minimize recall biases and participant burden while maximizing ecological validity. There have been limited efforts to characterize the use of mEMDA in behavioral research settings.

OBJECTIVE

The aims of this study were to summarize mEMDA protocols used in research to date, to characterize key aspects of these assessment approaches, and to discuss the advantages and disadvantages of mEMDA compared with the traditional dietary assessment methods as well as implications for future mEMDA research.

METHODS

Studies that used mobile devices and described mEMDA protocols to assess dietary intake were included. Data were extracted according to Preferred Reporting of Systematic Reviews and Meta-Analyses and Cochrane guidelines and then synthesized narratively.

RESULTS

The review included 20 studies with unique mEMDA protocols. Of these, 50% (10/20) used participant-initiated reports of intake at eating events (event-contingent mEMDA), and 50% (10/20) used researcher-initiated prompts requesting that participants report recent dietary intake (signal-contingent mEMDA). A majority of the study protocols (60%, 12/20) enabled participants to use mobile phones to report dietary data. Event-contingent mEMDA protocols most commonly assessed diet in real time, used dietary records for data collection (60%, 6/10), and provided estimates of energy and nutrient intake (60%, 6/10). All signal-contingent mEMDA protocols used a near real-time recall approach with unannounced (ie, random) abbreviated diet surveys. Most signal-contingent protocols (70%, 7/10) assessed the frequency with which (targeted) foods or food groups were consumed. Relatively few (30%, 6/20) studies compared mEMDA with the traditional dietary assessment methods.

CONCLUSIONS

This review demonstrates that mEMDA has the potential to reduce participant burden and recall bias, thus advancing the field beyond current dietary assessment methods while maximizing ecological validity.

Use of social network analysis in the development, dissemination, implementation, and sustainability of health behavior interventions for adults: A systematic review

Interest in conceptualizing, measuring, and applying social network analysis (SNA) in public health has grown tremendously in recent years. While these studies have broadened our understanding of the role that social networks play in health, there has been less research that has investigated the application of SNA to inform health-related interventions. This systematic review aimed to capture the current applied use of SNA in the development, dissemination, implementation, and sustainability of health behavior interventions for adults. We identified 52 articles published between 2004 and 2016. A wide variety of study settings were identified, most commonly in the US context and most often related to sexual health and HIV prevention. We found that 38% of articles explicitly applied SNA to inform some aspect of interventions. Use of SNA to inform intervention development (as opposed to dissemination, implementation, or sustainability) was most common. The majority of articles represented in this review (n = 39) were quantitative studies, and 13 articles included a qualitative component. Partial networks were most represented across articles, and over 100 different networks measures were assessed. The most commonly described measures were network density, size, and degree centrality. Finally, very few articles defined SNA and not all articles using SNA were theoretically-informed. Given the nascent and heterogeneous state of the literature in this area, this is an important time for the field to coalesce on terminology, measures, and theoretical frameworks. We highlight areas for researchers to advance work on the application of SNA in the design, dissemination, implementation and sustainability of behavioral interventions.

How has big data contributed to obesity research? A review of the literature

There has been growing interest in the potential of ‘big data’ to enhance our understanding in medicine and public health. Although there is no agreed definition of big data, accepted critical components include greater volume, complexity, coverage and speed of availability. Much of these data are ‘found’ (as opposed to ‘made’), in that they have been collected for non-research purposes, but could include valuable information for research. The aim of this paper is to review the contribution of ‘found’ data to obesity research to date, and describe the benefits and challenges encountered. A narrative review was conducted to identify and collate peer-reviewed research studies. Database searches conducted up to September 2017 found original studies using a variety of data types and sources. These included: retail sales, transport, geospatial, commercial weight management data, social media, and smartphones and wearable technologies. The narrative review highlights the variety of data uses in the literature: describing the built environment, exploring social networks, estimating nutrient purchases or assessing the impact of interventions. The examples demonstrate four significant ways in which ‘found’ data can complement conventional ‘made’ data: firstly, in moving beyond constraints in scope (coverage, size and temporality); secondly, in providing objective, quantitative measures; thirdly, in reaching hard-to-access population groups; and lastly in the potential for evaluating real-world interventions. Alongside these opportunities, ‘found’ data come with distinct challenges, such as: ethical and legal questions around access and ownership; commercial sensitivities; costs; lack of control over data acquisition; validity; representativeness; finding appropriate comparators; and complexities of data processing, management and linkage. Despite widespread recognition of the opportunities, the impact of ‘found’ data on academic obesity research has been limited. The merit of such data lies not in their novelty, but in the benefits they could add over and above, or in combination with, conventionally collected data.

#MyDepressionLooksLike: Examining Public Discourse About Depression on Twitter

BACKGROUND

Social media provides a context for billions of users to connect, express sentiments, and provide in-the-moment status updates. Because Twitter users tend to tweet emotional updates from daily life, the platform provides unique insights into experiences of mental health problems. Depression is not only one of the most prevalent health conditions but also carries a social stigma. Yet, opening up about one's depression and seeking social support may provide relief from symptoms.

OBJECTIVE

The aim of this study was to examine the public discourse of the trending hashtag #MyDepressionLooksLike to look more closely at how users talk about their depressive symptoms on Twitter.

METHODS

We captured 3225 original content tweets for the hashtag #MyDepressionLooksLike that circulated in May of 2016. Eliminating public service announcements, spam, and tweets with links to pictures or videos resulted in a total of 1978 tweets. Using qualitative content analysis, we coded the tweets to detect themes.

RESULTS

The content analysis revealed seven themes: dysfunctional thoughts, lifestyle challenges, social struggles, hiding behind a mask, apathy and sadness, suicidal thoughts and behaviors, and seeking relief.

CONCLUSIONS

The themes revealed important information about the content of the public messages that people share about depression on Twitter. More research is needed to understand the effects of the hashtag on increasing social support for users and reducing social stigma related to depression.

Perspective: Randomized Controlled Trials Are Not a Panacea for Diet-Related Research

Research into the role of diet in health faces a number of methodologic challenges in the choice of study design, measurement methods, and analytic options. Heavier reliance on randomized controlled trial (RCT) designs is suggested as a way to solve these challenges. We present and discuss 7 inherent and practical considerations with special relevance to RCTs designed to study diet: 1) the need for narrow focus; 2) the choice of subjects and exposures; 3) blinding of the intervention; 4) perceived asymmetry of treatment in relation to need; 5) temporal relations between dietary exposures and putative outcomes; 6) strict adherence to the intervention protocol, despite potential clinical counter-indications; and 7) the need to maintain methodologic rigor, including measuring diet carefully and frequently. Alternatives, including observational studies and adaptive intervention designs, are presented and discussed. Given high noise-to-signal ratios interjected by using inaccurate assessment methods in studies with weak or inappropriate study designs (including RCTs), it is conceivable and indeed likely that effects of diet are underestimated. No matter which designs are used, studies will require continued improvement in the assessment of dietary intake. As technology continues to improve, there is potential for enhanced accuracy and reduced user burden of dietary assessments that are applicable to a wide variety of study designs, including RCTs.

Leveraging Social Media to Promote Public Health Knowledge: Example of Cancer Awareness via Twitter

Background

As social media becomes increasingly popular online venues for engaging in communication about public health issues, it is important to understand how users promote knowledge and awareness about specific topics.

Objective

The aim of this study is to examine the frequency of discussion and differences by race and ethnicity of cancer-related topics among unique users via Twitter.

Methods

Tweets were collected from April 1, 2014 through January 21, 2015 using the Twitter public streaming Application Programming Interface (API) to collect 1% of public tweets. Twitter users were classified into racial and ethnic groups using a new text mining approach applied to English-only tweets. Each ethnic group was then analyzed for frequency in cancer-related terms within user timelines, investigated for changes over time and across groups, and measured for statistical significance.

Results

Observable usage patterns of the terms "cancer", "breast cancer", "prostate cancer", and "lung cancer" between Caucasian and African American groups were evident across the study period. We observed some variation in the frequency of term usage during months known to be labeled as cancer awareness months, particularly September, October, and November. Interestingly, we found that of the terms studied, "colorectal cancer" received the least Twitter attention.

Conclusions

The findings of the study provide evidence that social media can serve as a very powerful and important tool in implementing and disseminating critical prevention, screening, and treatment messages to the community in real-time. The study also introduced and tested a new methodology of identifying race and ethnicity among users of the social media. Study findings highlight the potential benefits of social media as a tool in reducing racial and ethnic disparities.

A new source of data for public health surveillance: Facebook likes

Background

Investigation into personal health has become focused on conditions at an increasingly local level, while response rates have declined and complicated the process of collecting data at an individual level. Simultaneously, social media data have exploded in availability and have been shown to correlate with the prevalence of certain health conditions.

Objective

Facebook likes may be a source of digital data that can complement traditional public health surveillance systems and provide data at a local level. We explored the use of Facebook likes as potential predictors of health outcomes and their behavioral determinants.

Methods

We performed principal components and regression analyses to examine the predictive qualities of Facebook likes with regard to mortality, diseases, and lifestyle behaviors in 214 counties across the United States and 61 of 67 counties in Florida. These results were compared with those obtainable from a demographic model. Health data were obtained from both the 2010 and 2011 Behavioral Risk Factor Surveillance System (BRFSS) and mortality data were obtained from the National Vital Statistics System.

Results

Facebook likes added significant value in predicting most examined health outcomes and behaviors even when controlling for age, race, and socioeconomic status, with model fit improvements (adjusted R²) of an average of 58% across models for 13 different health-related metrics over basic sociodemographic models. Small area data were not available in sufficient abundance to test the accuracy of the model in estimating health conditions in less populated markets, but initial analysis using data from Florida showed a strong model fit for obesity data (adjusted R²=.77).

Conclusions

Facebook likes provide estimates for examined health outcomes and health behaviors that are comparable to those obtained from the BRFSS. Online sources may provide more reliable, timely, and cost-effective county-level data than that obtainable from traditional public health surveillance systems as well as serve as an adjunct to those systems.

Twitter and Health Science Research

Twitter is a communication platform that can be used to conduct health science research, but a full understanding of its use remains unclear. The purpose of this narrative literature review was to examine how Twitter is currently being used to conduct research in the health sciences and to consider how it might be used in the future. A time-limited search of the health-related research was conducted, which resulted in 31 peer-reviewed articles for review. Information relating to how Twitter is being used to conduct research was extracted and categorized, and an explanatory narrative was developed. To date, Twitter is largely being used to conduct large-scale studies, but this research is complicated by challenges relating to collecting and analyzing big data. Conversely, the use of Twitter to conduct small-scale investigations appears to be relatively unexplored.

The use of crowdsourcing for dietary self-monitoring: crowdsourced ratings of food pictures are comparable to ratings by trained observers

OBJECTIVE

Crowdsourcing dietary ratings for food photographs, which uses the input of several users to provide feedback, has potential to assist with dietary self-monitoring.

MATERIALS AND METHODS

This study assessed how closely crowdsourced ratings of foods and beverages contained in 450 pictures from the Eatery mobile app as rated by peer users (fellow Eatery app users) (n = 5006 peers, mean 18.4 peer ratings/photo) using a simple 'healthiness' scale were related to the ratings of the same pictures by trained observers (raters). In addition, the foods and beverages present in each picture were categorized and the impact on the peer rating scale by food/beverage category was examined. Raters were trained to provide a 'healthiness' score using criteria from the 2010 US Dietary Guidelines.

RESULTS

The average of all three raters' scores was highly correlated with the peer healthiness score for all photos (r = 0.88, p<0.001). Using a multivariate linear model (R(2) = 0.73) to examine the association of peer healthiness scores with foods and beverages present in photos, peer ratings were in the hypothesized direction for both foods/beverages to increase and ones to limit. Photos with fruit, vegetables, whole grains, and legumes, nuts, and seeds (borderline at p = 0.06) were all associated with higher peer healthiness scores, and processed foods (borderline at p = 0.06), food from fast food restaurants, refined grains, red meat, cheese, savory snacks, sweets/desserts, and sugar-sweetened beverages were associated with lower peer healthiness scores.

CONCLUSIONS

The findings suggest that crowdsourcing holds potential to provide basic feedback on overall diet quality to users utilizing a low burden approach.

Factors related to sustained use of a free mobile app for dietary self-monitoring with photography and peer feedback: retrospective cohort study

BACKGROUND

Healthy eating interventions that use behavior change techniques such as self-monitoring and feedback have been associated with stronger effects. Mobile apps can make dietary self-monitoring easy with photography and potentially reach huge populations.

OBJECTIVE

The aim of the study was to assess the factors related to sustained use of a free mobile app ("The Eatery") that promotes healthy eating through photographic dietary self-monitoring and peer feedback.

METHODS

A retrospective analysis was conducted on the sample of 189,770 people who had downloaded the app and used it at least once between October 2011 and April 2012. Adherence was defined based on frequency and duration of self-monitoring. People who had taken more than one picture were classified as "Users" and people with one or no pictures as "Dropouts". Users who had taken at least 10 pictures and used the app for at least one week were classified as "Actives", Users with 2-9 pictures as "Semi-actives", and Dropouts with one picture as "Non-actives". The associations between adherence, registration time, dietary preferences, and peer feedback were examined. Changes in healthiness ratings over time were analyzed among Actives.

RESULTS

Overall adherence was low-only 2.58% (4895/189,770) used the app actively. The day of week and time of day the app was initially used was associated with adherence, where 20.28% (5237/25,820) of Users had started using the app during the daytime on weekdays, in comparison to 15.34% (24,718/161,113) of Dropouts. Users with strict diets were more likely to be Active (14.31%, 900/6291) than those who had not defined any diet (3.99%, 742/18,590), said they ate everything (9.47%, 3040/32,090), or reported some other diet (11.85%, 213/1798) (χ(2) 3=826.6, P<.001). The average healthiness rating from peers for the first picture was higher for Active users (0.55) than for Semi-actives (0.52) or Non-actives (0.49) (F2,58167=225.9, P<.001). Actives wrote more often a textual description for the first picture than Semi-actives or Non-actives (χ(2) 2=3515.1, P<.001). Feedback beyond ratings was relatively infrequent: 3.83% (15,247/398,228) of pictures received comments and 15.39% (61,299/398,228) received "likes" from other users. Actives were more likely to have at least one comment or one "like" for their pictures than Semi-actives or Non-actives (χ(2) 2=343.6, P<.001, and χ(2) 2=909.6, P<.001, respectively). Only 9.89% (481/4863) of Active users had a positive trend in their average healthiness ratings.

CONCLUSIONS

Most people who tried out this free mobile app for dietary self-monitoring did not continue using it actively and those who did may already have been healthy eaters. Hence, the societal impact of such apps may remain small if they fail to reach those who would be most in need of dietary changes. Incorporating additional self-regulation techniques such as goal-setting and intention formation into the app could potentially increase user engagement and promote sustained use.

Real-time sharing and expression of migraine headache suffering on Twitter: a cross-sectional infodemiology study

BACKGROUND

Although population studies have greatly improved our understanding of migraine, they have relied on retrospective self-reports that are subject to memory error and experimenter-induced bias. Furthermore, these studies also lack specifics from the actual time that attacks were occurring, and how patients express and share their ongoing suffering.

OBJECTIVE

As technology and language constantly evolve, so does the way we share our suffering. We sought to evaluate the infodemiology of self-reported migraine headache suffering on Twitter.

METHODS

Trained observers in an academic setting categorized the meaning of every single "migraine" tweet posted during seven consecutive days. The main outcome measures were prevalence, life-style impact, linguistic, and timeline of actual self-reported migraine headache suffering on Twitter.

RESULTS

From a total of 21,741 migraine tweets collected, only 64.52% (14,028/21,741 collected tweets) were from users reporting their migraine headache attacks in real-time. The remainder of the posts were commercial, re-tweets, general discussion or third person's migraine, and metaphor. The gender distribution available for the actual migraine posts was 73.47% female (10,306/14,028), 17.40% males (2441/14,028), and 0.01% transgendered (2/14,028). The personal impact of migraine headache was immediate on mood (43.91%, 6159/14,028), productivity at work (3.46%, 486/14,028), social life (3.45%, 484/14,028), and school (2.78%, 390/14,028). The most common migraine descriptor was "Worst" (14.59%, 201/1378) and profanity, the "F-word" (5.3%, 73/1378). The majority of postings occurred in the United States (58.28%, 3413/5856), peaking on weekdays at 10:00h and then gradually again at 22:00h; the weekend had a later morning peak.

CONCLUSIONS

Twitter proved to be a powerful source of knowledge for migraine research. The data in this study overlap large-scale epidemiological studies, avoiding memory bias and experimenter-induced error. Furthermore, linguistics of ongoing migraine reports on social media proved to be highly heterogeneous and colloquial in our study, suggesting that current pain questionnaires should undergo constant reformulations to keep up with modernization in the expression of pain suffering in our society. In summary, this study reveals the modern characteristics and broad impact of migraine headache suffering on patients' lives as it is spontaneously shared via social media.

Are public health organizations tweeting to the choir? Understanding local health department Twitter followership

Background

One of the essential services provided by the US local health departments is informing and educating constituents about health. Communication with constituents about public health issues and health risks is among the standards required of local health departments for accreditation. Past research found that only 61% of local health departments met standards for informing and educating constituents, suggesting a considerable gap between current practices and best practice.

Objective

Social media platforms, such as Twitter, may aid local health departments in informing and educating their constituents by reaching large numbers of people with real-time messages at relatively low cost. Little is known about the followers of local health departments on Twitter. The aim of this study was to examine characteristics of local health department Twitter followers and the relationship between local health department characteristics and follower characteristics.

Methods

In 2013, we collected (using NodeXL) and analyzed a sample of 4779 Twitter followers from 59 randomly selected local health departments in the United States with Twitter accounts. We coded each Twitter follower for type (individual, organization), location, health focus, and industry (eg, media, government). Local health department characteristics were adopted from the 2010 National Association of City and County Health Officials Profile Study data.

Results

Local health department Twitter accounts were followed by more organizations than individual users. Organizations tended to be health-focused, located outside the state from the local health department being followed, and from the education, government, and non-profit sectors. Individuals were likely to be local and not health-focused. Having a public information officer on staff, serving a larger population, and “tweeting” more frequently were associated with having a higher percentage of local followers.

Conclusions

Social media has the potential to reach a wide and diverse audience. Understanding audience characteristics can help public health organizations use this new tool more effectively by tailoring tweet content and dissemination strategies for their audience.

Electronic word of mouth on twitter about physical activity in the United States: exploratory infodemiology study

Background

Twitter is a widely used social medium. However, its application in promoting health behaviors is understudied.

Objective

In order to provide insights into designing health marketing interventions to promote physical activity on Twitter, this exploratory infodemiology study applied both social cognitive theory and the path model of online word of mouth to examine the distribution of different electronic word of mouth (eWOM) characteristics among personal tweets about physical activity in the United States.

Methods

This study used 113 keywords to retrieve 1 million public tweets about physical activity in the United States posted between January 1 and March 31, 2011. A total of 30,000 tweets were randomly selected and sorted based on numbers generated by a random number generator. Two coders scanned the first 16,100 tweets and yielded 4672 (29.02%) tweets that they both agreed to be about physical activity and were from personal accounts. Finally, 1500 tweets were randomly selected from the 4672 tweets (32.11%) for further coding. After intercoder reliability scores reached satisfactory levels in the pilot coding (100 tweets separate from the final 1500 tweets), 2 coders coded 750 tweets each. Descriptive analyses, Mann-Whitney U tests, and Fisher exact tests were performed.

Results

Tweets about physical activity were dominated by neutral sentiments (1270/1500, 84.67%). Providing opinions or information regarding physical activity (1464/1500, 97.60%) and chatting about physical activity (1354/1500, 90.27%) were found to be popular on Twitter. Approximately 60% (905/1500, 60.33%) of the tweets demonstrated users’ past or current participation in physical activity or intentions to participate in physical activity. However, social support about physical activity was provided in less than 10% of the tweets (135/1500, 9.00%). Users with fewer people following their tweets (followers) (P=.02) and with fewer accounts that they followed (followings) (P=.04) were more likely to talk positively about physical activity on Twitter. People with more followers were more likely to post neutral tweets about physical activity (P=.04). People with more followings were more likely to forward tweets (P=.04). People with larger differences between number of followers and followings were more likely to mention companionship support for physical activity on Twitter (P=.04).

Conclusions

Future health marketing interventions promoting physical activity should segment Twitter users based on their number of followers, followings, and gaps between the number of followers and followings. The innovative application of both marketing and public health theory to examine tweets about physical activity could be extended to other infodemiology or infoveillance studies on other health behaviors (eg, vaccinations).

An exploration of social circles and prescription drug abuse through Twitter

Background

Prescription drug abuse has become a major public health problem. Relationships and social context are important contributing factors. Social media provides online channels for people to build relationships that may influence attitudes and behaviors.

Objective

To determine whether people who show signs of prescription drug abuse connect online with others who reinforce this behavior, and to observe the conversation and engagement of these networks with regard to prescription drug abuse.

Methods

Twitter statuses mentioning prescription drugs were collected from November 2011 to November 2012. From this set, 25 Twitter users were selected who discussed topics indicative of prescription drug abuse. Social circles of 100 people were discovered around each of these Twitter users; the tweets of the Twitter users in these networks were collected and analyzed according to prescription drug abuse discussion and interaction with other users about the topic.

Results

From November 2011 to November 2012, 3,389,771 mentions of prescription drug terms were observed. For the 25 social circles (n=100 for each circle), on average 53.96% (SD 24.3) of the Twitter users used prescription drug terms at least once in their posts, and 37.76% (SD 20.8) mentioned another Twitter user by name in a post with a prescription drug term. Strong correlation was found between the kinds of drugs mentioned by the index user and his or her network (mean r=0.73), and between the amount of interaction about prescription drugs and a level of abusiveness shown by the network (r=0.85, P<.001).

Conclusions

Twitter users who discuss prescription drug abuse online are surrounded by others who also discuss it—potentially reinforcing a negative behavior and social norm.