Barriers to and Facilitators for Using Nutrition Apps: Systematic Review and Conceptual Framework

Integrating Vision-Language Models for Accelerated High-Throughput Nutrition Screening

Addressing the critical need for swift and precise nutritional profiling in healthcare and in food industry, this study pioneers the integration of vision-language models (VLMs) with chemical analysis techniques. A cutting-edge VLM is unveiled, utilizing the expansive UMDFood-90k database, to significantly improve the speed and accuracy of nutrient estimation processes. Demonstrating a macro-AUCROC of 0.921 for lipid quantification, the model exhibits less than 10% variance compared to traditional chemical analyses for over 82% of the analyzed food items. This innovative approach not only accelerates nutritional screening by 36.9% when tested amongst students but also sets a new benchmark in the precision of nutritional data compilation. This research marks a substantial leap forward in food science, employing a blend of advanced computational models and chemical validation to offer a rapid, high-throughput solution for nutritional analysis.

Digital health and medical technology for perioperative sarcopenia optimisation and prehabilitation - Where to go from here?

Sarcopenia has been shown to cause poorer outcomes in surgical oncology. With the advancement of artificial intelligence technology, body composition analysis can be obtained with ease. Given the lead time between cancer diagnosis and surgery, selected patients at risk of complications secondary to sarcopenia may be amenable to prehabilitation. The COVID-19 pandemic has led to the rapid adaptation of digital health and medical technology. Our perspective piece will review the current available evidence and propose innovative ways to incorporate technology into physical and nutritional prehabilitation.

LIFANA - toward developing a meal recommender system as a dietary support app for the elderly

Background: Though a variety of eHealth/mHealth dietary solutions exist, many are ill-adapted to the target population and local eating habits. A specific need exists for the elderly, a growing vulnerable population with limited digital literacy. The LIFANA project aimed at developing a mobile nutrition solution, i.e. a dietary meal-recommender app for personalized meal planning useful for the elderly. Methods: In addition to considering age, gender, and physical activity, the app assured sufficient intake of calories and proteins. The solution was optimized to consider local eating culture in Portugal (PT)/The Netherlands (NL) where it was tested. Recipes (>300) were included and aligned with national food composition dietary databases (FCDBs) to analyse their nutritional values for meal planning. Individual dietary preferences, food restrictions (i.e., allergies), and budget considerations were included in the user profile. The development process involved user integration, including focus groups and usability evaluations, followed by longer field trials in Portugal (n=53 participants, age 60-81 y, 14 months) and the Netherlands (n=107, age 52-86 y, 3 months). Endpoints regarding acceptance/usage frequency, anthropometric measures and (in PT) blood pressure and body fat were collected. Results: 23/34 elderly finalized the trials in PT/NL. No significant changes in anthropometry or other assessed markers, including blood pressure, were observed. 9% (NL) and 47% (PT) of users reported that they would consider using the solution if it were on the market. Conclusions: Via an iterative adaptive process, a dietary app was developed and improved that demonstrated acceptance/user-friendliness comparable to other tools available on the market and allowed - despite the COVID crisis - for stable anthropometric markers and blood pressure. However, it was also observed that additional features, such as a link to an online shopping app, and closer personal follow-up was associated with increased usability and acceptance of the solution and thus further personalization and nudges are warranted to increase employment of such dietary apps.

What Is the Tech Missing? Nutrition Reporting in Type 1 Diabetes

INTRODUCTION

Type 1 Diabetes (T1D) presents self-management challenges, requiring an additional 180 daily decisions to regulate blood glucose (BG) levels. Despite the potential, T1D-focused applications have a 43% attrition rate. This work delves into the willingness of people living with T1D (PwT1D) to use technology.

METHOD

An online questionnaire investigated the current practices for carbohydrate estimation, nutritional tracking, and attitudes towards technology engagement, along with hypothetical scenarios and preferences regarding technology use.

RESULTS

Thirty-nine responses were collected from PwT1D (n = 33) and caregivers (n = 6). Nutrition reporting preferences varied, with 50% favoring 'type and scroll' while 30% preferred meal photographing. Concerning the timing of reporting, 33% reported before meals, 55% after, and 12% at a later time. Improved Time in Range (TIR) was a strong motivator for app use, with 78% expressing readiness to adjust insulin doses based on app suggestions for optimizing TIR. Meal descriptions varied; a single word was used in 42% of cases, 23% used a simple description (i.e., "Sunday dinner"), 30% included portion sizes, and 8% provided full recipes.

CONCLUSION

PwT1D shows interest in using technology to reduce the diabetes burden when it leads to an improved TIR. For such technology to be ecologically valid, it needs to strike a balance between requiring minimal user input and providing significant data, such as meal tags, to ensure accurate blood glucose management without overwhelming users with reporting tasks.

Characterization of adults concerning the use of a hypothetical mHealth application addressing stress-overeating: an online survey

BACKGROUND

About 40% of people respond to stress by consuming more unhealthy foods. This behavior is associated with increased energy intake and the risk of obesity. As mobile health (mHealth) applications (apps) have been shown to be an easy-to-use intervention tool, the characterization of potential app users is necessary to develop target group-specific apps and to increase adherence rates.

METHODS

This cross-sectional online survey was conducted in the spring of 2021 in Germany. Sociodemographic data and data on personality (Big Five Inventory, BFI-10), stress-eating (Salzburg Stress Eating Scale, SSES), and technology behavior (Personal Innovativeness in the Domain of Information Technology, PIIT; Technology Acceptance Model 3, TAM 3) were collected.

RESULTS

The analysis included 1228 participants (80.6% female, mean age: 31.4 ± 12.8 years, mean body mass index (BMI): 23.4 ± 4.3 kg/m2). Based on the TAM score, 33.3% (409/1228) of the participants had a high intention to use a hypothetical mHealth app to avoid stress-overeating. These persons are characterized by a higher BMI (24.02 ± 4.47 kg/m2, p < 0.001), by being stress-overeaters (217/409, 53.1%), by the personality trait "neuroticism" (p < 0.001), by having specific eating reasons (all p < 0.01), and by showing a higher willingness to adopt new technologies (p < 0.001).

CONCLUSION

This study suggests that individuals who are prone to stress-overeating are highly interested in adopting an mHealth app as support. Participants with a high intention to use an mHealth app seem to have a general affinity towards new technology (PIIT) and appear to be more insecure with conflicting motives regarding their diet.

TRIAL REGISTRATION

This survey was registered in the German Clinical Trials Register (Registration number: DRKS00023984).

Exploring dietitians' views on digital nutrition educational tools in Malaysia: a qualitative study

BACKGROUND/OBJECTIVES

Dietitians frequently use nutrition education tools to facilitate dietary counselling sessions. Nevertheless, these tools may require adaptation to keep pace with technological advancements. This study had a 2-fold purpose: first, to identify the types of nutrition education tools currently in use, identify their limitations, and explore dietitians' perspectives on the importance of these tools; second, to investigate the features that dietitians prefer in digital nutrition education tools.

SUBJECTS/METHODS

A semi-structured face-to-face interview was conducted among 15 dietitians from selected public hospitals, primary care clinics, and teaching hospitals in Malaysia. Inductive thematic analysis of the responses was conducted using NVivo version 12 software.

RESULTS

Most dietitians used physical education tools including the healthy plate model, pamphlets, food models, and flip charts. These tools were perceived as important as they facilitate the nutrition assessment process, deliver nutrition intervention, and are time efficient. However, dietitians described the current educational tools as impersonal, outdated, limited in availability due to financial constraints, unhandy, and difficult to visualise. Alternatively, they strongly favoured digital education tools that provided instant feedback, utilised an automated system, included a local food database, were user-friendly, developed by experts in the field, and seamlessly integrated into the healthcare system.

CONCLUSION

Presently, although dietitians have a preference for digital educational tools, they heavily rely on physical nutrition education tools due to their availability despite the perception that these tools are outdated, impersonal, and inconvenient. Transitioning to digital dietary education tools could potentially address these issues.

Understanding Heterogeneity in Individual Responses to Digital Lifestyle Intervention Through Self-Monitoring Adherence Trajectories in Adults With Overweight or Obesity: Secondary Analysis of a 6-Month Randomized Controlled Trial

BACKGROUND

Achieving clinically significant weight loss through lifestyle interventions for obesity management is challenging for most individuals. Improving intervention effectiveness involves early identification of intervention nonresponders and providing them with timely, tailored interventions. Early and frequent self-monitoring (SM) adherence predicts later weight loss success, making it a potential indicator for identifying nonresponders in the initial phase.

OBJECTIVE

This study aims to identify clinically meaningful participant subgroups based on longitudinal adherence to SM of diet, activity, and weight over 6 months as well as psychological predictors of participant subgroups from a self-determination theory (SDT) perspective.

METHODS

This was a secondary data analysis of a 6-month digital lifestyle intervention for adults with overweight or obesity. The participants were instructed to perform daily SM on 3 targets: diet, activity, and weight. Data from 50 participants (mean age: 53.0, SD 12.6 y) were analyzed. Group-based multitrajectory modeling was performed to identify subgroups with distinct trajectories of SM adherence across the 3 SM targets. Differences between subgroups were examined for changes in clinical outcomes (ie, body weight, hemoglobin A1c) and SDT constructs (ie, eating-related autonomous motivation and perceived competence for diet) over 6 months using linear mixed models.

RESULTS

Two distinct SM trajectory subgroups emerged: the Lower SM group (21/50, 42%), characterized by all-around low and rapidly declining SM, and the Higher SM group (29/50, 58%), characterized by moderate and declining diet and weight SM with high activity SM. Since week 2, participants in the Lower SM group exhibited significantly lower levels of diet (P=.003), activity (P=.002), and weight SM (P=.02) compared with the Higher SM group. In terms of clinical outcomes, the Higher SM group achieved a significant reduction in body weight (estimate: -6.06, SD 0.87 kg; P<.001) and hemoglobin A1c (estimate: -0.38, SD 0.11%; P=.02), whereas the Lower SM group exhibited no improvements. For SDT constructs, both groups maintained high levels of autonomous motivation for over 6 months. However, the Lower SM group experienced a significant decline in perceived competence (P=.005) compared with the Higher SM group, which maintained a high level of perceived competence throughout the intervention (P=.09).

CONCLUSIONS

The presence of the Lower SM group highlights the value of using longitudinal SM adherence trajectories as an intervention response indicator. Future adaptive trials should identify nonresponders within the initial 2 weeks based on their SM adherence and integrate intervention strategies to enhance perceived competence in diet to benefit nonresponders.

TRIAL REGISTRATION

ClinicalTrials.gov NCT05071287; https://clinicaltrials.gov/study/NCT05071287.

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID)

RR2-10.1016/j.cct.2022.106845.

A Smartphone Food Record App Developed for the Dutch National Food Consumption Survey: Relative Validity Study

BACKGROUND

In the Dutch National Food Consumption Survey, dietary intake has been assessed since 2003 through 24-hour dietary recalls using the GloboDiet software. A new self-administered smartphone food record app called DitEetIk! was developed for potential use in future surveys.

OBJECTIVE

This study aims to evaluate the data collected using the DitEetIk! app and its relative validity for food group, energy, and nutrient intake compared with the previous dietary assessment method (GloboDiet 24-hour dietary recalls).

METHODS

A total of 300 participants aged 18 to 79 years were recruited from a consumer panel. Participants were asked to keep a record of their consumption using the DitEetIk! app on 3 nonconsecutive days. Trained dietitians conducted a 24-hour dietary recall interview by telephone using the GloboDiet software (International Agency for Research on Cancer) regarding 1 of 3 DitEetIk! recording days. Nutrient intake was calculated using the NEVO database (version 2021/7.0). Relative validity was studied by comparing data from GloboDiet 24-hour dietary recalls and the DitEetIk app for the same day. Participants with implausible records, defined as days with energy intake of <0.6 or >3.0 basal metabolic rate, were excluded from the analyses. For 19 food groups and 29 nutrients, differences in median intake were assessed using the Wilcoxon signed rank test, and Spearman correlation coefficients were calculated. Bland-Altman plots with mean differences and 95% limits of agreement were created for energy intake and the contribution to energy intake from fat, carbohydrates, and protein.

RESULTS

A total of 227 participants completed a combination of a DitEetIk! app recording day and a 24-hour dietary recall interview for the same day. Of this group, 211 participants (n=104, 49.3% men and n=107, 50.7% women) had plausible recording days. Of all recorded food items, 12.8% (114/894) were entered via food barcode scanning, and 18.9% (169/894) were searched at the brand level. For 31% (5/16) of the food groups, the median intake assessed using the DitEetIk! app was >10% lower than that assessed using 24-hour dietary recalls; this was the case for fruit (P=.005), added fats (P=.001), milk and milk products (P=.02), cereal products (P=.01), and sauces (P<.001). This was also the case for 14% (4/29) of the nutrients (all P<.001). Regarding mean intake, differences were generally smaller. Regarding energy intake, the mean difference and 95% limits of agreement were 14 kcal (-1096 to 1124). Spearman correlation coefficients between intake assessed using the DitEetIk! app and 24-hour dietary recalls ranged from 0.48 to 0.88 (median 0.78) for food groups and from 0.58 to 0.90 (median 0.72) for nutrients.

CONCLUSIONS

Compared with GloboDiet 24-hour dietary recalls, the DitEetIk! app assessed similar mean energy intake levels but somewhat lower median intake levels for several food groups and nutrients.

Digital health interventions for all? Examining inclusivity across all stages of the digital health intervention research process

Digital interventions offer many possibilities for improving health, as remote interventions can enhance reach and access to underserved groups of society. However, research evaluating digital health interventions demonstrates that such technologies do not equally benefit all and that some in fact seem to reinforce a "digital health divide." By better understanding these potential pitfalls, we may contribute to narrowing the digital divide in health promotion. The aim of this article is to highlight and reflect upon study design decisions that might unintentionally enhance inequities across key research stages-recruitment, enrollment, engagement, efficacy/effectiveness, and retention. To address the concerns highlighted, we propose strategies including (1) the standard definition of "effectiveness" should be revised to include a measure of inclusivity; (2) studies should report a broad range of potential inequity indicators of participants recruited, randomized, and retained and should conduct sensitivity analyses examining potential sociodemographic differences for both the effect and engagement of the digital interventions; (3) participants from historically marginalized groups should be involved in the design of study procedures, including those related to recruitment, consent, intervention implementation and engagement, assessment, and retention; (4) eligibility criteria should be minimized and carefully selected and the screening process should be streamlined; (5) preregistration of trials should include recruitment benchmarks for sample diversity and comprehensive lists of sociodemographic characteristics assessed; and (6) studies within trials should be embedded to systematically test recruitment and retention strategies to improve inclusivity. The implementation of these strategies would enhance the ability of digital health trials to recruit, randomize, engage, and retain a broader and more representative population in trials, ultimately minimizing the digital divide and broadly improving population health.

Dissemination Strategies for mHealth Apps: Systematic Review

BACKGROUND

Among the millions of mobile apps in existence, thousands fall under the category of mobile health (mHealth). Although the utility of mHealth apps has been demonstrated for disease diagnosis, treatment data management, and health promotion strategies, to be effective they must reach and be used by their target audience. An appropriate marketing strategy can ensure that apps reach potential users and potentially convert them to actual users. Such a strategy requires definitions of target end users, communication channels, and advertising content, as well as a timeline for effectively reaching and motivating end users to adopt and maintain engagement with the mHealth app.

OBJECTIVE

The aim of this study was to identify strategies and elements that ensure that end users adopt and remain engaged with mHealth apps.

METHODS

A systematic search of the PubMed, PsycINFO, Scopus, and CINAHL databases was conducted for suitable studies published between January 1, 2018, and September 30, 2022. Two researchers independently screened studies for inclusion, extracted data, and assessed the risk of bias. The main outcome was dissemination strategies for mHealth apps.

RESULTS

Of the 648 papers retrieved from the selected databases, only 10 (1.5%) met the inclusion criteria. The marketing strategies used in these studies to inform potential users of the existence of mHealth apps and motivate download included both paid and unpaid strategies and used various channels, including social media, emails, printed posters, and face-to-face communication. Most of the studies reported a combination of marketing concepts used to advertise their mHealth apps. Advertising messages included instructions on where and how to download and install the apps. In most of the studies (6/10, 60%), instructions were oriented toward how to use the apps and maintain engagement with a health intervention. The most frequently used paid marketing platform was Facebook Ads Manager (2/10, 20%). Advertising performance was influenced by many factors, including but not limited to advertising content. In 1 (10%) of the 10 studies, animated graphics generated the greatest number of clicks compared with other image types. The metrics used to assess marketing strategy effectiveness were number of downloads; nonuse rate; dropout rate; adherence rate; duration of app use; and app usability over days, weeks, or months. Additional indicators such as cost per click, cost per install, and clickthrough rate were mainly used to assess the cost-effectiveness of paid marketing campaigns.

CONCLUSIONS

mHealth apps can be disseminated via paid and unpaid marketing strategies using various communication channels. The effects of these strategies are reflected in download numbers and user engagement with mHealth apps. Further research could provide guidance on a framework for disseminating mHealth apps and encouraging their routine use.

Impact of feedback generation and presentation on self-monitoring behaviors, dietary intake, physical activity, and weight: a systematic review and meta-analysis

Self-monitoring of dietary intake, physical activity, and weight is a key strategy in behavioral interventions, and some interventions provide self-monitoring feedback to facilitate goal setting and promote engagement. This systematic review aimed to evaluate whether feedback increases intervention effectiveness, and which forms of feedback presentation (e.g., personalized vs. not personalized) and generation (i.e., human vs. algorithm-generated) are most effective. To achieve this aim, 5 electronic databases (PubMed/MEDLINE, Web of Science, CINAHL, PsycINFO, and Google Scholar) were searched in April 2022 and yielded 694 unique records, out of which 24 articles reporting on 19 studies were included (with a total of 3261 participants). Two reviewers independently screened titles and abstracts and then full texts and categorized articles as eligible or excluded according to the pre-registered criteria (i.e., availability of full text, peer reviewed manuscript in English; adult participants in a randomized controlled trial that included both self-monitoring and feedback; comparisons of different forms of feedback or comparisons of feedback vs. no feedback; primary outcomes of diet, physical activity, self-monitoring behavior, and/or weight). All included studies were assessed for methodological quality independently by two reviewers using the revised Cochrane risk-of-bias tool for randomized studies (version 2). Ten studies compared feedback to no feedback, 5 compared human- vs. algorithm-generated feedback, and the remaining 4 studies compared formats of feedback presentation (e.g., frequency, richness). A random effects meta-analysis indicated that physical activity interventions with feedback provision were more effective than physical activity interventions without feedback (d = 0.73, 95% CI [0.09;1.37]). No meta-analysis could be conducted for other comparisons due to heterogeneity of study designs and outcomes. There were mixed results regarding which form of feedback generation and presentation is superior. Limitations of the evidence included in this review were: lack of details about feedback provided, the brevity of most interventions, the exclusion of studies that did not isolate feedback when testing intervention packages, and the high risk of bias in many studies. This systematic review underlines the importance of including feedback in behavioral interventions; however, more research is needed to identify most effective forms of feedback generation and presentation to maximize intervention effectiveness.Trial registration (PROSPERO)CRD42022316206.

Patients' acceptability of self-selected digital health services to support diet and exercise among people with complex chronic conditions: Mixed methods study

Objective

The acceptability of being offered a choice from a suite of digital health service options to support optimal diet and exercise behaviors in adults with complex chronic conditions was evaluated. This study sought to understand many areas of acceptability including satisfaction, ease of use, usefulness and user appropriateness and perceived effectiveness.

Methods

This mixed-methods study was embedded within a randomized-controlled feasibility trial providing digital health services managing diet and exercise for adults from specialist kidney and liver disease clinics. Post study surveys and semistructured interviews were used to determine patients' acceptability of the trial interventions. Quantitative (surveys) and qualitative (surveys and interviews) results were merged using integrative analysis and mapped to each construct of the modified version of the Theoretical Framework of Acceptability.

Results

Seventeen interviews (intervention group) and 50 surveys (n = 24 intervention, n = 26 comparator) completed from a possible 67 participants were analyzed. In the intervention group, the survey results revealed high areas of acceptability for the digital health services including overall support received, ease of use, timely advice and feeling safe. The interviews also revealed high areas of acceptability including convenience, ability to adopt healthier behaviors and having regular interactions with health professionals. However, the interviews also revealed lower areas of acceptability as a result of absence of individualization, low digital literacy, and limitations from life circumstances.

Conclusions

Recipients of digital health services that supported diet and exercise interventions found these useful, effective, and safe. Individualized care, technical support and patient confidence remain important to improve the acceptability of digital health service interventions.

Reducing intervention- and research-induced inequalities to tackle the digital divide in health promotion

Social inequalities are an important contributor to the global burden of disease within and between countries. Using digital technology in health promotion and healthcare is seen by some as a potential lever to reduce these inequalities; however, research suggests that digital technology risks re-enacting or evening widening disparities. Most research on this digital health divide focuses on a small number of social inequality indicators and stems from Western, educated, industrialized, rich, and democratic (WEIRD) countries. There is a need for systematic, international, and interdisciplinary contextualized research on the impact of social inequality indicators in digital health as well as the underlying mechanisms of this digital divide across the globe to reduce health disparities. In June 2023, eighteen multi-disciplinary researchers representing thirteen countries from six continents came together to discuss current issues in the field of digital health promotion and healthcare contributing to the digital divide. Ways that current practices in research contribute to the digital health divide were explored, including intervention development, testing, and implementation. Based on the dialogue, we provide suggestions for overcoming barriers and improving practices across disciplines, countries, and sectors. The research community must actively advocate for system-level changes regarding policy and research to reduce the digital divide and so improve digital health for all.

Examining Theoretical Frameworks and Antecedents of Health Apps and Wearables Use: A Scoping Review

The advancement of health apps and wearables has garnered substantial academic attention, particularly in examining why individuals decide to use or not use them. In response to the extensive body of research on this topic, we conducted a scoping review of 61 articles published from 2007 to 2022, aiming to examine the dominant theoretical frameworks and antecedents of health apps and wearables use. The findings demonstrated that the dominant theoretical frameworks within this domain were rooted in the human-computer interaction theories, notably the Technology Acceptance Model and the Unified Theory of Acceptance and Use of Technology. Next, our review identified four levels of antecedents: technological, individual, societal, and policy. At the technological level, emphasis was placed on functionality, reliability, and technological infrastructure. Individual antecedents encompassed socio-demographics, personality traits, cognitive responses to benefits and risks, emotional and affective responses, self-efficacy, and digital literacy. Societal antecedents highlighted the role of social networks and social norms, while policy antecedents elaborated on laws, regulations, and guidelines that encouraged health technology adoption. Our discussion illuminated that the evolving trend of theoretical frameworks in health apps and wearables use research, initially rooted in human-computer interaction, is progressively moving toward more comprehensive perspectives. We further underscored the importance of delving into societal and policy antecedents, which often are overshadowed by the more commonly discussed technological and individual factors. In conclusion, we advocated for a multi-stakeholder collaborative network approach, as this would enable communication researchers to understand the use of health apps and wearables more comprehensively.

Surviving & Thriving; a healthy lifestyle app for new US firefighters: usability and pilot study protocol

In the United States (US), new firefighters' fitness and health behaviors deteriorate rapidly after fire academy graduation. Over the long-term, this increases their risks for chronic diseases. This study protocol describes the proposed usability testing and pilot study of a newly designed and developed healthy lifestyle smartphone app, "Surviving & Thriving", tailored towards young US firefighters. "Surviving & Thriving" will provide interactive educational content on four lifestyle factors; nutrition, sleep, physical activity, and resilience, and include a personalized journey, habit tracker, and elements of gamification to promote engagement and long-term healthy behavior change. The first phase of the app development entails alpha testing by the research team and pre-beta testing by a fire service expert panel which will help refine the app into a pre-consumer version. Upon completion of the full app prototype, beta 'usability' testing will be conducted among new fire academy graduates from two New England fire academies to collect qualitative and quantitative feedback via focus groups and satisfaction surveys, respectively. A last phase of piloting the app will evaluate the app's efficacy at maintaining/improving healthy lifestyle behaviors, mental health metrics, and physical fitness metrics. We will also evaluate whether firefighters' perceived "health cultures" scores (ratings of each fire station's/fire department's environments as to encouraging/discouraging healthy behaviors) modify the changes in health metrics after utilizing the app for three to six months. This novel user-friendly app seeks to help new firefighters maintain/improve their health and fitness more effectively, reducing their risk of lifestyle-related chronic disease. Firefighters who can establish healthy habits early in their careers are more likely to sustain them throughout their lives.

Decision Trade-Offs in Ecological Momentary Assessments and Digital Wearables Uptake: Protocol for a Discrete Choice Experiment

BACKGROUND

Ecological momentary assessments (EMAs) and digital wearables (DW) are commonly used remote monitoring technologies that capture real-time data in people's natural environments. Real-time data are core to personalized medical care and intensively adaptive health interventions. The utility of such personalized care is contingent on user uptake and continued use of EMA and DW. Consequently, it is critical to understand user preferences that may increase the uptake of EMA and DW.

OBJECTIVE

The study aims to quantify users' preferences of EMA and DW, examine variations in users' preferences across demographic and behavioral subgroups, and assess the association between users' preferences and intentions to use EMA and DW.

METHODS

We will administer 2 discrete choice experiments (DCEs) paired with self-report surveys on the internet to a total of 3260 US adults through Qualtrics. The first DCE will assess participants' EMA preferences using a choice-based conjoint design that will ask participants to compare the relative importance of prompt frequency, number of questions per prompt, prompt type, health topic, and assessment duration. The second DCE will measure participants' DW preferences using a maximum difference scaling design that will quantify the relative importance of device characteristics, effort expectancy, social influence, and facilitating technical, health care, and market factors. Hierarchical Bayesian multinomial logistic regression models will be used to generate subject-specific preference utilities. Preference utilities will be compared across demographic (ie, sex, age, race, and ethnicity) and behavioral (ie, substance use, physical activity, dietary behavior, and sleep duration) subgroups. Regression models will determine whether specific utilities are associated with attitudes toward or intentions to use EMA and DW. Mixture models will determine the associations of attitudes toward and intentions to use EMA and DW with latent profiles of user preferences.

RESULTS

The institutional review board approved the study on December 19, 2022. Data collection started on January 20, 2023, and concluded on May 4, 2023. Data analysis is currently underway.

CONCLUSIONS

The study will provide evidence on users' preferences of EMA and DW features that can improve initial uptake and potentially continued use of these remote monitoring tools. The sample size and composition allow for subgroup analysis by demographics and health behaviors and will provide evidence on associations between users' preferences and intentions to uptake EMA and DW. Limitations include the cross-sectional nature of the study, which limits our ability to measure direct behavior. Rather, we capture behavioral intentions for EMA and DW uptake. The nonprobability sample limits the generalizability of the results and introduces self-selection bias related to the demographic and behavioral characteristics of participants who belong to web-based survey panels.

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID)

DERR1-10.2196/47567.

Assessing daily energy intake in adult women: validity of a food-recognition mobile application compared to doubly labelled water

Accurate dietary assessment is crucial for nutrition and health research. Traditional methods, such as food records, food frequency questionnaires, and 24-hour dietary recalls (24HR), have limitations, such as the need for trained interviewers, time-consuming procedures, and inaccuracies in estimations. Novel technologies, such as image-based dietary assessment apps, have been developed to overcome these limitations. SNAQ is a novel image-based food-recognition app which, based on computer vision, assesses food type and volume, and provides nutritional information about dietary intake. This cross-sectional observational study aimed to investigate the validity of SNAQ as a dietary assessment tool for measuring energy and macronutrient intake in adult women with normal body weight (n = 30), compared to doubly labeled water (DLW), a reference method for total daily energy expenditure (TDEE). Energy intake was also estimated using a one-day 24HR for direct comparison. Bland-Altman plots, paired difference tests, and Pearson's correlation coefficient were used to assess agreement and relationships between the methods. SNAQ showed a slightly higher agreement (bias = -329.6 kcal/day) with DLW for total daily energy intake (TDEI) compared to 24HR (bias = -543.0 kcal/day). While both SNAQ and 24HR tended to underestimate TDEI, only 24HR significantly differed from DLW in this regard (p < 0.001). There was no significant relationship between estimated TDEI and TDEE using SNAQ (R2 = 27%, p = 0.50) or 24HR (R2 = 34%, p = 0.20) and there were no significant differences in energy and macronutrient intake estimates between SNAQ and 24HR (Δ = 213.4 kcal/day). In conclusion, these results indicate that SNAQ provides a closer representation of energy intake in adult women with normal body weight than 24HR when compared to DLW, but no relationship was found between the energy estimates of DLW and of the two dietary assessment tools. Further research is needed to determine the clinical relevance and support the implementation of SNAQ in research and clinical settings. Clinical trial registration: This study is registered on ClinicalTrials.gov with the unique identifier NCT04600596 (https://clinicaltrials.gov/ct2/show/NCT04600596).

Perspective: A Conceptual Framework for Adaptive Personalized Nutrition Advice Systems (APNASs)

Nearly all approaches to personalized nutrition (PN) use information such as the gene variants of individuals to deliver advice that is more beneficial than a generic "1-size-fits-all" recommendation. Despite great enthusiasm and the increased availability of commercial services, thus far, scientific studies have only revealed small to negligible effects on the efficacy and effectiveness of personalized dietary recommendations, even when using genetic or other individual information. In addition, from a public health perspective, scholars are critical of PN because it primarily targets socially privileged groups rather than the general population, thereby potentially widening health inequality. Therefore, in this perspective, we propose to extend current PN approaches by creating adaptive personalized nutrition advice systems (APNASs) that are tailored to the type and timing of personalized advice for individual needs, capacities, and receptivity in real-life food environments. These systems encompass a broadening of current PN goals (i.e., what should be achieved) to incorporate "individual goal preferences" beyond currently advocated biomedical targets (e.g., making sustainable food choices). Moreover, they cover the "personalization processes of behavior change" by providing in situ, "just-in-time" information in real-life environments (how and when to change), which accounts for individual capacities and constraints (e.g., economic resources). Finally, they are concerned with a "participatory dialog between individuals and experts" (e.g., actual or virtual dieticians, nutritionists, and advisors) when setting goals and deriving measures of adaption. Within this framework, emerging digital nutrition ecosystems enable continuous, real-time monitoring, advice, and support in food environments from exposure to consumption. We present this vision of a novel PN framework along with scenarios and arguments that describe its potential to efficiently address individual and population needs and target groups that would benefit most from its implementation.

Identification of the Most Suitable Mobile Apps to Support Dietary Approaches to Stop Hypertension (DASH) Diet Self-Management: Systematic Search of App Stores and Content Analysis

Smartphone apps might provide an opportunity to support the Dietary Approaches to Stop Hypertension (DASH) diet, a healthy diet designed to help lower blood pressure. This study evaluated DASH diet self-management apps based on their quality, likely effectiveness, and data privacy/security to identify the most suitable app(s). A systematic search and content analysis were conducted of all DASH diet apps available in Google Play and the Apple App Store in the UK in November 2022. Apps were included if they provided DASH diet tracking. A previous systematic literature review found some commercial apps not found in the app store search, and these were also included in this review. Three reviewers used the App Quality Evaluation Tool (AQEL) to assess each app's quality across seven domains: knowledge acquisition, skill development, behaviour change, purpose, functionality, and appropriateness for adults with hypertension. Domains with a score of 8 or higher were considered high-quality. Two reviewers assessed the apps' data privacy and security and then coded Behaviour change techniques (BCTs) linked to the Theoretical Domain Framework (TDF) underpinning the likely effectiveness of the apps. Seven DASH diet apps were assessed, showing the limited availability of apps supporting DASH diet self-management. The AQEL assessment showed that three apps scored higher than eight in most of the AQEL domains. Nineteen BCTs were used across the apps, linked to nine TDF action mechanisms that may support DASH diet self-management behaviours. Four apps met standards for privacy and security. All seven apps with self-monitoring functionality had sufficient theoretical basis to demonstrate likely effectiveness. However, most had significant quality and data security shortcomings. Only two apps, NOOM and DASH To TEN, were found to have both adequate quality and security and were thus deemed suitable to support DASH diet self-management.

An Evaluation of Interactive mHealth Applications for Adults Living with Cancer

This study evaluated the quality and usefulness of interactive mobile health (mHealth) applications (apps) for adults with cancer. The PRISMA guidelines were followed to add rigor to the search, as well as to the data collection and analysis. The apps available in the most used app stores (Google Play and Apple) with interactive tailored features were identified. To supplement this, a Google web search was also conducted. The apps were evaluated for their quality using the validated Mobile App Rating Scale (MARS) and for their usefulness using a checklist of end users' desired features derived from the literature. The searches returned 3046 apps and 17 were retained for evaluation. The average quality score of the apps across the sample was 3.62/5 (SD 0.26, range: 3.14-4.06), with Outcomes4me scoring the highest. On average, the apps scored 50% (SD 2.5, range: 31-88%) on the usefulness checklist, with Cancer.net scoring the highest. The lowest-scoring categories were communications features on the usefulness checklist and "information" on the MARS, indicating areas for future work. The findings identified the apps of an acceptable quality and usefulness that could be recommended to those with cancer.

Improving Predictability and Effectiveness in Preventive Digital Health Interventions: Scoping Review

BACKGROUND

Lifestyle-related diseases caused by inadequate diet and physical activity cause premature death, loss of healthy life years, and increased health care costs. Randomized controlled trial (RCT) studies indicate that preventive digital health interventions (P-DHIs) can be effective in preventing these health problems, but the results of these studies are mixed. Adoption studies have identified multiple factors related to individuals and the context in which they live that complicate the transfer of positive results from RCT studies to practical use. Implementation studies have revealed barriers to the large-scale implementation of mobile health (mHealth) solutions in general. Consequently, there is no clear path to delivering predictable outcomes from P-DHIs and achieving effectiveness when scaling up interventions to reduce health problems in society.

OBJECTIVE

This research aimed to expand our understanding of how to increase the outcome predictability of P-DHIs by focusing on physical activity and diet behaviors and amplify our understanding of how to improve effectiveness in large-scale implementations.

METHODS

The research objective was pursued through a multidisciplinary scoping review. This scoping review used the PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews) as a guide. A comprehensive search of Web of Science and PubMed limited to English-language journal articles published before January 2022 was conducted. Google Scholar was used for hand searches. Information systems theory was used to identify key constructs influencing outcomes of IT in general. Public health and mHealth literature were used to identify factors influencing the adoption of, outcomes from, and implementation of P-DHIs. Finally, the P-DHI investment model was developed based on information systems constructs and factors from the public health and mHealth literature.

RESULTS

In total, 203 articles met the eligibility criteria. The included studies used a variety of methodologies, including literature reviews, interviews, surveys, and RCT studies. The P-DHI investment model suggests which constructs and related factors should be emphasized to increase the predictability of P-DHI outcomes and improve the effectiveness of large-scale implementations.

CONCLUSIONS

The research suggests that outcome predictability could be improved by including descriptions of the constructs and factors in the P-DHI investment model when reporting from empirical studies. Doing so would increase our understanding of when and why P-DHIs succeed or fail. The effectiveness of large-scale implementations may be improved by using the P-DHI investment model to evaluate potential difficulties and possibilities in implementing P-DHIs to create better environments for their use before investing in them and when designing and implementing them. The cost-effectiveness of large-scale implementations is unknown; implementations are far more complicated than just downloading and using apps, and there is uncertainty accompanying implementations given the lack of coordinated control over the constructs and factors that influence the outcome.

A mobile health application for patients eligible for statin therapy: app development and qualitative feedback on design and usability

BACKGROUND

Cardiovascular disease is the leading cause of death in the United States (US). Despite the well-recognized efficacy of statins, statin discontinuation rates remain high. Statin intolerance is a major cause of statin discontinuation. To accurately diagnose statin intolerance, healthcare professionals must distinguish between statin-associated and non-statin-associated muscle symptoms, because many muscle symptoms can be unrelated to statin therapy. Patients' feedback on muscle-related symptoms would help providers make decisions about statin treatment. Given the potential benefits and feasibility of existing apps for cardiovascular disease (CVD) management and the unmet need for an app specifically addressing statin intolerance management, the objectives of the study were 1) to describe the developmental process of a novel app designed for patients who are eligible for statin therapy to lower the risk of CVD; 2) to explore healthcare providers' feedback of the app; and 3) to explore patients' app usage experience.

METHODS

The app was developed by an interdisciplinary team. Healthcare provider participants and patient participants were recruited in the study. Providers were interviewed to provide their feedback about the app based on screenshots of the app. Patients were interviewed after a 30 days of app usage.

RESULTS

The basic features of the app included symptom logging, vitals tracking, patient education, and push notifications. Overall, both parties provided positive feedback about the app. Areas to be improved mentioned by both parties included: the pain question asked in symptom tracking and the patient education section. Both parties agreed that it was essential to add the trend report of the logged symptoms.

CONCLUSIONS

The results indicated that providers were willing to use patient-reported data for disease management and perceived that the app had the potential to facilitate doctor-patient communication. Results also indicated that user engagement is the key to the success of app efficacy. To promote app engagement, app features should be tailored to individual patient's needs and goals. In the future, after it is upgraded, we plan to test the app usability and feasibility among a more diverse sample.

Incorporating Consumers' Needs in Nutrition Apps to Promote and Maintain Use: Mixed Methods Study

BACKGROUND

Nutrition apps seem to be promising tools for supporting consumers toward healthier eating habits. There is a wide variety of nutrition apps available; however, users often discontinue app use at an early stage before a permanent change in dietary behavior can be achieved.

OBJECTIVE

The main objective of this study was to identify, from both a user and nonuser perspective, which functionalities should be included in nutrition apps to increase intentions to start and maintain use of these apps. A secondary objective was to gain insight into reasons to quit using nutrition apps at an early stage.

METHODS

This study used a mixed methods approach and included a qualitative and a quantitative study. The qualitative study (n=40) consisted of a home-use test with 6 commercially available nutrition apps, followed by 6 focus group discussions (FGDs) to investigate user experiences. The quantitative study was a large-scale survey (n=1420), which was performed in a representative sample of the Dutch population to quantify the FGDs' results. In the survey, several app functionalities were rated on 7-point Likert scales ranging from 1 (very unimportant) to 7 (very important).

RESULTS

A total of 3 different phases of app use, subdivided into 10 user-centric app aspects and 46 associated app functionalities, were identified as relevant nutrition app elements in the FGDs. Relevance was confirmed in the survey, as all user-centric aspects and almost all app functionalities were rated as important to include in a nutrition app. In the starting phase, a clear introduction (mean 5.45, SD 1.32), purpose (mean 5.40, SD 1.40), and flexible food tracking options (mean 5.33, SD 1.45) were the most important functionalities. In the use phase, a complete and reliable food product database (mean 5.58, SD 1.41), easy navigation (mean 5.56, SD 1.36), and limited advertisements (mean 5.53, SD 1.51) were the most important functionalities. In the end phase, the possibility of setting realistic goals (mean 5.23, SD 1.44), new personal goals (mean 5.13, SD 1.45), and continuously offering new information (mean 4.88, SD 1.44) were the most important functionalities. No large differences between users, former users, and nonusers were found. The main reason for quitting a nutrition app in the survey was the high time investment (14/38, 37%). This was also identified as a barrier in the FGDs.

CONCLUSIONS

Nutrition apps should be supportive in all 3 phases of use (start, use, and end) to increase consumers' intentions to start and maintain the use of these apps and achieve a change in dietary behavior. Each phase includes several key app functionalities that require specific attention from app developers. High time investment is an important reason to quit nutrition app use at an early stage.

Smartphone Apps for Problem Gambling: A Review of Content and Quality

Purpose of review

Problem gambling can have profound consequences for affected individuals, yet only a small proportion of people with problem gambling seek treatment. Mobile phone applications (apps) may provide an effective and scalable therapeutic option. The purpose of this study was to evaluate publicly available mobile apps aimed at improving problematic gambling behavior.

Recent findings

To date, there are no published studies that have evaluated the quality of publicly available smartphone apps for problem gambling in the US. There is thus a significant gap in knowledge of existing apps for addressing problem gambling.

Summary

This study included a review of 14 problem-gambling-specific apps. Apps that incorporated cognitive-behavioral therapy concepts and in-app communities were associated with better aesthetics and information quality scores. Additionally, in-app communities were associated with better engagement scores. Our results highlight the importance of evidence-based and engaging features in apps designed to help people with problem gambling.

Quality, Usability, and Effectiveness of mHealth Apps and the Role of Artificial Intelligence: Current Scenario and Challenges

The use of artificial intelligence (AI) and big data in medicine has increased in recent years. Indeed, the use of AI in mobile health (mHealth) apps could considerably assist both individuals and health care professionals in the prevention and management of chronic diseases, in a person-centered manner. Nonetheless, there are several challenges that must be overcome to provide high-quality, usable, and effective mHealth apps. Here, we review the rationale and guidelines for the implementation of mHealth apps and the challenges regarding quality, usability, and user engagement and behavior change, with a special focus on the prevention and management of noncommunicable diseases. We suggest that a cocreation-based framework is the best method to address these challenges. Finally, we describe the current and future roles of AI in improving personalized medicine and provide recommendations for developing AI-based mHealth apps. We conclude that the implementation of AI and mHealth apps for routine clinical practice and remote health care will not be feasible until we overcome the main challenges regarding data privacy and security, quality assessment, and the reproducibility and uncertainty of AI results. Moreover, there is a lack of both standardized methods to measure the clinical outcomes of mHealth apps and techniques to encourage user engagement and behavior changes in the long term. We expect that in the near future, these obstacles will be overcome and that the ongoing European project, Watching the risk factors (WARIFA), will provide considerable advances in the implementation of AI-based mHealth apps for disease prevention and health promotion.

Is the uptake, engagement, and effectiveness of exclusively mobile interventions for the promotion of weight-related behaviors equal for all? A systematic review

Mobile health interventions are promising behavior change tools. However, there is a concern that they may benefit some populations less than others and thus widen inequalities in health. This systematic review investigated differences in uptake of, engagement with, and effectiveness of mobile interventions for weight-related behaviors (i.e., diet, physical activity, and sedentary behavior) based on a range of inequality indicators including age, gender, race/ethnicity, and socioeconomic status. The protocol was registered on PROSPERO (CRD42020192473). Six databases (CINAHL, EMBASE, ProQuest, PsycINFO, Pubmed, and Web of Science) were searched from inception to July 2021. Publications were eligible for inclusion if they reported the results of an exclusively mobile intervention and examined outcomes by at least one inequality indicator. Sixteen publications reporting on 13 studies were included with most reporting on multiple behaviors and inequality indicators. Uptake was investigated in one study with no differences reported by the inequality indicators studied. Studies investigating engagement (n = 7) reported differences by age (n = 1), gender (n = 3), ethnicity (n = 2), and education (n = 2), while those investigating effectiveness (n = 9) reported differences by age (n = 3), gender (n = 5), education (n = 2), occupation (n = 1), and geographical location (n = 1). Given the limited number of studies and their inconsistent findings, evidence of the presence of a digital divide in mobile interventions targeting weight-related behaviors is inconclusive. Therefore, we recommend that inequality indicators are specifically addressed, analyzed, and reported when evaluating mobile interventions.

Stance4Health Nutritional APP: A Path to Personalized Smart Nutrition

Access to good nutritional health is one of the principal objectives of current society. Several e-services offer dietary advice. However, multifactorial and more individualized nutritional recommendations should be developed to recommend healthy menus according to the specific user's needs. In this article, we present and validate a personalized nutrition system based on an application (APP) for smart devices with the capacity to offer an adaptable menu to the user. The APP was developed following a structured recommendation generation scheme, where the characteristics of the menus of 20 users were evaluated. Specific menus were generated for each user based on their preferences and nutritional requirements. These menus were evaluated by comparing their nutritional content versus the nutrient composition retrieved from dietary records. The generated menus showed great similarity to those obtained from the user dietary records. Furthermore, the generated menus showed less variability in micronutrient amounts and higher concentrations than the menus from the user records. The macronutrient deviations were also corrected in the generated menus, offering a better adaptation to the users. The presented system is a good tool for the generation of menus that are adapted to the user characteristics and a starting point to nutritional interventions.

User testing to modify the MyHealthyGut digital health application for inflammatory bowel disease

Introduction

Inflammatory bowel disease, characterized by chronic intestinal inflammation, can be subcategorized into Crohn's disease and ulcerative colitis. The treatment for these conditions is unique to each patient and may include lifestyle changes, pharmaceutical intervention, and surgery. Lifestyle changes, such as dietary intervention, are a cornerstone of inflammatory bowel disease symptom management. Given the daily burden of this disease, self-management is paramount in coping with and/or minimizing symptoms. The MyHealthyGut application, successfully proven to be a self-management tool for celiac disease, shows promise for use in an inflammatory bowel disease patient population.

Objective

To conduct user testing to gather valuable insights for the development of an IBD-focused version of the existing MyHealthyGut app.

Methods

Participants included inflammatory bowel disease patients and healthcare practitioners. Participants used the application for a 2-week period, followed by participation in a focus group or individual interview to provide feedback. Qualitative questionnaires were administered verbally and feedback was recorded. Thematic analysis techniques were used for data quantification and analysis.

Results

15 participants were recruited and enrolled. Of these, 14 participants took part in the focus group and/or individual interviews. The feedback suggested changes related to clinical uses, food and symptom tracking, ease of use, and educational content. All (100%) participants reported that they would either use the application themselves or recommend it to patients, once their suggestions were implemented.

Conclusion

Through user testing and feedback collection, priorities for app modification were identified. Areas for modification in the app functions and features, ease of use, and content were identified. Once updated to meet the needs of inflammatory bowel disease patients, the MyHealthyGut app may be a useful tool for IBD self-management.

Middle-aged and older adults' acceptance of mobile nutrition and fitness tools: A qualitative typology

Background

The utilization of mobile health (mHealth) devices such as nutrition and fitness tools seems to be promising in facilitating healthy lifestyle behaviors in middle-aged and older adults. As user acceptance plays a decisive role in the successful implementation of mHealth tools, it is vital to examine the target groups' acceptance, particularly their usage behavior and attitudes toward these tools. This qualitative study aimed to explore how far middle-aged as well as older adults accept mobile nutrition and fitness tools and to identify facilitators and barriers shaping their acceptance.

Methods

Twenty-one qualitative semi-structured interviews were conducted with German adults aged 50 years and older. Data material was analyzed using Qualitative Content Analysis (Kuckartz).

Results

A comprehensive acceptance typology with three acceptance types could be reconstructed: The Rejection Type, The Selective Acceptance Type, and The Comprehensive Acceptance Type. The target group's acceptance of mobile nutrition and fitness tools appeared to differ considerably across the three acceptance types and between the two different types of mHealth tools - with mobile nutrition tools having been less accepted. Among others, high levels of usability were identified as a key facilitator, while a desire for autonomy and privacy concerns showed to be prominent barriers.

Conclusion

The resulting typology indicates a pronounced heterogeneity among middle-aged and older adults regarding their acceptance of mobile nutrition and fitness tools. The findings highlight a need for more individualized mHealth tools along with respective promotion strategies that are specifically tailored to the needs and expectations of middle-aged and older adults.

The use and acceptability of diet-related apps and websites in Australia: Cross-sectional study

Objective

Diet-related apps and websites are developed to help improve dietary intake. The aim of this study is to explore the use and acceptability of diet-related apps and websites in Australia.

Methods

In a cross-sectional study, 241 participants (mean age = 40.6 years) completed an online survey about demographic characteristics, lifestyle behaviours and health concerns, experience and confidence in technology use, and preferences, attitudes and perception of diet app and website use. Descriptive analysis and unadjusted multiple logistic regression were used to explore data.

Results

Overall, 63.5% of participants were current or previous app users. App users were more confident in using technology, more concerned about diet and weight, and more trusting of information provided in diet-related apps compared to non-app users (p ≤ .05). Features such as food tracking, nutrient check and barcode scanning were preferred by both users and non-users. The likelihood of using diet-related apps was higher for those who trust the app information (OR 5.51, 95%CI: 2.40-12.66), often count calories (OR 2.28, 95%CI: 1.01-5.24) and are often on diet (OR 4.16, 95% CI: 1.21-14.21) compared to their counterparts.

Conclusions

More than half of the Australians that participated in this study used diet-related apps and websites. App features that allow the user to accurately record and monitor food intake and scan barcodes may motivate app use. Future public health strategies may take advantage of diet-related apps and websites to improve dietary behaviour at the population level and reduce the burden of obesity and non-communicable diseases.

Middle-aged and older adults' acceptance of mobile nutrition and fitness apps: A systematic mixed studies review

BACKGROUND

To promote healthy aging, the support of digital mobile health tools such as mobile applications (apps) addressing a healthy diet or physical activity appears promising, particularly when initiated before entering old age. For such tools to be effective, middle-aged and older adults' acceptance need to be studied in depth.

OBJECTIVE

The aim of this systematic review was to provide an integrative synthesis of the current state of research regarding the question in how far middle-aged and older adults (people aged 50 years and above) accept mobile nutrition and fitness apps to gain a deeper understanding of the influencing factors shaping this target group's usage behaviour and needs.

METHODS

The review process followed the PRISMA guidelines. The databases Medline, Embase, Web of Science as well as reference lists were systematically searched. Study quality was assessed using the MMAT and AXIS appraisal tools. Data of the included studies were extracted and thereupon narratively synthesized, involving thematic analysis.

RESULTS

Of N = 8823 articles screened, n = 7 studies could be identified-five quantitative, cross-sectional ones and two qualitative studies. Overall, the synthesized findings showed a lower acceptance among middle-aged and older adults compared to younger populations, which was particularly reflected in lower usage rates and more negative attitudes towards such apps (e.g., Perceived usefulness, Ease of use). The target group's acceptance of fitness apps was greater compared to nutrition apps. Findings on contextual factors and social determinants were inconsistent (e.g., regarding gender differences).

CONCLUSION

While cross-study comparability was limited, the synthesized evidence underscores the importance to target mobile nutrition and fitness apps to the distinctive and heterogeneous needs of middle-aged and, particularly, of older adults. The scarcity of the existing body of knowledge highlights the need of further (longitudinal) research.

PROSPERO PROTOCOL REGISTER NUMBER

CRD42020159409.

Low– and Medium–Socioeconomic-Status Group Members’ Perceived Challenges and Solutions for Healthy Nutrition: Qualitative Focus Group Study

Background

Although digital tools for healthy nutrition have shown great potential, their actual impact remains variable as digital solutions often do not fit users’ needs and barriers. This is especially poignant for priority communities in society. Involving these groups in citizen science may have great benefits even beyond the increase in knowledge of the lives and experiences of these groups. However, this requires specialized skills. Participants from priority groups could benefit from an approach that offers sensitization and discussion to help them voice their needs regarding healthy nutrition and technology to support healthy eating.

Objective

This study aimed to gather insights into people’s thoughts on everyday eating practices, self-regulation in healthy eating, and skill acquisition and on applying technological innovations to these domains.

Methods

Participants answered 3 daily questionnaires to garner their current practices regarding habits, self-regulation, skills, and technology use surrounding healthy eating and make it easier for them to collect their thoughts and experiences (sensitization). Within a week of filling out the 3 questionnaires, participants took part in a web-based focus group discussion session. All sessions were transcribed and analyzed using a thematic qualitative approach.

Results

A total of 42 people took part in 7 focus group interviews of 6 people each. The analysis showed that participants would like to receive support from technology for a broad range of aspects of nutrition, such as measuring the effect their personal nutrition has on their individual health, providing them with reliable product information, giving them practical guidance for healthy eating and snacking, and reducing the burden of registering food intake. Technology should be easy to use, reduce burdens, and be tailored to personal situations. Privacy and cost were major concerns for the participants.

Conclusions

This study shows that people from low– and medium–socioeconomic-status groups have a need for specific support in tailoring their knowledge of healthy nutrition to their own situation and see technology as a means to achieve this.

Characteristics of smartphone-based dietary assessment tools: a systematic review

Smartphones have become popular in assessing eating behaviour in real-life and real-time. This systematic review provides a comprehensive overview of smartphone-based dietary assessment tools, focusing on how dietary data is assessed and its completeness ensured. Seven databases from behavioural, social and computer science were searched in March 2020. All observational, experimental or intervention studies and study protocols using a smartphone-based assessment tool for dietary intake were included if they reported data collected by adults and were published in English. Out of 21,722 records initially screened, 117 publications using 129 tools were included. Five core assessment features were identified: photo-based assessment (48.8% of tools), assessed serving/ portion sizes (48.8%), free-text descriptions of food intake (42.6%), food databases (30.2%), and classification systems (27.9%). On average, a tool used two features. The majority of studies did not implement any features to improve completeness of the records. This review provides a comprehensive overview and framework of smartphone-based dietary assessment tools to help researchers identify suitable assessment tools for their studies. Future research needs to address the potential impact of specific dietary assessment methods on data quality and participants' willingness to record their behaviour to ultimately improve the quality of smartphone-based dietary assessment for health research.

White Paper: Open Digital Health - accelerating transparent and scalable health promotion and treatment

In this White Paper, we outline recommendations from the perspective of health psychology and behavioural science, addressing three research gaps: (1) What methods in the health psychology research toolkit can be best used for developing and evaluating digital health tools? (2) What are the most feasible strategies to reuse digital health tools across populations and settings? (3) What are the main advantages and challenges of sharing (openly publishing) data, code, intervention content and design features of digital health tools? We provide actionable suggestions for researchers joining the continuously growing Open Digital Health movement, poised to revolutionise health psychology research and practice in the coming years. This White Paper is positioned in the current context of the COVID-19 pandemic, exploring how digital health tools have rapidly gained popularity in 2020-2022, when world-wide health promotion and treatment efforts rapidly shifted from face-to-face to remote delivery. This statement is written by the Directors of the not-for-profit Open Digital Health initiative (n = 6), Experts attending the European Health Psychology Society Synergy Expert Meeting (n = 17), and the initiative consultant, following a two-day meeting (19-20th August 2021).

Exploring Saudi Individuals' Perspectives and Needs to Design a Hypertension Management Mobile Technology Solution: Qualitative Study

Hypertension is a chronic condition caused by a poor lifestyle that affects patients' lives. Adherence to self-management programs increases hypertension self-monitoring, and allows greater prevention and disease management. Patient compliance with hypertension self-management is low in general; therefore, mobile health applications (mHealth-Apps) are becoming a daily necessity and provide opportunities to improve the prevention and treatment of chronic diseases, including hypertension. This research aims to explore Saudi individuals' perspectives and needs regarding designing a hypertension management mobile app to be used by hypertension patients to better manage their illnesses. Semi-structured interviews were conducted with 21 Saudi participants to explore their perspectives and views about the needs and requirements in designing a hypertension mobile technology solution, as well as usability and culture in the Saudi context. The study used NVivo to analyze data and divided the themes into four main themes: the app's perceived health benefits, features and usability, suggestions for the app's content, and security and privacy. The results showed that there are many suggestions for improvements in mobile health apps that developers should take into consideration when designing apps. The mobile health apps should include physical activity tracking, related diet information, and reminders, which are promising, and could increase adherence to healthy lifestyles and consequently improve the self-management of hypertension patients. Mobile health apps provide opportunities to improve hypertension patients' self-management and self-monitoring. However, this study asserts that mobile health apps should not share users' data, and that adequate privacy disclosures should be implemented.

Users' Perspective on the AI-Based Smartphone PROTEIN App for Personalized Nutrition and Healthy Living: A Modified Technology Acceptance Model (mTAM) Approach

The ubiquitous nature of smartphone ownership, its broad application and usage, along with its interactive delivery of timely feedback are appealing for health-related behavior change interventions via mobile apps. However, users' perspectives about such apps are vital in better bridging the gap between their design intention and effective practical usage. In this vein, a modified technology acceptance model (mTAM) is proposed here, to explain the relationship between users' perspectives when using an AI-based smartphone app for personalized nutrition and healthy living, namely, PROTEIN, and the mTAM constructs toward behavior change in their nutrition and physical activity habits. In particular, online survey data from 85 users of the PROTEIN app within a period of 2 months were subjected to confirmatory factor analysis (CFA) and regression analysis (RA) to reveal the relationship of the mTAM constructs, i.e., perceived usefulness (PU), perceived ease of use (PEoU), perceived novelty (PN), perceived personalization (PP), usage attitude (UA), and usage intention (UI) with the users' behavior change (BC), as expressed via the acceptance/rejection of six related hypotheses (H1-H6), respectively. The resulted CFA-related parameters, i.e., factor loading (FL) with the related p-value, average variance extracted (AVE), and composite reliability (CR), along with the RA results, have shown that all hypotheses H1-H6 can be accepted (p < 0.001). In particular, it was found that, in all cases, FL > 0.5, CR > 0.7, AVE > 0.5, indicating that the items/constructs within the mTAM framework have good convergent validity. Moreover, the adjusted coefficient of determination (R 2) was found within the range of 0.224-0.732, justifying the positive effect of PU, PEoU, PN, and PP on the UA, that in turn positively affects the UI, leading to the BC. Additionally, using a hierarchical RA, a significant change in the prediction of BC from UA when the UI is used as a mediating variable was identified. The explored mTAM framework provides the means for explaining the role of each construct in the functionality of the PROTEIN app as a supportive tool for the users to improve their healthy living by adopting behavior change in their dietary and physical activity habits. The findings herein offer insights and references for formulating new strategies and policies to improve the collaboration among app designers, developers, behavior scientists, nutritionists, physical activity/exercise physiology experts, and marketing experts for app design/development toward behavior change.

Usage of Mobile Applications or Mobile Health Technology to Improve Diet Quality in Adults

The use of mobile applications for dietary purposes has dramatically increased along with the consistent development of mobile technology. Assessing diet quality as a dietary pattern or an indicator across key food groups in comparison to those recommended by dietary guidelines is useful for identifying optimal nutrient intake. This systematic review aims to explore mobile applications and their impact on the diet quality of the user. The electronic databases of The Cumulative Index to Nursing and Allied Health Literature (Cinahl), The American Psychological Association’s (APA Psycinfo), and PubMed were systematically searched for randomised and non-randomised controlled trials to retrieve papers from inception to November 2021. Ten studies with 1638 participants were included. A total of 5342 studies were retrieved from the database searches, with 10 articles eligible for final inclusion in the review. The sample sizes ranged from 27 to 732 participants across the included studies, with 1638 total participants. The ratio of female to male participants in the studies was 4:1. The majority of the mobile applications or M-health interventions were used to highlight dietary health changes (six studies), with the remainder used to reduce weight or blood sugar levels (four studies). Each study used a different measure to quantify diet quality. Studies were either assessed by diet quality scoring or individual dietary assessment, of the ten studies, six studies reported an improvement in diet quality following diet-related mobile application use. Mobile applications may be an effective way to improve diet quality in adults; however, there is a need for more targeted and longer-term studies that are expressly designed to investigate the impact using mobile applications has on diet quality.

mHealth Interventions for Self-management of Hypertension: Framework and Systematic Review on Engagement, Interactivity, and Tailoring

BACKGROUND

Engagement is essential for the effectiveness of digital behavior change interventions. Existing systematic reviews examining hypertension self-management interventions via mobile apps have primarily focused on intervention efficacy and app usability. Engagement in the prevention or management of hypertension is largely unknown.

OBJECTIVE

This systematic review explores the definition and role of engagement in hypertension-focused mobile health (mHealth) interventions, as well as how determinants of engagement (ie, tailoring and interactivity) have been implemented.

METHODS

A systematic review of mobile app interventions for hypertension self-management targeting adults, published from 2013 to 2020, was conducted. A total of 21 studies were included in this systematic review.

RESULTS

The engagement was defined or operationalized as a microlevel concept, operationalized as interaction with the interventions (ie, frequency of engagement, time or duration of engagement with the program, and intensity of engagement). For all 3 studies that tested the relationship, increased engagement was associated with better biomedical outcomes (eg, blood pressure change). Interactivity was limited in digital behavior change interventions, as only 7 studies provided 2-way communication between users and a health care professional, and 9 studies provided 1-way communication in possible critical conditions; that is, when abnormal blood pressure values were recorded, users or health care professionals were notified. The tailoring of interventions varied at different aspects, from the tailoring of intervention content (including goals, patient education, advice and feedback from health professionals, reminders, and motivational messages) to the tailoring of intervention dose and communication mode. Tailoring was carried out in a number of ways, considering patient characteristics such as goals, preferences, disease characteristics (eg, hypertension stage and medication list), disease self-management experience levels, medication adherence rate, and values and beliefs.

CONCLUSIONS

Available studies support the importance of engagement in intervention effectiveness as well as the essential roles of patient factors in tailoring, interactivity, and engagement. A patient-centered engagement framework for hypertension self-management using mHealth technology is proposed here, with the intent of facilitating intervention design and disease self-management using mHealth technology.

User Engagement and Abandonment of mHealth: A Cross-Sectional Survey

Mobile health (mHealth) apps have great potential to improve health outcomes. Given that mHealth apps have become ubiquitous, there is limited focus on their abandonment. Data concerning crucial metrics, including reasons for adoption and discontinued use, are limited. This study aims to gain broad insights into utilization of mHealth and game-like features promoting user engagement. We conducted a cross-sectional survey of 209 mHealth users worldwide. The 17-item survey assessed sociodemographics, as well as the key motivators for mHealth uptake and discontinued use. Our findings show that sports and fitness activity tracking were the most common categories of health apps, with most users engaging with them at least several times a week. Interestingly, the most downloaded mHealth apps among younger adults include MyFitnessPal, Fitbit, Nike Run Club, and Samsung Health. Critical drivers of abandonment of mHealth apps were amotivation, loss of interest, and experimenting with different apps to identify the most suitable tool. Additionally, the financial cost of mHealth apps is crucial, with most participants advocating for free or more affordable apps. The study findings suggest that while many individuals utilize mHealth, several factors drive their abandonment. Moreover, data indicate that mHealth developers need to consider gamification strategies to sustain user commitment, as well as psychological variables, such as intrinsic motivation.

Quality improvement and usability testing of the PortfolioDiet.app, a web-based health application to translate nutrition therapy for cardiovascular risk reduction in primary care (Preprint)

Background

The Portfolio Diet, or Dietary Portfolio, is a therapeutic dietary pattern that combines cholesterol-lowering foods to manage dyslipidemia for the prevention of cardiovascular disease. To translate the Portfolio Diet for primary care, we developed the PortfolioDiet.app as a patient and physician educational and engagement tool for PCs and smartphones. The PortfolioDiet.app is currently being used as an add-on therapy to the standard of care (usual care) for the prevention of cardiovascular disease in primary care. To enhance the adoption of this tool, it is important to ensure that the PortfolioDiet.app meets the needs of its target end users.

Objective

The main objective of this project is to undertake user testing to inform modifications to the PortfolioDiet.app as part of ongoing engagement in quality improvement (QI).

Methods

We undertook a 2-phase QI project from February 2021 to September 2021. We recruited users by convenience sampling. Users included patients, family physicians, and dietitians, as well as nutrition and medical students. For both phases, users were asked to use the PortfolioDiet.app daily for 7 days. In phase 1, a mixed-form questionnaire was administered to evaluate the users’ perceived acceptability, knowledge acquisition, and engagement with the PortfolioDiet.app. The questionnaire collected both quantitative and qualitative data, including 2 open-ended questions. The responses were used to inform modifications to the PortfolioDiet.app. In phase 2, the System Usability Scale was used to assess the usability of the updated PortfolioDiet.app, with a score higher than 70 being considered acceptable.

Results

A total of 30 and 19 users were recruited for phase 1 and phase 2, respectively. In phase 1, the PortfolioDiet.app increased users’ perceived knowledge of the Portfolio Diet and influenced their perceived food choices. Limitations identified by users included challenges navigating to resources and profile settings, limited information on plant sterols, inaccuracies in points, timed-logout frustration, request for step-by-step pop-up windows, and request for a mobile app version; when looking at positive feedback, the recipe section was the most commonly praised feature. Between the project phases, 6 modifications were made to the PortfolioDiet.app to incorporate and address user feedback. At phase 2, the average System Usability Scale score was 85.39 (SD 11.47), with 100 being the best possible.

Conclusions

By undertaking user testing of the PortfolioDiet.app, its limitations and strengths were able to be identified, informing modifications to the application, which resulted in a clinical tool that better meets users’ needs. The PortfolioDiet.app educates users on the Portfolio Diet and is considered acceptable by users. Although further refinements to the PortfolioDiet.app will continue to be made before its evaluation in a clinical trial, the result of this QI project is an improved clinical tool.

Digital Interventions to Promote Healthy Eating in Children: Umbrella Review

BACKGROUND

eHealth and web-based service delivery have become increasingly common during the COVID-19 pandemic. Digital interventions may be highly appealing to young people; however, their effectiveness compared with that of the usual face-to-face interventions is unknown. As nutrition interventions merge with the digital world, there is a need to determine the best practices for digital interventions for children.

OBJECTIVE

The aim of this study is to examine the effectiveness of digital nutrition interventions for children on dietary outcomes compared with status quo interventions (eg, conventional face-to-face programming or nondigital support).

METHODS

We conducted an umbrella review of systematic reviews of studies assessing primary research on digital interventions aimed at improving food and nutrition outcomes for children aged <18 years compared with conventional nutrition education were eligible for inclusion.

RESULTS

In total, 11 systematic reviews published since 2015 were included (7/11, 64%, were of moderate quality). Digital interventions ranged from internet, computer, or mobile interventions to websites, programs, apps, email, videos, CD-ROMs, games, telehealth, SMS text messages, and social media, or a combination thereof. The dose and duration of the interventions varied widely (single to multiple exposures; 1-60 minutes). Many studies have been informed by theory or used behavior change techniques (eg, feedback, goal-setting, and tailoring). The effect of digital nutrition interventions for children on dietary outcomes is small and inconsistent. Digital interventions seemed to be the most promising for improving fruit and vegetable intake compared with other nutrition outcomes; however, reviews have found mixed results.

CONCLUSIONS

Owing to the heterogeneity and duration of digital interventions, follow-up evaluations, comparison groups, and outcomes measured, the effectiveness of these interventions remains unclear. High-quality evidence with common definitions for digital intervention types evaluated with validated measures is needed to improve the state of evidence, to inform policy and program decisions for health promotion in children. Now is the time for critical, robust evaluation of the adopted digital interventions during and after the COVID-19 pandemic to establish best practices for nutrition interventions for children.

Short and Long-Term Innovations on Dietary Behavior Assessment and Coaching: Present Efforts and Vision of the Pride and Prejudice Consortium

Overweight, obesity and cardiometabolic diseases are major global health concerns. Lifestyle factors, including diet, have been acknowledged to play a key role in the solution of these health risks. However, as shown by numerous studies, and in clinical practice, it is extremely challenging to quantify dietary behaviors as well as influencing them via dietary interventions. As shown by the limited success of 'one-size-fits-all' nutritional campaigns catered to an entire population or subpopulation, the need for more personalized coaching approaches is evident. New technology-based innovations provide opportunities to further improve the accuracy of dietary assessment and develop approaches to coach individuals towards healthier dietary behaviors. Pride & Prejudice (P&P) is a unique multi-disciplinary consortium consisting of researchers in life, nutrition, ICT, design, behavioral and social sciences from all four Dutch Universities of Technology. P&P focuses on the development and integration of innovative technological techniques such as artificial intelligence (AI), machine learning, conversational agents, behavior change theory and personalized coaching to improve current practices and establish lasting dietary behavior change.