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This chapter attempts to distinguish the major types of distribution channels firms utilize, including distributors and retailers. Key characteristics are identified of direct channels. Then, indirect channels are detailed, including the major challenges faced in operating them. What determines whether a direct or indirect channel is chosen and implemented by the firm is explained in a clear fashion. However, that said, and in most cases, both direct and indirect channels are utilized by firms in multiple-channel distribution arrangements.
Accurate assessment of an individual’s diet is vital to study the effect of diet on health. Image-based methods, which use images as input, may improve the reliability of dietary assessment. We developed an iOS application that uses computer vision to identify food from images. This study aimed to assess the accuracy of energy intake (EIapp) estimates from the application by comparing them to estimated energy expenditure (EE) and to the EI estimates from a validated dietary assessment tool, the 24-h recall (EIrecall). Participants were recruited from a randomised controlled trial called He Rourou Whai Painga. Participants recorded all intake over 7 d using the application, which provided a mean daily EI; this was compared to the EI estimated by two 24-h recalls. The EI from the application and the recalls were compared to EE, estimated using indirect calorimetry and wrist-worn accelerometry. EI estimates from the application and the 24-h recalls were lower than EE, with a mean bias of -1814 kJ (95% CI -3012 to -615, p = 0.005) and -1715 kJ (95% CI -3237 to -193, p = 0.029), respectively. The mean bias between EI from the application and the 24-h recall was 783 kJ (95% CI -875 to 2441, p = 0.33). This suggests that the EI estimates from the application are comparable to the 24-h recall method, a validated and widely used tool in nutritional research.
Interstage monitoring programs for single ventricle disease have been developed to reduce morbidity and mortality. There is increased use of telemedicine and mobile application monitoring. It is unknown if there are disparities in use based on patient socio-demographic factors.
Methods:
We conducted a retrospective cohort study of patients enrolled in the single ventricle monitoring program and KidsHeart application at a single centre from 4/21/2021 to 12/31/2023. We investigated the association of socio-demographic factors with telemedicine usage, mobile application enrollment and usage. We assessed resource utilisation and weight changes by program era.
Results:
There were 94 children in the cohort. Patients with Norwood and ductal stent had higher mean telemedicine visits per month (1.8 visits, p = 0.004), without differences based on socio-demographic factors. There were differences in application enrollment with more Black patients enrolled compared to White patients (p = 0.016). There were less Hispanic patients enrolled than Non-Hispanic patients (p = 0.034). There were no Spaish speaking patient’s enrolled (p = 0.0015). There were no patients with maternal education of less than high school enrolled and all those with maternal education of advanced degree were enrolled (p = 0.0016). There was decreased mobile application use in those from neighbourhoods in the lowest income quartile. There were decreased emergency department visits with mobile application monitoring. Mean weight-for-age z-scores had increased from start to completion of the program in all eras.
Discussion:
Differences were seen in mobile application enrollment and usage based on socio-demographic factors. Further work is needed to ensure that all patients have access to mobile application usage.
There is increasing empirical evidence for the positive mental health effects of compassion-based interventions. Although numerous smartphone apps offering compassion-based interventions (‘compassion apps’) are now available for the general public, the quality of these apps has not yet been reviewed. A qualitative review of existing compassion apps serves as a crucial first step toward testing the efficacy of these apps, by identifying good-quality compassion apps that might be worth the investment of a scientific trial.
Aims
The current study focuses on reviewing the quality of existing compassion apps.
Method
Existing compassion apps were identified through searches in the Google Play Store and App Store. The 24 included apps were reviewed on their quality by using the Mobile App Rating Scale, and on their consistency with current evidence by comparing them to existing and studied compassion-based interventions.
Results
Of the 24 included apps, eight were identified that met the criteria of being consistent with existing and studied compassion-based interventions, and acceptable to good overall quality. The other 16 apps failed to meet one or both of these criteria.
Conclusions
Good-quality compassion apps are available, but many of the available apps fail to meet certain quality criteria. In particular, many apps failed to offer sufficient relevant and correct information, or failed to offer this information in an entertaining and interesting way. It is recommended that future compassion apps are based on a clear definition of compassion, offer evidence- and theory-based exercises and implement tools for increasing engagement.
Smartphone applications are used widely in healthcare, including antimicrobial applications such as Microguide. There has been no review of hospitals using this smartphone application for ENT conditions.
Methods
This study analysed all hospital accounts using Microguide and examined the ENT conditions that were listed.
Results
In total, 123 hospitals were included in this study; 45 ENT-related conditions were listed on Microguide across all hospitals, with an average of 8 conditions listed per hospital.
Conclusion
There is a significant disparity of ENT conditions listed on Microguide. A suggested list is recommended to be included for ENT departments using Microguide, to help improve antimicrobial stewardship for the specialty.
Nutrition-related smartphone applications (apps) could improve children’s nutrition knowledge and skills. However, little is known about the quality of nutrition-related apps for children. This study aimed to identify and evaluate the quality of nutrition-related smartphone apps designed for children ages 4–17.
Design:
This systematic appraisal is guided by the Protocol for App Store Systematic Reviews.
Setting:
Using Google’s Advanced Search, we identified 1814 apps/1184 additional apps in an updated search on iOS, of which twenty-four were eligible. The apps’ objective and subjective quality were evaluated using the twenty-three-item, five-point Mobile App Rating Scale. The objective quality scale consists of four subscales: engagement, functionality, aesthetics and information.
Results:
Most of the apps (75 %) focussed solely on promoting nutrition skills, such as making food dishes, rather than nutrition knowledge. Of the twenty-four apps, 83 % targeted children 4–8 years old. The app objective quality mean score was 3·60 ± 0·41. The subscale mean scores were 3·20 ± 0·41 for engagement, 4·24 ± 0·47 for functionality, 4·03 ± 0·51 for aesthetics and 2·94 ± 0·62 for information. The app subjective quality mean score was 2·10 ± 0·90.
Conclusions:
More robust approaches to app development leveraging co-design approaches, including involving a multidisciplinary team of experts to provide evidence-based nutrition information, are warranted.
Mental health clinicians perform complex tasks with patients that potentially could be improved by the massive computing power available through mobile apps. This study aimed to analyse commercially available mobile and computer applications (apps) focused on treating psychiatric disorders. Apps were analysed by two independent raters for whether they took advantage of computer power to process data in a fashion that augments four main elements of clinical treatment including (1) assessment/diagnosis, (2) treatment planning, (3) treatment fidelity monitoring, and (4) outcome tracking. The evidence base for each of these apps was also explored via PsychINFO, Research Gate and Google Scholar. Searches of the Google Play Store, the Apple App Store, and the One Mind PsyberGuide found 722 apps labelled for mental health use, of which 163 apps were judged relevant to clinical work with patients with psychiatric disorders. Fifty-nine of these were determined to contain a computer-driven function for at least one of the four main elements of clinical treatment. The most common element was assessment/diagnosis (55/59 apps), followed by outcome tracking (34/59 apps). Six apps updated treatment plans using user input. Only one app tracked treatment fidelity. None of the apps contained computer-driven functions for all four elements. Twelve apps were supported in randomized clinical trials to show greater efficacy compared with either wait-list or other active treatments. Results showed that these four clinical elements can be meaningfully augmented, but the full potential of computer processing appears unreached in mental health-related apps.
Key learning aims
(1) To understand what apps are currently available to treat clinical-level psychiatric problems.
(2) To understand how many of the commercially available mental health-focused apps can be used for the treatment of clinical populations.
(3) To understand how mental health services can be complemented by utilizing computer processing power within apps.
The objective of this scoping review was to examine the research question: In the adults with or without cardiometabolic risk, what is the availability of literature examining interventions to improve or maintain nutrition and physical activity-related outcomes? Sub-topics included: (1) behaviour counseling or coaching from a dietitian/nutritionist or exercise practitioner, (2) mobile applications to improve nutrition and physical activity and (3) nutritional ergogenic aids.
Design:
The current study is a scoping review. A literature search of the Medline Complete, CINAHL Complete, Cochrane Database of Systematic Reviews and other databases was conducted to identify articles published in the English language from January 2005 until May 2020. Data were synthesised using bubble charts and heat maps.
Setting:
Out-patient, community and workplace.
Participants:
Adults with or without cardiometabolic risk factors living in economically developed countries.
Results:
Searches resulted in 19 474 unique articles and 170 articles were included in this scoping review, including one guideline, thirty systematic reviews (SR), 134 randomised controlled trials and five non-randomised trials. Mobile applications (n 37) as well as ergogenic aids (n 87) have been addressed in several recent studies, including SR. While primary research has examined the effect of individual-level nutrition and physical activity counseling or coaching from a dietitian/nutritionist and/or exercise practitioner (n 48), interventions provided by these practitioners have not been recently synthesised in SR.
Conclusion:
SR of behaviour counseling or coaching provided by a dietitian/nutritionist and/or exercise practitioner are needed and can inform practice for practitioners working with individuals who are healthy or have cardiometabolic risk.
Health apps are software programs that are designed to prevent, diagnose, monitor, or manage conditions. Inconsistent terminology for apps is used in research literature and bibliographic database subject headings. It can therefore be challenging to retrieve evidence about them in literature searches. Information specialists at the United Kingdom's National Institute for Health and Care Excellence (NICE) have developed novel validated search filters to retrieve evidence about apps from MEDLINE and Embase (Ovid).
Methods
A selection of medical informatics journals was hand searched to identify a “gold standard” (GS) set of references about apps. The GS set was divided into a development and validation set. The filters’ search terms were derived from and tested against the development set. An external development set containing app references from published NICE products was also used to inform the development of the filters. The filters were then validated using the validation set. Target recall was >90 percent. The filters’ overall recall, specificity, and precision were calculated using all the references identified from the hand search.
Results
Both filters achieved 98.6 percent recall against their validation sets. Overall, the MEDLINE filter had 98.8 percent recall, 71.3 percent specificity, and 22.6 percent precision. The Embase filter had 98.6 percent recall, 74.9 percent specificity, and 24.5 percent precision.
Conclusions
The NICE health apps search filters retrieve evidence about apps from MEDLINE and Embase with high recall. They can be applied to literature searches to retrieve evidence about the interventions by information professionals, researchers, and clinicians.
The aim of this study was to develop a module which could be used to facilitate the assessment of mobile medical applications (MMA) for regulatory and reimbursement purposes.
Methods
In-depth interviews were conducted with policymakers, healthcare practitioners, and application developers to determine possible pathways and impediments to MMA reimbursement. These findings were integrated with our previous research on MMA reimbursement and regulation to create a module that could be used with existing health technology assessment (HTA) methodological frameworks to guide the evaluation of MMAs.
Results
Stakeholders indicated that they trust how traditional medical devices are currently appraised for reimbursement. They were concerned that there was a lack of clarity regarding which entity in the health system was responsible for determining app quality. They were also concerned about the digital health literacy of medical practitioners and patients. Concepts emerging from our previous research were reinforced by the interview findings, including that the connectivity and cybersecurity of apps need to be considered, along with an assessment of software reliability. It is also critical that the credibility of the information presented in apps is assessed as it could potentially mislead patients and clinicians.
Conclusion
An MMA evaluation module was created that would enable an existing HTA process to be adapted for the assessment of MMA technology. These adaptations include making provisions for an assessment of app cybersecurity, the impact on MMA clinical utility of software updates, and compatibility issues. Items to address concerns around practitioner responsibility and app misinformation were also incorporated into the module.
The number of medical mobile phone applications continues to grow. Although otorhinolaryngology-specific applications represent a small proportion, there are exciting innovations emerging for the specialty. This article will assess the number of applications available and review how they may be used in clinical practice.
Method
The application stores of the two most popular mobile phone platforms, Apple and android, were searched using multiple search terms.
Results
A total of 107 ENT applications were identified and categorised according to intended use. Eight applications were reviewed in more detail and assessed on whether a doctor or allied health professional was involved in their design and if they were evidence-based.
Conclusion
There are a number of ENT-specific smartphone applications currently available. As the technology progresses, their scope has extended beyond being purely for reference. Nevertheless, it remains difficult to assess the validity and security of these applications.
The aim of this study is to determine whether the approach used in Australia to regulate mobile medical applications (MMA) is consistent with international standards and is suitable to address the unique challenges of these technologies.
Methods
The policies of members of the International Medical Device Regulator's Forum (IMDRF) were analyzed, to determine whether these regulatory bodies address IMDRF recommendations for the clinical evaluation of software as a medical device (SaMD). Case-studies of varying types of regulated MMAs in Australia and the United States were also reviewed to determine how well the guidance in the IMDRF's SaMD: Clinical Evaluation (2017) document was operationalized.
Results
All included jurisdictions evaluated the effectiveness of MMAs and addressed the majority of the key sub-categories recommended in the IMDRF guidance document. However, safety principles concerning information security (cybersecurity) and potential dangers of misinformation (risk-classification) were generally not addressed in either the case-studies or in the policy documents of international regulatory bodies. Australia's approach was consistent with MMA regulation conducted internationally. None of the approaches used by global regulatory bodies adequately addressed the risk of misinformation from apps and the potential for adverse clinical consequences.
Conclusions
The risks posed by MMAs are mainly through the information they provide and how this is used in clinical decision-making. Policy in Australia and elsewhere should be adjusted to follow the IMDRF risk-classification criteria to address potential harms from misinformation. Australian regulatory information should also be updated so the harm posed by cybersecurity and connectivity can be comprehensively evaluated.
To describe low-income parents’ and caregivers’ perceptions of the Cooking Matters Mobile Application (CM App) meal planning and preparation features.
Design:
Explanatory mixed-methods design where data were gathered via online surveys based on the Theory of Planned Behaviour and the Theory of Reasoned Action, followed by telephone interviews.
Setting:
CM App, a mobile phone-based resource geared towards low-income parents and caregivers of young children (pregnancy/infant to age 5 years) for meal planning and preparation, with features based on skills taught in the Cooking Matters course: recipes, shopping list and meal planning.
Participants:
Low-income parents and caregivers (survey participants, n 461; interview participants, n 20) who had downloaded the CM App to their smartphone and agreed to participate in the current evaluation.
Results:
Attitudes and self-efficacy related to CM App’s subject matter and functions (meal planning; recipe use; creating and using a shopping list) were measured via surveys and interviews. Mean (sd) responses were positive towards ‘meal planning’ and ‘shopping and cooking’ (4·17 (0·63) and 3·49 (0·86) on a 5-point Likert scale, respectively). Interviewees described meal planning and preparation behaviours as intrinsic, based on habit, and influenced by family preference and food costs. Early adopters of the CM App may already be engaged in and/or are motivated to engage in the targeted health behaviours.
Conclusions:
Users may benefit most from incorporating into their routines new ways to prepare easy, cost-efficient, healthy meals at home that their families will enjoy.
A crucial component of a hospital’s disaster plan is an efficient staff recall communication method. Many hospitals use a “calling tree” protocol to contact staff members and recall them to work. Alternative staff recall methods have been proposed and explored.
Methods
An unannounced, multidisciplinary, randomized emergency department (ED) staff recall drill was conducted at night - when there is the greatest need for back-up personnel and staff is most difficult to reach. The drill was performed on December 14, 2017 at 4:00am and involved ED staff members from three hospitals which are all part of the McGill University Health Centre (MUHC; Montreal, Quebec, Canada). Three tools were compared: manual phone tree, instant messaging application (IMA), and custom-made hospital Short Message Service (SMS) system. The key outcome measures were proportion of responses at 45 minutes and median response time.
Results
One-hundred thirty-two participants were recruited. There were 44 participants in each group after randomization. In the manual phone tree group, 18 (41%) responded within 45 minutes. In the IMA group, 11 participants (25%) responded in the first 45 minutes. In the SMS group, seven participants responded in the first 45 minutes (16%). Manual phone tree was significantly better than SMS with an effect size of 25% (95% confidence interval for effect: 4.6% to 45.0%; P=.018). Conversely, there was no significant difference between manual phone tree and IMA with an effect size of 16% (95% confidence interval for effect: −5.7% to 38.0%; P=.17) There was a statistically significant difference in the median response time between the three groups with the phone tree group presenting the lowest median response time (8.5 minutes; range: 2.0 to 8.5 minutes; P=.000006).
Conclusion:
Both the phone tree and IMA groups had a significantly higher response rate than the SMS group. There was no significant difference between the proportion of responses at 45 minutes in the phone tree and the IMA arms. This study suggests that an IMA may be a viable alternative to the traditional phone tree method. Limitations of the study include volunteer bias and the fact that there was only one communication drill, which did not allow staff members randomized to the IMA and SMS groups to fully get familiar with the new staff recall methods.
HomierV, HamadR, LarocqueJ, ChasséP, KhalilE, FrancJM.A Randomized Trial Comparing Telephone Tree, Text Messaging, and Instant Messaging App for Emergency Department Staff Recall for Disaster Response. Prehosp Disaster Med. 2018;33(5):471–477.
Smartphone Apps are one of the tools available to support patients who wish to quit smoking. Content analysis studies have indicated multiple deficiencies within these Apps including minimal use of evidence-based research and Nicotine Dependence Treatment Provider (NDTP) in App development. The aim of this study was to determine quality and features of smoking cessation Apps available on Android® and iOS® platforms.
Methods:
The first fifty free smoking cessation Apps available for download using the search term smoking cessation on Google Play Store and Apple App Store were chosen. Each of these Apps was analyzed and categorized based on ratings, target audience age, language, and a variety of tracking functionalities noted on the Apps. Indications and suggestions regarding either the use of NDTP or evidence-based behavior change protocols were noted.
Results:
There were no significant differences in the features of smoking cessation Apps on Android and iOS. Only 15 percent of all Apps analyzed on both platforms indicated some involvement of NDTP and there was no difference between the two platforms. More than 50 percent of Apps studied were downloaded over half a million times and the average user rating was 3.89/5.00 for Android and 3.72/5.00 for iOS with no significant difference.
Conclusions:
Most smoking cessation Apps in both platforms offer basic tracking functionalities with limited motivational tips. Only a handful of Apps have moved beyond this role and while their development is applaudable much innovation remains.
To identify and appraise existing evaluation frameworks for mobile medical applications (MMA) and determine their suitability for use in health technology assessment (HTA) of these technologies.
Methods:
Systematic searches were conducted of seven bibliographic databases to identify literature published between 2008 and 2016 on MMA evaluation frameworks. Frameworks were eligible if they were used to evaluate at least one of the HTA domains of effectiveness, safety, and/or cost and cost-effectiveness of an MMA. After inclusion, the frameworks were reviewed to determine the number and extent to which other elements of an HTA were addressed by the framework.
Results:
A total of forty-five frameworks were identified that assessed MMAs. All frameworks assessed whether the app was effective. Of the thirty-four frameworks that examined safety, only seven overtly evaluated potential harms from the MMA (e.g., the impact of inaccurate information). Only one framework explicitly considered a comparator. Technology specific domains were sporadically addressed.
Conclusion:
None of the evaluation frameworks could be used, unaltered, to guide the HTA of MMAs. To use these frameworks in HTA they would need to identify relevant comparators, improve assessments of harms and consider the ongoing effect of software updates on the safety and effectiveness of MMAs. Attention should also be paid to ethical issues, such as data privacy, and technology specific characteristics. Implications: Existing MMA evaluation frameworks are not suitable for use in HTA. Further research is needed before an MMA evaluation framework can be developed that will adequately inform policy makers.
This article attempts to highlight the challenges and possibilities for hearing healthcare through technology and aural rehabilitation in a resource-constrained setting, using South Africa as an example.
Results and conclusion
The authors argue that it is possible to enhance service delivery by using free resources and maximising the limited existing resources. In order to provide a sustainable hearing healthcare service in developing countries, it is pertinent to understand the context where the services are needed, and not just adopt an approach developed for a different context. Audiologists in such settings need to employ strategies to develop context-specific tools, and adapt existing tools to serve the needs of the local population. Some examples, although not exhaustive, are provided in the article.
To verify the reliability of information, the sources of information used and the user opinions of the free mobile applications (apps) with nutritional information available in Brazil.
Design
Descriptive, cross-sectional study.
Setting
We evaluated the content about nutrition of free apps available on the App Store of iPhone 5S with software iOS 8.4.1 and on the Play Store of the Android platform, version 2.3.6. For this, we compared the nutrition information provided by the app with (i) the Brazilian Food Composition Table (TACO), of 2011; (ii) food composition table: support for nutritional decision, of 2002; and (iii) the National Study of Family Expenditure: food composition tables, of 1999. The evaluation included the description and quantity of macro- and micronutrients in foods. In addition, we evaluated the trustworthiness of information about food energy values and analysed the comments and ratings made by users.
Subjects
Mobile apps related to nutrition.
Results
We assessed sixteen apps for mobile devices. Considering the foods selected (a basic Brazilian food basket for the month of August 2015), the apps presented partially adequate or inadequate information about food composition (macro- and micronutrients). The adequacy of the food energy values ranged from 0 to 57·1 %. Despite this, the apps received positive ratings by users.
Conclusions
The mobile apps about nutrition currently available and evaluated in the present study in Brazil are not useful for nutritional guidance because most of them are not based on reliable sources of information.
The aim of the present paper is to summarise current and future applications of dietary assessment technologies in nutrition surveys in developed countries. It includes the discussion of key points and highlights of subsequent developments from a panel discussion to address strengths and weaknesses of traditional dietary assessment methods (food records, FFQ, 24 h recalls, diet history with interviewer-assisted data collection) v. new technology-based dietary assessment methods (web-based and mobile device applications). The panel discussion ‘Traditional methods v. new technologies: dilemmas for dietary assessment in population surveys’, was held at the 9th International Conference on Diet and Activity Methods (ICDAM9), Brisbane, September 2015. Despite respondent and researcher burden, traditional methods have been most commonly used in nutrition surveys. However, dietary assessment technologies offer potential advantages including faster data processing and better data quality. This is a fast-moving field and there is evidence of increasing demand for the use of new technologies amongst the general public and researchers. There is a need for research and investment to support efforts being made to facilitate the inclusion of new technologies for rapid, accurate and representative data.
Mobile applications, or apps, have gained widespread use with the advent of modern smartphone technologies. Previous research has been conducted in the use of mobile devices for learning. However, there is decidedly less research into the use of mobile apps for health learning (eg, patient self-monitoring, medical student learning). This deficiency in research on using apps in a learning context is especially severe in the disaster health field. The objectives of this article were to provide an overview of the current state of disaster health apps being used for learning, to situate the use of apps in a health learning context, and to adapt a learning framework for the use of mobile apps in the disaster health field. A systematic literature review was conducted by using the PRISMA checklist, and peer-reviewed articles found through the PubMed and CINAHL databases were examined. This resulted in 107 nonduplicative articles, which underwent a 3-phase review, culminating in a final selection of 17 articles. While several learning models were identified, none were sufficient as an app learning framework for the field. Therefore, we propose a learning framework to inform the use of mobile apps in disaster health learning. (Disaster Med Public Health Preparedness. 2017;11:487–495)