Literature DB >> 35171109

Mobile Apps for Hematological Conditions: Review and Content Analysis Using the Mobile App Rating Scale.

Álvaro Narrillos-Moraza1, Patricia Gómez-Martínez-Sagrera1, Miguel Ángel Amor-García1, Vicente Escudero-Vilaplana1, Roberto Collado-Borrell1, Cristina Villanueva-Bueno1, Ignacio Gómez-Centurión2, Ana Herranz-Alonso1, María Sanjurjo-Sáez1.   

Abstract

BACKGROUND: Hematological conditions are prevalent disorders that are associated with significant comorbidities and have a major impact on patient care. Concerning new tools for the care of these patients, the number of health apps aimed at hematological patients is growing. Currently, there are no quality analyses or classifications of apps for patients diagnosed with hematological conditions.
OBJECTIVE: The aim of this study is to analyze the characteristics and quality of apps designed for patients diagnosed with hematological conditions by using the Mobile App Rating Scale (MARS).
METHODS: We performed an observational, cross-sectional descriptive study of all smartphone apps for patients diagnosed with hematological conditions. A search was conducted in March 2021 using the following terms: anemia, blood cancer, blood disorder, hematological cancer, hematological malignancy, hematological tumor, hematology, hemophilia, hemorrhage, lymphoma, leukemia, multiple myeloma, thalassemia, thrombocytopenia, and thrombosis. The apps identified were downloaded and evaluated by 2 independent researchers. General characteristics were registered, and quality was analyzed using MARS scores. Interrater reliability was measured by using the Cohen κ coefficient.
RESULTS: We identified 2100 apps in the initial search, and 4.19% (88/2100) of apps met the inclusion criteria and were analyzed. Of the 88 apps, 61% (54/88) were available on Android, 30% (26/88) were available on iOS, and 9% (8/88) were available on both platforms. Moreover, 7% (6/88) required payment, and 49% (43/88) were updated in the last year. Only 26% (23/88) of the apps were developed with the participation of health professionals. Most apps were informative (60/88, 68%), followed by preventive (23/88, 26%) and diagnostic (5/88, 6%). Most of the apps were intended for patients with anemia (23/88, 26%). The mean MARS score for the overall quality of the 88 apps was 3.03 (SD 1.14), ranging from 1.19 (lowest-rated app) to 4.86 (highest-rated app). Only 47% (41/88) of the apps obtained a MARS score of over 3 points (acceptable quality). Functionality was the best-rated section, followed by aesthetics, engagement, information, and app subjective quality. The five apps with the highest MARS score were the following: Multiple Myeloma Manager, Hodgkin Lymphoma Manager, Focus On Lymphoma, ALL Manager, and CLL Manager. The analysis by operating system, developer, and cost revealed statistically significant differences in MARS scores (P<.001, P<.001, and P=.049, respectively). The interrater agreement between the 2 reviewers was substantial (k=0.78).
CONCLUSIONS: There is great heterogeneity in the quality of apps for patients with hematological conditions. More than half of the apps do not meet acceptable criteria for quality and content. Most of them only provide information about the pathology, lacking interactivity and personalization options. The participation of health professionals in the development of these apps is low, although it is narrowly related to better quality. ©Álvaro Narrillos-Moraza, Patricia Gómez-Martínez-Sagrera, Miguel Ángel Amor-García, Vicente Escudero-Vilaplana, Roberto Collado-Borrell, Cristina Villanueva-Bueno, Ignacio Gómez-Centurión, Ana Herranz-Alonso, María Sanjurjo-Sáez. Originally published in JMIR mHealth and uHealth (https://mhealth.jmir.org), 16.02.2022.

Entities:  

Keywords:  blood; hematology; mHealth; mobile apps; mobile phone; quality; rating tool

Mesh:

Year:  2022        PMID: 35171109      PMCID: PMC8892317          DOI: 10.2196/32826

Source DB:  PubMed          Journal:  JMIR Mhealth Uhealth        ISSN: 2291-5222            Impact factor:   4.947


Introduction

Background

The use of mobile technologies for health is increasing at an unstoppable rate. App capabilities for sharing health care information or real-time patient monitoring make them an important health tool because of their ease of use, broad reach, and wide acceptance [1]. At the beginning of 2021, more than 53,000 medical apps were available in the Android Play Store (one of the main download platforms) [2]. Medical apps have targeted a diverse number of conditions, such as diabetes [3,4], pain [5], rheumatic [6] and psychiatric disorders [7], COVID-19 [8-10], or cancer [11-13]. Apps for patients diagnosed with hematological conditions are also found on the main download platforms, although there is little information about them. Hematological conditions comprise a wide range of disorders that can be classified as nonmalignant (anemia, hemorrhagic, or thrombotic disorders and conditions affecting blood-forming organs) and malignant (hematological cancers, such as Hodgkin and non-Hodgkin lymphoma, leukemia, or multiple myeloma, among others) [14]. These diseases meet all criteria for qualifying as a very important public health problem, with serious morbidities affecting patients worldwide [14-16]. Many of these conditions, such as hemophilia or anemia, are highly prevalent and become chronic. These patients could benefit from tools that improve treatment adherence or self-management guidelines, making medical apps an increasingly attractive option for this purpose [17,18]. Considering the large number of health apps available for patients with hematological conditions and the increasing interest in tools that encourage patient self-care, a proper review is needed. However, no clear consensus exists as to the appropriate method to assess the quality of health apps [19]. The Mobile App Rating Scale (MARS) is the most widely used scale for evaluating the quality and content of health apps. This allows the evaluation and comparison of apps by relating to their user engagement, functionality, aesthetics, and information quality [20,21]. In addition, it provides a quantitative and validated system that allows both users and health care professionals to avoid unreliable information.

Objective

The aim of our study is to analyze the characteristics and quality of mobile apps for patients diagnosed with hematological conditions using the MARS.

Methods

Study Design

We performed an observational, descriptive, cross-sectional study of all smartphone apps for patients diagnosed with hematological conditions, including hematological malignancies, various types of anemia, and hemorrhagic and thrombotic diathesis, available on the Android and iOS platforms. The study followed the PRISMA-P (Preferred Reporting Items for Systematic Review and Meta-Analysis Protocols) 2015 guidelines for systematic reviews [22].

Eligibility Criteria

A search on the Apple App Store and Android Play Store was performed in February 2021 by 2 independent health professionals with experience in app analysis, design, and development (PGMS and ANM). The following search terms were used: anemia, blood cancer, blood disorder, hematological cancer, hematological malignancy, hematological tumor, hematology, hemophilia, hemorrhage, lymphoma, leukemia, multiple myeloma, thalassemia, thrombocytopenia, and thrombosis. The reviewers screened the title and download page of the apps. Only apps intended for patients or their caregivers and in English or Spanish were selected. Those apps potentially eligible were downloaded and installed on the appropriate, corresponding mobile device, regardless of the cost. iOS apps were installed on an iPhone 7 (version 14.4.2; Apple Inc) and Android apps on a Nexus 5X (Android version 8.1.0; Google LLC). Apps with nonscientific content; intended for health care professionals; duplicated; not specific for hematological conditions; specific to congresses, meetings, and charitable purposes; and those with restricted access were excluded from the review.

Data Extraction and Quality Assessment

Apps were individually evaluated in isolation by the same 2 independent reviewers. Variables analyzed were app name, search term (for what the app was found), platform (Android or iOS), developer, hematological disorder, cost, app category (books and reference works, education, entertainment, health and fitness, health and wellness, lifestyle, medicine, simulation, and social media), date of the last update, language, and purpose. Concerning the developer, if hospitals, health authorities, universities, scientific societies, or patients’ associations were involved in the design of an app, we classified them as developed by a health organization. The purpose was further classified into the following categories: diagnostic, informative, and preventive depending on whether the priority of the app was to run self-diagnosis, to provide generic data about one or several conditions, or to track treatment and symptoms, respectively. Grading was assessed by the same 2 independent reviewers according to the validated MARS. Data extraction, analysis, and grading were completed within 60 days. The MARS is a multidimensional instrument that assesses the quality of mobile health apps. The quality assessment consists of a total of 23 items covering 5 dimensions. The dimensions are (1) engagement (5 items: entertainment, interest, customization, interactivity, and target adequacy), (2) functionality (4 items: performance, ease of use, navigation, and gestural design), (3) aesthetics (3 items: layout, graphics, and visual appeal), (4) information quality (7 items: accuracy of app description, goals, quality of information, quantity of information, quality of visual information, evidence base, and credibility), and (5) subjective quality (4 items: recommendation, payment willingness, frequency of use, and overall rating). All items were rated on a 5-point scale (1=inadequate; 2=poor; 3=acceptable; 4=good; 5=excellent). Then, the overall quality of the app was obtained from the mean score of the domains [20,21].

Data Analysis

Quantitative variables were expressed as means and SDs and categorical variables as frequencies and percentages. Continuous variables were compared using the 2-tailed t test when the distribution was normal or the Mann-Whitney test when it was not. κ coefficient was used to measure the interrater reliability of the data analyzed by the 2 independent researchers [23]. Data were analyzed using Stata (version IC-16; StataCorp). A P value <.05 was considered statistically significant.

Results

Overview

A total of 2100 apps were retrieved from the Apple App Store and Android Play Store (1661 Android apps and 439 iOS apps). After screening the description and the screenshots available at the app platforms and deleting apps duplicated, 128 apps were selected as potentially eligible. After downloading and checking the fulfillment of the inclusion criteria, 88 apps were finally included in the descriptive analysis. A flow diagram illustrating the selection and exclusion of apps at various stages of the study is shown in Figure 1.
Figure 1

PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) flow diagram and app selection. MARS: Mobile App Rating Scale.

PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) flow diagram and app selection. MARS: Mobile App Rating Scale.

Characteristics and Purposes of Included Apps

In total, of the 88 apps, 8 (9%) were found on both digital distribution platforms, whereas 54 (61%) were obtained only from the Android Play Store, and 26 (30%) were only available at the Apple App Store. In addition, of the 88 apps, only 6 (7%) required payment (mean cost: mean €3.16 [US $3.60], SD €1.57 [US $1.79]). Table 1 shows the general characteristics of apps.
Table 1

General characteristics of the apps.

CharacteristicsApps, n (%)
Platform
Android54 (61)
iOS26 (30)
Android and iOS8 (9)
Cost
No82 (93)
Yes6 (7)
Category
Medicine35 (40)
Health and wellness33 (38)
Health and fitness8 (9)
Education7 (8)
Books and reference works1 (1)
Entertainment1 (1)
Lifestyle1 (1)
Simulation1 (1)
Social media1 (1)
Date of the last update
20121 (1)
20162 (2)
20177 (8)
201812 (14)
201919 (22)
202034 (39)
20219 (10)
Not updated4 (4)
Language
English80 (92)
Spanish4 (4)
English and Spanish4 (4)
General characteristics of the apps. Regarding purpose, most of the apps were informative (60/88, 68%), followed by preventive (23/88, 26%) and diagnostic (5/88, 6%). Of the 88 apps, a total of 43 apps (49%) were updated in the last year, and 23 apps (26%) were designed and developed with the participation of some kind of health care organization. The distribution of apps regarding hematological conditions was anemia (23/88, 26%), leukemia (12/88, 14%), hemophilia (11/88, 13%), thrombosis (8/88, 9%), thalassemia (7/88, 8%), hematological cancers (leukemia, lymphoma, or myeloma; 5/88, 6%), hemorrhage (5/88, 6%), lymphoma (4/88, 5%), leukemia or lymphoma (3/88, 3%), thrombocytopenia (3/88, 3%), multiple myeloma (2/88, 2%), hematological conditions (2/88, 2%), anemia or hemophilia (1/88, 1%), anemia or thalassemia (1/88, 1%), and hemochromatosis (1/88, 1%). The information on hematological conditions, purpose, app platform, free of cost, updates, developer, and language is shown in Tables 2 and 3.
Table 2

Characteristics of the apps analyzed. Apps are presented in alphabetical order, from those that start with "A" to those that start with "I."

Name of the app (developer)Hematological diseasePurposePlatformFreeUpdated in the last 12 monthsDeveloped by a health organizationLanguage
IaPbDciOSAndroid EdSe
Alimentos para la anemia (Jotathat)Anemia
All Blood Disease and Treatment A-Z (Patrikat Softech)Blood disorders
ALL Manager (Point of Care)Leukemia
ALL Xplained (MedicineX)Leukemia
Anemia (Rouseapps)Anemia
Anemia (El Makaoui)Anemia
Anemia Care Diet & Nutrition (RecoveryBull)Anemia
Anemia Home Remedies (StatesApps)Anemia
Anemia Home Remedies (Salim Garba Usman)Anemia
Bleeder (Hannes Jung)Hemophilia
Bleeding After Birth (Jaco Apps)Hemorrhage
Bleeding Disorder (Koodalappz)Hemorrhage
Blood Cancer (Digital Planete Space)Hematological cancers
Blood Cancer Tips (Free Apps For Everyone)Hematological cancers
Blood Clot Home & Natural Remedies (Salim Garba Usman)Thrombosis
Blood Count Reader free (Yurii Shevchenko)Anemia
Blood Diseases (Medico_Guide)Blood disorders
Blood Group Genes (Gaurav Mathur)Anemia or hemophilia
Caprini DVT Risk (NorthShore University HealthSystem)Thrombosis
Childhood Leukemia: A Preventable Disease (FreeCreativity2019)Leukemia
CIB—Coagulation Intervention Brigade (LFB Biomedicaments)Hemorrhage
CLL Manager (Point of Care)Leukemia
CLL Watch and Wait Tracker (Lymphoma Canada)Leukemia or lymphoma
CML Life (Incyte Corporation)Leukemia
CML Today (Leukemia Patient Advocates Foundation)Leukemia
Diario de INR (Web Factor BV)Thrombosis
Don’t Walk Alone (Lymphoma Canada)Leukemia
Easy Diagnosis—Thalassemia (Sarah Tinmaswala)Thalassemia
EasyCoagLite (Loic Letertre)Thrombosis
Focus On Lymphoma (Lymphoma Research Foundation)Lymphoma
Folate & B12 Counter and Tracker (First Line Medical Communications)Anemia
Food For Anemia (MixLabApps)Anemia
HaemActive—Fitness for People with haemophilia (NovoNordisk A/S)Hemophilia
Haemophilia Pal (Haemophilia Pal)Hemophilia
Hemo Control (The Simulation Crew)Hemophilia
Hemophilia Disease (Bedieman)Hemophilia
Hemophilia Support (MyHealthTeams)Hemophilia
Hodgkin Lymphoma Manager (Point of Care)Lymphoma
Home Remedies for Anemia (Anil Krishna)Anemia
How To Cure Leukemia (Apps How To Apps)Leukemia
iClot (Cranworth Medical Ltd)Thrombosis
Increase A Low Platelet Count Naturally (FingertipApps)Thrombocytopenia
INR Care (Nikhil Patel)Thrombosis
Iron Counter and Tracker (First Line Medical Communications)Anemia
Iron Deficiency Anemia (Bedieman)Anemia
Iron Tracker—Hemochromatosis (IronTracker)Hemochromatosis

aI: informative.

bP: preventive.

cD: diagnostic.

dE: English.

eS: Spanish.

Table 3

Characteristics of the apps analyzed. Apps are presented in alphabetical order, from those that start with "J" to those that start with "Z."

Name of the app (developer)Hematological diseasePurposePlatformFreeUpdated in the last 12 monthsDeveloped by a health organizationLanguage
IaPbDciOSAndroid EdSe
Juntos contra la anemia (Andres Moran Tello)Anemia
Leucemia—Sintomas Y Tratamiento—FAQ (Things To Do)Leukemia
Leukemia: Symptoms And Treatment (The Reyv)Leukemia
Leukemia Disease (Bedieman)Leukemia
Leukemia Disease Treatment (Woochi Developer)Leukemia
LLS CAR T (The Leukemia and Lymphoma Society)Blood cancers
LLS Health Manager (The Leukemia and Lymphoma Society)Blood cancers
LRF Understanding Lymphoma (Lymphoma Research Foundation)Lymphoma
LRFFactSheets (Lymphoma Research Foundation)Lymphoma
Microhealth Hemofilia (MicroHealth LLC)Hemophilia
Mi Hemofilia (Rogelio Robles Tarano)Hemophilia
Multiple Myeloma Manager (Point of Care)Multiple myeloma
My Blood Count (Sean Bottomley)Anemia
My HHT Tracker (Cure HHT)Hemochromatosis
My INR (iMonitorMy)Thrombosis
My Iron Manager (Good Dog Design Pty Ltd)Anemia
Myeloma Cancer Guide (Everyone Learning Apps)Multiple myeloma
myPROBE (Design2Code Inc)Hemophilia
myWAPPS (Design2Code Inc)Hemophilia
NCCN Patient Guides for Cancer (National Comprehensive Cancer Network)Blood cancers
PA Pernicious Anaemia (B12 Global Limited)Anemia
Pernicious-Anemia Advice (MoreFlow)Anemia
Pregnancy & Anaemia (Fumo)Anemia
Recetas y consejos para combatir la anemia (App Free Enjoy)Anemia
Recognize Anemia Disease (Media Clinic)Anemia
Recognize Hemophilia Disease (Media Clinic)Hemophilia
Recognize Thalassemia Disease (Media Clinic)Thalassemia
Recognize Thrombocytopenia (Media Clinic)Thrombocytopenia
Sickle Cell Anemia (Fumo)Anemia
Sickle Cell Anemia Home remedy (JGWS)Anemia
Sickle Cell Disease (Kabirapp)Anemia
STB—Stop The Bleed (Uniformed Services University)Hemorrhage
SUSOKA (Subrata Saha)Thalassemia
Thalassemia Early Detection (ILIANA)Thalassemia
Thalassemia Disease (Bedieman)Thalassemia
ThaliMe (Curatio Networks Inc)Thalassemia
thalTracker (University Health Network)Thalassemia
The Cancer App (Interactive Pharma solutions limited)Blood cancers
The Seven Types of Anemia (Mrbeli)Thalassemia or anemia
Transplant Guidelines (National Marrow Donor Program/Be The Match)Blood cancers
Trombocytopenia Disease (Bedieman)Thrombocytopenia
VTE Calc (Lindum Medical Ltd)Thrombosis

aI: informative.

bP: preventive.

cD: diagnostic.

dE: English.

eS: Spanish.

Characteristics of the apps analyzed. Apps are presented in alphabetical order, from those that start with "A" to those that start with "I." aI: informative. bP: preventive. cD: diagnostic. dE: English. eS: Spanish. Characteristics of the apps analyzed. Apps are presented in alphabetical order, from those that start with "J" to those that start with "Z." aI: informative. bP: preventive. cD: diagnostic. dE: English. eS: Spanish.

Rating of Apps on the MARS

The specific MARS ratings for each app are shown in Tables 4 and 5. The mean score for the overall quality was 3.03 (SD 1.14), ranging from 1.19 (lowest rated app) to 4.86 (highest rated app). On average, the best-rated section was functionality (mean 3.44, SD 1.07), followed by aesthetics (mean 3.10, SD 1.23), engagement (mean 3.06, SD 1.32), information (mean 2.95, SD 1.09), and app subjective quality (mean 2.61, SD 1.28).
Table 4

Mobile App Rating Scale scores of the evaluated apps (rating out of 5). The first half (41/88, 47%) of the apps are presented here.

Name of the app (developer)Engagement, scoreFunctionality, scoreAesthetics, scoreInformation, scoreSubjective quality, scoreOverall
Multiple Myeloma Manager (Point of Care)5.005.005.004.574.754.86
Hodgkin Lymphoma Manager (Point of Care)5.005.005.004.434.754.84
Focus On Lymphoma (Lymphoma Research Foundation)4.904.884.834.435.004.81
ALL Manager (Point of Care)5.004.884.674.434.884.77
CLL Manager (Point of Care)5.004.754.674.434.754.72
Transplant Guidelines (National Marrow Donor Program/Be The Match)4.805.004.504.434.504.65
HaemActive—Fitness for people with haemophilia (NovoNordisk A/S)4.904.385.004.574.384.64
Mi Hemofilia (Rogelio Robles Tarano)4.304.634.834.794.634.63
My INR (iMonitorMy)4.604.884.174.644.384.53
My Iron Manager (Good Dog Design Pty Ltd)4.604.504.504.714.134.49
myWAPPS (Design2Code Inc)4.904.884.674.073.884.48
CLL Watch and Wait Tracker (Lymphoma Canada)4.604.004.674.364.754.47
Bleeder (Hannes Jung)4.704.504.504.144.504.47
Microhealth Hemofilia (MicroHealth LLC)5.004.504.174.214.254.43
Iron Tracker—Hemochromatosis (IronTracker)4.404.634.674.434.004.42
STB—Stop The Bleed (Uniformed Services University)4.004.634.334.644.504.42
PA Pernicious Anaemia (B12 Global Limited)4.704.504.504.144.134.39
Hemophilia Pal (Haemophilia Pal)4.504.384.174.434.384.37
ThaliMe (Curatio Networks Inc)4.604.504.673.793.884.29
My HHT Tracker (Cure HHT)4.704.634.503.434.134.28
CML Life (Incyte Corporation)4.404.754.673.713.634.23
INR Care (Nikhil Patel)4.504.384.673.294.134.19
Diario de INR (Web Factor BV)4.604.134.673.933.634.19
NCCN Patient Guides for Cancer (National Comprehensive Cancer Network)3.104.754.674.364.004.17
My Blood Count (Sean Bottomley)4.804.384.503.643.504.16
LLS Health Manager (The Leukemia and Lymphoma Society)4.704.003.834.214.004.15
thalTracker (University Health Network)4.604.504.503.863.254.14
Don’t Walk Alone (Lymphoma Canada)4.903.384.174.213.384.01
The Cancer App (Interactive Pharma Solutions Limited)4.304.254.503.713.133.98
Hemophilia Support (MyHealthTeams)4.603.753.673.144.503.93
CML Today (Leukemia Patient Advocates Foundation)3.704.383.504.293.633.90
Pernicious Anemia Advice (MoreFlow)3.104.504.334.003.503.89
ALL Xplained (MedicineX)3.104.384.003.712.753.59
VTE Calc (Lindum Medical Ltd)3.804.383.173.862.633.56
myPROBE (Design2Code Inc)3.804.254.002.712.133.38
Alimentos para la anemia (Jotathat)2.703.133.503.433.133.18
Folate & B12 Counter and Tracker (First Line Medical Communications)3.104.132.503.362.633.14
Blood Group Genes (Gaurav Mathur)4.203.254.002.212.003.13
Iron Counter and Tracker (First Line Medical Communications)3.104.132.503.362.503.12
All Blood Disease and Treatment A-Z (Patrikat Softech)2.603.883.003.212.503.04
LRF Understanding Lymphoma (Lymphoma Research Foundation)3.103.383.333.362.003.03
Table 5

Mobile App Rating Scale scores of the evaluated apps (rating out of 5). The second half (47/88, 53%) of the apps are presented here.

Name of the app (developer)Engagement, scoreFunctionality, scoreAesthetics, scoreInformation, scoreSubjective quality, scoreOverall
LRFFactSheets (Lymphoma Research Foundation)3.403.383.173.141.882.99
Juntos contra la anemia (Andres Moran Tello)3.003.133.173.072.382.95
EasyCoagLite (Loic Letertre)3.302.883.002.792.502.89
Hemo Control (The Simulation Crew)3.603.003.502.071.882.81
Caprini DVT Risk (NorthShore University HealthSystem)3.703.382.672.571.382.74
Recognize Thrombocytopenia (Media Clinic)2.303.882.002.501.752.49
Thalasemia Early Detection (Iliana)3.003.252.672.211.252.48
Recognize Hemophilia Disease (Media Clinic)2.303.881.672.501.882.44
Sickle Cell Anemia Home remedy (JGWS)1.802.633.002.502.252.44
Recognize Thalassemia Disease (Media Clinic)2.303.881.672.501.752.42
Increase A Low Platelet Count Naturally (FingertipApps)1.803.382.332.432.132.41
Recognize Anemia Disease (Media Clinic)2.303.252.172.501.752.39
Anemia (RouseApps)2.003.382.002.571.882.36
LLS CAR T (The Leukemia and Lymphoma Society)2.403.252.832.071.252.36
Blood Clot Home & Natural Remedies (Salim Garba Usman)2.003.252.672.211.632.35
Anemia Home Remedies (StatesApps)1.803.632.172.291.752.33
Bleeding After Birth (JacoApps)1.903.132.832.141.632.33
The Seven Types of Anemia (MrBeli)2.203.252.002.361.752.31
Sickle Cell Disease (Kabirapp)1.902.382.832.002.252.27
Bleeding Disorder (Koodalappz)2.102.502.832.291.632.27
Blood Diseases (Medico_Guide)1.802.632.272.292.002.18
Childhood Leukemia: A Preventable Disease (FreeCreativity2019)1.802.631.832.212.382.17
Trombocytopenia Disease (Bedieman)1.802.752.002.501.752.16
Food For Anemia (MixLabApps)1.803.132.332.141.382.16
Iron Deficiency Anemia (Bedieman)1.803.002.002.211.752.15
Hemophilia Disease (Bedieman)1.802.752.002.501.632.14
Thalassemia Disease (Bedieman)1.702.752.002.501.632.12
Easy Diagnosis—Thalassemia (Sarah Tinmaswala)1.903.251.672.001.382.04
Home Remedies for Anemia (Anil Krishna)1.802.632.171.931.632.03
SUSOKA (Subrata Saha)2.402.382.171.571.381.98
Leucemia—Sintomas Y Tratamiento—FAQ (Things To Do)1.602.132.002.431.501.93
Anemia Care Diet & Nutrition (RecoveryBull)2.002.132.002.001.501.93
Sickle Cell Anemia (Fumo)1.802.381.831.791.631.88
iClot (Cranworth Medical Ltd)1.902.002.171.931.381.87
Pregnancy & Anaemia (Fumo)1.802.382.001.791.381.87
Anemia (El Makaoui)1.502.752.001.641.251.83
Anemia Home Remedies (Salim Garba Usman)1.802.001.831.861.631.82
CIB—Coagulation Intervention Brigade (LFB Biomedicaments)1.401.252.501.211.251.52
Leukemia Disease (Bedieman)1.501.501.331.711.131.43
Recetas y consejos para combatir la anemia (App Free Enjoy)1.601.501.501.431.001.41
Leukemia: Symptoms And Treatment (The Reyv)1.501.751.171.431.131.39
Myeloma Cancer Guide (Everyone Learning Apps)1.201.751.501.501.001.39
Leukemia Disease Treatment (Woochi Developer)1.401.501.171.431.251.35
Blood Cancer (Digital Planete Space)1.401.711.171.291.001.31
How To Cure Leukemia (Apps How To Apps)1.101.751.171.141.001.23
Blood Cancer tips (Free Apps For Everyone)1.001.631.171.141.001.19
Blood-Count Reader free (Yurii Shevchenko)1.801.131.001.001.001.19
Mobile App Rating Scale scores of the evaluated apps (rating out of 5). The first half (41/88, 47%) of the apps are presented here. Mobile App Rating Scale scores of the evaluated apps (rating out of 5). The second half (47/88, 53%) of the apps are presented here. Comparison by app distribution platform (Apple App Store and Android Play Store) revealed a mean MARS score of 3.85 (SD 0.35) for apps developed for iOS (n=34) and 2.67 (SD 0.30) for apps developed for Android (n=62), resulting in a statistically significant difference (P<.001). Apps whose development had been supported by a health organization obtained better scores (mean 3.75, SD 0.29; n=23) than those that had not (mean 2.78, SD 0.31; n=65; P<.001). Finally, another statistically significant difference (P=.049) was found when the overall MARS scores were analyzed considering whether the apps were free (mean 2.97, SD 0.30; n=82) or required payment (mean 3.92, SD 0.29; n=6; P=.049). The comparison by different characteristics is shown in Table 6.
Table 6

Results of the Mobile App Rating Scale evaluation: comparison by different characteristics.

CategoryOperating systemDeveloperCost
Android (n=62), scoreiOS (n=34), scoreP valueNo health organization (n=65), scoreHealth organization (n=23), scoreP valueFree (n=82), scorePayment (n=6), scoreP value
Engagement2.594.16<.0012.763.88<.0012.984.12.04
Functionality3.094.01<.0013.234.02.0023.384.29.04
Aesthetics2.663.91<.0012.823.90.0023.043.89.10
Information2.643.52<.0012.703.67<.0012.903.70.08
Subjective quality2.263.34<.0012.373.29.0022.543.58.052
Overall2.673.85<.0012.783.75<.0012.973.92.049
The mean κ coefficient score for the five MARS domains was 0.78. κ values between 0.61 and 0.81 indicate that interrater agreement between the 2 reviewers was substantial. The only item with a score less than 0.61 was ease of use (Table 7).
Table 7

Kappa score and interrater reliability for the Mobile App Rating Scale domains.

DomainWeighted Cohen κAgreement, %
Engagement 0.8293.1
Entertainment0.6386.7
Interest0.7290.4
Customization0.9095.2
Interactivity0.8492.6
Target group0.7390.4
Functionality 0.6990.6
Performance0.6788.5
Ease of use0.5487.1
Navigation0.6487.9
Gestural design0.7190.3
Aesthetics 0.8093.1
Layout0.7691.7
Graphics0.7690.7
Visual appeal0.7892.4
Information 0.8093.5
Accuracy of the app in the description (Apple App Store and Android Play Store)0.7793.1
Goals0.7892.8
Quality of information0.7391.0
Quantity of information0.6788.6
Visual information0.6386.4
Evidence base0.9196.3
Credibility0.8494.3
Subjective quality 0.8092.8
Would you recommend this app to people who might benefit from it?0.7891.5
Would you pay for this app?0.8694.2
How many times do you think you would use this app in the next 12 months if it was relevant to you?0.7790.3
What is your overall star rating of the app?0.7992.2
Results of the Mobile App Rating Scale evaluation: comparison by different characteristics. Kappa score and interrater reliability for the Mobile App Rating Scale domains.

Discussion

Principal Findings

This is the first study to provide a systematic search and ranking of apps for patients diagnosed with hematological conditions available in the Apple App Store and Android Play Store, using the MARS as a standardized methodology for the classification, assessment, and validation of these apps. We found that there were more apps available in the Android Play Store than in the Apple App Store, as mentioned in other studies [8,11,24], which can imply that uploading an app into the Android Play Store is an easier process. We observed that almost half of the apps (43/88, 49%) had been updated in the last year, as previously reported [25]. Considering hematology as a medical field that is constantly growing in complexity and extending its therapeutic arsenal, this low rate of app content actualization is insufficient [26]. Of 88 apps, only 23 (26%) were designed with the participation of some kind of health organization. The absence of health care professionals in the development of health apps continues to be raised time and time again. Amor-García et al [11] observed that only 15.2% of apps for patients with genitourinary cancer involved health professionals in their design process. When reviewing apps for medication management, Tabi et al [27] observed a similar result (14.6%). It would seem crucial that health care professionals be involved in the creation of medical apps; however, this scarcely happens. Moreover, the fact that most health-related apps are free favors accessibility [27]. Our results expose the high prevalence of informative apps (60/88, 68%), as reported by other authors [6,11]. The majority of these apps provide generic data about one or several pathologies, including symptoms, diagnostics, and treatment, focusing solely on education. One-third of the total of informative apps is intended for patients with anemia, which highlights the interest in anemia self-management, as it is the most common blood disorder globally [18]. Preventive apps are less numerous (23/88, 26%), although their quality and performance are significantly higher. These apps focus on handling the pathology after diagnosis, allowing for treatment and laboratory values tracking and recording of symptoms and adverse events. We found these types of apps the most appropriate and useful for patients with hematological conditions because many blood conditions require chronic and complex pharmacologic treatment [28,29]. Only 5 diagnostic apps were evaluated. It is worth mentioning STB—Stop The Bleed, an app designed to help anyone learn how to safely and effectively deal with life-threatening bleeding, which has demonstrated the potential of mobile apps in emergency scenarios [30]. The other 4 diagnostic apps are screening tools based on hematological parameters, questionnaires, and gene traits. Its objectives are to predict blood groups or certain hereditary pathologies, such as hemophilia or thalassemia. The main limitation is again the lack of evidence-based content, which in this case could mislead patients into not seeking professional advice. The potential of apps to be implemented as remote diagnostic tools for hematological conditions is very high. This is the case of AnemoCheck Mobile, an app that estimates hemoglobin levels by analyzing the color of fingernail beds and detects anemia, serving as a completely noninvasive anemia screening tool [31]. The MARS has demonstrated its potential as a simple, reliable, and flexible health care app-quality rating scale [21]. It analyzes the quality of an app by evaluating 23 items, grouped into 5 domains, and rating on a 5-point scale. Our study showed a mean score of 3.03, considering a score of 3 as acceptable. This result is similar to the scores showed by other authors using the MARS to evaluate health apps for other conditions. The mean score found by Salazar et al [5] for apps designed for chronic pain management was 3.17, and Kwan et al [6] showed a mean score of 3.48 for apps targeted at patients with spondyloarthritis, out of 18 and 5 apps evaluated, respectively. Knitza et al [24] reviewed 28 rheumatology apps and obtained an overall MARS score of 3.85. The median overall MARS score of the analysis of 34 apps targeted toward supporting heart failure symptom monitoring was 3.4 [32]. In a larger sample study, Amor-García et al [11] evaluated 46 apps for patients with genitourinary cancers and found a mean score of 2.98. It is worth noting that our study encompasses a higher number of apps evaluated than any of the studies cited. Thus, the overall quality of health apps in digital platforms is moderate, and there remains considerable scope for improvement. Of the 88 apps, 41 (47%) hematological apps obtained a score of at least 3 points, meaning that more than half of the apps for hematological conditions do not meet acceptable criteria for quality and content. Moreover, of the 88 apps, only 28 (32%) exceeded 4 points in the overall score. MARS ratings ranged from 1.19 (Blood Count Reader) to 4.86 (Multiple Myeloma Manager), indicating the highly inconsistent quality of apps. The apps with the highest scored were Multiple Myeloma Manager, Hodgkin Lymphoma Manager, Focus On Lymphoma, ALL Manager, and CLL Manager. All of them were exclusive to the Apple App Store, except Focus On Lymphoma, which was available in both platforms. These apps showed high scores in the engagement and functionality domains. The main characteristic that defines these top-rated apps was the active patient participation, offering wide treatment and symptom monitoring options, reminders, and schedules edition. The five apps with the highest score had a plain preventive purpose, whereas informative apps scored lower on the MARS despite being more frequent. The comparison by operating system showed a statistically significant difference favoring iOS apps over Android apps in all 5 MARS domains, a tendency that has been observed in a similar evaluation about genitourinary apps [11]. The reason could be that the Apple App Store has stricter standards to include apps. Although we observed that only 26% (23/88) of the apps involved the participation of health professionals in their design, their quality was significantly higher. The lack of health professional involvement is a constant that has already been highlighted by several authors, expressing their concern about app content and compromising patient safety [33-35]. However, 4 of the best apps (Multiple Myeloma Manager, Hodgkin Lymphoma Manager, ALL Manager, and CLL Manager) were developed by @Point of Care, a platform consisting of nonmedical stakeholders and dedicated to creating medical apps for patients and clinicians. @Point of Care has designed apps focused on diverse pathologies, some of them obtaining considerably high MARS scores in other studies similar to ours [11]. The analysis by cost revealed another statistically significant difference, positioning payment apps ahead of free apps in terms of quality, although the fact that only 6 hematological apps were not free and all of them were developed for iOS can destabilize the comparison. Functionality was the domain that scored the highest on the MARS test, as described by other authors [11,36]. This implies that the apps are easy to navigate and efficient. Leaving subjective quality aside, engagement and information were the domains with the lowest MARS scores. Engagement reflects the capacity of the app to be personalized by the user. Patients usually search for a health app that allows for medication management, clinical and analytical parameter register, and symptom tracking [28,37]. Patients with hematological conditions would benefit significantly from this type of assistance, as several blood conditions demand constant patient monitoring and high adherence to treatment for a better health outcome [18,30]. My INR, INR Care, and Diario de INR are apps that allow anticoagulated patients to record and track their international normalized ratio readings and antivitamin K dosages. They could help improve adherence and avoid potential complications, such as the risk of bleeding or clots. HaemActive is a fitness app especially tailored to patients with hemophilia, who require special exercises that imply a minimal risk of bleeding. The app includes weekly training planning, explainer videos, and easy customization. In addition, patients expressed their interest in using health apps to communicate with their physicians [28,38]. Concerning the information domain, there is 1 specific item assessing the evidence base, which explores the extent to which the app has been scientifically tested. However, this item was excluded from all calculations, as no clinical studies to support the effectiveness and safety of any of the apps could be found. Thus, empirical studies should be conducted for apps to determine their clinical impact on outcomes for patients diagnosed with hematological conditions [13].

Recommendations for Health App Development

The number of health apps available and studies reviewing their quality is steadily growing, which will help health professionals to recommend apps to patients. This activity acquires even further relevance, considering the still little control from regulatory authorities over health app development. We have observed that the main issues that need to be addressed when designing health apps are as follows: no participation of health organizations in app development, questionable sources of information, and deficient interactivity and personalization options [35]. Production of medical apps from nonmedical stakeholders has benefits in terms of creativity in the design of apps. However, it must be combined with clinician assistance to boost the credibility of medical information with such apps. Concerning patients with hematological conditions, registering analytical information, treatment prescribed, and symptoms is highly recommendable for apps to help them in their care.

Limitations

First, only apps available in the Android Play Store and Apple App Store, with contents in English or Spanish and accessed from a Spanish IP address were included, assuming the possibility of having missed some other apps dedicated to hematological conditions. Another limitation could be that app quality was assessed using the MARS, which is limited by the subjectivity of the evaluators. Nevertheless, this issue is partially addressed by the high interrater reliability of the data analyzed by the 2 independent researchers. We believe that this evaluation should allow health care professionals and patients to identify which apps meet minimum standards of quality and safety in their content.

Conclusions

We provide the first systematic review of apps related to hematological conditions, identifying 88 apps and rating them using the MARS. The study shows great heterogeneity among their quality. Many of these apps emerge as tools for consulting information, being the most frequent functionality, although not the highest rated. A very small number of them offer a comprehensive self-management approach incorporating evidence-based strategies. Only 26% (23/88) of the apps were developed with the assistance of health care professionals. The top 5 rated apps—Multiple Myeloma Manager, Hodgkin Lymphoma Manager, Focus On Lymphoma, ALL Manager, and CLL Manager—allowed for active patient participation and app personalization. Higher scores in quality were observed in iOS apps, apps developed by health organizations, and payment apps.
  34 in total

Review 1.  Telemedicine and telerehabilitation: current and forthcoming applications in haemophilia.

Authors:  Elena A Boccalandro; Giuseppe Dallari; Pier Mannuccio Mannucci
Journal:  Blood Transfus       Date:  2019-02-04       Impact factor: 3.443

Review 2.  Mobile Health Apps That Help With COVID-19 Management: Scoping Review.

Authors:  Hanson John Leon Singh; Danielle Couch; Kevin Yap
Journal:  JMIR Nurs       Date:  2020-08-06

3.  Preferred reporting items for systematic review and meta-analysis protocols (PRISMA-P) 2015 statement.

Authors:  David Moher; Larissa Shamseer; Mike Clarke; Davina Ghersi; Alessandro Liberati; Mark Petticrew; Paul Shekelle; Lesley A Stewart
Journal:  Syst Rev       Date:  2015-01-01

4.  Features and Functionalities of Smartphone Apps Related to COVID-19: Systematic Search in App Stores and Content Analysis.

Authors:  Roberto Collado-Borrell; Vicente Escudero-Vilaplana; Cristina Villanueva-Bueno; Ana Herranz-Alonso; Maria Sanjurjo-Saez
Journal:  J Med Internet Res       Date:  2020-08-25       Impact factor: 5.428

5.  German Mobile Apps in Rheumatology: Review and Analysis Using the Mobile Application Rating Scale (MARS).

Authors:  Johannes Knitza; Koray Tascilar; Eva-Maria Messner; Marco Meyer; Diana Vossen; Almut Pulla; Philipp Bosch; Julia Kittler; Arnd Kleyer; Philipp Sewerin; Johanna Mucke; Isabell Haase; David Simon; Martin Krusche
Journal:  JMIR Mhealth Uhealth       Date:  2019-08-05       Impact factor: 4.773

6.  Evaluation of Mobile Apps Targeted at Patients With Spondyloarthritis for Disease Monitoring: Systematic App Search.

Authors:  Yu Heng Kwan; Wei Jie Ong; Mengfei Xiong; Ying Ying Leung; Jie Kie Phang; Charmaine Tze May Wang; Warren Fong
Journal:  JMIR Mhealth Uhealth       Date:  2019-10-28       Impact factor: 4.773

Review 7.  Mobile Health Apps for Medical Emergencies: Systematic Review.

Authors:  Alejandro Plaza Roncero; Gonçalo Marques; Beatriz Sainz-De-Abajo; Francisco Martín-Rodríguez; Carlos Del Pozo Vegas; Begonya Garcia-Zapirain; Isabel de la Torre-Díez
Journal:  JMIR Mhealth Uhealth       Date:  2020-12-11       Impact factor: 4.773

8.  Scaling up mHealth: where is the evidence?

Authors:  Mark Tomlinson; Mary Jane Rotheram-Borus; Leslie Swartz; Alexander C Tsai
Journal:  PLoS Med       Date:  2013-02-12       Impact factor: 11.069

9.  Interrater reliability: the kappa statistic.

Authors:  Mary L McHugh
Journal:  Biochem Med (Zagreb)       Date:  2012       Impact factor: 2.313

10.  Measuring the Quality of Mobile Apps for the Management of Pain: Systematic Search and Evaluation Using the Mobile App Rating Scale.

Authors:  Alejandro Salazar; Helena de Sola; Inmaculada Failde; Jose Antonio Moral-Munoz
Journal:  JMIR Mhealth Uhealth       Date:  2018-10-25       Impact factor: 4.773

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  1 in total

1.  Apps for Covid-19 in Germany: assessment using the German Mobile App Rating Scale.

Authors:  Felix Holl; Fabian Flemisch; Walter Swoboda; Johannes Schobel
Journal:  JAMIA Open       Date:  2022-09-26
  1 in total

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