The “ABILITY” category groups those features that aim to improve or facilitate patients' capabilities to perform active behaviors (to manage the disease or improve their health status). Such features typically support patients in executing disease related actions such as performing physical therapy, taking medical measurements or support medication intake.
Reduction features aim to minimizes the effort needed to complete the desired health behavior or disease management action. It transforms a complex action into a simpler one, e.g. by performing complex calculations or automating part of the action for the patient.
Can the mHealth app remember or calculate disease parameters, in order to reduce the cognitive effort needed from the patient?
Can the mHealth app store medication regimens or elaborate exercise procedures?
Note: A mHealth app that automatically logs patients' data is considered Tracking.
Tunneling features aim to help the patient perform a series of actions necessary for the health behavior or disease management. Tunneling is typically used to guide the patient towards a bigger of more distant goal, by providing the different steps over time, in order to achieve the desired health status.
Can a wizard be used to guide the patient through a lengthy process?
Can complex tasks be split up into a series of smaller, easier tasks that can be executed sequentially?
Note: Simply providing information on the different steps is considered Instruction (e.g. an illustrated manual).
Note: When the patient can set a personal goal, this is considered Goal Setting. However, Tunneling and Goal Setting often go hand in hand.
Instruction features aim to help the patient to better understand ‘how’ to perform a disease management action, or how to use the mHealth application to achieve the target health behavior.
Does the mHealth app provide a help function to explain how to execute specific disease management actions?
Can tips be given so that the patient understands ‘how’ to correctly perform a certain action?
Can the mHealth app offer a section with frequently asked questions?
Note: Providing information why it is important to perform a health behavior is considered General Information .
Rehearsal features provide a safe zone for patients to try out health behaviors or performing disease related tasks, before executing them ‘for real’. Rehearsal of a target behavior allows the patient to feel more confident when performing the target behavior.
Does the mHealth app allow the patient to rehearse a certain action before being executed or communicated to a health professional?
Can a patient first tryout how to perform a certain operation such as giving an injection a number of times?
Can a patient exercise a certain cognitive task to understand how it works?
Note: For Rehearsal, the app needs to be able to measure or track the patient's actions.
Reminders help the patient remember to perform the target health behavior or disease management action in a specific situation. Reminders can be time-based but they can also rely on other contextual information (e.g. weather, location, certain actions...). In this manner, reminders can also be understood as triggers.
Can the patient set an alarm at a time or an interval of his or her choosing?
Are notifications being sent to the patient or the care circle on when to perform an action when being at the appropriate location?
Can a message to perform the intended behavior be sent out in a specific context (weather, location…)?
Note: With today's technology, not only reminders in time are possible but also reminders based on other or a combination of multiple aspects, i.e. location, weather, amount of physical activity...
The “INFORMATION” category groups those features that provide disease related information, either at the general level (for everyone), tailored (subgroups) or personalized (for one individual), and may even provide bespoke information about the future.
General Information features provide information about the disease or the target health behavior increases the understanding of the disease or health behavior, and ‘why’ it is important to perform certain behaviors or disease management actions.
Can the mHealth app provide an information-section on the disease or health behavior, listing e.g. severity, prevalence, cause, life expectancies, medication, etc.
Can the mHealth app shed light through on the importance of the target health behavior or possible disease management actions, e.g. how it helps reducing side effects or prolong quality of living?
Macro tailored information features provide information adapted to suit a specific patient group. Macro tailoring targets groups of patients, characterized by a specific disease parameter, gender, age group...
Can the patient indicate to what subtype he or she belongs to?
Can the app filter out relevant information, based on the subtype of disease the patient belongs to?
Note: In case information is organized by subtypes but a patient does not need to indicate to what group he or she belongs, and consequently there is no change in the information provided by the mHealth app depending on the group the patient belongs to, this is NOT considered as Macro Tailoring, but rather General Information.
Micro tailored information features provides information on the disease or health behavior adapted to suit a specific patient. Micro tailoring targets individual patients and provide idiosyncratic information for each specific patient.
Can algorithms (e.g. recommender techniques) be used to adapt the information incorporated in the application on the basis of specific characteristics and traits of the patient? This not only relates to disease parameters, but equally to age, gender, socio-economic status, geographic location, language, usage history…
Note: In case a patient can first select a personal goal to tailor disease management actions or strategies, this should be flagged as Goal Setting, not Micro Tailoring.
Note: In case a patient can enter personal information, but this is only used to address that person superficially (e.g. to welcome with the first name, but not to tailor actual information) then this should be flagged as Personalization.
Simulation features provide bespoke information about the future, and how disease may evolve over time, or what health effects may be related to certain behaviors.. These features help simulate effects over time, based on data provided by and/or actions performed by the patient.
Can the application forecast future disease status based on current disease management actions and/or data (e.g. future weight loss based on current calorie intake)?
The “AWARENESS & PERSONAL INSIGHTS” category groups those features that aim to provide users with more awareness of and insight into their disease status, or the disease management actions performed in relation to the target behavior.
Logging features provides the possibility to manually or verbally enter information related to the disease status into the mHealth app, to be retrieved later and possibly to be shared with others.
Does the app provide a diary or notebook where patients can log relevant information?
Does the application allow a patient to manually enter data related to the target health behavior?
Can patients add information on disease status via the microphone or keyboard of the mHealth app?
Note: The difference between Logging and Tracking lies in that for Tracking this happens without the patient's effort, whereas for Logging, conscious and intentional effort from the patient is demanded.
Note: Logging goes hand in hand with Self-Monitoring. However, this is not always the case, it is possible that logged data is sent to a database for health researchers, without giving access to patients themselves.
Tracking features allow for the automated capturing of data, by sensors in the smartphone, or via wearables or contextual sensors linked to the mHealth app. In this way, physical and physiological data is captured by the app, to further disease insight and support actions.
Can disease management actions be recorded via sensors in the mHealth app?
Can the application automatically link to and collect data via wearables, regarding the target health behavior?
Note: The difference between Logging and Tracking is that Tracking happens without the patient's effort, whereas for Logging, conscious and intentional effort from the patient is demanded.
Note: Tracking is different from Reduction in that Reduction reduces a complex task to a simpler task, e.g. by performing complex computations, conducting automated searches or storing lengthy procedures, but not by automated collection of data.
Note: Tracking goes hand in hand with self-Monitoring. However, this is not always the case, it is possible that Tracking data is sent to a database for health researchers without giving access to patients themselves.
Self-Monitoring features allow patients to follow-up on their disease status, disease management actions, or health behavior data through visualizations. Hence, Self-Monitoring implies displaying the data of the patient (captured either through logging or tracking), over a certain time period.
Does the mHealth app visualize disease status parameters and/or health actions in a meaningful manner?
Can patients scroll, filter, zoom in and out on data, based on time, location, data type…?
Can the patient’s health related data be visualized in such a way that it allows to track progress over time?
Note: The representation of data for Self-Monitoring can both be graphical (graphs, drawings, images) as well was text-based.
Note: Self-Monitoring goes hand in hand with Tracking and Logging.
Goal Setting features allow a patient is able to set a personal goal for his/her health behavior or disease status, and track the progress towards that goal.
Is the patient able to choose a goal and possibly a timeframe to achieve this goal?
Can the patient specify how, what and when to reach a specific goal related to disease status or health behaviors?
Note: In case the app coaches the patient through a process but does not allow to set an individual goal, this should be flagged as Tunneling, not Goal Setting
Suggesting applies when the mHealth app suggests different possible actions related to the target behavior, rather than only one. With suggestion, the mHealth app ‘suggests’ rather than obliges a certain action?
Can the mHealth app provide different types of actions to achieve a certain target behavior (e.g. climb two stairs or do 30 jumping jacks)?
Can the mHealth app rephrase certain actions as choices rather than obligations?
The “INCENTIVIZATION” category groups those features that provide (external) incentives for patients to execute or adhere to certain health related behaviors. Often these features are also labeled as gamification.
Rewards features incentivize a patient to perform the target health behavior or disease management action. Upon performing the desired behavior, the patient is virtually rewards via badges, experience points…
Does the mHealth app present virtual rewards such as stars, badges, experience points... to the patient when the intended behavior is executed?
Can the mHealth app provide a voucher or coupon to the patient to motivate the patient?
Note: Rewards can be as simple as accumulating points through the use of an app.
Note: Rewards can also be physical rewards.
Praise features aspire to make the patient feel appreciated and competent by giving messages that encourage and laude the efforts of the patient.
Can the mHealth app offer encouraging messages to the patient, during or after his or her actions?
Note: When the Praise is given in such a manner that this is also visible for others, than this should be flagged as Recognition (e.g. an app that posts on Facebook that a user has attained a certain goal).
Recognition publicly offers praise for a patient’s health-related actions, by posting encouraging and lauding messages at fora where others can see this.
Can the mHealth app post messages of attained health targets at social network sites?
Does the application feature a section that shows e.g. ‘the patient of the month’ or a patient who has performed extraordinary well?
Note: Recognition does not need to imply that one patient is outperforming others.
The “TRUSTWORTHINESS & LIKING” category groups features related to how the application can increase its credibility and liking by the patient.
Personalization features allow the patient to personalize the designs and styling of the mHealth app, for example when he/she is able to choose the layout of the mHealth app, change colors, change the skin or set a welcome message.
Can the patient customize what is and what is shown on the dashboard of the mHealth app?
Is the patient able to change the colorscheme of the mHealth app?
Can the patient provide and be addressed with a nick name?
Note: Micro/Macro Tailoring, implies that the mHealth app personalizes/adapts the content itself, not merely the styling.
Verifiability features allow a patient to be able to verify the (scientific) quality of the mHealth app, and look up what are the origins of the content, the contributors to and creators of the app.
Is the patient presented with information that shows the validity of the content of the application (e.g. a link to a scientific research article, a testimonial...)?
Can the patient inspect who created the application?
Note: This is closely related to Expertise, where trust in the application is installed via other people (health experts, expert users, celebrities) advocating the app.
Expertise related features ensure that patients understand that the content is devised by people or used by people who have expertise, e.g. health professionals, celebrities or other patients. The focus is on highlighting people or organizations using or advocating the mHealth app.
Does the mHealth app display people or organization(s) who promote the application?
Does the mHealth app provide testimonies of people using the app?
Does the mHealth app show quotes of famous doctors who liked the app?
Does the mHealth app show ratings and reviews of how others evaluated the app?
Note: This is closely related to Verifiability, which focuses on providing insight in the (scientific) quality of the app, the content and creators.
Surface Credibility features provide a way for the patient to judge the quality of the application at first glance, in order to install trust and credibility.
Can the mHealth app avoid showing advertisements, banners, pop-ups?
Is the visual design of the application sleek and consistent with design guidelines?