Navigating mental health apps
Mobile phones are ubiquitous in society and owned by a majority of psychiatric patients, including those with severe mental illness. Their versatility as a platform can extend mental health services in the areas of communication, self-monitoring, self-management, diagnosis, and treatment. However, the efficacy and reliability of publicly available applications (apps) have yet to be demonstrated. Numerous articles have noted the need for rigorous evaluation of the efficacy and clinical utility of smartphone apps, which are largely unregulated. Professional clinical organizations do not provide guidelines for evaluating mobile apps. Stand-alone apps designed for psychological interventions can be used independently of a mental health care professional. In contrast, there are treatment apps designed to be used in conjunction with and under the guidance of a health care professional (e.g., DBTCoach). Recently, apps related to mental health are increasingly avail- able and provide methods of tracking a variety of behaviors, thoughts, and symptoms. These apps are generally related to one of the following broad categories: self-reports of mood states, symptom tracking, therapy, diagnosis, coaching, and/or assessment. Peer support apps are also available, such as instapeer, which connects individuals diagnosed with cancer with other survivors or current patients.
Few apps have empirical research to support their use as standalone treatments, and so a trend in the field has been for the development of apps to serve as adjuncts to in-person therapy.
Chan, Torous, Hinton, and Yellowlees (2015) developed this framework for users and mental health service providers to evaluate mental health mobile apps:
First, patients and providers can use the following three dimensions of evaluation criteria for mental health mobile apps:
1. Usefulness dimension
• Validity and accuracy: Does the app work as advertised?
• Reliability: Will the app consistently function from session to session?
• Effectiveness: Is the app clinically effective—with demonstrated improved outcomes—for the target population, disease, or disability?
• Time and number of sessions: What time is required for the user to derive some benefit from the app?
2. Usability dimension
• Satisfaction and reward: Is the app pleasurable and enjoyable to use, or does it discourage repeat use?
• Usability: Can the user easily—or with minimal training—use and understand the app?
• Disability accessibility: Is the app usable by those with disabilities (e.g., incorporates screen readers for blind users, closed captions for the hard-of-hearing and deaf communities)?
• Cultural accessibility: Does the app work effectively with the user’s culture (as defined by factors such as ethnicity and language)?24
• Socioeconomic and generational accessibility: Does the app take into account socioeconomic status and the user’s age, with potential implications for the user’s digital health literacy?
3. Integration and infrastructure dimension
• Security: Are the app’s data encrypted on the device and/or in transmission? Are they anonymized, or do they contain personal health information? If so, what do they do?
• Workflow integration: Does the app work within its user’s workflow?
• Data integration: Does the app share data with other apps, networks, and medical record systems?
• Safety: Does the app take into account patient safety, such as suicidality or homicidality?
Second, mobile apps can be categorized to target one or more of the following stages in a provider’s workflow:
Education and training: Can the app be used to educate or train clinicians, patients, families, and/or support staff?
Reference: Can the app provide information (e.g., pharmacotherapies, local social services) for either clinician education or point of care?
History data input and output: Can the app gather history (e.g., from the patient, from the patient’s teachers, from the patient’s caregivers) and provide useful, comprehensible output?
Physical data input and output: Can the app include physical health data (e.g., sleep hours, blood pressure, heart rate, number of steps walked)?
Diagnosis: Does the app provide a differential diagnosis? How much confidence does it have in such a diagnosis?
Treatment and intervention: Does the app provide treatment and/or interventions? Is it for acute use (e.g., mood tracking for acute severe depression) or chronic use (e.g., long-term cognitive training for schizophrenia)?
Patient–provider communication: How will an app improve or worsen communication between patients and providers? Apps, for instance, could prompt patients to talk about sensitive issues.
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