Evidence-Based Reviews

Mental health apps: What to tell patients

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An evaluation model created specifically for such apps can help guide your discussions.

AUDIO: Dr. Torous describes key points to cover when discussing apps with patients.



Have your patients asked you about smartphone apps? If they haven’t yet, they may soon, as interest in apps for mental health continues to expand. There are now >10,000 mental health–related smartphone apps.1 The rapid rise of these apps is partly due to their potential to transform a patient’s smartphone into a monitoring and therapeutic platform, capable of capturing mental health symptoms in real time and delivering on-the-go therapy. Setting aside questions about the potential of mobile health, 2 urgent questions remain for the busy psychiatrist in clinical practice: What is the current evidence base for mental health apps, and what should you tell your patients about them?

For most apps, evidence of efficacy is limited

While the evidence base for mental health smartphone apps continues to expand, for many of these apps, there is no evidence of effectiveness. The growing consensus is that most commercially available apps are not evidence-based and some are even dangerous. For example, researchers who examined >700 mindfulness apps on the iTunes and Google Play stores found that only 4% provided acceptable mindfulness training and education.2 Another study of 58 apps that claimed to offer sobriety assessments found that none had ever been formally evaluated.3 Evidence-based reviews of suicide prevention apps have identified potentially harmful apps,4 and studies evaluating apps for bipolar disorder5 and depression6 have yielded similar results—few have any evidence supporting their use, and some offer dangerous and harmful advice. For example, researchers found that one app for bipolar disorder advised patients who are experiencing a manic episode to drink alcohol.5 Currently, the vast majority of commercially available apps are not appropriate for clinical care. This finding is not unique to mental health; similar findings have been reported for apps for cancer.7 The bottom line is that the apps that your patients are finding, and perhaps already using, may not be useful or effective.

However, early studies have demonstrated efficacy of some apps for several conditions, including schizophrenia,8 depression,9 anxiety disorders,10 and suicidal ideation.11 Although many of the apps evaluated in these studies are not available to the public, or still require large-scale assessment before they are ready for mainstream clinical care, this research demonstrates that mental health apps can help improve treatment outcomes. As this research develops, a wave of evidence-based and effective mental health apps may be available in the near future.

Although it is unknown how many patients are presently using mental health apps, there is strong anecdotal evidence that an increasing number of patients who use these apps and other forms of digital technology are finding some benefits. In many cases, patients may actually be ahead of the research. For example, one study that conducted an online survey of patients with schizophrenia noted that some patients are using their smartphones to play music to help block auditory hallucinations.12

Why online reviews are of limited use

As this evidence continues to mature, and with an ever-growing number of mental health apps available on commercial marketplaces, busy psychiatrists need to navigate this complex space. Even psychiatrists who decide to not use apps as part of care still need to be knowledgeable about them, because patients are likely to ask about the benefits of using apps, and they will expect an informed response. How would you reply if your patient asked you about a new mood-tracking app he or she recently heard about? On what would you base your recommendation and opinion?

Reading online app reviews for guidance is not a good solution. A recent study found little relationship between the star ratings of health apps and the quality of those apps,13 which suggests that a 5-star rating on the app store is of limited use.

Unlike medications whose ingredients do not change over time, or manualized psychotherapies that use specific protocols, mental health apps are dynamic and constantly changing.14 Think of how often the apps on your smartphone update. Thus, the version of a mental health app that your patient downloads today may be very different from the version that received a favorable user review last month. And just as there is no single medication or therapy that is ideal for every patient, neither is there a single “best” app for all patients with the same disorder. Picking an app is a personal decision that cannot be made based on a single score or numeric rating. Furthermore, the validity of app rating systems is unclear. One study found a wide variation in the interrater reliability of measures used to evaluate apps from sources that included PsyberGuide, the Anxiety and Depression Association of America, and the research literature. Quality measures such as effectiveness, ease of use, and performance had relatively poor interrater reliability.15 This means that, for example, an app that one patient finds “easy to use” may be difficult to use for another. Thus, providing patients with suggestions based on an app’s ratings may result in providing information that sounds useful, but often is misleading.

A model for evaluating apps

One possible solution is a risk-based and personalized assessment approach to evaluating mental health apps. Although it does not offer scoring or recommendations of specific apps, the American Psychiatric Association (APA) App Evaluation Model (Figure) provides a framework to guide discussion and informed decision-making about apps. (The authors of this article helped create this model, but receive no compensation for that volunteer work.) The pyramid shape reflects the hierarchical nature of the model. To begin the process, start at the base of the pyramid and work upward.

The American Psychiatric Association App Evaluation Model image

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