A comprehensive review of how technology is evolving the way we can modify behaviors and improve behaviorally-relevant treatments was recently published by Nicole Nugent and colleagues in the journal Behavior Modification.
Here, we summarize key points from this article, which articulates both the importance of ongoing, repeated behavioral assessments as a way to understand the impact of a given intervention, as well as the limitations of traditional approaches that may be overcome through the use of technology.
Conventional Strategies for Measuring and Monitoring Emotion, Cognition, and Behavior
To understand both a client’s experience and the effect of interventions on that experience, therapists need data beyond what they can collect in therapy sessions. Before technology offered the kind of connectedness that is now possible, therapists relied heavily on patients or their caregivers to help in the collection of such data. A major limitation of this approach is that it is often difficult for people to remember to log the information they are supposed to at the times they are supposed to, making the data subject to mistaken recall. In addition, given our internal biases and the unconscious influences on our behavior, self-reporting is often inherently inaccurate or incomplete.
There have been several attempts to overcome these weaknesses associated with the traditional approach to behavioral assessment. For instance, therapists have conducted in-home sessions. However, the drawback of this in-home strategy is that people often do not behave as they normally would when they know they are being observed. The data collected through this method may therefore also contain inaccuracies.
Technology-Based Approaches to Behavioral Assessment
Ecological momentary assessment (EMA) incorporates computing devices into the monitoring process to facilitate data collection in real-time. This approach not only helps to prevent retrospective logging of relevant information, but it also makes it easier to evaluate the influence of certain environmental or contextual information on the person being monitored. Additionally, the information gathered through EMA can be combined with data from standard pen-and-paper approaches to develop a more dynamic understanding of the client and the effect of situational factors on them.
- Active Ecological Assessment: When EMA is active, subjects participate in the collection of data by engaging with their devices. Whether the specific EMA protocol calls for subjects to report information at random or in response to a specific event, active EMA relies on subjects interacting with technology in real-time.
Benefits of this approach include the potential for a care team to gain valuable information on when and how to intervene from a treatment perspective, and the ability to implement strategically designed protocols that provide the precise data that the care team can act upon.
One drawback of active EMA is that it depends on the development of or choice of EMA protocol to best evaluate the issue at hand, which are not trivial tasks. It also requires that the subject willingly engage in the data collection process.
- Passive Ecological Assessment: With advances in technology, it has become relatively easy to collect data passively, rather than to require active input from subjects. Termed digital phenotyping, this passive type of data collection through smart devices enables huge volumes of data that are more objective than client-reported data. The number and type of relevant technologies that can support this type of data collection continues to grow and has allowed for the capture of information related to things ranging from heart rate to geographical location.
Other advantages of passive EMA are that it is noninvasive and can provide information that even well-designed EMA protocols may not catch. This approach has already been shown to be well-received by clients who are voluntarily allowing for this type of low-burden data collection.
Technologies for Client Monitoring
One way that technology can support therapists’ monitoring is by providing information on speech. In addition to the content, other aspects of speech such as rate and quantity of speech, can be indicative of distinct emotional states or changes in states. Mobile speech analysis has begun to be used as a noninvasive way to monitor the progression of Parkinson’s disease and may also provide value by allowing clinicians to gauge how effective certain medical interventions are.
The technologies that can provide a way for therapists to monitor clients and capture critical data are not limited to wearables and smart phones. Social media, for instance, offers a relatively new way for therapists to increase their awareness of their clients’ experiences and gain a window into some of their psychology.
While more research is needed to understand exactly how social media activity can serve to explain aspects of the user, studies thus far have pointed to the potential for social media activity to help to characterize the risk of certain mental health issues, such as suicidal ideation. Regardless of what may be measurable or quantifiable through social media activity, social therapists can gather new information on their clients by observing their social media activity and incorporate this information into their assessments.
Applications of Technology for Intervention
Technology has afforded profound progress in the area of behavioral assessment and has influenced treatment by providing previously inaccessible information about clients and their conditions. However, it is now beginning to impact treatment in other ways. Rather than serve simply as a data collection tool, technology is also beginning to offer the opportunity for timely intervention.
Because data from passive EMA techniques can be continuously collected and analyzed, it also provides a unique opportunity to intervene to affect behavior in real-time. For instance, passive EMA data can be incorporated into apps that nudge people to increase their activity levels or provide them with aptly timed guidance on deep breathing or relaxation.
EMA that is accompanied by the delivery of a treatment is referred to as ecological momentary intervention (EMI). Though relatively new, research is showing that EMIs may serve as an effective self-help tool for specific patient demographics, such as for those with anxiety and depression. This notion has led to the development of downloadable apps and tools to support these efforts, though the efficacy of most of these tools has not yet been adequately tested.
While the ecological sampling that technology allows has provided a way to overcome significant limitations of conventional behavior assessments and to offer potentially more appropriate interventions in a timelier manner, there are still challenges for clinicians. For instance, with the onslaught of new data, clinicians now need better tools to enable them to analyze the data efficiently. Machine-learning strategies may eventually help clinicians translate these high volumes of data into actionable information that can improve treatment.
The unprecedented level of data poses certain risks to patients as well, such as the potential loss of privacy. However, at the same time, the interventions that may now be implemented due to the combination of technology-driven data and clinical expertise may reduce barriers to treatment, offering cost-effective solutions and enhancing access to health care. Nonetheless, in the age of big data, some of the weaknesses of conventional strategies for monitoring behavior may creep back in. For instance, clients who feel surveilled while monitored through technology may behave less authentically than they would in normal life, just as could occur in the company of a therapist.
There are still some hurdles before technology-based monitoring of emotion, cognition, and behavior is truly optimized, but technology has already significantly expanded therapists’ ability to understand their clients and provide improved care. It will never replace clinical expertise, but it can provide critical tools that skilled clinicians can deploy to help them evaluate and treat their patients.
Nugent, N.R. et al. (2019). Innovations in technology and mechanisms of change in behavioral interventions. Behavior Modification, 1-28.