The authors have declared that no competing interests exist.
Current psychological treatment approaches that rely on time-intensive, face-to-face psychotherapy are not capable of meeting the demand for mental health services. Mental health interventions that promote self-regulation and self-management of symptoms will play an increasingly important role in the well-being of millions of individuals. Self-monitoring is a core assessment and intervention component of many mental health interventions and an obligatory first step in the self-regulation process. The present paper reviews prominent theories of self-regulation and describes classic studies spanning clinical, social, cognitive, and personality psychology, which identify potential mechanisms underlying self-monitoring. At the empirical level, we describe the use of self-monitoring across a range of behavioral interventions directed at mental health and physical outcomes, identify factors that influence the effects of self-monitoring, and suggest ways in which technology can be incorporated into these interventions to improve the reach of psychological interventions.
The vast majority of individuals with mental health needs who would benefit from efficacious psychological treatments do not receive them.
The focus of this theoretical and empirical review is the potential utility of self-monitoring for behavior change within the context of mental health interventions. An apocryphal quote often attributed to the mathematician and statistician Karl Pearson, “That which is measured improves,” captures the seemingly self-evident and logical conclusion that systematic self-monitoring (the process of measurement) facilitates behavior change. The evidence for this conclusion will be discussed, first, in light of theoretical models of self-regulation, and then in the context of empirical findings, including recent literature on self-management techniques for mental health utilizing technology.
The review to follow will begin with a brief historical narrative of self-regulation theories. The purpose of the theoretical review is to provide a foundation for identifying potential mechanisms by which self-monitoring operates as a stand-alone intervention. It has been argued that, in an era of rapidly expanding technology, innovation development must be guided by theory.
Following an overview of self-regulation theories, this review will discuss the origins of self-monitoring in the psychotherapy literature, with a focus on well-established psychotherapeutic interventions that prominently utilize self-monitoring as an intervention component. Observation of one’s own behavior is considered crucial to most formalized psychotherapeutic interventions, including but not limited to self-management skills training, motivational enhancement, and behavioral activation.
Finally, the present review will highlight recent empirical literature concerning the use of self-monitoring in formalized, technology-based (Internet- or smartphone-based) mental health interventions. Key features that affect the utility of self-monitoring will be highlighted, drawing on all areas of the broader health literature that are relevant to behavior change. The purpose of expanding the review to the broader health literature is to capture important information about moderators of treatment effect, as the mental health literature is nascent and therefore may benefit from principles derived from other areas of study.
Before proceeding, it should be noted that there exists a vast literature on the self-regulation of physical health behaviors, particularly with the use of technology in managing diabetes,
Self-regulation models
Theoretical models point to three chief mechanisms that may underlie the utility of self-monitoring in behavior change: a desire to change one’s behavior that prompts movement or action towards one’s goals (what could broadly be termed motivation); a behavioral goal, ideal or standard; and a means of measuring performance, often self-monitoring. In the following section, three theories will be discussed as prototypical examples of the behavioral, information-processing, and social-cognitive perspectives of self-regulation, with a focus on the indispensable role of self-monitoring within these models.
A seminal early contribution is found in Kanfer and Karoly’s behavioral model of “self-control”
The behavioral model posits that the primary mechanism of self-monitoring is to develop awareness of the controlling stimuli (environmental and psychological) and one’s own responses. This is a necessary first step before an individual can choose to initiate a different behavior. Per Kanfer, "self-monitoring…serves as a precondition for the execution of new adaptive behaviors" (p. 150)
A highly influential model advanced by Carver
In the information processing model, self-regulation functions as a hypothesized test-operate-test-exit (TOTE) unit. “Test” refers to the processes of self-monitoring, evaluation, and comparison to a goal. “Operate” corresponds to adjusting or changing one’s actions as indicated by the test results. After behavioral adjustments have been made, testing occurs again to determine the success of one’s efforts. If the new input matches the standard, the system is deactivated (“exit”) until another discrepancy between goal and input is discovered.
Ultimately, self-monitoring in a negative feedback loop informs the persistence or adjustment of behaviors to match one’s goals.
Bandura’s social cognitive model
Per Bandura, “people cannot influence their own motivation and actions very well if they do not pay adequate attention to their own performances” (p. 250).
In daily life, others rarely provide systematic, explicit feedback about our own behavior. Therefore, self-observation and self-monitoring are two of the de facto methods by which we regulate our own behaviors.
There are a few differences among the three self-regulation models presented here. Kanfer and Karoly’s model
Ultimately, some common threads also emerge among the three major theories of self-regulation discussed here. First, a goal or behavioral standard must exist to guide behavior. Second, and most relevant to this review, self-monitoring is a necessary first step for any self-regulation or behavior change because of the feedback it provides to the individual about his or her current performance.
Most psychotherapies aim to help the individual shift from more reactive to more purposeful behavior. Self-monitoring aligns well with this goal because it asks clients to attend to the antecedents and consequences of behaviors. Self-monitoring has been described as "a temporary disengagement from automaticity, or a transition from 'mindlessness' to 'mindfulness'“
Self-monitoring is used across many psychotherapeutic interventions for a multitude of purposes, from data gathering and reporting, to increasing self-awareness, to functioning as an active intervention that changes future thoughts and behaviors. In the following section, a brief overview will be provided of how self-monitoring has been used historically in psychotherapeutic interventions. The goal is to provide a foundation for the subsequent section, which describes more extensively recent technological adaptations to self-monitoring in psychotherapy.
The systematic collection of behavioral data has always been a hallmark of operant behavior modification. As it became apparent in the literature that self-monitoring of one’s own behavior led to reactive effects
As the cognitive revolution evolved and psychological interventions transitioned from traditional behavioral modification to the cognitive behavioral therapy movement of the 1970s, self-monitoring was incorporated into these treatments as well. Psychotherapy relies heavily on client introspection. Per Prochaska and Norcross, “verbal psychotherapies begin by working to raise the individual’s level of observation” because “increasing consciousness…increases the information available to individuals so that they can make the most effective response to stimuli impinging on them” (pp. 12-13).
Thought records are a central intervention component of cognitive therapies for depression and anxiety to help clients identify and challenge automatic thoughts.
Other types of CBT involve worry records, daily mood records, and records of obsessions and compulsions.
Another influential psychological intervention that systematically utilizes self-monitoring is motivational interviewing (MI).
may involve biased estimates of how often a particular behavior occurs (e.g., an underestimation of how many drinks ones consume each week, or an overestimation of how much studying occurs during group study time). Self-monitoring may elucidate relations between a problem behavior and its consequences (e.g., measures of alcohol consumption with next-day mood and performance measures). MI conforms nicely to Carver’s cybernetic negative feedback loop model,
MI principles have been applied as brief interventions (BIs) for unhealthy alcohol use.
Although most self-monitoring in CBT focuses on prospective monitoring of behavior, an intervention from the stress literature, written disclosure, takes a retrospective form and involves the processing of a previous significant event. Pennebaker and colleagues have demonstrated that writing about emotionally significant memories has positive mental and physical health benefits.
Self-monitoring interventions are poised to become more prominent with the rise of Internet and smartphone technology. Technology-based interventions, whether they are stand-alone treatments or techniques that augment existing empirically-supported therapies, are not labor-intensive and are conducive to widespread dissemination. Even if the incremental effect sizes of these interventions are small, as stated by Sobell and colleagues,
Internet and mobile technologies have enabled new methodologies for self-monitoring, building upon established research techniques such as ecological momentary assessment (EMA)
One possible application of such technologies is self-diagnosis. For example, Groot
Consistent with this proposal, there already exist a number of popular commercial websites and mobile applications that allow individuals to track moods and events to see the warning signs of emerging psychological or relationship problems. Consumers desire increased self-awareness and insight, and new technologies empower them to find the information for themselves. Some technology-based mental health interventions focus on diagnostic self-monitoring,
Individuals vary in their adherence to recommended self-monitoring protocols.
Technology is uniquely outfitted to gather data in an automatic, continuous fashion. Smartphones are often equipped with features that allow for unobtrusive monitoring of behavioral indicators or correlates of mental health. Examples include accelerometers and Global Positioning Systems to track movement and activity, light sensors to provide inferences about sleep/wake patterns, and microphones and software to detect the quantity and quality of human speech.
Technology-based self-monitoring programs have been tested for the purposes of, reducing alcohol, marijuana, and tobacco use.
Technology-based interventions for alcohol management have shown varying results depending on the intervention and target population. Brief intervention (BI) using normative feedback has been shown to be effective for reducing drinking among those with unhealthy alcohol use
However, the literature is more mixed when examining psychotherapy treatment for alcohol use disorders that involve self-monitoring. Rose and colleagues
Surprisingly, Helzer and colleagues
A test of the Internet-based application Moderate Drinking,
Technology-based self-monitoring interventions for smoking have been more promising than those for alcohol management. MOMENT, a self-monitoring smartphone intervention for teens who are heavy marijuana users, reduced desire and use.
Another promising smartphone application (“app”) for smoking cessation is SmartQuit
Researchers have hypothesized that mobile technologies could be especially useful for tracking affective instability and disorders because of the opportunity for in-the-moment assessment of emotional states.
In stress management programs, online assessment has great potential for elucidating the situations, events, and emotions that comprise a broad experience such as “stress.” An example is an Internet-based stress and coping daily diary that is used with Cognitive-Affective Stress Management Training.
For children diagnosed with autism spectrum disorder (ASD), technology-based interventions that facilitate self-monitoring have demonstrated promising results as well. Personal prompting devices have been found to decrease stereotypy in middle school aged boys
Deitchman and colleagues
Studies investigating the efficacy of treatment maintenance for eating disorders (ED) using text message technology have shown mixed results. Bauer and colleagues
Schizophrenia is refractory to most traditional treatment modalities and has therefore been targeted with technology-based interventions for specific component symptoms. Preliminary efficacy trials suggest that a symptom self-management smartphone application, FOCUS, might help those with schizophrenia and schizoaffective disorder in reducing symptoms of depression, psychosis, and general psychopathology.
There has been a recent proliferation in the number of technology-based interventions that rely on Internet and smartphone app technology, but the majority of these interventions are commercial products that are not well researched. Those that are researched have demonstrated mixed findings even within the same target condition.
As such, at this point, providers should be cautious in recommending online tools to patients without sufficient informed consent about the potential drawbacks or null effects associated with these tools. Given the paucity of sufficiently-powered randomized control trials (RCTs) in the research literature and the presence of conflicting information based on the RCTs that are published, it is difficult to determine whether technology-based self-monitoring interventions contribute over and above the efficacy of other types of self-monitoring.
If researchers have noted advantages of technology-based self-monitoring over other forms of self-monitoring, the primary benefits have been the ubiquity of mobile technology,
Although self-monitoring has become an important component in many behavior change interventions, it is not uniformly associated with positive outcomes
| Feature | Definition | Predicted Effect |
| Outcome expectancies | Beliefs concerning the likely outcome of a behavior | Positive outcome expectancies, namely believing that self-monitoring will effect change, increases the likelihood of seeing an effect. |
| Complexity and detail | The number of different items being monitored and the level of detail required for each item | Increasing levels of complexity and detail seem to have a negative effect on adherence and outcome. |
| Sufficiency and quality | The level of detail needed to make self-monitoring meaningful | Only one study has found that a minimum level of detail may be necessary to see effects. |
| Timing | Whether self-monitoring occurs before or after the target behavior | Monitoring immediately before a behavior is about to occurs is thought to be either better or equivalent to post-behavior monitoring in terms of reactivity effects. |
Expectancies concerning the likely outcome of a behavior is an important determinant of whether or not that behavior will occur. Outcome expectancies are a major component of social cognitive theories advanced by Bandura
One obvious drawback of self-monitoring is the time or energy burden it can place on the client if monitoring is detail-intensive. One smoking cessation study found significantly lower rates of returning to a second treatment session among groups who were assigned to record daily cigarette consumption compared to groups asked only to pay attention to the situations in which they smoked (40-60% vs. 90%).
In a non-clinical study with undergraduate social psychology students, Hayes and Cavior
Helsel and colleagues
Thus, while a minimal level of self-monitoring is necessary to promote behavior change, intensive or highly detailed self-monitoring has the potential to burden the client and detract from treatment adherence.
On the other hand, some research suggests that the quality or thoroughness of self-monitoring may matter at least some of the time. These findings seemingly contradict the notion that mere engagement, as measured by number of recordings, is the best predictor for self-monitoring reactivity.
In one study of 18 adolescents in a behavioral weight control treatment
From the perspective of self-regulation, the timing of self-monitoring may affect behavior change efforts. Awareness that a behavior is going to occur is likely to be more useful than awareness of a behavior after it has already happened, under the assumption that earlier awareness allows for a disruption of the habitual behavior chain and an initiation of an alternate response.
In the weight loss literature, one study
Over fifteen years ago, Febbraro and Clum
While research on self-monitoring showed notable decline in the 1980s, self-monitoring remains an unquestioned central component of many psychotherapies.
One important area of research and application is the increasing use of technology in behavior change programs. As Kazdin and Blasé
One unanswered question about self-monitoring reactivity is the degree to which observed behavior change is the result of self-monitoring specifically, or whether those effects could be due to individual differences, such as trait conscientiousness. An important future direction for research on self-monitoring interventions is to assess individual difference variables to identify whether the intervention effects remain after taking into account possible personality traits related to differential outcome.
Another limitation to be addressed in future studies is the reliance on the self-monitoring records themselves or other self-reported outcome measures. The evidence for self-monitoring effects would be greatly strengthened by multitrait-multimethod assessment approaches, such as by including objective behavioral measures when available (e.g., blood alcohol level) and other methods of assessment (e.g., clinical interview as well as self-report).
The theoretical and empirical literature suggest that self-monitoring is necessary for behavioral regulation and is indispensable to many psychotherapies. Internet and mobile technologies have allowed individuals to conveniently access self-monitoring methods throughout their daily lives with the tap of a finger. Given the ubiquity of smartphones around the world, in both rich and poor countries, there is tremendous potential for population impact with the use of mobile mental health technologies.
The empirical literature suggests that technological innovations can make consistent and accurate self-monitoring more feasible. The benefits of this may be particularly pronounced in areas such as emotional disorders, where cognition is most likely to be skewed by the very processes one means to better understand, e.g., depression or anxiety.
Given the exponential capacity of computers to encode and process information, technology-based self-monitoring programs also have the potential to personalize medicine in novel and unprecedented ways. By utilizing an individual’s own data in real-time, computerized interventions have the potential to adapt and personalize assessment measures and coping tools. Technology opens up the possibility for rapid, responsive, iterative adjustments in assessment and treatment, and it is able to do this on a scale that would be impossible in a traditional, face-to-face health care delivery model.