“ That which is measured improves ” : A Theoretical and Empirical Review of Self-Monitoring in Self-Management and Adaptive Behavior Change

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 selfregulation 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. DOI : 10.14302/issn.2474-9273.jbtm-16-1180 Corresponding author: Jessica A. Chen, Center of Innovation for Veteran-Centered and Value-Driven Care, VA Puget Sound; Department of Health Services, University of Washington. Email: chenj4@uw.edu


Introduction
The vast majority of individuals with mental health needs who would benefit from efficacious psychological treatments do not receive them. 1 The failure of current one-on-one treatment modalities to meet existing mental health needs requires economically feasible, short-term and, in some cases, selfadministered or web-based prescriptive treatments that exist outside specialized health care settings. 2Health care is becoming increasingly patient-centered, moving away from provider-centric models of care to ones in which patients take increasing responsibility for lifestyle modifications, behavioral change, and self-regulation. 3,4is may be particularly true for psychological health. 5e 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. 6,7Similar historical narrative reviews in the behavioral medicine literature have applied self-regulation theory to understanding the mechanisms underlying self-management of chronic health conditions. 8llowing an overview of self-regulation theories, this review will discuss the origins of self-monitoring in the psychotherapy literature, with a focus on well- 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, 10,11 smoking cessation for individuals with chronic medical conditions 12 , and weight management 13 .Although physical and mental health are intertwined, the health behavior literature is largely outside the scope of this review and has been extensively reviewed elsewhere [14][15][16] .This review will discuss the self-regulation of physical health behaviors (e.g., smoking) only when it is directly applicable to understanding the modifiers of self-monitoring effectiveness.Similarly, for quite some time educational researchers have been investigating the importance of self-monitoring in managing disruptive classroom behaviors and increasing on-task learning.health, the education literature is outside the scope of the present review.

Self-Regulation
Self-regulation models [21][22][23]  Comparison of Models.There are a few differences among the three self-regulation models presented here.Kanfer and Karoly's model 23 was developed with the closest ties to psychotherapy and is therefore more concerned with self-regulation in situations where there is a conflict between incompatible goals, or where one behavioral tendency is more habitual and another is more controlled. 28Social cognitive 21 and learning models 23 emphasize the importance of affect for shaping behavior more so than do information processing models, which emphasize positive or negative evaluations of one's current state motivate behavior change.
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.

The Origins of Self-Monitoring in Psychotherapeutic Interventions
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'" 29 .
Self-monitoring is used across many psychotherapeutic interventions for a multitude of purposes, from data gathering and reporting, to increasing selfawareness, to functioning as an active intervention that changes future thoughts and behaviors.In the following section, a brief overview will be provided of how selfmonitoring 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 selfmonitoring in psychotherapy.

Traditional Behavior Modification
The systematic collection of behavioral data has available to individuals so that they can make the most effective response to stimuli impinging on them" (pp.12 -13). 34Cognitive behavioral therapies (CBT), in particular, emphasize data gathering by the client.CBT has utilized self-monitoring so extensively that only a brief overview of common, evidence-based CBT methods will be discussed here.
Thought records are a central intervention component of cognitive therapies for depression and anxiety to help clients identify and challenge automatic thoughts. 35,36For panic disorder, ongoing self-monitoring of panic attacks helps the client identify situations in which panic attacks are more likely to occur, understand how panic attacks are experienced (through recording of physical sensations, thoughts, behaviors), more accurately judge their varying levels of anxiety and panic than is possible with retrospective recall, and monitor ongoing progress. 37her types of CBT involve worry records, daily mood records, and records of obsessions and compulsions. 38,39CBT for bulimia and binge eating disorders utilizes a daily food diary for monitoring eating and planning meals, thus serving both a record keeping and self-regulation (planning) function.Dialectical behavior therapy employs a diary card for clients to track their skills use between sessions. 40,41[44] Motivational Interviewing and Brief Alcohol

Intervention
Another influential psychological intervention that systematically utilizes self-monitoring is motivational interviewing (MI). 45MI is a nondirective intervention in which self-monitoring is used to provide concrete evidence of discrepancies between the client's current conceptions of self and their actual behavior, thereby motivating behavior change.Clients' current conceptions 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, 22 in which discrepancies between the current state and some standard engages motivated change.
MI principles have been applied as brief interventions (BIs) for unhealthy alcohol use. 46BIs often rely on the collection of personal data (e.g., recent drinking patterns) followed by the provision of normative feedback. 47The goal of BIs is to provide corrective information to address some of the biases that may mediate unhealthy alcohol use. 48,49The underlying mechanisms of BIs are similar to the functions of feedback and goal-setting in Bandura's social-cognitive model. 50

Retrospective Self-Monitoring
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.][53] According to Pennebaker and Segal, 52 the act of remembering and organizing autobiographical events to create a "personal story" allows individuals to integrate thoughts and feelings and derive meaning from their experiences.In doing so, personal experiences take on structure and a sense of predictability, which render the emotional impact of a traumatic life event more manageable.Self-monitoring involves becoming aware of one's patterns of thoughts,

Self-Diagnosis
Internet and mobile technologies have enabled new methodologies for self-monitoring, building upon established research techniques such as ecological momentary assessment (EMA) 55 , the experience sampling method (ESM) 56 , web-based daily diaries 57 .
These technologies make frequent and event-specific assessment much more feasible.
One possible application of such technologies is self-diagnosis.For example, Groot 58 notes that in the "flow of life," the difference between a bad mood or difficult period of time and depression may not be apparent to the individual until a depressive episode is quite severe.Many people may be unaware that their mood is significantly more negative than their baseline.
Groot proposes that continuous, longitudinal selfmonitoring, combined with the appropriate data analysis software, could allow individuals to diagnose the "phenotype" of depression in themselves earlier than would be possible without regular self-monitoring.
Furthermore, repeated sampling of environmental variations may allow the individual to identify triggering or sensitive events that could be handled differently in the future.
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, 59,60 such as for unhealthy alcohol use 61 or eating disordered behavior. 62

Unobtrusive Self-Monitoring
Individuals vary in their adherence to recommended self-monitoring protocols. 63At times, the very target of measurement (i.e., mental health symptoms) may limit or impair individuals' cognitive and functional capabilities to engage in consistent self-monitoring. 64is has led some to advocate for more "passive" or unobtrusive methods of self-monitoring that can gather data without active involvement from the participant.the quantity and quality of human speech. 64Emerging research has found that these unobtrusive measurements are correlated with self-report of mental health symptoms, which suggests they may useful for continuous symptom monitoring. 64Studies that have combined data from active self-monitoring and passive or unobtrusive measures, such as geographically explicit ecological momentary assessment (GEMA), found that certain mental health-relevant phenomena (e.g., substance use craving) can be predicted by geospatial location. 65Additionally, one small trial that tested unobtrusive self-monitoring as an intervention itself, combined with personalized feedback and tailored interventions delivered via smartphone, found promising reductions in depression symptoms. 66

Substance Use
Technology-based self-monitoring programs have been tested for the purposes of, reducing alcohol, marijuana, and tobacco use. 67 unhealthy alcohol use 46 , and when BIs are provided online, the results seem to be equivalent to face-to-face methods. 68,69wever, the literature is more mixed when examining psychotherapy treatment for alcohol use disorders that involve self-monitoring.Rose and colleagues 70

A test of the Internet-based application
Moderate Drinking, 74 which was designed for heavy drinkers, showed reduced consumption rates postintervention; however, the application utilized numerous treatment components, including self-monitoring and goal setting, and it was unclear which components were essential mechanisms of change.
Smoking.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. 75The authors posit that receiving feedback directly after submitting self-monitoring data may have been critical to the intervention's efficacy.

Another promising smartphone application
("app") for smoking cessation is SmartQuit 76 , which is based on the behavior change principles of Acceptance and Commitment Therapy (ACT). 77As its name implies, ACT focuses on increasing the willingness to experience aversive events, such as physical cravings for tobacco, while committing to behaviors that are in accordance with important goals and values, such as improved health outcomes).One of the most effective features of the SmartQuit program is a self-monitoring component that involves the tracking of urges to smoke, tracking of urges experienced without smoking, and the number of smoke-free days. 78,79Positive feedback (badges) that are earned by experiencing urges without smoking is assumed to reinforce smoking cessation and enhance self-efficacy.Among smokers who completed the program, 88% reduced their cigarettes and 33% quit completely. 76This research also showed the importance of inducing participants to engage in active selfmonitoring for a sufficient period of time to complete the program. 79Other research on smoking cessation apps (e.g., SmokefreeVET80 for U.S. military veterans) have found similar results regarding the effect of engagement on outcome, namely that users who use the app with greater frequency also achieve better outcomes.

Affect, Stress, and Anxiety
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. 81Real-time assessment, as compared with retrospective recall, may better capture affect and therefore increase accurate self-awareness. 59,60This hypothesis is supported by Harrison and colleagues 82 who tested "myCompass," a mobile phone tool that involves real-time self-monitoring, messaging prompts, and online CBT education modules, The tool was associated with reductions in symptoms of anxiety, depression, and stress.Reid and colleagues 19 reported a significant reduction anxiety, depression, and stress for adolescents using mobiletype, a mobile phone app designed to track affective states, among other.A systematic review 83 of the utility of electronic selfmonitoring of mood for patients with bipolar disorder determined that the evidence for self-monitoring as a stand-alone intervention was inconclusive.Some studies lacked sufficient internal validity to draw conclusions about the effect of self-monitoring, and one randomized clinical trial actually found potentially harmful effects for self-monitoring of depressive symptoms, although this finding has yet to be replicated.The authors suggest a thoughtful and critical approach to the use of electronic self-monitoring of mood symptom in bipolar disorder.
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 Internetbased stress and coping daily diary that is used with Cognitive-Affective Stress Management Training. 42,44The daily diary assesses the characteristics of stressful situations, cognitive appraisals, potential stress-reducing reappraisals, affective responses, and extent-use and perceived effectiveness of a dozen possible coping strategies.It allows clients to discover relationships between situations, thoughts, and feelings and is used to provide idiographic administration of a brief manualized cognitive-behavioral intervention. 42,43In this program, the potential effects of stand-alone selfmonitoring on stress-related clinical outcomes remains untested.

Autism Spectrum Disorder
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 84 and increase on-task behaviors in boys between the ages of eight and thirteen. 85,86These prompting devices have the advantage of being inconspicuous, and they have been found to facilitate independence in children with ASD by reducing the number of adult cues needed. 85,87itchman and colleagues 88 89 found that selfmonitoring with a vibrating watch, which acted as a personal prompting device, was even more effective than VFB.In a study comparing the efficacy of paperand-pencil to iPad self-monitoring, Bouck and colleagues 87 found that the number of tasks adolescents with ASD completed and the number of prompts they needed was only slightly improved with the iPad.
Although each of these studies had samples of four or fewer participants, results suggest that technologies that facilitate self-monitoring may help address a range of symptoms associated with ASD.

Eating Disorders
Studies investigating the efficacy of treatment 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, 82,94 improved data validity compared to retrospective reports in some cases (e.g., alcohol use) 73 , and timely feedback 91,95 .Understanding the features that promote or limit the effects of self-monitoring is critical when considering the development of innovative interventions rooted in selfmanagement principles.A summary of the features discussed in the following section is included in Table 1.90%). 103Complex or detailed self-monitoring may be intimidating early in treatment, particularly if the psychotherapist does not provide a clear rationale for its utility. 102

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 The level of detail needed to make Only one study has found that a minimum level of 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.Helsel and colleagues 106 found that weight loss patients who transitioned to an abbreviated selfmonitoring method halfway through treatment returned more food and exercise diaries than those who continued with a traditional detailed method, and the two groups had comparable outcomes.The authors conclude that it may be the engagement with selfmonitoring, rather than the level of detail, that is important for behavior change.This parallels the research from smoking cessation apps that suggests that engagement with self-monitoring, as measured by the number of times that it occurs, is one of the most significant predictors of treatment outcome. 79us, 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.

Sufficiency and Quality
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 107 , the only aspect of selfmonitoring associated with post-treatment and threemonth follow-up body mass index (BMI) was what the authors termed "recording sufficiency," defined as recording five or more food or beverage items in a day.
By contrast, there was no significant association between BMI and the number of days recorded, which suggests that merely submitting more recordings was not enough to effect change in weight.While this finding on recording sufficiency is suggestive, it has yet to be replicated.Future research should consider whether a minimum level of quality or sufficiency is necessary to make self-monitoring useful.
Timing 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. 23However, there have been inconsistent findings regarding whether the reactivity of selfmonitoring varies as a function of its timing.
In the weight loss literature, one study 108 found that monitoring planned food intake before eating led to greater weight loss than monitoring the amount of food consumed.In contrast, Karoly and Doyle 102 used a between-subjects design with undergraduate students to compare pre-and post-behavior monitoring and found that monitoring smoking urges (pre-behavior) did not lead to better outcomes than monitoring cigarettes consumed (post-behavior).Because both groups were equally successful in decreasing cigarette consumption, it may be that pre-behavior monitoring aided the selfmotivating and directive functions of self-regulation, whereas post-behavior monitoring exerted its effects through self-punishment. 21Ultimately, there is no clear conclusion about whether the timing of self-monitoring matters, and most treatment protocols continue to utilize post-behavior recording.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).

Future Directions
The theoretical and empirical literature suggest that self-monitoring is necessary for behavioral disorders, where cognition is most likely to be skewed by the very processes one means to better understand, e.g., depression or anxiety. 110,111ven the exponential capacity of computers to encode and process information, technology-based selfmonitoring 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.
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 selfmanagement skills training, motivational enhancement, and behavioral activation. 9Finally, 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.
always been a hallmark of operant behavior modification.As it became apparent in the literature that selfmonitoring of one's own behavior led to reactive effects 30 , self-monitoring became a central treatment component in operant programs designed to enhance Self-monitoring self-regulation, such as smoking cessation programs.[31][32][33]By taking measurements of specific target behaviors (e.g., cigarette smoking), selfawareness was enhanced and this, in many cases, motivated behavior change assuming the person possessed the requisite behavior change skills.Selfmonitoring also served as a self-reinforcer for behavior change when people observed objective evidence of improvement. 21Cognitive Behavioral Therapy 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.Psychothera-Freely Available Online www.openaccesspub.org| JBTM CC-license DOI : 10.14302/issn.2474-9273.jbtm-16-1180Vol-1 Issue 4 Pg.no.-23 py 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…increase[s] the information

Freely
Available Online www.openaccesspub.org| JBTM CC-license DOI : 10.14302/issn.2474-9273.jbtm-16-1180Vol-1 Issue 4 Pg.no.-24 emotions, and behaviors and then constructing hypotheses about why certain behaviors occur under certain conditions.Similar to more traditional, formalized CBT interventions, the therapeutic effects of written disclosure paradigms are thought to be mediated through the cognitive processes of awareness and insight.Technological Applications of Self-Monitoring 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, 54 cumulative per capita gains can translate into large benefits for society.Furthermore, individual, face-to-face therapy cannot work as the only model of treatment delivery if our aim is to meet the existing demand for psychological services. 1The following section discusses the overall trend in health care towards greater self-management through new technologies and reviews empirical studies that have examined the efficacy of these technologies within psychotherapeutic interventions.
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 Freely Available Online www.openaccesspub.org| JBTM CC-license DOI : 10.14302/issn.2474-9273.jbtm-16-1180Vol-1 Issue 4 Pg.no.-25 These interventions target different aspects of the recovery process, from unhealthy use to maintenance of treatment gains.Technology-based interventions have the potential to overcome barriers associated with traditional substance use treatment, such as stigma, privacy concerns, and time constraints.Technology-based interventions may offer a means for overcoming some of these barriers by minimizing patient commitment and maximizing privacy.Alcohol 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

93 Summary
maintenance for eating disorders (ED) using text message technology have shown mixed results.Bauer and colleagues90 asked patients discharged from inpatient ED treatment to send in weekly symptom reports for 16 weeks via text message, and study investigators sent patients weekly tailored feedback.The authors suggest that the feedback may have been viewed as supportive, acted as a helpful reminder of CBT skills, and encouraged participants to seek outpatient treatment when needed.However, results should be interpreted with caution as remission rates between the intervention and control group did not differ in a clinically significant way.Similarly, Shapiro and colleagues91 found reduced symptomology for binging and purging at the conclusion of a 12-week intervention during which participants texted symptoms nightly.However, despite the high adherence rate for completers, the study had a slightly higher attrition rate than non-technology based studies for treating bulimia nervosa.SchizophreniaSchizophrenia 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. 92The FOCUS smartphone intervention consists of symptom self-monitoring through brief assessment and self-management resources for mood regulation, medication adherence, social functioning, and improved sleep.The outcomes of the self-monitoring assessment were used to inform which self-management resources patients would have access to in the app.For instance, reports of anxiety in social interactions might lead to a suggestion to use cognitive restructuring ("test your thinking"), whereas reports of auditory hallucinations would prompt a suggestion to listen to music.The authors found high rates of acceptability among participants based on app usage, which was in part attributed to including patients in the app development phase to refine use, design, and functionality.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.59,60,62As 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 Freely Available Online www.openaccesspub.org| JBTM CC-license DOI : 10.14302/issn.2474-9273.jbtm-16-1180Vol-1 Issue 4 Pg.no.-28 technology-based self-monitoring interventions contribute over and above the efficacy of other types of self-monitoring.
Influence the Effects of Self-Monitoring Although self-monitoring has become an important component in many behavior change interventions, it is not uniformly associated with positive outcomes 96-99 , as the recent literature on technological innovations makes clear.Information or awareness alone does not necessarily produce behavior change.The inconsistency of positive effects has led some to ask, which variables affect the utility of self-monitoring as an intervention? 100 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 Bandura26 and Mischel.101Karoly and Doyle 102 manipulated outcome expectancies for selfmonitoring, telling half of their smoking cessation clients that self-recording had been proven effective for smoking cessation in the past, while the remaining clients were told that the self-recording technique was still under investigation.The positive outcome expectancy groups showed greater reductions in smoking than the negative expectancy groups, which suggests that providing a clear treatment rationale and positive expectations for the utility of self-monitoring can improve treatment outcome.The authors proposed that positive outcome expectancies increase motivation and treatment compliance, which in turn lead to better outcomes.Complexity and DetailOne obvious drawback of selfmonitoring 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.

Freely
Available Online www.openaccesspub.org| JBTM CC-license DOI : 10.14302/issn.2474-9273.jbtm-16-1180Vol-1 Issue 4 Pg.no.-30 Conclusions Over fifteen years ago, Febbraro and Clum 109 conducted a meta-analysis on the effectiveness of selfregulation techniques (e.g., self-monitoring, selfreinforcement) as primary treatment interventions.Compared to no intervention at all, self-monitoring (SM) yielded a small but significant effect size (d = .29).When interventions utilizing other self-regulation techniques (e.g., self-reinforcement) were added, the comparison of SM-alone and SM-plus to waitlist/minimal contact control groups yielded a medium effect size (d = .45),suggesting that self-regulation interventions that combine self-monitoring and other treatment modalities are effective.The somewhat modest effect sizes of these techniques as stand-alone interventions must be counterbalanced with the fact that they are often far more efficient than one-on-one psychotherapies.They may lend themselves to well-designed self-administered interventions, perhaps aided by therapist consultation and monitoring.Notably, this meta-analysis was conducted prior to the recent proliferation of selfmanagement smartphone apps and other Internet-based interventions rooted in self-regulation theory.While research on self-monitoring showed notable decline in the 1980s, self-monitoring remains an unquestioned central component of many psychotherapies. 100Future research should more closely examine what contribution or additive effect, if any, selfmonitoring has within an already empirically supported treatment.One important area of research and application is the increasing use of technology in behavior change programs.As Kazdin and Blasé 1 have noted, traditional models of mental health service delivery are simply incapable of addressing existing demand.Recent innovations, such as self-administered interventions and "big data" methods that utilize built-in features of our existing technologies to gather more data than a single individual can track 64 , have positioned the field of mental health care to expand access to services in an unprecedented way.Virtually all of these innovations rely, in part, on technology-enabled self-monitoring of situations, behaviors, emotions, and consequences.Limitations 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 selfmonitoring 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.
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 selfmonitoring more feasible.The benefits of this may be particularly pronounced in areas such as emotional Freely Available Online www.openaccesspub.org| JBTM CC-license DOI : 10.14302/issn.2474-9273.jbtm-16-1180Vol-1 Issue 4 Pg.no.-31

23 Freely Available Online www
25nitoring 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, informationprocessing, and social-cognitive perspectives of selfregulation, with a focus on the indispensable role of selfmonitoring within these models.Theoretical ModelsBehavioral Model A seminal early contribution is found in Kanfer and Karoly's behavioral model of "selfcontrol"23, defined as disengagement from habitual, automatic, or dominant action tendencies.Kanfer and 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)24.While the behavioral model was one of the first to propose that self-monitoring is necessary for self-regulation, the model does not provide clear explanations for why or under what this model is the notion of a "negative feedback loop," a term borrowed from cybernetics and information processing.The negative feedback loop proposes four components of self-regulation: a goal or standard, input (from self-monitoring), comparison of the current state to a desired one (discrepancy monitoring), and feedback (behavioral change).25In the information processing model, selfregulation functions as a hypothesized test-operate-testexit (TOTE) unit."Test"refers to the processes of selfmonitoring, 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") .openaccesspub.org| JBTM CC

-license DOI : 10.14302/issn.2474-9273.jbtm-16-1180 Vol
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).
-1 Issue 4 Pg.no.-22 a non-clinical study with undergraduate social psychology students, Hayes and Cavior 104 found that