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Introduction

The Experience sampling method (ESM) or Ecological momentary assessment (EMA) is a research procedure employed to collect and study data concerning the daily activities of life. The ecological momentary assessment technique entails what people do, feel and think during their daily lives. It consists of documenting the systemic self-reports from a sample of individuals at various occasions during the waking hours of a normal day. The data retrieved helps in assessing the daily routine of the individuals, and their thinking patterns. Furthermore, the experience sampling method also compares the psychological states of different populations such as men, women, adolescents, adults, disturbed, and normal.

The EMA/ESM data collection is usually triggered by signals such as notifications from the Qolty application. The experience sampling method evaluates the experience, behavior, and moment to moment fluctuations in mental states in the daily life. In general, it demands the participants to complete an assessment usually in the form of short questionnaires repeatedly over a specific period.

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These questionnaires entail current mood, perceptions, cognitions, behaviors, and the description of the momentary context (location, company, activity). (Delespaul et al. 1995; Stone et al. 1994). As a whole, these assessments focus on the symptoms, adaptive functioning, and the overall well-being of the participants (Csikszentmihalyi et al. 2013).

History

Kurt Lewin (1935) was the first to advocate the need of the topology of daily activities i.e. the scientific study of the everyday life. He was of the opinion that by determining the psychological aspects of life, especially the intrapsychic aspects of existence, it would be easier to probe the thought and behavior domains of human beings. Unfortunately, Lewin did not have a valid analysis method for studying daily experience. Roger barker, P.V. Gump, and Herbert Wright devised an observational technique based on the behavioral approach that had creditable scientific support but neglected Lewin’s concern for the intrapsychic aspects of existence. Their observational technique was only useful in studying the public behavioral aspects and did not deem to observe the private life of the individuals.

The experience sampling method was originated with paper and pencil methods, usually through a diary that was returned to the investigator after the daily recording of activities throughout a week or a specified period of sampling. However, a single-page questionnaire technique was also employed that was mailed in daily and the postmark verified.

Diary techniques provided a reliable measure for probing the public and private lives of individuals. Early dairy studies by Bevans 1913, Altshuller 1923, and more sophisticated diary studies (Szalai et al. 1975; Robinson 1977) have provided valuable insight into the activities performed by individuals during their waking hours. For instance, Szalai et al. 1975 assessed that American and European adults spent far less time relaxing than adults across the globe. However, still, their focus was on the behavioral aspect neglecting the thought pattern and feelings of the individuals.

Despite the early success of experience sampling methods, the intrapsychic variables still needed to be evaluated in a noteworthy fashion. Afterward, personality research nurtured the development of psychometric procedures that used the conventional paper and pencil technique to probe the thoughts and feelings of humans. Although most psychometric studies endeavored to measure stable traits rather than daily experience, there was an increasing shift in determining the individual’s quality of life. However, the breakthrough came when Campbell 1976 investigated the various segments of normal existence.

Another methodological limitation of the experience sampling method was the people’s self-assessment based on recognition and recall. Evidence suggests that people cannot provide reliable assessment of intricate dimensions of their own personality or experiences if the data is not collected promptly (Yarmey 1979). This limitation was later overshadowed when the ecological momentary assessments were recorded in real-time. Also, one-time assessments were subjected to cultural and ethnic stereotypes, thereby providing unreliable data (Shweder 1975).

As far as the methodology is concerned, paper and pencil technique was evolved into the hand-held computer devices such as the PDA’s (Personal Digital Assistants). This technique also proved to be successful in overcoming the potential pitfalls of retrospective recall. The data was collected in a timely fashion, and the program itself records the exact time of data entry.

In the present smartphone-driven world, these conventional techniques have been outshone by the applications such as Qolty that makes Ecological momentary assessment simple and straightforward. The experience sampling methods are becoming more executable for multiple purposes and in multiple contexts. The application platform provides a robust and actionable approach to psychological science (Miller 212). Cohn et al. 2011 believed that these apps enhance compliance as they directly intervene in people’s lives promoting positive vibes. This application platform can revolutionize the entire scenario by recording the people’s activities of lives and thought patterns in the closest time possible. This technique makes Ecological momentary assessment way too easy and engaging as it was before; opening new avenues for researchers to design and implement new studies in a reliable fashion.

Conventionally, these assessments were administered through paper and pen method used in combination with pagers or electronic wristwatches (Delespaul et al. 1995). With the advancement in technology, electronic devices (PDA’s), and smartphone apps such as Qolty surpassed the traditional pen and paper technique. The surveys are usually short and completed within 1 to 2 minutes. The items are designed for prompt and easy data collection which usually comprise of open-ended questions, checklists or self-report Likert scales, and visual analog scales (Csikszentmihalyi et al. 2013).

Study Designs

The scheduling, arrangement and temporal coverage of Experience sampling method can be broadly categorized into event-based and time-based sampling schemes (Shiffman et al. 2007; Wheeler and Reis 1991). The Ecological momentary assessment is representative of the subject’s experience or behavior; therefore, an efficient design should capture the data in a real-time manner keeping in view the aims of the study.

Event-based monitoring focuses only on the distinct events or episodes in subject’s lives, disregarding the entire experience. For instance, drinking episodes (Todd et al. 2005), or headaches (Niere and Jerak 2004). On the contrary, time-based schemes illustrate experience more broadly and inclusively. For instance, observation of mood variation with respect to time without predetermined emphasis on distinct events.

Event-Based Scheme

In many cases such as drinking, panic attacks, or violence the clinical and research interest is event or episode centered. In event-based monitoring, the data is recorded on the occurrence of a predefined event of interest. For instance, subjects might be asked to fill an assessment when they engage in a social interaction lasting over 10 minutes (Reis and Wheeler 1991), have a panic attack (Taylor et al. 1990), or take a medicine (Jonasson et al. 1999). Usually, the subject has to determine when the event has taken place and initiate an assessment. In some cases, predefined events are recorded as episodic flare-ups of otherwise perpetual experiences such as an intense episode of pain (McCarberg 2007), or an outburst of cigarette craving (Shiffman et al. 1997a).  The main aim of this scheme is to determine the occurrence of the episode — their frequency, intensity, antecedent mood, and time distribution (Schlundt et al. 1985, Shiffman et al. 1996b).

Pitfalls of Event-Based Schemes

The most challenging part is defining an algorithm for declaring an event. If the events are too frequent, it would be illogical to record all the occurrences. Therefore, a subset of these events needs to be sampled at random instances (Shiffman et al. 2002). Another drawback is the absence of a reliable measure to verify compliance i.e. the accuracy of the data is not ascertained. The event- based schemes are prone to falsification. For example, Hufford et al. 2007 concluded that medication compliance is exaggerated in self-report. However, this limitation is compensated by the use of the electronic devices for assessment. For instance, Shiffman and Paty 2003 demonstrated that subject’s electronic diary records of cigarettes were in line with the biochemical measures of smoking.

Time-Based Schemes

Some clinical parameters such as pain and mood cannot be easily evaluated through event-based monitoring as they keep on varying continuously. The Ecological momentary assessments can be made with a variety of time-based assessment schedules. Some approaches require assessment at fixed intervals. For example, the ambulatory monitoring of blood pressure every 30 to 45 minutes (Kamarck et al. 1998). These fixed intervals serve to analyze autocorrelation and time series studies efficiently.

On the contrary, some studies rely on irregular intervals, usually defined by social parameters. For instance, Hensley et al. 2003 instructed the subjects to complete an assessment for asthma in the morning and evening each day. This technique is, however, subject to potential bias as the subjects complete the assessment at their own discretion. Also, the subjects might recall completing their assessment when the symptoms get worse, thus biasing the sample of mood.

An alternative approach to fixed intervals is a variable schedule, which usually collects data at random occasions. It is a better representation of subject’s overall physiological state. For instance, Affleck et al. 1998 assessed subjects once in each predefined time window in the morning, afternoon, or evening with random intervals of assessment schedule. These specific time windows serve to analyze autocorrelation and time series studies efficiently; each time block serving as an individual unit of analysis. However, the variable scheduling requires some signaling method that alerts the subject to complete the assessment. With Qolty app, an alert notification is popped up every time the subject needs to fill in the assessment. Although the subject initiates the assessment filling, appropriate time-based sampling technique should be incorporated beforehand to enhance participant’s compliance.

Combination Schemes

For an efficient experience sampling method design, different sampling schemes can be combined to get a synergistic effect, or to test a specific hypothesis. When the investigator is interested in the circumstances associated with an episode, combining an event-based scheme with time-based monitoring can prove to be beneficial.

When both the schemes are combined, time-based assessments can also document the antecedents or sequelae of events. It was manifested by the work of Shiffman and Waters 2004 when they employed the time-based scheme to exhibit that ex-smokers were experiencing intense affective distress in the hours following a smoking lapse (the event). It was also demonstrated that self-efficacy decreased after a lapse, but not following the occasions when the subject successfully resisted the urge to smoke (Shiffman et al. 1997b).

Time-based assessments can be used to follow-up on the sequelae of a documented event; how quickly the medication delivers its therapeutic effect and how long the relief lasts. For instance, Sheftell et al. 2005 instructed the subjects to record the onset of migraines and then scheduled a series of assessments as follow-ups.

The different time-based schedules can also be combined successfully. This approach was manifested in the study of Muraven et al. 2005. They assessed the social drinking behavior in subjects throughout the day, and in addition, also scheduled to ask about the hangovers from the preceding night’s drinking episode in the morning.

Applications

The experience sampling method has countless applications, broadly classified into four categories. These four categories are individual differences, natural history, temporal sequences, and contextual associations.

Individual Differences

The ecological momentary assessment data is aggregated to measure the individual subject’s response over the specified period of time. For instance, in the case of the pain experienced by the patient, the data could be gathered before and after the intervention to quantify the subject’s quality of life. The aggregated ESM data is projected to provide reliable (because of aggregation) and valid (because of the absence of recall bias, representative sampling, and ecological validity) assessments.

Natural History

To elaborate natural history, ecological momentary assessment measures are analyzed for trajectories over time. The time factor serves as an independent variable, whereas the subject’s intrinsic variation over time is taken the dependent variable. For instance, McCarthy et al. 2006 demonstrated the trends of various withdrawal symptoms experienced by the ex-smokers after quitting. The ESM data revealed that some symptoms, although intense in the early phase gradually faded away with time, while others increased and lingered, and still others increased only progressively over time. These trajectories declined the widely held beliefs about the progression of the withdrawal syndrome and were linked with differences in treatment outcomes. Therefore, the basic descriptive evidence about the natural history of the symptoms over time can pave path for the better understanding of clinical disorders and consequences.

Temporal Sequences

The longitudinal nature of experience sampling method data is employed to probe events or experiences in the closest time possible, whether to document antecedents or outcomes of events or behaviors or to examine the cascades of events. In these assessments, the sequence of events is the main focus.

Curry and Marlatt 1987 hypothesized that the psychological response to lapses plays an integral part towards the development of relapse. Later, Shiffman et al. 1997b investigation on smoking cessation assessed smoker’s affect and self-efficacy before and after lapses to smoking, and their effects on consequent development toward relapse. Marlatt’s hypothesis was validated by Shiffman et al. 1997b by comparing assessments before and after lapses, stating that lapses would result in increased negative affect and decreased self-efficacy. However, later comparisons with EMA data depicted that retrospective reports of relapse episodes were erroneous and biased. The subjects recalled their mood as worse than it actually had been, and those who started smoking again at the time of recall exaggerated the demoralizing nature of the initial lapse. Therefore, a valid and robust understanding of behavior could be accomplished with prospective assessments of the flow of behavior and experience.

These cases represent the utilization of EMA data to assess hypothesis with respect to the dynamic connections among procedures over time. Data provided by EMA studies might be compared to a motion picture, in which dynamic correlations emerge over time, whereas worldwide or recall based assessments are analogous to a still photograph, a solitary static preview of time. By providing temporal resolution, experience sampling methods enable investigators to scrutinize sequences of events and experiences, and empower them to analyze and break down the cascade of events in specific periods of time for better understanding.

Human behaviors are intricate; therefore, insight into micro-processes can give a better understanding of the overall process. Many theories of psychopathology and treatment focus on how disease process unfolds over time. In addition, splitting the events into micro-processes can help develop more efficacious interventions. The ability of the Experience Sampling methods to focus on dynamic processes and situational influences is potentially the most stellar contribution in the field of clinical psychology.

Contextual Associations

Contextual association studies usually investigate the association between two or more events or experiences occurring simultaneously. Although the data is collected longitudinally, the analysis of contextual association is cross-sectional, and it focuses on the co-occurrence of events or experiences rather than their sequence; timeframe is not represented explicitly. For instance, Myin-Germeys et al. 2001 probed emotions associated with stressful events to scrutinize a diathesis-stress model of schizophrenia. They concluded that susceptibility to schizophrenia would be reflected as excessive emotional outburst accompanying stress.

Schizophrenics, their first-degree relatives (who are hereditarily susceptible), and controls were surveyed 10 times daily about distressing occasions and mood. An examination of individual differences in average demonstrated that schizophrenics reported more negative effect and more stressful occasions, whereas susceptible people and controls did not vary. The contextual association between the stressor and mood uncovered that the first degree relatives responded more unequivocally than did controls. This contextual association was helpful in determining the genetic predisposition due to schizophrenia.

Understanding the momentary cross-sectional relationship between various aspects of experience has, likewise, been essential for foundational investigations of the structure of behavior and experience. To address whether positive and negative feelings are inverses or are autonomous dimensions and can be experienced simultaneously: Feldman-Barrett and Russell 1998 utilized EMA data to address the contention that albeit one could be both happy and distressed over some period, but in a specific moment, these opposite forces cannot co-exist together.

Although most contextual association studies are conducted between different variables within the same individual, a fascinating variation discussed the impact of one individual on the other in a relationship (Bolger et al. 2005). In accordance with the same line of thought, Larson et al. 1994 instructed the couples to track their experience in parallel and record how the mood of each affected the other. They concluded that a husband’s mood when he comes home from work greatly influences his wife’s mood, but not vice versa.

Applications of Experience Sampling Method in Treatment and Intervention

The experience sampling method/ecological momentary assessment can also help in designing effective treatment and intervention plans.

Applications in Treatment

Besides the applications in the research data, the EMA studies can also be employed for ongoing assessment during treatment. A properly structured EMA data can provide revealing opportunities for the treatment plan. As change is expected during treatment, ongoing assessments can prove to be informative. EMA data can also capture the processes and mediators of psychotherapy-induced change.

Kramer et al. 2014 demonstrated that the supplemental use of ecological momentary assessment along with the standard antidepressant treatment might prove to be an effective tool. They concluded that the EMA data complement the anti-depressive treatment significantly, and EMA-derived positive feedback was correlated with the linear decrease in HDRS depressive symptoms over time that lingered until the previous follow-up six months later.

Applications in Intervention

The implementation of EMA methods in real-time interventions can revolutionize the clinical treatment plans. Newman et al. 2003 discussed a variety of electronic assessment methods for the treatment of psychological disorders. Earlier, Newman et al. 1997 reported that a brief Electronic momentary assessment for panic disorder was comparable in efficacy to a longer therapist administered treatment. This depicts the incremental benefits of EMA intervention. Momentary interventions have also been evaluated in addictive disorders (Riley et al. 2002) and eating disorders (Norton et al. 2003).

The idea of delivering intervention immediately on the spot can address behaviors at crucial moments in patient’s life. The individual patient’s history may prove to be helpful in designing effective interventions for others. Additionally, the screening of patients over time could be beneficial in making predictive algorithms. For instance, by noticing the increasing stress levels, and intervening in the early phase before the symptoms get worse.

Strengths and Limitations

Strengths

ESM was only used for research in the identification of moment-to-moment patterns and mechanisms of psychopathology (Wichers et al. 2011), but now both the patients and professional caregivers have ready access to real-life data with the advent of applications and personal digital assistants (PDAs). The ESM interventions (ESM-I) can change indirect real-life dynamic patterns to clear, visualized, and quantifiable configurations. These results can make dysfunctional patterns modifiable. An additional benefit of ESM-I is that it does not require an additional investment of clinicians (Myin-germeys et al. 2011), and can be easily implemented in standard mental health care. ESM-I has emerged as a new viable approach in improving personalized mental health care, and it is going to become the most widely used mobile health tool in clinical practice (Wichers et al. 2011; Trull et al. 2009).

The experience sampling method has high ecological validity because assessments are made in real-time (Csikszentmihalyi et al. 2103; Shiffman et al. 2008). It avoids memory strains and aggregation because only the actual moment is constantly assessed over time; increases accuracy and is considerably easier to administer (Shiffman et al. 2008). The repeated assessments are collected in different contexts, which allows researchers to unravel and understand the variability in mental states and psychological constructs (Myin-Germeys et al. 2009).

The ecological momentary assessments usually cover a wide range of aspects such as mental state, mobility, quality of life, and social network in a single questionnaire. This reduces the need of separate questionnaires for every construct. As the same assessments are repeated over time, assessment error is almost negligible, and the sensitivity to detect change (Bolger et al. 2013) is also enhanced significantly. This, in turn, strengthens the validity, reliability, and transparency of the patterns of individual assessments (Stone et al. 2007)

Ecological momentary assessments make the patients empowered as they can relate the findings with their mental and psychological states more efficiently. These assessments actively indulge the patients making the treatment plan productive (Simons et al. 2105).

Limitations

The most concerning disadvantage of the experience sampling method is its time-consuming nature. Therefore, the assessments should be kept as brief as possible, ideally 1 to 2 minutes. Another limitation of ecological momentary assessment could be the veracity of the data because of the absence of a reliable independent check. However, the individual who is in constant touch with the patient can help identify the accuracy of the data (Tse et al. 2002)

The repeated(exclusive) assessments to negative mood states can invoke negative feelings. However, a balanced survey can diminish this limitation. For instance, by jumbling the sequence of items such that the positive and negative momentary mood questions are thoroughly assorted.

Module Integrations

Utilizing Qolty for Ecological Momentary assessments allows for integration with powerful tools exclusive to Qolty. Cadence intelligent multichannel delivery, Calor heat map tracking, and Corridor geofencing of your EMA assessments allows for entirely new possibilities, for a fraction of the price.

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