**Individual Abstract Number: 1419**

**A personalized stress fingerprint: Does knowing your stress barriers and facilitators improve your daily exercise bouts?**

Karina Davidson, PhD, Medicine and Psychiatry, Columbia University Medical Center, New York, New York, Sunmoo Yoon, PhD, School of Nursing, Columbia University, New York, New York, Joseph Schwartz, PhD, Psychiatry, Stony Brook University School of Medicine, Stony Brook, New York, Matthew Burg, PhD, Medicine and Anesthesiology, Yale University School of Medicine, New Haven, Connecticut, Ian Kronish, MD, MPH, Medicine, Columbia University Medical Center, New York, New York, Carmela Alcantara, PhD, Social Work, Columbia University, New York, New York, Julian Jacob, BA, Faith Parsons, MS, Beatrice Konrad, BA, Keith Diaz, PhD, Medicine, Columbia University Medical Center, New York, New York

**Purpose:** To test if individuals randomized to receive feedback regarding their person-specific "stress and physical activity fingerprint" – stress sources associated with low exercise – subsequently increase daily exercise.

**Method:** We enrolled a single cohort of 79 intermittently exercising, healthy adults. Observational data were collected for 360 days. Coupling ecological momentary assessment (EMA) with smartphone technology and actigraphy, we monitored daily exposure to psychosocial stressors in real time, in ecologically valid settings such as home and work. Each morning the participant responded to questions: 1) "How stressful do you expect today to be?" 2) "How likely are you to exercise today?" using a response scale of 0 (Not at all) to 10 (Extremely); these questions were asked in the past tense at night. Participants were prompted via text message 3 times during the day to answer questions about key sources of stress and stress appraisal, using the 4-item Perceived Stress Scale.

Physical activity was objectively monitored using a wrist-based model of the Fitbit®. If the subject exercised for one 30-minute period – defined as ≥24 out of any 30 consecutive mins of moderate or vigorous intensity activity or self-reported (EMA) exercising for 30 mins – the day was counted as an 'exercise day.'

At 180 days, we built a 'personalized stress and physical activity fingerprint', or N-of-1 observational model of stress perception and exercise. Of the 73 remaining in the study, 39 randomly-assigned participants received their stress fingerprint, and 34 did not. We obtained physical activity data and EMA as above for the subsequent 180 days.

**Results:** Mean age of participants was 32.4 ± 10.1, 41.1% were male and 26.1% were Hispanic; no demographic differences were noted between groups. A multilevel generalized linear model provided estimates of mean % days exercised by group and period (3 months pre- vs 3 months post-fingerprint). The % days exercised decreased from 43% to 32% in the control group (p<0.001) and from 44% to 40% among those receiving the fingerprint (p=ns); the differential decline of 7% between groups was statistically significant (p<0.05).

**Conclusions:** A stress and physical activity fingerprint conveying personalized factors that predispose one to exercise on a given day had a prophylactic effect on the maintenance of exercise behavior over 6 months.

**Symposium 1428**

**Thursday, March 16 from 5:00 - 6:00 pm**

**Health-Relevant Social Environment Sampling Techniques**

Megan L. Robbins, PhD, Psychology, University of California, Riverside, Riverside, CA, Megan L. Robbins, PhD, Psychology, University of California, Riverside, Riverside, CA, Robert C. Wright, MA, Psychology, University of California, Riverside, Riverside, CA, Peggy M. Zoccola, PhD, Psychology, Ohio University, Athens, OH, Joshua M. Smyth, PhD, Biobehavioral Health and Medicine, The Pennsylvania State University, University Park, PA

Psychosomatic research has historically relied on retrospective accounts and observation of in-lab behavior for measurement of psychosocial processes. However, technology has provided psychology researchers with an exciting set of methodological tools to assess psychosocial processes in daily life. Social environment sampling techniques enable in-the-moment data collection, facilitating a more comprehensive understanding of psychosocial processes than was previously possible. The use of three social environment sampling techniques will be described, using empirical data as examples to give an overview of how such techniques can be used in psychosomatic research. The first two methods gather psychosocial information from the observer's perspective. The first method is the Electronically Activated Recorder (EAR), a device participants wear on their waistline that records snippets of ambient sound. The EAR can be used for measuring psychosocial variables as predictors of psychological adjustment to serious illness such as breast cancer, or as an outcome measure for assessing changes to daily life following intervention, such as an alternative treatment for major depressive disorder. The second method utilizes publicly available online social network (OSN) data to track how patients discuss illness-related information and navigate the coping context. For example, linguistic differences observed in the types of language used in OSN posts about pain versus general topics may indicate meaning-making about the pain experience. This talk will discuss the potential to use such data to predict health behavior and adjustment outcomes by linking it to clinical data. Finally, the third social environment sampling technique yields social environment information via the participants' perspective. Ecological Momentary Assessment (EMA) can be used to assess psychological states and social factors in-the-moment. The presentation will demonstrate the utility of EMA to examine within-day patterns of emotion and salivary cortisol as a function of trait rumination. All three talks highlight advancements technology has made to directly measure psychosocial factors in real time. Thus, social environment sampling brings measurement of health-relevant psychosocial processes where they naturally occur—in the context of everyday life.

**Individual Abstract Number: 1430**

**The EAR as a Naturalistic Observation Measure of Patients' Social Behavior**

Megan L. Robbins, PhD, Psychology, University of California, Riverside, Riverside, CA, Charles Raison, MD, Psychiatry, University of Wisconsin-Madison, Madison, WI, Matthias R. Mehl, PhD, Psychology, University of Arizona, Tucson, AZ

The Electronically Activated Recorder (EAR) is a naturalistic observation tool for sampling audible aspects of social environments and behavior. It periodically records snippets of ambient sounds, adding the observer's perspective to psychosocial assessments in cross-sectional, longitudinal, and experimental health-related research. Two studies highlight the use of the EAR in patient samples. The first study investigated 52 couples coping with breast cancer, who wore the EAR over one weekend while the patient was on active treatment. Using a sampling rate of 50 s every 9 min, we found that 4.3% (SD=5.6) of their conversations were about cancer, and that spouses' engagement in substantive conversations about cancer with patients was associated with patients' improved adjustment over a two-month period. The data also revealed what topics did come up most frequently in everyday life while couples coped: work (M=10.6%, SD=6.0), leisure (M=9.1%, SD=5.2), eating (M=8.2%, SD=4.0), body (M=6.8%, SD=4.0), home (M=6.7%, SD=4.2), and money (M=6.4%, SD=4.6). Beyond understanding the landscape of everyday conversations while coping, the EAR can also be used as a behavioral outcome measure for experimental tests of medical and well-being interventions. A preliminary, randomized controlled trial of whole body hyperthermia (WBH; heating the body with infrared lights to 101.3°F degrees) as a treatment for major depressive disorder revealed a substantial effect on depression among those in the treatment group (n=14), relative to controls (n=9). Self-reports and interviews to assess
depression are certainly the gold standard for assessing treatment efficacy; however, corroboration with behavioral measures of quality of life elucidate the effect of treatment on patients' everyday life. Participants in the WBH condition spent significantly less time alone than those in the control condition following treatment, F(1,22)=6.63, p=.02, η²=.25. They also spent marginally more time emotionally disclosing to others, F(1,22)=3.91, p=.06, η²=.16, suggesting a general effect of WBH on the social lives of patients with major depressive disorder. In summary, the EAR adds assessment of psychosocial factors without reliance on participants' recollections and biases inherent in self-reports. It can be used for objective assessment of social behavior relevant to psychosomatic research.

**Individual Abstract Number: 1431**

**Using Online Social Network Data to Investigate Pain Experiences**

Robert C. Wright, MA, Psychology, Ryan Rivas, BA, Vagelis Hristidis, PhD, Computer Science, Megan L. Robbins, PhD, Psychology, University of California, Riverside, Riverside, CA

Patients are increasingly turning to illness-specific online social networks (OSNs) for support and information. For researchers, these public forums offer a glimpse into naturally-occurring interactions which are implicated in downstream health outcomes. Past research has shown word use predicts important health outcomes; therefore, this study sought to expand on past research by identifying meaningful differences in natural pain discussions on OSN platforms. A validated pain-specific Linguistic Inquiry and Word Count (LIWC) dictionary was used to identify pain-related posts from three illness-related OSNs—fibromyalgia (n=343,439), rheumatoid arthritis (n=12,430), and breast cancer (n=2525). LIWC is text-analysis software that calculates the proportion of words that fall into various dictionaries. As predicted, pain was a major topic mentioned on all three sites (M<sub>posts</sub>=62.18%; 99% CI [61.97, 62.39]). In pain versus non-pain posts, there was a higher proportion of first-person personal pronouns (e.g. “I had to learn to ask for and accept help”), t(215125) = -60.783, p < 0.001, d = .262. There was also a higher proportion of cognitive processing words (e.g. “I decided that something had to be done”), t(197106) = -67.748, p < 0.001, d = .305. Conversely, in pain versus non-pain posts there were fewer social related words (e.g. “he’s a friend of a friend AND he has a sister with fibro”), t(186403) = 91.894, p < 0.001, d = .426; and fewer positive emotion words (e.g. “Can’t get much **better** than that”), t(156653) = 129.837, p < 0.001, d = .660. Taken together, the linguistic differences observed in the types of language used in pain versus non-pain posts may indicate meaning-making about the pain experience, as evidenced by higher proportions of self-focused and cognitive processing words. Notably, this study utilized a natural form of patient-to-patient communication which allows users to freely discuss their conditions without researcher interference. These massive data can provide insight into evolving support networks, such as tracking patient coping and support interactions over time. Ultimately, pairing clinical and OSN data will allow researchers to gain insight into factors contributing to coping outcomes. OSN data provides researchers with a cheap, noninvasive way to monitor patient behavior outside the clinic for psychosomatic research.

**Individual Abstract Number: 1429**

**Using Ecological Momentary Assessment to Examine Gender Differences in Trait Rumination, Momentary Distress, and Diurnal Cortisol in Daily Life**

Peggy M. Zoccola, PhD, Psychology, Ohio University, Athens, OH, Sally Dickerson, PhD, Office of Sponsored Research, Pace University, New York City, NY, Matthew Zawadzki, PhD, Psychology, University of California, Merced, Merced, CA, Katrina Hamilton, BA, Psychology, Ohio University, Athens, OH

There is accumulating evidence that ruminating on stressors can prolong stress-related physiological activation, including salivary

cortisol. However, prior work from our group and others indicates that the rumination-related physiological activation may differ for men and women. For example, following a laboratory speech stressor, women with greater rumination tendencies have had flatter cortisol slopes and higher evening cortisol compared to men. In the current study, we tested whether these gender-specific rumination-cortisol patterns are present in daily life, and whether gender differences in diurnal momentary distress may shed light on divergent rumination-cortisol profiles for men and women.

We invited 124 healthy young adults 18–36 years of age (56% women) to complete a laboratory speech stressor and 5 consecutive days of ecological momentary assessment (EMA) of mood and salivary cortisol. For the EMA component, participants rated their current emotions and provided saliva samples each day at the following times: at wake, 12:00 PM, 2:00 PM, 4:00 PM, 6:00 PM, and 8:00 PM. Trait rumination was assessed during the initial laboratory visit. Multilevel linear models were used to identify diurnal patterns of cortisol concentrations and distress.

Although men and women did not differ in ruminative tendencies, trait rumination predicted flatter diurnal cortisol slopes for women compared to men across the 5 days of observation, consistent with our prior work, F(1,2502) = 5.86, p = .016. EMA of momentary distress showed that, similar to the diurnal cortisol findings, trait rumination interacted with gender and time to predict distress, F(1,2213) = 4.51, p = .034. For women, higher trait rumination scores predicted increasing distress throughout the day. Trait rumination did not predict diurnal change in distress for men. Results remained significant in the presence of potential confounding variables, including depressed mood. Results support past work that trait rumination predicts different cortisol response patterns for men and women. Our findings also highlight the utility of using EMA to examine within-day patterns of emotion and salivary cortisol as a function of trait rumination. EMA helps us to better understand social contextual factors in physiological activation by revealing within-day changes in distress that co-occur with changes in cortisol.

## How to Cite your Abstract

The May 2017 (volume 79, number 4) on-line issue of *Psychosomatic Medicine* contains the 2017 meeting abstracts.

The on-line journal is *Psychosomatic Medicine's* journal of record for indexing purposes. To cite a meeting abstract in one's vita, use Volume 79, Number 4 and the page number in which your abstract appears. Note each page number appears with the letter A in front of the page number.