PHILIP ZIMBARDO, PH.D., SARAH BRUNSKILL, M.A. & ANTHONY FERRERAS, M.S. Social Intensity Syndrome Theory: Looking at the Military as a Subculture PHILIP ZIMBARDO, PH.D., SARAH BRUNSKILL, M.A. & ANTHONY FERRERAS, M.S.

Background Past studies The social environment has powerful effects on individual behaviors and can often change the way they normally behave E.g., Milgram Study, Stanford Prison Study Each of the experiments, however, produced only temporary changes in participants’ attitudes and behaviors. What about real life? Obviously, the social situation in which people find themselves in is a powerful influence on their behaviors, attitudes, and perceptions

Social Experiments in Real Life Real life situations are created and structured to produce long lasting effects in people who participate. Religious cults Military Religious cults - adopt more intense and long-term versions of the principles used in social experiments to change new members’ attitudes, values, and behaviors to create life members devout to the organization’s views and cause Military - . Serving in the military involves a much longer term exposure to situations that are much more intense than the experiments mentioned above, and must reach beyond the changes in job-related behaviors in civilian organizations; the military must replace much of what their recruits learned since very early life. The intensity is greater because every aspect of recruits’ and servicemen’s lives is controlled and manipulated to socialize them to adopt attitudes and bring about new behaviors (Dyer, 1985)

Why? The present study failed to find literature analyzing the effects of the intense, long-term socialization that happens in the military on Veterans’ lives beyond their service The purpose Introduce a new theoretical concept that describes this social phenomenon, Explore its assumptions about intense and long-term effects of military socialization. The composite of causes and effects related to long-term military socialization is new to academia and is referred to here as Social Intensity Syndrome (SIS).

What is SIS? Social Intensity Syndrome (SIS) – Is the descriptive term for the complex of values, attitudes, and behaviors organized around personal attraction to and desire to maintain association with Male dominated social groupings.

WHERE DID THE IDEA COME FROM? REPORTS OF SPOUSE AND FAMILY ABUSE AMONG RETURNING VETS FROM OVERSEAS HIGH RATES OF REDEPLOYMENT AMONG IRAQ VETS BACK TO CONFLICT ZONES. SOME VETS HAVE REDEPLOYED 4 AND 5 TIMES! WHY?

WHERE ELSE DID THE IDEA COME FROM? My Fair Lady, Rex Harrison singing WHY CAN’T A WOMAN BE MORE LIKE A MAN?

Conceptual Assumptions Men, are attracted to social settings that involve the presence of a group of other men That attraction is greater when: The more intense the nature of the relationship The more exclusive it is of tolerating “outsiders” or those who have not qualified for that group membership The more embedded each man is perceived to be within that group E.g., the military, deployment, gangs, contact team sports, fraternities, prisons, some cults, and bars/ pubs. Examples of such social groups are the military, especially during boot camp and deployment, gangs, contact team sports, fraternities, prisons, some cults, and bars.

Conceptual Assumptions Men experience a positive arousal, when they feel they are part of such an all MALE social group. Cortisol, Adrenergic system activation, or testosterone increase Men adapt to that level of social intensity contact as an optimally desired personal and social state. Over time, that degree of social intensity becomes a “set point” of desirable functioning, operating at a non-conscious level.

Conceptual Assumptions When separated from such socially intense group settings, men experience a sense of … Isolation and then boredom Withdrawal symptoms Which are greater the longer the prior duration of their group participation

Behavioral Predictions Those with high levels of SIS will do some or all of the following: Respond to the negative affect of disengagement from such groups by engaging in: Arousing activities (e.g., such as high risk ventures, daring deeds, getting into arguments and fights, drinking to excess, gambling, motorcycling, and similarly intense actions.) Choose Male group activities over smaller pairings of one or a few other men. (homo-avoidance) Choose all men groupings over mixed gender ones.

Behavioral Predictions Feel less comfortable in the presence of women as “friends.” Women/spouse less trusted than men. Spend more time in symbolic male groups, E.g., watching sports in a sports bar, fantasy football or baseball competitions. Report high levels of boredom after separating from the socially intense grouping. Recall greater positive and fewer negative aspects of one’s time in that group. Deal with the arousal deficit by seeking redeployment if in the military.

Behavioral Predictions Deal with the arousal deficit by Hanging around settings where there are likely to be other men who also belong to such high intensity groupings E.g., VA hospital lobbies, sports team “fanatics”, etc. More likely to engage in Spousal abuse Divorced or separate from mates More likely to experience Alcoholism, Drug addiction, Commit crimes, Suffer higher levels of PTSD They are also more likely to engage in spousal abuse and divorced or separate from mates with whom they had a positive relationship prior to deployment or team membership.

Behavioral Predictions Men who are paroled from prison may engage in crimes in which they are more likely to get caught non-conscious attempt to return to the socially intense prison atmosphere. Develop generally negative attitudes toward women as “the other” who do not understand them, prefer pornography and sex with prostitutes over consensual sexual relationships with equal status female mates.

Transitioning from Active to Inactive The change is typically abrupt and without proper training for dealing with their now “new other” life. Military personnel leave the culture and enter another for which they have little or no training to deal with as independent, socially responsible civilian adults Find it difficult to relate to civilians Find that ordinary life is boring, tedious, non challenging Begin to social isolate themselves Begin to feel inadequate, incompetent AND NO ONE IS AWARE OF THE SIS TRAP AT WORK! these young adults were socialized to deal with child and adolescent issues, and combat situations, but never to deal with adult civilian responsibilities and independent functioning; they skipped this important life training and transition.

Lyrics from My Fair Lady: Reprise lamenting the failure of women to be men Why can't a woman be more like a man? Men are so honest, so thoroughly square; Eternally noble, historically fair. Who, when you win, will always give your back a pat. Why can't a woman be like that? Why does every one do what the others do? Can't a woman learn to use her head? Why do they do everything their mothers do? Why don't they grow up, well, like their father instead?

Women would be more loved if they were MEN Why can't a woman take after a man? Men are so pleasant, so easy to please. Whenever you're with them, you're always at ease. But by and large we are a marvelous sex! Why can't a woman take after a man? 'Cause men are so friendly, good-natured and kind. A better companion you never will find. Why can't a woman be more like a man? Men are so decent, such regular chaps; Ready to help you through any mishaps; Ready to buck you up whenever you're glum. Why can't a woman be a chum? Why can't a woman be like me?

Creating a New SIS Survey SARAH R. BRUNSKILL, M.A.

Item writing and selection 150 preliminary items were created Interviews with Veterans, military family members and clinicians Literature reviews Received consultation from Veterans and active military personnel The criterion for item retention Alignment with the theoretical assumptions Appropriateness Wording Relevancy Using the theoretical assumptions developed by Dr. Zimbardo, 150 preliminary items for potential selection received consultation from veterans and active military personnel to ensure appropriateness of item topics and wording. After receiving consultation, researcher selected items based on alignment with the theoretical assumptions, appropriateness, wording, relevancy.

Measures 1oo exploratory items Used a 1 to 5 Likert type scale Length Intended to measure the various conceptual aspects of SIS. Higher scores on this scale reflect/endorsed SIS Used a 1 to 5 Likert type scale “Disagree Strongly” to “Agree Strongly” Length Approximately 30 minutes 2 items needed to be reverse coded Demographic questions helped determine whether they were active/inactive deployed/nondeployed Used a 1 to 5 Likert type scale “Disagree Strongly” to “Agree Strongly” to indicate their level of agreement to each statement Time About 30 min

Sample Question

Procedure A group of 5 undergraduates and 1 PI contacted both active and inactive military personnel through… Websites, Social media, Personal contacts, Military lists, Veteran services, Senior centers, Education facilities, Interest groups, est.

Recruitment Snowball Method friends, family, other acquaintances or individuals lists on public websites as the contact person for a military group contacts asked to forward the letter to their military network recipients were asked to forward the letter to others We know from previous experience that this a very hard group to break into this group due to their general distrust for research and psychology. Through using the snowball methods to recruit participants we were able to... finding champions within the military, we were able to break into the culture access people we otherwise would not be able to. First, a recruitment letter was emailed and physically handed out to friends, family and other acquaintances who are inactive and active military personnel. Second, the recruitment letter was distributed to acquaintances with military contacts asked to forward the letter to their military network. Finally, recruitment letter recipients were asked to forward the letter to others. Reportedly, this method even reached several military/veteran organizations.

Participants N (survey hits) 618 (100%) n (completed surveys) 346 (56.0%) Female 11 (3.2%) Male 335 (96.8%) Missing items Eligible surveys for analysis 324 (52.4%) 618 – people went to the first page 346 – completed the survey 324 (52.4%) – of the surveys were eligible for analysis Better than chance Qualifications for survey- Male over 18 take survey online read English currently serving or have served in US military

Participant Demographics Age 18 to 24 16 (5.0%) 25 to 35 57 (17.8%) 26 to 45 55 (17.2%) 46 to 55 52 (16.3%) 56 to 65 70 (21.9%) 66 to 75 35 (10.9%) 76 and above Ethnicity African American 7 (2.2%) Asian/Pacific Islander 46 (14.2%) Caucasian 241 (74.6%) Hispanic/Latino 19 (5.9%) Other 10 (3.1%) A good distribution amongst the age groups. We need to get more 18-24 Ethnicity – need to get a more diverse sample Currently working on these things by focusing on these groups

Military Demographics n (n = 324) 2010 Military Census Military Branch Air Force 92 (28.5%) 24.1% Army 139 (43.0%) 39.8% Coast Guard 5 (1.5%) 2.3% Marine Corp 36 (11.1%) 10.2% Navy 51 (15.8%) 23.5% Category Active/Not Deployed 17 (5.2%) Active/Deployed 88 (27.2%) Inactive/Not Deployed 45 (13.9%) Inactive/Deployed 174 (53.7%) We are still working to create a better distribution amongst military branches; however, we found that it falls very close to the military's own distribution Deployment defined and asked by asking if the participant had been deployed to a “combat/conflict zone” were asked to select 0-5+ Finally, we have identified four groups to that should express varying levels of SIS: Active/Non-deployed – Current servicemen who have not been deployed Active/Deployed – Current servicemen who have experienced combat Inactive/Non-deployed – Veterans who were never deployed Inactive/Deployed – Veterans who have experienced combat

Predicted Ranking of SIS Higher SIS Lower SIS Active/Non-deployed Active/Deployed Inactive/Deployed Inactive/Non-deployed Active/Non-deployed, individuals should express the lowest levels of SIS and its characteristics, they are still actively involved in the military have not experienced the socially intense situations that those who have been deployed have. Active/Deployed, still immersed in the intense social environment providing the social support have immediate access to those who have also been deployed. Inactive/Non-deployed, this groups have been separated from the social support with which they are most comfortable. Inactive/Deployed respondents should express the highest levels of SIS they have been separated from constant access of the military culture and those who share the same intense experiences

Data Screening Data was screened for outliers Minimum amount of data for analysis Not satisfied Need an estimated >500 cases Exploratory preliminary factor analysis Current N = 324 ~3 cases per variable Data was screened for univariate outliers no out of range outliers were found This is a preliminary analysis, welcome suggestions ~3 cases per variable aiming for a minimum of 5

Assumption Testing Factorability Kaiser-Meyer-Olkin Bartlett’s test of sphericity Anti-image correlation matrix Communalities Factorability 100 of the 100 items correlated at least .3 suggesting reasonable factorability Kaiser-Meyer-Olkin measure of sampling adequacy was above the recommend value of .6. being .919 we were confident that a factor analysis was appropriate Bartlett’s test of sphericity was significant diagonals of the anti-image correlation matrix all over .5, supporting the inclusion of each item in the factor analysis. communalities all above .3 Given these overall indicators, an exploratory factor analysis was conducted with all 100 items.

Variance Explained Principle components analysis was used the primary purpose was to identify compute scores for the factors underlying in SIS 19 were observed with an eigen value over 1.0

Scree Plot While 19 variables were observe, the scree plot suggests an estimated 3-6 factor loadings before leveling off Three, four, five and six factor solutions were examined, using both varimax and oblimin rotations of the factor loading matrix.

Variance Explained With 3 Factors The three factor solution, which explained 39.65% of the variance, was preferred because of its previous theoretical support, the ‘leveling off’ of eigen values on the scree plot after three factors, and the insufficient number of primary loadings and difficulty of interpreting the fourth factor and subsequent factors. There was little difference between the varimax and oblimin solutions, thus both solutions were examined in the subsequent analyses before deciding on an varimax rotation for the final solution.

Example of Items Eliminated Question Reason 1 I feel my best when with my MILITARY friends. Cross-loading on factors 1 and 2 Since being deployed, I am more interested in connecting with my MILITARY friends. The guys I was close to in my unit probably understand me better than anyone else currently in my life. I prefer to be around people most of the time. Cross-loading on factors 1 and 3 I enjoy playing extreme sports (e.g., skydiving, cliff diving, motorsports, etc.). Did not have a high enough factor loading During several steps, a total of 50 items were eliminated because they did not contribute to a simple factor structure failed to meet a minimum criteria of having a primary factor loading of .4 or above, no cross-loading of .3 or above.

Final Factor Analysis: Assumption Testing Factorability Kaiser-Meyer-Olkin Bartlett’s test of sphericity Anti-image correlation matrix Communalities factorability 50 of the 50 items correlated at least .3 suggesting reasonable Kaiser-Meyer-Olkin measure of sampling adequacy was above the recommend value of .6. being a .908 Bartlett’s test of sphericity significant diagonals of the anti-image correlation matrix all over .5, supporting the inclusion of each item in the factor analysis. communalities all above .3 Given these overall indicators, a factor analysis was conducted with all 50 items.

Final Factor Analysis: Variance Explained A principle-components factor analysis of the remaining 50 items, the three factors explaining 45.1% of the variance which increased from the original 3 factor solution (39%) An Varimax provided the best defined factor structure. All items had primary loadings over .4 and no cross-loading items

Reliability Analyses: Factor 1 Title/theme – Trust Number of items = 29 a = .954 Example Questions Factor Loading It is easier to trust my MILITARY friends than my significant other .779 It is hard for me to trust women .742 I wish my significant other was more like my best MILITARY friends .714 I distance myself from my NON-MILITARY friends .633 I distance myself from my SIGNIFICANT OTHER .621 I feel like my family gets in the way of hanging out with my MILITARY friends .491 Internal consistency for each of the scales was examined using Cronbach’s alpha. The alphas was HIGH for family (Excellent range) No substantial increases in alpha for any of the scales could have been achieved by eliminating more items.

Reliability Analyses: Factor 2 Title/theme – Nostalgia N = 12 a = .835 Example Questions Factor Loading I want to reenlist because I miss the excitement .780 I enjoyed being in the military .709 I wanted to redeploy because I missed the people .708 I have more good memories with my MILITARY friends than bad .628 There is a level of excitement that I felt just being part of that unit on a day-to-day basis .568 Internal consistency for each of the scales was examined using Cronbach’s alpha. The alphas was GOOD for Deployment (good range) If item “I feel down when I am with my MILITARY friends” is deleted raise alpha to .870

Reliability Analyses: Factor 3 Title/theme – Social Bonding N = 9 a = .837 Example Questions Factor Loading I often feel the need to be around others .836 I often feel an intense need to be around people .787 I feel lonely when friends are too busy to hangout .655 I do NOT like being alone .600 I would rather hangout with a group rather than hangout with just one friend .556 Internal consistency for each of the scales was examined using Cronbach’s alpha. The alphas was GOOD for Deployment (good range) If item “When I am out, I talk to anyone around me” is deleted raise alpha to .849  

Descriptive statistics for all 3 factors No. of items Mean (SD) Skewness Kurtosis Alpha Factor 1 (Trust) 29 2.37 (.95) .48 -.68 .95 Factor 2 (Nostalgia) 12 3.43 (.74) -.30 -.50 .84 Factor 3 (Social Bonding) 9 2.59 (.81) .27 -.41 Composite scores were created for each of the three factors, based on the mean of the items which had their primary loadings on each factor. Factor 1 (Trust) displayed a slight positive skewed distribution, Factor 2 (Nostalgia) displayed a slight negatively skewed distribution, Factor 3 (Social Bonding) displayed a slight positive to normal distribution

Descriptive Statistics by Military Category n Factor 1 (Trust) Factor 2 (Nostalgia) Factor 3 (Social Bonding) Overall SIS Mean (SD) Active/ Not Deployed 17 1.88 (.72) 3.71 (.65) 2.76 (.77) 2.78 (.42) Active/ Deployed 88 2.13 (.81) 3.34 (.66) 2.70 (.74) 2.72 (.50) Inactive/ 45 2.02 (.68) 3.43 (.68) 2.28 (.70) 2.57 (.48) Inactive/ Deployed 174 2.64 (1.02) 3.46 (.80) 2.60 (.86) 2.90 (.65) Higher reports of SIS falls in line with the theory Lower reports of SIS is closer to civilian

Descriptive Statistics by Military Category n Factor 1 (Trust) Factor 2 (Nostalgia) Factor 3 (Social Bonding) Overall SIS Mean (SD) Active/ Not Deployed 17 1.88 (.72) 3.71 (.65) 2.76 (.77) 2.78 (.42) Active/ Deployed 88 2.13 (.81) 3.34 (.66) 2.70 (.74) 2.72 (.50)* Inactive/ 45 2.02 (.68) 3.43 (.68) 2.28 (.70) 2.57 (.48) Inactive/ Deployed 174 2.64 (1.02) 3.46 (.80) 2.60 (.86) 2.90 (.65)* Active Deployed vs Inactive/Deployed SIG DIFFERENCE (P = .016) Inactive/ Not Deployed vs Inactive/Deployed SIG DIFFERENCE (P = .002) No Sig Difference Active/Not Deployed vs Active Depolyed Active/Not Deployed vs Inactive/ Not Deployed Active/Not Deployed vs Inactive/Deployed Active Deployed vs Inactive/ Not Deployed *p = .016

Descriptive Statistics by Military Category n Factor 1 (Trust) Factor 2 (Nostalgia) Factor 3 (Social Bonding) Overall SIS Mean (SD) Active/ Not Deployed 17 1.88 (.72) 3.71 (.65) 2.76 (.77) 2.78 (.42) Active/ Deployed 88 2.13 (.81) 3.34 (.66) 2.70 (.74) 2.72 (.50) Inactive/ 45 2.02 (.68) 3.43 (.68) 2.28 (.70) 2.57 (.48)* Inactive/ Deployed 174 2.64 (1.02) 3.46 (.80) 2.60 (.86) 2.90 (.65)* Higher reports of SIS falls in line with the theory Lower reports of SIS is closer to civilian Active Deployed vs Inactive/Deployed SIG DIFFERENCE (P = .016) Inactive/ Not Deployed vs Inactive/Deployed SIG DIFFERENCE (P = .002) No Sig Difference Active/Not Deployed vs Active Depolyed Active/Not Deployed vs Inactive/ Not Deployed Active/Not Deployed vs Inactive/Deployed Active Deployed vs Inactive/ Not Deployed *p = .002

Ranking of SIS Predicted Ranking Actual Ranking Higher SIS Higher SIS Lower SIS Active/Non-deployed Active/Deployed Inactive/Deployed Inactive/Non-deployed Higher SIS Lower SIS Active/Non-deployed Active/Deployed Inactive/Deployed Inactive/Non-deployed Inactive/Non-deployed, lowest reports of SIS, have an easier time going back into civilian life after leaving the military. This appears to be related to them not being deployed. Active/Deployed, 2nd lowest reported SIS. still immersed in the intense social environment providing the social support system immediate access to those who have also been deployed and the life or death experiences. Active/Non-deployed, 2nd highest reports of SIS. This is our younger group (18-24), this is their identity they most likely have been wanting to be apart of this culture for a long time. Inactive/Deployed highest reports of SIS. they have been separated from constant access of the military culture those who share the same intense experiences of being deployed.

Ranking of SIS Predicted Ranking Actual Ranking Higher SIS Higher SIS Lower SIS Active/Non-deployed Active/Deployed Inactive/Deployed Inactive/Non-deployed Higher SIS Lower SIS Active/Non-deployed Active/Deployed Inactive/Deployed Inactive/Non-deployed Interestingly, what we also found is a predictive model. Once the military status changed, the reports of SIS change. If you were deployed  higher SIS If you were not deployed  lower SIS HOW CAN WE USE THIS Prior to exiting the military, de-escalation/ civilian integration training needs to happen clinicians can help prepare active/deployed service members prior to being discharged, to help lessen some of the negative aspects of having higher reports of SIS once they become inactive Social integration Helping the spouses Education to support the sig other Prevent misunderstand Help family unit

Conclusions 3 distinct factors Trust Nostalgia Social Bonding Internally consistent Saw directional trends of SIS and how it affects certain groups Support for the foundational theory of SIS Next steps Write a theory paper Standardizing survey and publish Disseminating information to clinicians and Veterans Affairs Overall, these analyses indicated that three distinct factors were that these factors were moderately internally consistent. Primary

Questions Contact info Sarah Brunskill – sbrunskill@gmail.com If you know anyone who is serving or has served in the military, and think they might participate, please let us know.