UWW Presentation

1. COMMUNITY
CONNECTEDNESS
AND CLEAVAGES
INTERSECTIONS WITH HEALTH & HEALTH PROMOTION
KIFFER G. CARD

2. OBJECTIVESParticipants will be able to
+ describe the importance of “community connectedness” for individual and
population health;
+ understand how observational data can be used to identify communities
and heterogeneity within them; and
+ generate strategies for studying communities and implementing health
interventions among them.
+

3. WHAT IS
COMMUNITY?
+

4. Tonnies
Durkheim
Gemeinschaft
Based on feelings of
togetherness and
bonding between
members.
Gesellschaft
Based on reliance on one
another and ability to
leverage relationships for
personal gain.
Mechanical
Solidarity
Cohesion comes
from connection and
homogeneity
Organic
Solidarity
Cohesion comes from
interdependence on one
another
Collectivism Individualism
Community Society
What is
community?

5. Group
Isolates
Recognizes Authority
Values Personal
Freedom
Accepts Risk
Collectivists
Recognizes Authority
Values Solidarity
Avoids Risk
Individualists
Disregards Authority
Values Personal
Freedom
Manages Risk
Dissenters
Disregards Authority
Values Solidarity
Embraces Risk
Grid
What is
community?
Low Cohesion High Cohesion
HierarchicalEgalitarian

6. Speech
Codes
“Speech and thought have
been elaborated as
specialized tools for decision-
making, but the social
structure still retains a strong
grip on its members, even to
the extent that its underlying
assumptions are not
challenged.”
“Speech forms are firmly
embedded in a stable social
structure. The primary use of
language is to affirm and
embellish the social structure
which rests upon
unchallengeable
metaphysical assumptions.”
“Here are the people
who live using
elaborated speech to
review and revise
existing categories of
thought. To challenge
received ideas.”
“The social structure
has lost its grip...is
unstable, a transitional
phase…the individual is
valued above the social
structure.”
Family
Control
Elaborated Restricted
PositionalPersonal
Where do
these sort of
cultural
categories
come from?

7. Union Membership
Associations Membership
Social Trust
1960-2000
What
happened
starting in
the 1950’s
and
1960’s?

8. WHAT IS DRIVING
THESE TRENDS?
+

9. Individualism Index
Urbanization
Income Inequality
Rising
Urbanization
Rising Income
Inequality
Rising
Individualism

10. “ This new world of networked individualism
is oriented around looser, more fragmented
networks that provide on-demand succor.
Such networks had already formed before the
coming of the internet. Still, the revolutionary
social change from small groups to broader
personal networks has been powerfully
advanced by the widespread use of the
internet and mobile phones.
Barry Wellman
Sociologist, University of Toronto

11. Rosser et al. (2008) “Are communities dying or in transition?”
Heterosexuals are integrating into gay neighborhoods, gay venues are disappearing, gay event
attendance is decreasing, volunteerism at gay organizations is in decline, visibility of gay
communities is increasing.
Rowe & Dowsett (2008) “Role for gay community in prevention?”
The ethos of safe sex which once bound the community is gone. Subcultures, intertwined in risk,
and ambivalence about the gay community has emerged as a new normal for gay communities.
Holt (2011) “Gay men and ambivalence about ‘gay community.’
The concept of 'personal communities' may better reflect the ways in which gay men engage
with each other and their social networks.
Zablotska et al. (2012) “Gay men’s participation in community life”
The proportion of men who socialized mainly with gay men declined and the Internet use to
connect with sex partners increased over time. Gay social engagement was associated with HIV
positive serostatus, unprotected anal intercourse with regular partners and a high frequency of
HIV/STI testing.
Kelly et al. (2013) “Exploring the gay community question.”
Experiences of gay community are shaped principally by network relations rather than residential
proximity to gay institutions,
Community Decline
Researchers
are
increasingly
concerned
about gay
men’s
community
involvement

12. PLACE|SPACE
+
Analysis
• Multivariable Linear Regression Analysis
with logged outcome variable and robust
standard errors to account for
heteroscedasticity
Variables
• App-User Density
• 2014 Census & National Household
Survey Data
Sampling
• Grid of Sampling Points across the
area
• Count number of Grindr profiles
within 1 mile.

13. What’s
happening
to gay
spaces?

14. Population
density
only
partially
explains
trends in
app-user
density.

15. West End
Strathcona &
Mt. Pleasant
0
5000
10000
15000
20000
25000
30000
0 50 100 150 200
AverageDisseminationAreaPopulation
Density
1-mile Sampling Area App User Density
App User
Density by
Population
Density

16. Number of
Momentum
Health Study
Participants

17. 5km Clinic
Coverage by
App User
Density

18. Factors
associated
with
app-user
density.

19. VIRTUAL SPACES
+
Analysis
• Multivariable Linear Regression Analysis
with logged outcome variable and robust
standard errors to account for
heteroscedasticity
Variables
• App-User Density
• 2014 Census & National Household
Survey Data
Sampling
• Grid of Sampling Points across the
area
• Count number of Grindr profiles
within 1 mile.

20. Community
Based
Organizations
ID
Description of
Organization
Months of
Observation
Number of
“Facebook Fans”
Number of
Posts Shared by
Organization
Number of
Engagements
1 AIDS Service Organization 78 1,168 1,458 1,281
2a Gay Men’s Research
Organization
47 422 578 262
2b Anti-Stigma Social Media
Campaign*
10 1,126 242 524
3 AIDS Fundraising
Organization
79 1,578 699 1,385
4 Gay Men’s Health
Organization
80 2,290 2,166 3,184
5 LGBT2SQ Pride
Organization
74 8,813 1,791 7,405
6 AIDS Service Organization 65 1,015 1,921 675
7 Queer Community
Organization
80 5,571 3,607 9,351
8a Youth-led Health
Organization
74 1,097 758 824
8b Peer-led Program for
Young GBT2SQ*
54 716 851 598
Median (Q1, Q3) 74 (57, 79) 1,147 (1,036, 2,112) 1,155 (714, 1,889) 1,053 (617, 2,734)
Total 639.55 23,796 14,071 25,489

21. Engagements
with CBO
content

22. B SE IRR p
Health Message
PreP 1.29 0.12 3.64 <.0001
Stigma 0.47 0.08 1.60 <.0001
Mental Health 0.42 0.11 1.52 <.0001
Treatment 0.16 0.1 1.17 0.10
Testing 0.14 0.07 1.15 0.06
Research 0.01 0.08 1.01 0.90
Condoms -0.06 0.1 0.94 0.55
Dating -0.33 0.09 0.72 <.001
Predictors
of
Post
Engagement

23. INVOLVEMENT
+
Analysis
• Trends
• Latent Class Analysis
Variables
• Residence
• Collectivism
• Participation
Sampling
• Respondent Driven Sampling
• Sexually Active GBM, >16 Years

24. Respondent
Driven
Sampling
In EquilibriumOut of Equilibrium

25. 719 participants recruited; 119 (16.6%) were seeds
COLOUR: white = HIV-negative; black = HIV-positive; grey = unknown
SHAPE: circle = 16-24 years; square = 25-39 years, triangle = 40+ years
RDS Chains
in
Momentum
Health Study

26. Progress in
Recruitment
0
50
100
150
200
250
300
350
400
Participants Recruited Seeds
Feb 2012 Feb 2013
119

27. Recruitment
of Cohort
Gay-identified: 79.9% (n=655)
Ever had an HIV test: 92.2% (n=730)
HIV-negative: 78.6% (n=551) Social Time with GBM: >25%: 67.7% (n=592)
<$30k/yr: 72.9% (n=485)
P6M sduCAS: 36.3% (n=291) || CAS: 62.3% (n=504)
White: 68.8% (n=585) || Indigenous: 9.5% (n=50)
“Always” Uses condoms: 57.6% (n=426)
Age <24: 21.9% (n=147) || Age ≥40: 34.9% (n=296)Online Sex Seeking: 67.3% (n=586)

28. 49% 51%
78% 70%
80%
66%
39%
29%
83%
54%
25%
30%
76%
62%
22%
27%
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
1 2 3 4 5 6 7 8
Proportion(%)
Visit Number
Lives in the West End/ Downtown (in P6M)
Believes Community involvement is Important/Somewhat Important
Went to Gay Bars and Clubs More than Monthly (in P6M)
Attended Gay Group Meetings (in P6M)
Read Gay News Media (in P6M)
Spent More than 50% of Social Time with Other GBM (in P6M)
Sought Sex Online Using Apps or Websites (in P6M)
Went to the Most Recent Pride Parade (in P12M)
Community
Involvement
Across Visits

29. Wellman (2001, 2003) “Networked Individualism?”
Online and offline participation in voluntary organizations and politics are
positively correlated.
Penard (2010) “Virtual Ties”
Volunteerism and trust are associated with online socializing. But online
socializing may reduce face-to-face contact with friends.
Neves (2013) “Social Capital and Internet”
Review highlights a mixture of studies in the literature, but a positive
relationship between internet use and social capital is uncovered.
Bauernschuster (2014) “Surfing Alone?”
No evidence of negative effects of the Internet on several aspects of social
capital.
Internet Use and Social Capital
Internet
doesn’t
seem to be
the driving
force
behind the
decline.

30. Any vs. None
>Monthly vs.
monthly/none
More than
monthly vs. <
monthly
Play on gay sports team 1.24 (0.73-2.09) 1.14 (0.60-2.15) 1.31 (0.61-2.81)
Attend gay specific groups 1.32 (0.84-2.07) 1.29 (0.89-1.87) 1.32 (0.84-2.07)
Attend gay bars/clubs 1.33 (0.95-1.87) 1.22 (0.91-1.65) 1.41 (1.01-1.97)
Read gay bars/clubs 0.85 (0.63-1.14) 0.85 (0.63-1.14) 1.72 (1.18-2.49)
Pride parade participation 0.99 (0.73-1.34) - -
Number of groups attended 1.11 (0.96-1.29) - -
Bivariate sensitivity analysis of factors associated with
online sex seeking vs. none
Bivariable Multivariable
Social Time Spent with Gay Men
26-75% vs. <25% 2.20 (1.58-3.08) 1.99 (1.33-2.97)
>76% vs. <25% 1.54 (0.96-2.48) 1.17 (0.66-2.08)
Collectivism 1.07 (1.01-1.14) 1.08 (1.01-1.16)
No. of Facebook Friends 1.09 (1.05-1.13) 1.08 (1.03-1.13)
Selected covariates of online sex seeking vs. none
Online
dating
doesn’t
seem to be
associated
with lower
community
involvement

31. HOW DO YOU GO
ABOUT WORKING
WITH A COMMUNITY?
+

32. HETEROGENEITY
+
Using Latent Class Analysis to Identify Sub-
Groups and Sub-Cultures

33. Barrett & Pollack (2005) “Whose Gay Community?”
Non-white, working-class men are less likely to connect to the gay community
and identify as gay.
Fraser (2008) “Young men, queer and theories of gay community”
Despite the widely held perception that queer is supplanting gay among young
same-sex attracted men in Australia, participants do not support this
assumption. Further, conventional models of community (vs. individualism)
continue to prioritize sameness and cooperation for common goals. Yet,
participants feel excluded from community by their own differences.
Goltz (2014) “Shifting Generational Perspectives and tensions.”
Emergent generational divide in the conceptualization and articulation of "gay
identity" as well as how this identity is understood in relation to "the gay
community."
Lewis (2015) “Community Cleavages”
Perceived hierarchies of acceptance for the various subgroups as well as an
age effect wherein middle-aged men perceive the least acceptance for all
groups. These differences are linked with the uneven impact of social, political,
and institutional changes relevant to gay and bisexual men in Canada.
Community Cleavages

34. Latent Class
Analysis
SD
D
A
SA
γ1 γ2 γ3 γ4 γ5

35. Latent Class
Analysis
SD
D
A
SA
γ1 γ2 γ3 γ4 γ5

36. Latent Class
Analysis
SurveyDesignAnalysisInterpretation
C
γ1 γ2 γ3 γ4 γ5
K1
K2
K3
γ6 γ7 γ8 γ9
Indicators
Latent
Variable
Classes

37. Patterns of Community Connectedness
Among Gay and Bisexual Men
Example #1

38. • Read gay news/ media, P6M
• Attended gay group meetings, P6M
• Attended gay pride parade, P12M
• Spent >50% social time with GBM
• Attended gay bars, P6M
• Played on gay sports team, P6M
• Used apps to seek sex, P6M
• Used websites to seek sex, P6M
• Had Facebook, Currently
LCA
Indicators

39. 0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1
Attend Gay
Bars/Clubs
Read Gay
News/Media
Attended
Pride Parade
>50% Social
Time with
GBM
Attend Gay
Groups
Used Apps
to Seek Sex
Used
Websites
to Seek Sex Has
Facebook
ItemResponseProbabilities
Socialites Traditionalists Techies

40. 0
50
100
150
200
250
300
Feb. 2012 -
Jul. 2012
Aug. 2012 -
Jan. 2013
Feb. 2013 -
Jul. 2013
Aug. 2013 -
Jan. 2014
Feb. 2014 -
Jul. 2014
Aug. 2014 -
Jan. 2014
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
TotalNumberRecruited
(Line)
ProportionofRecruitsinEachGroup
(Bar)
Techies Traditionalists Socialites Total

41. Traditionalists vs.
Socialites
Techies vs. Socialites
Techies vs.
Traditionalists
aOR (95%CI) aOR (95%CI) aOR (95%CI)
Age (per year older) 1.06 (1.04-1.07) 1.01 (1.00-1.03) 0.96 (0.94-0.98)
Annual Income (≥30,000 vs. <$30,000) 0.43 (0.28-0.66) 0.59 (0.41-0.86) 1.38 (0.89-2.15)
Current Relationship
Monogamous/Married Ref Ref Ref
(Partially) Open 0.67 (0.37-1.22) 1.12 (0.60-2.07) 1.67 (0.88-3.19)
No Regular Partner 0.54 (0.32-0.91) 1.45 (0.85-2.47) 2.70 (1.54-4.74)
Collectivism 0.82 (0.75-0.89) 0.75 (0.69-0.81) 0.92 (0.84-0.99)
Stigma Scale 0.93 (0.87-0.99) 1.00 (0.94-1.06) 1.07 (1.00-1.15)
HIV Tested, Ever 0.37 (0.17-0.84) 1.23 (0.52-2.91) 3.30 (1.43-7.63)
Ask Partners their HIV Status 0.57 (0.38-0.85) 1.03 (0.71-1.48) 1.80 (1.20-2.70)
CAS with serodiscordant/unknown partner, P6M 0.74 (0.48-1.14) 1.32 (0.91-1.92) 1.79 (1.16-2.70)
# Male Sex Partners, P6M 0.99 (0.98-1.00) 1.00 (1.00-1.00) 1.01 (1.00-1.02)
Recruitment Time (odds per month) 0.98 (0.96, 1.01) 1.03 (1.00, 1.05) 1.05 (1.02, 1.08)

42. Any substance reported by more than 30
participants.
Example #2

43. What groups are
likely to emerge?
+

44. Class Names Limited Conventional Sex Club Street Assorted
Distribution 296 (36.7) 203 (25.9) 90 (11.4) 69 (9.5) 82 (12.1) 34 (4.5)
Alcohol 75.6 100.0 84.3 98.6 75.8 92.9
Marijuana 29.6 79.7 74.0 90.2 70.1 93.2
Tobacco 23.2 43.1 47.0 69.1 69.9 84.9
Erectile Drugs 10.9 22.2 78.0 8.5 14.7 66.8
Poppers 20.1 36.9 74.8 51.9 32.7 73.7
Crystal 1.3 5.0 77.2 2.3 38.7 100.0
Cocaine 0.9 15.2 44.6 72.5 44.1 96.3
GHB 0.6 2.0 86.5 33.4 13.3 81.7
Ecstasy 0.0 20.2 65.7 89.1 4.8 83.3
Ketamine 0.0 2.7 41.3 43.2 0.0 91.2
Mushrooms 0.0 14.9 5.1 51.7 1.4 36.5
LSD 0.0 0.0 0.0 26.5 4.2 30.7
Heroin 0.0 0.0 0.0 0.0 19.9 35.8
Oxycodone 0.0 1.5 7.5 5.9 13.9 34.8
Crack 0.7 0.0 14.5 3.2 39.1 58.6

45. Conventional Use
Age 1.00 (0.99, 1.02)
Sexual Sensation Seeking Scale 1.03 (0.99, 1.09)
Escape Movie Scale 1.01 (0.98, 1.05)
Non-Gay Identified 1.48 (0.82, 2.68)
HIV-Positive 1.03 (0.61, 1.74)
Annual Income > $30,000 0.94 (0.62, 1.42)
Stably Housed 0.77 (0.38, 1.57)
Occupation (vs. unemployed)
Professionals/Upper Class 0.97 (0.57, 1.67)
Working Class/Lower Class 1.21 (0.71, 2.06)
Income from Drug Sales. P6M 2.17 (0.39, 12.04)
Attended Group Sex Events. P6M 1.22 (0.77, 1.94)
Attend Gay-Bars/Clubs. P6M 2.32 (1.37, 3.92)

46. Club Drug Use
Age 0.93 (0.89, 0.96)
Sexual Sensation Seeking Scale 1.14 (1.06, 1.23)
Escape Movie Scale 1.03 (0.98, 1.08)
Non-Gay Identified 1.86 (0.85, 4.08)
HIV-Positive 0.73 (0.24, 2.22)
Annual Income > $30,000 1.15 (0.62, 2.12)
Stably Housed 1.46 (0.42, 5.04)
Occupation (vs. unemployed)
Professionals/Upper Class 0.59 (0.28, 1.26)
Working Class/Lower Class 0.62 (0.29, 1.32)
Income from Drug Sales. P6M 6.51 (1.11, 38.29)
Attended Group Sex Events. P6M 0.77 (0.38, 1.58)
Attend Gay-Bars/Clubs. P6M 4.37 (1.56, 12.26)

47. Sex Drug Use
Age 1.01 (0.98, 1.03)
Sexual Sensation Seeking Scale 1.12 (1.04, 1.20)
Escape Movie Scale 1.08 (1.03, 1.13)
Non-Gay Identified 1.22 (0.51, 2.90)
HIV-Positive 3.98 (2.07, 7.65)
Annual Income > $30,000 2.92 (1.59, 5.35)
Stably Housed 0.66 (0.27, 1.62)
Occupation (vs. unemployed)
Professionals/Upper Class 0.41 (0.20, 0.83)
Working Class/Lower Class 0.57 (0.28, 1.15)
Income from Drug Sales. P6M 9.24 (1.72, 49.8)
Attended Group Sex Events. P6M 2.41 (1.34, 4.31)
Attend Gay-Bars/Clubs. P6M 0.89 (0.47, 1.69)

48. Street Drug Use
Age 1.01 (0.98, 1.03)
Sexual Sensation Seeking Scale 1.04 (0.97, 1.11)
Escape Movie Scale 1.09 (1.05, 1.15)
Non-Gay Identified 3.16 (1.63, 6.10)
HIV-Positive 1.75 (0.92, 3.32)
Annual Income > $30,000 0.77 (0.39, 1.50)
Stably Housed 0.29 (0.14, 0.59)
Occupation (vs. unemployed)
Professionals/Upper Class 0.30 (0.15, 0.61)
Working Class/Lower Class 0.42 (0.22, 0.81)
Income from Drug Sales. P6M 2.12 (0.32, 14.2)
Attended Group Sex Events. P6M 0.77 (0.4, 1.49)
Attend Gay-Bars/Clubs. P6M 1.02 (0.56, 1.86)

49. Assorted Drug Use
Age 0.95 (0.91, 0.99)
Sexual Sensation Seeking Scale 1.13 (1.02, 1.26)
Escape Movie Scale 1.07 (1.00, 1.14)
Non-Gay Identified 2.97 (1.14, 7.72)
HIV-Positive 5.97 (2.18, 16.34)
Annual Income > $30,000 1.06 (0.41, 2.79)
Stably Housed 0.23 (0.08, 0.63)
Occupation (vs. unemployed)
Professionals/Upper Class 0.58 (0.20, 1.75)
Working Class/Lower Class 1.04 (0.39, 2.76)
Income from Drug Sales. P6M 19.77 (3.65, 106.89)
Attended Group Sex Events. P6M 3.26 (1.39, 7.63)
Attend Gay-Bars/Clubs. P6M 0.79 (0.33, 1.88)

50. 12.2%
10.9%
24.5%
28.3%
11.8%
12.0%
10.7% 10.7%
27.4%
28.5%
13.4%
9.6%
0%
5%
10%
15%
20%
25%
30%
35%
Visit 1 Visit 2 Visit 3 Visit 4 Visit 5
Proportion(%)ofparticipantsineachclass
Street Drug Use Limited Drug Use Club Drug Use
Sex Drug Use Conventional Drug Use Assorted Drug Use

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