32
The Sounds of Social Life: Observing Humans in Their Natural Habitat Matthias R. Mehl Department of Psychology The University of Arizona

The Sounds of Social Life: Observing Humans in Their ... · PDA-based recording software Samples snippets of ambient sounds e.g., 30 sec every 12.5 min (4% of the day) ≈ 70 sound

  • Upload
    others

  • View
    3

  • Download
    0

Embed Size (px)

Citation preview

Page 1: The Sounds of Social Life: Observing Humans in Their ... · PDA-based recording software Samples snippets of ambient sounds e.g., 30 sec every 12.5 min (4% of the day) ≈ 70 sound

The Sounds of Social Life:Observing Humans in Their

Natural Habitat

Matthias R. Mehl Department of PsychologyThe University of Arizona

Page 2: The Sounds of Social Life: Observing Humans in Their ... · PDA-based recording software Samples snippets of ambient sounds e.g., 30 sec every 12.5 min (4% of the day) ≈ 70 sound

A Method Matrix

???Behavioral Observation

Self-Report

Natural Environment

In the Lab

Page 3: The Sounds of Social Life: Observing Humans in Their ... · PDA-based recording software Samples snippets of ambient sounds e.g., 30 sec every 12.5 min (4% of the day) ≈ 70 sound

An “Acoustic Observation” Sampling Approach

Page 4: The Sounds of Social Life: Observing Humans in Their ... · PDA-based recording software Samples snippets of ambient sounds e.g., 30 sec every 12.5 min (4% of the day) ≈ 70 sound

PDA-based recording software Samples snippets of ambient sounds e.g., 30 sec every 12.5 min (4% of the day)

≈ 70 sound files per day

The EAR** EAR = Electronically Activated Recorder (Mehl et al., 2001)

Page 5: The Sounds of Social Life: Observing Humans in Their ... · PDA-based recording software Samples snippets of ambient sounds e.g., 30 sec every 12.5 min (4% of the day) ≈ 70 sound

The Evolution of a Method

Analog EAR (1997-2000)

Digital EAR (2000 - 2005)

PocketEAR (2005 - )

Page 6: The Sounds of Social Life: Observing Humans in Their ... · PDA-based recording software Samples snippets of ambient sounds e.g., 30 sec every 12.5 min (4% of the day) ≈ 70 sound

EAR Obtrusiveness

0%

1%

2%

3%

4%

5%

6%

7%

8%

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23

Time after receiving the EAR (in hours awake)

% o

f tim

e ta

lkin

g ab

out t

he E

AR

N = 97

Talking about the EARMehl & Holleran (2007)

Page 7: The Sounds of Social Life: Observing Humans in Their ... · PDA-based recording software Samples snippets of ambient sounds e.g., 30 sec every 12.5 min (4% of the day) ≈ 70 sound

EAR Compliance

0%

2%

4%

6%

8%

10%

12%

14%

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23

Time after receiving the EAR (in hours awake)

% o

f tim

e no

t wea

ring

the

EA

R

N = 97

Not Wearing the EARMehl & Holleran (2007)

Page 8: The Sounds of Social Life: Observing Humans in Their ... · PDA-based recording software Samples snippets of ambient sounds e.g., 30 sec every 12.5 min (4% of the day) ≈ 70 sound

EAR-Assessment of Daily Life

Person-Environment Interactions

Locations

Private vs. public places, inside vs. outside

Activities

TV, music, studying, church, going out

Interactions

dyadic vs. group, same vs. opposite sex settings

Topics

Relationships, Fashion, Sex, Sports, Politics, Health

Word Choice

Emotion words, cognitive words, swearing, “like”, pronouns

Social Environments

Environment Selection

NaturalConversations

Environment Interaction

Mehl & Robbins (in press)

Page 9: The Sounds of Social Life: Observing Humans in Their ... · PDA-based recording software Samples snippets of ambient sounds e.g., 30 sec every 12.5 min (4% of the day) ≈ 70 sound

Naturalistic observation allows for the assessment of subtle social behaviors that evade self-reports. The “Venus = Mars?” Project

(Mehl, Vazire, Ramirez-Esparza, Slatcher, & Pennebaker, 2007)

The “Knowing Me, Knowing You” Project(Vazire & Mehl, 2008)

The US-Mexico Project(Ramirez, Mehl, Álvarez-Bermúdez & Pennebaker, 2009)

Naturalistic observation can provide ecological, behavioral criteria that are independent of self-report.

Mehl (2009)

What Is the Added Value of Naturalistic Observation?

The “Eavesdropping on Happiness” Project(Mehl, Vazire, Holleran, & Clark, in press)

Page 10: The Sounds of Social Life: Observing Humans in Their ... · PDA-based recording software Samples snippets of ambient sounds e.g., 30 sec every 12.5 min (4% of the day) ≈ 70 sound

Naturalistic observation can provide ecological, behavioral criteria that are independent of self-report

Knowing me, knowing you:The relative accuracy and unique predictive

validity of self-ratings and other-ratings of daily behavior

Vazire & Mehl, JPSP, 2008

Page 11: The Sounds of Social Life: Observing Humans in Their ... · PDA-based recording software Samples snippets of ambient sounds e.g., 30 sec every 12.5 min (4% of the day) ≈ 70 sound

Most people assume they know themselves better than anyone else knows them.

Reviewer C: “the best criterion for a target’s personality is his or her self-ratings … Otherwise, the whole enterprise of personality assessment seriously needs to re-think itself”

But how do you test the relative accuracy of self- and other knowledge?

Knowing Me, Knowing You

N = 80 college students wore the EAR for 4 days Participants and 3 informants rated the participants on how

much they engage in 20 daily behaviors. The EAR-assessed frequency with which participants actually

engaged in these behaviors was used as accuracy criterion.

Page 12: The Sounds of Social Life: Observing Humans in Their ... · PDA-based recording software Samples snippets of ambient sounds e.g., 30 sec every 12.5 min (4% of the day) ≈ 70 sound

How Accurate Were Self- and Other-Ratings?

r = .26

r = .26 (.23)

Self-Ratings of Daily Behavior

EAR-Coded Frequencies of Daily Behavior

Other-Ratings of Daily Behaviors

(averaged across all behaviors)

β = .18, ∆ R2 = .04

β = .18, ∆ R2 = .04

Self and others are equally (in)accurate and possess unique insight into how a person typically behaves.

Page 13: The Sounds of Social Life: Observing Humans in Their ... · PDA-based recording software Samples snippets of ambient sounds e.g., 30 sec every 12.5 min (4% of the day) ≈ 70 sound

Naturalistic observation can provide ecological, behavioral criteria that are independent of self-report

Are Mexicans More Or Less Sociable Than Americans?

Ramirez, Mehl, Álvarez-Bermúdez & Pennebaker, JRP, 2009

Page 14: The Sounds of Social Life: Observing Humans in Their ... · PDA-based recording software Samples snippets of ambient sounds e.g., 30 sec every 12.5 min (4% of the day) ≈ 70 sound

Are Mexicans More or Less Sociable than Americans?

EAR Study with 46 students from Monterrey, Mexico and 52 students from Austin, Texas.

Self-reported extraversion, sociability, and talkativeness

EAR-observed time spent with others, socializing, and talking

Reference group effect? Differential response bias?

43%34% time spent talking p < .001

Page 15: The Sounds of Social Life: Observing Humans in Their ... · PDA-based recording software Samples snippets of ambient sounds e.g., 30 sec every 12.5 min (4% of the day) ≈ 70 sound

Display of Interdependent Self

Display of Independent Self

Do Mexicans and Americans Differ in How They are Social?

Immediate, public vs. remote, private expression of sociability

Page 16: The Sounds of Social Life: Observing Humans in Their ... · PDA-based recording software Samples snippets of ambient sounds e.g., 30 sec every 12.5 min (4% of the day) ≈ 70 sound

Naturalistic observation allows for the assessment of subtle social behaviors that evade self-reports. The “Venus = Mars?” Project

(Mehl, Vazire, Ramirez-Esparza, Slatcher, & Pennebaker, 2007)

The “Knowing Me, Knowing You” Project(Vazire & Mehl, 2008)

The US-Mexico Project(Ramirez, Mehl, Álvarez-Bermúdez & Pennebaker, 2009)

Naturalistic observation can provide ecological, behavioral criteria that are independent of self-report.

Mehl (2009)

What Is the Added Value of Naturalistic Observation?

The “Eavesdropping on Happiness” Project(Mehl, Vazire, Holleran, & Clark, in press)

Page 17: The Sounds of Social Life: Observing Humans in Their ... · PDA-based recording software Samples snippets of ambient sounds e.g., 30 sec every 12.5 min (4% of the day) ≈ 70 sound

Naturalistic Observation allows for the assessment of subtle social behaviors that evade self-reports

Are Women Really More Talkative Than Men?

Mehl, Vazire, Ramirez-Esparza, Slatcher, & Pennebaker, Science, 2007

Page 18: The Sounds of Social Life: Observing Humans in Their ... · PDA-based recording software Samples snippets of ambient sounds e.g., 30 sec every 12.5 min (4% of the day) ≈ 70 sound

“A woman uses about 20,000 words per day while a man uses about 7,000”*

The Female Brain

“All of this is hardwired into the brains of women. These are the talents women are born with that many men, frankly, are not”

* The numbers have been taken out in the second print

Page 19: The Sounds of Social Life: Observing Humans in Their ... · PDA-based recording software Samples snippets of ambient sounds e.g., 30 sec every 12.5 min (4% of the day) ≈ 70 sound
Page 20: The Sounds of Social Life: Observing Humans in Their ... · PDA-based recording software Samples snippets of ambient sounds e.g., 30 sec every 12.5 min (4% of the day) ≈ 70 sound

The “Language Mythbuster”

Mark Liberman

Page 21: The Sounds of Social Life: Observing Humans in Their ... · PDA-based recording software Samples snippets of ambient sounds e.g., 30 sec every 12.5 min (4% of the day) ≈ 70 sound

We Had Been Counting Words For Years …

202717–234 daysUSA199864718–2610 daysUSA20015

494717–222 daysUSA20014203117–254 daysMexico20033374217–234 daysUSA20032565618–297 daysUSA20041

Menn

Womenn

range(years)

Sample sizeAgeDurationLocationYearSample

111,040 valid waking recordings; 851,276 recorded words

Page 22: The Sounds of Social Life: Observing Humans in Their ... · PDA-based recording software Samples snippets of ambient sounds e.g., 30 sec every 12.5 min (4% of the day) ≈ 70 sound

Are Women Really More Talkative Than Men?

16,215(7,301)

15,669(8,663)

Cohen’s d = 0.07, p = .248

Page 23: The Sounds of Social Life: Observing Humans in Their ... · PDA-based recording software Samples snippets of ambient sounds e.g., 30 sec every 12.5 min (4% of the day) ≈ 70 sound

Responses to the Study

Page 24: The Sounds of Social Life: Observing Humans in Their ... · PDA-based recording software Samples snippets of ambient sounds e.g., 30 sec every 12.5 min (4% of the day) ≈ 70 sound

A Funny Take on It …

Page 25: The Sounds of Social Life: Observing Humans in Their ... · PDA-based recording software Samples snippets of ambient sounds e.g., 30 sec every 12.5 min (4% of the day) ≈ 70 sound

Or Closer to the Truth …

Page 26: The Sounds of Social Life: Observing Humans in Their ... · PDA-based recording software Samples snippets of ambient sounds e.g., 30 sec every 12.5 min (4% of the day) ≈ 70 sound

Naturalistic observation allows for the assessment of subtle social behaviors that evade self-reports

Eavesdropping on Happiness

Mehl, Vazire, Holleran, & Clark, Psych Science, 2010

Page 27: The Sounds of Social Life: Observing Humans in Their ... · PDA-based recording software Samples snippets of ambient sounds e.g., 30 sec every 12.5 min (4% of the day) ≈ 70 sound

Is the happy (daily) life full of superficial, happy-go-lucky moments or full of profound social encounters (“happy ignoramus” vs. “fulfilled deep thinker”)?

Eavesdropping on Happiness

96 participants wore the EAR for 4 days Well-being was assessed with self-reports of life-

satisfaction and self- and informant reports of happiness EAR codings

Time spent alone, time spent with others Small-talk (uninvolved conversation of a banal nature; only trivial

information gets exchanged) Substantive conversations (involved conversation of a substantive

nature; meaningful information gets exchanged)

Page 28: The Sounds of Social Life: Observing Humans in Their ... · PDA-based recording software Samples snippets of ambient sounds e.g., 30 sec every 12.5 min (4% of the day) ≈ 70 sound

Eavesdropping on Happiness

The happy daily life is social rather than solitary and conversationally deep rather than superficial.

r = -.35 & r = .31, ps < .01 r = -.33 & r = .28, ps < .01

Page 29: The Sounds of Social Life: Observing Humans in Their ... · PDA-based recording software Samples snippets of ambient sounds e.g., 30 sec every 12.5 min (4% of the day) ≈ 70 sound

Summary

It allows us to study actual, real-world behavior in addition to (global, retrospective, or momentary) perceptions of such behavior.

This is important because only that way can we learn about what causes

convergence of and discrepancies between the two. ultimately, actual, real-world behavior tends to be

the (explicit or implied) end-point of our theories.

In essence, what is the added value of naturalistic observation with a method such as the EAR?

Page 30: The Sounds of Social Life: Observing Humans in Their ... · PDA-based recording software Samples snippets of ambient sounds e.g., 30 sec every 12.5 min (4% of the day) ≈ 70 sound

“We wish to suggest, gently and respectfully,that social and personality psychology try toput a bit more behavior back into the scienceof behavior (…). We advocate a renewedcommitment to including direct observation ofbehavior whenever possible and in at least ahealthy minority of research projects.”

(Baumeister,Vohs, & Funder,2007)

Page 31: The Sounds of Social Life: Observing Humans in Their ... · PDA-based recording software Samples snippets of ambient sounds e.g., 30 sec every 12.5 min (4% of the day) ≈ 70 sound

Day-to-DaySocial Lives

Personality

Relationships

Health

Culture

The Broader Context of this Research

SighingSwearing

Page 32: The Sounds of Social Life: Observing Humans in Their ... · PDA-based recording software Samples snippets of ambient sounds e.g., 30 sec every 12.5 min (4% of the day) ≈ 70 sound

the participants for sharing the sounds of their personal daily lives. the research assistants for coding and transcribing the EAR sound files.

James Pennebaker, Sam Gosling, Simine Vazire, Jason Rentfrow, Nairan Ramirez, Andrea Garcia, Shannon Holleran, Megan Robbins, and all the other people who directly or indirectly contributed to the projects. The NIH (R03CA137975) and ACS (IRG-74–001–28) for their support.

Thanks to …

Allison Lake Cecilia Boyed Jordan Lopuszanski Lizzette Enriquez Sean Randall

Alyssa Fu Chelsea Joseph Josh Lewis Margaret Jarvis Shannon Finley

Amanda Grossman Erin Armstrong Kaitlin Groch Baroi Mary Arbuthnot Shelby Clarke

Andres O'Donnell Gina Myers Katherine Calkins Monica Berumen Stephanie Carlson

Annette Enriquez Jamie Johns Kristin Donneley Monica Miller Stephanie Levitt

Ariel Anderson Jaz Miller Kyle Keller Rachel Tasky Zach Smith

Ashley Godfrey Jessica Corl Lauren Carmichal Rose Estes

Ashley Lau Jilletta Begay Lindsay Keefer Ruben Lespron

Aubrey Arrington John Putz Lindsey Ishikawa Sara Ziebell