Media Use, Face-to-Face Communication, Media Multitasking and Social Wellness among 8-12 Year Old Girls
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Media Use, Face-to-Face Communication, Media Multitasking and Social Wellness among 8-12 Year Old Girls

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The CERI OECD/National Science Foundation International Conference took place in Paris, at the OECD Headquarters on 23-24 January 2012. Here the presentation of Session 6, Technology, Item 2.

The CERI OECD/National Science Foundation International Conference took place in Paris, at the OECD Headquarters on 23-24 January 2012. Here the presentation of Session 6, Technology, Item 2.

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Media Use, Face-to-Face Communication, Media Multitasking and Social Wellness among 8-12 Year Old Girls Media Use, Face-to-Face Communication, Media Multitasking and Social Wellness among 8-12 Year Old Girls Presentation Transcript

  • Media use, face-to-face communication, media multitasking and social well- being among tweenage girls ! Roy Pea, Cliff Nass, Lynn Meheula, Marcus Rance and Aman Kumar Stanford University Supported by NSF Grants #0835854 and #0841556
  • Issues !•  Key developmental period in tweenage years of 8- to 12-years old for socio- emotional development•  Emerging values & choices of a new “always-on” generation for media use and multi-tasking?•  Socio-emotional correlates for profiles of media use and media multitasking?
  • Overview of Study Questions !•  Age•  Access/ownership of technology (TV, computer, cellphone)•  About friends•  Media use•  Media use while using media•  General social outlook•  Comparison of online and offline friends•  Miscellaneous behavioral questions (e.g. sleep)
  • Survey!•  3,461 girls, age 8-12 •  Population was over 1M girls who read Discovery Girls magazine•  August/September 2010•  Web-based - 20 minutes to complete
  • Issues of Representativeness !•  Participants had to be aware of Discovery Girls magazine •  Quite a large fraction of tweens•  All participants had web access and 95% of the respondents had computers in their homes •  Higher than average
  • Nonetheless, an Excellent Sample!•  All 50 states •  Comparable levels of cell phone use and media use to national samples•  Highly reliable measures•  Bottom Line? •  Excellent dataset for looking at relationships between variables (far better than experiments) •  Absolute rates should be viewed with more caution
  • Categories of Media and F2F!1. Watching video content, inc.videogames2. Listening to music3. Reading or doing homework4a. Emailing or sending messages/postingon Facebook4b. Text or instant message5. Talk on the phone or video chat6. Participate in face-to-face conversation
  • Categories of Media and F2F!1. Watching video content, inc.videogames2. Listening to music3. Reading or doing homework4a. Emailing or sending messages/postingon Facebook4b. Text or instant message5. Talk on the phone or video chat6. Participate in face-to-face conversation
  • Determining Media Use," Determining Multitasking!•  Question 1: “On an average day, how long [do you X]?” (e.g. watch video content: TV, YouTube, movies, etc.) •  Six-point scale: from ‘never’ to ‘more than 4 hours’•  Question 2: “On an average day, while [doing X], how often are you doing the following other things at the same time? •  Same six-point scale
  • How Media Multitasking Index" (MMI) is calculated!•  Media Multitasking Index for each person: •  Calculates (on average) how many additional media streams are being consumed when one is consuming any given media stream.•  Sum of answers to Question 2 for five media categories, not including F2F communication (“How often are you also doing Y?”) divided by sum of answers to Question 1 for the five media categories (“How often do you do X?”)
  • How F2F Media Multitasking Index" is calculated!•  F2F Media Multitasking Index: •  Calculates (on average) how many additional media streams are being consumed when one is interacting F2F.•  Sum of answers for F2F and the five other media categories (“On an average day, while participating in face-to-face conversations, how many hours are you also doing Y?”) is divided by # hours for “How often do you F2F communicate?”
  • Index 1: Social Success !•  “Please rate how much you agree with each statement” •  Strongly Disagree (=1) to Strongly Agree (=6) •  “I feel like I have a lot of friends” •  “I find it easy to make friends” •  “People my age understand me” •  “I feel like I have a lot of close friends” •  “I find it easy to keep friends” •  “I feel like I’m important to my friends” •  “I feel accepted by people my age”•  Very high reliability: Cronbach’s alpha=.87
  • Index 2: Normalcy Feelings !•  “Please rate how much you agree with each statement” •  [Strongly Disagree (=1) to Strongly Agree (=6)] •  “Compared to people my age, I feel normal” •  “I often feel like I’m not normal compared to people my age” •  “I often feel rejected by other people my age”•  Reliable index: alpha=.68
  • Online vs. In-Person Friends !•  For list of questions about sources of positive or negative feelings, participants answered on a six-point scale: •  Definitely Online Friends (=1) to Definitely In-Person Friends (=6)•  Using this definition: •  “’Online Friends’ are the friends that you interact with MOSTLY online… •  ‘In-Person Friends’ are friends that you interact with MOSTLY in person.”
  • Index 3: Source of Positive Feelings !•  Definitely Online Friends (=1) to Definitely Off-line Friends (=6)•  Extremely reliable: alpha = .94 •  Who do you share more •  I feel closer to … secrets with? •  I feel more comfortable with … •  Which do you want to be more •  In which group do you have like? more close friends? •  Which do you trust more? •  Who makes you feel more •  Which do you value more? accepted? •  Which understands your •  I feel better after talking to … feelings more? •  I feel more supported by … •  I fit in better with …
  • Index 4: Source of Negative Feelings ! •  Definitely Online Friends (=1) to Definitely Offline Friends (=6) •  Extremely reliable: alpha = .94 •  “I feel more judged by …” •  “I feel more stressed by …” •  “Which can hurt your feelings more …?”
  • Other Behavioral Variables !•  Index 5: How many hours of sleep per night? •  “Less than 6 hours” (=1) to “More than 10 hours” (=6)•  Index 6: How many friends do you have that your parents think are bad influences? •  (Scale: 0, 1, 2, 3 or more)•  Do you own a cellphone?•  Do you have a TV in your bedroom?
  • Summary Statistics !•  Avg media use@day: 6.9 hours (SD=3.40) •  Not too unlike Kaiser Generation M2 data (ages 8-19) - taking into account that boys and older groups are heavier users•  Average F2F@day: 2.1 hours (SD=1.49)•  MMI: When using a medium the average 8-12 year old girl uses 1.4 other media concurrently•  F2F MMI: is also 1.4 extra media @ medium for F2F communication
  • Media Use Correlations" and Media Multitasking!•  Only small to moderate correlations between uses of media types (video, music, reading, online interactions, talking on phone, F2F interaction) - suggesting they attract different persons•  Online communication use is most strongly associated with media multitasking (r= .44, p<.001)
  • Media Multitasking (MMT) !•  Talking on the phone, online communication, and music are all positively related to MMT•  Cell phone ownership and having a TV in one’s room positively related to MMT•  F2F communication negatively related to MMT even when controlling for media use
  • F2F Media Multitasking!•  Every category of media use but reading is strongly and positively related to F2F MMT (reading is negatively related)•  F2F communication is negatively related to F2F media multitasking•  Younger children tend to do more multitasking while face-to-face than older children•  Presence of TV in the bedroom strongly associated with more F2F MMT
  • Correlations Between Media Use & " Types of Media Multitasking!•  Total Media Use and F2F Media Multitasking are only weakly correlated: •  Suggests media use while F2F is a different category of behavior than using media in general•  Yet Media Multitasking and F2F Media Multitasking are highly correlated when controlling for media use: •  Implying that multitasking is a generalized behavior
  • Social success !•  Video use is strongly and negatively associated with social success•  Face to face communication is positively associated with feelings of social success•  Reading use is moderately and negatively associated with social success (but this correlation turns out to be due to extremity effects)•  Older girls in the 8-12 year range feel less social success
  • Feelings of Normalcy!•  As with social success, video and reading use are negatively associated with feelings of normalcy•  While face to face communication is positively associated with feelings of normalcy•  Both media multitasking and age are negatively associated with feelings of normalcy
  • Number of friends one’s parents think are a bad influence !•  Video use, talking on the phone and online interactions are all strongly associated with a greater number of friends perceived by parents as bad influences – while face-to-face communication is negatively related•  Media multitasking is very strongly and positively related to this variable
  • Hours of Sleep!•  Video use and online communication use are negatively associated with number of hours of sleep•  Media multitasking is strongly and negatively associated to amount of sleep•  But face to face communication is positively associated to hours of sleep•  Age is strongly and negatively related to hours of sleep, as is having a TV in one’s room and owning a cellphone
  • Positive and Negative Feelings !•  Even heavy online media users tend to derive their positive feelings principally from in-person friends •  No more than 10.1% of respondents for even one item get their positive feelings principally from online friends rather than in-person friends•  In contrast – half of respondents attribute their negative feelings to online friends and half to in-person friends
  • Summary!•  Trouble 1: Quantity of video use is correlated with various negative socio-emotional outcomes: •  Less social success, less normalcy feelings, less sleep, more friends parents think are bad influences•  Trouble 2: Quantity of online communication* correlated with the negative socio-emotional outcomes studied•  Trouble 3: Quantity of media multiasking correlated with the negative socio-emotional outcomes studied•  Ray of hope! Quantity of face-to-face communication is positively associated with: •  Greater social success, more normalcy feelings, more sleep, fewer friends parents think are bad influences
  • Limitations!•  Correlations don’t yield causal inferences: •  Effects may run either way - or both ways (media <-> social) •  Strong negative correlations for video use & positive social feelings…but we cannot conclude watching high volumes of video is responsible for that situation…. •  It could be that due to low positive social feelings (loneliness, awkwardness, autism spectrum…), participants turn to video watching instead of F2F interactions •  …and we also don’t know the content of their video use either (presumably some uses could be more positively related to social wellness)
  • Futures !•  Longitudinal & intervention studies •  With fine-grained experiental methods •  Focused ethnographies of ‘critical events’ as media use & social experiences ‘collide’ (e.g. What are social reactions to co-present texting, calls, etc.?)•  Studies of new media production and engagement beyond consumption•  Summing up: Why these results are important