1. Time Spent Using Technology and In-Person with Friends & Family Predict Objective Sleep Outcomes among Adolescents Royette Tavernier, Jennifer Heissel, Michael Sladek, Kathryn Grant, & Emma Adam APS - Chicago May 27, 2016

2. (Lenhart, 2015; Pew Research Center) 92% of adolescents report going online daily 24% report going online “almost constantly” Prevalence of Technology Use among Adolescents

3. Why study Technology Use during Adolescence? Emotional Identity Cognitive Interpersonal Sleep (Cain & Gradisar, 2010; Hale & Guan, 2015; Subrahmanyam et al., 2001; Valkenburg & Peter, 2009)

4. Sleep during Adolescence Recommended: 8-10 hours Reality: Significant sleep debt (Keyes et al., 2015)

5. Technology Use and Sleep during Adolescence Presence of technology devices in the bedroom is associated with poorer sleep: later bedtimes, longer sleep latencies, shorter sleep hours, less restful sleep, increased daytime sleepiness (Cain & Gradisar, 2010; Hale & Guan, 2015)

6. Limitations of Past Research 1)Predominantly based on between-person effects (i.e., individual differences) 2)Subjective measures of sleep 3)Lack of assessment of time spent engaged in in- person interactions

7. The Present Study To examine both between- and within- person effects of adolescents’ time use (i.e., technology use and in-person interactions with friends and family) on 3 sleep behaviors

8. Participants Subsample from a larger study (CITIES); who took part in the ‘sleep component’ 3-day daily diary study N = 77 (42.9% female) Age: 11 – 18 years (Mean = 14.37, SD = 1.95) Race: 20.5% White; Ethnicity: 63% Non-Hispanic

9. Measures Sleep –Actigraphy (AW64 Phillips Respironics) – 3 days i)Sleep latency: Amount of time taken to fall asleep ii)Sleep hours: Total sleep time (minus waking) iii)Sleep Efficiency: % of time spent sleeping

10. Measures Time Use: Texting: “Thinking about your day today, how many times did you…” a)Send a text-message? b) Receive a text message? Response Scale: 1 = none; 2 = 1-20; 3 = 20-40; 4 = 40-60; 5 = 60-80; 6 =80-100; 7 = 100+

11. Measures Time Use: “Thinking about your day today, approx. how much time did you spend…” o Instant messaging (e.g., Facebook, chat, AIM)? o Using Facebook/other social media? o Using Twitter? o Talking on the phone? o Watching TV, video, or DVD? o Playing video games (e.g., Xbox or computer)? o Working on a computer (desktop or laptop)? o In face-to-face interactions with friends o In face-to-face interactions with family Response Scale: 1 = 0 minutes; 2 = 1-15 minutes; 3 = 16-29 minutes; 4 = 30-59 minutes; 5 = 1-2 hours; 6 =2-4 hours; 7 = 4+ hours

12. Analyses 2-Level Hierarchical Linear Model (HLM) –Level I: Day-level –Level II: Person-level Covariates: – Age –Gender –Income –Race –Ethnicity –Caffeine use

13. Results Mean (SD) Sleep latency23.40 (28.29) Sleep hours6.10 (0.96) Sleep Efficiency80.99 (7.39)

14. Results 1-2 hours 16-29 mins. 30-59 mins. 1-15 mins. <1 min.

15. Results Fixed Effect Person-Level Texting Instant Messaging Facebook Twitter Talk on phone Watch TV Video games Computer (work) Friends Family

16. Results Sleep Latency Fixed EffectCoefficient (SE) Person-Level Texting-.036 (.041) Instant Messaging-.072 (.051) Facebook.008 (.075) Twitter.023 (.042) Talk on phone.007 (.047) Watch TV.043 (.044) Video games.099 (.042)* Computer (work).040 (.054) Friends-.119 (.050)* Family.003 (.060)

17. Results Sleep LatencySleep Hours Fixed EffectCoefficient (SE) Person-Level Texting-.036 (.041)-.007 (.116) Instant Messaging-.072 (.051)-.081 (.171) Facebook.008 (.075)-.014 (.149) Twitter.023 (.042).072 (.128) Talk on phone.007 (.047).127 (.099) Watch TV.043 (.044)-.175 (.122) Video games.099 (.042)*-.074 (.118) Computer (work).040 (.054)-.236 (.125)+ Friends-.119 (.050)*-.102 (.117) Family.003 (.060).230 (.066)

18. Results Sleep LatencySleep HoursSleep Efficiency Fixed EffectCoefficient (SE) Person-Level Texting-.036 (.041)-.007 (.116).000 (.007) Instant Messaging-.072 (.051)-.081 (.171).002 (.009) Facebook.008 (.075)-.014 (.149)-.005 (.011) Twitter.023 (.042).072 (.128).004 (.009) Talk on phone.007 (.047).127 (.099)-.006 (.010) Watch TV.043 (.044)-.175 (.122)-.013 (.007)* Video games.099 (.042)*-.074 (.118)-.010 (.008) Computer (work).040 (.054)-.236 (.125)+-.003 (.008) Friends-.119 (.050)*-.102 (.117).021 (.008) Family.003 (.060).230 (.066).004 (.010)

19. Results Sleep Latency Fixed EffectCoefficient (SE) Day-Level Texting-.027 (.034) Instant Messaging.045 (.038) Facebook-.000 (.030) Twitter.035 (.058) Talk on phone-.008 (.036) Watch TV-.050 (.042) Video games-.046 (.057) Computer (work).035 (.031) Friends-.077 (.034)* Family.094 (.044)*

20. Results Sleep LatencySleep Hours Fixed EffectCoefficient (SE) Day-Level Texting-.027 (.034)-.236 (.091)* Instant Messaging.045 (.038)-.117 (.099) Facebook-.000 (.030)-.030 (.094) Twitter.035 (.058).200 (.151) Talk on phone-.008 (.036).325 (.141)* Watch TV-.050 (.042).014 (.104) Video games-.046 (.057)-.096 (.126) Computer (work).035 (.031)-.269 (.101)** Friends-.077 (.034)*.060 (.094) Family.094 (.044)*.-013 (.110)

21. Results Sleep LatencySleep HoursSleep Efficiency Fixed EffectCoefficient (SE) Day-Level Texting-.027 (.034)-.236 (.091)*.008 (.005) Instant Messaging.045 (.038)-.117 (.099)-.004 (.005) Facebook-.000 (.030)-.030 (.094)-.003 (.005) Twitter.035 (.058).200 (.151)-.003 (.008) Talk on phone-.008 (.036).325 (.141)*.004 (.006) Watch TV-.050 (.042).014 (.104).003 (.006) Video games-.046 (.057)-.096 (.126).004 (.007) Computer (work).035 (.031)-.269 (.101)**-.013 (.005)* Friends-.077 (.034)*.060 (.094).010 (.006)+ Family.094 (.044)*.-013 (.110)-.011 (.006)+

22. Discussion Time Use: Technology o Texting, watching TV, playing video games, & working on the computer negatively impacted sleep  Physiological and cognitive arousal  Decreased perceived sleepiness  Exposure to blue light (Higuchi et al., 2005; Weaver et al., 2010; Dworak et al., 2007) o Time spent talking on the phone positively impacted sleep (hours)  Provision of immediate feedback, added emotional nuance, and opportunities for emotional expression

23. Discussion Time Use: In-person o Friends: promoted good sleep (shorter sleep latencies and higher sleep efficiency)  Emotional well-being o Family: associated with poorer sleep  Pre-bedtime routines  Arousal (Snell et al., 2007)

24. Future Research Small N limited the number of analyses (e.g., moderation by race, gender, SES) Assess content of technology use and in-person interactions Include objective measure of time use

25. Strengths Assessed a number of different technology use variables Assessed both between- and within- effects (multiple assessments across days) Objective assessments of sleep

26. Thank You Co-authors Research Assistants Participants & Parents