全部 标题 作者
关键词 摘要

OALib Journal期刊
ISSN: 2333-9721
费用:99美元

查看量下载量

相关文章

更多...
PLOS ONE  2013 

A Smartphone Ecological Momentary Assessment/Intervention “App” for Collecting Real-Time Data and Promoting Self-Awareness

DOI: 10.1371/journal.pone.0071325

Full-Text   Cite this paper   Add to My Lib

Abstract:

We have designed a flexible ecological momentary assessment/intervention smartphone (EMA/EMI) “app”. We examine the utility of this app for collecting real-time data, and assessing intra-subject variability, by using it to assess how freshman undergraduates spend their time. We also explore whether its use can promote greater self-awareness. Participants were randomly divided into an experimental group, who used the app, and a control group, who did not. We used the app to collect both randomized in-the-moment data as well as end-of-day data to assess time use. Using a posttest survey we asked participants questions about how they spent time throughout the school semester. We also asked the experimental group about their experience with the app. Among other findings, 80.49% participants indicated that they became more aware of how they spent their time using the app. Corroborating this report, among the experimental group, end-of-semester self-assessment of time spent wasted, and time spent using electronics recreationally, predicted semester GPA at a strength comparable to high school GPA and ACT score (two of the best single predictors for first semester college GPA), but had no correlation among controls. We discuss the advantages and limitations of using apps, such as ours, for EMA and/or EMI.

References

[1]  Wundt W (1896) Grundriss der psychologie. Leipzig: Verlag von Wilhelm Engelmann.
[2]  Wilhelm P, Perrez M, Pawlik K (2011) Conducting research in daily life: A historical overview. In: Mehl M, Conner T, editors. Handbook of research methods for studying daily life. New York: Guilford. 108–123.
[3]  Brunswik E (1955) Representative design and probabilistic theory in a functional psychology. Psychol Rev 62: 193–217.
[4]  Hammond KR (1998) Ecological Validity: Then and Now. Available: http://www.brunswik.org/notes/essay2.htm?l. Accessed 2012 Sep 12.
[5]  Schwarz N (2007) Retrospective and concurrent self-reports: The rationale for real-time data capture. In: Stone A, Shiffman S, Atienza A, Nebeling L, editors. The science of real-time data capture: Self-reports in health research. New York: Oxford University Press. 11–26.
[6]  Hammaker EL (2012) Why researchers should think “within-person”: A Paradigmatic rationale. In: Mehl M, Conner T, editors. Handbook of research methods for studying daily life. New York: Guilford. 43–61.
[7]  Shiffman S (2009) Ecological momentary assessment (EMA) in studies of substance use. Psychol Assess 21: 486–97.
[8]  Nock MK, Prinstein MJ, Sterba SK (2009) Revealing the form and function of self-injurious thoughts and behaviours: A real-time ecological assessment study among adolescents and young adults. J Abnorm Psychol 118: 816–27.
[9]  Rutledge T, Stucky E, Dollarhide A, Shively M, Jain S, et al. (2009) A real-time assessment of work stress in physicians and nurses. Health Psychol 28: 194–200.
[10]  Myin-Germeys I, Oorschot M, Collip D, Lataster J, Delespaul P, et al. (2009) Experience sampling research in psychopathology: opening the black box of daily life. Psychol Med 39: 1533–1547.
[11]  James S, Brumfitt S, Cowell P (2009) The influence of communication situation on self-report in people who stutter. Int J Speech Lang Pathol 11: 34–44.
[12]  Johansen B, Wedderkopp N (2010) Comparison between data obtained through real-time data capture by SMS and a retrospective telephone interview. Chiropr & Manual Ther 18: 1–7.
[13]  Axén I, Boden L, Kongsted A, Wedderkopp N, Jensen I, et al. (2012) Analyzing repeated data collected by mobile phones and frequent text messages. An example of Low back pain measured weekly for 18 weeks. BMC Med Res Methodol 12: 105–17.
[14]  Badr H, Laurenceau JP, Schart L, Basen-Engquist K, Turk D (2010) The daily impact of pain from metastatic breast cancer on spousal relationships: a dyadic electronic diary study. Pain 151: 644–54.
[15]  Mulvaney SA, Rothman RL, Dietrich MS, Wallston KA, Grove E, et al. (2011) Using mobile phones to measure adolescent diabetes adherence. Health Psychol 31: 43–50.
[16]  Hicks J, Ramanathan N, Falaki H, Longstaff B, Parameswaran K, et al. (2010) ohmage: An open mobile system for activity and experience sampling. CENS Technical Reports 100: 1–25.
[17]  Courvoisier DS, Eid M, Lischetzke T, Schreiber WH (2010) Psychometric properties of a computerized mobile phone method for assessing mood in daily life. Emotion 10: 115–24.
[18]  Murphy SL, Smith DM, Clauw DJ, Alexander NB (2008) The impact of momentary pain and fatigue on physical activity in women with osteoarthritis. Arthritis Care Res 59: 849–56.
[19]  Frates EP, Moore M, Lopez C, McMahon G (2011) Coaching for behavior change in physiatry. Am J Phys Med Rehabil 90: 1074–82.
[20]  Shiffman S, Stone AA, Huffman MR (2008) Ecological Momentary Assessment. Annu Rev Clin Psycho 4: 1–32.
[21]  Berkman ET, Dickerson J, Falk EB, Lieberman MD (2011) Using SMS text messaging to assess moderators of smoking reduction: Validating a new tool for ecological measurement of health behaviors. Health Psychol 30: 186–94.
[22]  Ferguson SG, Shiffman S (2011) Using the methods of ecological momentary assessment in substance dependence research–smoking cessation as a case study. Substance Use & Misuse 46: 87–95.
[23]  Bylsma LM, Taylor-Clift A, Rottenbergh J (2011) Emotional reactivity to daily events in major and minor depression. J Abnorm Psychol 120: 155–67.
[24]  Cook PF, McElwain CJ, Bradley-Springer LA (2010) Feasibility of a daily electronic survey to study prevention behavior with HIV-infected individuals. Res Nurs Health 33: 221–34.
[25]  MacDonnell K, Narr-King S, Murphy D, Parsons J, Huszti H (2011) Situational temptation for HIV medication adherence in High-Risk Youth. AIDS Patient Care STDs 25: 47–52.
[26]  Rizvi SL, Dimeff LA, Skutch J, Carroll D (2011) A pilot study of the DBT Coach: An interactive mobile phone application for individuals with borderline personality disorder and substance use disorder. Behav Ther 42: 589–600.
[27]  Wichers M, Hartmann J, Kramer I, Lothmann C, Peeters F, et al. (2011) Translating assess- ments of the film of daily life into person-tailored feedback interventions in depression. Acta Psychiatr Scand123: 402–3.
[28]  Trull T, Ebner-Priemer U (2012) Ambulatory assessment. Annu Rev Clin Psychol.
[29]  Stone A, Shiffman S, Schwartz J, Broderick J, Hufford M (2002) Patient non-compliance with paper diaries. BMJ 324: 1193–94.
[30]  Miller G (2012) The smartphone psychology manifesto. Perspect Psychol Sci 7: 221–237.
[31]  Cohn AM, Hunter-Reel D, Hagman BT, Mitchell J (2011) Promoting behavioral change from alcohol use through mobile technology: The future of ecological momentary assessment. Alcohol Clin Ex Res 12: 2209–15.
[32]  Smith A (March, 2012). 46% of American adults are smartphone owners: Smartphone users now outnumber users of more basic mobile phones within the national adult population. Pew Internet & American Life Project. Washington, DC: Pew Research Center.
[33]  Bolger N, Davis A, Rafaeli E (2003) Diary methods: Capturing life as it is lived. Annu Rev Psychol 54: 579–616.
[34]  Noble J, Sawyer R (2002) Predicting different levels of academic success in college using high school GPA and ACT composite score. Iowa City, IA: ACT, Inc.
[35]  Robbins S, Allen J, Casillas A, Peterson CH, Le H (2006) Unraveling the differential effects of motivational and skills, social, and self-management measures from traditional predictors of college outcomes. J Educ Psychol 98: 598–616.
[36]  Korotitsch WJ, Nelson-Gray RO (1999) An overview of self-monitoring research in assessment and treatment. Psychol Assess 2: 415–25.
[37]  Barta WD, Tennen H, Litt MD (2011) Measurement reactivity in diary research. In: Mehl M, Conner T, editors. Handbook of research methods for studying daily life. New York: Guilford. 108–123.
[38]  Ravert RD, Calix SI, Sullivan MJ (2012) Using mobile phones to collect daily experience data from college undergraduates. J Coll Student Dev 51: 343–352.
[39]  Soul Shift Resources: A Measure of a Life Transformed. Available: http://www.collegewes.com/soulshift. Accessed 2013 May 13.
[40]  Demiralp E, Thompson R, Mata J, Jaeggi S, Buschkuehl M, et al. (2012) Feeling blue or turquoise? Emotional differentiation in major depressive disorder. Psychol Sci 23: 1410–16.
[41]  eMarketer: Digital Intelligence, INC (2012) Smartphones continue to gain share as US mobile usage plateaus. Available: http://www.emarketer.com/Mobile/Article.?aspx?R=1008958. Accessed 2012 Sep 10.
[42]  Cisco Systems, INC (2012) Cisco visual networking index: Global mobile traffic forecast update, 2011–2016. Available: http://www.cisco.com/en/US/solutions/col?lateral/ns341/ns525/ns537/ns705/ns827/wh?ite_paper_c11-520862.html. Accessed 2012 Sep 10.
[43]  Burgin CJ, Silva PJ, Eddington KM, Kwapil TR (2012) Palm or cell? Comparing personal digital assistants and cell phones for experience sampling research. Soc Sci Comput Rev 31: 244–51.
[44]  Prochaska JO, Velicer WF (1997) The transtheoretical model of health behavior change. Am J Health Promot 12: 38–48.

Full-Text

Contact Us

service@oalib.com

QQ:3279437679

WhatsApp +8615387084133