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Depression and Internet Use among Older Adolescents: An Experience Sampling Approach

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DOI: 10.4236/psych.2012.329112    5,411 Downloads   8,585 Views   Citations


Background: Depression is common and consequential among adolescents. Previous work has found varied relationships between depression and internet use. The purpose of this study was to examine internet use and depression by applying a rigorous assessment tool: experience sampling method (ESM). Methods: Older adolescents between the ages of 18 and 23 years were recruited from a large state university. Participants received 6 text message surveys randomly each day during a 7-day ESM campaign. Survey questions assessed whether they were currently online and for how long. Participants also completed the PHQ-9 depression survey. Calculation of internet use time included multilevel modeling and probability modeling. Analysis of covariance (ANCOVA) assessed the association between internet use and depression. Results: Among our 189 participants, the mean age was 18.9 (SD = .9), 58.8% were female and most were Caucasian (90.5%). Total daily internet use time was calculated as 66 minutes by ESM summary, 55 minutes by ESM modeling and 65 minutes by probability modeling. We found a difference in PHQ-9 scores when comparing low daily internet use (<30 minutes), regular use (30 minutes to 3 hours) and high use (>3 hours) (p = .01) with a significant U-shaped association (p = .004). The high use group had a mean PHQ-9 score of 7.3 (SD = 5.1) compared to the regular use group score of 4.9 (SD = 3.9) (p = .02). Conclusions: Results suggest a U shaped association between internet use and depression. These findings may present statistical differences that lack clinical significance.

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Moreno, M. , Jelenchick, L. , Koff, R. & Eickhoff, J. (2012). Depression and Internet Use among Older Adolescents: An Experience Sampling Approach. Psychology, 3, 743-748. doi: 10.4236/psych.2012.329112.


[1] Arroll, B., Goodyear-Smith, F., Crengle, S., Gunn, J., Kerse, N., Fish- man, T., & Hatcher, S. (2010). Validation of PHQ-2 and PHQ-9 to screen for major depression in the primary care population. The Annals of Family Medicine, 8, 348-353. doi:10.1370/afm.1139
[2] Association, A. C. H. (2009). American College Health Association: National College Health Assessment II: Reference Group Data Re- port Fall 2008. Baltimore: American College Health Association.
[3] Beck, A. T. (2008). The evolution of the cognitive model of depression and its neurobiological correlates. American Psychiatric Association, 165, 969-977. doi:10.1176/appi.ajp.2008.08050721
[4] Cameron, I. M., Cardy, A., Crawford, J. R., du Toit, S. W., Hay, S., Lawton, K., & Reid, I. C. (2011). Measuring depression severity in general practice: discriminatory performance of the PHQ-9, HADS-D, and BDI-II. British Journal of General Practice, 61, e419-426. doi:10.3399/bjgp11X583209
[5] Cameron, I. M., Reid, I. C., & Lawton, K. (2010). PHQ-9: Sensitivity to change over time. British Journal of General Practice, 60, 535- 536. doi:10.3399/bjgp10X514909
[6] Cannon, D. S., Tiffany, S. T., Coon, H., Scholand, M. B., McMahon, W. M., & Leppert, M. F. (2007). The PHQ-9 as a brief assessment of lifetime major depression. Psychological Assessment, 19, 247-251. doi:10.1037/1040-3590.19.2.247
[7] Deas, D., & Brown, E. S. (2006). Adolescent substance abuse and psychiatric comorbidities. Journal of Clinical Psychiatry, 67, e02. doi:10.4088/JCP.0706e02
[8] Eisenberg, D., Golberstein, E., & Gollust, S. E. (2007). Help-seeking and access to mental health care in a university student population. Medical Care, 45, 594-601. doi:10.1097/MLR.0b013e31803bb4c100005650-200707000-00003
[9] Gallagher, R. P. (2007). National Survey of Couseling Center Directors, 2006. URL (last checked 1 October 2010).
[10] Gangadharbatla, H. (2008). Facebook Me: Collective self-esteem, need to belong, and internet self-efficacy as predictors of the iGeneration’s attitudes toward social networking sites. Journal of Interactive Ad- vertising, 8, 5-15.
[11] Garlow, S. J., Rosenberg, J., Moore, J. D., Haas, A. P., Koestner, B., Hendin, H., & Nemeroff, C. B. (2008). Depression, desperation, and suicidal ideation in college students: Results from the American Foundation for Suicide Prevention College Screening Project at Emory University. Depression and Anxiety, 25, 482-488. doi:10.1002/da.20321
[12] Hankin, B. L., & Abramson, L. Y. (2001). Development of gender differences in depression: An elaborated cognitive vulnerability-trans- actional stress theory. Psychological Bulletin, 127, 773-796. doi:10.1037/0033-2909.127.6.773
[13] Hunt, J., & Eisenberg, D. (2010). Mental health problems and help- seeking behavior among college students. Journal of Adolescent Health, 46, 3-10. doi:10.1016/j.jadohealth.2009.08.008
[14] Hyde, J. S., Mezulis, A. H., & Abramson, L. Y. (2008). The ABCs of depression: integrating affective, biological, and cognitive models to explain the emergence of the gender difference in depression. Psy- chological Review, 115, 291-313. doi:10.1046/j.1525-1497.2001.016009606.x
[15] Kessler, R. C., Foster, C. L., Saunders, W. B., & Stang, P. E. (1995). Social consequences of psychiatric disorders I: Educational attain- ment. The American Journal of Psychiatry, 152, 1026-1032.
[16] Kroenke, K., Spitzer, R. L., & Williams, J. B. (2001). The PHQ-9: Va- lidity of a brief depression severity measure. Journal of General Internal Medicine, 16, 606-613.
[17] Lavin, M., Marvin, K., McLarney, A., Nola, V., & Scott, L. (1999). Sensation seeking and collegiate vulnerability to internet dependence. CyberPsychology & Behavior, 2, 425-430.
[18] Lenhart, A., Purcell, K., Smith, A., & Zickuhr, K. (2010). Social media and young adults. Washington, DC: Pew Internet and American Life Project.
[19] Malpass, A., Shaw, A., Kessler, D., & Sharp, D. (2010). Concordance between PHQ-9 scores and patients’ experiences of depression: A mixed methods study. British Journal of General Practice, 60, e231- 238. doi:10.3399/bjgp10X502119
[20] Manea, L., Gilbody, S., & McMillan, D. (2012). Optimal cut-off score for diagnosing depression with the Patient Health Questionnaire (PHQ-9): A meta-analysis. Canadian Medical Association Journal, 184, 191-196. doi:10.1503/cmaj.110829
[21] Martin, A., Rief, W., Klaiberg, A., & Braehler, E. (2006). Validity of the Brief Patient Health Questionnaire Mood Scale (PHQ-9) in the general population. General Hospital Psychiatry, 28, 71-77. doi:10.1016/j.genhosppsych.2005.07.003
[22] Mathers, M., Canterford, L., Olds, T., Hesketh, K., Ridley, K., & Wake, M. (2009). Electronic media use and adolescent health and well-be- ing: Cross-sectional community study. American Academy of Pediat- rics, 9, 307-314.
[23] McCarty, C. A., Kosterman, R., Mason, W. A., McCauley, E., Hawkins, J. D., Herrenkohl, T. I., & Lengua, L. J. (2009). Longitudinal associations among depression, obesity and alcohol use disorders in young adulthood. General Hospital Psychiatry, 31, 442-450. doi:10.1016/j.genhosppsych.2009.05.013
[24] Miranda, J., & Persons, J. B. (1988). Dysfunctional attitudes are mood-state dependent. Journal of Abnormal Psychology, 97, 76-79. doi:10.1037/0021-843X.97.1.76
[25] Moore, M., Ali, S., Stuart, B., Leydon, G. M., Ovens, J., Goodall, C., & Kendrick, T. (2012). Depression management in primary care: An observational study of management changes related to PHQ-9 score for depression monitoring. British Journal of General Practice, 62, 451-457. doi:10.3399/bjgp12X649151
[26] Moreno, M. A., Jelenchick, L., Koff, R., Eickhoff, J. E., Diermyer, C., & Christakis, D. A. (2012). Internet use and multitasking among older adolescents: An experience sampling approach. Computers and Human Behavior, 28, 1097-1102.
[27] O'Kearney, R., Gibson, M., Christensen, H., & Griffiths, K. M. (2006). Effects of a cognitive-behavioural internet program on depression, vulnerability to depression and stigma in adolescent males: A school-based controlled trial. Cognitive Behaviour Therapy, 35, 43-54. doi:10.1080/16506070500303456
[28] Rao, U. (2006). Links between depression and substance abuse in adolescents: Neurobiological mechanisms. American Journal of Preven- tive Medicine, 31, S161-S174. doi:10.1016/j.amepre.2006.07.002
[29] Rao, U., & Chen, L. A. (2009). Characteristics, correlates, and outcomes of childhood and adolescent depressive disorders. Dialogues in Clinical Neuroscience, 11, 45-62.
[30] Royer, H., Keller, M. L., & Heidrich, S. M. (2009). Young adolescents’ perceptions of romantic relationships. Sex Education, 9, 395-408. doi:10.1080/14681810903265329
[31] Shiffman, S., Kirchner, T. R., Ferguson, S. G., & Scharf, D. M. (2009). Patterns of intermittent smoking: An analysis using Ecological Mo- mentary Assessment. Addictive Behaviors, 34, 514-519.
[32] Shiffman, S., Stone, A. A., & Hufford, M. R. (2008). Ecological momentary assessment. Annual Review of Clinical Psychology, 4, 1-32. doi:10.1146/annurev.clinpsy.3.022806.091415
[33] Smarr, K. L., & Keefer, A. L. (2011). Measures of depression and depressive symptoms: Beck Depression Inventory-II (BDI-II), Center for Epidemiologic Studies Depression Scale (CES-D), Geriatric Depression Scale (GDS), Hospital Anxiety and Depression Scale (HADS), and Patient Health Questionnaire-9 (PHQ-9). Arthritis Care & Research, 63, S454-S466. doi:10.1002/acr.20556
[34] Smith, J. M., Alloy, L. B., & Abramson, L. Y. (2006). Cognitive vulnerability to depression, rumination, hopelessness, and suicidal ideation: Multiple pathways to self-injurious thinking. Suicide and Life-Threatening Behavior, 36, 443-454. doi:10.1521/suli.2006.36.4.443
[35] Trull, T., & Ebner-Priemer, U. (2009). Using experience sampling methods/ecological momentary assessment (ESM/EMA) in clinical assessment and clinical research: Introduction to the special section. Psychological Assessment, 21, 457-462. doi:10.1037/a0017653
[36] Vance, K., Howe, W., & Dellavalle, R. P. (2009). Social internet sites as a source of public health information. Dermatologic Clinics, 27, 133-136.
[37] Zogby. (2011). The State of K-12 Cyberethics, Cybersafety and Cy- bersecurity Curriculum in the United States. The National Cyber Security Alliance.

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