Associations between online sexual solicitation and depressive symptomatology

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  • Correlates of in-person bullying behavior, a reference point for online harassment, report a significant relationship between being a victim of bullying and depressive symptomatology cross-sectionally (Hawker & Boulton, 2000; Haynie, Nansel & Eitel et al., 2001) as well as over time (Kaltiala-Heino, Rimpela, Rantanen & Rimpela, 2000).
    The majority of literature focuses on in-person sexual behavior; while different from sexual solicitation, it provides a general framework for the possible associations between depression and online sexual solicitation. Community-based research indicates depressive symptoms may be related to increased risk for subsequent sexual abuse (Boney-McCoy & Finkelohor, 1996). Further, depressive symptomatology has been linked to risky sexual practices for both males and females (Shrier, Harris, Sternberg et al., 2001). To better understand the possible associations between depression and unwanted sexual solicitation online, additional research is needed.
  • Correlates of in-person bullying behavior, a reference point for online harassment, report a significant relationship between being a victim of bullying and depressive symptomatology cross-sectionally (Hawker & Boulton, 2000; Haynie, Nansel & Eitel et al., 2001) as well as over time (Kaltiala-Heino, Rimpela, Rantanen & Rimpela, 2000).
    The majority of literature focuses on in-person sexual behavior; while different from sexual solicitation, it provides a general framework for the possible associations between depression and online sexual solicitation. Community-based research indicates depressive symptoms may be related to increased risk for subsequent sexual abuse (Boney-McCoy & Finkelohor, 1996). Further, depressive symptomatology has been linked to risky sexual practices for both males and females (Shrier, Harris, Sternberg et al., 2001). To better understand the possible associations between depression and unwanted sexual solicitation online, additional research is needed.
  • Based upon the DSM IV definition of a major depressive episode:
    Major depressive symptomatology (5+sxs & functional impairment): 5%, N=77
    Minor depressive symptomatology (3+ sxs): 14%, N=211
    Mild/no symptoms: 81%, N=1,201
  • Exploratory factor analysis identified a latent variable described as “Interactive Internet activity” (eigenvalue>1). Included variables were: using the Internet (ever) for Instant messaging, emailing, downloading files, updating a web page, connecting to a news group, visiting chat rooms, and looking up movie information; logging onto the Internet from home versus all other places; using the Internet five or more days a week; self-rated Internet expert (almost or definitely) versus being less skilled; and importance of Internet to self (very, extremely) versus less importance. Factor scores were used to categorize respondents into one of three groups: 1) highly interactive (1 or more SD above the mean), 2) average interactive (scores within 1 SD of the mean), and 3) less than average (1 or more SD below the mean; reference group).
    Substance use: Youth respondents were asked about the frequency of five types of substance use in the previous year, including: tobacco, alcohol, inhalants, marijuana, and all other drugs. Each was dichotomized (4 or more times vs. fewer) to put the variables on the same scale as other variables included in the exploratory factor analysis. One factor was identified (eigenvalue>1), which included all five variables. Because of the data distribution of the sum of the five variables, total scores were categorized into three groups: low users (1 or more SD below the mean; reference group), average users (scores within 1 SD of the mean), and heavy users (1 or more SD above the mean).
    Life challenge: Indication of life challenge was also included because of its association with depressive symptoms 5. Thus, interpersonal challenge was noted for young people who reported two or more versus fewer of the following events: being attacked by one person, being attacked by a gang, having something stolen from the young people, being hit by a peer, or by being ‘picked on’ by a peer in the previous year. Further, two or more life challenges (Range: 0-4) in the previous year included the following experiences: death in the immediate family, moving to a new community, caregiver divorce, and loss of job among the caregivers in the previous year.
  • Females: OR: 2.3 p=.008; minor depression: 1.83, p=.01
    Males: OR: 5.9, p<.001; minor depression: 1.3, p=.4
  • Logit estimates Number of obs = 283
    Wald chi2(2) = 5.66
    Prob > chi2 = 0.0590
    Log likelihood = -155.53989 Pseudo R2 = 0.0175
    (standard errors adjusted for clustering on id)
    ------------------------------------------------------------------------------
    | Robust
    distsext | Odds Ratio Std. Err. z P>|z| [95% Conf. Interval]
    -------------+----------------------------------------------------------------
    depmid | 1.781513 .623385 1.65 0.099 .8972994 3.537044
    dephigh | 2.271429 .9198913 2.03 0.043 1.027014 5.023677
    ------------------------------------------------------------------------------
  • Associations between online sexual solicitation and depressive symptomatology

    1. 1. Associations between online sexual solicitation and depressive symptomatology by Michele Ybarra, MPH PhD Philip Leaf, PhD American Public Health Association 131th Annual Meeting Nov 15-19 2003, San Francisco, CA Thank you to Dr. David Finkelhor and his colleagues at the University of New Hampshire for the use and guidance of the Youth Internet Safety Survey data, and to my dissertation committee for their support and direction: Dr. Philip Leaf, Dr. William Eaton, Dr. Diener-West, Dr. Steinwachs, and Dr. Cheryl Alexander * Thank you for your interest in this presentation.  Please note that analyses included herein are preliminary.  More recent, finalized analyses can be found in: Ybarra, M. L., Leaf, P. J., & Diener-West, M. (2004). Sex differences in youthreported depressive symptomatology and unwanted internet sexual solicitation. Journal Of Medical Internet Research, 6(1), e5, or by contacting CiPHR for further information.
    2. 2. Unwanted sexual solicitation online Three main types of sexual solicitation (Finkelhor, Mitchell & Wolak, 2000)    Sexual talk  15 y.o. girl: “I was on the Internet with [this] guy and all of a sudden the guy began to get perverted. I found it to be really uncomfortable.” Sexual information  11 y.o. girl: “I was talking with a man and he started to ask me about my physical features…[the] color of my eyes and bra size” Sexual acts  A 11 year old girl: “they told me to play with myself”  A 13 year old boy:” we were talking to this one girl and she wondered how big my privates were and she asked me to jack off so she could bang or something”
    3. 3. Depressive symptomatology in childhood  6% of youth at any time  Significant public health burden    (Kessler & Walters, 1998) Increased risk for adult depressive episode and other disorders (Lewinsohn, Rohde, Klein & Seeley, 1999; Kessler, McGonagle, Swartz et al., 1993) Increased health care utilization (Wu, Hoven, Bird et al., 1999) Demographic differences  Affects more females than males (Simonoff, Pickles, Meyer et al., 1997; Kazdin & Marciano, 1998; Silberg, Pickles, Rutter et al., 1999)  Risk of onset increases through adolescence 1998) (Kazdin & Marciano,
    4. 4. Links between depressive symptomatology and sexual experiences  Child sexual abuse related to major depression and other clinical problems (Kendall-Tackett, Meyer-Williams & Finkelhor, 1993; Rind, Depressive symptoms may be related to increased risk for subsequent sexual abuse (Boney-McCoy & Finkelhor, 1996). Bauserman, Tromovitch; 1997).  Depressive symptomatology has been linked to risky sexual practices for both males and females (Shrier, Harris, Sternberg et al., 2001).
    5. 5. Hypothesis Depressive symptomatology will be linked to increased likelihood for Internet sexual solicitation.
    6. 6. Youth Internet Safety Study Methodology Study design:       National probability design Cross-sectional Telephone survey Fall 1999 and Spring 2000 1,501 youth and 1 caregiver 82% participation among contacted and eligible households
    7. 7. YISS Study Methodology (cont) Inclusion criteria      10-17 years old Use Internet at least 3 times in previous 3 months (anywhere) English speaking Live in household for at least 2 weeks in previous year Caregiver and youth consent
    8. 8. Measures: Report of depressive symptomatology Major depressive-like symptomatology Minor depressive-like symptomatology Mild or no symptoms 14% 81% 5%    Major depressive-like symptomatology: 5+ sxs & functional impairment Minor depressive-like symptomatology: 3+ sxs Mild/no symptoms: <3 sxs
    9. 9. Additional measures and indicators Internet use Psychosocial indicators Demographic characteristics Interactive Internet activity*, most frequent Internet activity, average daily use, Internet Service Provider, Harassment towards others Substance use**, # of close friends, frequency of interaction, # of life challenges, # of interpersonal challenges, physical/sexual victimization Age, household income, race/ethnicity, sex
    10. 10. Additional information about Interactive Internet factor Exploratory factor analysis identified a latent variable described as “Interactive Internet activity” (eigenvalue>1). Factor scores were used to categorize respondents into one of three groups: 1) highly interactive (1 or more SD above the mean), 2) average interactive (scores within 1 SD of the mean), and 3) less than average (1 or more SD below the mean; reference group). Included variables were:  using the Internet (ever) for Instant messaging, emailing, downloading files, updating a web page, connecting to a news group, visiting chat rooms, and looking up movie information;  logging onto the Internet from home versus all other places;  using the Internet five or more days a week;  self-rated Internet expert (almost or definitely) versus being less skilled;  importance of Internet to self (very, extremely) versus less importance.
    11. 11. Additional information about substance use factor Youth respondents were asked about the frequency of use in the previous year for five types of substances:      Tobacco Alcohol Inhalants Marijuana, and All other drugs. Each was dichotomized (4 or more times vs. fewer) to put the variables on the same scale as other variables included in the exploratory factor analysis. One factor was identified (eigenvalue>1), which included all five variables. Because of the data distribution of the sum of the five variables, total scores were categorized into three groups: low users (1 or more SD below the mean; reference group), average users (scores within 1 SD of the mean), and heavy users (1 or more SD above the mean).
    12. 12. Statistical methods     Complete data requirements: N=1,489 Logistic regression Stratify by sex Parsimonious logistic regression model
    13. 13. General findings    19% of regular Internet users in the previous year (Finkelhor, Mitchell & Wolak, 2000) 25% of those sexually solicited felt very/extremely upset or afraid (Finkelhor, Mitchell & Wolak, 2000) Females are 2 times as likely to be targeted than males  77% are 14 years and older  48% of perpetrators are youth
    14. 14. Odds ratio for reporting Internet sexual solicitation Odds of online solicitation given report of depressive symptomatology 4 3.54 *** 3 2 1.55* 1 Mild or no symptoms (Reference) *p<.05; **p<.01; ***p<.001 Minor depressive-like symptoms Major depressive-like sympoms
    15. 15. Unwanted sexual solicitation by sex & depressive symptomatology Mild/no symptoms 100% *p<.05; **p<.01; ***p<.001 83% Minor symptoms Major symptoms 83% 80% 71% 70% 60% 40% 20% 19%** 12% ** 10% 16% 15% 5% *** 14% 3% 0% Not solicited Females Solicited Not solicited Males Solicited
    16. 16. Final logistic regression model of sexual solicitation: Male Internet users (n=782) Youth characteristics AOR (95% CI) P-Value Major depressive-like symptoms 2.72 (1.15, 6.40) 0.02 Minor depressive-like symptoms 0.89 (0.45, 1.77) 0.74 Mild/Absent symptomatology 1.00 (Reference) Depression Psychosocial challenge Life challenge (2+) Interpersonal victimization (2+) 2.94 (1.33, 6.50) 0.01 1.87 (1.12, 3.14) 0.02
    17. 17. Male Internet users:(Cont) Youth characteristics AOR (95% CI) P-Value Frequent 4.80 (2.47, 9.35) <0.01 Moderate 2.13 (1.16, 3.94) 0.02 Infrequent 1.00 (Reference) Chat room 3.13 (1.60, 6.11) <.001 Email 1.57 (0.84, 2.94) 0.16 Instant Messaging 1.10 (0.52, 2.32) 0.80 All other 1.00 (Reference) Internet usage characteristics Interactive Internet use Most frequent Internet activity Harasser of others online 1.80 (1.01, 3.20) 0.05
    18. 18. Final logistic regression model of sexual solicitation: Female Internet users (n=707) Youth characteristics AOR (95% CI) P-Value Major depressive-like symptoms 1.40 (0.65, 2.99) 0.39 Minor depressive-like symptoms 1.62 (0.96, 2.76) 0.07 Depression Mild/Absent symptoms 1.00 (Reference group) Psychosocial characteristics Substance use High user 2.87 (1.13, 7.34) 0.03 Average user Mild/non-user 2.09 (0.97, 4.53) 0.06 Interpersonal victimization (2+) 1.00 (Reference group) 1.82 (1.15, 2.89) 0.01
    19. 19. Female Internet users (cont) Youth characteristics AOR (95% CI) P-Value 4.07 (2.48, 6.68) <.001 Frequent 3.21 (1.79, 5.77) <.001 Moderate 2.12 (1.34, 3.37) <.001 Infrequent 1.00 (Reference group) Internet usage characteristics Harasser of others online Interactive Internet use Most frequent Internet activity Chat room 3.10 (1.62, 5.93) <.001 Instant Messaging 1.34 (0.68, 2.62) 0.39 Email 1.30 (0.81, 2.07) 0.28 All other 1.00 (Reference group)
    20. 20. Emotional distress among sexual solicitation targets % of y out h w it hin depr essiv e cat egor y 40% 35% 38% * 32% 30% 25% Maj or depressive sympt omat olgoy 21% 20% Mild/ no sxs 15% 10% 5% 0% Em ot ionally dist ressed *p<.05 Minor depressive sympt omt ology
    21. 21. Summary Self-reported major depressive symptomatology is significantly related to the report of unwanted sexual solicitation    All youth: OR = 3.53, CI: 2.19, 5.71 Among males: OR = 5.90, CI: 2.79, 12.49 Among females: OR = 2.33, CI: 1.25, 3.45 After adjusting for other significant characteristics, a relationship persists among otherwise similar males, but not females:   Males: AOR = 2.72, CI: 1.15, 6.40 Females: AOR = 1.40, CI: 0.65, 2.99
    22. 22. Study Limitations 1. 2. 3. Cross sectional data Definition of depressive symptomatology not a measure of “caseness” of major depression Potential undercounting of some populations (i.e., non-English speaking youth, households without a telephone)
    23. 23. Implications for public health researchers   The Internet is an influential environment that is shaping and affecting youth today If we are to understand and identify positive and negative risks young people face, the Internet must necessarily be on the forefront of the research agenda.
    24. 24. Implications for health practitioners   As more youth go online, Internet-related ‘conditions’ will be more common Questions about the Internet should be integrated into the well-being check
    25. 25. Future Studies Future studies should:  Investigate the temporality of events  Identify additional subpopulations of vulnerable youth
    26. 26. Conclusion Results suggest a cross-sectional relationship between self-reported depressive symptomatology and increased odds of unwanted sexual solicitation online. Understanding the complex interaction between mental health and online interactions, especially the influence of malleable characteristics such as depressive symptomatology and Internet usage, is an important area of emerging research.

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