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Patterns of Social Media Use Among Psychiatrically Hospitalized Adolescents

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Abstract

Adolescents’ use of social media (SM) has increased drastically in recent years, with more than 80% of teens now belonging to sites such as Instagram, Snapchat, and Facebook. ¹ This has critical implications for youths’ psychosocial development. Research increasingly supports a differential susceptibility model of media effects, ² whereby certain adolescents show increased risk for negative effects of SM use. Emerging research with community samples of youth suggest that mental health concerns may be one factor that heightens vulnerability to adverse SM experiences. In particular, youth with internalizing symptoms are more likely to report negative emotional responses to SM activity. ³ In addition, youth with suicidal thoughts or behaviors are more likely to experience cybervictimization, and may be at risk for exposure to suicide-related SM content. ⁴ Despite this preliminary evidence, almost no research to date has examined SM use among youth with clinically severe psychiatric presentations. This has significantly limited our understanding of a central feature in the lives of youth with mental illness. To address this limitation, we examined SM experiences among a large sample of psychiatrically hospitalized adolescents. We sought to determine the prevalence of positive and negative SM experiences in this population, and to explore differences in SM use based on diagnostic presentation.
Patient-Centered Outcomes Research Institute (PCORI), the Cancer Pre-
vention Research Institute of Texas (CPRIT), Johnson and Johnson, and
Janssen Research and Development, LLC. He has received editorial
compensation from Healthcare Global Village, Engage Health Media, and
Oxford University Press. Drs. Pop and Kinney and Mr. Grannemann report
no biomedical nancial interests or potential conicts of interest.
Correspondence to Radu Pop, PhD, University of Texas Southwestern
Medical Center, 5323 Harry Hines Boulevard, Dallas, TX 75390-9119;
e-mail: radu.pop@utsouthwestern.edu
0890-8567/$36.00/Published by Elsevier Inc. on behalf of the American
Academy of Child and Adolescent Psychiatry.
https://doi.org/10.1016/j.jaac.2019.01.019
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Am J Psychiatry. 2006;163:28-40.
Patterns of Social Media Use Among
Adolescents Who Are Psychiatrically
Hospitalized
To the Editor:
dolescentsuse of social media (SM) has
increased drastically in recent years, with more
than 80% of teens now belonging to sites such
as Instagram, Snapchat, and Facebook.
1
This has critical
implications for youthspsychosocial development.
Research increasingly supports a differential susceptibility
model of media effects,
2
whereby certain adolescents
show increased risk for negative effects of SM use.
Emerging research with community samples of youth suggest
that mental health concerns may be one factor that heightens
vulnerability to adverse SM experiences. In particular, youth
with internalizing symptoms are more likely to report negative
emotional responses to SM activity.
3
In addition, youth with
suicidal thoughts or behaviors are more likely to experience
cybervictimization, and may be at risk for exposure to suicide-
related SM content.
4
Despite this preliminary evidence,
almost no research to date has examined SM use among
youth with clinically severe psychiatric presentations. This has
signicantly limited our understanding of a central feature in
the lives of youth with mental illness. To address this limi-
tation, we examined SM experiences among a large sample of
psychiatrically hospitalized adolescents. We sought to deter-
minetheprevalenceofpositiveandnegativeSMexperiences
in this population, and to explore differences in SM use based
on diagnostic presentation.
METHOD
Participants
Participants included 433 adolescents (aged 1118 years,
mean age ¼14.6 years) who were hospitalized in a
psychiatric inpatient facility at an academic medical
hospital in the northeastern United States. Demographic
information was collected from medical records. Partici-
pants were 61.7% female; 66.5% white, 10.2% African
American, and 19.6% Hispanic/Latinx. For health in-
surance, 53.9% of participants had Medicaid, 45.4%
private insurance, and 0.7% self-pay. A total of 87.8% of
participants reported having access to a cell phone
(82.2% to a smartphone). In all, 30.7% of participants
used SM an average of 1 hour or less per day, 41.3% used
it between 2 and 5 hours, and 27.9% used it more than 5
hours. The Institutional Review Board approved this
research; informed consent was waived due to classica-
tion as a retrospective chart review, as measures were
administered during the standard admission process for
the unit.
Measures
Surveys were self-administered at the beginning of the
patients hospital stay as part of a larger battery
completed during the admission process. Measures
focused on symptoms and risk factors, with some ques-
tions related to quality improvement. A 10-item measure
of positive and negative SM experiences was developed
based on a review of prior literature (see Table S1,
available online). Participants indicated (yes/no) whether
they had had any of these experiences in the 2 weeks
prior to hospitalization. Participants completed a single
item from the Self-Injurious Thoughts and Behaviors
Interview (SITBI)
5
assessing lifetime history of a
suicide attempt. Trained masters and doctoral level
A
Journal of the American Academy of Child & Adolescent Psychiatry www.jaacap.org 635
Volume 58 / Number 6 / June 2019
LETTERS TO THE EDITOR
clinicians administered the Childrens Interview for
Psychiatric Syndromes (ChIPS)
6
to determine psychiatric
diagnoses.
Statistical Analyses
Chi-square tests compared the prevalence, in the 2 weeks
prior to hospitalization, of SM experiences by sex (Table 1).
Further analyses were then stratied by sex. For boys and
girls separately, chi-square tests were used to compare the
prevalence of these SM experiences between participants
with and without at least one prior suicide attempt in their
lifetime (Table 2), and between those with and without
internalizing disorder diagnoses (ie, any anxiety or depres-
sive disorder) (Table 3). The BenjaminiHochberg pro-
cedure
7
was applied to adjust for multiple comparisons,
while maintaining power and minimizing false negatives.
Controlling the false discovery rate at 0.05 resulted in an
adjusted critical signicance value of p¼.025.
RESULTS
The majority of youth reported positive experiences on
SM in the past 2 weeks, including using SM to distract
from difcult situations (65.4%) and receiving support or
encouragement from friends (57.0%). However, negative
emotional experiences were also common, with 37.4%
having compared themselves negatively to others on SM
and 30.7% feeling left out or excluded. These experiences
were particularly common among girls compared to boys.
In addition, among both boys and girls, youth with
internalizing diagnoses were more likely to report having
compared themselves negatively to others and having felt
excluded. A small percentage of youth had viewed content
encouraging suicide (14.8%) or self-injury (16.6%); these
behaviors were particularly common among youth with
internalizing disorders and/or lifetime history of at least
one suicide attempt.
DISCUSSION
This exploratory study offered a rare opportunity to
examine SM use among a large, diverse sample of adoles-
cents with acute psychiatric concerns. Findings indicate
high prevalence rates of both positive and negative SM
experiences in this population, especially among girls,
echoing emerging research suggesting heightened emotional
responses to SM among vulnerable youth.
1,3
In addition,
TABLE 1 Prevalence of Social Media Experiences Over Past 2 Weeks, With Comparisons by Sex
Full Sample (N ¼433) Girls (n ¼267) Boys (n ¼166)
c
2pn (%) n (%) n (%)
Social Media Used
a
Snapchat 331 (76.4) 219 (82.0) 112 (67.5) 12.04
b
.001
Text messaging 325 (75.1) 212 (79.4) 113 (68.1) 7.02
b
.008
Instagram 311 (71.8) 208 (77.9) 103 (62.0) 12.71
b
<.001
Facebook 233 (53.8) 148 (55.4) 85 (51.2) 0.74 .391
Twitter 129 (29.8) 85 (31.8) 44 (26.5) 1.39 .238
No social media used 24 (5.55) 9 (3.4) 15 (9.0) 6.28
b
.012
Negative Emotional Experiences on Social Media
Compared self negatively to others 162 (37.4) 134 (50.2) 28 (16.9) 48.53
b
<.001
Felt left out or excluded 133 (30.7) 97 (36.3) 36 (21.7) 10.31
b
.001
Positive Emotional Experiences on Social Media
Received social support or encouragement 247 (57.0) 170 (63.7) 77 (46.4) 12.48
b
<.001
Distracted self from difcult situations or emotions 283 (65.4) 207 (77.5) 76 (45.8) 45.56
b
<.001
Mental IllnessLRelated Social Media Behaviors
Viewed content encouraging self-injury 72 (16.6) 54 (20.2) 18 (10.8) 6.50
b
.011
Viewed content encouraging suicide 64 (14.8) 47 (17.6) 17 (10.2) 4.40 .036
Posted about own mental health issues 93 (21.5) 74 (27.7) 19 (11.4) 16.07
b
<.001
General Social Media Behaviors
Was bullied, harassed, or teased 86 (19.9) 67 (25.1) 19 (11.4) 11.98
b
.001
Talked to a stranger
c
176 (40.6) 119 (44.6) 57 (34.3) 4.44 .035
Got into a ght or argument 185 (42.7) 118 (44.2) 67 (40.4) 0.62 .433
Note:
a
Social media tools listed here were the top 5 most popular among participants, from a list of 10 sites.
b
Statistically signicant at p.025, as determined by BenjaminiHochberg procedure. Sensitivity analyses were run excluding those who reported
using no social media (n ¼24; 5.55%). The pattern of signicant and nonsignicant results remained the same.
c
Strangerdened as someone the participant has talked to online but has never met in person.
636 www.jaacap.org Journal of the American Academy of Child & Adolescent Psychiatry
Volume 58 / Number 6 / June 2019
LETTERS TO THE EDITOR
TABLE 2 Prevalence of Social Media Experiences Over Past 2 Weeks Among Adolescents With and Without Lifetime History of Suicide Attempt
Girls Boys
Suicide Attempt
History
a
(n ¼158)
No Suicide Attempt
History (n ¼109)
c
2p
Suicide Attempt
History
a
(n ¼72)
No Suicide Attempt
History (n ¼94)
c
2pn (%) n (%) n (%) n (%)
Negative Emotional Experiences on Social Media
Compared self negatively to others 88 (55.7) 46 (42.2) 4.70 .030 16 (22.2) 12 (12.8) 2.60 .107
Felt left out or excluded 60 (38.0) 37 (33.9) 0.45 .501 23 (31.9) 13 (13.8) 7.88
b
.005
Positive Emotional Experiences on Social Media
Received social support or encouragement 105 (66.5) 65 (59.6) 1.30 .255 40 (55.6) 37 (39.4) 4.30 .038
Distracted self from difcult situations or emotions 132 (83.5) 75 (68.8) 8.04
b
.005 38 (52.8) 38 (40.4) 2.51 .113
Mental IllnessLRelated Social Media Behaviors
Viewed content encouraging self-injury 42 (26.6) 12 (11.0) 9.70
b
.002 13 (18.1) 5 (5.3) 6.84
b
.009
Viewed content encouraging suicide 39 (24.7) 8 (7.3) 13.38
b
<.001 15 (20.8) 2 (2.1) 15.52
b
<.001
Posted about own mental health issues 53 (33.5) 21 (19.3) 6.56
b
.010 10 (13.9) 9 (9.6) 0.75 .387
General Social Media Behaviors
Was bullied, harassed, or teased 47 (29.7) 20 (18.3) 4.46 .035 11 (15.3) 8 (8.5) 1.84 .175
Talked to a stranger
c
78 (49.4) 41 (37.6) 3.61 .058 27 (37.5) 30 (31.9) 0.56 .453
Got into a ght or argument 80 (50.6) 38 (34.9) 6.51
b
.011 29 (40.3) 38 (40.4) 0.00 .985
Note:
a
Total number of participants with lifetime history of at least one suicide attempt was 230 (53.1%)
b
Statistically signicant at p.025, as determined by BenjaminiHochberg procedure. Sensitivity analyses were run excluding those who reported using no social media (n ¼24; 5.55%).
Patterns of signicant and nonsignicant results remained the same.
c
Stranger dened as someone participant has talked to online but has never met in person.
Journal of the American Academy of Child & Adolescent Psychiatry www.jaacap.org 637
Volume 58 / Number 6 / June 2019
LETTERS TO THE EDITOR
TABLE 3 Prevalence of Social Media Experiences Over Past 2 Weeks Among Adolescents With and Without Internalizing Disorder Diagnoses
Girls Boys
Internalizing
Disorder
Diagnosis
a
(n ¼233)
No Internalizing
Disorder Diagnosis
(n ¼32)
c
2p
Internalizing
Disorder
Diagnosis
a
(n ¼98)
No Internalizing
Disorder Diagnosis
(n ¼56)
c
2pn (%) n (%) n (%) n (%)
Negative Emotional Experiences on Social Media
Compared self negatively to others 126 (56.5) 3 (9.4) 24.86
b
<.001 21 (21.4) 3 (5.4) 7.00
b
.008
Felt left out or excluded 86 (38.6) 4 (12.5) 8.33
b
.004 28 (28.6) 4 (7.1) 9.94
b
.002
Positive Emotional Experiences on Social Media
Received social support or encouragement 143 (64.1) 21 (65.6) 0.027 .868 48 (49.0) 21 (37.5) 1.90 .168
Distracted self from difcult situations or emotions 182 (81.6) 15 (46.9) 19.22
b
<.001 52 (53.1) 15 (26.8) 10.01
b
.002
Mental Illness-Related Social Media Behaviors
Viewed content encouraging self-injury 51 (22.9) 0 (0.0) 9.15
b
.002 15 (15.3) 2 (3.6) 5.00
b,c
.025
Viewed content encouraging suicide 44 (19.7) 1 (3.1) 5.31
b,c
.021 14 (14.3) 1 (1.8) 6.33
b
.012
Posted about own mental health issues 65 (29.1) 6 (18.8) 1.51 .220 15 (15.3) 2 (3.6) 5.00
b,c
.025
General Social Media Behaviors
Was bullied, harassed, or teased 59 (26.5) 6 (18.8) 0.88 .349 10 (10.2) 5 (8.9) 0.07 .797
Talked to a stranger
d
105 (47.1) 9 (28.1) 4.07 .044 37 (37.8) 15 (26.8) 1.92 .166
Got into a ght or argument 103 (46.2) 11 (34.4) 1.58 .209 40 (40.8) 22 (39.3) 0.04 .852
Note:
a
The no internalizing disorder group (n ¼88) was primarily made up of youth with oppositional deant or conduct disorders (n ¼43, 48.8%), substance abuse disorders (n ¼12, 13.6%),
and attention-decit/hyperactivity disorder (n ¼12, 13.6%). Those with comorbid presentations (internalizing disorder plus other diagnoses) were included in the internalizing disorder group.
A total of 24 participants (5.55%) did not complete diagnostic interviews, and were excluded from the internalizing disorder analyses. These participants did not differ on any demographic or
study variables.
b
Statistically signicant at p.025, as determined by BenjaminiHochberg procedure.
c
Sensitivity analyses were run excluding those who reported using no social media (n ¼24; 5.55%). Patterns of signicant and nonsignicant results remained the same, with the exception of
differences in viewing content encouraging suicide among girls (p¼.033) and viewing content encouraging self-injury and posting about mental health issues among boys (p¼.032).
d
Stranger dened as someone participant has talked to online but has never met in person.
638 www.jaacap.org Journal of the American Academy of Child & Adolescent Psychiatry
Volume 58 / Number 6 / June 2019
LETTERS TO THE EDITOR
certain negative experiences (eg, comparing oneself nega-
tively to others and feeling excluded) and behaviors (eg,
viewing pro-suicide content) may be particularly common
among youth with internalizing disorders and/or a history of
suicide attempt. SM plays a signicant role in the lives of
vulnerable youth, with nearly 70% of our sample reporting
use of SM for 2 or more hours per day. Although pre-
liminary, results provide a critical starting point for under-
standing SM use in this population. Future research will be
needed to continue identifying SM experiences that may
serve as intervention targets among youth with mental
illness.
Jacqueline Nesi, PhD
Jennifer C. Wolff, PhD
Jeffrey Hunt, MD
Accepted March 5, 2019.
Drs. Nesi, Wolff, and Hunt are with the Warren Alpert Medical School of Brown
University, Providence, RI, and Bradley Hospital, Riverside, RI. Drs. Nesi and
Wolff are also with Rhode Island Hospital, Providence, RI.
This research was supported in part by a grant to Dr. Nesi from the American
Foundation for Suicide Prevention (AFSP; PDF-010517). Dr. Nesi had full access
to all the data in the study and takes responsibility for the integrity of the data
and the accuracy of the data analysis. The American Foundation for Suicide
Prevention had no role in the design and conduct of the study; collection,
management, analysis, and interpretation of the data; and preparation, review,
or approval of the manuscript; or decision to submit the manuscript for
publication. The content is solely the responsibility of the authors and does not
necessarily represent the ofcial views of AFSP.
Preliminary results were presented as a poster at the Digital Media and
Developing Minds Second National Congress and Exposition, October 1518,
2018, Cold Spring Harbor, Long Island, NY.
Disclosure: Drs. Nesi, Wolff, and Hunt report no biomedical nancial interests
or potential conicts of interest.
Correspondence to Jacqueline Nesi, PhD, De partment of Psychiatry and
Human Behavior, Alpert Medical School of Brown University, 1 Hoppin
Street, Suite 204, Providence, RI 02903; e-mail: jacqueline_nesi@brown.
edu
0890-8567/$36.00/ª2019 American Academy of Child and Adolescent
Psychiatry
https://doi.org/10.1016/j.jaac.2019.03.009
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All statements expressed in this column are those of the authors and do not
reect the opinions of the Journal of the American Academy of Child and
Adolescent Psychiatry. See the Instructions for Authors for information about
the preparation and submission of Letters to the Editor.
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LETTERS TO THE EDITOR
TABLE S1 Social Media Questionnaire
1. Do you have a cell phone or have access to a cell phone? Yes No
2. If you do have a cell phone, is it a smartphone (eg, iPhone, Android)? Yes No Doesnt Apply
(I dont have a cell phone)
3. Social mediarefers to any app, website, or electronic tool that involves social interaction. Which of the following types of social
media do you use? (Check all that apply).
Facebook | Text messaging | Instagram | Messaging apps (eg, WhatsApp, Kik) | Snapchat | Online Pinboards (eg, Pinterest) | Twitter |
Discussion boards (eg, Reddit) | Tumblr | Anonymous sharing or question apps (eg, Whisper, Ask.fm) | None of the above (I dont
use social media)
4. On average on a typical day, how much time do you spend using ANY social media? Add up all the time you spend across all apps,
websites, and other tools. If youre not sure, just take your best guess.
None (I do not use any social media) | Less than 1 hour | 1 hour | 2 hours | Between 3 and 5 hours | Between 5 and 9 hours | 10 or
more hours
5. Here are some questions about things you may have seen, done, or experienced related to social media. Please indicate whether
or not you experienced these things in the last 2 weeks.
1) I was bullied, harassed, or teased on social media. Yes No
2) I saw photos or posts on social media that made me feel left out or excluded. Yes No
3) I got into a ght or argument with someone on social media. Yes No
4) I compared myself negatively (eg, my appearance or accomplishments) to other people
on social media.
Yes No
5) I looked at content (photos, posts, blogs) that encouraged self-injury (eg, cutting). Yes No
6) I looked at content (photos, posts, blogs) that encouraged suicide. Yes No
7) I talked to someone on social media that Ive never met in person. Yes No
8) I posted about my own depression, suicidal thoughts, or other mental health issues on
social media.
Yes No
9) I received support or encouragement from friends on social media. Yes No
10) I used social media to distract myself from difcult situations or emotions. Yes No
639.e1 www.jaacap.org Journal of the American Academy of Child & Adolescent Psychiatry
Volume 58 / Number 6 / June 2019
LETTERS TO THE EDITOR
... Through social media use, many undergraduates now have a platform for showing and displaying their talents, skills, abilities with the whole wide world. Social media have also been proven to provide opportunities for to enhance the mental health of users because it facilitates social connections and peer support (Naslund, 2020) According to Nesi, et al (2019), Social connection is one of the most well-known advantages of social media with 81% of students reporting that it increases their sense of connectedness to their peers. Prior research confirms that doing so increases people's well being, boosts acceptability or a sense of belonging. ...
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Background: Online self-harming and suicidal behavior is a novel and rapidly increasing phenomenon warranting comprehensive mapping of used research methods. Aim: To identify and map how knowledge on online self-harming and suicidal behavior is gathered, including how data are collected e.g. questionnaires and interviews. Methods: The review follows the Joanna Briggs Institute Manual for Scoping Reviews in tandem with Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews. A keyword search of three electronic databases was conducted on two occasions, yielding 5422 records. Following duplicate removal, the records were screened based on the following inclusion criterions; (1) in English or Nordic language and published between 2011-2022, (2) presenting results for self-harming and/or suicidal behavior on social media and (3) using tools for either interview or questionnaire aiming at assessment of the experience of online self-harming and suicidal behavior from the perspective of the person who engages in the behavior. A total of 64 articles were included. Results: 45 used questionnaires, 17 used interviews, and two studies mixed the two approaches. 17% of the studies had made some effort to ensure validity within the questionnaires and 15.8% gave full access to the interview guide. Conclusion: Research into online self-harming and suicidal behavior is characterized by a lack of validated measurements and methodological transparency. The results emphasize a need for further development, testing, and validation of questionnaires and greater openness and reflexivity in qualitative methodology to enable cross-study comparison and advance knowledge of this complex phenomenon.
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Living in the age of information means that information is all pervasive, uncensored, unreliable, and with the potential to influence. The unfettered access to information and communication through social media is a double-edged sword in the hands of youth. The impact of this was explored from socio-cultural, and mental health perspectives. Specifically, the role of media literacy in combating the challenges posed by usage of social media were explored in this chapter. Various theories, frameworks, models, and components of media literacy were analysed. Impact of the various media literacy interventions on the youth, case studies of specific information literacy programs across regions, and other relevant critiques were reviewed and consolidated. Further to this, recommendations have been presented on creating robust in-school, and outside-school media literacy programs for the youth. Keywords: media literacy, news literacy, youth development, youth education
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Adolescents increasingly find it difficult to picture their lives without social media. Practitioners need to be able to assess risk, and social media may be a new component to consider. Although there is limited empirical evidence to support the claim, the perception of the link between social media and mental health is heavily influenced by teenage and professional perspectives. Privacy concerns, cyberbullying, and bad effects on schooling and mental health are all risks associated with this population's usage of social media. However, ethical social media use can expand opportunities for connection and conversation, as well as boost self-esteem, promote health, and gain access to critical medical information. Despite mounting evidence of social media's negative effects on adolescent mental health, there is still a scarcity of empirical research on how teens comprehend social media, particularly as a body of wisdom, or how they might employ wider modern media discourses to express themselves. Youth use cell phones and other forms of media in large numbers, resulting in chronic sleep loss, which has a negative influence on cognitive ability, school performance, and socio-emotional functioning. According to data from several cross-sectional, longitudinal, and empirical research, smartphone and social media use among teenagers relates to an increase in mental distress, self-harming behaviors, and suicidality. Clinicians can work with young people and their families to reduce the hazards of social media and smartphone usage by using open, nonjudgmental, and developmentally appropriate tactics, including education and practical problem-solving.
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In this theoretical article, we introduce the Differential Susceptibility to Media Effects Model (DSMM), a new, integrative model to improve our understanding of media effects. The DSMM organizes, integrates, and extends the insights developed in earlier microlevel media-effects theories. It distinguishes 3 types of susceptibility to media effects: dispositional, developmental, and social susceptibility. Using the analogy of a mixing console, the DSMM proposes 3 media response states that mediate media effects: cognitive, emotional, and excitative. The assumptions on which the DSMM is based together explain (a) why some individuals are more highly susceptible to media effects than others, (b) how and why media influence those individuals, and (c) how media effects can be enhanced or counteracted.
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The common approach to the multiplicity problem calls for controlling the familywise error rate (FWER). This approach, though, has faults, and we point out a few. A different approach to problems of multiple significance testing is presented. It calls for controlling the expected proportion of falsely rejected hypotheses – the false discovery rate. This error rate is equivalent to the FWER when all hypotheses are true but is smaller otherwise. Therefore, in problems where the control of the false discovery rate rather than that of the FWER is desired, there is potential for a gain in power. A simple sequential Bonferroni-type procedure is proved to control the false discovery rate for independent test statistics, and a simulation study shows that the gain in power is substantial. The use of the new procedure and the appropriateness of the criterion are illustrated with examples.
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The common approach to the multiplicity problem calls for controlling the familywise error rate (FWER). This approach, though, has faults, and we point out a few. A different approach to problems of multiple significance testing is presented. It calls for controlling the expected proportion of falsely rejected hypotheses — the false discovery rate. This error rate is equivalent to the FWER when all hypotheses are true but is smaller otherwise. Therefore, in problems where the control of the false discovery rate rather than that of the FWER is desired, there is potential for a gain in power. A simple sequential Bonferronitype procedure is proved to control the false discovery rate for independent test statistics, and a simulation study shows that the gain in power is substantial. The use of the new procedure and the appropriateness of the criterion are illustrated with examples.
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To describe the development and summarize the psychometric properties of the Children's Interview for Psychiatric Syndromes (ChIPS). ChIPS is a highly structured interview designed for use by trained lay interviewers in children aged 6-18 years. It screens for 20 Axis I disorders as well as psychosocial stressors. Questions use simple language and short sentence structure to enhance subject comprehension and cooperation. The interview is based on DSM-IV and results are presented in a concise, easy-to-interpret manner. There are both child and parent versions. The psychometric properties of each version were studied. A series of 5 studies has demonstrated the validity of the DSM-III, DSM-III-R, and DSM-IV versions of the ChIPS as well as the validity of the P-ChIPS (parent version). Administration time is relatively brief, averaging 49 minutes for inpatients, 30 minutes for outpatients, and 21 minutes for a community-based sample. ChIPS can be used as a screening instrument to maximize a clinician's efficiency, as a diagnostic instrument in clinical research, and as a training instrument to help mental health professionals learn psychiatric diagnosis. It can also be used in epidemiological research.
Social media, social life: teens reveal their social media experiences
  • V Rideout
  • M B Robb
Rideout V, Robb MB. Social media, social life: teens reveal their social media experiences. San Francisco, CA: Common Sense Media; 2018.
Digital health practices, social media use, and mental well-being among teens and young adults in the
  • V Rideout
  • S Fox
Rideout V, Fox S. Digital health practices, social media use, and mental well-being among teens and young adults in the U.S..