The DOI matches its Crossref record; 108 of the 108 references it cites were found in a registry or an index; 62 of the 138 sources its claims cite were checked for support.
Social Media and Mental Health: Benefits, Risks, and Opportunities for Research and Practice
Open accessAbstract
Social media platforms are popular venues for sharing personal experiences, seeking information, and offering peer-to-peer support among individuals living with mental illness. With significant shortfalls in the availability, quality, and reach of evidence-based mental health services across the United States and globally, social media platforms may afford new opportunities to bridge this gap. However, caution is warranted, as numerous studies highlight risks of social media use for mental health. In this commentary, we consider the role of social media as a potentially viable intervention platform for offering support to persons with mental disorders, promoting engagement and retention in care, and enhancing existing mental health services. Specifically, we summarize current research on the use of social media among mental health service users, and early efforts using social media for the delivery of evidence-based programs. We also review the risks, potential harms, and necessary safety precautions with using social media for mental health. To conclude, we explore opportunities using data science and machine learning, for example by leveraging social media for detecting mental disorders and developing predictive models aimed at characterizing the aetiology and progression of mental disorders. These various efforts using social media, as summarized in this commentary, hold promise for improving the lives of individuals living with mental disorders.
Overview
AI snapshot
Written from the paper’s full text.
TL;DR
This commentary reviews evidence that social media is widely used by people with mental illness and may support social interaction, peer support, and engagement in services, while also carrying risks for symptoms, hostile interactions, and daily life. It argues that benefits should not yet be viewed as outweighing harms and calls for safeguards, ethical attention, and further research, including digital phenotyping and machine learning.
Key findings
- Social media use is common among psychiatric populations: about 70% among middle-aged/older individuals and those with serious mental illness, 72% among peer support agency respondents, 68% daily use among first-episode psychosis, over 97% among adolescents/young adults with psychotic or mood disorders, and 98% among adolescents recruited from community mental health centers; in 2020 there were an estimated 3.8 billion social media users worldwide, half the global population.
- Potential benefits include facilitating social interaction, access to peer support networks, and promoting engagement/retention in services; in a HORYZONS pilot, 95% engaged with the peer-to-peer networking feature and there were significant reductions in depression, while PeerFIT’s private Facebook group appeared to increase engagement.
- Risks include associations between heavy/prolonged social media use and anxiety/depressive symptoms; using 7–11 platforms versus 2 or fewer was associated with 3 times greater odds of high depressive symptoms and 3.2 times greater odds of high anxiety symptoms; cyberbullying is linked to depression/anxiety, with females twice as likely to be victims; youth with moderate-to-severe depressive symptoms were more likely to report hostile comments or being “trolled” (31% vs. 14%); over one third of social media users with serious mental illness expressed privacy concerns.
- Emerging opportunities include using machine learning and digital phenotyping on Twitter/Instagram data to study depression, schizophrenia communication patterns, and illness onset/course, though ethical concerns about consent, identifiability, and stigma remain.
Methods
- This is a commentary/narrative review, not a systematic review; the authors searched Medline and Google Scholar using terms “mental health” or “mental illness” and “social media,” and searched reference lists of recent reviews and relevant studies.
- They did not perform a systematic search or apply specific inclusion criteria based on study design or type of mental disorder.
- The main analysis is a narrative synthesis of benefits, risks, and future directions, without meta-analysis or new primary data.
Limitations
- Stated: the review is not systematic or exhaustive; it only summarizes published studies, omitting private-sector or gray literature; it did not assess risk of bias; few intervention studies reported negative findings, suggesting possible publication bias; and most studies were from the United States or other high-income settings, with a dearth of research in low- and middle-income countries.
- Evident and stated: many included studies are cross-sectional, making it difficult to draw conclusions about direction of causation.
- Evident: as a commentary, it relies on secondary literature and does not present original empirical findings.
Model-written summary. Check it against the paper before relying on it.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
45 No full text of the sources · 31 Supported · 23 Own interpretation · 17 Partly supported · 12 Sources not found · 6 Supported so far · 5 Own method · 2 Couldn’t confirm · 2 Own result · 1 Not checked yet · accuracy not yet measured
Every source the paper cites for this claim was checked and supports it.
In the paper
“For individuals who openly discuss mental health problems on Twitter, a study by Berry et al. (2017) found that this served as an important opportunity to seek support and to hear about the experiences of others (Berry et al., 2017).”
§ Social Media and Mental Health: Benefits, Risks, and Opportunities for Research and Practice > Social Media Use and Mental Health > Access to a Peer Support Network
What the sources say
- Supportedcites Berry et al., 2017 source
In Results, Theme 1 (page not provided), users describe receiving support and connecting with people who have similar experiences. The Discussion, Principal Findings (page not provided), likewise says Twitter allowed users to communicate with and receive support from others with similar experiences. (LLM, conf=0.90)
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
- Supported
Every source the paper cites for this claim was checked and supports it.
In the paper
“while other studies have found that some individuals may prefer to seek help for mental health concerns online rather than through in-person encounters (Batterham & Calear, 2017).”
§ Social Media and Mental Health: Benefits, Risks, and Opportunities for Research and Practice > Social Media Use and Mental Health > Facilitate Social Interaction
What the sources say
- Supportedcites Batterham & Calear, 2017 source
The Results section, “Preference for Online Programs Compared to Face-to-Face Programs” (page not provided), reports that 14.4% of participants would likely use online programs only for a personal or emotional problem. That supports the qualified claim that some individuals may prefer online help to in-person help, although face-to-face-only help was more common. (LLM, conf=0.92)
hedged- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
- Supported
Every source the paper cites for this claim was checked and supports it.
In the paper
“Individuals who self-identified as having a schizophrenia spectrum disorder responded to a survey shared through the National Alliance of Mental Illness (NAMI), and reported that visiting social media sites was one of their most common activities when using digital devices, taking up roughly 2 hours each day (Gay, Torous, Joseph, Pandya, & Duckworth, 2016).”
§ Social Media and Mental Health: Benefits, Risks, and Opportunities for Research and Practice > Social Media Use and Mental Health
What the sources say
- Supportedcites Gay, Torous, Joseph, Pandya, & Duckworth, 2016 source
The Methods section describes a NAMI-commissioned survey of people self-identifying as having schizophrenia, schizoaffective disorder, or another schizophrenia spectrum disorder; some respondents were recruited through NAMI’s mailing list and website. The Results section (Purpose of Use) lists visiting social networking sites among the most common device activities, at 2.0 hours per day. (LLM, conf=0.92)
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
- Supported
Every source the paper cites for this claim was checked and supports it.
In the paper
“In a qualitative study, participants with schizophrenia described greater anonymity, the ability to discover that other people have experienced similar health challenges, and reducing fears through greater access to information as important motivations for using the Internet to seek mental health information (Schrank, Sibitz, Unger, & Amering, 2010).”
§ Social Media and Mental Health: Benefits, Risks, and Opportunities for Research and Practice > Social Media Use and Mental Health > Facilitate Social Interaction
What the sources say
- Supportedcites Schrank, Sibitz, Unger, & Amering, 2010 source
Split into 2 atoms — 2 confirmed, 0 partially supported, 0 disputed, 0 misattributed, 0 unverifiable. Expand the claim to see per-atom verdicts.
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
- Supported
The cited sources support only part of this claim — read each source’s verdict below.
In the paper
“Recent studies have shown that individuals with mental disorders are increasingly gaining access to and using mobile devices, such as smartphones”
§ Social Media and Mental Health: Benefits, Risks, and Opportunities for Research and Practice > Social Media Use and Mental Health
What the sources say
- Partly supportedcites Firth et al., 2015 sourceExperimental — accuracy not yet measured
The Results and Discussion report that mobile-phone ownership increased over time among people with psychosis, and the Results report daily use by some phone owners. The study does not establish an increasing trend in use or smartphone ownership, and its findings on ownership are specific to psychotic disorders rather than mental disorders generally. Page numbers are not available in our copy. (LLM, conf=0.86)
- Not checked — no full text of the sourcecites Glick, Druss, Pina, Lally, & Conde, 2016 source
- Partly supportedcites Torous, Chan, et al., 2014 sourceExperimental — accuracy not yet measured
The Discussion’s Principal Findings report that 62.5% of surveyed psychiatric outpatients owned smartphones and that 70.6% were interested in using them to monitor symptoms. The paper predicts that access and engagement will grow, but its survey does not establish that ownership or actual use was increasing over time. (LLM, conf=0.86)
plaincorrelational- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
- Partly supported
The cited sources support only part of this claim — read each source’s verdict below.
In the paper
“Comparable findings were demonstrated among middle-age and older individuals with mental illness accessing services at peer support agencies, where 72% of respondents reported using social media (Aschbrenner, Naslund, Grinley, et al., 2018).”
§ Social Media and Mental Health: Benefits, Risks, and Opportunities for Research and Practice > Social Media Use and Mental Health
What the sources say
- Partly supportedcites Aschbrenner, Naslund, Grinley, et al., 2018 sourceExperimental — accuracy not yet measured
The Discussion reports that 72% of peer support agency respondents used social media. However, the Abstract Methods describes the survey population as adults aged 18 and over; the 72% figure is not reported specifically for middle-aged and older respondents. (LLM, conf=0.87)
boosted- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
- Partly supported
The cited sources support only part of this claim — read each source’s verdict below.
In the paper
“Rates of social media use among psychiatric populations have increased in recent years”
§ Social Media and Mental Health: Benefits, Risks, and Opportunities for Research and Practice > Social Media Use and Mental Health
What the sources say
- Partly supportedcites Brunette et al., 2019 sourceExperimental — accuracy not yet measured
The Discussion concludes that a growing number of people with serious mental illness use social media, supporting the direction of the claim. But it frames this as a suggestion from survey data, not a measured increase in social-media-use rates over time, and it concerns people with serious mental illness rather than psychiatric populations generally. No page number is available in our copy. (LLM, conf=0.82)
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
- Partly supported
The cited sources support only part of this claim — read each source’s verdict below.
In the paper
“participation in chat rooms may contribute to worsening symptoms in young people with psychotic disorders (Mittal, Tessner, & Walker, 2007)”
§ Social Media and Mental Health: Benefits, Risks, and Opportunities for Research and Practice > Challenges with Social Media for Mental Health > Impact on Symptoms
What the sources say
- Partly supportedcites Mittal, Tessner, & Walker, 2007 sourceExperimental — accuracy not yet measured
The Results report that adolescents who spent more time in chat rooms had more severe schizotypal personality disorder (SPD) symptom ratings. The Discussion raises the possibility that reducing Internet access might reduce symptom severity, but says experimental studies are needed; it does not establish that chat-room participation worsens symptoms. The study concerns adolescents with SPD, not young people with psychotic disorders generally. (LLM, conf=0.85)
hedgedconditional- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
- Partly supported
The cited sources support only part of this claim — read each source’s verdict below.
In the paper
“To date, this program has demonstrate preliminary effectiveness for meaningfully reducing cardiovascular risk factors that contribute to early mortality in this patient group (Aschbrenner, Naslund, Shevenell, Kinney, et al., 2016)”
§ Social Media and Mental Health: Benefits, Risks, and Opportunities for Research and Practice > Social Media Use and Mental Health > Promote Engagement and Retention in Services
What the sources say
- Partly supportedcites Aschbrenner, Naslund, Shevenell, Kinney, et al., 2016 sourceExperimental — accuracy not yet measured
The Results report significant reductions in weight and BMI, with 28% of participants achieving clinically significant weight loss. The Introduction links obesity to reduced life expectancy and weight loss to lower cardiovascular risk. But fitness did not improve significantly, and the Conclusions say randomized trials are still needed to determine whether the intervention reduces obesity-related cardiovascular risk; the claim is broader than the pilot’s findings. (LLM, conf=0.84)
boosteddirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
- Partly supported
Every source the paper cites for this claim was checked and supports it.
In the paper
“A computational study of mental health awareness campaigns on Twitter provides further support with inspirational posts and tips being the most shared (Saha et al., 2019).”
§ Social Media and Mental Health: Benefits, Risks, and Opportunities for Research and Practice > Social Media Use and Mental Health > Access to a Peer Support Network
What the sources say
- Supportedcites Saha et al., 2019 source
The Discussion states that personal tips and inspiration were the most widely shared content categories by volume and reach in the Twitter campaign studied. This supports the citing sentence’s paraphrase. (LLM, conf=0.93)
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
- Supported
- It may state two separate claims as one. 37
- Probably not a substantial claim. 12
The sources with a verdict support this claim; the rest weren’t checked yet, have no full text we could read, or their verdicts aren’t rated yet.
In the paper
“Other exploratory studies have found that many of these individuals with mental illness appear to turn to social media to share their personal experiences, seek information about their mental health and treatment options, and give and receive support from others facing similar mental health challenges”
§ Social Media and Mental Health: Benefits, Risks, and Opportunities for Research and Practice > Introduction
What the sources say
hedgedcorrelational- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
The cited sources support only part of this claim — read each source’s verdict below.
In the paper
“Studies have reported that individuals living with a range of mental disorders, including depression, psychotic disorders, or other severe mental illnesses, use social media platforms at comparable rates as the general population”
§ Social Media and Mental Health: Benefits, Risks, and Opportunities for Research and Practice > Introduction
What the sources say
- Partly supportedcites Aschbrenner, Naslund, Grinley, et al., 2018 sourceExperimental — accuracy not yet measured
The Results and Discussion report that social media use among peer support agency users with mental illness was comparable to use in the general adult population; the Discussion gives a rate of 72%. Our copy does not establish the claimed range up to 97% among younger people or comparable rates separately for depression and psychotic disorders. The supplied verbatim citing sentence does not include the age-specific percentages. (LLM, conf=0.86)
- Partly supportedcites M. L. Birnbaum et al., 2017 sourceExperimental — accuracy not yet measured
The Introduction (page unavailable) says that individuals with mental illness regularly use social media and that youth with newly diagnosed schizophrenia use it frequently. It does not establish comparable usage rates with the general population or report the claimed 70%–97% age-based range. (LLM, conf=0.85)
- Partly supportedcites Brunette et al., 2019 sourceExperimental — accuracy not yet measured
Split into 2 atoms — 0 confirmed, 2 partially supported, 0 disputed, 0 misattributed, 0 unverifiable. Expand the claim to see per-atom verdicts.
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
- Partly supported
Every source the paper cites for this claim was checked and supports it.
In the paper
“However, there remains uncertainty regarding the risks and potential harms of social media for mental health (Orben & Przybylski, 2019), and how best to weigh these concerns against potential benefits.”
§ Social Media and Mental Health: Benefits, Risks, and Opportunities for Research and Practice > Introduction
What the sources say
- Supportedcites Orben & Przybylski, 2019 source
The Discussion (pp. 11–14) says the possible negative impact of adolescents’ digital technology use on well-being remains uncertain: the analyses cannot establish whether technology use causes lower well-being. The Methods (p. 18) explicitly include social media use among the technology measures. The citation is attached to uncertainty about harms, not to the subsequent question of weighing harms against benefits. (LLM, conf=0.88)
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
- Supported
Every source the paper cites for this claim was checked and supports it.
In the paper
“Similarly, in a sample of adolescents ages 13-18 recruited from community mental health centers, 98% reported using social media, with YouTube as the most popular platform, followed by Instagram and Snapchat (Aschbrenner et al., 2019).”
§ Social Media and Mental Health: Benefits, Risks, and Opportunities for Research and Practice > Social Media Use and Mental Health
What the sources say
- Supportedcites Aschbrenner et al., 2019 source
The Results report 121 respondents aged 13–18 at four community mental health centers and state that 98% used social media. Table 1 in the Results ranks YouTube first (90%), followed by Instagram (78%) and Snapchat (76%). (LLM, conf=0.95)
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
- Supported
The cited sources support only part of this claim — read each source’s verdict below.
In the paper
“For adolescents and young adults ages 12 to 21 with psychotic disorders and mood disorders, over 97% reported using social media, with average use exceeding 2.5 hours per day (M. L. Birnbaum et al., 2017).”
§ Social Media and Mental Health: Benefits, Risks, and Opportunities for Research and Practice > Social Media Use and Mental Health
What the sources say
- Partly supportedcites M. L. Birnbaum et al., 2017 sourceExperimental — accuracy not yet measured
The Introduction says youth with newly diagnosed schizophrenia use social media frequently and spend several hours per day online. It does not give the claimed figure of over 97%, specify ages 12–21, or report average use exceeding 2.5 hours per day for a group including youth with mood disorders. No page number is available in our copy. (LLM, conf=0.86)
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
- Partly supported
Every source the paper cites for this claim was checked and supports it.
In the paper
“In a content analysis of comments posted to YouTube by individuals who self-identified as having a serious mental illness, there appeared to be opportunities to feel less alone, provide hope, find support and learn through mutual reciprocity, and share coping strategies for day-to-day challenges of living with a mental illness (Naslund, Grande, Aschbrenner, & Elwyn, 2014).”
§ Social Media and Mental Health: Benefits, Risks, and Opportunities for Research and Practice > Social Media Use and Mental Health > Access to a Peer Support Network
What the sources say
- Supportedcites Naslund, Grande, Aschbrenner, & Elwyn, 2014 source
Split into 2 atoms — 2 confirmed, 0 partially supported, 0 disputed, 0 misattributed, 0 unverifiable. Expand the claim to see per-atom verdicts.
hedgedcorrelational- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
- Supported
Every source the paper cites for this claim was checked and supports it.
In the paper
“as reflected in a study with data from 2017 showing comparable rates of social media use (approximately 70%) among individuals with serious mental illness in treatment as compared to low-income groups from the general population (Brunette et al., 2019).”
§ Social Media and Mental Health: Benefits, Risks, and Opportunities for Research and Practice > Social Media Use and Mental Health
What the sources say
- Supportedcites Brunette et al., 2019 source
The Methods section says the survey included 403 people in treatment for serious mental illness in fall 2017. The Results report 67.9% social-media use and say respondents’ Facebook use was similar to that of low-income adults. Page numbers are unavailable in our copy. (LLM, conf=0.92)
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
- Supported
Every source the paper cites for this claim was checked and supports it.
In the paper
“females were twice as likely to be victims of cyberbullying compared to males (Alhajji, Bass, & Dai, 2019)”
§ Social Media and Mental Health: Benefits, Risks, and Opportunities for Research and Practice > Challenges with Social Media for Mental Health > Facing Hostile Interactions
What the sources say
- Supportedcites Alhajji, Bass, & Dai, 2019 source
The Abstract reports that, in a nationally representative sample of US students in grades 9–12, females were twice as likely to report cyberbullying victimization as males. The Discussion likewise describes females as having twice the odds of being cyberbullied. (LLM, conf=0.94)
plaincorrelational- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
- Supported
Every source the paper cites for this claim was checked and supports it.
In the paper
“while stigmatizing content was rare, it was actually the most spread (re-tweeted) demonstrating that harmful content can travel quickly on social media (Saha et al., 2019)”
§ Social Media and Mental Health: Benefits, Risks, and Opportunities for Research and Practice > Challenges with Social Media for Mental Health > Facing Hostile Interactions
What the sources say
- Supportedcites Saha et al., 2019 source
The Discussion states that stigmatizing content was relatively small in volume compared with other categories but had the highest engagement in retweets and favorites per Twitter post. It also describes this as higher social diffusion, supporting the claim about its spread. (LLM, conf=0.94)
boostedcorrelational- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
- Supported
The cited sources support only part of this claim — read each source’s verdict below.
In the paper
“A recent review by Biagianti et al (2018) found that peer-to-peer support appeared to offer feasible and acceptable ways to augment digital mental health interventions for individuals with psychotic disorders by specifically improving engagement, compliance, and adherence to the interventions, and may also improve perceived social support (Biagianti, Quraishi, & Schlosser, 2018).”
§ Social Media and Mental Health: Benefits, Risks, and Opportunities for Research and Practice > Social Media Use and Mental Health > Promote Engagement and Retention in Services
What the sources say
- Partly supportedcites Biagianti, Quraishi, & Schlosser, 2018 sourceExperimental — accuracy not yet measured
Split into 2 atoms — 1 confirmed, 1 partially supported, 0 disputed, 0 misattributed, 0 unverifiable. Expand the claim to see per-atom verdicts.
hedgedconditional- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
- Partly supported
The cited sources support only part of this claim — read each source’s verdict below.
In the paper
“This may partly be driven by the detrimental effects of screen time on mental health, including increased severity of anxiety and depressive symptoms, which have been well documented (Stiglic & Viner, 2019).”
§ Social Media and Mental Health: Benefits, Risks, and Opportunities for Research and Practice > Challenges with Social Media for Mental Health > Impact on Symptoms
What the sources say
- Partly supportedcites Stiglic & Viner, 2019 sourceExperimental — accuracy not yet measured
The Results section (Mental health and well-being) reports moderately strong evidence of an association between screen time and depressive symptoms, but only weak evidence for an association with anxiety. The paper describes associations rather than establishing that screen time causes increased symptom severity, so the claim overstates the evidence, particularly for anxiety. (LLM, conf=0.88)
hedgeddirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
- Partly supported
The cited sources support only part of this claim — read each source’s verdict below.
In the paper
“Importantly, individuals with serious mental illness have also emphasized that any mental health intervention on social media would need to be moderated by someone with adequate training and credentials, would need to have ground rules and ways to promote safety and minimize risks, and importantly, would need to be free and easy to access.”
§ Social Media and Mental Health: Benefits, Risks, and Opportunities for Research and Practice > Discussion
What the sources say
- Partly supportedcites Naslund et al., 2017 sourceExperimental — accuracy not yet measured
The Conclusions (page unavailable) say that privacy risks, harms, and overall safety are critical considerations for social-media mental health programs. But the paper does not report participants emphasizing trained and credentialed moderation, ground rules, or free and easy access as requirements; the Discussion reports their interest in such programs, not those conditions. (LLM, conf=0.83)
hedged- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. It may state two separate claims as one.
- Partly supported
The cited sources support only part of this claim — read each source’s verdict below.
In the paper
“Precautions are needed to ensure that data is not made identifiable in ways that were not originally intended by the user who posted the content, as this could place an individual at risk of harm or divulge sensitive health information (Webb et al., 2017; Williams, Burnap, & Sloan, 2017).”
§ Social Media and Mental Health: Benefits, Risks, and Opportunities for Research and Practice > Future Directions for Social Media and Mental Health
What the sources say
- Partly supportedcites Webb et al., 2017 sourceExperimental — accuracy not yet measured
Section 4.3, p. 6, says users may not expect their tweets to be republished for other audiences and that revealing their identities could put them at risk of harm. Section 4.4, p. 7, explains how published tweet text can reveal a user's identity through search. The passages do not support the specific claim about divulging sensitive health information. (LLM, conf=0.87)
- Supportedcites Williams, Burnap, & Sloan, 2017 source
The Introduction (page unavailable) warns that publishing Twitter content can make sensitive personal information identifiable beyond its intended context and expose users to harm. The Discussion (page unavailable) gives suicidal ideation and inferred emotional distress as examples of sensitive information that, if published with identifiable posts, may stigmatise users or cause further harm. (LLM, conf=0.90)
hedgedconditional- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
- Partly supported
The cited sources support only part of this claim — read each source’s verdict below.
In the paper
“these individuals are more likely to experience mental health problems and more likely to experience online victimization when compared to heterosexual individuals (Mereish, Sheskier, Hawthorne, & Goldbach, 2019)”
§ Social Media and Mental Health: Benefits, Risks, and Opportunities for Research and Practice > Discussion
What the sources say
- Partly supportedcites Mereish, Sheskier, Hawthorne, & Goldbach, 2019 sourceExperimental — accuracy not yet measured
The Results ('Depressive symptoms, suicidality, substance use, and victimisation') report higher rates of depressive symptoms and cyber victimisation among Black sexual minority young people than among heterosexual participants. The claim says 'gender minorities,' but the study compares groups by sexual orientation, not gender-minority status. (LLM, conf=0.88)
hedgedcorrelational- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
- Rests on an assumption: Less is known about use of social media for seeking support for mental health concerns among gender minorities.
- Partly supported
Every source the paper cites for this claim was checked and supports it.
In the paper
“The reported risks of social media use were directly related to many aspects of everyday life, including concerns about threats to employment, fear of stigma and being judged, impact on personal relationships, and facing hostility or being hurt (Naslund & Aschbrenner, 2019)”
§ Social Media and Mental Health: Benefits, Risks, and Opportunities for Research and Practice > Challenges with Social Media for Mental Health > Consequences for Daily Life
What the sources say
- Supportedcites Naslund & Aschbrenner, 2019 source
The Results (Qualitative Findings; page not provided) identify the same four categories of concerns reported by participants: threats to employment, fear of stigma and being judged, impact on personal relationships, and facing hostility or being hurt. The study frames these specifically as privacy concerns about using social media for mental health among people with serious mental illness. (LLM, conf=0.95)
plaincorrelational- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
- Supported
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“We found many studies that highlighted risks associated with social media use for individuals living with mental illness; however, few studies of programs or interventions reported negative findings, suggesting the possibility that negative findings may go unpublished.”
§ Social Media and Mental Health: Benefits, Risks, and Opportunities for Research and Practice > Discussion
hedgedcorrelational- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
What the paper did — it cites no source for this, so there is none to check. The quote shows it is in the paper.
In the paper
“Given this broad objective, we did not perform a systematic search of the literature and we did not apply specific inclusion criteria based on study design or type of mental disorder.”
§ Social Media and Mental Health: Benefits, Risks, and Opportunities for Research and Practice > Introduction
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. It may state two separate claims as one.
A claim is checked only against the cited paper’s full text, never its abstract, and none is available for its sources.
In the paper
“Studies have found that individuals with serious mental disorders (Spinzy, Nitzan, Becker, Bloch, & Fennig, 2012) as well as young adults with mental illness (Gowen, Deschaine, Gruttadara, & Markey, 2012) appear to form online relationships and connect with others on social media as often as social media users from the general population.”
§ Social Media and Mental Health: Benefits, Risks, and Opportunities for Research and Practice > Social Media Use and Mental Health > Facilitate Social Interaction
What the sources say
hedged- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
In the paper
“mental disorders can experience symptoms including passive social withdrawal, blunted affect and attentional impairment, as well as active social avoidance due to hallucinations or other concerns (Hansen, Torgalsbøen, Melle, & Bell, 2009)”
§ Social Media and Mental Health: Benefits, Risks, and Opportunities for Research and Practice > Social Media Use and Mental Health > Facilitate Social Interaction
What the sources say
- Not checked — no full text of the sourcecites Hansen, Torgalsbøen, Melle, & Bell, 2009 source
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
In the paper
“among individuals with serious mental illness receiving community-based mental health services, a recent study found equivalent rates of social media use as the general population, even exceeding 70% of participants (Naslund, Aschbrenner, & Bartels, 2016).”
§ Social Media and Mental Health: Benefits, Risks, and Opportunities for Research and Practice > Social Media Use and Mental Health
What the sources say
- Not matchedcites Naslund, Aschbrenner, & Bartels, 2016
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
- Not matched
In the paper
“Bauer et al. (2013) reported that the main interest in online self-help forums for patients with bipolar disorder was to share emotions with others, allow exchange of information, and benefit by being part of an online social group (Bauer, Bauer, Spiessl, & Kagerbauer, 2013).”
§ Social Media and Mental Health: Benefits, Risks, and Opportunities for Research and Practice > Social Media Use and Mental Health > Access to a Peer Support Network
What the sources say
- Not checked — no full text of the sourcecites Bauer, Bauer, Spiessl, & Kagerbauer, 2013 source
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
In the paper
“Initial studies from 2015 found that nearly half of a sample of psychiatric patients were social media users, with greater use among younger individuals (Trefflich, Kalckreuth, Mergl, & Rummel-Kluge, 2015)”
§ Social Media and Mental Health: Benefits, Risks, and Opportunities for Research and Practice > Social Media Use and Mental Health
What the sources say
- Not checked — no full text of the sourcecites Trefflich, Kalckreuth, Mergl, & Rummel-Kluge, 2015 source
plaincorrelational- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
In the paper
“Specifically, different forms of support emerged, including ‘informational support’ about medication use or contacting mental health providers, ‘esteem support’ involving positive comments for encouragement, ‘network support’ for sharing similar experiences, and ‘emotional support’ to express understanding of a peer’s situation and offer hope or confidence (Chang, 2009).”
§ Social Media and Mental Health: Benefits, Risks, and Opportunities for Research and Practice > Social Media Use and Mental Health > Access to a Peer Support Network
What the sources say
- Not checked — no full text of the sourcecites Chang, 2009 source
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
In the paper
“In 2020, there are an estimated 3.8 billion social media users worldwide, representing half the global population (We Are Social, 2020).”
§ Social Media and Mental Health: Benefits, Risks, and Opportunities for Research and Practice > Social Media Use and Mental Health
What the sources say
- Not matchedcites We Are Social, 2020
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
hedged- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it. It may state two separate claims as one.
- Not matched
In the paper
“More recently, in a review of online social networking in people with psychosis, Highton-Williamson et al (2015) highlight that an important purpose of such online connections was to establish new friendships, pursue romantic relationships, maintain existing relationships or reconnect with people, and seek online peer support from others with lived experience (Highton-Williamson et al., 2015).”
§ Social Media and Mental Health: Benefits, Risks, and Opportunities for Research and Practice > Social Media Use and Mental Health > Access to a Peer Support Network
What the sources say
- Not checked — no full text of the sourcecites Highton-Williamson et al., 2015 source
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
In the paper
“with interactions being more fluid, and within the control of users, thereby overcoming possible social anxieties linked to in-person interaction (Indian & Grieve, 2014).”
§ Social Media and Mental Health: Benefits, Risks, and Opportunities for Research and Practice > Social Media Use and Mental Health > Facilitate Social Interaction
What the sources say
- Not checked — no full text of the sourcecites Indian & Grieve, 2014 source
hedgeddirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
In the paper
“Recent studies have reported negative effects of social media use on mental health of young people, including social comparison pressure with others and greater feeling of social isolation after being rejected by others on social media (Rideout & Fox, 2018).”
§ Social Media and Mental Health: Benefits, Risks, and Opportunities for Research and Practice > Challenges with Social Media for Mental Health > Impact on Symptoms
What the sources say
- Not matchedcites Rideout & Fox, 2018
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
plaincorrelational- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
- Not matched
In the paper
“Importantly, the majority of participants (95%) in this study engaged with the peer-to-peer networking feature of the program, with many reporting increases in perceived social connectedness and empowerment in their recovery process (Alvarez-Jimenez et al., 2013).”
§ Social Media and Mental Health: Benefits, Risks, and Opportunities for Research and Practice > Social Media Use and Mental Health > Promote Engagement and Retention in Services
What the sources say
- Not checked — no full text of the sourcecites Alvarez-Jimenez et al., 2013 source
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
In the paper
“Yet, reported negative effects were an increased exposure to harm, social isolation, depressive symptoms and bullying (Best et al., 2014).”
§ Social Media and Mental Health: Benefits, Risks, and Opportunities for Research and Practice > Challenges with Social Media for Mental Health
What the sources say
- Not checked — no full text of the sourcecites Best et al., 2014 source
plaincorrelational- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
In the paper
“In a review of 43 studies in young people, many benefits of social media were cited, including increased self-esteem, and opportunities for self-disclosure (Best, Manktelow, & Taylor, 2014).”
§ Social Media and Mental Health: Benefits, Risks, and Opportunities for Research and Practice > Challenges with Social Media for Mental Health
What the sources say
- Not checked — no full text of the sourcecites Best, Manktelow, & Taylor, 2014 source
plaindirectn = 43- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“It is hard to estimate a number needed to treat or harm today given the nascent state of research, which means the patient and clinician need to weigh the choice on a personal level.”
§ Social Media and Mental Health: Benefits, Risks, and Opportunities for Research and Practice > Future Directions for Social Media and Mental Health
plain- Asserted: passes — The authors put it forward as true.
- Checkable: fails — It may be too vague to check against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. It may be too vague to check against evidence.
What the paper did — it cites no source for this, so there is none to check. The quote shows it is in the paper.
In the paper
“Additionally, we only summarized published studies, and as a result, any reports from the private sector or websites from different organizations using social media or other apps containing social media-like features would have been omitted.”
§ Social Media and Mental Health: Benefits, Risks, and Opportunities for Research and Practice > Discussion
hedged- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“As we consider future research directions, the near ubiquitous social media use also yields new opportunities to study the onset and manifestation of mental health symptoms and illness severity earlier than traditional clinical assessments.”
§ Social Media and Mental Health: Benefits, Risks, and Opportunities for Research and Practice > Future Directions for Social Media and Mental Health
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim.
- Rests on an assumption: Social media use is near ubiquitous.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Despite the global reach of social media platforms, there is a dearth of research on the impact of these platforms on the mental health of individuals in diverse settings, as well as the ways in which social media could support mental health services in lower income countries where there is virtually no access to mental health providers.”
§ Social Media and Mental Health: Benefits, Risks, and Opportunities for Research and Practice > Discussion
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
- Rests on an assumption: Social media platforms have global reach.
- Rests on an assumption: Lower income countries have virtually no access to mental health providers.
What the paper did — it cites no source for this, so there is none to check. The quote shows it is in the paper.
In the paper
“Importantly, as we aimed to address this broad objective, we did not conduct a systematic review of the literature.”
§ Social Media and Mental Health: Benefits, Risks, and Opportunities for Research and Practice > Discussion
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“existing research looking at duration of exposure cannot account for the impact of specific types of content on mental health and is insufficient to fully understand the effects of using these platforms on mental health”
§ Social Media and Mental Health: Benefits, Risks, and Opportunities for Research and Practice > Challenges with Social Media for Mental Health > Facing Hostile Interactions
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Studies reporting on the threats of social media for individuals with mental illness are mostly cross-sectional, making it difficult to draw conclusions about direction of causation.”
§ Social Media and Mental Health: Benefits, Risks, and Opportunities for Research and Practice > Discussion
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: unclear — It is unclear why the paper says it holds.
It may state two separate claims as one.
In the paper
“female respondents were more likely to search online for information about depression or anxiety, and to try to connect with other people online who share similar mental health concerns, when compared to male respondents (Rideout & Fox, 2018)”
§ Social Media and Mental Health: Benefits, Risks, and Opportunities for Research and Practice > Discussion
What the sources say
- Not matchedcites Rideout & Fox, 2018
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
plaincorrelational- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
- Not matched
What the paper did — it cites no source for this, so there is none to check. The quote shows it is in the paper.
In the paper
“Another notable limitation is that we did not assess risk of bias in the studies summarized in this commentary.”
§ Social Media and Mental Health: Benefits, Risks, and Opportunities for Research and Practice > Discussion
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it.
What the paper did — it cites no source for this, so there is none to check. The quote shows it is in the paper.
In the paper
“Therefore, the studies reported here are not exhaustive, and there may be additional relevant studies that were not included.”
§ Social Media and Mental Health: Benefits, Risks, and Opportunities for Research and Practice > Discussion
hedged- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it. It may state two separate claims as one.
In the paper
“This aligns with growing emphasis on the need for greater integration of digital psychiatry, including apps, smartphones, or wearable devices, into patient care and clinical services through institution-wide initiatives and training clinical providers (Hilty, Chan, Torous, Luo, & Boland, 2019).”
§ Social Media and Mental Health: Benefits, Risks, and Opportunities for Research and Practice > Future Directions for Social Media and Mental Health
What the sources say
- Not checked — no full text of the sourcecites Hilty, Chan, Torous, Luo, & Boland, 2019 source
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it.
In the paper
“especially as these countries face a disproportionate share of the global burden of mental disorders, yet account for the majority of social media users worldwide (Naslund et al., 2019).”
§ Social Media and Mental Health: Benefits, Risks, and Opportunities for Research and Practice > Discussion
What the sources say
- Not matchedcites Naslund et al., 2019
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it. It may state two separate claims as one.
- Not matched
In the paper
“lesbian, gay, bisexual or transgender individuals frequently use social media for searching for health information and may be more likely compared to heterosexual individuals to share their own personal health experiences with others online (Rideout & Fox, 2018)”
§ Social Media and Mental Health: Benefits, Risks, and Opportunities for Research and Practice > Discussion
What the sources say
- Not matchedcites Rideout & Fox, 2018
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
hedgedcorrelational- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
- Not matched
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“As the field of digital mental health advances, the wide reach, ease of access, and popularity of social media platforms could be used to allow individuals in need of mental health services or facing challenges of mental illness to access evidence-based treatment and support.”
§ Social Media and Mental Health: Benefits, Risks, and Opportunities for Research and Practice > Conclusion
hedgedconditional- Asserted: passes — The authors put it forward as true.
- Checkable: fails — It may be too vague to check against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. It may be too vague to check against evidence.
- Rests on an assumption: Social media platforms have global reach.
The paper relies on this without support.
Social media platforms offer near continuous opportunities to connect and interact with others, regardless of time of day or geographic location.
“Social media platforms offer near continuous opportunities to connect and interact with others, regardless of time of day or geographic location.”
The paper relies on this without support.
Social media does not require the immediate responses necessary in face-to-face communication.
“Because social media does not require the immediate responses necessary in face-to-face communication”
The paper relies on this without support.
Social media is widely used among individuals living with mental illness.
“With the widespread use of social media among individuals living with mental illness combined with the potential to facilitate social interaction and connect with supportive peers, as summarized above, it may be possible to leverage the popular features of social media to enhance existing mental health programs and services.”
The paper relies on this without support.
The effects of social media on psychiatric symptoms for individuals living with more severe mental illnesses have received less attention.
“For individuals living with more severe mental illnesses, the effects of social media on psychiatric symptoms have received less attention.”
The paper relies on this without support.
Few studies have specifically explored the dangers of social media use from the perspectives of individuals living with mental illness.
“While few studies have specifically explored the dangers of social media use from the perspectives of individuals living with mental illness”
The paper relies on this without support.
Less is known about use of social media for seeking support for mental health concerns among gender minorities.
“Less is known about use of social media for seeking support for mental health concerns among gender minorities”
The paper relies on this without support.
The associations between social media use and mental health symptoms observed in the summarized studies reflect causal effects of social media use.
“Studies reporting on the threats of social media for individuals with mental illness are mostly cross-sectional, making it difficult to draw conclusions about direction of causation.”
The paper relies on this without support.
Social media use is near ubiquitous.
“As we consider future research directions, the near ubiquitous social media use also yields new opportunities to study the onset and manifestation of mental health symptoms and illness severity earlier than traditional clinical assessments.”
The paper relies on this without support.
There is a gap in clinical knowledge about the impact of social media on mental health.
“Given the gap in clinical knowledge about the impact of social media on mental health, clinicians should be aware of the many potential risks so that they can inform their patients, while remaining open to the possibility that their patients may also experience benefits through use of these platforms.”
The paper relies on this without support.
Patients increasingly show interest in accessing mental health information or services through social media.
“As patients increasingly show interest in accessing mental health information or services through social media, it will be necessary for health systems to recognize social media as a potential avenue for reaching or offering support to patients.”
The paper relies on this without support.
Social media platforms have global reach.
“Despite the global reach of social media platforms, there is a dearth of research on the impact of these platforms on the mental health of individuals in diverse settings, as well as the ways in which social media could support mental health services in lower income countries where there is virtually no access to mental health providers.”
The paper relies on this without support.
Lower income countries have virtually no access to mental health providers.
“Despite the global reach of social media platforms, there is a dearth of research on the impact of these platforms on the mental health of individuals in diverse settings, as well as the ways in which social media could support mental health services in lower income countries where there is virtually no access to mental health providers.”
The paper relies on this without support.
Mental illness is a socially stigmatizing health condition.
“For instance, data is typically captured from social media platforms without the consent or awareness of users (Bidargaddi et al., 2017), which is especially crucial when the data relates to a socially stigmatizing health condition such as mental illness (Guntuku, Yaden, Kern, Ungar, & Eichstaedt, 2017).”
The paper relies on this without support.
Many individuals may feel embarrassed or reluctant to talk to their clinicians about using social media to find mental health information out of concerns of being judged or dismissed.
“Alternatively, many individuals may feel embarrassed or reluctant to talk to their clinicians about using social media to find mental health information out of concerns of being judged or dismissed.”
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
The source backs part of the claim, not all of it — or backs it for a different population, condition or comparison.
In the citing paper
“For teens already experiencing social anxiety, the ability to curate and control online interactions may reinforce avoidance behaviors, leading to greater isolation and increased stress during in-person exchanges [46].”
From The Impact of Social Media & Technology on Child and Adolescent Mental Health (2025) · cites this paper as [46]
Experimental — accuracy not yet measuredThe source backs part of the claim, not all of it — or backs it for a different population, condition or comparison.
In the citing paper
“Online mental health communities provide peer encouragement, psychoeducation, and accessible coping strategies, offering support for individuals struggling with anxiety and depression [46].”
From The Impact of Social Media & Technology on Child and Adolescent Mental Health (2025) · cites this paper as [46]
Experimental — accuracy not yet measuredThe cited source says what the claim attributes to it.
In the citing paper
“Online help-seeking seems related to increased anonymity, accessibility, and inclusivity [31], and social media shows benefits for offering mental health care [32].”
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
Each contradiction between two passages listed here was confirmed by an independent check.
Rated minor: it would not touch a result — a value no result rests on, a p-value that stays on the same side of the significance level, or a conflict that is clerical, resolved elsewhere in the paper, or outside its own findings.
In the paper
§ Social Media and Mental Health: Benefits, Risks, and Opportunities for Research and Practice > Social Media Use and Mental Health > Promote Engagement and Retention in Services
“(Lal, Nguyen, & Theriault, 2018)”
§ Social Media and Mental Health: Benefits, Risks, and Opportunities for Research and Practice > References
“Lai S, Nguyen V, & Theriault J (2018). Seeking mental health information and support online”
Citations
Cites
The Lancet Commission on global mental health and sustainable development
Patel, V., Saxena, S., Lund, C., Thornicroft, G., Baingana, F., Bolton, P., Chisholm, D., Collins, P. Y., Cooper, J. L., Eaton, J., et al. (2018) · The Lancet · doi:10.1016/s0140-6736(18)31612-x · Cited by 3,692
Social psychological aspects of computer-mediated communication
Kiesler, S., Siegel, J., & McGuire, T. W. (1984) · American Psychologist · doi:10.1037/0003-066x.39.10.1123 · Cited by 2,630
Moorhead, S. A., Hazlett, D. E., Harrison, L., Carroll, J. K., Irwin, A., & Hoving, C. (2013) · Journal of Medical Internet Research · doi:10.2196/jmir.1933 · Cited by 2,517 · cited 4×
“…or misleading health information shared on social media and that social media users may not be aware of misleading information or conflicts of interest especially when the platforms promote popular content regardless of whether it is from a trustworthy source (Moorhead et al. 2013; Ventola 2014).”
BackgroundInfluentialAndreassen, C. S., Billieux, J., Griffiths, M. D., Kuss, D. J., Demetrovics, Z., Mazzoni, E., & Pallesen, S. (2016) · Psychology of Addictive Behaviors · doi:10.1037/adb0000160 · Cited by 2,095
Twenge, J. M., Joiner, T. E., Rogers, M. L., & Martin, G. N. (2018) · Clinical Psychological Science · doi:10.1177/2167702617723376 · Cited by 1,705 · cited 4×
“…(Andreassen et al. 2016; Berry et al. 2018; Best et al. 2014; Feinstein et al. 2013; Kross et al. 2013; Lin et al. 2016; Mittal et al. 2007; Stiglic and Viner 2019; Twenge and Campbell 2018; Twenge et al. 2018; Vannucci et al. 2017; Woods and Scott 2016) 2) Facing hostile interactions •…”
BackgroundInfluentialFacebook Use Predicts Declines in Subjective Well-Being in Young Adults
Kross, E., Verduyn, P., Demiralp, E., Park, J., Lee, D. S., Lin, N., Shablack, H., Jonides, J., & Ybarra, O. (2013) · PLoS ONE · doi:10.1371/journal.pone.0069841 · Cited by 1,596
Predicting Depression via Social Media
Choudhury, M. D., Gamon, M., Counts, S., & Horvitz, E. (2021) · Proceedings of the International AAAI Conference on Web and Social Media · doi:10.1609/icwsm.v7i1.14432 · Cited by 1,583 · cited 1×
“Specifically, conversations on Twitter have been analyzed to characterize the onset of depression (De Choudhury et al. 2013) as well as detecting users’ mood and affective states (De Choudhury et al. 2012), while photos posted to Instagram can yield insights for predicting depression (Reece and…”
BackgroundThe association between adolescent well-being and digital technology use
Orben, A., & Przybylski, A. K. (2019) · Nature Human Behaviour · doi:10.1038/s41562-018-0506-1 · Cited by 1,500
Twenge, J. M., & Campbell, W. K. (2018) · Preventive Medicine Reports · doi:10.1016/j.pmedr.2018.10.003 · Cited by 1,304
Woods, H. C., & Scott, H. (2016) · Journal of Adolescence · doi:10.1016/j.adolescence.2016.05.008 · Cited by 1,302
Cited by
Sorted by citations
Items 601–700 of 750
Aprisandani, D., & Setiawan, E. B. (2025) · International Conference on Information Technology and Computing (ICITCOM) · doi:10.1109/icitcom66635.2025.11265402
A Machine Learning Approach to Detecting and Classifying English Tweets
Alahmad, A. A., Aman, A. H. M., Qamar, F., et al. (2025) · International Conference on Cyber Resilience (ICCR) · doi:10.1109/iccr67387.2025.11291896
Kim, I. B., Choi, J., Park, S.-C., Koike, S., Kwon, J. S., Kim, E., Choi, H. S., Lee, J. Y., & Lee, Y. S. (2024) · Figshare · doi:10.6084/m9.figshare.24647333
Kim, I. B., Choi, J., Park, S.-C., Koike, S., Kwon, J. S., Kim, E., Choi, H. S., Lee, J. Y., & Lee, Y. S. (2024) · Figshare · doi:10.6084/m9.figshare.26645722
Kim, I. B., Choi, J., Park, S.-C., Koike, S., Kwon, J. S., Kim, E., Choi, H. S., Lee, J. Y., & Lee, Y. S. (2024) · Figshare · doi:10.6084/m9.figshare.26645725
Svetlak, M., Budíková, B., & Malatincová, M. (2025) · doi:10.2196/preprints.86383
Znaczenie wychowania do inteligencji emocjonalnej we współczesnym świecie
Knopp, K. A. (2025) · Psychologia Wychowawcza · doi:10.71358/pw.2607
Prediction and Monitoring of Human Being Mental Health Using Machine Learning Classifiers
Gantayet, R., Patro, S. P., & Padhy, N. (2025) · International Conference on Emerging Trends in Networks and Computer Communications (ETNCC) · doi:10.1109/etncc66224.2025.11299804
Williams, K., Lobban, F. A., & Chamberlain, E. (2025) · JMIR Human Factors · doi:10.2196/80717
Relationship Between Resiliency and Perceived Social Support in Adults With ADHD
Shibasaki, A., & ISHII, Y. (2025) · The Japanese Journal of Special Education · doi:10.6033/tokkyou.22a035
Rahi, B., & Arohi, A. (2026) · International Journal of Adolescence and Youth · doi:10.1080/02673843.2025.2610642 · Cited by 2
Galindo, C. D., Lopez, A., Avendaño, D. O., Ruiz, L. G., & Osorno, I. (2026) · Cureus · doi:10.7759/cureus.101014
Makki, R. (2025) · Physical Activity in Children · doi:10.61882/pach.2025.549827.1071
POYRAZER, M., Mühürdaroğlu, A. M., Çelik, M. E., Gökbulut, P., & Fırat, S. N. (2025) · doi:10.2196/preprints.90401
Shaluhiyah, Z., Qatrannada, S. A., Mahato, R. K., Agushybana, F., Handayani, S., Afriyanto, D. F., Rani, U., V, & Sulistyorini, D. (2026) · Frontiers in Big Data · doi:10.3389/fdata.2025.1717592
Ford, K., Jampaklay, A., Vapattanawong, P., Lucktong, A., Tangchonlatip, K., Yakoh, K., & Chamratrithirong, A. (2026) · Conflict and Health · doi:10.1186/s13031-026-00750-z · Cited by 1
Bouchillon, B. C. (2026) · Telematics and Informatics · doi:10.1016/j.tele.2026.102375
Prado, A. D. S., Hug, J., Eckert, M., Wundrack, R., Saee, S., Pougin, J., Kohls, E., & Rummel‐Kluge, C. (2026) · Child Abuse & Neglect · doi:10.1016/j.chiabu.2026.107924
Penggunaan Video Parodi dalam Tuntutan Fitnah
Fauzi, N. A. A. M., & Hassan, K. H. (2026) · Kanun: Jurnal Undang-undang Malaysia · doi:10.37052/kanun.38(1)no1
Social media, absorption, and stress: Divergent paths to self-esteem
Davis, S. W., Barahmand, U., Russo, R., Antunano, M., Asamoah, J., Bernstein, C., Bass, B., & Solodar, M. (2026) · Mediterranean Journal of Social & Behavioral Research · doi:10.29333/mjosbr/17853
Su, L., Qiu, L., Zheng, W., et al. (2026) · doi:10.2196/preprints.92770
Theriault, C., Cailhol, L., Poirier, S., Berubé, F.-A., Ouellet, E., David, P., & Hudon, A. (2026) · The Canadian Journal of Psychiatry · doi:10.1177/07067437251411023 · Cited by 1
Rodriguez, D. G., Gonzalez, E., & Haggan, C. (2026) · The Family Journal · doi:10.1177/10664807261420131
Automated Mental Health Assessment using Machine Learning
Deepa, Shenoy, A., Deepthi, Rao, D., & Dharsandia, H. (2025) · International Conference on Electronics, Communication and Aerospace Technology (ICECA) · doi:10.1109/iceca66444.2025.11382798
Jackson, J., Morton, J. P. I., Kirkman, A., Harrington, T., Aledeh, M., & Kotera, Y. (2026) · Mental Health & Prevention · doi:10.1016/j.mhp.2026.200492 · Cited by 3
How depression self-disclosure shapes engagement and discourse on Chinese social media
Hongyan, D., & Gu, L. (2026) · Digital Health · doi:10.1177/20552076261425518
Li, Y. (2026) · International Journal of Inclusive Education · doi:10.1080/13603116.2026.2628735 · Cited by 1
Liu, Z., Quan, Q., & Kim, S. (2026) · Frontiers in Psychology · doi:10.3389/fpsyg.2026.1700690
Sentiment-enhanced multi-class Transformer model for efficient suicide detection in Reddit texts
Yan, P., Khoei, T. T., & Singh, A. (2025) · International Conference on Electrical and Computer Engineering Researches (ICECER) · doi:10.1109/icecer65523.2025.11401264
Mahmood, R., David, A., Hu, D., Alshurafa, N. I., Haux, L. M., Hester, J. D., Kiselica, A. M., Liu, S., Qiu, C., Wu, C.-Y., et al. (2026) · JMIR Formative Research · doi:10.2196/84618
Alghamdi, A. M., Alzahrani, M. A., Alomari, R. A., Alghamdi, S. A., Alzahrani, R. A., Alzahrani Faisal Lafi, B., Alghamdi, H. M., Osman, N. M., & Almawazini, A. M. (2026) · doi:10.2196/preprints.93736
Szałkowski, P. (2026) · Przegląd Socjologii Jakościowej · doi:10.18778/1733-8069.22.1.03
The Role of Social Media in Youth-Led Protest
Manoharan, G. (2026) · IGI Global eBooks · doi:10.4018/979-8-3373-5581-8.ch004
Sex Differences in Social Media Addiction: The Mediating Effects of Social Media Use Motives
Lim, Y.-J. (2026) · ALPHA PSYCHIATRY · doi:10.31083/ap46105 · Cited by 1
Kearns, A., Mulvenna, M. D., Bond, R., & Moorhead, A. (2026) · Behaviour and Information Technology · doi:10.1080/0144929x.2026.2636693 · Cited by 1
Sazzed, S., Azade, R. S., Dehan, F. N., & Pial, M. E. R. (2025) · IEEE International Conference on Big Data (BigData) · doi:10.1109/bigdata66926.2025.11400847
Khandelwal, A. (2025) · Boletim da Sociedade Paranaense de Matemática · doi:10.5269/bspm.78406
Ladis, I., & Teachman, B. A. (2026) · Behaviour Research and Therapy · doi:10.1016/j.brat.2026.105007
Digital Media/Social Platforms and Mental Illness in Young Adult Literature
Richmond, K. J., & Olan, E. L. (2026) · doi:10.1093/9780191945540.003.0015
Social media groups could foster mental health self-efficacy through social identification
de Siqueira, A. U. B., Montiel, C., Doré, I., & Cárdenas, D. (2026) · BMC Psychology · doi:10.1186/s40359-026-04319-6
More, P. B., & Tiwari, V. (2026) · International Journal of Computational Intelligence and Applications · doi:10.1142/s1469026826300028
El reto de la educación física inclusiva en época de pandemia
Ruíz, H. T. (2025) · Lúdica Pedagógica · doi:10.17227/ludica.num41-22963
Demuyakor, J. (2026) · Fudan Journal of the Humanities and Social Sciences · doi:10.1007/s40647-026-00465-8
Lagun, N. (2026) · Research Square · doi:10.21203/rs.3.rs-9157969/v1
Li, Y., Liu, Z., & Liu, F. (2026) · doi:10.2196/preprints.96331
#MentalHealthDiagnosis and Self-Diagnosis: Harmful or Helpful on TikTok
Ju, R., Field‐Springer, K., Liu, Z., & Chandler, E. (2026) · Health Communication · doi:10.1080/10410236.2026.2652419
Depression classification based on automatic ontology generation and natural language processing
Goga, N., Vasilăţeanu, A., Popa, R. C., Popovici, A.-F., Popovici, R., Goga, M., Todea, D., Eni, A., & Hadăr, A. (2026) · Frontiers in Psychology · doi:10.3389/fpsyg.2026.1780802
Mabodi, R., Mbunge, E., Makaba, T., & Ntshingila, N. (2026) · Applied Sciences · doi:10.3390/app16073489 · Cited by 1
Harren, N. (2022) · theses.fr (ABES) · doi:10.70675/35c7d92cz534bz4cd2za939zfc1fa0155592
El-Ashry, A. M., Khedr, M. A., El‐Sayed, M. M., Tawfik, A. F., & Fatah, N. K. A. E. (2026) · Geriatric Nursing · doi:10.1016/j.gerinurse.2026.104054
Tekin, E. G., Taş, İ., Özsoy, E., & Griffiths, M. D. (2026) · Australian Psychologist · doi:10.1080/00050067.2026.2636263
Anilionytė, M., & Mikuličiūtė, V. (2026) · Psichologija · doi:10.15388/psichol.2026.75.5
Examining the Impact of Social Media Usage on the Mental Health of Youth in India
Chatare, R., Taori, D., & Dhurvey, U. B. (2025) · Splint International Journal Of Professionals · doi:10.5958/2583-3561.2025.00042.7
ARTIFICIAL INTELLIGENCE FOR EARLY DETECTION OF MENTAL HEALTH DISORDERS USING SOCIAL MEDIA DATA
Kaur, S. (2026) · International Journal of Engineering Technologies and Management Research · doi:10.29121/ijetmr.v13.i4.2026.1756 · Cited by 2
Jiang, D. (2026) · PLoS ONE · doi:10.1371/journal.pone.0347294 · Cited by 1
TOMIZAWA, R., Minakawa, S., & Gappmayer, G. (2026) · Journal of Occupational Science · doi:10.1080/14427591.2026.2651448 · Cited by 1
ŞENER, Y., Uzdıl, N., & Günaydın, Y. (2026) · Global Nursing Insights · doi:10.31125/globnursinsights.1760449
Özdemir, S., & Meriç, M. (2026) · Hemşirelikte araştırma geliştirme dergisi. · doi:10.69487/hemarge.1643765
Bozkuş-Demir, O., & Saylık, F. Z. (2026) · Klinik Psikoloji Dergisi · doi:10.57127/kpd.26024438.1658246
Seo, Y., & Nakada, Y. (2026) · Computers in Human Behavior Artificial Humans · doi:10.1016/j.chbah.2026.100313 · Cited by 1
De «fucking panza mileurista a millonario»: trabajo, disciplina y éxito en la manosfera
Martínez, L. M. (2026) · Estudios sobre el Mensaje Periodístico · doi:10.5209/esmp.107038
Jia, M., Cheng, J., Ju, R., & Zhu, J. (2026) · Journal of Communications In Healthcare · doi:10.1080/17538068.2026.2672325
Hao, Z., Yuan, M., Zhong, Z., Yan, M., Gao, Y., Mou, L., Song, C., Yang, K., Zhou, J., Liu, J., et al. (2026) · Frontiers in Communication · doi:10.3389/fcomm.2026.1816274
Dijital Stres ve Dijital Tükenmişlik Profili Üzerine Bir Araştırma
Çöllü, E. F. (2026) · Selçuk Üniversitesi Sosyal Bilimler Meslek Yüksekokulu dergisi · doi:10.29249/selcuksbmyd.1808881
Enhancing digital wellbeing in Saudi Arabia: pathways identified by societal stakeholders
Aljuboori, D., Kim, K., Saquib, J., Alomairah, S. A., Clary, L. K., Carras, M. C., Tuijnman, A., van Rooij, A. J., Albeyahi, F. S., Saquib, N., et al. (2026) · Frontiers in Human Dynamics · doi:10.3389/fhumd.2026.1760043
Cipriani, M., Notsu, H., Vaidya, S., Castillo, J., Hau, C., Li, S., Xia, W., Yacoub, D., Zhou, S. (., Birnbaum, M. L., et al. (2026) · Schizophrenia Bulletin Open · doi:10.1093/schizbullopen/sgag023
Self-citationFacial Expression Analysis for Understanding Emotional States in Cognitively Impaired Individuals
Akoliya, G. C., Sarode, V., Duche, R. N., et al. (2026) · SN Computer Science · doi:10.1007/s42979-026-04981-y
Carter, C. J., Noke, H., & Manninen, K. (2026) · International Small Business Journal Researching Entrepreneurship · doi:10.1177/02662426261436357
The Impact of Social Media Use on the Mental Health of Adolescents
AlSayyadi, K. A. H. A. (2026) · Emerald Group Publishing Limited eBooks · doi:10.1108/978-1-83708-686-320261020
Yu, S., Qian, L., & Wang, H. (2026) · JMIR Nursing · doi:10.2196/91498 · Cited by 1
Transmission of Food and Body Messages Across Generations: A Thematic Analysis
Dates, M., D’Aniello, C., Bryant, A., & Marmo, S. (2026) · Contemporary Family Therapy · doi:10.1007/s10591-026-09786-y
Ercengiz, M., Makas, S., Bayraktar, M., Şata, M., & Uğur, E. (2026) · BMC Psychology · doi:10.1186/s40359-026-04961-0
The interface between mental health and human rights: past, present and future
Martin, F., Bansal, N., Rana, S. S., MacManus, D., Forrester, A., & Sen, P. (2026) · BJPsych Advances · doi:10.1192/bja.2026.10210
Bakshi, K., & Gait, P. (2026) · Research Square · doi:10.21203/rs.3.rs-9952939/v1 · Cited by 1
Thampuratti, M., Tank, M., & Chandrani, K. V. (2026) · Indian Journal of Private Psychiatry · doi:10.5005/jp-journals-10067-0210
From Screens to Green Spaces: Lifestyle Influences on Mental Health among UniKL RCMP Students
Yee, K. T., Nwe, T. M., Lwin, S., Mg, T. M., Nwet, M., Aye, W. M., Than, T., Thwin, M. M., Khaing, M. M., & Yi, M. S. (2026) · Research Journal of Pharmacy and Technology · doi:10.52711/0974-360x.2026.00387
Scale development and validation of social media mindfulness: evidence from Chinese Douyin users
Li, M., & Chen, H. (2026) · Frontiers in Psychology · doi:10.3389/fpsyg.2026.1660076
Artificial Intelligence and Mental Health Discourse: Methodological Reflections for Nursing Practice
Wu, C.-J. J., & Hung, P. C. K. (2026) · Issues in Mental Health Nursing · doi:10.1080/01612840.2026.2665756
Li, W., Zhu, J., Guo, J., Chang, B., Zhang, J., Ma, Y., Hou, J., & Li, S. (2026) · Research Square · doi:10.21203/rs.3.rs-9485738/v1
Bilston, A., Daniels, S., Hasan, Y., & Schweizer, S. (2026) · JMIR Mental Health · doi:10.2196/94753 · Cited by 1
Life, death, and 280 characters: a hashtag analysis of #AssistedSuicide on X (2015–2025)
Opriessnig, E., Litvinova, O., Ma, Z.-L., Hua, Y., Mohanasundaram, A., Kletečka-Pulker, M., Atanasov, A., & Wochele-Thoma, T. (2026) · Frontiers in Digital Health · doi:10.3389/fdgth.2026.1744855 · Cited by 1
Bristol, N. M., Batallantes, F. J. P., Bacolod, E. N. C., Banzuela, J. R. B., & Serrano, S. R. (2026) · Journal of Health Communication · doi:10.1080/10810730.2026.2691986
Uğur, N. G., & Bayram, İ. (2026) · Frontiers in Psychiatry · doi:10.3389/fpsyt.2026.1839044
Statharakos, N., Papadopoulou, E., Vlontaki, V., Statharakou, A., & Moutos, D. (2026) · IGI Global eBooks · doi:10.4018/979-8-3373-8387-3.ch006
Shrivastava, S., Shrivastava, J., & Talreja, D. (2026) · Journal of Integrative Science and Societal Impact · doi:10.29121/jissi.v2.i1.2026.71 · Cited by 1
Methods in Reddit-Based Suicide Research: A Scoping Study
Hickam, S. M., Sursely, A. M., & Ghahramanlou‐Holloway, M. (2026) · Journal of Technology in Behavioral Science · doi:10.1007/s41347-026-00650-2
Li, Y., Liu, Z., & Liu, F. (2026) · JMIR Mental Health · doi:10.2196/96331 · Cited by 1
Israel, U. N., & Kpaduwa, I. (2026) · African Quarterly Social Science Review · doi:10.51867/aqssr.3.2.32
Wolf, J., Reinhard, M. A., Bodenbender, A., Boger, S., Kunz, J. I., Goerigk, S. A., Jobst, A., Padberg, F., & Grosse-Wentrup, F. (2026) · American Journal of Psychotherapy · doi:10.1176/appi.psychotherapy.20260004
(Dis)Connected: Youth and Parental Expectations of Australia’s Social Media Ban
Horwood, S., Torjinski, M., Hemmings, S. A., & Jarman, H. K. (2026) · International Journal of Human-Computer Interaction · doi:10.1080/10447318.2026.2695938 · Cited by 2
A Critical Review of AI-Powered Automation in Higher Education Undergraduate Hospitality Programs
Singh, P., Rohit, M. S., Maheshwari, N., & Singh, V. (2026) · Advances in computational intelligence and robotics book series · doi:10.4018/979-8-3373-7665-3.ch007
Increased Immersion in the Digital Multiverse: Implications for Adult Motivation
Dede, C. (2026) · IEEE Transactions on Learning Technologies · doi:10.1109/tlt.2026.3711900 · Cited by 1
BelhadjYoussef, M. H. (2026) · Journal of Nonprofit & Public Sector Marketing · doi:10.1080/10495142.2026.2701269
Prescott, J., Rathbone, A. L., Clarry, L., & Hanley, T. (2025) · University of Law: Publications Repository
THE ROLE OF SOCIAL MEDIA IN SHAPING MENTAL HEALTH: A REVIEW OF POSITIVE AND NEGATIVE EFFECTS
Kamrowska, M., Swiech, J., Apanasewicz, K., Kopacki, F., Szczeblewska, W., Jaskot, D., Marzec, J., Kita, N., Sztenc, N., & Broniszewska, P. (2026) · International Journal of Innovative Technologies in Social Science · doi:10.31435/ijitss.2(50).2026.5484
Mpinami, L. A., Sebata, N., & Chirongoma, S. (2026) · Springer eBooks · doi:10.1007/978-3-032-16069-0_5
Sanchez, L. H., Rondán, Y. Y. M., Poma, M. G. P., Rodríguez, I. A. C., Abanto-Ramírez, C. D., & Turpo-Chaparro, J. E. (2026) · Psychiatry International · doi:10.3390/psychiatryint7040157
Cherniak, A. D., Shmulewitz, D., Levitin, M. D., Skvirsky, V., Kor, A., Lev‐Ran, S., & Mikulincer, M. (2026) · International Journal of Mental Health and Addiction · doi:10.1007/s11469-026-01699-z
Metadata
- Authors
- Naslund, J. A., Bondre, A., Torous, J., & Aschbrenner, K. A.
- Affiliations
- Harvard University (US)
- Beth Israel Deaconess Medical Center (US)
- Dartmouth College (US)
- Corresponding author
- Naslund, John A.
- Venue
- Journal of Technology in Behavioral Science
- Published
- 2020-04-20
- Volume
- 5
- Issue
- 3
- Pages
- 245-257
- ISSN
- 2366-5963 (ISSN-L)
- PMC
- PMC7785056
- OpenAlex
- W3018892856
- Semantic Scholar
- 4e2eaf6dd4cdf713a8c4616007468aff3bdb0166
- Cited by
- 746
- References
- 107
- Citations by year
- 2026: 166 · 2025: 201 · 2024: 149 · 2023: 109 · 2022: 71 · 2021: 43 · 2020: 6
- FWCI
- 60.41
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- Journal of Technology in Behavioral Science (publishedVersion)
- PubMed (publishedVersion)
- PubMed Central (submittedVersion)
- Funders
- National Institute of Mental Health (U19MH113211, 1R01MH110965)
- Topics
- Social Sciences › Psychology › Social Psychology › Mental Health via Writing
- Social Sciences › Psychology › Applied Psychology › Digital Mental Health Interventions
- Social Sciences › Sociology and Political Science › Impact of Technology on Adolescents
- Keywords
- social media, mental health, peer support, mental illness, digital mental health interventions, evidence-based programs, mental disorder detection, prediction model, machine learning, data science, access to mental health care
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
A language model drew the claims from the paper on 2026-10-20, under version 3 of the claim definition (model deepseek-v4.1-flash, prompt extract-v3).
A second model labelled each claim on 2026-10-20 (model jev-1.13-20260917, definition revision gold-guideline-v0.2).
Cited sources are checked with a language model’s help (gpt-6-sol).
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review