Hostname: page-component-8448b6f56d-t5pn6 Total loading time: 0 Render date: 2024-04-24T00:10:45.769Z Has data issue: false hasContentIssue false

The association between the use of video games, social media and online dating sites, and the symptoms of anxiety and/or depression in adults aged 25 and over

Published online by Cambridge University Press:  18 January 2024

Maria El Haddad
Affiliation:
Sorbonne Université, INSERM, Institut Pierre Louis d’Epidémiologie et de Santé Publique (IPLESP), Equipe de Recherche en Epidémiologie Sociale (ERES), F75012 Paris, France
Irwin Hecker
Affiliation:
Sorbonne Université, INSERM, Institut Pierre Louis d’Epidémiologie et de Santé Publique (IPLESP), Equipe de Recherche en Epidémiologie Sociale (ERES), F75012 Paris, France
Solène Wallez
Affiliation:
Sorbonne Université, INSERM, Institut Pierre Louis d’Epidémiologie et de Santé Publique (IPLESP), Equipe de Recherche en Epidémiologie Sociale (ERES), F75012 Paris, France
Murielle Mary-Krause*
Affiliation:
Sorbonne Université, INSERM, Institut Pierre Louis d’Epidémiologie et de Santé Publique (IPLESP), Equipe de Recherche en Epidémiologie Sociale (ERES), F75012 Paris, France
Maria Melchior
Affiliation:
Sorbonne Université, INSERM, Institut Pierre Louis d’Epidémiologie et de Santé Publique (IPLESP), Equipe de Recherche en Epidémiologie Sociale (ERES), F75012 Paris, France
*
Corresponding author: Murielle Mary-Krause; Email: murielle.mary-krause@iplesp.upmc.fr
Rights & Permissions [Opens in a new window]

Abstract

People tend to spend more time in front of their screens, which can have repercussions on their social life, physical and mental health. This topic has mainly been studied in adolescents. Therefore, our study tested associations between the use of video games, social media and online dating leading to sexual relations (ODLSR), and symptoms of anxiety and/or depression among adults aged 25 and over. Data from the 2018 TEMPO cohort study were analyzed (n = 853, 65.0% women, aged 25–44, with an average of 37.4 ± 3.7 years). The exposure variables were as follows: (a) the frequency of video game use, (b) time spent on social media and (c) ODLSR. Data were analyzed using multivariate logistic regression models, adjusted for participants’ sociodemographic characteristics as well as history of mental health problems. Among the participants, 8.6% presented symptoms of anxiety and/or depression. An association between ODLSR and symptoms of anxiety and/or depression was found, especially among women. The results of this study will facilitate the improvement of support and care for adults, especially those with symptoms of anxiety and/or depression using dating applications. Future studies should investigate the determinants of using online meeting websites and their relationship with the occurrence of psychological difficulties in longitudinal studies to establish causality.

Type
Research Article
Creative Commons
Creative Common License - CCCreative Common License - BY
This is an Open Access article, distributed under the terms of the Creative Commons Attribution licence (http://creativecommons.org/licenses/by/4.0), which permits unrestricted re-use, distribution and reproduction, provided the original article is properly cited.
Copyright
© The Author(s), 2024. Published by Cambridge University Press

Impact statement

In recent years, and even more during the COVID-19 pandemic, screen use in various forms has become a frequent leisure activity among children, adolescents and adults in industrialized countries. The use of screen-based media has significant consequences on people’s lives, affecting sociability, physical activity, dietary intake and psychoactive substance use. Recently, concerns have grown about the impact of screen-based media use on individuals’ mental health. However, the majority of studies on video games and social media have focused on adolescents or young adults, with some on the elderly, but very few have evaluated associations with mental health among adults aged 25 and over. Thus, the objective of our study was to assess the relationship between video games, social media and online dating website use with symptoms of anxiety and depression in adults aged 25 and over, controlling for sociodemographic characteristics, as well as preexisting mental health problems. The findings from this study will contribute to a deeper understanding of this less-studied adult population, and will help improve the management of individuals who suffer from mental health disorders and engage with these applications. This is particularly important in a society where adults over 25 also tend to use screens widely – both professionally and recreationally – and are at risk of experiencing symptoms of anxiety and/or depression.

Introduction

In recent years, in industrialized countries, screen usage in various forms has become a common leisure activity among children, adolescents and adults (Global Web Index, 2018). In a large number of European countries, the percentage of the population using the Internet exceeds 90%, with the European average being 89.4%, and France ranking as the second European country for the Internet usage after Germany (Internet World Stats, 2022). In France, 98% of French adults aged 25–39 are connected to the Internet, and the time spent on social media has increased globally (Baromètre du numérique, 2019; Global Web Index, 2018). In 2021, an average of 1 h and 46 min was spent daily on social media in France (Gaudiaut, Reference Gaudiaut2022). According to a survey conducted in 2015 by the French National Center for Cinema and Animated Image, 7 out of 10 French people play video games (73.3%), with 80.3% of players being adult (41.6% aged 15–34 and 23.9% aged 35–49). Half of the video game users play on a daily basis, and the majority are men (Centre National du Cinéma et de l’image animée, 2015). Moreover, dating sites and apps are becoming more numerous. Few data about dating website use among French adults in the general population exist in research articles. One study conducted in 2013–2014 showed that 14% of 26–65-year-olds had used dating sites in 2013, compared to 9% in 2006, with the percentage decreasing with age from 29% among 26–30-year-olds to 3% among 61–65-year-olds (Bergström, Reference Bergström2016). A more recently published study conducted in 2018 in Normandy, France, among 1,208 teenagers aged 15–17 years showed that the weighted prevalence of active cybersexuality, including the use of dating websites, was 60% (Rousseau et al., Reference Rousseau, Asselin, Morello, Lecourtour, Brouard, Fauvet and Pizzoferrato2023). However, this study only included teenagers, and their prevalence of active cybersexuality must differ significantly from that of much older adults. Moreover, active cybersexuality in this study encompassed more than just dating website use. When studies are carried out in adults, they often concern special populations, such as people living with HIV (Jacomet et al., Reference Jacomet, Ologeanu-Taddei, Prouteau, Lambert, Linard, Bastiani and Dellamonica2020).

The use of screen-based media has consequences on people’s lives. One of the direct consequences can be on sociability, as spending time on the Internet limits face-to-face social interactions (Lissak, Reference Lissak2018; Small et al., Reference Small, Lee, Kaufman, Jalil, Siddarth, Gaddipati, Moody and Bookheimer2020). Nevertheless, it has been suggested that connecting with others online is a new form of sociability, which allows to have larger networks and easy communication (Fortunati et al., Reference Fortunati, Taipale and de Luca2013). In particular, online dating websites and applications can sometimes replace spontaneous encounters, as they are easy to use and meeting people directly in “real life” can seem simply frightening. Likewise, time spent on video games and social media could replace time and activities spent with friends or family, including physical activities and result in loneliness (van den Eijnden et al., Reference van den Eijnden, Koning, Doornwaard, van Gurp and Ter Bogt2018; Alshehri and Mohamed, Reference Alshehri and Mohamed2019). Moreover, screen time can be related to harmful health behaviors such as sedentary lifestyle, obesity, sleep disorders, eye disorders and addictive behaviors (Melchior et al., Reference Melchior, Chollet, Fombonne, Surkan and Dray-Spira2014; Biddle et al., Reference Biddle, Bengoechea García, Pedisic, Bennie, Vergeer and Wiesner2017; Cabré-Riera et al., Reference Cabré-Riera, Torrent, Donaire-Gonzalez, Vrijheid, Cardis and Guxens2019; Jaiswal et al., Reference Jaiswal, Asper, Long, Lee, Harrison and Golebiowski2019).

Recently, concerns have grown about the impact of screen-based media use on individuals’ mental health (Kaess et al., Reference Kaess, Durkee, Brunner, Carli, Parzer, Wasserman, Sarchiapone, Hoven, Apter, Balazs, Balint, Bobes, Cohen, Cosman, Cotter, Fischer, Floderus, Iosue, Haring, Kahn, Musa, Nemes, Postuvan, Resch, Saiz, Sisask, Snir, Varnik, Žiberna and Wasserman2014; Brailovskaia and Margraf, Reference Brailovskaia and Margraf2018; Ioannidis et al., Reference Ioannidis, Treder, Chamberlain, Kiraly, Redden, Stein, Lochner and Grant2018; Stockdale and Coyne, Reference Stockdale and Coyne2018; Brailovskaia et al., Reference Brailovskaia, Rohmann, Bierhoff, Schillack and Margraf2019b; Holtzhausen et al., Reference Holtzhausen, Fitzgerald, Thakur, Ashley, Rolfe and Pit2020; Cannito et al., Reference Cannito, Annunzi, Vigano, Dell’Osso, Vismara, Sacco, Palumbo and D’Addario2022). In particular, there is evidence that internet use or high screen time can be related to adolescents’ symptoms of depression, anxiety, suicidal ideation and suicide attempts (Liu et al., Reference Liu, Wu and Yao2016). In addition, young adults with high levels of rejection or with some mental health problems such as low self-esteem, or even severe mental health conditions were more likely to engage in online dating (Blackhart et al., Reference Blackhart, Fitzpatrick and Williamson2014; Hance et al., Reference Hance, Blackhart and Dew2017; Strubel and Petrie, Reference Strubel and Petrie2017; Rydahl et al., Reference Rydahl, Brund, Medici, Hansen, Straarup, Straszek and Østergaard2021). Moreover, a meta-analysis of Marino et al. among 13,929 participants with an average age of 21.93 years (range: 16.5–32.4) confirmed a positive correlation between problematic Facebook use and psychological distress, as well as a negative correlation between problematic Facebook use and well-being (Marino et al., Reference Marino, Gini, Vieno and Spada2018). However, the classification and criteria to define internet addiction are still controversial and subject to debate (Poli, Reference Poli2017). Few studies have been carried out on the consequences of internet use among adults, with the majority focusing on the elderly population. Some studies have found a reduction in depressive symptoms and suicidal ideation (Jun and Kim, Reference Jun and Kim2017; Wang et al., Reference Wang, Zhang, Feng and Wang2019) as well as an increase in life satisfaction (Lifshitz et al., Reference Lifshitz, Nimrod and Bachner2018). Unlike young people, internet use enables seniors to enjoy greater social inclusion (Forsman and Nordmyr, Reference Forsman and Nordmyr2017). Moreover, the majority of studies on video games and social media focus on adolescents or young adults, and only a few studies have evaluated the associations with mental health among adults aged 25 and over. Some studies were carried out among specific vulnerable populations, such as inpatients of a psychosomatic rehabilitation clinic (Brailovskaia et al., Reference Brailovskaia, Rohmann, Bierhoff, Margraf and Köllner2019a). Others were conducted during the COVID-19 pandemic (Gao et al., Reference Gao, Zheng, Jia, Chen, Mao, Chen, Wang, Fu and Dai2020; Brailovskaia and Margraf, Reference Brailovskaia and Margraf2022) a period when social media use increased (Masaeli and Farhadi, Reference Masaeli and Farhadi2021; Zhao and Zhou, Reference Zhao and Zhou2021).

Thus, the objective of our study was to assess the relationship between video game usage, social media engagement and online dating website use with symptoms of anxiety and/or depression in adults, controlling for sociodemographic characteristics as well as preexisting mental health problems that could potentially confound this association. Our hypothesis was that there exists an association, even among adults, between video game usage, social media engagement and online dating website use, and symptoms of anxiety and/or depression.

Methods

Sample and procedure

The TEMPO study (Epidemiological Trajectories in Population – “Trajectoires ÉpidéMiologiques en Population”) is a French longitudinal observational cohort that aims to understand lifecourse trajectories of mental health and addictive behaviors (including tobacco, alcohol, cannabis or other illicit drugs) from adolescence to adulthood (Mary-Krause et al., Reference Mary-Krause, Herranz Bustamante, Bolze, Galéra, Fombonne and Melchior2021).

This cohort started in 1991 among 2,582 persons aged 4–18 years, randomly drawn from the offspring of GAZEL cohort participants, an epidemiological cohort study comprising 20,000 volunteers employed by France’s national utilities company (Goldberg et al., Reference Goldberg, Leclerc and Zins2015). TEMPO participants were followed-up in 1999, 2009, 2011, 2015 and 2018 (Supplementary Figure 1). To counterbalance attrition, the sample was supplemented in 2011 by recruiting participants aged 18–35, whose parents also participated in the GAZEL cohort. Overall, 3,401 individuals participated in at least one TEMPO cohort study assessment between 1991 and 2018.

The present study is based on data from participants who, after being informed about the study’s purposes and agreeing to participate, completed the 2018 TEMPO cohort assessment (n = 864, 71% participation rate), which included questions about screen and media use.

The TEMPO cohort received approval from the ethical data collection supervisory bodies in France, including the Advisory Committee on the Treatment of Information for Health Research (Comité consultatif sur le traitement de l’information en matière de recherche dans le domaine de la santé, CCTIRS), and the French national committee for data protection (Commission Nationale de l’Informatique et des Libertés, CNIL, no. 908163).

Measures

Study outcome: Symptoms of anxiety and/or depression

Symptoms of anxiety and/or depression were measured using the adult self-report (ASR) (Achenbach et al., Reference Achenbach, Dumenci and Rescorla2003), which includes 41 items on symptoms of anxiety and/or depression over the preceding 12 months. The ASR is a validated standardized self-administered questionnaire assessing different dimensions of mental health across different age groups, designed to measure symptoms, that may be indicative of psychiatric disorders (Rescorla and Achenbach, Reference Rescorla, Achenbach and Maruish2004). Studying symptoms has been found to be a valid indicator of disorders, and also provides optimal statistical power for the statistical analyses (Waszczuk et al., Reference Waszczuk, Zimmerman, Ruggero, Li, MacNamara, Weinberg, Hajcak, Watson and Kotov2017). The anxious and depressed scale of the ASR has high reliability with test–retest correlations of 0.87, high internal consistency with a Cronbach’s alpha of 0.88, and high validity with a cross-validated percent of adults correctly classified as referred vs. non referred equal to 87% (sensitivity = 80%, specificity = 95%) (Achenbach and Rescorla, Reference Achenbach and Rescorla2003). The score of symptoms of anxiety and/or depression was calculated by summing all items and dichotomizing at or above the 85th percentile, which identifies individuals with potentially clinically significant symptoms (Achenbach et al., Reference Achenbach, Dumenci and Rescorla2003).

Exposure variables

Three exposure variables were studied: the frequency of playing video games, time spent on social media and online dating.

The frequency of playing video games was assessed using the following question: “In the past 6 months, how often have you played video games (on a computer, console, cell phone or tablet)?” The response options were: Never, once per month, between one and four times per month, several times a week and every day. No standard cut-off point was available for the frequency of playing video games. Therefore, the answers were grouped according to the variable distribution and divided into three categories: “Never”, “one to four times per month” and “multiple times per week”.

Social media use was assessed using the following questions: “If you have an account on the following social media or exchange platforms (Facebook, LinkedIn, YouTube, Pinterest, Google+, Copains d’Avant (a website making it possible to identify former classmates), Instagram, Viadeo, Snapchat, Twitter, Flickr, Tumblr, Myspace or Other), how many hours per day, per week, per month or per year do you spend using it?”. There was no standard cut-off point available for the time spent on social media among adults. However, it is recommended that the time spent seated should not exceed two consecutive hours to avoid sedentary lifestyle (Ministère de la santé et de la prévention, 2022). Furthermore, a study conducted among adolescents by AlSayyari et al. used a cut-off point of 2 h per day (AlSayyari and AlBuhairan, Reference AlSayyari and AlBuhairan2018). In the current study, the time spent on social media was estimated in hours per day, with an average of 1.5 h (standard deviation [SD] = 2.8). Therefore, a cut-off point of 2 h per day was chosen based on the distribution of the variable, resulting in the following categories: “Not at all”, “2 h per day or less” and “more than 2 h per day”.

Regarding online dating websites, participants answered the following question: “Have you ever had sexual relations with someone you met online on a dating website?” with answer choices: “Yes, once”, “Yes, several times”, “No, never”, “I do not wish to answer”. As only four people chose not to answer the question, making it impossible to create a separate category in the regression models, these four individuals were considered as missing variable in the regression models, and the variable was dichotomized into “Yes” and “No”. In this article, we will refer to this variable as “online dating leading to sexual relations” (ODLSR).

Covariates

Covariates included participants’ age, sex, living situation, same-sex sexual relations, socioeconomic index (SEI) and prior history of symptoms of anxiety and/or depression. As assessed in previous studies conducted among the TEMPO cohort participants, age was dichotomized into the two following categories: “under 30″ and “30 and above”. This allows us to account for the difference between young adults and older adults (Lachman, Reference Lachman2004; Barry et al., Reference Barry, Gomajee, Kousignian, Bustamante, Lakrout, Mary-Krause and Melchior2022). Living situation was defined as “lives with a partner and children”, “lives with a partner without children” or “lives alone”.

History of same-sex sexual relations was assessed by the following question: “Have you ever had sexual relations with someone of the same sex as you?” to which participants could answer “Yes, in the past 12 months”, “Yes, but not in the past 12 months”, “No, never” or “I do not wish to answer”. Answers were dichotomized into “yes”, “no” and “do not wish to answer”.

Participants’ SEI level was determined by combining four variables: educational level (< Bachelor’s degree +3 versus ≥ Bachelor’s degree +3), occupational grade (manual workers/clerks vs. other occupations), job stability over the previous 12 months (unstable vs. stable employment) and lifetime unemployment (≤ 6 months vs. >6 months). Each of these variables was coded as 0 and 2, respectively, and they were then summed to obtain an overall index. The lowest quartile was categorized as “low SEI” versus “intermediate-high SEI” (Redonnet et al., Reference Redonnet, Chollet, Fombonne, Bowes and Melchior2012).

Information on the history of symptoms of anxiety and/or depression was assessed using the ASR (Achenbach et al., Reference Achenbach, Dumenci and Rescorla2003) and obtained from TEMPO cohort waves preceding 2018, that is, 2011 or 2009, with the most recent information being taken into account. The score of symptoms of anxiety and/or depression was calculated by summing all items and dichotomizing at or above the 85th percentile, which identifies individuals with potentially clinically significant symptoms (Achenbach et al., Reference Achenbach, Dumenci and Rescorla2003).

Social support was assessed by determining the number of family members and friends that participants felt close to, using the following questions: “How many of your family members do you feel close to (i.e., you can talk to them about personal things or you can call for help)?” – “How many close friends do you have?” with answer choices “none”, “1 or 2”, “3 to 5”, “6 to 9” and “10 or more”. The last two categories were grouped together for the analysis.

The analysis also considered whether participants felt they required more assistance from those around them and from their partner, using the following questions: “Over the past 12 months, would you have needed more help from those around you?” – “In the last 12 months, would you have needed more help from your partner?” Participants could respond with “Not at all satisfied”, “Not completely satisfied”, “Neither satisfied nor dissatisfied”, “Satisfied”, “Very satisfied” or “Do not have a partner” for the second question. A summary variable regarding the need for more help was created.

Statistical analysis

To test the associations between different types of screen use and symptoms of anxiety and/or depression, we first conducted bivariate logistic regression. All covariables significantly associated with high levels of symptoms of anxiety and/or depression with a p-value ≤0.20 in this bivariate logistic regression model were included in various multivariable logistic regression models. These models included characteristics of screen use both separately and all together, in relation to participants’ symptoms of anxiety and/or depression. In additional analyses, we examined interactions between ODLSR and, (a) participants’ sex, and (b) history of same-sex sexual relations, and symptoms of anxiety and/or depression. A p-value <0.05 was considered to indicate statistical significance. All statistical analyses were performed using SAS® 9.4 software.

Results

Table 1 summarizes the participants’ characteristics. After excluding participants with missing values for symptoms of anxiety and/or depression, the analytical sample size was n = 853, and among them, 8.6% presented symptoms of anxiety and/or depression. Study participants were 25–44 years old (mean = 37.4, SD = 3.7). The majority were female (65.0%), living with a partner and children (64.6%), had never had same-sex sexual intercourse or refused to answer (91.6%), had an intermediate-high SEI level (71.9%), and 31.2% had a history of symptoms of anxiety and/or depression. Although between 45 and 50% of the participants had three to five close friends or family members, 6.7% felt they needed more help from their partner, relatives and friends.

Table 1. Characteristics of TEMPO cohort study participants according to presence or not of symptoms of anxiety and/or depression (N = 853, France, 2018)

a p-value of chi-square test or Fisher exact test when one or more expected values are less than 5.

Of the study participants, 39.0% never played video games, while 32.9% were frequent gamers (several times per week), 76.6% spent 2 h a day or less on social media, while 12.2% exceeded 2 h a day on these platforms. Additionally, 20.7% reported having had sexual intercourse with someone they met online. On average, participants spent 1.4 (SD = 2.8) h per day on social media. As shown in Table 2, the time spent on social media was significantly associated with the frequency of video game use (p < 0.001) as well as sexual intercourse with a partner met online (p < 0.001).

Table 2. Relations between video game use, time spent on social media and sexual intercourse with someone met online a dating website. (N = 853)

a p-value of chi square test.

Table 3 presents the unadjusted and adjusted associations between the frequency of video game use, time spent on social media, ODLSR and the presence of symptoms of anxiety and/or depression. In bivariate and multivariate logistic regression analyses (Table 3), compared to never users, video game users and participants who used social media did not show a higher level of symptoms of anxiety and/or depression. However, participants who reported having had sexual intercourse with someone they met online were more than 2 times more likely (95% confidence interval (CI) = 1.15–4.06) to have high levels of symptoms of anxiety and/or depression than those who did not use these websites.

Table 3. Associations between screen use and symptoms of anxiety and/or depression. (TEMPO cohort study, France, 2018; logistic regression analyses, Odds-ratio (OR) and 95% confidence interval (95% CI), N = 853)

a Adjusted for gender, living circumstances, socioeconomic index, prior history of symptoms of anxiety and/or depression; number of close family members; number of close friends and need for more help from your partner, relatives and friends.

In additional analyses stratified by sex, ODLSR was associated with symptoms of anxiety and/or depression in women (OR = 2.89; 95% CI = 1.41–5.93) but not in men (OR = 0.41; 95% CI = 0.04–4.88).

Discussion

The objective of our study was to evaluate the association between video game use, time spent on social media and ODLSR, and the likelihood of symptoms of anxiety and/or depression among adults. We found that neither the frequency of video game use nor the time spent on social media were associated with participants’ psychological difficulties. However, having met sexual partners online on a dating website was associated with an approximately twofold likelihood of symptoms of anxiety and/or depression, even after accounting for participants’ sociodemographic and mental health characteristics.

Unlike our study, which found no significant association between the use of video games or social media and symptoms of anxiety and/or depression, several past studies have shown significant associations between these characteristics among adults and adolescents (Andreassen et al., Reference Andreassen, Griffiths, Kuss, Mazzoni, Billieux, Demetrovics and Pallesen2016; Pontes, Reference Pontes2017; Brailovskaia and Margraf, Reference Brailovskaia and Margraf2018; Yoon et al., Reference Yoon, Kleinman, Mertz and Brannick2019; Brailovskaia et al., Reference Brailovskaia, Rohmann, Bierhoff, Margraf and Köllner2019a). Measures of addictive online behaviors varied according to the studies, with some of them using validated scales that may yield more precise estimates of problematic use than the questions measuring frequency and estimated time of use that we relied upon. However, it is worth noting that most prior studies were conducted among adolescents or young adults, rather than older adults (Yoon et al., Reference Yoon, Kleinman, Mertz and Brannick2019). Furthermore, when adults are studied, they are often combined with adolescents (Andreassen et al., Reference Andreassen, Griffiths, Kuss, Mazzoni, Billieux, Demetrovics and Pallesen2016; Pontes, Reference Pontes2017; Brailovskaia and Margraf, Reference Brailovskaia and Margraf2018), and associated factors as well as potential consequences may vary with age. It may be that among adults, as opposed to adolescents, video game and social network use are not associated with mental health. Although his findings showed that higher levels of attention deficit hyperactivity disorder (ADHD) traits were associated with more problematic behavior in video game, Panagiotidi founded no relationship between the frequency and duration of video game play and ADHD traits in an adult population (Panagiotidi, Reference Panagiotidi2017). Additionally, a meta-analytic study revealed that video game training has positive effects on various cognitive functions, including reaction time, attention, memory and global cognition in very old adults (Toril et al., Reference Toril, Reales and Ballesteros2014).

Our findings, indicating an association between the use of online dating websites to have sexual relations and the presence of psychological problems is consistent with previous studies that have reported associations with risk of depression, anxiety and low self-esteem (Strubel and Petrie, Reference Strubel and Petrie2017; Holtzhausen et al., Reference Holtzhausen, Fitzgerald, Thakur, Ashley, Rolfe and Pit2020; Lenton-Brym et al., Reference Lenton-Brym, Santiago, Fredborg and Antony2021). Notably, a cross-sectional survey conducted in 2018, which included 437 participants, mainly young adults, found that those who frequently used swipe-based dating applications or used them for an extended period had significantly higher levels of psychological distress and depression (Holtzhausen et al., Reference Holtzhausen, Fitzgerald, Thakur, Ashley, Rolfe and Pit2020). People with high levels of rejection sensitivity are especially likely to use online dating websites (Blackhart et al., Reference Blackhart, Fitzpatrick and Williamson2014; Hance et al., Reference Hance, Blackhart and Dew2017). And rejection sensitivity has been associated with mental health disorders, showing stability over time (Gao et al., Reference Gao, Assink, Cipriani and Lin2017), and may help explain the association between using online dating websites to have sexual relations and the presence of psychological problems. Unfortunately, the concept of rejection sensitivity was not mentioned in TEMPO. Additionally, it has also been observed that dating websites may be associated with low self-esteem and negative self-image following rejection (Strubel and Petrie, Reference Strubel and Petrie2017). Rydahl et al. showed that individuals with a history of bipolar disorder were more likely to engage in online dating (Rydahl et al., Reference Rydahl, Brund, Medici, Hansen, Straarup, Straszek and Østergaard2021). Moreover, it is difficult to know the exact causal pathway of this association. Distress may predict online dating. The literature supports this idea (Coduto et al., Reference Coduto, Lee-Won and Min Baek2020; Rydahl et al., Reference Rydahl, Brund, Medici, Hansen, Straarup, Straszek and Østergaard2021; Coffey et al., Reference Coffey, Bond, Stern and van Why2022; Mennig et al., Reference Mennig, Tennie and Barke2022) even though the exact nature of the relationship has not been proven. However, some studies indicate that among individuals with a history of affective disorders, 49% reported that the use of online dating during depressive episodes aggravated their symptoms (Rydahl et al., Reference Rydahl, Brund, Medici, Hansen, Straarup, Straszek and Østergaard2021). This suggests that the relationship between the use of online dating sites and symptoms of anxiety and/or depression could be bidirectional and should be studied in longitudinal designs to confirm or refute it.

Limitations and strengths

Prior to interpreting the findings, we need to mention several possible limitations. First, due to the design of TEMPO cohort and selective attrition, there is an over-representation of women and individuals with high socioeconomic positions among TEMPO participants. However, in our study, around half of the video game users played several times per week, which is similar to the results reported in 2015 by the French National Center for Cinema and Animated Image (Centre National du Cinéma et de l’image animée, 2015). Additionally, the average of 1 h and a half spent on social media daily was consistent with other national statistics (Gaudiaut, Reference Gaudiaut2022), making our results generalizable to the French population. In 2013, approximately 16–21% of French adults aged 31–40 connected to dating applications (Bergström, Reference Bergström2016) which is close to the percentage of TEMPO participants who had sexual intercourse with someone met on a dating website (21%). Moreover, the levels of psychological difficulties among TEMPO cohort participants are comparable to national estimates, making it an appropriate sample to study the associations between screen use and mental health.

Second, in the literature, other tools are generally used to assess video game use, such as the Problem Video Game Playing scale, or Internet Game Disorders Scale or time spent on video games, mainly conducted among adolescents (Tejeiro Salguero and Bersabé Moran, Reference Tejeiro Salguero and Bersabé Moran2002; Tejeiro et al., Reference Tejeiro, Espada, Gonzalvez and Christiansen2016; AlSayyari and AlBuhairan, Reference AlSayyari and AlBuhairan2018). It would have been preferable to use these tools rather than asking questions about social media and internet use. Nevertheless, it provides an idea of the use of these media, even if comparisons with other existing studies are challenging.

Third, the models were not adjusted on physical activity because no data were available on this topic. It has been shown that physical activity enhances a wide range of affective wellbeing, including mental health, particularly in older people (Chen et al., Reference Chen, Yau, Clemente and Ishihara2022). Additionally, engaging in physical activity has been found to be a preventive factor for internet addiction (Sayili et al., Reference Sayili, Pirdal, Kara, Acar, Camcioglu, Yilmaz, Can and Erginoz2023). Nevertheless, we took into account the time spent on social media per day, which could serve as a proxy of time spent on physical activity, as problematic social media use may be negatively associated with physical activity (Ren et al., Reference Ren, Tan, Huang, Cheng, Huang, Xu, Fang, Li, Zhang and Gao2022).

Our study has many strengths, which counterbalance the cited limitations. The longitudinal nature of the cohort reduces recall bias concerning the history of symptoms of anxiety and/or depression, which were assessed using data from previous waves of this cohort. Additionally, symptoms of anxiety and/or depression were assessed using a valid scale (Achenbach et al., Reference Achenbach, Dumenci and Rescorla2003). Furthermore, we accounted for an important cofactor that is often overlooked in other studies – the history of same-sex sexual relations, sexual minorities being more likely to be current online dating users (Castro et al., Reference Castro, Barrada, Ramos-Villagrasa and Fernández-del-Río2020). Our regression models were adjusted for this factor as well as for social support and the feeling of needing more help.

The originality of this study lies in the studied population. Indeed, the patterns of screen use by adults aged 25 and over and their consequences are less well-known than among adolescents and young adults, even though adults also tend to use screens extensively – both professionally and recreationally – and are at risk of symptoms of anxiety and/or depression. Furthermore, to the best of our knowledge, ours is one of the few studies that have examined ODLSR as a possible correlate of psychological distress among adults.

Conclusions

Our study extends the knowledge gained from research conducted among adolescents and contributes to a deeper understanding of this less-studied adult population. However, further research will be necessary to establish the direction of this association and the causal pathway. Additionally, it will aid in better managing individuals who suffer from mental health disorders and engage with these applications, as this can help them build self-confidence, improve self-image, and reduce fears of approaching others face-to-face. Moreover, the consequences of such use can be disastrous (Sparks et al., Reference Sparks, Zidenberg and Olver2022). Future studies should investigate the determinants of using online meeting websites, including rejection sensitivity and specific mental health disorders such as low self-esteem and severe mental health conditions, and their relationship with the occurrence of psychological difficulties in longitudinal studies to establish causality.

Open peer review

To view the open peer review materials for this article, please visit http://doi.org/10.1017/gmh.2024.2.

Supplementary material

The supplementary material for this article can be found at http://doi.org/10.1017/gmh.2024.2.

Data availability statement

Due to the personal questions asked in this study, research participants were guaranteed that the raw data will be remain confidential. On reasonable request including standards for General Data Protection Regulation data can be accessed, please send an email to . Anonymized data can only be shared after explicit approval of the French national committee for data protection for approval (Commission Nationale de l’Informatique et des Libertés, CNIL).

Acknowledgements

The authors thank the TEMPO study participants who provided data for this project.

Author contribution

Maria Melchior conceptualized, designed the study and found funds. Irwin Hecker and Solène Wallez coordinated administratively the study, conducted the data collection and the investigations. Maria Melchior and Murielle Mary-Krause designed the methodology and statistical analysis protocol. Maria El Haddad conducted the statistical analyses under the supervision of Maria Melchior and Murielle Mary-Krause. Maria El Haddad wrote the first draft of the manuscript and all authors contributed to and have approved the final manuscript.

Financial support

The TEMPO cohort was supported by the French National Research Agency (ANR), the French Institute for Public Health Research-IReSP (TGIR Cohortes), the French Inter-departmental Mission for the Fight against Drugs and Drug Addiction (MILDeCA), the French Institute of Cancer (INCa) and the Pfizer Foundation.

Competing interest

The authors declare that they have no known competing financial interest or personal relationships that could have appeared to influence the work reported in this paper.

Ethics statement

The TEMPO cohort received approval of bodies supervising ethical data collection in France, the Advisory Committee on the Treatment of Information for Health Research (Comité consultatif sur le traitement de l’information en matière de recherche dans le domaine de la santé, CCTIRS) and the French computer watchdog authority (Commission Nationale de l’Informatique et des Libertés, CNIL, no. 908163).

Footnotes

Murielle Mary-Krause is co-last author.

References

Achenbach, TM, Dumenci, L and Rescorla, LA (2003) DSM-oriented and empirically based approaches to constructing scales from the same item pools. Journal of Clinical Child & Adolescent Psychology 32, 328340. https://doi.org/10.1207/S15374424JCCP3203_02.CrossRefGoogle ScholarPubMed
Achenbach, TM and Rescorla, LA (2003) Manual for the ASEBA adult forms and profiles for ages 18–59: Adult self-report, adult behavior chesklist. An Integrated System of Multi-Informant Assessment. Burlington: University of Vermont, Research Center for Children, Youth & Families. Available at https://aseba.org/wp-content/uploads/2019/01/ASEBA-Reliability-and-Validity-Adult.pdf (accessed 10 July 2023).Google Scholar
AlSayyari, A and AlBuhairan, F (2018) Relationship of media exposure to substance use among adolescents in Saudi Arabia: Results from a national study. Drug and Alcohol Dependence 191, 174180. https://doi.org/10.1016/j.drugalcdep.2018.01.025.CrossRefGoogle ScholarPubMed
Alshehri, AG and Mohamed, AMAS (2019) The relationship between electronic gaming and health, social relationships, and physical activity among males in Saudi Arabia. American Journal of Men’s Health 13, 1557988319873512. https://doi.org/10.1177/1557988319873512.CrossRefGoogle ScholarPubMed
Andreassen, CS, Griffiths, MD, Kuss, DJ, Mazzoni, E, Billieux, J, Demetrovics, Z and Pallesen, S (2016) The relationship between addictive use of social media and video games and symptoms of psychiatric disorders: A large-scale cross-sectional study. Psychology of Addictive Behaviors 30, 252262. https://doi.org/10.1037/adb0000160.CrossRefGoogle Scholar
Baromètre du numérique (2019) Enquête sur la diffusion des technologies de l’information et de la communication dans la société française en 2019 (Survey on the diffusion of information and communication technologies in French society in 2019). Available at https://www.arcep.fr/uploads/tx_gspublication/rapport-barometre-num-2019.pdf (accessed 10 July 2023).Google Scholar
Barry, KM, Gomajee, R, Kousignian, I, Bustamante, JJH, Lakrout, P, Mary-Krause, M and Melchior, M (2022) Adolescent cannabis experimentation and unemployment in young to mid-adulthood: Results from the French TEMPO cohort study. Drug and Alcohol Dependence 230, 109201. https://doi.org/10.1016/j.drugalcdep.2021.109201.CrossRefGoogle Scholar
Bergström, M (2016) Sites de rencontres: qui les utilise en France ? Qui y trouve son conjoint ? Inst. Natl. d’études démographiques (Dating sites: Who uses them in France? Who finds his spouse there? National Instutute of Demographic studies) Populations & Sociétés 530, 14. https://www.ined.fr/fr/publications/editions/population-et-societes/sites-rencontres-qui-y-trouve-son-conjoint/ (accessed 10 July 2023).Google Scholar
Biddle, SJH, Bengoechea García, E, Pedisic, Z, Bennie, J, Vergeer, I and Wiesner, G (2017) Screen time, other sedentary behaviours, and obesity risk in adults: A review of reviews. Current Obesity Reports 6, 134147. https://doi.org/10.1007/s13679-017-0256-9.CrossRefGoogle ScholarPubMed
Blackhart, GC, Fitzpatrick, J and Williamson, J (2014) Dispositional factors predicting use of online dating sites and behaviors related to online dating. Computers in Human Behavior 33, 113118. https://doi.org/10.1016/j.chb.2014.01.022.CrossRefGoogle Scholar
Brailovskaia, J and Margraf, J (2018) What does media use reveal about personality and mental health? An exploratory investigation among German students. PLoS One 13, e0191810. https://doi.org/10.1371/journal.pone.0191810.CrossRefGoogle Scholar
Brailovskaia, J and Margraf, J (2022) Addictive social media use during Covid-19 outbreak: Validation of the Bergen social media addiction scale (BSMAS) and investigation of protective factors in nine countries. Current Psychology 21, 119. https://doi.org/10.1007/s12144-022-03182-z.Google Scholar
Brailovskaia, J, Rohmann, E, Bierhoff, HW, Margraf, J and Köllner, V (2019a) Relationships between addictive Facebook use, depressiveness, insomnia, and positive mental health in an inpatient sample: A German longitudinal study. Journal of Behavioral Addictions 8, 703713. https://doi.org/10.1556/2006.8.2019.63.CrossRefGoogle Scholar
Brailovskaia, J, Rohmann, E, Bierhoff, HW, Schillack, H and Margraf, J (2019b) The relationship between daily stress, social support and Facebook addiction disorder. Psychiatry Research 276, 167174. https://doi.org/10.1016/j.psychres.2019.05.014.CrossRefGoogle ScholarPubMed
Cabré-Riera, A, Torrent, M, Donaire-Gonzalez, D, Vrijheid, M, Cardis, E and Guxens, M (2019) Telecommunication devices use, screen time and sleep in adolescents. Environmental Research 171, 341347. https://doi.org/10.1016/j.envres.2018.10.036.CrossRefGoogle ScholarPubMed
Cannito, L, Annunzi, E, Vigano, C, Dell’Osso, B, Vismara, M, Sacco, PL, Palumbo, R and D’Addario, C (2022) The role of stress and cognitive absoprtion in predicting social network addiction. Brain Sciences 12, 643. https://doi.org/10.3390/brainsci12050643.CrossRefGoogle Scholar
Castro, Á, Barrada, JR, Ramos-Villagrasa, PJ and Fernández-del-Río, E (2020) Profiling dating apps users: Sociodemographic and personality characteristics. International Journal of Environmental Research and Public Health 17, 3653. https://doi.org/10.3390/ijerph17103653.CrossRefGoogle ScholarPubMed
Centre National du Cinéma et de l’image animée (2015) Les pratiques de consommation de jeux vidéo des Français (Video game consumption and practices among French population). Available at https://www.cnc.fr/jeu-video/etudes-et-rapports/etudes-prospectives/les-pratiques-de-consommation-de-jeux-video-des-francais_233935 (accessed 10 July 2023).Google Scholar
Chen, C, Yau, SY, Clemente, FM and Ishihara, T (2022) Editorial: The effects of physical activity and exercice on cognitive and affective wellbeing. Front in Behavioral Neuroscience 16, 1047758. https://doi.org/10.3389/fnbeh.2022.1047758.CrossRefGoogle Scholar
Coduto, KD, Lee-Won, RJ and Min Baek, Y (2020) Swiping for trouble: Problematic dating application use among psychosocially ditraught individuals and the paths to negative outcomes. Journal of Social and Personal Relationships 37, 212232. https://doi.org/10.1177/0265407519861153.CrossRefGoogle Scholar
Coffey, JK, Bond, DK, Stern, JA and van Why, N (2022) Sexcual experiences and attachment styles in online and offline dating contexts. International Journal of Sexual Health 34, 665678. https://doi.org/10.1080/19317611.2022.2110349.CrossRefGoogle ScholarPubMed
Forsman, AK and Nordmyr, J (2017) Psychosocial links between internet use and mental health in later life: A systematic review of quantitative and qualitative evidence. Journal of Applied Gerontology 36, 14711518. https://doi.org/10.1177/0733464815595509.CrossRefGoogle ScholarPubMed
Fortunati, L, Taipale, S and de Luca, F (2013) What happened to body-to-body sociability? Social Science Research 42, 893905. https://doi.org/10.1016/j.ssresearch.2012.12.006.CrossRefGoogle ScholarPubMed
Gao, J, Zheng, P, Jia, Y, Chen, H, Mao, Y, Chen, S, Wang, Y, Fu, H and Dai, J (2020) Mental health problems and social media exposure during COVID-19 outbreak. PLoS One 15, e0231924. https://doi.org/10.1371/journal.pone.0231924.CrossRefGoogle ScholarPubMed
Gao, S, Assink, M, Cipriani, A and Lin, K (2017) Associations between rejection sentivity and mental health outcomes: A meta-analytic review. Clinical Psychology Review 57, 5974. https://doi.org/10.1016/j.cpr.2017.08.007.CrossRefGoogle Scholar
Gaudiaut, T (2022) Où passe-t-on le plus de temps sur les réseaux sociaux ? (Where do we spend the most time on social media?) Available at https://fr.statista.com/infographie/18995/temps-moyen-passe-sur-les-reseaux-sociaux-par-pays/ (accessed 10 July 2023).Google Scholar
Global Web Index (2018) Report: The Digital trends to know for 2018. Available at https://www.gwi.com/reports/trends-18 (accessed 10 July 2023).Google Scholar
Goldberg, M, Leclerc, A and Zins, M (2015) Cohort profile update: The GAZEL cohort study. International Journal of Epidemiology 44, 7777g. https://doi.org/10.1093/ije/dyu224.CrossRefGoogle ScholarPubMed
Hance, MA, Blackhart, G and Dew, M (2017) Free to be me: The relationship between the true self, rejection sensitivity, and use of online dating sites. Journal of Social Psychology 158, 421429. https://doi.org/10.1080/00224545.2017.1389684.CrossRefGoogle ScholarPubMed
Holtzhausen, N, Fitzgerald, K, Thakur, I, Ashley, J, Rolfe, M and Pit, SW (2020) Swipe-based dating applications use and its association with mental health outcomes: A cross-sectional study. BMC Psychology 8, 112. https://doi.org/10.1186/s40359-020-0373-1.CrossRefGoogle ScholarPubMed
Internet World Stats (2022) Internet usage in the European Union 2022. Available at https://www.internetworldstats.com/stats9.htm (accessed 10 July 2023).Google Scholar
Ioannidis, K, Treder, MS, Chamberlain, SR, Kiraly, F, Redden, SA, Stein, DJ, Lochner, C and Grant, JE (2018) Problematic internet use as an age-related multifaceted problem: Evidence from a two-site survey. Addictive Behaviors 81, 157166. https://doi.org/10.1016/j.addbeh.2018.02.017.CrossRefGoogle ScholarPubMed
Jacomet, C, Ologeanu-Taddei, R, Prouteau, J, Lambert, C, Linard, F, Bastiani, P and Dellamonica, P (2020) E-health. Patterns of use and perceived benefits and barriers among people living with HIV and their physicians. Part2: Health apps and smart devices. Médecine et Maladies Infectieuses 50, 582589. https://doi.org/10.1016/j.medmal.2020.04.005.CrossRefGoogle Scholar
Jaiswal, S, Asper, L, Long, J, Lee, A, Harrison, K and Golebiowski, B (2019) Ocular and visual discomfort associated with smartphones, tablets and computers: What we do and do not know. Clinical and Experimental Optometry 102, 463477. https://doi.org/10.1111/cxo.12851.CrossRefGoogle Scholar
Jun, HJ and Kim, MY (2017) What accounts for the relationship between internet use and suicidal ideation of Korean older adults? A mediation analysis. Journal of Gerontology Series B 72, 846855. https://doi.org/10.1093/geronb/gbw163.Google ScholarPubMed
Kaess, M, Durkee, T, Brunner, R, Carli, V, Parzer, P, Wasserman, C, Sarchiapone, M, Hoven, C, Apter, A, Balazs, J, Balint, M, Bobes, J, Cohen, R, Cosman, D, Cotter, P, Fischer, G, Floderus, B, Iosue, M, Haring, C, Kahn, JP, Musa, GJ, Nemes, B, Postuvan, V, Resch, F, Saiz, PA, Sisask, M, Snir, A, Varnik, A, Žiberna, J and Wasserman, D (2014) Pathological internet use among European adolescents: Psychopathology and self-destructive behaviours. European Child & Adolescent Psychiatry 23, 10931102. https://doi.org/10.1007/s00787-014-0562-7.CrossRefGoogle ScholarPubMed
Lachman, ME (2004) Development in midlife. Annual Review of Psychology 55, 305331. https://doi.org/10.1146/annurev.psych.55.090902.141521.CrossRefGoogle ScholarPubMed
Lenton-Brym, AP, Santiago, VA, Fredborg, BK and Antony, MM (2021) Associations between social anxiety, depression, and use of mobile dating applications. Cyberpsychology, Behavior, and Social Networking 4, 8693. https://doi.org/10.1089/cyber.2019.0561.CrossRefGoogle Scholar
Lifshitz, R, Nimrod, G and Bachner, YG (2018) Internet use and well-being in later life: A functional approach. Aging & Mental Health 22, 8591. https://doi.org/10.1080/13607863.2016.1232370.CrossRefGoogle ScholarPubMed
Lissak, G (2018) Adverse physiological and psychological effects of screen time on children and adolescents: Literature review and case study. Environmental Research 164, 149157. https://doi.org/10.1016/j.envres.2018.01.015.CrossRefGoogle ScholarPubMed
Liu, M, Wu, L and Yao, S (2016) Dose-response association of screen time-based sedentary behaviour in children and adolescents and depression: A meta-analysis of observational studies. British Journal of Sports Medicine 50, 12521258. https://doi.org/10.1136/bjsports-2015-095084.CrossRefGoogle ScholarPubMed
Marino, C, Gini, G, Vieno, A and Spada, MM (2018) The associations between problematic facebook use, psychological distress and weel-being among adolescents and young adults: A systematic review and meta-analysis. Journal of Affective Disorders 226, 274281. https://doi.org/10.1016/j.jad.2017.10.007.CrossRefGoogle Scholar
Mary-Krause, M, Herranz Bustamante, JJ, Bolze, C, Galéra, C, Fombonne, EJ and Melchior, M (2021) Cohort profile: The TEMPO cohort study. International Journal of Epidemiology 50, 10671068k. https://doi.org/10.1093/ije/dyab026.CrossRefGoogle ScholarPubMed
Masaeli, N and Farhadi, H (2021) Prevalence of internet-based addictive behaviors during COVID-19 pandemic: A systematic review. Journal of Addictive Diseases 39, 468488. https://doi.org/10.1080/10550887.2021.1895962.CrossRefGoogle ScholarPubMed
Melchior, M, Chollet, AU, Fombonne, E, Surkan, PJ and Dray-Spira, R (2014) Internet and video game use in relation to overweight in young adults. American Journal of Health Promotion 28, 321324. https://doi.org/10.4278/ajhp.121023-ARB-515.CrossRefGoogle ScholarPubMed
Mennig, M, Tennie, S and Barke, A (2022) Self-perceived problematic use of online pornography is linked to clinically relevant levels of psychological distress and psychopathological symptoms. Archives of Sexual Behavior 51, 13131321. https://doi.org/10.1007/s10508-021-02101-w.CrossRefGoogle ScholarPubMed
Ministère de la Santé et de la Prévention (2022) Activité physique et santé (Physical activity and health). Available at https://solidarites-sante.gouv.fr/prevention-en-sante/preserver-sa-sante/article/activite-physique-et-sante (accessed 20 December 2022).Google Scholar
Panagiotidi, M (2017) Problematic video game play and ADHD traits in an adult population. Cyberpsychology, Behavior, and Social Networking 20, 292295. https://doi.org/10.1089/cyber.2016.0676.CrossRefGoogle Scholar
Poli, R (2017) Internet addiction update: Diagnostic criteria, assessment and prevalence. Neuropsychiatry 7, 48. https://doi.org/10.4172/neuropsychiatry.1000171.CrossRefGoogle Scholar
Pontes, HM (2017) Investigating the differential effects of social networking site addiction and internet gaming disorder on psychological health. Journal of Behavioral Addictions 6, 601610. https://doi.org/10.1556/2006.6.2017.075.CrossRefGoogle ScholarPubMed
Redonnet, B, Chollet, A, Fombonne, E, Bowes, L and Melchior, M (2012) Tobacco, alcohol, cannabis and other illegal drug use among young adults: The socioeconomic context. Drug and Alcohol Dependence 121, 231239. https://doi.org/10.1016/j.drugalcdep.2011.09.002.CrossRefGoogle ScholarPubMed
Ren, Z, Tan, J, Huang, B, Cheng, J, Huang, Y, Xu, P, Fang, X, Li, H, Zhang, D and Gao, Y (2022) Association between 24-hour movement behaviors and smartphone addiction among adolescents in Foshan City, Southern China: Compositional data analysis. International Journal of Environmental Research and Public Health 19, 9942. https://doi.org/10.3390/ijerph19169942.CrossRefGoogle ScholarPubMed
Rescorla, L and Achenbach, T (2004) The Achenbach system of empirically based assessment (ASEBA) for ages 18 to 90 years. In Maruish, ME (ed.), The Use of Psychological Testing for Treatment Planning and Outcomes Assessment. Volume 3: Instruments for adults. New York: Lawrence Erlbaum Associate Publishers, pp. 115152.Google Scholar
Rousseau, M, Asselin, I, Morello, R, Lecourtour, X, Brouard, J, Fauvet, R and Pizzoferrato, AC (2023) Prevalence and factors associated with active cybersexuality among teenagers between 15 and 17 years old: A cross sectional study in Normandy, France. Archives de Pédiatrie 30, 260265. https://doi.org/10.1016/j.arcped.2023.01.011.CrossRefGoogle Scholar
Rydahl, KFK, Brund, RBK, Medici, CR, Hansen, V, Straarup, KMN, Straszek, SPV and Østergaard, SD (2021) Use of social media and online dating among individuals with a history of affective disorder. Acta Neuropsychiatrica 33, 92103. https://doi.org/10.1017/neu.2020.36.CrossRefGoogle ScholarPubMed
Sayili, U, Pirdal, BZ, Kara, B, Acar, N, Camcioglu, E, Yilmaz, E, Can, G and Erginoz, E (2023) Internet addiction and social media addiction in medical faculty students: Prevalence, related factors, and association sith life satisfaction. Journal of Community Health 48, 189198. https://doi.org/10.1007/s10900-022-01153-w.CrossRefGoogle Scholar
Small, GW, Lee, J, Kaufman, A, Jalil, J, Siddarth, P, Gaddipati, H, Moody, TD and Bookheimer, SY (2020) Brain health consequences of digital technology use. Dialogues in Clinical Neuroscience 22, 179187. https://doi.org/10.31887/DCNS.2020.22.2/gsmall.CrossRefGoogle Scholar
Sparks, B, Zidenberg, AM and Olver, ME (2022) Involuntary celibacy: A review of incel ideology and experiences with dating, rejection, and associated mental health and emotional sequelae. Current Psychiatry Reports 24, 731740. https://doi.org/10.1007/s11920-022-01382-9.CrossRefGoogle ScholarPubMed
Stockdale, L and Coyne, SM (2018) Video game addiction in emerging adulthood: Cross-sectional evidence of pathology in video game addicts as compared to matched healthy controls. Journal of Affective Disorders 225, 265272. https://doi.org/10.1016/j.jad.2017.08.045.CrossRefGoogle ScholarPubMed
Strubel, J and Petrie, TA (2017) Love me tinder: Body image and psychosocial functioning among men and women. Body Image 21, 3438. https://doi.org/10.1016/j.bodyim.2017.02.006.CrossRefGoogle Scholar
Tejeiro, RA, Espada, JP, Gonzalvez, MT and Christiansen, P (2016) Psychometric properties of the problem video game playing scale in adults. European Review of Appied Psychology 66, 913. https://doi.org/10.1016/j.erap.2015.11.004.CrossRefGoogle Scholar
Tejeiro Salguero, RA and Bersabé Moran, RM (2002) Measuring problem video game playing in adolescents. Addiction 97, 16011606. https://doi.org/10.1046/j.1360-0443.2002.00218.x.CrossRefGoogle ScholarPubMed
Toril, P, Reales, JM and Ballesteros, S (2014) Video game training enhances cognition of older adults: A meta-analytic study. Psychology and Aging 29, 706716. https://doi.org/10.1037/a0037507.CrossRefGoogle ScholarPubMed
van den Eijnden, R, Koning, I, Doornwaard, S, van Gurp, F and Ter Bogt, T (2018) The impact of heavy and disordered use of games and social media on adolescents’ psychological, social, and school functioning. Journal of Behavioral Addictions 7, 697706. https://doi.org/10.1556/2006.7.2018.65.CrossRefGoogle ScholarPubMed
Wang, Y, Zhang, H, Feng, T and Wang, H (2019) Does internet use affect levels of depression among older adults in China? A propensity score matching approach. BMC Public Health 19, 1474. https://doi.org/10.1186/s12889-019-7832-8.CrossRefGoogle Scholar
Waszczuk, MA, Zimmerman, M, Ruggero, C, Li, K, MacNamara, A, Weinberg, A, Hajcak, G, Watson, D and Kotov, R (2017) What do clinicians treat: Diagnoses or symptoms? The incremental validity of a symptom-based, dimensional characterization of emotional disorders in predicting medication prescription patterns. Comprehensive Psychiatry 79, 8088. https://doi.org/10.1016/j.comppsych.2017.04.004.CrossRefGoogle ScholarPubMed
Yoon, S, Kleinman, M, Mertz, J and Brannick, M (2019) Is social network site usage related to depression? A meta-analysis of Facebook–depression relations. Journal of Affective Disorders 248, 6572. https://doi.org/10.1016/j.jad.2019.01.026.CrossRefGoogle ScholarPubMed
Zhao, N and Zhou, G (2021) COVID-19 stress and addictive social media use (SMU): Mediating role of active use and social media flow. Frontiers in Psychiatry 12, 635546. https://doi.org/10.3389/fpsyt.2021.635546.CrossRefGoogle ScholarPubMed
Figure 0

Table 1. Characteristics of TEMPO cohort study participants according to presence or not of symptoms of anxiety and/or depression (N = 853, France, 2018)

Figure 1

Table 2. Relations between video game use, time spent on social media and sexual intercourse with someone met online a dating website. (N = 853)

Figure 2

Table 3. Associations between screen use and symptoms of anxiety and/or depression. (TEMPO cohort study, France, 2018; logistic regression analyses, Odds-ratio (OR) and 95% confidence interval (95% CI), N = 853)

Supplementary material: File

El Haddad et al. supplementary material

El Haddad et al. supplementary material
Download El Haddad et al. supplementary material(File)
File 268.3 KB

Author comment: The association between the use of video games, social media and online dating sites, and the symptoms of anxiety and/or depression in adults aged 25 and over — R0/PR1

Comments

Dear Editor,

We would like to submit our paper, entitled The association between the use of video games, social media and online dating sites, and the anxiety-depression among adults over 30 for publication consideration in Global Mental health.

People tend to spend more time in front of their screens, even more during the COVID-19 pandemic, which can have repercussions on their social life, physical and mental health. This topic has mainly been studied in adolescents. So, our study tested associations between use of video games, social media and online dating websites, and anxiety-depressive disorders among adults over 30. Our study, conducted among a sample of adults drawn from the ongoing TEMPO cohort study, shows a significant association between online dating and symptoms of anxiety and depression, even after accounting for socio-demographic characteristics including same-sex sexual relations and preexisting psychological difficulties. This result is important to better target prevention campaign against internet and social media use, but also in order to better take care of people with mental health troubles using such apps.

We believe that our findings will be of interest to readers of Global mental health.

The authors declare no conflict of interest and all authors have approved the final version of the article. The content of the manuscript has not been published, or submitted for publication elsewhere.

Thank you very much for considering our research for publication in your journal.

Sincerely Yours

Review: The association between the use of video games, social media and online dating sites, and the symptoms of anxiety and/or depression in adults aged 25 and over — R0/PR2

Conflict of interest statement

I have no competing interests

Comments

GMH Review of paper “The association between the use of video games, social media and online dating sites, and the anxiety-depression among adults over 30”

General

This paper describes the results of a large cohort study named TEMPO that analysed the associations between videogame use, social media use, use of dating apps on the one hand, and symptoms of anxiety and depression on the other hand in a France cohort sample.

The topic has potential relevance to mental and wellbeing following the COVID pandemic, and increases in screen use due to lockdown restrictions is a worldwide phenomenon. Therefore, it might be a topic of global relevance. That said, the paper was submitted to GMH, which as a journal is focused strongly on mental health across the globe. Therefore, the introduction would strengthen if the results would be placed in a global context, explaining the background evidence from studies across the world, including also studies from countries in non-Western settings and in the global south. Also, it would be good if the discussion also gets a more global focus.

Further, the paper in its current has important limitations that dampened my enthusiasm while reading. Because there are quite some language errors throughout, unfinished sentences and redundancies, the paper would benefit from very careful proof reading by the authors, ideally by a colleague who is a native speaker. Also, the paper would benefit from restructuring, especially the discussion section, which is a hard read because it contains redundancies and is very wordy.

Below comments per section are provided.

Title:

-It is stated in the title but also throughout the manuscript that your sample consists of adults of over 30, whereas in the Results section (line 213) it is surprisingly mentioned that adults of 25-44 were included? This is a major issue, and should be clarified cq. corrected throughout the entire paper.

-You use the rather uncommon construct anxiety-depression. It is better to refer to “symptoms of anxiety and depression”, or “psychological distress” (which usually consists of anxiety and depression). Here and there you also use internalizing symptoms, which is not often used in the context of adults. Please be consistent and use a single common description.

Impact statement:

-Lines 14-20: the sentence “Thus…. such apps” is grammatically incorrect (“being to assess”), very long and should be shortened or changed to two sentences.

Abstract:

-Methods: in addition to sex also provide mean age and age range.

-Results: what was the proportion of people scoring above the cut-off for symproms af anxiety and depression?

-Lines 4-43: In the conclusion section, the authors suggest that prevention campaigns should target internet and social media use. That is strange, since no association was found between that and with symptoms of anxiety and depression. Furthermore, since this is a cross-sectional study, no causal inferences can be made between the use of specific social media and websites, and the occurrence of mental health symptoms. Therefore, it is premature to make strong suggestions regarding prevention campaigns.

Introduction

-line 53: you refer to research on internet use among French adults aged 25-39, but your study is on adults aged 30 and older (although this is not entirely clear)? Could you also find evidence for adults? And although Statista is commonly used by researchers and journalists throughout the world, we cannot rely on its statistical data. Would you have any data from research articles?

-the introduction focuses very much on adolescents, probably because that is where the bul of the evidence lies concerning the detrimental effects of internet use. Rather than focusing on the adolescent population here, previous research around internet use (dating behavior, gaming, and social media use) should be described as well.

-line 65: a reference is needed after “life”.

-line 68: the sentence …, with different intentions, content and psychological intent” reads poorly and is not clear. What intent(ions) and content are you referring to?

-line 82: in what age group was the Marino et al (2018) study carried out?

-lines 88-92: “When a study exist (?) …. increased”: grammatically incorrect and very lengthy, please rephrase

-line 94: internalizing symptoms: use consistent term for symptoms of anxiety and depression, for example, psychological distress.

-

Methods

-Line 102: TEMPO is a longitudinal study but you decided to use only data form the 2018 time point. Why? In the discission you mention several occasions that longitudinal studies should be carried out, so why did you not use other timepoints in your analysis?

-Lines 123-128: please mention the psychometric properties of the ARS.

-Lines 130-136 describes “Indeed, in the literature, other tools are generally used to assess video game use such as the Problem Video Game Playing scale (PVP), or Internet Game Disorders Scale (IGDS9), or time spent on video games, mainly conducted among adolescents.”This is not very relevant for the methods section, but I suggest to use this text when describing the limitations of the way you measured your variables of interest in the discussion.

-Lines 140-142: it is not clear whether you divided time spent on video gaming into two or three categories.

-Lines 156-160: You measure online dating with the question: “Have you ever had sexual relations with someone you met online on a dating website?" but online dating is not always sexual in nature. People may be just in the “talking stage” or “get to know each other phase”. Therefore, you should consider to give your construct a more appropriate and specific name, reflecting “online dating resulting from sexual relations” or using a similar description.

-line 158: “do not wish to answer” is considered as a “no”. This is a major problem, since it is more likely that these people would actually engage in online dating but are ashamed to answer. This is even more likely because you inquire about sexual relations resulting from it which may be associated with stigma. This variable should be coded as a missing variable and your data need to be re-analyzed with this variable recoded as such.

-line 167 (covariates): Why do you distinguish between under 30 years and above 30 years if you intend to include only people aged 30 years and above?

-line 182: You mention that you measured history of anxiety and depressive disorders. Since the ASR is described to be a self-report instrument, no disorders can be diagnosed with it, but rather the history of increased levels of psychological distress. It has been found that self-report instrument generally overestimate the presence of a disorder. Please also specify at what wave(s) this was measured and how

-line 200 (statistical analysis): what type of bivariate analyses did you carry out (Pearson correlations)? And what p-value did you consider to indicate statistical significance?

Results

-Line 230: “level of symptoms of anxiety-depression., as However…” Please correct

-Line 233: “does” should be “did”

Discussion

-the discussion is particularly hard to read. It is lengthy and it mentions several issues multiple times in different wording. In all, the text can be made more concise. The text on limitations and strengths could be greatly reduced. You should only mention 2-3 sentences describing strengths, and not more than one paragraph describing limitations.

-the discussion does not pay much attention to the fact that you in fact measured prolific sexual behaviors in part of your sample (engaging in sexual relations using online dating apps), you may add a few sentences on the association between these behaviors and mental health (anxiety and depression) found in previous research.

-Despite shortening the limitations section, an additional limitation that should be mentioned is how problematic internet use was measured. This research field is booming, and instruments are developed and validated for standardized measurement.

-lines 246-248: in the first paragraph of the discussion section, you already describe clinical implications of your findings and future research directions. It is better to add a more elaborated paragraph with these implications for practice, and a separate paragraph with future research implications at the end of your discussion, for example just before the final conclusion.

-Lines 249-262: how do you explain not finding an association between video gaming and social media use, and psychological distress in your study? Did you measure these variables differently, do you think that your sample differs? This can be better explained.

-Line 255: “(BFAS) and “: delete “and”

-Line 258: you are suggesting that you studied middle aged adults, which is only partly the case. Usually, middle aged adults are people between the age range of 40 to 60 whereas your sample was 25-44.

-Line 260: the sentence “Whether or not video …. verified in future studies” is confusing, since this was the aim of your study? Why do you suggest that another study needs to be carried out on the same topic? You sample size was large, so it may not be worthwhile to do another study on the exact same topic that may also not find any relation between video gaming and social media use and psychological distress?

-Lines 281-282: you mention that the relation between online dating and psychological distress is likely to be bidirectional. Would it be possible that it is not bidirectional, but that distress only predicts online dating, and not the other way around? I don’t think that your analyses can rule this hypothesis out. Further, the fact that you can’t draw any conclusions regarding causality between these two variables, is mentioned again under the limitations. It would be good to delete it under the limitations.

-Line 358: if it is in fact distress that causes people to seek for a partner online, it may not be the right target for a prevention campaign. It is tricky to arrive at clinical suggestions in the absence of causal proof. Also, the sentence “…. target prevention campaign….” is not grammatically correct.

-Line 361: you suggest that new longitudinal studies need to be carried out. Can’t you use future waves of the TEMPO study to answer these questions?

Review: The association between the use of video games, social media and online dating sites, and the symptoms of anxiety and/or depression in adults aged 25 and over — R0/PR3

Conflict of interest statement

Reviewer declares none.

Comments

The study’s analysis of 2018 TEMPO cohort data revealed a significant association between online dating and anxiety-depression symptoms, particularly among women. By focusing on a crucial demographic—middle-aged individuals aged 30 and above—this research provides valuable insights into the associations between social media, online dating, and anxiety-depressive disorders in adults over 30. Since previous studies have predominantly concentrated on adolescents, this study is particularly significant. Its findings have important implications for developing prevention campaigns targeting internet and social media use (specifically, online dating) in the 30+ age group and providing better care for those experiencing anxiety-depression symptoms.

The literature review is comprehensive, with references that are relevant to the topic, covering both historical literature and more recent developments. The few existing studies on online dating, social media usage, and depression are mostly listed and reviewed in the literature, demonstrating the review’s thoroughness.

The manuscript is well-written and organized. The use of the Adult Self-Report (ASR) is appropriate, and the variable regarding time spent on social media is well justified.

The statistical analysis was robust, and the findings were reasonable, given the study’s limitations (e.g., sample size and origins). Notably, the researchers addressed these limitations to ensure an accurate interpretation of the results. However, it would be beneficial for the author to provide more information on the TEMPO cohort, including the exact age range of the participants.

Recommendation: The association between the use of video games, social media and online dating sites, and the symptoms of anxiety and/or depression in adults aged 25 and over — R0/PR4

Comments

No accompanying comment.

Decision: The association between the use of video games, social media and online dating sites, and the symptoms of anxiety and/or depression in adults aged 25 and over — R0/PR5

Comments

No accompanying comment.

Author comment: The association between the use of video games, social media and online dating sites, and the symptoms of anxiety and/or depression in adults aged 25 and over — R1/PR6

Comments

Dear Editor,

Further to your response about the manuscript entitled “The association between the use of video games, social media and online dating sites, and the anxiety-depression among adults over 30”, reference GMH-23-0023, we would like to thank you for your interest in our manuscript. According to the reviewers’ comments, we have revised the manuscript and responded point-by-point to their comments. We also notified in red modifications in the manuscript, Tables, Highlights and Supplementary Material. We hope that our revised version is satisfactory.

Thank you very much for considering our research for publication in your journal.

Sincerely Yours

Murielle Mary-Krause

Review: The association between the use of video games, social media and online dating sites, and the symptoms of anxiety and/or depression in adults aged 25 and over — R1/PR7

Conflict of interest statement

I do not have any conflict of interest to report.

Comments

I appreciate the significant improvements made to the manuscript since the last review. However, I would like to highlight two primary concerns that must be addressed.

Concern 1:

In your response to a previous reviewer’s comment regarding line 158, you have classified the responses, “do not wish to answer,” as a “no”. Your justification was that only four participants selected this option and that this small number did not warrant a separate category, nor did it significantly alter your results. However, this decision is problematic.

The standard practice in data analysis is to dichotomize responses into “yes” and “no”, treating any non-answers as missing data or categorizing them separately. The choice to not answer is not equivalent to a negative response. While it’s true that the current size of this group (n=4) is small, the methodology should be robust enough to handle larger numbers. If it were n=400, for example, the impact could be significant. I would therefore advise treating these responses as missing data, focusing only on genuine yes/no responses.

Concern 2:

In the discussion section (Page 16), you have included a substantial new paragraph on the concepts of rejection sensitivity, low self-esteem, and how these factors relate to the use of online dating websites. References to studies by Blackhart et al., 2014; Hance et al., 2017; Strubel and Petrie, 2017; and, Rydahl et al., 2021 have been included in this discussion.

However, these concepts and references are not present in the literature review, and it appears that the TEMPO study data you provided in the study does not include these specific considerations. To maintain consistency and offer a comprehensive review of the topic, it would be beneficial to introduce these concepts in the literature review section if you intend to discuss them later. Alternatively, if the current dataset does not include these factors, they might be better placed as recommendations for future research.

Recommendation: The association between the use of video games, social media and online dating sites, and the symptoms of anxiety and/or depression in adults aged 25 and over — R1/PR8

Comments

No accompanying comment.

Decision: The association between the use of video games, social media and online dating sites, and the symptoms of anxiety and/or depression in adults aged 25 and over — R1/PR9

Comments

No accompanying comment.

Author comment: The association between the use of video games, social media and online dating sites, and the symptoms of anxiety and/or depression in adults aged 25 and over — R2/PR10

Comments

Pr Gary Belkin

Editor in Chief

Global Mental Health

Paris, November 2nd, 2023

Dear Editor,

Further to your response about the manuscript entitled “The association between the use of video games, social media and online dating sites, and the anxiety-depression among adults over 30”, reference GMH-23-0023, we would like to thank you for your interest in our manuscript. According to the reviewer’s comments, we have revised the manuscript and responded point-by-point to his.her comments. We also notified in red modifications in the manuscript, Tables, Highlights and Supplementary Material. We hope that our revised version is satisfactory.

Thank you very much for considering our research for publication in your journal.

Sincerely Yours

Murielle Mary-Krause

Review: The association between the use of video games, social media and online dating sites, and the symptoms of anxiety and/or depression in adults aged 25 and over — R2/PR11

Conflict of interest statement

Reviewer declares none.

Comments

In reviewing the revised paper, I note the authors‘ revision in the treatment of ’do not wish to answer‘ responses. Initially, equating these responses with a ’no' could potentially misrepresent the data. The updated approach (P9-10), which refrains from interpreting these as negative responses, seems more appropriate and in line with sound research practices. The re-analysis of the data to account for this change is also acknowledged (P12-13/24-25). I am satisfied with this methodological revision.

Recommendation: The association between the use of video games, social media and online dating sites, and the symptoms of anxiety and/or depression in adults aged 25 and over — R2/PR12

Comments

No accompanying comment.

Decision: The association between the use of video games, social media and online dating sites, and the symptoms of anxiety and/or depression in adults aged 25 and over — R2/PR13

Comments

No accompanying comment.