Introduction to Statistical Mediation Analysis

Addressing Moderated Mediation Hypotheses: Theory, Methods, and Prescriptions

This article provides researchers with a guide to properly construe and conduct analyses of conditional indirect effects, commonly known as moderated mediation effects. We disentangle conflicting d...

mediation: R Package for Causal Mediation Analysis

In this paper, we describe the R package mediation for conducting causal mediation analysis in applied empirical research. In many scientific disciplines, the goal of researchers is not only estimating causal effects of a treatment but also understanding the process in which the treatment causally affects the outcome. Causal mediation analysis is frequently used to assess potential causal mechanisms. The mediation package implements a comprehensive suite of statistical tools for conducting such an analysis. The package is organized into two distinct approaches. Using the model-based approach, researchers can estimate causal mediation effects and conduct sensitivity analysis under the standard research design. Furthermore, the design-based approach provides several analysis tools that are applicable under different experimental designs. This approach requires weaker assumptions than the model-based approach. We also implement a statistical method for dealing with multiple (causally dependent) mediators, which are often encountered in practice. Finally, the package also offers a methodology for assessing causal mediation in the presence of treatment noncompliance, a common problem in randomized trials.

Asymptotic and resampling strategies for assessing and comparing indirect effects in multiple mediator models

Hypotheses involving mediation are common in the behavioral sciences. Mediation exists when a predictor affects a dependent variable indirectly through at least one intervening variable, or mediator. Methods to assess mediation involving multiple simultaneous mediators have received little attention in the methodological literature despite a clear need. We provide an overview of simple and multiple mediation and explore three approaches that can be used to investigate indirect processes, as well as methods for contrasting two or more mediators within a single model. We present an illustrative example, assessing and contrasting potential mediators of the relationship between the helpfulness of socialization agents and job satisfaction. We also provide SAS and SPSS macros, as well as Mplus and LISREL syntax, to facilitate the use of these methods in applications.

Reconsidering Baron and Kenny: Myths and Truths about Mediation Analysis

Abstract. Baron and Kenny’s procedure for determining if an independent variable affects a dependent variable through some mediator is so well known that i

How do social media use, gaming frequency, and internalizing symptoms predict each other over time in early-to-middle adolescence?

Abstract Background The effects of adolescent digital technology use (e.g. social media, gaming) on their mental health are a major public health concern, but existing evidence is of mixed quality and findings have been inconclusive. Methods Separating within-person effects from between-person effects, a random-intercept cross-lagged panel model was applied to three annual waves of data (T1, T2, T3) on social media use, gaming, and internalizing symptoms among N = 25 629 adolescents (51% girls, average age 12 years, 7 months (SD = 3.58 months) at baseline) in Greater Manchester, England. Results Longitudinal relationships varied by gender, such that more frequent gaming at T2 predicted less time spent on social media use at T3 in girls (but not boys), and more frequent internalizing symptoms at T2 predicted reductions in gaming frequency at T3 in boys (but not girls). There was no evidence that time spent on social media or gaming frequency predicted later internalizing symptoms among girls or boys. Sensitivity analyses that distinguished active versus passive social media use replicated these findings. Conclusions The findings of this study do not support the widely held view that adolescent technology use is a major causal factor in their mental health difficulties.

Do social media experiments prove a link with mental health: A methodological and meta-analytic review.

Time spent on social media among the least influential factors in adolescent mental health: preliminary results from a panel network analysis

There is growing concern about the role of social media use in the documented increase of adolescent mental health difficulties. However, the current evidence remains complex and inconclusive. While increasing research on this area of work has allowed for notable progress, the impact of social media use within the complex systems of adolescent mental health and development is yet to be examined. The current study addresses this conceptual and methodological oversight by applying a panel network analysis to explore the role of social media on key interacting systems of mental health, wellbeing and social life of 12,041 UK adolescents. Here we find that, across time, estimated time spent interacting with social media predicts concentration problems in female participants. However, of the factors included in the current network, social media use is one of the least influential factors of adolescent mental health, with others (for example, bullying, lack of family support and school work dissatisfaction) exhibiting stronger associations. Our findings provide an important exploratory first step in mapping out complex relationships between social media use and key developmental systems and highlight the need for social policy initiatives that focus on the home and school environment to foster resilience.

A Statistical Interrogation of “The Case for Causality, Part 1” by Rausch and Haidt – Matthew B. Jané

I don’t know anything about the literature on social media and mental health so my focus on this post is to interrogate the statistical approach taken by the article written by Zach Rausch and Jonathon Haidt (link here) and to some extent the original meta-analysis by Ferguson.

The effect of social media on well-being differs from adolescent to adolescent

The question whether social media use benefits or undermines adolescents’ well-being is an important societal concern. Previous empirical studies have mostly established across-the-board effects among (sub)populations of adolescents. As a result, it is still an open question whether the effects are unique for each individual adolescent. We sampled adolescents’ experiences six times per day for one week to quantify differences in their susceptibility to the effects of social media on their momentary affective well-being. Rigorous analyses of 2,155 real-time assessments showed that the association between social media use and affective well-being differs strongly across adolescents: While 44% did not feel better or worse after passive social media use, 46% felt better, and 10% felt worse. Our results imply that person-specific effects can no longer be ignored in research, as well as in prevention and intervention programs.

The Impact of Internet and Social Media Use on Well-Being: A Longitudinal Analysis of Adolescents Across Nine Years

Abstract The present research examines the longitudinal average impact of frequency of use of Internet and social networking sites (SNS) on subjective well-being of adolescents in Germany. Based on five-wave panel data that cover a period of nine years, we disentangle between-person and within-person effects of media use on depressive symptomatology and life satisfaction as indicators of subjective well-being. Additionally, we control for confounders such as TV use, self-esteem, and satisfaction with friends. We found that frequency of Internet use in general and use of SNS in particular is not substantially related subjective well-being. The explanatory power of general Internet use or SNS use to predict between-person differences or within-person change in subjective well-being is close to zero. TV use, a potentially confounding variable, is negatively related to satisfaction with life, but it does not affect depressive symptomatology. However, this effect is too small to be of practical relevance.

Reciprocal Relationships between Trajectories of Depressive Symptoms and Screen Media Use during Adolescence

Adolescents are constantly connected with each other and the digital landscape through a myriad of screen media devices. Unprecedented access to the wider world and hence a variety of activities, particularly since the introduction of mobile technology, has given rise to questions regarding the impact of this changing media environment on the mental health of young people. Depressive symptoms are one of the most common disabling health issues in adolescence and although research has examined associations between screen use and symptoms of depression, longitudinal investigations are rare and fewer still consider trajectories of change in symptoms. Given the plethora of devices and normalisation of their use, understanding potential longitudinal associations with mental health is crucial. A sample of 1,749 (47% female) adolescents (10–17 years) participated in six waves of data collection over two years. Symptoms of depression, time spent on screens, and on separate screen activities (social networking, gaming, web browsing, TV/passive) were self-reported. Latent growth curve modelling revealed three trajectories of depressive symptoms (low-stable, high-decreasing, and low-increasing) and there were important differences across these groups on screen use. Some small, positive associations were evident between depressive symptoms and later screen use, and between screen use and later depressive symptoms. However, a Random Intercept Cross Lagged Panel Model revealed no consistent support for a longitudinal association. The study highlights the importance of considering differential trajectories of depressive symptoms and specific forms of screen activity to understand these relationships.

“Having All of Your Internal Resources Exhausted Beyond Measure and Being Left with No Clean-Up Crew”: Defining Autistic Burnout

Background: Although autistic adults often discuss experiencing “autistic burnout” and attribute serious negative outcomes to it, the concept is almost completely absent from the academic and clinical literature. Methods: We used a community-based participatory research approach to conduct a thematic analysis of 19 interviews and 19 public Internet sources to understand and characterize autistic burnout. Interview participants were autistic adults who identified as having been professionally diagnosed with an autism spectrum condition. We conducted a thematic analysis, using a hybrid inductive–deductive approach, at semantic and latent levels, through a critical paradigm. We addressed trustworthiness through multiple coders, peer debriefing, and examination of contradictions. Results: Autistic adults described the primary characteristics of autistic burnout as chronic exhaustion, loss of skills, and reduced tolerance to stimulus. They described burnout as happening because of life stressors that added to the cumulative load they experienced, and barriers to support that created an inability to obtain relief from the load. These pressures caused expectations to outweigh abilities resulting in autistic burnout. Autistic adults described negative impacts on their health, capacity for independent living, and quality of life, including suicidal behavior. They also discussed a lack of empathy from neurotypical people and described acceptance and social support, time off/reduced expectations, and doing things in an autistic way/unmasking as associated in their experiences with recovery from autistic burnout. Conclusions: Autistic burnout appears to be a phenomenon distinct from occupational burnout or clinical depression. Better understanding autistic burnout could lead to ways to recognize, relieve, or prevent it, including highlighting the potential dangers of teaching autistic people to mask or camouflage their autistic traits, and including burnout education in suicide prevention programs. These findings highlight the need to reduce discrimination and stigma related to autism and disability. Lay summary Why was this study done? Autistic burnout is talked about a lot by autistic people but has not been formally addressed by researchers. It is an important issue for the autistic community because it is described as leading to distress; loss of work, school, health, and quality of life; and even suicidal behavior. What was the purpose of this study? This study aimed to characterize autistic burnout, understand what it is like, what people think causes it, and what helps people recover from or prevent it. It is a first step in starting to understand autistic burnout well enough to address it. What did the researchers do? Our research group—the Academic Autism Spectrum Partnership in Research and Education—used a community-based participatory research approach with the autistic community in all stages of the study. We analyzed 9 interviews from our study on employment, 10 interviews about autistic burnout, and 19 public Internet sources (five in-depth). We recruited in the United States by publicizing on social media, by word of mouth, and through community connections. When analyzing interviews, we took what people said at face value and in deeper social context, and looked for strong themes across data. What were the results of the study? The primary characteristics of autistic burnout were chronic exhaustion , loss of skills , and reduced tolerance to stimulus . Participants described burnout as happening because of life stressors that added to the cumulative load they experienced, and barriers to support that created an inability to obtain relief from the load. These pressures caused expectations to outweigh abilities resulting in autistic burnout . From this we created a definition: Autistic burnout is a syndrome conceptualized as resulting from chronic life stress and a mismatch of expectations and abilities without adequate supports. It is characterized by pervasive, long-term (typically 3+ months) exhaustion, loss of function, and reduced tolerance to stimulus. Participants described negative impacts on their lives, including health , capacity for independent living , and quality of life , including suicidal behavior. They also discussed a lack of empathy from neurotypical people. People had ideas for recovering from autistic burnout including acceptance and social support , time off/reduced expectations , and doing things in an autistic way/unmasking . How do these findings add to what was already known? We now have data that autistic burnout refers to a clear set of characteristics, and is different from workplace burnout and clinical depression. We have the start of a model for why autistic burnout might happen. We know that people have been able to recover from autistic burnout and have some insights into how. What are the potential weaknesses in the study? This was a small exploratory study with a convenience sample. Although we were able to bring in some diversity by using three data sources, future work would benefit from interviewing a wider range of participants, especially those who are not white, have higher support needs, and have either very high or very low educational attainment. More research is needed to understand how to measure, prevent, and treat autistic burnout. How will these findings help autistic adults now or in the future? These findings validate the experience of autistic adults. Understanding autistic burnout could lead to ways to help relieve it or prevent it. The findings may help therapists and other practitioners recognize autistic burnout, and the potential dangers of teaching autistic people to mask autistic traits. Suicide prevention programs should consider the potential role of burnout. These findings highlight the need to reduce discrimination and stigma around autism and disability.

“Having All of Your Internal Resources Exhausted Beyond Measure and Being Left with No Clean-Up Crew”: Defining Autistic Burnout

Background: Although autistic adults often discuss experiencing “autistic burnout” and attribute serious negative outcomes to it, the concept is almost completely absent from the academic and clinical literature. Methods: We used a community-based participatory research approach to conduct a thematic analysis of 19 interviews and 19 public Internet sources to understand and characterize autistic burnout. Interview participants were autistic adults who identified as having been professionally diagnosed with an autism spectrum condition. We conducted a thematic analysis, using a hybrid inductive–deductive approach, at semantic and latent levels, through a critical paradigm. We addressed trustworthiness through multiple coders, peer debriefing, and examination of contradictions. Results: Autistic adults described the primary characteristics of autistic burnout as chronic exhaustion, loss of skills, and reduced tolerance to stimulus. They described burnout as happening because of life stressors that added to the cumulative load they experienced, and barriers to support that created an inability to obtain relief from the load. These pressures caused expectations to outweigh abilities resulting in autistic burnout. Autistic adults described negative impacts on their health, capacity for independent living, and quality of life, including suicidal behavior. They also discussed a lack of empathy from neurotypical people and described acceptance and social support, time off/reduced expectations, and doing things in an autistic way/unmasking as associated in their experiences with recovery from autistic burnout. Conclusions: Autistic burnout appears to be a phenomenon distinct from occupational burnout or clinical depression. Better understanding autistic burnout could lead to ways to recognize, relieve, or prevent it, including highlighting the potential dangers of teaching autistic people to mask or camouflage their autistic traits, and including burnout education in suicide prevention programs. These findings highlight the need to reduce discrimination and stigma related to autism and disability. Lay summary Why was this study done? Autistic burnout is talked about a lot by autistic people but has not been formally addressed by researchers. It is an important issue for the autistic community because it is described as leading to distress; loss of work, school, health, and quality of life; and even suicidal behavior. What was the purpose of this study? This study aimed to characterize autistic burnout, understand what it is like, what people think causes it, and what helps people recover from or prevent it. It is a first step in starting to understand autistic burnout well enough to address it. What did the researchers do? Our research group—the Academic Autism Spectrum Partnership in Research and Education—used a community-based participatory research approach with the autistic community in all stages of the study. We analyzed 9 interviews from our study on employment, 10 interviews about autistic burnout, and 19 public Internet sources (five in-depth). We recruited in the United States by publicizing on social media, by word of mouth, and through community connections. When analyzing interviews, we took what people said at face value and in deeper social context, and looked for strong themes across data. What were the results of the study? The primary characteristics of autistic burnout were chronic exhaustion , loss of skills , and reduced tolerance to stimulus . Participants described burnout as happening because of life stressors that added to the cumulative load they experienced, and barriers to support that created an inability to obtain relief from the load. These pressures caused expectations to outweigh abilities resulting in autistic burnout . From this we created a definition: Autistic burnout is a syndrome conceptualized as resulting from chronic life stress and a mismatch of expectations and abilities without adequate supports. It is characterized by pervasive, long-term (typically 3+ months) exhaustion, loss of function, and reduced tolerance to stimulus. Participants described negative impacts on their lives, including health , capacity for independent living , and quality of life , including suicidal behavior. They also discussed a lack of empathy from neurotypical people. People had ideas for recovering from autistic burnout including acceptance and social support , time off/reduced expectations , and doing things in an autistic way/unmasking . How do these findings add to what was already known? We now have data that autistic burnout refers to a clear set of characteristics, and is different from workplace burnout and clinical depression. We have the start of a model for why autistic burnout might happen. We know that people have been able to recover from autistic burnout and have some insights into how. What are the potential weaknesses in the study? This was a small exploratory study with a convenience sample. Although we were able to bring in some diversity by using three data sources, future work would benefit from interviewing a wider range of participants, especially those who are not white, have higher support needs, and have either very high or very low educational attainment. More research is needed to understand how to measure, prevent, and treat autistic burnout. How will these findings help autistic adults now or in the future? These findings validate the experience of autistic adults. Understanding autistic burnout could lead to ways to help relieve it or prevent it. The findings may help therapists and other practitioners recognize autistic burnout, and the potential dangers of teaching autistic people to mask autistic traits. Suicide prevention programs should consider the potential role of burnout. These findings highlight the need to reduce discrimination and stigma around autism and disability.

No effect of different types of media on well-being

It is often assumed that traditional forms of media such as books enhance well-being, whereas new media do not. However, we lack evidence for such claims and media research is mainly focused on how much time people spend with a medium, but not whether someone used a medium or not. We explored the effect of media use during one week on well-being at the end of the week, differentiating time spent with a medium and use versus nonuse, over a wide range of different media types: music, TV, films, video games, (e-)books, (digital) magazines, and audiobooks. Results from a six-week longitudinal study representative of the UK population 16 years and older (N = 2159) showed that effects were generally small; between-person relations but rarely within-person effects; mostly for use versus nonuse and not time spent with a medium; and on affective well-being, not life satisfaction.

Social Media Use and Well-Being Across Adolescent Development

Importance Social media’s association with adolescent well-being remains debated. Heavy use has been associated with distress, while abstinence may cause missed connections. Objective To investigate 3-year longitudinal associations between after-school social media use and adolescent well-being using a large longitudinal cohort dataset modeled within a repeated cross-sectional framework. Design, Setting, and Participants This cohort study included Australian students in grades 4 through 12 (2019-2022). After-school social media use was self-reported and grouped as none, moderate, or highest. Well-being was assessed using 8 validated indicators (eg, happiness, life satisfaction, emotional regulation), dichotomized as high vs low. Well-being was assessed concurrently with social media use during the annual school-based survey in each year of data collection. Data analysis was conducted from June to July 2025. Exposures Self-reported after-school social media use between 3 pm and 6 pm (weekdays), classified into 3 categories: none (0 h/wk), moderate (>0 to <12.5 h/wk), and highest (≥12.5 h/wk). Main Outcomes and Measures The primary outcome was overall well-being, measured as the mean score across 8 validated domains (happiness, optimism, life satisfaction, worry, sadness, perseverance, emotional regulation, and cognitive engagement), dichotomized as high vs low (<3 on a scale of 1-5). Secondary outcomes were each individual well-being indicator, similarly dichotomized. Mixed-effects logistic models were used for analyses, stratified by sex and adjusted for demographic covariates. Results The analytic sample included 100 991 adolescents, contributing 173 533 observations (86 582 [49.9%] observations from female participants; mean [SD] age, 13.5 [2.2] years). A U-shaped association was observed between after-school social media use and well-being. Compared with moderate users, adolescents with the highest use had greater odds of low well-being (grades 7-9, girls: odds ratio [OR], 3.13 [95% CI, 2.88-3.39]; boys: OR, 2.25 [95% CI, 1.86-2.72]), while nonusers also had higher odds of low well-being in later adolescence (grades 10-12, girls: OR, 1.79 [95% CI, 1.41-2.27]; boys: OR, 3.00 [95% CI, 2.01-4.46]). These patterns were consistent across survey years and robust to sensitivity analyses. Conclusions and Relevance In this cohort study of students in grades 4 through 12, social media’s association with adolescent well-being was complex and nonlinear, varying by age and sex. While heavy use was associated with poorer well-being and abstinence sometimes coincided with less favorable outcomes, these findings are observational and should be interpreted cautiously.

Social media’s enduring effect on adolescent life satisfaction

In this study, we used large-scale representative panel data to disentangle the between-person and within-person relations linking adolescent social media use and well-being. We found that social media use is not, in and of itself, a strong predictor of life satisfaction across the adolescent population. Instead, social media effects are nuanced, small at best, reciprocal over time, gender specific, and contingent on analytic methods.