Self-report bias in the observed correlation: A meta-analysis

2010 ◽  
Author(s):  
Dana Joseph ◽  
Daniel A. Newman ◽  
Emily J. Grijalva ◽  
Jing Guo
Keyword(s):  
Meta Analysis ◽  
Self Report ◽  
Report Bias

scholarly journals Prevalence of depression and depressive symptoms among outpatients: a systematic review and meta-analysis

BMJ Open ◽  
2017 ◽  
Vol 7 (8) ◽  
pp. e017173 ◽  
Author(s):  
Jinghui Wang ◽  
Xiaohang Wu ◽  
Weiyi Lai ◽  
Erping Long ◽  
Xiayin Zhang ◽  
...  
Keyword(s):  
Systematic Review ◽  
Depressive Symptoms ◽  
Meta Analysis ◽  
Significant Proportion ◽  
Depression Scale ◽  
Developed Countries ◽  
Self Report ◽  
Cochrane Library ◽  
Significant Heterogeneity ◽  
Prevalence Of Depression

ObjectivesDepression and depressive symptoms are common mental disorders that have a considerable effect on patients’ health-related quality of life and satisfaction with medical care, but the prevalence of these conditions varies substantially between published studies. The aim of this study is to conduct a systematic review and meta-analysis to provide a precise estimate of the prevalence of depression or depressive symptoms among outpatients in different clinical specialties.DesignSystematic review and meta-analysis.Data sources and eligibility criteriaThe PubMed and PsycINFO, EMBASE and Cochrane Library databases were searched to identify observational studies that contained information on the prevalence of depression and depressive symptoms in outpatients. All studies included were published before January 2016. Data characteristics were extracted independently by two investigators. The point prevalence of depression or depressive symptoms was measured using validated self-report questionnaires or structured interviews. Assessments were pooled using a random-effects model. Differences in study-level characteristics were estimated by meta-regression analysis. Heterogeneity was assessed using standard χ2tests and the I2statistic. The study protocol has been registered with PROSPERO under number CRD42017054738.ResultsEighty-three cross-sectional studies involving 41 344 individuals were included in this study. The overall pooled prevalence of depression or depressive symptoms was 27.0% (10 943/41 344 individuals; 95% CI 24.0% to 29.0%), with significant heterogeneity between studies (p<0.0001, τ2=0.3742, I2=96.7%). Notably, a significantly higher prevalence of depression and depressive symptoms was observed in outpatients than in the healthy controls (OR 3.16, 95% CI 2.66 to 3.76, I2=72.0%, χ2=25.33). The highest depression/depressive symptom prevalence estimates occurred in studies of outpatients from otolaryngology clinics (53.0%), followed by dermatology clinics (39.0%) and neurology clinics (35.0%). Subgroup analyses showed that the prevalence of depression and depressive symptoms in different specialties varied from 17.0% to 53.0%. The prevalence of depression and depressive symptoms was higher among outpatients in developing countries than in outpatients from developed countries. Moreover, the prevalence of depression and depressive symptoms in outpatients slightly decreased from 1996 to 2010. Regarding screening instruments, the Beck Depression Inventory led to a higher estimate of the prevalence of depression and depressive symptoms (1316/4702, 36.0%, 95% CI 29.0% to 44.0%, I2=94.8%) than the Hospital Anxiety and Depression Scale (1003/2025, 22.0%, 95% CI 12.0% to 35.0%, I2=96.6%).ConclusionOur study provides evidence that a significant proportion of outpatients experience depression or depressive symptoms, highlighting the importance of developing effective management strategies for the early identification and treatment of these conditions among outpatients in clinical practice. The substantial heterogeneity between studies was not fully explained by the variables examined.

scholarly journals GWAS of Depression Phenotypes in the Million Veteran Program and Meta-analysis in More than 1.2 Million Participants Yields 178 Independent Risk Loci

2020 ◽  
Author(s):  
Daniel F Levey ◽  
Murray B Stein ◽  
Frank R Wendt ◽  
Gita A Pathak ◽  
Hang Zhou ◽  
...  
Keyword(s):  
Gene Expression ◽  
Meta Analysis ◽  
African Ancestry ◽  
Genetic Correlations ◽  
Brain Regions ◽  
Self Report ◽  
European Ancestry ◽  
Causal Variants ◽  
Using Data ◽  
Genomic Risk

We report a large meta-analysis of depression using data from the Million Veteran Program (MVP), 23andMe Inc., UK Biobank, and FinnGen; including individuals of European ancestry (n=1,154,267; 340,591 cases) and African ancestry (n=59,600; 25,843 cases). We identified 223 and 233 independent SNPs associated with depression in European ancestry and transancestral analysis, respectively. Genetic correlations within the MVP cohort across electronic health records diagnosis, survey self-report of diagnosis, and a 2-item depression screen exceeded 0.81. Using transcriptome-wide association study (TWAS) we found significant associations for gene expression in several brain regions, including hypothalamus (NEGR1, p=3.19x10-25) and nucleus accumbens (DRD2, p=1.87x10-20). 178 genomic risk loci were fine-mapped to find likely causal variants. We identified likely pathogenicity in these variants and overlapping gene expression for 17 genes from our TWAS, including TRAF3. This study sheds light on the genetic architecture of depression and provides new insight into the interrelatedness of complex psychiatric traits.

scholarly journals Measurement Discrepancies Between Logged and Self-Reported Digital Media Use: A Systematic Review and Meta-Analysis

2020 ◽  
Author(s):  
Douglas Parry ◽  
Brittany I Davidson ◽  
Craig Sewall ◽  
Jacob T. Fisher ◽  
Hannah Mieczkowski ◽  
...  
Keyword(s):  
Systematic Review ◽  
Digital Media ◽  
Media Use ◽  
Meta Analysis ◽  
Well Being ◽  
Self Report ◽  
Effect Sizes ◽  
Objective Measures ◽  
Valid Index ◽  
Accurate Reflection

The influence of digital media on personal and social well-being is a question of immense public and academic interest. Scholars in this domain often use retrospective self-report measures of the quantity or duration of media use as a proxy for more objective measures, but the validity of these self-report measures remains unclear. Recent advancements in log-based data collection techniques have produced a growing collection of studies indexing both self-reported media use and device-logged measurements. Herein, we report a meta-analysis of this body of research. Based on 104 effect sizes, we found that self-reported media use was only moderately correlated with device-logged measurements, and that these self-report measures were rarely an accurate reflection of logged media use. These results demonstrate that self-reported measures of the quantity or duration of media use are not a valid index of the amount of time people actually spend using media. These findings have serious implications for the study of media use and well- being, suggesting that cautiousness is warranted in drawing conclusions regarding media effects from studies relying solely on self-reported measures of media use.

scholarly journals Prevalence of pre-stroke depression and its association with post-stroke depression: a systematic review and meta-analysis

2018 ◽  
Vol 49 (4) ◽  
pp. 685-696 ◽  
Author(s):  
Martin Taylor-Rowan ◽  
Oyiza Momoh ◽  
Luis Ayerbe ◽  
Jonathan J. Evans ◽  
David J. Stott ◽  
...  
Keyword(s):  
Systematic Review ◽  
Publication Bias ◽  
Meta Analysis ◽  
Assessment Method ◽  
Self Report ◽  
Funnel Plot ◽  
Strength Of Evidence ◽  
Post Stroke ◽  
Depression Assessment ◽  
Post Stroke Depression

AbstractBackgroundDepression is a common post-stroke complication. Pre-stroke depression may be an important contributor, however the epidemiology of pre-stroke depression is poorly understood. Using systematic review and meta-analysis, we described the prevalence of pre-stroke depression and its association with post-stroke depression.MethodsWe searched multiple cross-disciplinary databases from inception to July 2017 and extracted data on the prevalence of pre-stroke depression and its association with post-stroke depression. We assessed the risk of bias (RoB) using validated tools. We described summary estimates of prevalence and summary odds ratio (OR) for association with post-stroke depression, using random-effects models. We performed subgroup analysis describing the effect of depression assessment method. We used a funnel plot to describe potential publication bias. The strength of evidence presented in this review was summarised via ‘GRADE’.ResultsOf 11 884 studies identified, 29 were included (total participantsn= 164 993). Pre-stroke depression pooled prevalence was 11.6% [95% confidence interval (CI) 9.2–14.7]; range: 0.4–24% (I295.8). Prevalence of pre-stroke depression varied by assessment method (p= 0.02) with clinical interview suggesting greater pre-stroke depression prevalence (~17%) than case-note review (9%) or self-report (11%). Pre-stroke depression was associated with increased odds of post-stroke depression; summary OR 3.0 (95% CI 2.3–4.0). All studies were judged to be at RoB: 59% of included studies had an uncertain RoB in stroke assessment; 83% had high or uncertain RoB for pre-stroke depression assessment. Funnel plot indicated no risk of publication bias. The strength of evidence based on GRADE was ‘very low’.ConclusionsOne in six stroke patients have had pre-stroke depression. Reported rates may be routinely underestimated due to limitations around assessment. Pre-stroke depression significantly increases odds of post-stroke depression.Protocol identifierPROSPERO identifier: CRD42017065544

Interventions for Adolescents With ADHD to Improve Peer Social Functioning: A Systematic Review and Meta-Analysis

2020 ◽  
pp. 108705472090651 ◽  
Author(s):  
Sarah Morris ◽  
Jade Sheen ◽  
Mathew Ling ◽  
Denise Foley ◽  
Emma Sciberras
Keyword(s):  
Social Functioning ◽  
Randomized Trials ◽  
Meta Analysis ◽  
Parent Report ◽  
Self Report ◽  
Age Group ◽  
Control Groups ◽  
Social Interventions ◽  
Meta Analyses ◽  
And Control

Objective: Peer social functioning difficulties characteristic of ADHD persist into adolescence, but the efficacy of interventions for this age group remains unclear. Method: A systematic search of nonpharmacological interventions for adolescents with ADHD (10–18 years) identified 11 trials addressing social functioning, of which eight were included in meta-analyses. Results: Random effects meta-analyses of four randomized trials found no differences in social functioning between treatment and control groups by parent- ( g = −0.08 [−0.34, 0.19], k = 4, N = 354) or teacher-report ( g = 0.17 [−0.06, 0.40], k = 3, N = 301). Meta-analyses of nonrandomized studies indicated participants’ social functioning improved from baseline to postintervention by parent-report, but not teacher- or self-report. All trials had a high risk of bias. Conclusion: These results highlight the paucity of research in this age group. There is little evidence that current interventions improve peer social functioning. Clearer conceptualizations of developmentally relevant targets for remediation may yield more efficacious social interventions.

“Just the Way You Are”: Linking Music Listening on Spotify and Personality

2020 ◽  
pp. 194855062092322
Author(s):  
Ian Anderson ◽  
Santiago Gil ◽  
Clay Gibson ◽  
Scott Wolf ◽  
Will Shapiro ◽  
...  
Keyword(s):  
Machine Learning ◽  
Personality Traits ◽  
Meta Analysis ◽  
Streaming Data ◽  
Self Report ◽  
Big Five Personality ◽  
Music Listening ◽  
Listening Behavior ◽  
Listening Behaviors ◽  
Musical Preferences

Advances in digital technology have put music libraries at people’s fingertips, giving them immediate access to more music than ever before. Here we overcome limitations of prior research by leveraging ecologically valid streaming data: 17.6 million songs and over 662,000 hr of music listened to by 5,808 Spotify users spanning a 3-month period. Building on interactionist theories, we investigated the link between personality traits and music listening behavior, described by an extensive set of 211 mood, genre, demographic, and behavioral metrics. Findings from machine learning showed that the Big Five personality traits are predicted by musical preferences and habitual listening behaviors with moderate to high accuracy. Importantly, our work contrasts a recent self-report-based meta-analysis, which suggested that personality traits play only a small role in musical preferences; rather, we show with big data and advanced machine learning methods that personality is indeed important and warrants continued rigorous investigation.

Associations of screen work with neck and upper extremity symptoms: a systematic review with meta-analysis

2019 ◽  
Vol 76 (7) ◽  
pp. 502-509 ◽  
Author(s):  
Pieter Coenen ◽  
Henk F van der Molen ◽  
Alex Burdorf ◽  
Maaike A Huysmans ◽  
Leon Straker ◽  
...  
Keyword(s):  
Upper Extremity ◽  
Prospective Studies ◽  
Meta Analysis ◽  
Self Report ◽  
Musculoskeletal Symptoms ◽  
Tablet Computers ◽  
Increased Risk ◽  
Electronic Database Search ◽  
Meta Analyses ◽  
Upper Extremity Symptoms

ObjectivesIt has often been suggested that screen work (ie, work on desktop, laptop, notebook or tablet computers) is a risk factor for neck and upper extremity symptoms. However, an up-to-date overview and quantification of evidence are lacking. We aimed to systematically review the association of exposure to screen work with neck and upper extremity symptoms from prospective studies.MethodsAn electronic database search (PubMed, Embase, Cinahl and Scopus) for prospective studies on the association of exposure to screen work and musculoskeletal symptoms was conducted. Studies were synthesised regarding extracted data and risk of bias, and meta-analyses were conducted.ResultsAfter screening 3423 unique references, 19 articles from 12 studies (with 18 538 participants) were included for the current review, with the most recent exposure assessment reported in 2005. Studies described duration and input frequency of screen work (ie, computer, keyboard and mouse use, assessed using self-reports or software recordings) and musculoskeletal symptoms (ie, self-reported neck/shoulder and distal upper extremity symptoms and diagnosed carpal tunnel syndrome [CTS]). Although there was overall an increased occurrence of musculoskeletal symptoms with larger exposure to screen work (relative risk: 1.11 [1.03 1.19]), findings were rather inconsistent with weaker (and statistically non-significant) risks when screen work was assessed by software recording (1.05 [0.91 1.21]) compared to with self-report (1.14 [1.03 1.19]).ConclusionsWe found an increased risk of musculoskeletal symptoms with screen work. However, the evidence is heterogeneous, and it is striking that it lacks information from contemporary screen work using laptop, notebook or tablet computers.

scholarly journals Genetic meta‐analysis of obsessive–compulsive disorder and self‐report compulsive symptoms

2019 ◽  
Vol 183 (4) ◽  
pp. 208-216 ◽  
Author(s):  
Dirk J. A. Smit ◽  
Danielle Cath ◽  
Nuno R. Zilhão ◽  
Hill F. Ip ◽  
Damiaan Denys ◽  
...  
Keyword(s):  
Obsessive Compulsive Disorder ◽  
Meta Analysis ◽  
Self Report ◽  
Obsessive Compulsive ◽  
Compulsive Disorder

scholarly journals A Systematic Review and Meta-Analysis of Depression among Farming Populations Worldwide

2020 ◽  
Vol 17 (24) ◽  
pp. 9376
Author(s):  
Briana N. M. Hagen ◽  
Charlotte B. Winder ◽  
Jared Wootten ◽  
Carrie K. McMullen ◽  
Andria Jones-Bitton
Keyword(s):  
Systematic Review ◽  
Sampling Error ◽  
Meta Analysis ◽  
Group Analysis ◽  
The United States ◽  
Self Report ◽  
Design Elements ◽  
Prevalence Of Depression ◽  
Migrant Farm ◽  
Substantial Heterogeneity

A systematic review and meta-analysis were conducted to determine the overall prevalence of depression among farming populations globally, and explore any heterogeneity present. Eligible studies were primary research articles published in English, which involved the collection of data for the purpose of determining the prevalence of depression among a farming population. Four relevant databases were searched in January 2019. Potential for bias was assessed using a modified Quality Assessment of Diagnostic Accuracy Studies (QUADAS) tool. From 7662 records, 72 articles were deemed relevant and had data extracted. Of these, 45 utilized the Center for Epidemiologic Studies—Depression Revised scale (CES-D/DR) to quantify depression, 42 of which were conducted in the United States (U.S.). As a result, meta-analyses were restricted to this geographic location. Substantial heterogeneity was seen in the initial whole-group analysis (I2 = 97%), and while sub-group exploration suggested a significantly higher prevalence of depression among migrant farm workers (26%, 95% CI = 21–31%) than in studies examining a non-migrant farming population (12%, 95% CI = 8–17%), substantial heterogeneity remained (I2 = 96%), indicating that the majority of between study variation was due to factors other than sampling error. Additionally, the majority of studies (81%) in migrant farm worker populations were published since 2010, while only 21% of studies in non-migrant farming populations were published in this timeframe. It is possible with recent efforts to de-stigmatize mental illness, participants in more recent studies may be more likely to self-report depressive symptoms. Hence, while it appears that migrant farmworker populations may have an elevated prevalence of depression, it is also apparent that little research in the U.S. has been done to evaluate depression among non-migrant farming populations in recent years. Perhaps a reporting bias may account for some of the difference between the two populations. A research gap also appears to exist in estimating the prevalence of depression among farming populations outside of the US. Assessment for bias at the study level revealed challenges in reporting of key study design elements, as well as potential for selection bias in the majority of studies.

scholarly journals Effects of categorization and self-report bias on estimates of the association between obesity and mortality

2015 ◽  
Vol 25 (12) ◽  
pp. 907-911.e2 ◽  
Author(s):  
Samuel H. Preston ◽  
Ezra Fishman ◽  
Andrew Stokes
Keyword(s):  
Self Report ◽  
Report Bias
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