Interpretation biases have long been theorized to play a central role in depression. Yet, the strength of the empirical evidence for this bias remains a topic of debate. This meta-analysis aimed to estimate the overall effect size and to identify moderators relevant to theory and methodology. PsycINFO, Embase, Web of Science, Scopus, PubMed, and dissertation databases were searched. A random-effects meta-analysis was performed on 87 studies (N=9443). Results revealed a medium overall effect size (g=0.72, 95%-CI:[0.62;0.82]). Equivalent effect sizes were observed for patients diagnosed with clinical depression (g=0.60, 95%-CI:[0.37;0.75]), patients remitted from depression (g=0.59, 95%-CI:[0.33;0.86]), and undiagnosed individuals reporting elevated depressive symptoms (g=0.66, 95%-CI:[0.47;0.84]). The effect size was larger for self-referential stimuli (g=0.90, 95%-CI[0.78;1.01]), but was not modified by the presence (g=0.74, 95%-CI[0.59;0.90]) or absence (g=0.72, 95%-CI[0.58;0.85]) of mental imagery instructions. Similar effect sizes were observed for a negative interpretation bias (g=0.58, 95%-CI:[0.40;0.75]) and lack of a positive interpretation bias (g=0.60, 95%-CI:[0.36;0.85]). The effect size was only significant when interpretation bias was measured directly (g=0.88, 95%-CI[0.77;0.99]), but not when measured indirectly (g=0.04, 95%-CI[-0.14;0.22]). It is concluded that depression is associated with interpretation biases, but caution is necessary because methodological factors shape conclusions. Implications and recommendations for future research are outlined.

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BackgroundCognitive behavior therapy (CBT) is the first-line of treatment for overweight and obesity patients whose problems originate in maladaptive eating habits (e.g., emotional eating). However, in-person CBT is currently difficult to access by large segments of the population. The proposed SIGMA intervention (i.e., the Self-help, Integrated, and Gamified Mobile-phone Application) is a mHealth intervention based on CBT principles. It specifically targets overweight young adults with underlying maladaptive behaviors and cognitions regarding food. The SIGMA app was designed as a serious game and intended to work as a standalone app for weight maintenance or alongside a calorie-restrictive diet for weight loss. It uses a complex and novel scoring system that allows points earned within the game to be supplemented by points earned during outdoor activities with the help of an embedded pedometer.Methods/designThe efficacy of the SIGMA mHealth intervention will be investigated within a randomized, placebo-controlled trial. The intervention will be set to last 2 months with a 3-month follow-up. Selected participants will be young overweight adults with non-clinical maladaptive eating habits embodied by food cravings, binge eating, and emotional eating. The primary outcomes will be represented by changes in (1) self-reported maladaptive thoughts related to eating and body weight, (2) self-reported maladaptive eating behaviors in the range of urgent food cravings, emotional eating or binge eating, (3) as well as biased attentional processing of food items as indexed by reaction times. Secondary outcomes will be represented by changes in weight, Body Mass Index, general mood, and physical activity as indexed by the number of steps per day.DiscussionThrough an evidence-based cognitive behavioral approach and a user-friendly game interface, the SIGMA intervention offers a significant contribution to the development of a cost-effective and preventive self-help tool for young overweight adults with maladaptive eating habits.Trial registrationISRCTN, ID: 70907354. Registered on 6 February 2017. The ISRCTN registration is in line with the World Health Organization Trial Registration Data Set. The present paper represents the original version of the protocol. Any changes to the protocol will be communicated to ISRCTN.Electronic supplementary materialThe online version of this article (doi:10.1186/s13063-017-2340-6) contains supplementary material, which is available to authorized users.

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