Machine learning could predict binge behavior and help develop treatments for bulimia nervosa (BN) and alcohol use disorder (AUD). Therefore, this study evaluates person-specific and pooled prediction models for binge eating (BE), alcohol use, and binge drinking (BD) in daily life, and identifies the most important predictors.

A total of 120 patients (BN: 50; AUD: 51; BN/AUD: 19) participated in an experience sampling study, where over a period of 12 months they reported on their eating and drinking behaviors as well as on several other emotional, behavioral, and contextual factors in daily life. The study had a burst-measurement design, where assessments occurred eight times a day on Thursdays, Fridays, and Saturdays in seven bursts of three weeks. Afterwards, person-specific and pooled models were fit with elastic net regularized regression and evaluated with cross-validation. From these models, the variables with the 10% highest estimates were identified.

The person-specific models had a median AUC of 0.61, 0.80, and 0.85 for BE, alcohol use, and BD respectively, while the pooled models had a median AUC of 0.70, 0.90, and 0.93. The most important predictors across the behaviors were craving and time of day. However, predictors concerning social context and affect differed among BE, alcohol use, and BD.

Pooled models outperformed person-specific models and the models for alcohol use and BD outperformed those for BE. Future studies should explore how the performance of these models can be improved and how they can be used to deliver interventions in daily life.

This confirmatory study aimed to examine whether we can foresee recurrence of depressive symptoms using personalized modeling of rises in restlessness.

Participants were formerly depressed patients (N = 41) in remission who (gradually) discontinued antidepressants. Participants completed five smartphone-based Ecological Momentary Assessments (EMA) a day, for a period of 4 months, yielding a total of 21 180 observations. Statistical Process Control by means of Exponentially Weighted Moving Average (EWMA) control charts was used to detect rises in the EMA item ‘I feel restless’, for each individual separately.

An increase in restlessness was detected in 68.3% of the participants with recurring depressive symptoms, and in 26.3% of those who stayed in remission (Fisher's exact test p = 0.01, sensitivity was 68.3%, specificity was 73.7%). In the participants with a recurrence and an increase in restlessness, this increase could be detected in the prodromal phase of depression in 93.3% of the cases and at least a month before the onset of the core symptoms of depression in 66.7% of the cases.

Restlessness is a common prodromal symptom of depression. The sensitivity and specificity of the EWMA charts was at least as good as prognostic models based on cross-sectional patient characteristics. An advantage of the current idiographic method is that the EWMA charts provide real-time personalized insight in a within-person increase in early signs of depression, which is key to alert the right patient at the right time.

In many countries, depressed individuals often first visit primary care settings for consultation, but a considerable number of clinically depressed patients remains unidentified. Introducing additional screening tools may facilitate the diagnostic process.

This study aims to examine whether Experience Sampling Method (ESM)-based measures of depressive affect and behaviors can discriminate depressed from non-depressed individuals. In addition, the added value of actigraphy-based measures was examined.

We used data from two samples to develop and validate prediction models. The development dataset included 14 days of ESM and continuous actigraphy of currently depressed (n=43) and non-depressed individuals (n=82). The validation dataset included 30 days of ESM and continuous actigraphy of currently depressed (n=27) and non-depressed individuals (n=27). Backward stepwise logistic regression analyses were applied to build the prediction models. The performance of the models was assessed with the goodness of fit indices, calibration curves, and discriminative ability (AUC, the area under the receiver operating characteristic curve).

In the development dataset, the discriminative ability was good for the actigraphy model (AUC=0.790) and excellent for the ESM (AUC=0.991) and combined-domains model (AUC=0.993). In the validation dataset, the discriminative ability was reasonable for the actigraphy model (AUC=0.648) and excellent for the ESM (AUC=0.891) and combined-domains model (AUC=0.892).

ESM is a good diagnostic predictor and is easy to calculate, and, therefore, holds promise for implementation in clinical practice. Actigraphy shows no added value to ESM as a diagnostic predictor, but might still be useful when active monitoring with ESM is not feasible.

No significant relationships.

Greater affective inertia during the day (higher carry-over effects of prior affect to the current moment) is associated with depression and its development. However, the role of overnight affective inertia (from evening to morning) in depression, and the role of sleep therein, has been scarcely studied.

We examined i) the difference in overnight inertia for positive (PA) and negative affect (NA) between individuals with past depression, current depression, and no depression; ii) how sleep duration and quality influence overnight affective inertia in these groups, and iii) whether overnight affective inertia predicts depression development.

We used data of 579 women from the East-Flanders Prospective Twin Survey. First, individuals with past (n=82), current (n=26), and no depression (n=471) at baseline were examined, and then individuals who did (n=58) and did not (n=319) develop depression at 12-months follow-up. Affect was assessed 10 times a day for 5 days. Sleep was assessed with sleep diaries. Affective inertia was operationalized as the influence of affectt-1 on affectt. Linear mixed-effect models were used to test the hypotheses.

Overnight affective inertia was not associated with depression, neither was it differently associated with sleep characteristics in the depression groups. However, sleep characteristics were more negatively associated with morning NA in both depression groups compared to the non-depressed group. Overnight affective inertia did not predict the development of depression at follow-up.

Depression and sleep characteristics might be more related to mean affect levels rather than to more complex emotion dynamics measures. Replication of these findings with longer time-series is needed.

Preliminary results indicate that COVID-19 lockdown measures could lead to an increase in eating disorder pathology. However, some patients could be more vulnerable to experience such an increase than others. The reason why some patients are more susceptible to the impact of lockdown measures is still not known.

To analyze the impact of the Belgian COVID-19 lockdown measures on the surroundings, social context, negative affect (NA), positive affect (PA) and binge eating frequency of patients with bulimia nervosa (BN).

The data of 15 female patients with BN from an ongoing experience sampling method study were analyzed. Mixed effects models compared surroundings, social context, NA, PA and binge eating before and after the implementation of the lockdown measures.

After the implementation of the lockdown measures, significant changes in surroundings and social context were found as well as an increase in NA (p < 0.001) and decrease in PA (p = 0.015). Patients who experienced an increase in binge eating frequency also experienced a stronger increase in NA (p = 0.012) and decrease in PA (p = 0.026) after the lockdown measures were implemented.

Future research should also look at changes in surroundings, social context, affect and how these interact with factors such as personality traits and coping styles when investigating why some patients are more susceptible to the negative effects of lockdown measures than others.

It remains poorly understood how negative symptoms are experienced in the daily lives of individuals in the early stages of psychosis. We aimed to investigate whether altered affective experience, anhedonia, social anhedonia, and asociality were more pronounced in individuals with an at-risk mental state for psychosis (ARMS) and individuals with first-episode psychosis (FEP) than in controls.

We used the experience sampling methodology (ESM) to assess negative symptoms, as they occurred in the daily life of 51 individuals with FEP and 46 ARMS, compared with 53 controls.

Multilevel linear regression analyses showed no overall evidence for a blunting of affective experience. There was some evidence for anhedonia in FEP but not in ARMS, as shown by a smaller increase of positive affect (BΔat−risk v. FEP = 0.08, p = 0.006) as the pleasantness of activities increased. Against our expectations, no evidence was found for greater social anhedonia in any group. FEP were more often alone (57%) than ARMS (38%) and controls (35%) but appraisals of the social situation did not point to asociality.

Overall, altered affective experience, anhedonia, social anhedonia and asociality seem to play less of a role in the daily life of individuals in the early stages of psychosis than previously assumed. With the experience of affect and pleasure in daily life being largely intact, changing social situations and appraisals thereof should be further investigated to prevent development or deterioration of negative symptoms.

Little is known about how daily life mood reactivity to minor stressors (stress reactivity) might change following major depressive disorder (MDD) treatment. We investigate whether (i) mood states and appraisals of daily stressors change after treatment; (ii) stress reactivity to event, activity, or social stress differs; (iii) stress reactivity depends on severity of residual depressive symptoms; and (iv) stress reactivity in individuals with remitted or non-remitted depression differ from that of never-depressed individuals.

Thirty depressed individuals participated in an experience sampling study before and after a treatment period of 18 months; 39 healthy individuals formed a comparison group. Reactivity of positive affect (PA) and negative affect (NA) to daily stressors were measured.

More residual symptoms were associated with larger NA responses to stress. Compared to healthy controls, participants with non-remitted MDD showed higher NA-reactivity to all stressors. In contrast, stress reactivity to event and activity stressors was normalized in remitted patients. However, they still showed heightened NA-reactivity to social stress.

Greater stress reactivity to event and activity stress appears to be state-dependent. The heightened social stress reactivity in remitted patients suggests that sensitivity to social stress may reflect an underlying vulnerability in MDD.

The aim of the current study was to replicate findings in adults indicating that higher sensitivity to stressful events is predictive of both onset and persistence of psychopathological symptoms in a sample of adolescents and young adults. In addition, we tested the hypothesis that sensitivity to mild stressors in particular is predictive of the developmental course of psychopathology.

We analyzed experience sampling and questionnaire data collected at baseline and one-year follow-up of 445 adolescent and young adult twins and non-twin siblings (age range: 15–34). Linear multilevel regression was used for the replication analyses. To test if affective sensitivity to mild stressors in particular was associated with follow-up symptoms, we used a categorical approach adding variables on affective sensitivity to mild, moderate and severe daily stressors to the model.

Linear analyses showed that emotional stress reactivity was not associated with onset (ß = .02; P = .56) or persistence (ß = -.01; P = .78) of symptoms. There was a significant effect of baseline symptom score (ß = .53; P < .001) and average negative affect (NA: ß = .19; P < .001) on follow-up symptoms. Using the categorical approach, we found that affective sensitivity to mild (ß = .25; P < .001), but not moderate (ß = -.03; P = .65) or severe (ß = -.06; P = .42), stressors was associated with symptom persistence one year later.

We were unable to replicate previous findings relating stress sensitivity linearly to symptom onset or persistence in a younger sample. Whereas sensitivity to more severe stressors may reflect adaptive coping, high sensitivity to the mildest of daily stressors may indicate an increased risk for psychopathology.

Depression has been associated with abnormalities in neural underpinnings of Reward Learning (RL). However, inconsistencies have emerged, possibly owing to medication effects. Additionally, it remains unclear how neural RL signals relate to real-life behaviour. The current study, therefore, examined neural RL signals in young, mildly to moderately depressed – but non-help-seeking and unmedicated – individuals and how these signals are associated with depressive symptoms and real-life motivated behaviour.

Individuals with symptoms along the depression continuum (n = 87) were recruited from the community. They performed an RL task during functional Magnetic Resonance Imaging and were assessed with the Experience Sampling Method (ESM), completing short questionnaires on emotions and behaviours up to 10 times/day for 15 days. Q-learning model-derived Reward Prediction Errors (RPEs) were examined in striatal areas, and subsequently associated with depressive symptoms and an ESM measure capturing (non-linearly) how anticipation of reward experience corresponds to actual reward experience later on.

Significant RPE signals were found in the striatum, insula, amygdala, hippocampus, frontal and occipital cortices. Region-of-interest analyses revealed a significant association between RPE signals and (a) self-reported depressive symptoms in the right nucleus accumbens (b = −0.017, p = 0.006) and putamen (b = −0.013, p = .012); and (b) the quadratic ESM variable in the left (b = 0.010, p = .010) and right (b = 0.026, p = 0.011) nucleus accumbens and right putamen (b = 0.047, p < 0.001).

Striatal RPE signals are disrupted along the depression continuum. Moreover, they are associated with reward-related behaviour in real-life, suggesting that real-life coupling of reward anticipation and engagement in rewarding activities might be a relevant target of psychological therapies for depression.

Recent research emphasizes the importance of habit in explaining patterns of energy intake and choices of consumption. However, the nature of the association between habit strength and snacking has not been explored for all types of between-meal snacks.

Multilevel linear techniques were used to: (i) examine the association between habit strength and moment-to-moment energy intake (kilocalories) from snacks in daily life; and (ii) determine whether gender, age, level of education and BMI moderate the association between habit strength and moment-to-moment energy intake from snacks. A smartphone application based on the experience sampling method was used to map momentary between-meal snack intake in the context of daily life. Demographics and habit strength were assessed with an online composite questionnaire.

This research was performed in the Netherlands in the natural environment of participants’ daily life.

Adults (n 269) aged 20–50 years.

Habit strength was significantly associated with moment-to-moment energy intake from between-meal snacks in daily life: the higher the strength of habit to snack between meals, the higher the amount of momentary energy intake from snacks. The association between habit strength and moment-to-moment energy intake from snacks was moderated by education level. Additional analyses showed that habit strength was significantly associated with moment-to-moment energy intake from between-meal snacks in the low to middle level of education group.

It is recommended to address habitual between-meal snacking in future interventions targeting low- to middle-educated individuals.

Psychological models of psychosis were examined using Experience Sampling Methods (ESM) to explore relationships between dimensions and appraisals of key symptoms and affect.

Individuals were signalled to complete ESM booklets 10 times per day for six consecutive days; 534 data points were obtained from 12 out-patients with psychosis.

Although only 3.6% of spontaneous thoughts were psychosis related, these predicted more negative and less positive affect. Delusions and hallucinations, when present, were rated at a moderate level of intensity, and intensity was associated with distress, interference and preoccupation. Symptom dimensions were related to each other, with weaker associations with delusional conviction, which, it is hypothesized, may represent a separate factor. Conviction and appraisals relating to insight and decentring (‘my problems are something to do with the way my mind works’) were highly variable. Decentring appraisals of delusions, but not insight, were associated with less distress. Appraisals about the power of voices were strong predictors of negative affect and symptom distress.

This study demonstrates that ESM is a useful methodology to capture ‘online’ variability in psychotic phenomenology and provides evidence supporting cognitive models, which posit that psychotic symptoms are multi-dimensional phenomena, shaped by appraisals that, in turn, predict their emotional and behavioural sequelae.

Previous work suggests that daily life stress-sensitivity may be an intermediary phenotype associated with both genetic risk for depression and developmental stress exposures. In the current analysis we hypothesized that genetic risk for depression and three environmental exposures over the course of development [prenatal stress, childhood adversity and adult negative life events (NLEs)] combine synergistically to produce the phenotype of stress-sensitivity.

Twin pairs (n=279) participated in a momentary assessment study using the Experience Sampling Method (ESM), collecting appraisals of stress and negative affect (NA) in the flow of daily life. Prospective data on birthweight and gestational age, questionnaire data on childhood adversity and recent NLEs, and interview data on depression were used in the analyses. Daily life stress-sensitivity was modelled as the effect of ESM daily life stress appraisals on ESM NA.

All three developmental stress exposures were moderated by genetic vulnerability, modelled as dizygotic (DZ) or monozygotic (MZ) co-twin depression status, in their effect on daily life stress-sensitivity. Effects were much stronger in participants with MZ co-twin depression and a little stronger in participants with DZ co-twin depression status, compared to those without co-twin depression. NLE main effects and NLE genetic moderation were reducible to birthweight and childhood adversity.

The findings are consistent with the hypothesis that adult daily life stress-sensitivity is the result of sensitization processes initiated by developmental stress exposures. Genes associated with depression may act by accelerating the process of stress-induced sensitization.