Anticipation and Motivation as Predictors of Leisure and Social Enjoyment and Engagement in Young People With Depression Symptoms: Ecological Momentary Assessment Study
Bibliographic record
Abstract
Background: Participating in leisure and social activities can alleviate depression symptoms, yet effective strategies to enhance enjoyment and maintain long-term engagement remain scarce. Gaining insight into the reward subcomponents that influence daily experiences and drive behavior could uncover novel targets for intervention. Objective: This study examines the role of anticipation and motivation in predicting enjoyment and engagement in leisure activities and socializing among young people, and how these relationships are moderated by depression severity, using intensive longitudinal ecological momentary assessments. Methods: Participants (N=80; mean age 20, SD 2.3 years) used the Psymate2 smartphone app to report mood, enjoyment, current and anticipated activities, and social company 7 times daily for 6 days. Activity categories were relaxation, exercise, other leisure, work or school, studying, chores, shopping, hygiene, eating or drinking, and traveling, and company categories were partner, friends, family, colleagues, acquaintances, strangers, and nobody. Anticipation (anticipatory pleasure and expectation) and motivation (interest and preference) for upcoming activities were rated on Likert scales. Participants were grouped by depression severity, measured using the Mood and Feelings Questionnaire (MFQ): high (HD, MFQ ≥27, N=42), moderate (MD, MFQ 16-27, N=16), and low, that is, controls (C, MFQ ≤16, N=22). Totally, 2316 assessments met inclusion criteria. Results: Leisure activities (relaxation, exercise, and other leisure) and social company (partner, friends, and family) were rated most enjoyable across all groups. Higher depression symptoms were associated with reduced enjoyment of studying (β=-.03; P=.005), eating or drinking (β=-.02; P=.02), and other leisure activities (β=-.02; P=.02), as well as lower engagement in work or school (β=-.26; P=.02) and hygiene (β=-.08; P=.03), and increased inactivity (β=.17; P=.03). Time-lagged multilevel analyses showed that anticipatory pleasure predicted greater enjoyment across all activities (β=.12; P<.001) and social contexts (β=.33; P<.001), with consistent effects in controls and the high depression group. However, the more an activity was expected to happen, the less enjoyment was experienced in the whole sample (β=-.006; P=.001) and high depression group (β=-.008; P=.001) but not controls. Anticipatory pleasure and motivation (preference) predicted leisure engagement in the whole sample (β=.19, P=.003; β=.11, P<.001) and controls (β=.43, P=.005; β=.17, P=.048) but not the depression groups. Anticipatory pleasure predicted only leisure engagement in the high depression group when predictors and outcomes were matched for the same event (β=.22; P=.001). Anticipatory pleasure predicted social engagement in the whole sample (β=.095; P=.047) and controls (β=.34; P=.003), but not in the depression groups. Conclusions: These findings highlight the importance of anticipatory pleasure and intrinsic motivation in shaping young people's engagement and enjoyment of daily activities. Structured or externally driven contexts may dampen enjoyment-especially among those with depression-underscoring the need for novel interventions targeting anticipation and motivation to enhance sustained participation in rewarding activities, leading to improved well-being in individuals with depression.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".