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. 2026 Mar 5;26:259. doi: 10.1186/s12893-026-03526-7

Patterns of change in impulsivity after bariatric surgery: evidence from 24 months of follow-up

Ke-jia Wu 1,2,#, Xu-ge Qi 2,4,#, Jian-Zhong Di 1, Xiao-Dong Han 1,✉, Hui Zheng 1,3,✉
PMCID: PMC13069754  PMID: 41781929

Abstract

Background

Metabolic and bariatric surgery is the most effective obesity treatment, and it has been demonstrated that an individual’s preoperative impulsivity can modulate the effects of MBS. However, it remains unclear whether MBS subsequently alters impulsive personality traits and impulsive decision-making.

Methods

A total of 66 MBS candidates were followed for 24 months after surgery. Impulsive decision-making and impulsive personality were assessed using the Delay Discounting Task and the Barratt Impulsiveness Scale, respectively. A mixed linear model incorporating anxiety and depression levels was applied to examine postoperative changes across each three-month postoperative period (quarter).

Results

Patients with obesity showed a significant reduction in impulsive personality after surgery, reaching a level comparable to that of healthy controls within the first three months. Impulsive decision-making also improved substantially following surgery. While reductions in depression and anxiety contributed meaningfully to improvements in impulsive personality, they did not exert a significant influence on impulsive decision-making.

Conclusion

Both impulsive personality and impulsive decision-making improved significantly following MBS. Impulsive personality declined to a level similar to healthy individuals within the first three months, and improvements in depression and anxiety further facilitated this reduction. These findings highlight the clinical relevance of monitoring impulsivity and emotional symptoms after surgery, as such improvements may enhance postoperative behavioral adherence and long-term weight-management outcomes.

Keywords: Metabolic and bariatric surgery, Impulsive personality, Impulsive decision-making, Delayed discounting

Introduction

Obesity is a global health problem linked to type 2 diabetes, cardiovascular disease, and other comorbidities [17]. metabolic and bariatric surgery (MBS) is the most effective treatment for severe obesity, producing substantial and sustained weight loss and metabolic benefits [5, 38]. However, a subset of patients experiences suboptimal weight loss or weight regain [3], partly due to behavioral and psychological factors. Increasing evidence suggests that impulsivity, characterized by rapid, unplanned reactions to stimuli, as a contributor to maladaptive eating and poorer postoperative outcomes [26, 34].

Impulsivity is a behavioral tendency toward rapid responses with limited forethought and insufficient consideration of potential negative consequences [23]. In individuals with obesity, heightened impulsivity is associated with susceptibility to food rewards, poor planning, and impaired regulation of food intake, thereby contributing to weight gain [6]. Impulsivity has also been shown to predict weight loss outcomes following intervention [30]. However, prior research has largely focused on the relationship between impulsivity and postoperative weight outcomes [18], with few studies examining postoperative changes in impulsivity from a cognitive perspective after MBS [11].

Impulsivity is increasingly conceptualized as a multidimensional construct encompassing impulsive personality and impulsive decision-making [21]. Impulsive personality reflects relatively stable, trait-like tendencies and is commonly assessed using self-report measures such as the Barratt Impulsiveness Scale (BIS; Patton et al., [16, 27], whereas impulsive decision-making captures more dynamic, state-dependent choice processes and is typically measured using delay discounting tasks (DDT), with steeper discounting indicating greater impulsivity [22]. Assessing both facets provides a more comprehensive account of impulsivity, as trait-level tendencies do not fully determine real-time decision behavior. However, most prior studies have relied primarily on self-report measures, with limited use of behavioral or modeling-based tasks [11, 18, 37]. Individuals with obesity generally exhibit elevated impulsivity across both domains [7], which has been linked to reduced activity in the dorsolateral prefrontal cortex, a key region for self-regulation [14], as well as steeper delay discounting compared with individuals with normal weight [28]. However, how MBS affects different facets of impulsivity remains unclear, and existing findings are mixed. Some studies suggest that postoperative weight outcomes are more closely related to impulsive action than to trait impulsivity [37], whereas a recent systematic review reported reductions in impulsive personality following MBS, with trait-level changes predicting weight loss [11]. Large prospective studies further indicate that impulsivity, alongside psychopathology and disordered eating, predicts long-term postoperative weight trajectories [31, 32]. Overall, prior research has largely examined impulsive personality and impulsive decision-making in isolation, limiting conclusions regarding how MBS alters these complementary facets. Integrating both components within the same cohort is therefore essential to clarify postoperative behavioral change and to optimize long-term weight management after MBS.

Furthermore, emotional states may differentially influence cognitive representations and self-regulatory processes involved in impulsivity. Individuals with higher impulsive personality traits are more likely to rely on immediate, concrete representations, a tendency that can be amplified by anxiety and depressive symptoms through reduced top-down control and heightened sensitivity to affective cues [9]. Empirical evidence indicates that higher levels of anxiety and depressive symptoms are associated with greater impulsivity and poorer weight-loss outcomes, whereas postoperative reductions in these symptoms are linked to improved self-regulation and more favorable weight trajectories [34, 39]. Importantly, individuals seeking MBS frequently report elevated anxiety and depressive symptoms, which typically improve following surgery [12, 33]. Clinically, improvements in postoperative emotional symptoms may facilitate more goal-directed decision-making and support sustained weight loss, whereas persistent emotional distress may undermine behavioral control [25]. Overall, the present study assessed impulsive personality (BIS-11) and impulsive decision-making (DDT) before and 24 months after MBS, hypothesizing that both facets of impulsivity would decrease after surgery, that reductions in anxiety and depressive symptoms would be associated with reduced impulsivity.

Methods

In this observational cohort study, candidates for MBS were recruited and followed from March 2020 to October 2022. Patients signed informed consent and their anonymity was retained. As shown in Fig. 1, all eligible patients with obesity underwent MBS. At baseline(pre-surgery), demographic information (age, sex, years of education) and body mass index (BMI) data were collected for the patients with obesity and healthy participants included in the study, along with baseline measurements of impulsive decision-making and impulsive personality. Anxiety and depressive symptoms were also assessed as potential covariates. Following surgery, participants with obesity were followed up monthly during the first 18 months, with a final assessment conducted at 24 months postoperatively. Postoperative time was operationalized in three-month intervals (quarters) for statistical analyses. This study has been approved by the Ethics Committee of Shanghai Sixth People’s Hospital 2020-219-(1) conducted in accordance with the Declaration of Helsinki and APA ethical standards. The data that support the findings of this study are openly available in https://osf.io/hkjbe/overview.

Fig. 1.

Fig. 1

The recruitment of participants, study design and data analysis. Basic information of all participants was collected, including genders, education years, ages, and BMIs. All the participants were supposed to complete questionnaires and DDT task to evaluate their psychological factors. Postoperative follows-ups were performed in the first 18 months and the 24th month, with data from the first 18 months aggregated into 3-month quarters for analysis (boxed). The data was analysis by the Linear mixed model, the Mountain map, and the independent samples t test

Participants

From March 2020 to October 2022, 66 patients (37 with available baseline data) undergoing MBS at Department of Bariatric and Metabolic Surgery at the Sixth People’s Hospital of Shanghai Jiao Tong University were recruited and informed about the study. 55 healthy controls were recruited from the general community via online advertisements to compare the postoperative recovery of the patients. Participants with obesity were assessed and recruited by trained clinical physicians during routine preoperative visits. All participants were over 18 years old, had normal cognitive function, and no major medical illnesses, and provided written informed consent. Patients undergoing MBS met the criteria for obesity (BMI ≥ 26), whereas those with major medical illnesses or obesity secondary to metabolic syndrome were excluded to reduce clinical heterogeneity. Healthy controls had a BMI ≤ 24 and no history of major medical or psychiatric illness, and were assessed at baseline only. At the time of analysis, participants with obesity had been followed for up to 24 months postoperatively.

Measures

Impulsive decision-making

Impulsive decision-making was assessed using an online Delay Discounting Task (DDT), in which participants made 50 choices between a smaller immediate reward and a larger delayed reward, capturing the tendency to prefer immediate gratification over delayed but larger outcomes. Three computational models- the Hyperbolic Model, Exponential Model, and Constant Sensitivity Model- were fitted to participants’ choices at each time point, with the Constant Sensitivity Model best describing the data. Key parameters in this model included the delay discounting rate (k), indicating the degree to which future rewards are devalued, with higher k reflecting greater impulsivity; temporal sensitivity (s), reflecting how sharply individuals differentiate between immediate and delayed rewards, with higher s indicating a more dichotomous ‘present vs. future’ perspective; and inverse temperature (β), capturing choice consistency, with higher inverse temperature indicating more deterministic and consistent decisions. Together, these parameters provide a comprehensive measure of cognitive impulsivity.

Impulsive personality

The Barratt Impulsiveness Scale-11 (BIS-11; Patton, Stanford, & Barratt [27]), was adopted to measure impulsiveness. The test allows to detect 3 components of impulsivity: motor impulsiveness (acting without thinking), attentional impulsiveness (not focusing on the task at hand, cognitive instability), and nonplan impulsiveness (lack of orientation to the future). The test consists of 30 items, with Likert scale ranging from 1 (rarely/never) and 4 (often/always). In this study, the Cronbach alpha coefficient of the scale was 0.79. Results of Confirmatory Factor Analysis (CFA) showed that χ²/df = 4.736, Comparative Fit Index (CFI) = 0.869, Tucker-Lewis Index (TLI) = 0.856, Root Mean Square Error of Approximation (RMSEA) = 0.092(90%CI = 0.088, 0.097), indicating a suitable validity.

Anxiety levels

The anxiety level was measured by Beck Anxiety Inventory designed by Beck [1]. The scale includes 21 self-assessment items, and the degree to which the subject is bothered by multiple anxiety symptoms is used as an indicator, using a 4-point scale. The criteria were “1” for none; “2” for mild, not much bother; “3” for moderate, feeling uncomfortable but tolerable; “4 " means severe. The Cronbach’s α for the scale in this study was 0.92. Results of CFA showed that χ²/df = 7.423, CFI = 0.737, TLI = 0.708, RMSEA = 0.121(90%CI = 0.115, 0.127), which indicates it has a suitable validity in this study.

Depression level

The depression level was assessed by the Beck depression inventory, which was developed by Beck [2]. The questionnaire included 21 items, each item is rated from 0 to 3, and the total score of the scale is the sum of 21 items, and the scale score ranges from 0 to 63; according to the score boundaries provided by the original scale: The total score of 0–13 is no depression, 14–19 is mild depression, 20–28 is moderate depression, and 29–63 is severe depression. The Cronbach alpha coefficient of the questionnaire in this study was 0.94. Results of CFA showed that χ²/df = 4.116, CFI = 0.904, TLI = 0.893, RMSEA = 0.084 (90%CI = 0.078, 0.090), indicating it has a good validity in this study.

Data analyses

The statistical analysis and mapping were performed based on Jamovi v2.3.16, GraphPad v 9.4.1 and R x64 4.1.2. Firstly, descriptive statistics were performed on BMI data, impulsivity, and related psychological variables at baseline. Subsequently, postoperative data were aggregated into quarterly intervals, with each quarter representing a three-month period. This approach integrated the intensive follow-up assessments into a unified longitudinal framework and reduced short-term variability. Mixed linear models (MLMs) were then applied, with postoperative quarter included as a fixed effect, to examine the associations between postoperative impulsive decision-making, impulsive personality, and time since surgery in patients. The MLMs were specified as follows:

  • BIS-11~ 1 + quarter + (1 | Participants)

  • BIS-11 nonplan ~ 1 + quarter +( 1 | Participants)

  • BIS-11 motor ~ 1 + quarter +( 1 | Participants)

  • BIS-11 attention ~ 1 + quarter +( 1 | Participants)

  • r~ 1 + quarter +( 1 | Participants)

  • s ~ 1 + quarter +( 1 | Participants)

  • β ~ 1 + quarter +( 1 | Participants)

In order to further explore the alterations of impulsive personality in patients after MBS, we compared impulsive personality in patients undergoing MBS with that of participants without obesity. First, we used propensity score matching based on age, gender, and years of education to consider whether patients with obesity seeking MBS could be compared with healthy individuals. We first attempted 1:1 nearest neighbor propensity score matching without substitution, using covariate-treated logistic regression to estimate propensity score. This matching specification produced a poor balance, so we instead tried an exact match for propensity scores, which produced an adequate balance. Subsequently, we conducted an independent sample T-test between the impulsive personality scores of matched patients and those of healthy individuals one quarter after surgery.

To further explore the reasons for the alteration of impulsive personality and impulsive decision-making after MBS. We then used anxiety and depression as covariables to examine the effects of these factors on impulsivity after MBS. The updated MLM model is as follows:

  • BIS-11 ~ 1 + quarter + BAI + quarter: BAI+( 1 | Participants)

  • BIS-11 ~ 1 + quarter + BDI + quarter: BDI+( 1 | Participants)

  • BIS-11 nonplan ~ 1 + quarter + BAI + quarter: BAI+( 1 | Participants)

  • BIS-11 nonplan ~ 1 + quarter + BDI + quarter: BDI+( 1 | Participants)

  • BIS-11 motor ~ 1 + quarter + BAI + quarter: BAI+( 1 | Participants)

  • BIS-11 motor ~ 1 + quarter + BDI + quarter: BDI+( 1 | Participants)

  • BIS-11 attention ~ 1 + quarter + BAI + quarter: BAI+( 1 | Participants)

  • BIS-11 attention ~ 1 + quarter + BDI + quarter: BDI+( 1 | Participants)

  • s ~ 1 + quarter + BAI + quarter: BAI+( 1 | Participants)

  • s ~ 1 + quarter + BDI + quarter: BDI+( 1 | Participants)

  • r ~ 1 + quarter + BAI + quarter: BAI+( 1 | Participants)

  • r ~ 1 + quarter + BDI + quarter: BDI+( 1 | Participants)

  • β ~ 1 + quarter + BAI + quarter: BAI+( 1 | Participants)

  • β ~ 1 + quarter + BDI + quarter: BDI+( 1 | Participants)

Compared with traditional repeated measure ANOVA, the mix linear model has a great advantage in dealing with missing values in datasets. Due to the possible missing in longitudinal data collection, MLM can employ restricted maximum likelihood to obtain the best estimations of each parameter, and therefore can include the remaining observations to avoid the waste of resources caused by data discarding due to missing values and the deviation of results caused by not considering all sample information.

Results

The characters of participants

In this study, preoperative data were collected from 37(27 female) of the 66 patients to examine potential covariates and to investigate whether patients’ impulsive personality and decision making would change substantially following MBS. Table 1 summarizes sociodemographic, anthropometric information (age, education years, BMI), and psychological measures (impulsive personality, impulsive decision-making, BAI, BDI, PSQI) for patients with obesity and healthy participants at baseline.

Table 1.

Mean values of the parameters of the participants at baseline

Group(M ± SD) t p Cohen’s d
Patients (N = 37) Healthy subject
(N = 55)
Age 28.5 ± 5.54 30.27 ± 8.74 -1.84 0.070 -0.390
Education years 14.2 ± 2.85 15.89 ± 3.84 -2.21 0.030* -0.470
BMI 38.49 ± 5.98 20.96 ± 1.46 22.41 < .001*** 4.765
Discounting rate k 0.13 ± 0.14 - - - -
Temporal sensitivity 1.29 ± 0.51 - - - -
Inverse temperature 0.14 ± 0.13 - - - -
BIS-11 non-planning 41.8 ± 18.6 33.68 ± 15.80 2.11 0.038* 0.449
BIS-11 motor 41.4 ± 15.1 35.45 ± 15.38 3.87 < .001*** 0.823
BIS-11 attention 43.5 ± 14.5 40.68 ± 13.75 2.41 0.018* 0.512
BIS-11 total score 42.23 ± 48.2 36.61 ± 10.36 4.02 < .001*** 0.854
BAI 9.97 ± 9.11 3.02 ± 4.30 5.54 < .001*** 1.178
BDI 13.7 ± 9.56 8.29 ± 8.40 4.01 < .001*** 0.853

SD standard deviation, M mean, BMI body mass index, BIS-11 Barratt Impulsiveness Scale-11, BIS-11 non-planning non-planning subscale of BIS-11, BIS-11 motor motor impulsivity subscale of BIS-11, BIS-11 attention attentional impulsivity subscale of BIS-11, BIS-11 total score total score of BIS-11, BAI Beck Anxiety Inventory, BDI Beck Depression Inventory, Discounting rate k discounting rate from Delay Discounting Task, Temporal sensitivity temporal sensitivity from Delay Discounting Task. Inverse temperature inverse temperature from Delay Discounting Task

*p < 0.05. ***p < 0.00

The alteration in impulsivity

To test our hypothesis that MBS can improve impulsivity in patients with obesity, we adopted a mixed linear model with postoperative time as the predictive variable, impulsivity in patients (including impulsive decision-making and impulsive personality) as the predictive variable, and patients as clustering (see the methods section for specific formulas). The results supported our hypothesis, and the patients showed a significant decline in impulsive personality and impulsive decision-making compared with the preoperative results.

The alteration in impulsivity personality

The impulsive personality of patients decreased significantly after MBS (t (69) = 22.04, p < 0.001), as shown in Fig. 2, whose decline was concentrated in the first quarter (t (370) = 2.64, p < 0.01) and remained stable in each quarter after that. For the three dimensions of impulsive personality, as shown in Fig. 3, nonplan impulse (t (66) = 17.30, p < 0.001), motor impulse (t (71) = 16.51, p < 0.001) and attention impulse (t (70) = 21.72, p < 0.001) showed significant alterations after surgery, and motor impulse (t (376) = 2.85, p < 0.01) and attention impulse (t (378) = 2.95, p < 0.01) also showed a significant decrease in the first quarter after surgery.

Fig. 2.

Fig. 2

Impulsive personality stabilization after MBS. Panel a show the dispersion of patient BIS-11 scores across postoperative quarters. The gray area represents distribution density, and the red vertical line indicates the central tendency for each quarter. Panel b depicts changes in BIS-11 scores after MBS, based on mixed linear model analyses. Small black dots represent individual scores, large black dots show the mean for each quarter, and lines indicate individual trajectories. In the legend, black lines denote significant differences between quarters, and gray lines indicate non-significant differences

Fig. 3.

Fig. 3

Impulsive personality subdimensions stabilization after MBS. Panels a–c show the dispersion of patient non-planning, motor, and attentional impulsivity across postoperative quarters. The gray area represents the distribution density, and the red vertical line indicates the central tendency for each quarter. Panels d–f depict changes in these subdimensions after MBS, derived from mixed linear model analyses. Small black dots represent individual patient scores, large black dots show the mean for each quarter, and lines indicate individual trajectories. In the legend, black lines denote significant differences between quarters, and gray lines indicate non-significant differences

In addition, in order to further explore the decline of impulsive personality after MBS, we conducted an independent sample t-test between impulsive personality of patients in the first quarter after surgery and healthy control group based on propensity score. As shown in Fig. 4, the results indicated that after one quarter of MBS, there was no significant difference in impulsive personality score between patients with obesity and healthy people (p = 0.079), and there was no significant difference in the subdimensions of motor impulse (p = 0.071) and attention impulse (p = 0.565), while the nonplan impulse of postoperative patients was significantly higher than that of healthy subjects (t (99) =2.44, p < 0.05).

Fig. 4.

Fig. 4

Impulsive personality of two groups after MBS. Panels a, b, c, and d show the results of independent sample T-test for impulsive personality between obese and healthy subject in the quarter after surgery

The alteration in impulsivity decision-making

For the three indicators of patients’ impulsive decision-making, as shown in Fig. 5, time sensitivity (t (63) = 53.1, p < 0.001), discounting rate k (t (71) = 7.89, p < 0.001), inverse temperature (t (78) = 10.90, p < 0.001) showed significant alteration. Of these, the discounting rate k for patients, began to increase significantly in the third quarter after surgery (t (410) = 4.30, p < 0.001). For patients’ time sensitivity index, a significant decrease was observed in the second quarter after surgery (t (416) =-5.11, p < 0.001), a significant increase was observed in the 6th quarter after surgery (t (434) = 2.71, p < 0.01). The inversion temperature of patients began to increase significantly in the third quarter after surgery (t (419) = 3.75, p < 0.001).

Fig. 5.

Fig. 5

Impulsive decision-making stabilization after MBS. Panels a–c show the dispersion of patient time sensitivity, discounting rate (k), and inverse temperature across postoperative quarters. The gray area represents distribution density, and the red vertical line indicates the central tendency for each quarter. Panels d–f depict changes in these measures after MBS, based on mixed linear model analyses. Small black dots represent individual patient scores, large black dots show the mean for each quarter, and lines indicate individual trajectories. In the legend, black lines denote significant differences between quarters, and gray lines indicate non-significant differences

In addition to comparisons to baseline, we also performed a replication comparison, which compares alterations at two adjacent points in time to determine in which quarter after surgery this improvement occurred primarily. We found that for alterations in postoperative patients’ discounting rate k, the discounting rate k decreased significantly in the third quarter after surgery (t (385) =-4.72, p < 0.001), while the discounting rate k increased significantly in the fourth quarter (t (387) = 4.76, p < 0.001). As for the alteration in time sensitivity of patients, there was a significant decrease in time sensitivity in patients in the second (t(394) = 3.98, p < 0.001) and third (t(391) = 9.85, p < 0.001) postoperative quarters, and in the fourth (t(402)=-9.94, p < 0.001) and the sixth quarter (t(396)=-11.71, p < 0.001), there was a significant increase in time sensitivity, while by the eighth quarter (t(416) = 4.69, p < 0.001) had a significant decrease. Inverse temperature decreased significantly in the third quarter after surgery (t (393) =-5.42, p < 0.001), and increased significantly in the fourth quarter (t (396) = 3.93, p < 0.001). However, in the eighth quarter (t (411) =-7.36, p < 0.001), again showing a significant decline (as shown in Fig. 4). Thus, the above illustrates that the time window for improving patients’ impulsive decision-making after surgery is mainly between the third and eighth quarters.

Covariant factors of impulsive personality

In order to further investigate the factors affecting the alterations in impulsive personality and impulsive decision making after surgery, we updated the existing mixed linear model to include depression and anxiety as covariables (see the Methods section for specific formulas). The results showed that postoperative depression and anxiety had no significant effect on the alterations of impulsive decision-making, but for the alterations of impulsive personality, depression (t (372) =-3.44, p < 0.001) and anxiety (t (352) =-3.09, p < 0.005) had significant influence on the decline of impulsive personality in the first quarter after surgery. Patients with high depression and anxiety levels had a slower decline in impulsive personality after surgery, while patients with low depression and anxiety levels had a faster decline in impulsive personality after surgery.

In addition, to further explore how depression and impulsivity affect the alterations of impulsive personality after surgery, we constructed similar models for the three sub-dimensions of impulsive personality, and found that depression (t (380) =-3.91, p < 0.001) and anxiety level (t (357) =-3.56, p < 0.001) The influence on postoperative impulsive personality alteration was reflected in the cognitive impulse dimension. For nonplan impulse and motor impulse, there was no significant difference in postoperative impulsive personality alteration in patients with different levels of depression or anxiety.

Discussion

This study prospectively examined the improvement in impulsivity in patients with obesity after MBS and explored the associated effects using a mixed linear model. The main findings are as follows: (1) Impulsive personality in patients undergoing MBS improved significantly and did not differ significantly from healthy individuals one quarter after surgery. (2) Impulsive decision-making in patients improved significantly after MBS. (3) There was a significant interaction between changes in impulsive personality and changes in depressive and anxiety symptoms among patients undergoing MBS, consistent with our hypothesis. First, impulsive personality showed a marked reduction following MBS, particularly during the early postoperative period, with significant improvements observed across non-planning, motor, and attentional impulsivity. These changes were comparable to healthy controls shortly after surgery, consistent with previous findings linking MBS to modulation of reward-related and executive-control systems [13, 35]. Some researchers suggest that a decrease in impulsive personality predicts greater weight loss and can contribute to successful weight control by reducing pathological eating behaviors [19, 34]. Compared with behavioral interventions such as diet or exercise, whose outcomes are often influenced by baseline impulsivity and marked variability, MBS may offer the additional benefit of altering impulsive personality traits, potentially supporting sustained weight loss and long-term weight maintenance in individuals with obesity. However, a rebound in impulsive personality was observed at the eighth postoperative stages, echoing prior reports of relapse [37]. This pattern underscores the importance of ongoing psychological monitoring and targeted behavioral support after surgery, as sustained regulation of impulsive traits may be critical for long-term weight maintenance.

Second, impulsive decision-making improved significantly after MBS across all parameters derived from the constant-sensitivity model, including temporal sensitivity, discounting rate, and inverse temperature. These improvements became most evident after the third postoperative quarter, aligning with evidence that enhanced executive function and dopaminergic signaling accompany postoperative weight loss [10, 14, 18]. MBS alters neural activity in the cerebral cortex associated with food reward through a variety of pathways, including alterations in the availability of dopamine receptors [4]. Then, by further comparing the alterations at two adjacent time points, we found that the improvement in impulsive decision-making after MBS in participants with obesity occurred mainly after the third quarter. Given that impulsive decision-making predicts postoperative weight outcomes [29, 31], this period may represent a critical window during which cognitive changes and weight loss mutually reinforce one another, highlighting the value of close clinical attention to decision-making tendencies in early postoperative follow-up.

In addition, postoperative anxiety and depressive symptoms were significantly associated with impulsive personality but not with impulsive decision-making. Patients with higher levels of anxiety and depression showed elevated impulsive personality, particularly attentional impulsivity, which is closely linked to emotional dysregulation and maladaptive eating behaviors [24]. Prior longitudinal studies indicate that MBS is often accompanied by substantial improvements in anxiety and depressive symptoms, which are also important psychological predictors of surgical success [20, 36, 39]. The distinct emotional effects on impulsive personality and impulsive decision-making likely reflects differences in construct sensitivity and supported by evidence that self-report and behavioral measures of impulsivity show weak correlations and reflect partially distinct psychological constructs [8]. As a self-reported and trait-like construct, impulsive personality is more directly influenced by affective states, whereas DDT assess context dependent cognitive processes that are less susceptible to emotional fluctuation and more strongly shaped by postoperative neurobiological changes [15]. These findings suggest that postoperative psychological support targeting anxiety and depression, such as psychosocial interventions and cognitive behavioral therapy may help stabilize impulsive personality, particularly attentional control, thereby enhancing long-term surgical outcomes [40].

However, there are some limitations in this study. First, the return rate of our sample needs to be improved. Since we did a long span of follow-up of patients with obesity after MBS, there were more missing data in the process. In future studies, we will further improve postoperative follow-up and maximize recovery through updating our follow-up protocols and sample collection procedures, and communicating with patients more efficiently, including the validation of contact info at recruitment. Secondly, this study was conducted more through questionnaires as well as behavioral task for patient condition collection and lacked neuroimaging to detect physiological alterations in patients’ periphery, which shall be considered in future studies.

Conclusion

In summary, the present study shows that both impulsive personality and impulsive decision-making improved significantly after MBS, with impulsive personality reaching levels comparable to those of healthy controls during the early postoperative period. Moreover, reductions in postoperative depression and anxiety were significantly associated with improvements in impulsive personality. Together, these findings underscore the importance of early psychological monitoring and targeted support for anxiety and depression to help stabilize impulsive tendencies and optimize long-term postoperative outcomes.

Acknowledgements

The authors would like to acknowledge Hui-Lin Zhang and Chuan-Yu Yin, Hui-Ting Cai for their help with data collection, data analysis and advice on writing the article.

Authors’ contributions

Conceptualization, Jian-Zhong Di and Hui Zheng; Data curation, Ke-Jia Wu; Investigation, Xu-Ge Qi; Methodology, Ke-Jia Wu, Xiao-Dong Han; Visualization, Ke-Jia Wu; Writing – original draft, Ke-Jia Wu; Writing – review & editing, Xu-Ge Qi and Hui Zheng.

Funding

Support was provided by the Shanghai Health Commission project (NO. 20214098); Shanghai Science and Technology Committee project (NO. 22dz1204700), National Science and Technology Major Project of the Ministry of Science and Technology of China (NO. 2022YFC2407004).

Data availability

The data that support the findings of this study are openly available in osf.io/hkjbe.

Declarations

Ethics approval and consent to participate

This study has been approved by the Ethics Committee of Shanghai Sixth People’s Hospital 2020-219-(1) conducted in accordance with the Declaration of Helsinki and APA ethical standards. All participants from study provided written informed consent before taking part in the research.

Competing interests

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Footnotes

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Ke-jia Wu and Xu-ge Qi contributed equally to this work.

Contributor Information

Xiao-Dong Han, Email: 18930172941@163.com.

Hui Zheng, Email: zh.dmtr@gmail.com.

References

  • 1.Beck AT, Epstein N, Brown G, Steer RA. An inventory for measuring clinical anxiety: psychometric properties. J Consult Clin Psychol. 1988;56:893–7. [DOI] [PubMed] [Google Scholar]
  • 2.Beck AT, Rush AJ, Shaw BF, Emery G. Cognitive therapy of depression. New York: Guilford Press; 1979. [Google Scholar]
  • 3.Brandão I, Ramalho S, Pinto-Bastos A, Arrojado F, Faria G, Calhau C, Coelho R, Conceição E. Metabolic profile and psychological variables after bariatric surgery: association with weight outcomes. Eat Weight Disorders: EWD. 2015;20(4):513–8. [DOI] [PubMed] [Google Scholar]
  • 4.Bruce JM, Hancock L, Bruce A, Lepping RJ, Martin L, Lundgren JD, Malley S, Holsen LM, Savage CR. Changes in brain activation to food pictures after adjustable gastric banding. Surg Obes Relat Diseases: Official J Am Soc Bariatr Surg. 2012;8(5):602–8. [DOI] [PubMed] [Google Scholar]
  • 5.Buchwald H, Avidor Y, Braunwald E, Jensen MD, Pories W, Fahrbach K, et al. Bariatric surgery: a systematic review and meta-analysis. JAMA. 2004;292(14):1724. [DOI] [PubMed] [Google Scholar]
  • 6.Burger KS, Berner LA. A functional neuroimaging review of obesity, appetitive hormones and ingestive behavior. Physiol Behav. 2014;136:121–7. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 7.Chalmers DK, Bowyer CA, Olenick NL. Problem drinking and obesity: A comparison in personality patterns and life-style. Int J Addict. 1990;25:803–17. [DOI] [PubMed] [Google Scholar]
  • 8.Creswell KG, Wright AGC, Flory JD, Skrzynski CJ, Manuck SB. Multidimensional assessment of impulsivity-related measures in relation to externalizing behaviors. Psychol Med. 2019;49(10):1678–90. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 9.Cyders MA, Smith GT, Spillane NS, Fischer S, Annus AM, Peterson C. Integration of impulsivity and positive mood to predict risky behavior: development and validation of a measure of positive urgency. Psychol Assess. 2007;19(1):107–18. [DOI] [PubMed] [Google Scholar]
  • 10.Frank S, et al. Altered brain activity in severely obese women May recover after Roux-en Y gastric bypass surgery. Int J Obes (Lond). 2014;38(3):341–8. [DOI] [PubMed] [Google Scholar]
  • 11.Giel KE, Camacho-Barcia L, Schultze-Rhonhof L, et al. Longitudinal dynamics of impulsivity in individuals undergoing obesity surgery – a systematic review. Rev Endocr Metab Disord. 2025. 10.1007/s11154-025-10000-x. Advance online publication. [DOI] [PubMed]
  • 12.Gill H, Kang S, Lee Y, Rosenblat JD, Brietzke E, Zuckerman H, McIntyre RS. The long-term effect of bariatric surgery on depression and anxiety. J Affect Disord. 2019;246:886–94. [DOI] [PubMed] [Google Scholar]
  • 13.Guerrieri R, Nederkoorn C, Jansen A. The effect of an impulsive personality on overeating and obesity: current state of affairs. Psihologijske Teme. 2008;17(2):265–86. [Google Scholar]
  • 14.Han XD, Zhang HW, Xu T, Liu L, Cai HT, Liu ZQ, Li Q, Zheng H, Xu T, Yuan TF. How impulsiveness influences obesity: the mediating effect of Resting-State brain activity in the DlPFC. Front Psychiatry. 2022;13:873953. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 15.Herman AM, Critchley HD, Duka T. Risk-Taking and impulsivity: the role of mood States and interoception. Front Psychol. 2018;9:1625. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 16.Huang Y, Luan S, Wu B, Li Y, Wu J, Chen W, Hertwig R. (2024). Impulsivity is a stable, measurable, and predictive psychological trait. Proc Natl Acad Sci USA, 121(24), e2321758121. [DOI] [PMC free article] [PubMed]
  • 17.Kopelman PG. Obesity as a medical problem. Nature. 2000;404:635–43. [DOI] [PubMed] [Google Scholar]
  • 18.Kulendran M, Borovoi L, Purkayastha S, Darzi A, Vlaev I. Impulsivity predicts weight loss after obesity surgery. Surg Obes Relat Dis. 2017;13(6):1033–40. [DOI] [PubMed] [Google Scholar]
  • 19.Larsen F, Torgersen S. Personality changes after gastric banding surgery for morbid obesity. A prospective study. J Psychosom Res. 1989;33:323–34. [DOI] [PubMed] [Google Scholar]
  • 20.Law S, Dong S, Zhou F, Zheng D, Wang C, Dong Z. Bariatric surgery and mental health outcomes: an umbrella review. Front Endocrinol. 2023;14:1283621. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 21.MacKillop J, et al. The latent structure of impulsivity: impulsive choice, impulsive action, and impulsive personality traits. Psychopharmacology. 2016;233(18):3361–70. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 22.Makarenko I, Mahroug A, Jutras-Aswad D, Larney S, Martel-Laferrière V, Bruneau J. Measurement of impulsivity and its role in drug use behaviours and related health, harm and treatment outcomes among people who use illicit drugs—a scoping review. Int J Mental Health Addict. 2025. 10.1007/s11469-025-01537-8. Advance online publication. [DOI] [PMC free article] [PubMed]
  • 23.Michaud A, Vainik U, Garcia-Garcia I, Dagher A. Overlapping neural endophenotypes in addiction and obesity. Front Endocrinol. 2017;8:127. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 24.Murphy CM, Stojek MK, MacKillop J. Interrelationships among impulsive personality traits, food addiction, and body mass index. Appetite. 2014;73:45–50. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 25.Murton LM, Plank LD, Cutfield R, Kim D, Booth MWC, Murphy R, Serlachius A. Bariatric surgery and psychological health: A randomised clinical trial in patients with obesity and type 2 diabetes. Obes Surg. 2023;33(5):1536–44. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 26.Nederkoorn C, Jansen E, Mulkens S, Jansen A. Impulsivity predicts treatment outcome in obese children. Behav Res Ther. 2007;45(5):1071–5. [DOI] [PubMed] [Google Scholar]
  • 27.Patton JH, Stanford MS, Barratt ES. Factor structure of the Barratt impulsiveness scale. J Clin Psychol. 1995;51:768–74. [DOI] [PubMed] [Google Scholar]
  • 28.Robinson E, Roberts C, Vainik U, Jones A. The psychology of obesity: an umbrella review and evidence-based map of the psychological correlates of heavier body weight. Neurosci Biobehavioral Reviews. 2020;119:468–80. [DOI] [PubMed] [Google Scholar]
  • 29.Sarwer DB, Allison KC, Wadden TA, Ashare R, Spitzer JC, McCuen-Wurst C, Wu J. Psychopathology, disordered eating, and impulsivity as predictors of outcomes of bariatric surgery. Surg Obes Relat Dis. 2019;15(4):650–5. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 30.Sarwer DB, Wadden TA, Ashare RL, Spitzer JC, McCuen-Wurst C, LaGrotte C, Williams NN, Edwards M, Tewksbury C, Wu J, Tajeu G, Allison KC. Psychopathology, disordered eating, and impulsivity in patients seeking bariatric surgery. Surg Obes Relat Diseases: Official J Am Soc Bariatr Surg. 2021;17(3):516–24. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 31.Sarwer DB, Wadden TA, Ashare R, Spitzer JC, McCuen-Wurst C, LaGrotte C, Williams N, Soans R, Tewksbury C, Wu J, Tajeu G, Allison KC. Psychopathology, disordered eating, and impulsivity as predictors of weight loss 24 months after metabolic and bariatric surgery. Surg Obes Relat Diseases: Official J Am Soc Bariatr Surg. 2024;20(7):634–42. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 32.Sarwer DB, Allison KC, Bailer BA, Faulconbridge LF. Psychosocial characteristics of bariatric surgery candidates. In: Still C, Sarwer D, Blankenship J, editors. The ASMBS textbook of bariatric surgery. New York, NY: Springer; 2014. [Google Scholar]
  • 33.Sarwer DB, Wadden TA, Fabricatore AN. Psychosocial and behavioral aspects of bariatric surgery. Obes Res. 2005;13:639–48. [DOI] [PubMed] [Google Scholar]
  • 34.Schag MI, Giel KE, Ölschläger S, von Skoda E-M, Zipfel FM, Teufel S, M. The impact of impulsivity on weight loss four years after bariatric surgery. Nutrients. 2016;8(11):721. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 35.Smith DG, Robbins TW. The Neurobiological underpinnings of obesity and binge eating: a rationale for adopting the food addiction model. Biol Psychiatry. 2013;73(9):804–10. [DOI] [PubMed] [Google Scholar]
  • 36.Testa G, Granero R, Siragusa C, Belligoli A, Sanna M, Rusconi ML, Angeli P, Vettor R, Foletto M, Busetto L, Fernández-Aranda F, Schiff S. Psychological predictors of poor weight loss following LSG: relevance of general psychopathology and impulsivity. Eat Weight Disorders: EWD. 2020;25(6):1621–9. [DOI] [PubMed] [Google Scholar]
  • 37.Yeo D, Toh A, Yeo C, Low G, Yeo JZ, Aung MO, Rao J, Kaushal S. The impact of impulsivity on weight loss after bariatric surgery: a systematic review. Eat Weight Disorders: EWD. 2021;26(2):425–38. [DOI] [PubMed] [Google Scholar]
  • 38.Yeo D, Yeo C, Low TY, Ahmed S, Phua S, Oo AM, Rao J, Koura A, Venkataraman K, Kaushal S. Outcomes after metabolic surgery in Asians-a Meta-analysis. Obes Surg. 2019;29(1):114–26. [DOI] [PubMed] [Google Scholar]
  • 39.Yin CY, Zhang HL, Liu L, et al. Immediate improvement in anxiety and sleep quality with delayed depression response after bariatric surgery in a longitudinal cohort study. Sci Rep. 2025;15:32973. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 40.Zhan X, Zheng X, Wang J, Yang N, Cai J, Ren M, Xie M. Psychosocial intervention for improving health in patients with bariatric surgery: a Meta-analysis[J]. Chin J Nurs. 2023;58(23):2920–7. [Google Scholar]

Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Data Availability Statement

The data that support the findings of this study are openly available in osf.io/hkjbe.


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