Predictors Of Trajectories Research Articles

Development of Self-Reported Reward Responsiveness and Inhibitory Control and the Role of Clinical and Neural Predictors.

Understanding the development of adolescent reward responsiveness and inhibitory control is important as they are implicated in key outcomes, such as depression. However, relatively few studies have examined the self-reported experience of this development longitudinally, and past findings have been mixed. Here, we examined the longitudinal development of self-reported reward responsiveness and inhibitory control in youth, as well as clinical and neural measures as predictors of these longitudinal trajectories. We assessed 223 youth aged 9-17 across 36 months. We modeled growth trajectories of several measures of reward responsiveness and inhibitory control using multilevel models. We tested reward-related functional connectivity, depression symptoms, and parental risk for psychopathology as moderators of longitudinal growth. Self-reported inhibitory control increased linearly across adolescence. However, contrary to hypotheses and common models of adolescent development, self-reported reward responsiveness decreased linearly across adolescence. Baseline functional connectivity and clinical risk measures did not significantly moderate trajectories. Results suggest that within-person changes in the phenomenological experience of reward responsiveness may not match developmental expectations based on cross-sectional and neuroimaging studies. More attention is needed to the longitudinal study of subjective experience of reward responsiveness.

The Development of Intellect in Emerging Adults: Predictors of Longitudinal Trajectories

Intellect is an important personality trait, especially with regard to the prediction and explanation of intellectual performance, such as occupational or academic success. However, much less is known about the development of Intellect. I present results from a longitudinal study spanning eight years to investigate changes in Intellect during a critical period: the transition from school to vocation. The study is based on a large and heterogeneous sample with up to 1964 participants. Using a facet approach, I investigate predictors of longitudinal trajectories theoretically derived from construct definition, including subjective and objective attributes of education and profession; attitudes regarding the malleability of personality traits; as well as personality traits beyond Intellect, especially intelligence. Results reveal some support for the social investment principle according to neo-socioanalytic theory, as epistemic job demands and epistemic leisure activities predicted the increase in Intellect over time. The study contributes to our understanding of the development of personality traits related to intellectual achievement, including important internal and external predictors of longitudinal trajectories.

Prospective associations between stressors and alcohol use from early adolescence to young adulthood in Mexican-origin youth in the United States.

Stressors experienced across multiple domains (e.g., family and peers) may contribute to alcohol use trajectories; however, little is known about the longitudinal links between stressors and alcohol use among Latinx youth. Guided by prior work on stressors and alcohol use, the present study used longitudinal data to examine whether Mexican-origin adolescents' (N = 674; 50% female; 28% Mexico born; 72% U.S. born) experiences of family and peer stressors across early to middle adolescence (Mage = 10.86, SDage = 0.51) predicted trajectories of alcohol use frequency and binge drinking from middle adolescence to young adulthood (Mage = 23.17, SDage = 0.59). Using two strategies for modeling stressors, we report results that showed more support for stressors across early adolescence as predictors of alcohol use trajectories when stressors were modeled as growth trajectories versus modeled as distal and proximal stressors. Findings underscore the need to consider strategies to attenuate the longitudinal links between stressors and alcohol use among Mexican-origin youth. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Exploring variations in subjective well-being among Norwegian retirees: A growth mixture modelling approach.

This study aimed to identify subgroups of Norwegian retirees with similar trajectories of subjective well-being (SWB) across the retirement transition and to explore how various factors influence these SWB trajectories. The study employed growth mixture modelling to analyze longitudinal data, exploring the trajectories of life satisfaction, positive affect and negative affect in retirement transition. It also examined the influence of factors such as demographic, living arrangement, pre-retirement work conditions, individual characteristics and available resources on these SWB trajectories. Contrary to the hypothesised three distinct SWB trajectories in retirement, the results more strongly support a single group solution for life satisfaction and positive affect. For negative affect, a two-group solution, consisting of one group with stable low and another with stable high negative affect, was preferred. The study identified several predictors of SWB trajectories. The findings suggest that retirement is a neutral life event with stable SWB trajectories. However, several factors significantly influence whether retirees experience higher or lower SWB in retirement. The findings of this study provide updated insights into the heterogeneity of the retirement experience, as well as highlight important factors for retirement SWB.

Trajectories of cold but not mechanical sensitivity correspond with disability trajectories after whiplash injury.

Developmental trajectories for neck disability after whiplash injury have been identified. Their relationship to cold and mechanical sensitivity trajectories is not known. We aimed to (1) identify recovery trajectories of cold and mechanical sensitivity, (2) explore their codevelopment with disability trajectories, (3) identify predictors of sensitivity trajectories, and (4) explore codevelopment of cold and mechanical sensitivity trajectories. Participants (n = 233) were assessed at <1, 3, 6, and 12 months after whiplash injury. Outcomes were cold pain detection threshold (CPT at neck), pressure pain detection thresholds (PPT, neck C5, and tibialis anterior), and the Neck Disability Index. We used group-based trajectory models to identify postinjury recovery trajectories and multinominal logistic regression to explore associations between baseline characteristics and trajectory membership. We identified the following trajectory groups: CPT (low [50.0%], moderate [29.7%], and high [20.4%] sensitivity); PPT C5 (low [10.8%] and high [89.2%] sensitivity); and PPT tibialis anterior (low [23.9%], moderate [39.0%], and high [37.1%] sensitivity); all were stable over the 12 months. There was good correspondence between disability and cold sensitivity trajectory groups but not for mechanical sensitivity; cold and mechanical sensitivity trajectories were not well associated. Higher baseline pain predicted membership of the high cold sensitivity trajectory (RR 1.27, 95% CI 1.01-1.59) and hyperarousal symptoms predicted membership of the moderate cold sensitivity trajectory (RR 1.17, 95% CI 1.01-1.36). We found no associations between baseline characteristics and mechanical sensitivity. There is an interplay between cold allodynia, pain, and hyperarousal symptoms in development of ongoing disability after whiplash injury. Different mechanisms likely underlie cold and mechanical sensitivity.

Using machine learning methods to identify trajectories of change and predict responders and non-responders to short-term dynamic therapy

Objectives Predicting therapy responders can significantly improve clinical outcomes. This study aims to identify predictors of response to short-term dynamic therapy. Methods Data from 95 patients who underwent 16-session therapy were analyzed using machine learning. Weekly progress was monitored with the Outcome Questionnaire (OQ45) and Target Complaints (TC). A machine learning model identified change trajectories for responders and non-responders, with a random forest algorithm and elastic net modeling predicting trajectory group membership using pre-treatment data. Results A weak positive relationship was found between the trajectories of the two outcome variables. The results of the different analysis methods were compared and discussed. Important predictors of OQ45 trajectories, based on random forest modeling, included initial symptom severity, difficulties in emotion regulation, coldness, avoidant attachment, conscientiousness, interpersonal problems, non-acceptance of negative emotion, neuroticism, emotional clarity, impulsivity, and emotion awareness (72.8% accuracy). Initial problem severity, self-scarifying extraversion, and non-assertiveness were the most dominant predictors for TC trajectories (62.8% accuracy). Conclusions These findings offer data-driven insights for selecting short-term dynamic therapy. Predicting response for the OQ45, a nomothetic measure, does not extend to the TC, an idiographic measure, and vice versa, highlighting the importance of multidimensional outcome evaluations for personalized treatment.

Trajectories and predictors of depressive symptoms among pregnant women: A 3-year longitudinal study.

Not all women experience the same changes in depression from pregnancy through the years following childbirth, but the patterns of prenatal and postnatal depression are underexplored. This study investigated the trajectories and associated predictors of depressive symptoms in women from pregnancy through the first 3 years postpartum. We followed 340 pregnant women from an antenatal clinic in Hong Kong, first at 20-24 weeks of gestation, then at 4 weeks after childbirth, and again at 3 years after childbirth. Pregnant women reported their depressive symptoms whether they had intimate partner violence, health conditions, adverse childhood experiences, family support, and perceived partner involvement. Latent class growth analysis was applied to identify distinct trajectories of depression, and binary logistic regressions were performed to analyze predictors of trajectories. We found that 26.5% of women showed clinical depressive symptoms at 20-24 weeks of gestation, 9.7% at 4 weeks after childbirth, and 12.6% at 3 years after childbirth. Two classes were identified: a low-stable group (86.2%) and a relapsing/remitting group (13.8%). Women with a history of trauma (i.e., intimate partner violence and adverse childhood experiences) and mental health difficulties were more likely to be classified in the relapsing/remitting group than in the low-stable group. Family support and partner emotional involvement appeared to protect the women from suffering relapsing/remitting depression. The findings highlight the importance of screening for depression throughout pregnancy and extending several years postpartum. Distinguishing the different trajectories of depression and identifying its associated factors are critical to providing targeted interventions to the most vulnerable women (i.e., a relapsing/remitting group in the present study). (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Symmetry Preservation in Hamiltonian Systems: Simulation and Learning

This work presents a general geometric framework for simulating and learning the dynamics of Hamiltonian systems that are invariant under a Lie group of transformations. This means that a group of symmetries is known to act on the system respecting its dynamics and, as a consequence, Noether’s theorem, conserved quantities are observed. We propose to simulate and learn the mappings of interest through the construction of G-invariant Lagrangian submanifolds, which are pivotal objects in symplectic geometry. A notable property of our constructions is that the simulated/learned dynamics also preserves the same conserved quantities as the original system, resulting in a more faithful surrogate of the original dynamics than non-symmetry aware methods, and in a more accurate predictor of non-observed trajectories. Furthermore, our setting is able to simulate/learn not only Hamiltonian flows, but any Lie group-equivariant symplectic transformation. Our designs leverage pivotal techniques and concepts in symplectic geometry and geometric mechanics: reduction theory, Noether’s theorem, Lagrangian submanifolds, momentum mappings, and coisotropic reduction among others. We also present methods to learn Poisson transformations while preserving the underlying geometry and how to endow non-geometric integrators with geometric properties. Thus, this work presents a novel attempt to harness the power of symplectic and Poisson geometry toward simulating and learning problems.

Trajectories of self-reported fatigue following initiation of multiple sclerosis disease-modifying therapy

BackgroundWe analysed the COMparison Between All immunoTherapies for Multiple Sclerosis (NCT03193866), a Swedish nationwide observational study in relapsing–remitting multiple sclerosis (RRMS), to identify trajectories of fatigue and their association with...

Predictors of treatment response trajectories to cognitive behavioral therapy for chronic fatigue syndrome: A cohort study

BackgroundThe response to cognitive behavioral therapy (CBT) for chronic fatigue syndrome (CFS) varies greatly between patients, but predictors of treatment success remain to be elucidated. We aimed to identify patient subgroups based on fatigue trajectory during CBT, identify pre-treatment predictors of subgroup membership, and disentangle the direction of predictor – outcome relationships over time. Methods297 individuals with CFS were enrolled in a standardized CBT program consisting of 17 sessions, with session timing variable between participants. Self-reported levels of fatigue, depressive, anxiety, and somatic symptoms, perceived stress, and positive affect were collected pre-treatment, and after 3, 10, and 15 sessions. Latent Class Growth Analysis (LCGA) was used to identify subgroups based on fatigue trajectories and baseline predictors of group membership. Cross-lagged structural equation models were used to disentangle predictor-outcome relationships. ResultsLCGA identified four fatigue trajectory subgroups, which were labelled as “no improvement” (23 %), “weak improvement” (45 %), “moderate improvement” (23 %), and “strong improvement” (9 %) classes. Higher pre-treatment levels of depressive, anxiety, and somatic symptoms, stress, and lower levels of positive affect predicted membership of the “no improvement” subgroup. Reductions in anxiety preceded reductions in fatigue, while the depressive symptoms – fatigue relationship was bidirectional. ConclusionsOn a group level, there were statistically significant reductions in fatigue after 15 sessions of CBT, with important individual differences in treatment response. Higher pre-treatment levels of anxious, depressive, and somatic symptoms and perceived stress are predictors of lack of response, with reductions in anxiety and stress preceding improvements in fatigue.

Predictors of Anxiety Trajectories in Cohort of First-Year College Students

Predictors of Anxiety Trajectories in Cohort of First-Year College Students

How Well Can We Measure Chronic Pain Impact in Existing Longitudinal Cohort Studies? Lessons Learned

Multiple large longitudinal cohorts provide opportunities to address questions about predictors of pain and pain trajectories, even when not anticipated in the design of the historical databases. This focus article uses 2 empirical examples to illustrate the processes of assessing the measurement properties of data from large cohort studies to answer questions about pain. In both examples, data were screened to select candidate variables that captured the impact of chronic pain on self-care activities, productivity, and social activities. We describe a series of steps to select candidate items and evaluate their psychometric characteristics in relation to the measurement of pain impact proposed. In the UK Biobank, a general lack of internal consistency of variables selected prevented the identification of a satisfactory measurement model, with lessons for the measurement of chronic pain impact. In the English Longitudinal Study of Ageing, a measurement model for chronic pain impact was identified, albeit limited to capturing the impact of pain on self-care and productivity but lacking coverage related to social participation. In conjunction with its Supplementary Material, this focus article aims to encourage exploration of these valuable prospectively collected data to support researchers to make explicit the relationships between items in the databases and constructs of interest in pain research and to use empirical methods to estimate the possible biases in these variables. PerspectiveThis focus article outlines a theory-driven approach for fitting new measurement models to data from large cohort studies and evaluating their psychometric properties. This aims to help researchers develop an empirical understanding of the gains and limitations connected with the process of repurposing the data stored in these datasets.

Identifying latent subtypes of symptom trajectories in major depressive disorder patients and their predictors.

This study aimed to identify different symptom trajectories based on the severity of depression symptoms within a 2-month follow-up, and to explore predictive factors for different symptom trajectories. Three hundred and ninety-two adults diagnosed with major depressive disorder (MDD) were recruited from two longitudinal cohorts. Patients received antidepressant treatment as usual, and the depression symptoms were evaluated by the 17-item Hamilton depression rating scale (HAMD-17) at baseline, two weeks, and eight weeks. Based on the HAMD-17 scores, different trajectories of symptom change were distinguished by applying Growth Mixture Modeling (GMM). Furthermore, the baseline sociodemographic, clinical, and cognitive characteristics were compared to identify potential predictors for different trajectories. Through GMM, three unique depressive symptom trajectories of MDD patients were identified: (1) mild-severity class with significant improvement (Mild, n = 255); (2) high-severity class with significant improvement (High, n = 39); (3) moderate-severity class with limited improvement (Limited, n = 98). Among the three trajectories, the Mild class had a relatively low level of anxiety symptoms at baseline, whereas the High class had the lowest education level and the worst cognitive performance. Additionally, participants inthe Limited class exhibited an early age of onset and experienced a higher level of emotional abuse.MDD patients could be categorised into three distinct latent subtypes through different symptom trajectories in this study, and the characteristics of these subtype patients may inform identifications for trajectory-specific intervention targets.

Real-world experience with long-term albumin in patients with cirrhosis and ascites

Background and AimsLong-term albumin (LTA) is currently standard of care for patients with decompensated cirrhosis in many Italian hepatological centres. This real-life study aimed to describe patient, logistical and treatment-related characteristics in daily clinical practice and to identify predictors of response. MethodsMulticentre, retrospective, observational study in patients with cirrhosis and ascites receiving LTA between 01/2016 and 02/2022 and followed until death, TIPS, transplantation or 02/2023. Results312 patients, the majority with alcohol-related cirrhosis, were included. At baseline, median Child-Pugh was 8, MELD 15, and MELD-Na 18. Ascites was grade 2 in 55% of patients, grade 3 in 35% and refractory in 27%, while 47% had paracentesis in the previous 6 months. Median LTA was 10 months with a median dose of 40 g/week.Ascites resolved to grade 0-1 in 34% of patients within the first 3 months and 56% at the end of treatment. Predictors of ascites resolution were age (p=0.007), baseline grade of ascites (p=0.007), no paracentesis in the previous 6 months (p=0.001), etiological treatment in the past 12 months or during LTA (p=0.005), weekly albumin dose (p=0.014) and serum albumin concentration of 40 g/L after one month of treatment (p=0.017). Of the 83 patients with refractory ascites at inclusion, 26% had grade 0/1 ascites at the last observation. No severe albumin-related side-effects were reported and only 1% discontinued due to logistic reasons. ConclusionsLTA is feasible as an outpatient treatment for the management of ascites. In the current study, more than half of patients receiving LTA on top of diuretics resolved their ascites, including some with refractory ascites. Predictors of response to LTA provide useful information for tailoring treatment. IMPACT AND IMPLICATIONSThe ANSWER randomized clinical trial has shown that long-term albumin treatment (LTA) is an effective approach for the management of patients with cirrhosis and ascites. This observational study provides novel information on target patients, modalities and length of treatment, predictors of ascites resolution, stopping criteria, and clinical trajectories of patients on treatment.LTA is a feasible option in the daily clinical practice for the management of ascites when given on top of diuretics. Rather than an alternative therapy, LTA should be integrated with the other treatments options already available for patients with difficult-to-treat ascites. The predictive factors of response identified in the present study can help physicians to individualize LTA and optimize the decision-making process.

Early childhood executive control modulates negative affectivity's role in increasing adolescent body mass index trajectories.

Executive control and temperament have been associated with pediatric obesity. However, interactions between these constructs in relation to future weight outcomes have not been investigated. This longitudinal study examined early childhood executive control, early temperament (negative affectivity and surgency), and their interactions as predictors of adolescent BMI trajectories. At age 5.25, children (N = 229) completed executive control tasks, and parents completed the Child Behavior Questionnaire to assess temperament. BMI was calculated annually between ages 14-17. Greater early negative affectivity predicted more positive BMI growth. Although early childhood executive control was not associated with BMI growth, greater negative affectivity predicted greater BMI escalation at average and below average executive control abilities. For children without robust executive control abilities early in development, negative affectivity may be a risk factor for accelerated adolescent BMI growth. Targeted assessment of early risk factors may be useful for childhood obesity prevention efforts.

Developmental trajectories of professional preparedness among senior nursing students during clinical placement: A longitudinal study

BackgroundNewly graduated nurses' lack of professional competence is associated with inadequate preparation during their clinical placement as nursing students. Clinical placement is a critical stage in the development of nursing students' professional preparedness. However, research on the trajectory of nursing students' professional preparedness during clinical placement has not yielded findings with the same specificity. ObjectivesThe aim of this study is to estimate differences in professional preparedness levels at different clinical placement stages, to identify distinct patterns of professional preparedness trajectories during clinical placement, and to evaluate predictors of these trajectory group memberships. DesignA quantitative longitudinal study. SettingsParticipants were recruited on a voluntary basis using convenience sampling at a tertiary hospital in Nanning, China. Participants224 senior nursing students were initially invited to participate in the study. A total of 178 nursing students successfully completed the follow-up assessments at baseline, as well as at 1 month, 4 months, and 8 months into their clinical placement. MethodsParticipants completed four online surveys, during which their professional preparedness level was measured using the Perceived Professional Preparedness questionnaire for senior nursing students. Professional preparedness scores at different time points were compared using one-way repeated measures ANOVA and latent growth model. Group-based trajectory model was applied to identify professional preparedness trajectories. Multiple logistic regression was adopted to determine the predictors of trajectory group memberships. ResultsThe entire sample of Senior nursing students experienced a significant increase in professional preparedness during clinical placement. The best-fitting group-based trajectory model delineated three distinct trajectories: low-slowly increase trajectory (27.53 % of sample), moderate-rapidly increase trajectory (47.19 % of sample) and a high-stably increase trajectory (25.28 % of sample). Male, good and excellent academic performance, and very high degree of professional interest are the predictors of the moderate-rapidly increase trajectory. While male, good and excellent academic performance, high and very high degree of professional interest and participating in medical-related part-time employment are the predictors of the high-stable increase trajectory. ConclusionsSenior nursing students exhibit different levels of professional preparedness throughout their clinical placement. Simultaneously, three different trajectories were identified among the sample of nursing students. Therefore, in future research, greater attention should be directed towards the professional preparedness levels of nursing students with different trajectories, and early identification and targeted interventions should be prioritized.

Using machine learning to explore the predictors of life satisfaction trajectories in older adults.

Life satisfaction is vital for older adults' well-being, impacting various life aspects. It is dynamic, necessitating nuanced approaches to capture its trajectories accurately. This study aimed to explore the diverse trajectories and predictors of life satisfaction among older adults in China using longitudinal data from the China Health and Retirement Longitudinal Study. Latent class growth modeling and growth mixture modeling were employed to identify distinct trajectories of life satisfaction. Machine learning (ML) models were developed to predict different trajectories and identify important predictors of different trajectories. Four distinct trajectories of life satisfaction were identified, showcasing nuanced patterns of life satisfaction that changed over time. ML models, especially random forest, effectively predicted these trajectories. Emotional experiences (particularly the frequency of happiness and loneliness), body mass index, and self-report health emerged as significant predictors of different life satisfaction trajectories. Our finding revealed the importance of focusing on individuals or groups with consistently low life satisfaction and paying more attention to mental and physical health predictors. Our models might guide future targeted preventative treatments.

Predicting the trajectory of non-suicidal self-injury among adolescents.

Non-suicidal self-injury (NSSI) is common among adolescents receiving inpatient psychiatric treatment and the months post-discharge is a high-risk period for self-injurious behavior. Thus, identifying predictors that shape the course of post-discharge NSSI may provide insights into ways to improve clinical outcomes. Accordingly, we used machine learning to identify the strongest predictors of NSSI trajectories drawn from a comprehensive clinical assessment. The study included adolescents (N = 612; females n = 435; 71.1%) aged 13-19-years-old (M = 15.6, SD = 1.4) undergoing inpatient treatment. Youth were administered clinical interviews and symptom questionnaires at intake (baseline) and before termination. NSSI frequency was assessed at 1-, 3-, and 6-month follow-ups. Latent class growth analyses were used to group adolescents based on their pattern of NSSI across follow-ups. Three classes were identified: Low Stable (n = 83), Moderate Fluctuating (n = 260), and High Persistent (n = 269). Important predictors of the High Persistent class in our regularized regression models (LASSO) included baseline psychiatric symptoms and comorbidity, past-week suicidal ideation (SI) severity, lifetime average and worst-point SI intensity, and NSSI in the past 30 days (bs = 0.75-2.33). Only worst-point lifetime suicide ideation intensity was identified as a predictor of the Low Stable class (b = -8.82); no predictors of the Moderate Fluctuating class emerged. This study found a set of intake clinical variables that indicate which adolescents may experience persistent NSSI post-discharge. Accordingly, this may help identify youth that may benefit from additional monitoring and support post-hospitalization.

Analysis of Longitudinal Patterns and Predictors of Medicine Use in Residential Aged Care Using Group-Based Trajectory Modeling: The "MEDTRAC-Cardiovascular" Longitudinal Cohort Study.

Cardiovascular diseases are the leading cause of death globally. Ensuring ongoing use of medicines-medication persistence-is crucial, yet no prior studies have examined this in residential aged care facilities (RACFs). We aimed to identify long-term trajectories of persistence with cardiovascular medicines and determine predictors of persistence trajectories. A longitudinal cohort study of 2837 newly admitted permanent residents from 30 RACFs in New South Wales, Australia. We monitored weekly exposure to six cardiovascular medicine classes-lipid modifiers, angiotensin-converting enzyme inhibitors/angiotensin receptor blockers (ACEI/ARBs), beta-blockers, diuretics, calcium channel blockers (CCB), and cardiac therapy-over 3 years. Group-based trajectory modeling was employed to determine persistence trajectories for each class. At baseline, 76.6% (n = 2172) received at least one cardiovascular medicine with 41.2% receiving lipid modifiers, 31.4% ACEI/ARBs, 30.2% beta-blockers, 24.4% diuretics, 18.7% CCBs, and 14.8% cardiac therapy. The model identified two persistence trajectories for CCBs and three trajectories for all other classes. Sustained high persistence rates ranged from 68.4% (ACEI/ARBs) to 79.8% (beta-blockers) while early decline in persistence and subsequent discontinuation rates ranged from 7.6% (cardiac therapy) to 25.3% (CCBs). Logistic regressions identified 11 predictors of a declining persistence across the six medicine classes. Our study revealed varied patterns of cardiovascular medicine use in RACFs, with 2-3 distinctive medicine use trajectories across different classes, each exhibiting a unique clinical profile, and up to a quarter of residents discontinuing a medicine class. Future studies should explore the underlying reasons and appropriateness of nonpersistence to aid in identifying areas for improvement.

Distinct Longitudinal Trajectories of Symptom Burden Predict Clinical Outcomes in End-Stage Liver Disease.

Little has been reported about the clinical relevance and trajectories of symptoms in end-stage liver disease (ESLD). The purpose of this prospective study was to identify trajectories of change in symptom burden over the course of 12 months in adults with ESLD. Patients were recruited from hepatology clinics at 2 healthcare systems. Validated measures were used to assess physical and psychological symptoms. Latent growth mixture modeling and survival and growth modeling were used to analyze the survey data. Data were available for 192 patients (mean age 56.5 ± 11.1 years, 64.1% male, mean Model for ESLD (MELD) 3.0 19.2 ± 5.1, ethyl alcohol as primary etiology 33.9%, ascites 88.5%, encephalopathy 70.8%); there were 38 deaths and 39 liver transplantations over 12 months. Two symptom trajectories were identified: 62 patients (32.3%) had high and unmitigated symptoms, and 130 (67.7%) had lower and improving symptoms. Patients with high and unmitigated symptoms had twice the hazard of all-cause mortality (subhazard ratio 2.53, 95% confidence interval: 1.32-4.83) and had worse physical ( P < 0.001) and mental quality of life ( P = 0.012) compared with patients with lower and improving symptoms. Symptom trajectories were not associated with MELD 3.0 scores ( P = 0.395). Female sex, social support, and level of religiosity were significant predictors of symptom trajectories ( P < 0.05 for all). There seems to be 2 distinct phenotypes of symptom experience in patients with ESLD that is independent of disease severity and associated with sex, social support, religiosity, and mortality. Identifying patients with high symptom burden can help optimize their care.