The Use of Growth Mixture Modeling for Studying Resilience to Major Life Stressors in Adulthood and Old Age: Lessons for Class Size and Identification and Model Selection

Infurna, Frank J.; Grimm, Kevin J.

doi:10.1093/geronb/gbx019

Cited by 53 publications

(69 citation statements)

References 39 publications

(56 reference statements)

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“…More specifically, Diallo and colleagues (2016) found that assuming homogeneity of variance led to over-extraction of classes; data were simulated for one-class underlying the sample, and by applying the aforementioned assumption of homogeneity of variance lead to 4 classes being found in the data. Using empirical data, Infurna and Grimm (in press) further demonstrated the importance of the homogeneity of variance of assumption by showing that relaxing this assumption led to improved model fit and better identification of sub-groups in the data. In sum, results of this study confirm the critical need for researchers to allow for such variability; the failure to allow for these in assumptions applied at the outset can lead to misleading findings about the nature and sizes of resilient trajectories (Infurna & Grimm, in press; Infurna & Luthar, 2016; in press).…”

Section: Discussionmentioning

confidence: 99%

“…For example, what is the importance of categorizing participants into the commonly found classes (e.g., resilient, recovery, growth, and chronic low) based on their trajectories over time (for discussion, see Infurna & Grimm, in press)? As shown in Figure 2, the distinctiveness between classes is mostly due to differences in levels in the outcome rather than on the trajectory.…”

Section: Discussionmentioning

confidence: 99%

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Parents’ adjustment following the death of their child: Resilience is multidimensional and differs across outcomes examined

Infurna

Luthar

2017

Journal of Research in Personality

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We examine whether the previously reported commonness of resilience to significant adversity extends to parents’ death of a child. To examine our research questions, we apply growth mixture models to longitudinal data from 461 parents in the HILDA study who had experienced child loss. The proportion of parents manifesting resilience were 44%, 56%, 21%, 32%, and 16% for life satisfaction, negative affect, positive affect, general health, and physical functioning, respectively. Only 5% were resilient across all five indices, whereas 28% did not show a resilient trajectory across all outcomes. Social connectedness, anticipating comfort when distressed, and everyday role functioning were the strongest predictors of resilient adaptation. Findings underscore that resilience is not a unidimensional construct.

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Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Parents’ adjustment following the death of their child: Resilience is multidimensional and differs across outcomes examined

Infurna

Luthar

2017

Journal of Research in Personality

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“…The rationale for this decision is often rooted in a desire to reduce the complexity of the estimation rather than for substantive reasons (Bauer & Curran, 2003;Enders & Tofighi, 2008;Gilthorope et al, 2014;Harring & Hodis, 2016, Infurna & Grimm, 2017Infurna & Luthar, 2016;van de Schoot, Sijbrandij, Winter, Depaoli, & Vermunt, 2017).…”

Section: Within-class Variationmentioning

confidence: 99%

“…Though commonly implemented in empirical settings (Infurna & Grimm, 2017), the approach of constraining variance terms across classes has been widely criticized in the methodological literature. The main reason being that the rationale behind this modeling decision is to aid estimation rather than because theory posits that each latent class actually has equal variance(s).…”

Section: Within-class Variationmentioning

confidence: 99%

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Covariance pattern mixture models: Eliminating random effects to improve convergence and performance

McNeish

Harring

2019

Behav Res

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Growth mixture models (GMMs) are prevalent for modeling unknown population heterogeneity via distinct latent classes. However, GMMs are riddled with convergence issues, often requiring researchers to atheoretically alter the model with cross-class constraints to obtain convergence. We discuss how within-class random effects in GMMs exacerbate convergence issues even though these random effects rarely help to answer typical research questions. That is, latent classes provide a discretization of continuous random effects, so including additional random effects within latent classes can unnecessarily complicate the model. These random effects are commonly included to properly specify the marginal covariance; however, random effects are inefficient for patterning a covariance matrix, resulting in estimation issues. Such a goal can be achieved more simply covariance pattern models, which we extend to the mixture model context in this paper (covariance pattern mixture models, CPMMs). We provide evidence from theory, simulation, and an empirical example showing that employing CPMMs (even if misspecified) instead of GMMs can circumvent computational difficulties that can plague GMMs without sacrificing the ability to answer the type of questions commonly asked in empirical studies. Results show advantages of CPMMs with respect to improved class enumeration, and less biased class-specific growth trajectories in addition to vastly improved convergence rates. Results also show that constraining covariance parameters across classes to bypass convergence issues with GMMs leads to poor results. An extensive software appendix is included to assist researchers run CPMMs in Mplus.

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Comorbid Prolonged Grief, PTSD, and Depression Trajectories for Bereaved Family Surrogates

Wen,

Prigerson,

Chou

et al. 2023

JAMA Netw Open

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ImportanceFamily surrogates of patients who die in an intensive care unit (ICU) are at risk of cooccurring prolonged grief disorder (PGD), posttraumatic stress disorder (PTSD), and depressive disorder during bereavement, but symptom trajectories are often explored individually.ObjectivesTo simultaneously examine and determine co-occurrence of PGD, PTSD, and depressive symptom trajectories.Design, Setting, and ParticipantsThis cohort study was conducted in ICUs of 2 Taiwanese medical centers from January 2018 to March 2020, with follow-up through July 2022. Participants included surrogates responsible for decision-making who provided data 6 to 24 months after the death of their loved one. Data were analyzed from August to December 2022.Main Outcomes and MeasuresPGD was assessed with the 11 grief symptom items of the PG-13; PTSD, the Impact of Event Scale–Revised; and depressive symptoms, the depression subscale of the Hospital Anxiety and Depression Scale at 6, 13, 18, and 24 months after the death. Latent growth mixture modeling was conducted to identify distinct trajectories, and joint latent class analysis was used to assess joint patterns of trajectories.ResultsA total of 303 participants were included, with most younger than 56 years (207 participants [68.3%]), female (177 participants [58.4%]), and married (228 participants [75.2%]), and their relationship with the patient was mostly spouse (88 participants [29.0%]) or adult child (166 participants [54.8%]). Three trajectories were identified each for PGD, PTSD, and depressive symptoms. A resilience trajectory was predominant across PGD (253 participants [83.5%]), PTSD (250 participants [82.5%]), and depressive (200 participants [66.0%]) symptoms. Second most common was a recovery trajectory identified for PGD (36 participants [11.9%]) and PTSD (41 participants [13.5%]) symptoms, while for depressive symptoms, a moderate trajectory (72 participants [23.8%]) signified persistent moderate distress. A chronic trajectory characterized by persistently high distress was identified for PGD (14 participants [4.6%]) and depressive (31 participants [10.2%]) symptoms, whereas a unique delayed-onset trajectory (12 participants [4.0%]) was identified for PTSD symptoms. Most family surrogates (228 participants [75.2%]) experienced cooccurring PGD, PTSD, and depressive symptom trajectories, but multiple patterns were discordant. Symptom trajectories cooccurred in joint patterns: resilient (247 participants [81.5%]), recovered (43 participants [14.1%]), and distressed (14 participants [4.5%]). These patterns were characterized by high conditional probabilities for the resilience (PGD, 0.999; PTSD, 0.999; depressive, 0.804), recovery (PGD, 0.854; PTSD, 0.890; depressive, 0.588), and chronic (PGD, 0.921; PTSD, 0.789; depressive, 0.980) symptom trajectories.Conclusions and RelevanceIn this cohort study, grief-related psychological symptoms evolved in complex ways during ICU bereavement, as characterized by heterogeneous trajectories. Some ICU bereaved surrogates experienced persistent elevated PGD, PTSD, and depressive symptoms individually or conjointly, underscoring the importance of early screening to identify this population at high risk of comorbid psychological distress trajectories.

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The Use of Growth Mixture Modeling for Studying Resilience to Major Life Stressors in Adulthood and Old Age: Lessons for Class Size and Identification and Model Selection

Cited by 53 publications

References 39 publications

Parents’ adjustment following the death of their child: Resilience is multidimensional and differs across outcomes examined

Parents’ adjustment following the death of their child: Resilience is multidimensional and differs across outcomes examined

Covariance pattern mixture models: Eliminating random effects to improve convergence and performance

Comorbid Prolonged Grief, PTSD, and Depression Trajectories for Bereaved Family Surrogates

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