When pregnancy and pandemic coincide: changes in stress and anxiety over the course of pregnancy

BACKGROUND

Pregnant women experienced high levels of perceived stress and anxiety at the onset of the COVID-19 pandemic. However, the course of stress and anxiety in individual pregnant women during the pandemic is unknown.

METHODS

Participants were 1,087 women ≤20 weeks pregnant in April-May 2020 (T1) at recruitment into the Stony Brook COVID-19 Pregnancy Experiences (SB-COPE) Study, with additional assessments in July-August 2020 (T2) and October 2020 (T3). Growth mixture models conditioned on covariates were used to identify patterns of change over time in pandemic-related stress (originating from feeling unprepared for birth and fearing perinatal infection), pregnancy-specific stress, and anxiety symptoms.

RESULTS

A uniform pattern of change (i.e. one-class solution) in stress perceptions was observed over time. Participants showed the same functional form of decreases in all three types of stress perceptions over the course of their pregnancy and as the pandemic persisted. Initial level of stress did not predict change over time. Anxiety symptoms had a two-class solution in which 25% of participants had high and convex patterns of anxiety, and 75% had low levels with concave patterns.

DISCUSSION

Stress perceptions and anxiety patterns of change over the course of pregnancy during the COVID-19 pandemic were different. Therefore, to evaluate the well-being of pregnant women during a global health crisis, it is important to assess both stress perceptions and emotional stress responses (i.e. anxiety). Screening for anxiety symptoms in early pregnancy would be valuable as symptoms may not spontaneously decrease even when stressful conditions improve.

Psychotic experiences and negative symptoms from adolescence to emerging adulthood: developmental trajectories and associations with polygenic scores and childhood characteristics

BACKGROUND

Psychotic experiences and negative symptoms (PENS) are common in non-clinical populations. PENS are associated with adverse outcomes, particularly when they persist. Little is known about the trajectories of PENS dimensions in young people, nor about the precursory factors associated with these trajectories.

METHODS

We conducted growth mixture modelling of paranoia, hallucinations, and negative symptoms across ages 16, 17, and 22 in a community sample (N = 12 049-12 652). We then described the emergent trajectory classes through their associations with genome-wide polygenic scores (GPS) for psychiatric and educational phenotypes, and earlier childhood characteristics.

RESULTS

Three trajectory classes emerged for paranoia, two for hallucinations, and two for negative symptoms. Across PENS, GPS for clinical help-seeking, major depressive disorder, and attention deficit hyperactivity disorder were associated with increased odds of being in the most elevated trajectory class (OR 1.07-1.23). Lower education GPS was associated with the most elevated trajectory class for hallucinations and negative symptoms (OR 0.77-0.91). Conversely for paranoia, higher education GPS was associated with the most elevated trajectory class (OR 1.25). Trajectory class associations were not significant for schizophrenia, obsessive-compulsive disorder, bipolar disorder, or anorexia GPS. Emotional/behaviour problems and life events in childhood were associated with increased odds of being in the most elevated trajectory class across PENS.

CONCLUSIONS

Our results suggest latent heterogeneity in the development of paranoia, hallucinations, and negative symptoms in young people that is associated with specific polygenic scores and childhood characteristics.

Health trajectories of international humanitarian aid workers: growth mixture modelling findings from a prospective cohort study

BACKGROUND

Most staff stay healthy during humanitarian work, although some worsen. Mean scores on health indicators may be masking individual participants struggling with health issues.

AIMS

To investigate different field assignment-related health trajectories among international humanitarian aid workers (iHAWs) and explore the mechanisms used to stay healthy.

METHOD

Growth mixture modelling analyses for five health indicators using pre-/post-assignment and follow-up data.

RESULTS

Among 609 iHAWs three trajectories (profiles) were found for emotional exhaustion, work engagement, anxiety and depression. For post-traumatic stress disorder (PTSD) symptoms, four trajectories were identified. The 'healthy/normative' trajectory had the largest sample size for all health indicators (73-86%). A stable (moderate) 'ill health' trajectory was identified for all health indicators (7-17%), except anxiety. An 'improving' trajectory was found for PTSD and anxiety symptoms (5-14%). A minority of staff (4-15%) worsened on all health indicators. Deterioration continued for PTSD, depressive symptoms and work engagement 2 months post-assignment. A strong sense of coherence was associated with higher odds of belonging to the 'healthy' trajectory. Female biological sex was associated with higher odds of belonging to the 'worsening' depression and anxiety trajectories. Extended duration of field assignment was related to higher odds of belonging to the 'worsening' depressive symptoms trajectory.

CONCLUSIONS

Most iHAWs stayed healthy during their assignment; a stable 'ill health' trajectory was identified for most health indicators. Sense of coherence is an important mechanism for understanding the health of all iHAWs in the different health trajectories, including the 'healthy' profile. These findings give new possibilities to develop activities to prevent worsening health and help strengthen iHAWs' ability to remain healthy under stress.

Trajectories of childhood social isolation in a nationally representative cohort: Associations with antecedents and early adulthood outcomes

Background

This study examined early life antecedents of childhood social isolation, whether these factors accounted for poor outcomes of isolated children, and how these associations varied according to patterns of stability and change in childhood isolation.

Methods

Participants included 2232 children from the Environmental Risk (E-Risk) Longitudinal Twin Study. We conducted growth mixture modelling (GMM) on combined parent and teacher reports of children's social isolation when children were 5, 7, 10 and 12 years, and we assessed associations with age-5 antecedents and age-18 outcomes using regression analyses.

Results

We identified three linear developmental trajectories of increasing (4.75%), decreasing (5.25%) and low stable (90.00%) social isolation. Age-5 attention deficit hyperactivity disorder (ADHD) symptoms, emotional problems, prosocial behaviours, maternal personality (openness) and size of school were associated with the decreasing trajectory of social isolation. When controlling for these antecedents, increasingly isolated children were still more likely to experience ADHD symptoms, loneliness, lower job optimism and lower physical activity at age 18.

Conclusions

Isolated children follow distinct patterns of change over childhood and isolation seems most detrimental to health at the time it is experienced. Social isolation can be a valuable indicator of co-occurring problems and provide targets for mental health intervention in young people.

Trajectory Modelling Techniques Useful to Epidemiological Research: A Comparative Narrative Review of Approaches

Trajectory modelling techniques have been developed to determine subgroups within a given population and are increasingly used to better understand intra- and inter-individual variability in health outcome patterns over time. The objectives of this narrative review are to explore various trajectory modelling approaches useful to epidemiological research and give an overview of their applications and differences. Guidance for reporting on the results of trajectory modelling is also covered. Trajectory modelling techniques reviewed include latent class modelling approaches, ie, growth mixture modelling (GMM), group-based trajectory modelling (GBTM), latent class analysis (LCA), and latent transition analysis (LTA). A parallel is drawn to other individual-centered statistical approaches such as cluster analysis (CA) and sequence analysis (SA). Depending on the research question and type of data, a number of approaches can be used for trajectory modelling of health outcomes measured in longitudinal studies. However, the various terms to designate latent class modelling approaches (GMM, GBTM, LTA, LCA) are used inconsistently and often interchangeably in the available scientific literature. Improved consistency in the terminology and reporting guidelines have the potential to increase researchers' efficiency when it comes to choosing the most appropriate technique that best suits their research questions.

Modelling changes in anxiety and depression during low-intensity cognitive behavioural therapy: An application of growth mixture models

OBJECTIVES

Research largely supports the clinical effectiveness of low-intensity cognitive behavioural therapy (LICBT) for mild-to-moderate anxiety and depression, delivered by psychological well-being practitioners (PWPs). Knowledge regarding the predictors of treatment response, however, is relatively limited. The primary aim of this study was to model the heterogeneity in longitudinal changes in anxiety and depression throughout LICBT provided by PWPs in Northern Ireland (NI), and to explore associations between pre-treatment variables and differences in treatment response.

METHODS

Growth mixture modelling (GMM) techniques were employed to examine changes in psychological status in clients (N = 253) over the first six sessions of treatment, to identify divergent early response trajectories. A series of pre-treatment variables were used to predict class membership using chi-square tests and binary logistic regression models.

RESULTS

There was one class representing improvement and one representing no improvement for both anxiety and depression. Class membership was predictive of treatment outcome. Pre-treatment variables associated with less improvement included unemployment, risk of suicide, neglect of self or others, using medication, receiving previous or concurrent treatments, a longer duration of difficulties, and comorbidities.

CONCLUSIONS

Findings indicate most of the sample populated an 'improvers' class for both depression and anxiety. Pre-treatment variables identified as predictive of poor treatment response may need to be considered by practitioners in potential triage referral decision policies, supporting cost-effective and efficient services. Further research around predictors of clinical outcome is recommended.

PRACTITIONER POINTS

Most of the sample belonged to an 'improvers' class. Several pre-treatment variables predicted poor treatment response (unemployment, suicide risk, neglect, medication, previous or concurrent treatments, longer duration of difficulties, and comorbidities). Few studies have utilized GMM to determine predictors of outcome following LICBT Regarding pre-treatment variables, the possibility of self-report bias cannot be excluded. The time period was relatively short, although represented the optimum number of sessions recommended for LICBT. The lack of a control group and random allocation were the main limitations.

Group-based trajectory modelling for BMI trajectories in childhood: A systematic review

Childhood obesity is an important public health issue. We aimed to systematically review studies that used group-based trajectory modelling approaches to investigate body mass index (BMI) trajectories in early childhood, explore associated determinants, and the association with body composition outcomes. Five databases were searched systematically for studies using group-based trajectory modelling approaches to track BMI trajectories from birth. Fourteen studies using latent class growth analysis or growth mixture modelling to track BMI trajectories were identified. Three or four trajectories were identified in most studies. High maternal pre-pregnancy BMI was the most frequently identified risk factor for membership of a rapid gain trajectory. Significant associations between rapid weight gain and stable high trajectories and body measures at follow-up were identified by several studies. Relatively similar trajectories were identified across studies. Trajectories characterized by rapid weight gain were associated with several predictors, as well as body measures at follow-up, however not with great consistency. Similar associations with body measure outcomes were found for stable high and rapid gain trajectories, suggesting that long-term outcomes do not differ greatly between children with consistently high BMI and children with rapid increases in BMI. As the shape and timing of the trajectories differed between studies, it is difficult to draw conclusions.

Identifying subgroups of renal function trajectories

Background

Renal function in patients with chronic kidney disease (CKD) may follow different trajectory profiles. The aim of this study was to evaluate and illustrate the ability of the latent class linear mixed model (LCMM) to identify clinically relevant subgroups of renal function trajectories within a multicenter hospital-based cohort of CKD patients.

Methods

We analysed data from the NephroTest cohort including 1967 patients with all-stage CKD at baseline who had glomerular filtration rate (GFR) both measured by 51 Cr-EDTA renal clearance (mGFR) and estimated by the CKD-EPI equation (eGFR); 1103 patients had at least two measurements. The LCMM was used to identify subgroups of GFR trajectories, and patients' characteristics at baseline were compared between the subgroups identified.

Results

Five classes of mGFR trajectories were identified. Three had a slow linear decline of mGFR over time at different levels. In the two others, patients had a high level of mGFR at baseline with either a strong nonlinear decline over time ( n  = 11) or a nonlinear improvement ( n  = 94) of mGFR. Higher levels of proteinuria and blood pressure at baseline were observed in classes with either severely decreased mGFR or strong mGFR decline over time. Using eGFR provided similar findings.

Conclusion

The LCMM allowed us to identify in our cohort five clinically relevant subgroups of renal function trajectories. It could be used in other CKD cohorts to better characterize their different profiles of disease progression, as well as to investigate specific risk factors associated with each profile.

Distinctive trajectory groups of mental health functioning among assertive community treatment clients: an application of growth mixture modelling analysis

OBJECTIVE

Assertive community treatment (ACT) studies that have used conventional, statistical growth modelling methods have not examined different trajectories of outcomes or covariates that could influence different trajectories, even though heterogeneity in outcomes has been established in other research on severe mental illness. The purpose of our study was to examine the general trend in mental health functioning of ACT clients over a 2-year follow-up time period, to discover groups of ACT clients with distinctive longitudinal trajectories of mental health functioning, and to examine if some of the key sociodemographic and illness-related factors influence group membership.

METHOD

A 2-year, prospective, within-subjects study of 216 ACT clients within southern Ontario, collected functional outcome data at baseline and 12 and 24 months using the Colorado Client Assessment Record. Baseline covariates included sex, primary diagnosis, number of comorbidities, hospitalization history, and duration of illness. Growth mixture modelling (GMM) was used to examine trajectories.

RESULTS

Clinical staff assessments of ACT clients showed a statistically significant improvement in functioning and 84% achieved successful community tenure. GMM analysis identified 2 classes of ACT clients: class 1 (79.63% of clients) experienced lower and stable overall functioning, and class 2 (20.37%) showed a better baseline functioning score and improvement in the overall functioning over time. Class membership was predicted by the number of comorbidities and diagnosis.

CONCLUSIONS

Our study suggests general stability in overall functioning for the sampled ACT clients over 2 years, but significant heterogeneity in trajectories of functioning.

An observational study of response heterogeneity in children with attention deficit hyperactivity disorder following treatment switch to modified-release methylphenidate

BACKGROUND

Methylphenidate (MPH) has been shown to be effective in the treatment of attention deficit hyperactivity disorder (ADHD) in children. The overall population of children and adolescents with ADHD may comprise distinct clusters of patients that differ in response to MPH. The aim of this analysis was to look for subgroups with different treatment trajectories and to identify their distinctive features.

METHODS

OBSEER was a prospective, observational study examining the effectiveness and safety of once-daily modified-release MPH over 3 months in patients (aged 6-17 years) with ADHD under routine care. Assessments were carried out at baseline (Visit 1), after 1-3 weeks (Visit 2) and 6-12 weeks (Visit 3) after first use of once-daily modified-release MPH. Change in ADHD symptoms, as rated by parents and teachers, was examined post hoc in patients of the intent-to-treat-population (N = 822), using growth-mixture modelling to detect response trajectory groups after switching medication. Age, MPH dose at Visit 1 before medication switch, prescribed once-daily modified-release MPH dose at Visits 1 and 2, conduct problems and emotional symptoms were considered predictors of response subgroups.

RESULTS

Assessing formal statistical criteria and usefulness of the models, a 4-class solution best fitted the data: after switching medication two response groups with severe symptoms at study start and subsequent substantial treatment effects, and two showing no or comparatively little treatment effect, one of which had severe and the other less severe symptoms at study start. Patient age, conduct problems and MPH dose at Visit 1 were predictors of inclusion in subgroups.

CONCLUSIONS

Older children and children with few conduct problems were more likely to be members of a patient cluster with fewer symptoms at study start. Children with a low MPH dose before medication switch had a higher chance of being in the patient cluster with a strong treatment response after switching medication. The current analyses should assist in identifying children likely to achieve a favourable treatment course with MPH and, additionally, those who are in need of alternative treatment options.