Interpersonal Process of Dyadic Coping in Rheumatoid Arthritis: A Perspective From the Australian Rheumatology Association Database.

OBJECTIVE: Dyadic coping, the process of coping that transpires between couples challenged by one partner's illness, is an important predictor of disease adjustment and patient well-being. However, the extent of dyadic coping in rheumatoid arthritis (RA) remains unclear. This study examines the effect of dyadic coping on psychological distress and relationship quality from the perspectives of both participants with RA and their spouses. METHODS: Participants and their spouses were invited to participate in an online survey study if they were aged ≥ 18 years and had lived together for more than a year. The survey included the Chronic Pain Grade Scale, Dyadic Coping Inventory, Depression Anxiety Stress Scale, and Dyadic Adjustment Scale. Participants and spouses completed the survey independently. The actor-partner interdependence model was used to analyze the dyadic data. RESULTS: One hundred sixty-three couples participated. Our findings showed that participants who reported higher supportive dyadic coping reported lower depression, anxiety, and stress, and higher relationship quality, whereas participants who reported higher negative dyadic coping reported higher depression, anxiety, and stress, and lower relationship quality. Spouses who reported higher supportive dyadic coping reported higher relationship quality, but no effect on depression, anxiety, and stress was observed. In contrast, spouses who reported higher negative dyadic coping reported higher levels of depression, anxiety, and stress, and lower relationship quality. CONCLUSION: Participants' and spouses' perceptions of supportive and negative dyadic coping closely influenced their psychological distress and relationship quality. Further, having a partner with RA also seemed to affect the spouse, especially when there was a negative dyadic coping pattern.

Historical Trends and Future Projections of Demand for Permanent Residential Aged Care for Older People in Australia, 2008-2052.

OBJECTIVES: To examine the historical trends and predict the future rates and total volumes of permanent residential aged care (PRAC) service utilization in Australia. DESIGN: A population-based repeated cross-sectional and projection study of non-indigenous older people (≥65 years) accessing PRAC in Australia was conducted. SETTING AND PARTICIPANTS: Publicly available aged care admissions from the Australian Institute of Health and Welfare and population estimates from the Australian Bureau of Statistics were used. METHODS: Historical incidence rates (per 1000 people), incidence rate ratios (IRRs) and 95% CIs of PRAC admission from 2008-2009 to 2020-2021 were estimated using negative binomial regression models. The future incidence and prediction intervals (PIs) of PRAC admission between 2021-2022 and 2051-2052 were projected using a generalized additive model-negative binomial regression. All estimates were adjusted or standardized by sex and age. RESULTS: Between 2008-2009 and 2020-2021, the adjusted admission to PRAC decreased (from 23.6/1000 people to 15.7/1000 people with an IRR = 0.97/year, 95% CI 0.97-0.98). The projected PRAC admission rate will decrease to 12.1/1000 (95%PI 10.8-13.3) by 2037-2038 and 9.0/1000 (95%PI 7.6-10.4) by 2051-2052. The projected volume of PRAC admission will be 73,988 (95%PI 65,960-81,425) at its highest point in 2037-2038 and 64,579 (95%PI 54,258-74,543) in 2051-2052. CONCLUSIONS AND IMPLICATIONS: The utilization of PRAC has decreased in the past decade, and a predicted decrease in PRAC use in future years is estimated. However, the volume of PRAC utilization will still increase for the next 15 years (until 2037-2038) due to our increasingly older population. These findings can inform service planning of PRAC access in Australia.

Objectively measured infant and toddler screen time: Findings from a prospective study.

Objective: Screen time guidelines recommend no screens under two years due to the potential negative impacts on development. While current reports suggest many children exceed this, research relies on parent reports of their children's screen exposure. We objectively assess screen exposure during the first two years and how it differs by maternal education and gender. Methods: This Australian prospective cohort study used speech recognition technology to understand young children's screen exposure over an average day. Data collection occurred every six months when children were 6, 12, 18 and, 24 months old (n = 207). The technology provided automated counts of children's exposure to electronic noise. Audio segments were then coded as screen exposure. Prevalence of screen exposure was quantified, and differences between demographics examined. Results: At six months, children were exposed to an average of 1hr, 16 min (SD = 1hr, 36 min) of screens per day, increasing to an average of 2 h, 28 min (SD = 2 h, 4 min) by 24-months. Some children at six months were exposed to more than 3 h of screen time per day. Inequalities in exposure were evident as early as six months. Children from higher educated families were exposed to 1hr,43 min fewer screens per day, 95%CI (-2hr, 13 min, -1hr, 11 min) compared to lower educated households, with this difference remaining consistent as children age. Girls were exposed to an additional 12 min of screens 95%CI (-20 min, 44 min) per day compared to boys at six months, but this difference reduced to only 5 min by 24-months. Conclusion: Using an objective measure of screen exposure, many families exceed screen time guidelines, the extent increasing with child's age. Furthermore, substantial differences between maternal education groups emerge as young as six months old. This highlights the need for education and supports for parents around screen use in the early years, balanced within the realities of modern life.

Child protection contact among children of culturally and linguistically diverse backgrounds: A South Australian linked data study.

AIM: To describe the cumulative incidence of child protection (CP) system contact, maltreatment type, source of reports to age 7 years, and socio-demographic characteristics for culturally and linguistically diverse (CALD) Australian children. METHODS: We used CP, education, health, and birth registrations data for children followed from birth up to age 7 from the South Australian Better Evidence, Better Outcomes, Linked Data (SA BEBOLD) platform. PARTICIPANTS: SA born children enrolled in their first year of school from 2009 to 2015 (n = 76 563). CALD defined as non-Aboriginal or Torres Strait Islander, spoken language other than English, Indigenous or Sign, or had at least one parent born in a non-English speaking country. OUTCOMES MEASURES: For CALD and non-CALD children, we estimated the cumulative incidence (risk) of CP contacts up to age 7, relative risk and risk differences for all levels of CP contact from notification to out-of-home care (OOHC), primary maltreatment type, reporter type, and socio-economic characteristics. Sensitivity analyses explored different population selection criteria and CALD definitions. RESULTS: By age 7, 11.2% of CALD children had 'screened-in' notifications compared to 18.8% of non-CALD (risk difference [RD] 7.6 percentage points (95% confidence interval: 6.9-8.3)), and 0.6% of CALD children experienced OOHC compared to 2.2% of non-CALD (RD 1.6 percentage points (95% confidence interval: 1.3-1.8)). Emotional abuse was the most common substantiated maltreatment type for CALD and neglect for non-CALD. Among both groups, the most common reporter sources were police and education sector. Socio-economic characteristics were broadly similar. Sensitivity analyses results were consistent with primary analyses. CONCLUSION: By age 7, CALD children had lower risk of contact with all levels of CP. Estimates based on primary and sensitivity analyses suggested CALD children were 5-9 percentage points less likely to have a report screened-in, and from 1.0 to 1.7 percentage points less likely to have experienced OOHC.

Application of multilevel models for predicting pain following root canal treatment.

OBJECTIVES: This study developed predictive models for one-week acute and six-month persistent pain following root canal treatment (RCT). An additional aim was to study the gain in predictive efficacy of models containing clinical factors only, over models containing sociodemographic characteristics. METHODS: A secondary data analysis of 708 patients who received RCTs was conducted. Three sets of predictors were used: (1) combined set, containing all predictors in the data set; (2) clinical set and (3) sociodemographic set. Missing data were handled by multiple imputation using the missing indicator method. The multilevel least absolute selection and shrinkage operator (LASSO) regression was used to select predictors into the final multilevel logistic models. Three measures, the area under the receiver operating characteristic curve (AUROC) and precision-recall curve (AUPRC) and calibration curves, were used to assess the predictive performance of the models. RESULTS: The selected-in factors in the final models, using LASSO regression, are related to pre- and intra-treatment clinical symptoms and pain experience. Predictive performance of the models remained the same with the inclusion (exclusion) of the socio-demographic factors. For predicting one-week outcome, the model built with combined set of predictors yielded the highest AUROC and AUPRC of 0.85 and 0.72, followed by the models built with clinical factors (AUROC = 0.82, AUPRC = 0.66). The lowest predictive ability was found in models with only sociodemographic characteristics (AUROC = 0.68, AUPRC = 0.40). Similar patterns were observed in predicting six-month outcome, where the AUROC for models with combined, clinical and sociodemographic sets of predictors were 0.85, 0.89 and 0.66, respectively, and the AUPRC were 0.48, 0.53 and 0.22, respectively. CONCLUSIONS: Clinical factors such as the severity and experience of pre-operative and intra-operative pain were discovered important to the subsequent development of pain following RCTs. Adding sociodemographic characteristics to the models with clinical factors did not change the models' predictive performance or the proportion of explained variance.

Reflection on modern methods: risk ratio regression-simple concept yet complex computation.

The risk ratio (RR) is the ratio of the outcome among the exposed to risk of the outcome among the unexposed. This is a simple concept, which makes one wonder why it has not gained the same popularity as the odds ratio. Using logistic regression to estimate the odds ratio is quite common in epidemiology and interpreting the odds ratio as a risk ratio, under the assumption that the outcome is rare, is also common. On one hand, estimating the odds ratio is simple but interpreting it is hard. On the other, estimating the risk ratio is challenging but its interpretation is straightforward. Issues with estimating risk ratio still remain after four decades. These issues include convergence of the algorithm, the choice of regression specification (e.g. log-binomial, Poisson) and many more. Various new computational methods are available which help overcome the issue of convergence and provide doubly robust estimates of RR.

Individuals with Inflammatory Bowel Disease Have an Altered Gut Microbiome Composition of Fungi and Protozoa.

It is known that the bacterial gut microbiome is altered in inflammatory bowel disease (IBD), but far less is known about the role of eukaryotic microorganisms in IBD. While eukaryotes are rarer than bacteria within the gastrointestinal environment, the current literature suggests that they may also be implicated in IBD. In our study, we characterized these often-neglected eukaryotic microbial communities by identifying fungi and protozoa in published shotgun stool metagenomes from 355 people with IBD (206 with Crohn's disease, 126 with ulcerative colitis, and 23 with IBD-unclassified) and 471 unaffected healthy individuals. The individuals with IBD had a higher prevalence of fungi, particularly Saccharomyces cerevisiae, and a lower prevalence of protozoa, particularly Blastocystis species (subtypes 1, 2, 3, and 4). Regression analysis showed that disease state, age, and BMI were associated with the prevalence and abundance of these two genera. We also characterized the eukaryotic gut microbiome in a shotgun stool metagenomic dataset from people with IBD who received fecal transplants, with samples pre- and post-transplantation, and from their donors. We found that in some FMT recipients, a single eukaryotic species remained stable over time, while in other recipients, the eukaryotic composition varied. We conclude that the eukaryotic gut microbiome is altered and varies over time in IBD, and future studies should aim to include these microbes when characterizing the gut microbiome in IBD.

Explaining the gap in the experience of depression among arthritis patients.

OBJECTIVE: To explain the factors contributing to the gap in depression between employed arthritis patients with and without paid sick leave. METHODS: Blinder-Oaxaca decomposition analysis was used to identify factors that explain the gap in the experience of depressive symptoms among arthritis patients with paid and unpaid sick leave. Data from the 2018 National Health Interview Survey, USA, was used. RESULTS: A total of 7189 of the NHIS survey participants given the diagnosis of arthritis were identified, of which 39% were male and 61% were female, with mean age of 63.5 years. The decomposition findings suggest patients in the unpaid sick leave group were more likely to report depressive symptoms compared to patients with paid sick leave. The major contributors to the gap in the report of depressive symptoms are sex (female) and annual income (less than 35,000 USD). CONCLUSION: Findings suggest that the absence of paid sick leave is a key determinant for experiencing depressive symptoms among individuals with arthritis. The provision of paid sick leave may reduce report of depressive symptoms among employed arthritis patients in the USA. KEY POINTS: • Individuals with arthritis are consistently at greater risk of depression and unemployment as compared to individuals without arthritis. • To date greater emphasis is put on determinants of unemployment, while there is no available data on benefits associated with being employed, such as sick leave, and how it affects mental health. • Patients with unpaid sick leave appear to experience more persistent depressive symptoms than patients with access to paid sick leave. • To tackle burden of depression among arthritis patients, provision of paid sick leave may be an effective intervention.

Effect of oral health literacy on self-reported tooth loss: A multiple mediation analysis.

BACKGROUND: This study aims to investigate the mediating pathways of oral health literacy (OHL) and oral health-related behaviours on the relationship between education and self-reported tooth loss among Australian adults. METHODS: Data used for studying the effects of mediating pathways are from the National Dental Telephone Interview Survey 2013, a random sample survey of Australian adults aged 18+ years. To study the mediating effects, we use counterfactual-based analysis. To decompose the effect of multiple mediator's alternate, to natural effect, methods such as interventional effects have been proposed. In this paper, we use these approaches to decompose the effect between education, OHL and oral health-related behaviours on self-reported tooth loss. Sensitivity analysis was performed for unmeasured confounding with multiple mediators. RESULTS: Data were available for 2936 Australian adults. The prevalence of persons with ≥12 self-reported tooth loss was approximately 15%. The average total causal effect from the low education group was nearly 150%, and the interventional indirect effect through OHL and the dependence of oral health-related behaviours on OHL to more than 12 missing teeth were 20% and 120%, respectively, higher than in the high education group. Sensitivity analysis indicated if the difference in the prevalence of unmeasured confounder is as big as 6% the direct effect and the indirect effect remains as observed. CONCLUSIONS: An additional two-fifths reduction on having more than 12 missing teeth for Australian adults with lower education level could be achieved if the proportion of lower OHL was decreased and optimal dental behaviours were increased.

The education word gap emerges by 18 months: findings from an Australian prospective study.

BACKGROUND: The idea of the '30 million word gap' suggests families from more socioeconomically advantaged backgrounds engage in more verbal interactions with their child than disadvantaged families. Initial findings from the Language in Little Ones (LiLO) study up to 12 months showed no word gap between maternal education groups. METHODS: Families with either high or low maternal education were purposively recruited into a five-year prospective study. We report results from the first three waves of LiLO when children were 6, 12 and 18 months old. Day-long audio recordings, obtained using the Language Environment Analysis software, provided counts of adult words spoken to the child, child vocalizations and conversational turns. RESULTS: By the time children were 18 months old all three measures of talk were 0.5 to 0.7 SD higher among families with more education, but with large variation within education groups. Changes in talk from 6 to 18 months highlighted that families from low educated backgrounds were decreasing the amount they spoke to their children (- 4219.54, 95% CI -6054.13, - 2384.95), compared to families from high educated backgrounds who remained relatively stable across this age period (- 369.13, 95% CI - 2344.57, 1606.30). CONCLUSIONS: The socioeconomic word gap emerges between 12 and 18 months of age. Interventions to enhance maternal communication, child vocalisations and vocabulary development should begin prior to 18 months.

Associations between Apgar scores and children's educational outcomes at eight years of age.

BACKGROUND: Low Apgar scores are associated with neonatal morbidity and mortality, but effects of Apgar scores of 0-5, 6, 7, 8 and 9 (compared with 10) on longer-term neurodevelopmental outcomes are less clear. AIM: To examine the associations between Apgar scores of 0-5, 6, 7, 8 and 9 (compared with 10) and children's educational outcomes as measured by the Australian National Assessment Program-Literacy and Numeracy (NAPLAN) tests at age eight. MATERIALS AND METHODS: We merged perinatal data including all children born in South Australia from 1999 to 2008 with school assessment data (NAPLAN). School assessments included five learning areas (domains)-reading, writing, spelling, grammar and numeracy. Each domain was categorised according to performing at or below National Minimum Standards (≤NMS). Effects were estimated using Augmented Inverse Probability Weighting (AIPW) accounting for a range of maternal, perinatal and sociodemographic characteristics. RESULTS: Risk differences comparing five-minute Apgar scores of 0-5 with Apgar scores of 10 for children performing ≤NMS for each domain were: reading (0.07 (95% CI -0.16 to 0.29)), writing (0.27 (95% CI -0.14 to 0.68)), spelling (0.15 (95% CI -0.10 to 0.40)), grammar (0.04 (95% CI -0.21 to 0.29)) and numeracy (0.21 (95% CI -0.04 to 0.45)). Risk differences for children performing ≤NMS were also evident when Apgar score of 6 was compared with Apgar score of 10. CONCLUSIONS: Children with five-minute Apgar scores of 0-5 and 6, compared with Apgar score of 10, are at higher risk of scoring at/below the NMS on the NAPLAN assessments at eight years.

Comparison of the Tree-Based Machine Learning Algorithms to Cox Regression in Predicting the Survival of Oral and Pharyngeal Cancers: Analyses Based on SEER Database.

This study aims to demonstrate the use of the tree-based machine learning algorithms to predict the 3- and 5-year disease-specific survival of oral and pharyngeal cancers (OPCs) and compare their performance with the traditional Cox regression. A total of 21,154 individuals diagnosed with OPCs between 2004 and 2009 were obtained from the Surveillance, Epidemiology, and End Results (SEER) database. Three tree-based machine learning algorithms (survival tree (ST), random forest (RF) and conditional inference forest (CF)), together with a reference technique (Cox proportional hazard models (Cox)), were used to develop the survival prediction models. To handle the missing values in predictors, we applied the substantive model compatible version of the fully conditional specification imputation approach to the Cox model, whereas we used RF to impute missing data for the ST, RF and CF models. For internal validation, we used 10-fold cross-validation with 50 iterations in the model development datasets. Following this, model performance was evaluated using the C-index, integrated Brier score (IBS) and calibration curves in the test datasets. For predicting the 3-year survival of OPCs with the complete cases, the C-index in the development sets were 0.77 (0.77, 0.77), 0.70 (0.70, 0.70), 0.83 (0.83, 0.84) and 0.83 (0.83, 0.86) for Cox, ST, RF and CF, respectively. Similar results were observed in the 5-year survival prediction models, with C-index for Cox, ST, RF and CF being 0.76 (0.76, 0.76), 0.69 (0.69, 0.70), 0.83 (0.83, 0.83) and 0.85 (0.84, 0.86), respectively, in development datasets. The prediction error curves based on IBS showed a similar pattern for these models. The predictive performance remained unchanged in the analyses with imputed data. Additionally, a free web-based calculator was developed for potential clinical use. In conclusion, compared to Cox regression, ST had a lower and RF and CF had a higher predictive accuracy in predicting the 3- and 5-year OPCs survival using SEER data. The RF and CF algorithms provide non-parametric alternatives to Cox regression to be of clinical use for estimating the survival probability of OPCs patients.

Educational activities on language and behavioural outcomes at school entry are more important for socioeconomically disadvantaged children: a prospective observational study of Australian children.

BACKGROUND: To investigate whether time spent in educational activities at 2-3 years and developmental outcomes at school entry differ among children from different socioeconomic backgrounds. METHODS: Participants were from the Longitudinal Study of Australian Children (n=4253). Time spent in educational activities was collected using 24-hour time-use diaries. Income was measured using parent self-report. Receptive vocabulary was assessed using the Peabody Picture Vocabulary Test, and problem behaviours were measured by the Strengths and Difficulties Questionnaire. Marginal structural models were used to test whether the effects of educational activities on outcomes differed by income. RESULTS: Children exposed to both <30 min/day in educational activities and being in a low-income household were at greater risk of poorer outcomes at school entry than the simple sum of their independent effects. Compared with children who spent ≥30 min/day in educational activities from high-income households, children who experienced <30 min/day in educational activities from low-income households had a 2.30 (95% CI 1.88 to 2.80) higher risk of having a receptive vocabulary score in the lowest quartile at school entry. The Relative Excess Risk due to Interaction of 0.15 (95% CI -0.38 to 0.67) was greater than 0, indicating a super-additive effect measure modification by income. These patterns were similar for behavioural outcomes. CONCLUSIONS: Our findings suggest that if there was an intervention of sufficient dose to increase the amount of time spent in educational activities to at least 30 min/day for children in the lower-income group, the risk of children having sub-optimal receptive vocabulary would be reduced by 45% and the risk of teacher-reported conduct and hyperactivity problems reduced by 67% and 70%, respectively.

Longitudinal Mediation Analysis Using Natural Effect Models.

Mediation analysis is concerned with the decomposition of the total effect of an exposure on an outcome into the indirect effect, through a given mediator, and the remaining direct effect. This is ideally done using longitudinal measurements of the mediator, which capture the mediator process more finely. However, longitudinal measurements pose challenges for mediation analysis, because the mediators and outcomes measured at a given time point can act as confounders for the association between mediators and outcomes at a later time point; these confounders are themselves affected by the prior exposure and outcome. Such posttreatment confounding cannot be dealt with using standard methods (e.g., generalized estimating equations). Analysis is further complicated by the need for so-called cross-world counterfactuals to decompose the total effect. This work addresses these challenges. In particular, we introduce so-called natural effect models, which parameterize the direct and indirect effect of a baseline exposure with respect to a longitudinal mediator and outcome. These can be viewed as a generalization of marginal structural mean models to enable effect decomposition. We introduce inverse probability weighting techniques for fitting these models, adjusting for (measured) time-varying confounding of the mediator-outcome association. Application of this methodology uses data from the Millennium Cohort Study, a longitudinal study of children born in the United Kingdom between September 2000 and January 2002.

A Dyadic Perspective on Coping and its Effects on Relationship Quality and Psychological Distress in Couples Living with Chronic Pain: A Longitudinal Study.

OBJECTIVE: Dyadic coping is a process of coping within couples that is intended not only to support the patient with chronic pain but also to maintain equilibrium in the relationship. This study aims to investigate the effect of patient-perceived and spouse-reported dyadic coping on both the patient and their partner's relationship quality and anxiety, stress, and depression over time. METHODS: One hundred thirty-nine couples, with one partner experiencing chronic pain, participated in this study. Spanning three measurements over six months, couples reported on their anxiety, stress, depression, relationship quality, and dyadic coping. RESULTS: Patient-perceived supportive dyadic coping was positively associated with both partners' relationship quality but was negatively associated with spouses' stress over time. Patient-perceived negative dyadic coping was negatively associated with both partners' relationship quality and positively associated with patients' depression and spouses' depression and stress over time. Spouse-reported supportive dyadic coping showed a positive association with their own relationship quality and a negative association with spouses' depression at baseline and patients' depression at three-month follow-up. Spouse-reported negative dyadic coping was negatively associated with their relationship quality at baseline and positively associated with their partner's anxiety and stress at six-month and three-month follow-up, respectively. Similar inference was observed from the findings of growth curve model. CONCLUSIONS: As compared with spouse report, patient perception of dyadic coping is a better predictor of both partners' relationship quality and psychological outcomes over time. Both partners may benefit from early psychosocial intervention to improve their dyadic coping, relationship quality, and psychological outcomes.

Which time investments in the first 5 years of life matter most for children's language and behavioural outcomes at school entry?

BACKGROUND: The ways children spend their time is one of the most valuable inputs for healthy child development. It is unknown which time investment yields the greatest return for children's language and behavioural outcomes at school entry. METHODS: We used data from the first three waves (2004, 2006, 2008) of the Longitudinal Study of Australian Children (n = 4253). At every wave, parents completed 24-h time-use diaries on one randomly selected week and one weekend day. The amount of time children spent on 11 activities at ages 0-1, 2-3 and 4-5 years was analysed. Receptive vocabulary was assessed using the Peabody Picture Vocabulary Test, and externalizing behaviours were measured by the Strengths and Difficulties Questionnaire, completed by parents and teachers at 4-5 years. To identify which time investment in the first 5 years of life mattered most for children's outcomes, a new production function was developed. This production function was estimated using a log-log linear regression model. RESULTS: Relative to other time investments, time spent on educational activities at 2-3 years of age was the most important time investment for receptive vocabulary and behavioural outcomes at school entry. After adjusting for confounding, every 1 h invested in educational activities at 2-3 years was associated with a 0.95% [95% CI (confidence interval): 0.62, 1.28] increase in receptive vocabulary, and a -5.72% (95% CI: -7.71, -3.73) and -9.23% (95% CI: -12.26, -6.20) reduction in parent- and teacher-reported externalizing problem behaviours. Time invested in play was also important to both receptive vocabulary and behaviour. One hour invested in play at 2-3 and 4-5 years was associated with a 0.68% (95% CI: 0.38, 0.98) and 0.71% (95% CI: 0.39, 1.03) increase in children's receptive vocabulary at school entry. In addition, time invested in play at 2-3 and 4-5 years was associated with reduced problem behaviours at school entry. In contrast, screen time at all ages was associated with poorer parent- and teacher-reported externalizing problem behaviours. CONCLUSIONS: These results suggest that time invested in educational activities at 2-3 years of age yield the greatest return for children's receptive vocabulary and behaviour at school entry.

Effect decomposition through multiple causally nonordered mediators in the presence of exposure-induced mediator-outcome confounding.

Avin et al (2005) showed that, in the presence of exposure-induced mediator-outcome confounding, decomposing the total causal effect (TCE) using standard conditional exchangeability assumptions is not possible even under a nonparametric structural equation model with all confounders observed. Subsequent research has investigated the assumptions required for such a decomposition to be identifiable and estimable from observed data. One approach was proposed by VanderWeele et al (2014). They decomposed the TCE under three different scenarios: (1) treating the mediator and the exposure-induced confounder as joint mediators; (2) generating path-specific effects albeit without distinguishing between multiple distinct paths through the exposure-induced confounder; and (3) using so-called randomised interventional analogues where sampling values from the distribution of the mediator within the levels of the exposure effectively marginalises over the exposure-induced confounder. In this paper, we extend their approach to the case where there are multiple mediators that do not influence each other directly but which are all influenced by an exposure-induced mediator-outcome confounder. We provide a motivating example and results from a simulation study based on from our work in dental epidemiology featuring the 1982 Pelotas Birth Cohort in Brazil.