Our Publications

2018


He awa whiria—braided rivers: Understanding the outcomes from Family Start for Māori

2018

In Aotearoa New Zealand the “braided rivers—he awa whiria” metaphor is facilitating conversations between Māori (indigenous peoples) and non-Māori researchers about the integration of knowledge systems. Rhema Vaithianathan, Tim Maloney and their co-authors explore how an approach based on he awa whiria can work in practice in the examination of the efficacy for Māori whānau (families) of the government’s intensive home-visiting programme, Family Start. Published in Evaluation Matters—He Take Tō Te Aromatawai Online First.

Citiation:

Cram, F., Vette, M., Wilson, M., Vaithianathan, R., Maloney, T., & Baird, S. (2018). He awa whiria—braided rivers: Understanding the outcomes from Family Start for Maori. Evaluation Matters, 165-207.


Estimating the economic costs of ethnic health inequalities: protocol for a prevalence-based cost-of-illness study in New Zealand (2003-2014)

June 2018

This paper is a protocol for a proposed study, by researchers including Rhema Vaithianathan, that will investigate inequities in health between the indigenous Māori and non-Māori adult population in New Zealand and estimate the economic costs associated with these differences.

Citation:

Reid, P., Paine, S., Te Ao, B., Vaithianathan, R., Willing, E., & Wyeth, E. (2018, June 19). Estimating the Economic Costs of Ethnic Health Inequties: Protocol for a Prevalence-Based-Cost-of-Illness-Study in New Zealand (2003-2014). BMJ Open, 1-7.


Labour market effects of activating sick-listed workers

April 2018

Bénédicte Rouland and her co-authors use data from a large-scale randomized controlled trial conducted in Danish job centres to investigate the effects of activating sick-listed workers on subsequent labour market outcomes. Comparing treated and controls, the authors find an overall unfavourable effect on subsequent labour market outcomes.

Citation:

Rehwald, K., Rosholm, M., & Rouland, B. (2018). Labour market effects of activating sick-listed workers. Labour Economics.


Cumulative Prevalence of Maltreatment Among New Zealand Children, 1998–2015

April 2018

Bénédicte Rouland and Rhema Vaithianathan explore the cumulative prevalence in New Zealand of notifications to child protective services, substantiated maltreatment cases and out-of-home placements.  The study shows that 1 in 4 New Zealand children will be subject to at least 1 notification at age 17, an incidence of notification higher than that of medicated asthma among children.

Citation:

Rouland, B., & Vaithianathan, R. (2018). Cumulative Prevalence Of Maltreatment Among New Zealand Children, 1998–2015 . American journal of public health, 108(4), 511-513.


A Case Study of Algorithm-Assisted Decision Making in Child Maltreatment Hotline Screening Decisions

2018

Diana Benavides-Prado, Oleksandr Fialko, Rhema Vaithianathan, Alexandra Chouldechova and Emily Putnam-Hornstein describe their work on developing, validating, fairness auditing, and deploying a risk prediction model in Allegheny County, PA, USA. They discuss the results of their analysis to-date and highlight critical problems and data bias issues that present challenges for model evaluation and deployment.

Citation:

Chouldechova, A., Putnam-Hornstein, E., Benavides-Prado, D., Fialko, O., & Vaithianathan, R. (2018). A case study of algorithm-assisted decision making in child maltreatment hotline screening decisions. Proceedings of Machine Learning Research, 1-15.


Injury and Mortality Among Children Identified as at High Risk of Maltreatment

February 2018

This study by Rhema Vaithianathan, Bénédicte Rouland and Emily Putnam-Hornstein explored a model which assigned risk scores for the risk of a substantiated finding of maltreatment to children born in New Zealand in 2010, to see whether children at the highest 10% and 20% of risk would have an elevated chance of injury or death in early childhood. The study found that children assessed as being “very high risk” (highest 10%) and “high-risk” (highest 20%) had 4.8 times and 4.2 times respectively higher post-neonatal mortality rates than other children.

Citation:

Vaithianathan, R., Rouland, B., & Putnam-Hornstein, E. (2017). “Injury and Mortality Among Children Identified as at High Risk of Maltreatment”. Pediatrics 141(2).


2017


Risk assessment and decision making in child protective services: Predictive risk modeling in context

June 2017

The authors, including Rhema Vaithianathan, review the literature and provide a context for predictive risk modelling in the current risk assessment paradigm in child protective services. They describe how predictive analytics or predictive risk modelling using linked administrative data may provide a useful complement to current approaches.

Citation

Cuccaro-Alamin, S., Foust, R., Vaithianathan, R., & Putnam-Hornstein, E. (2017). “Risk assessment and decision making in child protective services: Predictive risk modelling in context”. Children and Youth Services Review 79


Decomposing ethnic differences in university academic achievement in New Zealand

June 2017

Tim Maloney and Zhaoyi Cao use individual-level administrative data to examine the extent and potential explanations for the relatively poorer academic performance of three ethnic minority groups in their first year of study at a New Zealand university. Substantial differences in course completion rates and letter grades are found for Māori, Pasifika, and Asian students relative to their European counterparts. These large and significant gaps persist in the face of alternative definitions of ethnicity and sample restrictions.

Citation:

Cao, Zhaoyi & Maloney, Tim. (2017). Decomposing ethnic differences in university academic achievement in New Zealand. Higher Education. 75. 10.1007/s10734-017-0157-6.


Family Start Impact Study: Selected Extensions

April 2017

This report provides selected extensions to a 2016 quasi-experimental impact evaluation of the Family Start Home Visiting programme.  The extensions explore the efficacy of Family Start for additional sub-populations of participant families, and when delivered by sub-populations of providers.  Results indicate that Family Start was effective in reducing some measures of post-neonatal infant mortality across sub-groups studied, including teen and non-teen mothers, children in families with and without past contact with Child Youth and Family, and Maori children receiving Family Start from Maori and mainstream providers.

Citation

Vaithianathan, R., Wilson, M., Maloney, T. and Baird, S. (2016). The Impact of the Family Start Home Visiting Programme on Outcomes for Mothers and Children: A Quasi-Experimental Study. Wellington: Ministry of Social Development.


Developing Predictive Risk Models to Support Child Maltreatment Hotline Screening Decisions: Allegheny County Methodology and Implementation

April 2017

This methodology document traces the development and implementation of the Allegheny Family Screening Tool (AFST), a child welfare predictive risk-modelling tool built by a research team led by Rhema Vaithianathan. The AFST is intended to support call screening of child maltreatment referrals by Allegheny County Department of Human Services.  The methodology document includes an overview of existing practice, methodology and performance metrics of the model and details of the external validation and next steps for the model rebuild.

Citation

Vaithianathan, R., Jiang, N., Maloney, T., Nand, P., & Putnam-Hornstein, E. (2017). Developing Predictive Risk Models to Support Child Maltreatment Hotline Screening Decisions: Allegheny County Methodology. Centre for Social Data Analytics. Auckland: Centre for Social Data Analytics.


Black–White Differences in Child Maltreatment Reports and Foster Care Placements: A Statistical Decomposition Using Linked Administrative Data

March 2017

The age and marital status of parents explains racial disparities in Child Protective Service (CPS) involvement, according to a study co-authored by Tim Maloney and Rhema Vaithianathan. In the study, birth records for all children born in Allegheny County, Pennsylvania, between 2008 and 2010 were linked to administrative service records.

Citation

Maloney, T., Jiang, N., Putnam-Hornstein, E., Dalton, E., & Vaithianathan, R. (2017). Black–White differences in child maltreatment reports and foster care placements: A statistical decomposition using linked administrative data. Maternal and child health journal21(3), 414-420.


Impact of school-based support on educational outcomes of teen-mothers: Evidence from New Zealand's "Teen Parent Units"

February 2017

Researchers found New Zealand teenage mothers with access to Teen Parent Units (TPUs) had better educational outcomes than those with no access. This research was conducted through the linkage of social sector administrative data.

Citation

Vaithianathan, R., Maloney, T., Wilson, M., Staneva, A., & Jiang, N. (2017) Impact of school-based support on educational outcomes of teen-mothers: Evidence from New Zealand's "Teen Parent Units" Working Paper.


2016


Impact of the Family Start Home Visiting Programme on Outcomes for Mothers and Children: A Quasi-Experimental Study

February 2016

Family Start workers make regular home visits and, using a structured program, seek to improve parenting capability and practice. These resources from the Ministry of Social Development evaluate the impact of the Family Start programme in improving outcomes for participating families

Citation

Vaithianathan, R., Wilson, M., Maloney, T., & Baird, S. (2016). The Impact of the Family Start Home Visiting Programme on Outcomes for Mothers and Children: A Quasi-Experimental Study. Ministry of Social Development.


2014


Using predictive modelling to identify students at risk of poor university outcomes

November 2014

This paper outlines the use of predictive risk modeling tools to identify vulnerable students and understand factors that place these students at risk of non-completion and non-retention early in their university careers. Administrative data from the enrollment process is used to identify the factors contributing to these adverse outcomes.

Citation

Jia, P., & Maloney, T. (2015).Using predictive modelling to identify students at risk of poor university outcomesHigher Education70(1), 127-149.


Demand in New Zealand hospitals: Expect the unexpected?

October 2014

This article presents a model to predict patient demand at the hospital facility level, which is established with data from a national database of hospital admissions.The paper also constructs two indicators of demand shocks, at hospital and disease chapter levels, including an assessment of the consequent impact on patient outcomes.

Citation

Jiang, N., & Pacheco, G. (2014). Demand in New Zealand hospitals: expect the unexpected? Applied Economics46(36), 4475-4489.


Addressing child maltreatment in New Zealand: Is poverty reduction enough?

August 2014

This publication discusses the use of predictive risk models to target early and appropriate intervention to reduce child maltreatment and suggests potential issues that may arise from this approach to child protection.\

Citation

Dare, T., Vaithianathan, R., & De Haan, I. (2014). Addressing child maltreatment in New Zealand: is poverty reduction enough?Educational philosophy and theory46(9), 989-994.


2013


Integrating care for high risk patients in England using the virtual ward model

November 2013

This paper provides a discussion of the extent to which integrated care was achieved in the analysis of virtual wards in Croydon, Devon and Wandsworth. Key success factors and challenges are identified from the results of the case studies.

Citation

Lewis, G., Vaithianathan, R., Wright, L., Brice, M., Lovell, P., Rankin, S., & Bardsley, M. (2013). Integrating care for high-risk patients in England using the virtual ward model: lessons in the process of care integration from three case sites. International journal of integrated care13(4).


Children in the public benefit system at risk of maltreatment

September 2013

This paper outlines the method of using an automated predictive risk model to identify children at high risk of maltreatment, as well as discussing the strategic targeting of prevention activities toward these individuals.

Citation

Vaithianathan, R., Maloney, T., Putnam-Hornstein, E., & Jiang, N. (2013). Children in the public benefit system at risk of maltreatment: Identification via predictive modeling. American journal of preventive medicine45(3), 354-359.