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Can Early Intervention Improve Maternal Well-Being? Evidence from a Randomized Controlled Trial

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Objective This study estimates the effect of a targeted early childhood intervention program on global and experienced measures of maternal well-being utilizing a randomized controlled trial design. The primary aim of the intervention is to improve children’s school readiness skills by working directly with parents to improve their knowledge of child development and parenting behavior. One potential externality of the program is well-being benefits for parents given its direct focus on improving parental coping, self-efficacy, and problem solving skills, as well as generating an indirect effect on parental well-being by targeting child developmental problems. Methods Participants from a socio-economically disadvantaged community are randomly assigned during pregnancy to an intensive 5-year home visiting parenting program or a control group. We estimate and compare treatment effects on multiple measures of global and experienced well-being using permutation testing to account for small sample size and a stepdown procedure to account for multiple testing. Results The intervention has no impact on global well-being as measured by life satisfaction and parenting stress or experienced negative affect using episodic reports derived from the Day Reconstruction Method (DRM). Treatment effects are observed on measures of experienced positive affect derived from the DRM and a measure of mood yesterday. Conclusion The limited treatment effects suggest that early intervention programs may produce some improvements in experienced positive well-being, but no effects on negative aspects of well-being. Different findings across measures may result as experienced measures of well-being avoid the cognitive biases that impinge upon global assessments.
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RESEARCH ARTICLE
Can Early Intervention Improve Maternal
Well-Being? Evidence from a Randomized
Controlled Trial
Orla Doyle
1
*, Liam Delaney
2
, Christine O’Farrelly
3
, Nick Fitzpatrick
4
, Michael Daly
2
1UCD School of Economics & UCD Geary Institute for Public Policy, University College Dublin, Belfield,
Dublin 4, Ireland, 2Behavioural Science Centre, Stirling Management School, Stirling University, United
Kingdom & UCD Geary Institute for Public Policy, University College Dublin, Belfield, Dublin 4, Ireland,
3Centre for Mental Health, Imperial College London, Commonwealth Building, Hammersmith Hospital
Campus, Du Cane Road, London, United Kingdom, 4Frontier Economics, 71 High Holborn, London, United
Kingdom
*Orla.Doyle@ucd.ie
Abstract
Objective
This study estimates the effect of a targeted early childhood intervention program on global
and experienced measures of maternal well-being utilizing a randomized controlled trial
design. The primary aim of the intervention is to improve children’s school readiness skills by
working directly with parents to improve their knowledge of child development and parenting
behavior. One potential externality of the program is well-being benefits for parents given its
direct focus on improving parental coping, self-efficacy, and problem solving skills, as well as
generating an indirect effect on parental well-being by targeting child developmental problems.
Methods
Participants from a socio-economically disadvantaged community are randomly assigned
during pregnancy to an intensive 5-year home visiting parenting program or a control group.
We estimate and compare treatment effects on multiple measures of global and experi-
enced well-being using permutation testing to account for small sample size and a stepdown
procedure to account for multiple testing.
Results
The intervention has no impact on global well-being as measured by life satisfaction and
parenting stress or experienced negative affect using episodic reports derived from the Day
Reconstruction Method (DRM). Treatment effects are observed on measures of experi-
enced positive affect derived from the DRM and a measure of mood yesterday.
Conclusion
The limited treatment effects suggest that early intervention programs may produce some
improvements in experienced positive well-being, but no effects on negative aspects of well-
PLOS ONE | DOI:10.1371/journal.pone.0169829 January 17, 2017 1 / 25
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OPEN ACCESS
Citation: Doyle O, Delaney L, O’Farrelly C,
Fitzpatrick N, Daly M (2017) Can Early Intervention
Improve Maternal Well-Being? Evidence from a
Randomized Controlled Trial. PLoS ONE 12(1):
e0169829. doi:10.1371/journal.pone.0169829
Editor: Jacobus P. van Wouwe, TNO,
NETHERLANDS
Received: October 4, 2016
Accepted: November 17, 2016
Published: January 17, 2017
Copyright: ©2017 Doyle et al. This is an open
access article distributed under the terms of the
Creative Commons Attribution License, which
permits unrestricted use, distribution, and
reproduction in any medium, provided the original
author and source are credited.
Data Availability Statement: All relevant data are
within the paper and its Supporting Information
files.
Funding: The study was funded by the Irish
Research Council through the Government of
Ireland Collaborative Project Scheme. The overall
trial was funded by the Northside Partnership,
through The Atlantic Philanthropies and the
Department of Children and Youth Affairs. The
funding source had no involvement in the study
design, collection, analysis, and interpretation of
the data, in the writing of the report, or in the
being. Different findings across measures may result as experienced measures of well-
being avoid the cognitive biases that impinge upon global assessments.
Introduction
Understanding the impact of targeted early intervention policies on the life-long development
of children is an increasingly important focus of modern policymakers. One potential exter-
nality of such interventions is welfare improvements for parents, particularly for policies that
target parenting and coping skills. Such benefits may yield value both directly, through their
immediate impact on parental utility, and indirectly, through improvements in child health
and development. Understanding how to quantify these benefits is essential for providing a
full account of the costs and benefits of early intervention policies.
The identification of the utility effects of public policies is frequently hampered by non-
experimental designs which limit inferences regarding causality. Randomized controlled trials
are widely considered the most robust means of determining impact [1], yet few experimental
evaluations incorporate comprehensive measures of utility into estimates of treatment effects.
Global well-being measures are increasingly used as direct measure of utility and are based on
retrospective assessments of evaluative (e.g. life satisfaction) and hedonic (e.g. happiness) well-
being. More recently, studies have argued for a more disaggregated approach where experi-
enced utility is measured at the level of the day or even in real-time e.g. [2,3]. To date, few
studies have used these utility flow measures to evaluate public policies, including targeted
intervention programs.
In this paper, we report findings on the impact of an early intervention program on the
well-being of mothers in a disadvantaged area of Ireland. Our paper adds to the literature by
exploiting a randomized controlled trial in which participants are assigned to an intensive
five-year home visiting parenting program or a control group that receives low level supports
common to both groups. The primary aim of the program is to improve children’s school
readiness skills by working directly with parents to improve their knowledge of child develop-
ment and parenting behavior. Thus, one potential externality of the program is well-being
effects for parents given its focus on improving parental coping, self-efficacy, and problem
solving skills. In particular, the logic model underlying the program is based on the assump-
tion that promoting change in parents’ knowledge, attitudes, and well-being would mediate
gains for children by increasing parenthood enjoyment and developing secure parent-child
relationships [4]. Previous studies on the impact of this program up to 36 months of age identi-
fied a number of effects on the primary outcomes of the trial, namely, children’s cognitive,
behavioral, and physical health [5,6]. It is possible that such improvements in child outcomes
may be mediated by improvements in parental outcomes, or improvements in child outcomes
may lead to improvements in parental outcomes. The objective of this paper is to test for pro-
gram effects on parental well-being, a secondary outcome of the trial, using a novel combina-
tion of methods.
The study is the first to examine the impact of a policy intervention on measures of both
experienced and global well-being using an experimental design. This distinction between
experienced and global well-being has been described as reflecting the difference between “liv-
ing life” and “thinking about life” [7]. In this study, global well-being is captured using mea-
sures of life satisfaction and a standardized measure of parenting stress. Experienced well-
being is captured using daily reports of average, positive, and negative affect derived from the
Day Reconstruction and Maternal Well-Being
PLOS ONE | DOI:10.1371/journal.pone.0169829 January 17, 2017 2 / 25
decision to submit the paper for publication. The
authors are fully independent from the funders.
Competing Interests: The authors have declared
that no competing interests exist.
Day Reconstruction Method (DRM) and a measure of mood yesterday. As the DRM incorpo-
rates time use data, it allows us to measure parental well-being during times spent with and
without the target child. This is particularly relevant given the ambiguity of the effect of chil-
dren on parental well-being, an issue that is complicated by selection into parenthood [8,9].
Thus, measuring well-being at multiple points of the day may help to improve understanding
about the causal relationship between children and parental well-being. Time use data also
allows us to determine whether any identified treatment effects are driven by differences in
parents’ daily activities.
Utilizing previously developed methodology [10], we employ permutation testing to address
issues relating to the small sample size used and, as a robustness test, we apply a stepdown pro-
cedure to mitigate the likelihood of accepting a false positive due to multiple hypothesis testing.
Finally, we estimate unconditional models, in addition to conditional models, which allow us to
control for any baseline imbalance between the groups.
Overall, we find limited evidence that the program improves maternal well-being, however
we do identify a treatment effect on experienced reports of happiness across episodes of the
study day as measured by the DRM. In most specifications, this applies to episodes both with
and without the target child. We also find a treatment effect on an experienced measure of
mood yesterday, yet not during periods when participants are with their child(ren). Consistent
with the early intervention literature, the program has no impact on negative aspects of well-
being, including experienced negative affect and a global standardized measure of parenting
stress. In addition, while higher proportions of the treatment group report being satisfied with
their lives compared to the control group, these differences do not reach statistical significance.
We also find no differences between the treatment and control groups in time use across the
study day concerning the amount of time or types of activities mothers engage in with their
child.
The paper is structured as follows. The next section outlines conceptual issues involved in
measuring well-being and their relevance for the evaluation of early intervention programs.
This is followed by a description of the intervention under investigation and the well-being
measures employed. Next, we outline our empirical model and statistical methods before pre-
senting the results. Finally, we discuss the findings and conclude.
Background and Literature
Well-being and evaluation of public policy
The use of well-being measures in public policy has been widely debated in recent years [11].
Concerns regarding an overreliance on financial measures of utility have led to calls for global
well-being measures to be incorporated into national progress indicators e.g. [12,13,14,15].
There is also a growing interest in using well-being measures to evaluate public goods and poli-
cies [16,17,18,19,20]. However, one issue with this approach is the identification of causal
effects, and while instrumental variable estimates or exploiting fine-grained exogenous variation
in the provision of the good e.g. [21], can be used, these methods require restrictive assump-
tions. Thus, it is becoming increasingly common to pilot test provision of public goods using
random assignment [22,23].
Maternal welfare and early intervention p
Regarding policies which aim to boost children’s skills, recent studies using random assign-
ment have focused on targeted early intervention programs [24,10,25]. Less work, however,
has examined the effect of these interventions on the welfare of parents. While such effects
may exist, it is difficult to hypothesise the likely direction of the effect. For example, their
Day Reconstruction and Maternal Well-Being
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impact on parental consumption may be ambiguous if there are substitution effects whereby
parents reduce their employment in order to spend more time with their children. Conse-
quently, measuring parental welfare directly may prove more informative regarding the utility
effects of early intervention programs.
Home visiting programs (HVPs) are a common form of early intervention that aim to
mediate gains for children by working directly with parents [26]. Such programs may result in
improved parental well-being as they typically target maternal health, encourage parents to
adopt sensitive, responsive, and consistent parenting behaviors, and assist in family planning
and the pursuit of education and employment opportunities [27]. Despite this conceptual
premise, HVP studies do not always examine outcomes for parents and children or explicitly
test these pathways [26]. Nonetheless, meta-analytic findings suggests that the effects for
parents are concentrated on parenting behaviors, attitudes, and skills [28,29]. There is also evi-
dence, albeit less consistent, for improvements in parental life course outcomes [28,29].
Less is known about the impact of HVPs on parental psychological well-being. On the one
hand, HVPs may improve well-being directly through improved maternal coping, problem
solving, and self-efficacy skills, and through the therapeutic relationship with the home visitor,
and indirectly through the reduction of child behavioral problems, parent-child conflict,
changes in parental health behaviors, and increased social support–although evidence for
these outcomes is mixed e.g., [30]. Alternatively, drawing on the family investment theory
[31], HVPs may have deleterious effects on well-being if the intervention promotes substantial
parental investment in the child which comes at a cost of increased parental time, effort, and
emotional outlays in the short-run, with the expectation that parental utility will increase in
the long run.
Research in the HVP field has focused predominantly on global measures of negative affect
given the burden that stress and depression exert on parent functioning and the subsequent
consequences for child well-being e.g., [32,33,34]. Yet, a systematic review found that HVPs
are not sufficiently powerful, in and of themselves, to substantially mitigate depression as mea-
sured by standardized self-report instruments [35]. Equally, HVPs tend not to be effective in
reducing parent-reported levels of stress [29]. Comparatively fewer studies have examined the
impact of HVPs on positive aspects of parental well-being such as self-efficacy and self-esteem.
Theories of self-efficacy, which link people’s beliefs about their capabilities to their subsequent
motivation, behavior, and well-being [36], are central to many HVPs [27]. Studies that have
examined positive aspects of well-being are inconclusive [37,38], and have yet to be subject to
systematic review. The evidence to date suggests that it may be easier for HVPs to alter parent-
ing behaviors than emotional states [39].
Global versus experienced measures of well-being
A critical issue for evaluations of public policies, including early intervention programs, is how
well-being should be measured [40,41]. A growing literature has emerged on the use of global
retrospective measures of well-being, such as evaluations of life satisfaction and accounts of
happiness. These measures have the advantage of providing information on appraisal of cir-
cumstances and feelings about them; however debate exists regarding their consistency. A
number of studies have documented how immediate mood and context can bias retrospective
evaluations, and have argued that the act of thinking about such quantities may focus individu-
als on aspects of their life that are not crucial to their actual well-being (e.g., [42]). Further-
more, retrospective happiness accounts tend not to accurately represent experience as such
accounts are overly influenced by intense or recent experiences [3]. In addition, people may
Day Reconstruction and Maternal Well-Being
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simply fail to accurately recall their well-being over extended periods of several days or weeks,
introducing error into well-being estimates.
It has been argued that experienced utility is a more reliable measure of well-being as it
directly captures emotional experiences in real time [2]. The experience sampling approach
collects information on respondents’ self-reported emotional responses to their daily experi-
ences at specific points during a day using electronic devices as prompts [43]. It has been
widely applied in clinical psychology and psychiatry studies e.g., [44,45,46,47,48,49]
The use of the DRM has been proposed as an alternative means of recording fluctuations in
experienced well-being in a less burdensome manner [3]. The DRM is completed in a single
session during which respondents divide the previous day into discrete episodes which are
then rated across several positive and negative affective states. Compared with experience sam-
pling, the DRM has the advantage of eliciting events over an entire day without interfering
with the day’s activities. The DRM has been used in a variety of non-experimental settings
including measuring time use and emotional well-being among the unemployed [40,50],
examining individuals with optimal mental health [51], and studying women during the tran-
sition to motherhood [52].
Another important distinction when measuring well-being concerns positive and negative
affect, which have been shown to represent different dimensions of well-being with distinct
correlates. For example, negative affect (including feelings of stress, anxiety, anger, and impa-
tience) is traditionally associated with health issues, whereas positive affect (including feelings
of happiness, calm, focus, and control) is associated with social engagement [53,54,55]. An
advantage of the DRM is its ability to elicit ratings of both positive and negative affect.
One potential concern when using the DRM is that respondents may not accurately recall
emotions experienced the previous day. Several studies have examined this issue by comparing
DRM ratings with ratings provided in real time using experienced sampling methods, and all
find a reasonably high degree of convergence [45,56,3,57,58]. Furthermore, a positive corre-
lation between DRM measures of negative affect and fluctuations in heart rate, an objective
indicator of psychological stress, has been found [59]. See [60] for a critical review of DRM
research.
Although the DRM is less burdensome than experienced sampling, it nonetheless requires
participant effort [61]. Consequently, interest has developed in less intensive measures of expe-
rienced well-being that are still robust to cognitive biases which affect global measures. One
practical alternative is a measure of mood yesterday which requires respondents to provide an
overall appraisal of their emotional states across the course of the previous day. Although these
measures have been incorporated in some large scale social surveys, evidence is still needed to
endorse their value as a viable proxy for more intensive measures of experienced affect [62].
Material and Methods
Experimental set-up
The RCT was registered with the International Standard Randomised Controlled Trial
Number (ISRCTN) register, (unique identifier ISRCTN04631728—The evaluation of the
Preparing For Life early childhood intervention programme, http://www.controlled-trials.
com/ISRCTN04631728). As the program is a community-based intervention targeting
school readiness skills rather than a clinical trial examining health outcomes, the trial was
registered post-recruitment rather than prospectively. All study procedures were approved
by the UCD Human Research Ethics Committee, the Rotunda Hospital Ethics Committee,
and the National Maternity Hospital Ethics Committee, and was conducted and reported
in conformity with CONSORT guidelines (see S1 Protocol). All participants gave written
Day Reconstruction and Maternal Well-Being
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informed consent before randomization. Written informed consent for those under the age
of 18 was provided by their parents/guardians. Information on the design of the trial has
been published elsewhere [63] (also see S2 Protocol).
The original study enrolled pregnant women from a suburban community in Dublin, Ire-
land, which had above national average rates of unemployment, school dropout, lone parent
households, and public housing. The inclusion criteria included all pregnant women living in
the catchment area during the recruitment period, regardless of parity. There were no exclu-
sion criteria. This within-community universal approach was adopted to avoid the stigmatiza-
tion which may arise in programs with highly selective inclusion criteria. Participation was
voluntary and recruitment took place between the 29
th
of January 2008 and the 4
th
of August
2010 through two maternity hospitals and in the community. Recruitment and randomization
were conducted by the program recruitment officer.
The sample size was calculated based on a small effect size (ES, standardized difference between
group means) for child school readiness skills as identified by a previous meta-analytic study of
home visiting programs [29]. Specifically, a mean difference between the treatment and control
groups of between 2 and 5 points (depending on the study included in the meta-analysis) on stan-
dardized cognitive development scores (average standardized ES = 0.184) was expected. Given this
effect size, in order to power the study at the 80% level, based on an alpha level of .05 using a two-
tailed t-test, a sample size of approximately 117 in both groups was required. In total, 233 partici-
pants were recruited and a computerised unconditional probability randomization procedure,
with no stratification or block techniques, assigned 115 participants to the treatment group and
118 to the control group. To ensure randomization was not compromised, the computerized pro-
cedure generated an automatic email which was sent to the program manager and the principal
investigator and included the participant’s assignment condition and identification code. Attempts
to reassign participants would trigger a second email highlighting any intentional subversion of
the randomization process.
The population based recruitment rate was 52% based on the number of live births in the
community during the recruitment window. A further 22% of eligible participants were not
contactable and a further 26% met the program recruiter or made contact but did not join the
program. To identify whether there are systematic differences between eligible participants
and eligible non-participants, a socio-demographic profile survey was conducted with a sam-
ple of eligible non-participants (n = 102) when their children were 4 years old. An analysis of
these data indicated that the eligible non-participants were of a slightly higher socioeconomic
status than the participants who joined the program. This suggests that the program was effec-
tive in targeting the families most in need of intervention.
There were no statistically significant differences between the original treatment and con-
trol groups on 90.5% (114/126) of baseline variables, suggesting the randomization procedure
was successful [63].
The treatment included the Preparing for Life (PFL) HVP [4] and the Triple P Positive Par-
enting Program [64]. The treatment aims to improve the health and development of children
by intervening during pregnancy and working with families until the children start school at
age 4/5. The program was developed in response to evidence that children from the catchment
area were lagging behind their peers in terms of cognitive and non-cognitive skills at school
entry [65]. PFL is a manualized program which is grounded in the theories of human attach-
ment [66], socio-ecological development [67], and social-learning [36].
Treatment. The treatment prescribes twice monthly home visits, lasting approximately
one hour, delivered by mentors from a cross-section of professional backgrounds including
education, social care, and youth studies. Mentors received extensive training prior to program
implementation and monthly supervision thereafter. Each family is assigned the same mentor
Day Reconstruction and Maternal Well-Being
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over the course of the treatment where possible. The home visits are tailored based on the age
of the child and the needs of the family and are guided by a set of Tip Sheets presenting best-
practice information on pregnancy, parenting, and child health and development.
This study refers to the impact of the treatment on a secondary outcome, maternal well-
being, and includes participants who were engaged with the program for at least two and a half
years. The program is anticipated to have an impact on well-being due to the nature of the
mentor-mother relationship and the supports provided. Specifically, the mentors support
mothers by building a strong relationship with them and helping them to improve their par-
enting and problem solving skills using role modelling, coaching, discussion, encouragement,
and feedback. In addition, a number of Tip Sheets delivered between pregnancy and the child’s
second birthday focus on maternal personal and social well-being, including the mother’s rela-
tionship with the father, social support, support services available in the community, self-care,
exercise, and postnatal depression. For example, one Tip Sheet provides information on the
prevalence and symptoms of postnatal depression, while a Tip Sheet on self-care suggests that
mothers reward themselves by relaxing and doing something that makes them feel good.
The treatment group are also invited to participate in an additional parenting course (Triple
P Positive Parenting Program) [68] when their children are between 2 and 3 years old. Triple P
promotes healthy parenting practices and positive parent-child attachment. Meta-analysis of
Triple P has demonstrated positive effects for parenting practices and children’s social, emo-
tional, and behavioral outcomes [68]. The majority of treatment participants took part in
Group Triple P which consists of five 2-hour group discussion sessions and three individual
phone calls facilitated by the mentors.
Common supports. Both the treatment and control groups receive some common supports
including developmental materials and book packs. Both groups are also encouraged to attend
public health workshops on stress management and healthy eating which are already available to
the wider community, however relatively few members of either group attend these sessions. The
control group also has access to a support worker who can help them avail of community services
if needed, while this function is provided by the mentors for the treatment group.
Participants
Of the original 233 participants, 192 were eligible to participate in the well-being sub-study as
they had not voluntarily or involuntarily dropped out of the original study at the time of data
collection. 32 participants (treatment = 17; control = 15) voluntarily dropped out and a further
9 (treatment = 6; control = 3) involuntarily dropped out due to miscarriage, maternal death,
child death, or moved out of the catchment area at the time of data collection. Fig 1 depicts the
CONSORT diagram for participants in the original trial and the present sub-study. Mothers
were invited to take part in the sub-study by telephone, and a flyer was sent to those who could
not be reached. The study was described as “A Day in the Life of a Parent”, the goal of which
was to collect information on parents’ daily lives and to learn about the different emotions
parents experience during a typical day. Of the 192 target participants, 101 (treatment = 46;
control = 55) took part in the sub-study, 34 refused, 2 agreed but did not participate, and 54
could not be reached by telephone, text, or letter. Participants were at various stages in the pro-
gram when they participated in the sub-study; the youngest child was 24.6 months and the old-
est child was 62.5 months old. Thus, program duration differs for each participant as data
collection was conducted over a one year period.
In order to test for selection into the sub-study, we compare those who participated to those
who did not on 48 baseline measures of socio-demographics, health, parenting, and psychomet-
rics. Participants who chose to take part in the sub-study did not differ from those who did not
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on 96% of the baseline characteristics (46/48) using two-tailed tests with a 10% cut-off for signifi-
cance. Significant differences on 2 (4%) measures indicated that mothers in the sub-study were
more open (as per the Ten Item Personality Index (TIPI) [69]), and more likely to have their
activity impaired by illness. Importantly, there is no selection into the sub-study based on treat-
ment status as 46% of the treatment group participated in the sub-study and 54% of the control
Fig 1. CONSORT Flow Diagram.
doi:10.1371/journal.pone.0169829.g001
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group (p = 0.287). This suggests that there was no systematic selection into the sub-study based
on a wide range of observable characteristics.
S1 Table presents descriptive statistics on the participating sample for a selection of the
baseline variables disaggregated by treatment status. On average, mothers were between 25
and 26 years old and had one non-PFL child. Approximately half of participants were first
time mothers, over 55% lived in public housing, and approximately 40% had not completed
second level education and identified themselves as being unemployed. A significantly higher
proportion of treatment mothers had a boy as their PFL target child (48%) than control moth-
ers (31%).
An analysis examining differences between the treatment and control groups who partici-
pated in the sub-study found that the groups do not differ on 92% (44/48) of baseline mea-
sures. This suggests that the randomization assumption is still valid. Significant differences on
the 4 (8%) measures indicate that the treatment group were less likely to exercise, had lower
self-efficacy scores [(as per the Pearlin Self Efficacy Scale [70]) and emotional attachment
scores (as per the Vulnerable Attachment Style Questionnaire (VASQ) [71]), and were less
likely to know multiple neighbours compared to control participants.
Given the limited sample size, it is not optimal to control for all variables upon which the
two groups differ, therefore, the Bayesian Information Criterion (BIC) is used to determine
which covariates to include [72]. The BIC, which measures goodness of fit, is estimated for dif-
ferent combinations of baseline variables, while accounting for the number of variables included
in the model. A similar method is adopted in [24]. The set of variables which result in the lowest
BIC is infant gender, program duration, emotional attachment, number of neighbours known,
and exercise.
Data collection
The survey was piloted between November 2012 and January 2013 with a convenience sample
of parents (n = 5), PFL program staff (n = 7), and PFL pilot families (n = 5). Data collection
commenced 1
st
February 2013 and ended 30
th
November 2013 when the target sample was
exhausted. Participants were visited in their homes or a community centre by a researcher
who was blind to treatment assignment on two occasions over a three weekday period. On the
first day, participants were given diaries and asked to record the next day’s activities. On the
third day the survey was completed. Participants were given a 20 voucher as a thank you for
their participation. The survey (~50 minutes) consisted of: an adapted Day Reconstruction
Method (DRM) [3], mood yesterday questions, global questions of life satisfaction, and the
Parenting Stress Index (PSI) [73].
Instruments
Adapted day reconstruction method (DRM) [3]. The DRM was adapted for this study
based on the research question, literature review, and piloting. To assist with completion, par-
ticipants were asked to keep a diary of the study day which they could use during the survey as
a prompt to describe each of the day’s episodes in terms of the time it began and ended, the
type of activity they were participating in, where they were, and who they were interacting
with, either in person or on the phone. Participants were also asked to rate each episode in
terms of 12 affect states including 5 positive states (happy, affectionate, competent, relaxed, in
control), and 7 negative states (depressed, impatient, criticized, angry, frustrated, irritated,
stressed) on a 7-point Likert scale from not at all to very strongly. On average, episodes lasted
80 minutes, and participants recorded approximately 11 episodes per day, which is in line with
prior DRM research e.g., [59].
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The 12 individual affect states are examined separately across the entire day and are aver-
aged to create positive and negative affect scores. The difference between positive and negative
affect is also calculated to provide an overall measure of utility, known as net affect. All scores
are weighted by episode length, such that longer episodes contribute more towards a partici-
pant’s affect state than shorter episodes.
To overcome the potential issue of different participants interpreting the affect states in a
different manner, we also use the U-index to capture the proportion of time a participant
spends in an unpleasant state [42]. An episode is categorized as unpleasant if the highest rated
affect state is a negative one. Crucially, all participants need not view a certain scale point as
being precisely equivalent, they only need to have the same ranking of affect states. The
U-Index is also weighted by episode length. For all scores derived from the DRM, we compare
the treatment and control groups for the entire day and for subsets of episodes spent with and
without the PFL target child.
Measures of mood yesterday. To explore the utility of a less intensive proxy of experi-
enced affect, participants were asked to indicate the percentage of time they spent in a bad
mood, a little low or irritable, in a mildly pleasant mood, and in a very good mood in relation
to the day overall and in terms of the time they spent with their child(ren). The mood variable
is a continuous measure ranging from 0–100% indicating the proportion of time spent in a
good mood (mildly pleasant mood plus a very good mood).
Global life satisfaction. To assess participants’ global evaluations of their well-being, par-
ticipants were asked to indicate the degree to which they were satisfied with their “life as a
whole”, “life at home”, and their “life as a parent” on a 4-point Likert scale from very unsatis-
fied to very satisfied. Three binary variables (satisfied plus very satisfied versus unsatisfied plus
very unsatisfied) are created.
Parenting stress index short form (PSI) [73]. The PSI includes 36 items rated on a
5-point Likert scale ranging from strongly disagree to strongly agree. The scale yields a total
stress score (α= 0.90) and three subscale scores: Parental Distress (α= 0.90), Parent-Child
Dysfunctional Interaction (α= 0.90), and Difficult Child (α= 0.89). Responses are summed to
generate scores for each subscale and the Total Stress score. A binary variable is created to rep-
resent mothers scoring above a cut-off of 90, indicating a high level of stress. The PSI also con-
tains a measure of defensive responding [73] derived from the widely used Crowne-Marlowe
Social Desirability Scale. These questions pertain to routine parenting experiences, a denial of
which can be interpreted as defensive rather than accurate responding. A score of 10 or below
on this scale indicates defensive responding.
S2 Table presents the correlations between the various well-being measures and finds a
strong correlation among the measures derived from the DRM. The DRM measures are mod-
erately correlated with the measure of mood yesterday, yet only weakly correlated with the
global measure of life satisfaction and the PSI measures. These correlations suggest that the
global and experienced measures of well-being may represent different measures.
Data analytic Procedures
Empirical approach
This study adopts an intention-to-treat approach. The standard treatment effect framework
describes the observed outcome Y
i
of participant i 2I by:
Yi¼DiYið1Þ þ ð1DiÞYið0Þi2I¼ f1 . . . Ng ð1Þ
where I = {1 . . . N} denotes the sample space, D
i
denotes the treatment assignment for partici-
pant i (D
i
= 1 for the intention-to-treat sample, D
i
= 0 otherwise) and (Y
i
(0), Y
i
(1)) are
Day Reconstruction and Maternal Well-Being
PLOS ONE | DOI:10.1371/journal.pone.0169829 January 17, 2017 10 / 25
potential outcomes for participant i. We test the null hypothesis of no treatment effect on
maternal well-being via:
Yi¼b0þb1Diþið2Þ
Eq 2 is estimated using t-tests/OLS regressions for continuous outcomes and chi-squared
tests/logistic regressions for binary outcomes, both excluding and including relevant group
differences. Permutation-based hypothesis testing is also used as it does not depend on distri-
butional assumptions and thus facilitates the estimation of treatment effects in small samples
[74]. A permutation test relies on the assumption of exchangeability under the null hypothesis.
Permutation tests work by calculating the observed test statistic which compares the outcomes
of the treatment and control group. Then, the data are repeatedly shuffled so that the treatment
assignment of some participants is switched between the groups. The p-value for the permuta-
tion test is the proportion of permutations that have a test statistic more extreme than the
observed test statistic in the original sample. Permutation tests based on 100,000 replications
are computed.
The permutation procedure relies on the exchangeability properties of the joint distribution
of outcomes and treatment assignment. When the exchangeability property is not obvious, e.g.
the two groups differ on certain characteristics, a conditional inference that relies on restricted
classes of permutations can be implemented. This procedure uses the conditional exchange-
ability property and tests for program effects while controlling for variables upon which the
joint distribution of outcomes and treatment assignment is exchangeable. Conditional permuta-
tion testing first partitions the sample into subsets, termed orbits, each consisting of participants
with common background measures. Under the null hypothesis of no treatment effect, treat-
ment and control outcomes have the same distributions within an orbit. Thus, the exchange-
ability assumption is restricted to strata defined by the controls. In our conditional analysis we
include the six control variables identified using the BIC procedure. One binary variable is used
to produce the orbits: child gender. However, using orbits proves problematic with multiple
conditioning variables as the strata become too small leading to a lack of variation within each
orbit. To circumvent this problem we assume a linear relationship between the remaining five
conditioning variables and the outcomes. The control set includes program duration, emotional
attachment score, number of neighbours known, and exercise. Thus, we partition the data into
orbits on the basis of the child’s gender and then regress each outcome on the five variables
assumed to share a linear relationship with the outcomes. Next, the residuals are permuted,
based on 100,000 replications, from this regression within the orbits. This method is referred to
as the Freedman–Lane procedure [75] and was found to be statistically sound in a series of
Monte Carlo studies [76]. The results below include both conditional and unconditional per-
mutation testing.
Additional analysis
Analysing the impact of the program on multiple well-being measures increases the likelihood
of a Type-1 error and studies of RCTs have been criticized for overstating treatment effects
due to this ‘multiplicity’ effect [77]. To address this issue we employ the stepdown procedure
[78] whereby we calculate a t-statistic for each null hypothesis in a family of outcomes and
placing them in descending order. The outcome measures included in each family should be
correlated and measure a similar construct. Thus, the well-being measures are placed into 14
stepdown families and the procedure is conducted only on the families where significant dif-
ferences are identified in the individual tests. Using the permutation testing method, the larg-
est observed t-statistic is compared with the distribution of maxima permuted t-statistics. If
Day Reconstruction and Maternal Well-Being
PLOS ONE | DOI:10.1371/journal.pone.0169829 January 17, 2017 11 / 25
the probability of observing this statistic by chance is high (p 0.1), we fail to reject the joint
null hypothesis that the treatment has no impact on any outcome in the family of measures
being tested. If the probability of observing this t-statistic is low (p <0.1), we reject the joint
null hypothesis and proceed by excluding the most significant individual hypothesis and test
the subset of hypotheses that remain for joint significance. This process of dropping the most
significant individual hypothesis continues until only one hypothesis remains. ‘Stepping
down’ through the hypotheses allows us to isolate the hypotheses that lead to a rejection of the
null. This method is superior to Bonferroni adjustment as it accounts for interdependence
across outcomes.
In addition to examining differences in well-being, we also explore patterns of time use
across the treatment and control groups regarding interactions (with the PFL target child, the
participant’s partner, and other family members), locations (home and workplace), and activi-
ties (looking after and playing with children, relaxing/socializing, housework/cooking, exercis-
ing and commuting).
We apply two-tailed tests for all analyses as we are not proposing a specific directional
hypothesis regarding the program’s impact on well-being.
Results
Descriptive statistics on affect measures
For each episode, participants report a score for a range of affect states which are classified as
positive or negative. To generate descriptive statistics, the positive and negative affect values
are standardized for the entire sample to have a zero mean and a standard deviation of one.
Every episode recorded is assigned an hour corresponding to the midpoint of the episode. For
each midpoint hour from 08:00 to 22:00, the average positive and negative affect is calculated
separately for the treatment and control groups. Fig 2 illustrates the pattern of average positive
affect over the course of the study day and shows that the treatment group report higher posi-
tive affect scores at every hour, compared to the control group.
Conversely, Fig 3 indicates that there is no clear difference in negative affect between the
two groups. Both the treatment and control groups display a similar pattern of mid-morning
and mid-afternoon peaks in negative affect, followed by an evening decline as is typical (e.g.
[59;79]).
Fig 2. Standardized average positive affect for treatment and control groups.
doi:10.1371/journal.pone.0169829.g002
Day Reconstruction and Maternal Well-Being
PLOS ONE | DOI:10.1371/journal.pone.0169829 January 17, 2017 12 / 25
Estimation of treatment effects
Tables 14present estimates of treatment effects for experienced and global measures of
maternal well-being. The unconditional means and standard deviations are reported through-
out. Four columns of p-values are presented in each table representing the statistical signifi-
cance of the treatment effect from an unconditional t-test/chi-squared test, an unconditional
permutation test, a conditional t-test/chi-squared test, and a conditional permutation test,
respectively. Given the few observed differences between the treatment and control groups at
baseline, the conditional results represent the most reliable set of findings. Overall, the t-tests
and the permutation tests produce very similar results.
Table 1 compares the treatment and control groups in terms of their mood yesterday, net
affect, and U-Index for the day as a whole and also for time spent with and without the PFL
child. Both groups report spending approximately three-quarters of the study day in a positive
mood. This increases to four-fifths during episodes spent with children. The treatment group
reports spending a significantly higher proportion of their day in a positive mood, relative to
the control group, yet this difference is only significant in the conditional models.
In terms of the DRM measures, on average, participants in both groups report a net affect
score of approximately 3 which implies that participants experience positive emotions three
points more intensively on the 0–6 Likert scale than negative emotions. Both groups spend
approximately 10% of their day in an episode where the strongest emotion is a negative one, as
shown by the U-Index. Both groups experience a slight decline in net affect and a correspond-
ing slight rise in the U-Index in episodes when they are without their PFL child. No significant
treatment effects are identified for the net affect or U-Index measures.
Table 2 compares the treatment and control groups in terms of their overall positive affect
and individual positive affect states for the day as a whole and also time spent with and without
the PFL child. Feelings of competence and control receive the highest ratings, while feeling
relaxed receives the lowest. This pattern differs depending on whether participants were with/
without their PFL child, with participants reporting substantially higher levels of affection dur-
ing episodes with the PFL child. A treatment effect is identified in the unconditional models
for overall positive affect for episodes spent without the PFL child. In the conditional models,
the p-values are slightly larger and not statistical significant at conventional levels.
Fig 3. Standardized average negative affect for treatment and control groups.
doi:10.1371/journal.pone.0169829.g003
Day Reconstruction and Maternal Well-Being
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For individual positive affect states, we find that treatment participants report significantly
higher levels of happiness for the day overall and during times spent without the PFL child in
the unconditional and conditional models. In all models, apart from the conditional permuta-
tion model, the treatment group also report higher levels of happiness during times spent with
the PFL child. In the conditional permutation model, the treatment group are significantly
more relaxed during episodes without their child. The groups do not significantly differ on the
remaining positive affect states.
Tests comparing positive affect states when with and without the PFL target child (not
reported) show that participants from both groups are significantly less affectionate during
episodes without their PFL child, yet the control group experience a larger decline. Addition-
ally, control group participants feel significantly less in control when they are without their
PFL child, while treatment participants are significantly more relaxed when without their PFL
child.
Table 3 compares the treatment and control groups in terms of their negative affect and
individual negative affect states for the entire day and for time spent with and without their
PFL child. No significant treatment effects are identified. Both treatment and control partici-
pants tend to give the highest ratings to feeling stressed and impatient, with depressed and crit-
icised receiving the lowest ratings. Overall, ratings of negative affect states seem to be slightly
less intense when participants were not with their PFL child, although none of these differ-
ences are significant for either group (not reported).
Table 4 presents the results for the global measures of life satisfaction and the standardized
measure of parenting stress. In terms of life satisfaction, the majority of participants in both
groups report that they are satisfied with their life overall, as a parent, and at home. A slightly
higher proportion of treatment participants than control participants report that they are satis-
fied across all three categories, however none of these differences are statistically significant.
Table 1. Treatment Effects for Experienced Well-being: Mood Yesterday, Net Affect and U-Index.
M
TREATMENT
(SD)M
CONTROL
(SD)p
a
p
b
p
a
p
b
Unconditional Conditional
Mood Yesterday
Portion of day spent in a positive mood 0.76 (0.18) 0.71 (0.25) 0.321 0.308 0.047** 0.035**
Portion of day spent with children in a positive mood 0.83 (0.21) 0.84 (0.19) 0.821 0.827 0.783 0.673
Net Affect
Net Affect 3.03 (1.41) 2.84 (1.37) 0.511 0.512 0.329 0.269
Net affect during time spent with PFL child 2.98 (1.58) 2.95 (1.38) 0.916 0.917 0.603 0.637
Net affect during time spent without PFL child 3.00 (1.78) 2.68 (1.59) 0.353 0.356 0.355 0.188
U-Index
U-Index 0.10 (0.14) 0.09 (0.18) 0.686 0.689 0.777 0.315
U-Index during time spent with PFL child 0.10 (0.16) 0.08 (0.18) 0.453 0.461 0.703 0.758
U-Index during time spent without PFL child 0.11 (0.24) 0.12 (0.27) 0.874 0.875 0.907 0.235
Notes: The sample size is 101 (Treatment = 46, Control = 55), except when we restrict the analysis to time spend without the PFL child as 5 control
participants did not record any episodes without their PFL child, therefore n = 96 (Treatment = 46, Control = 50), and apart from Mood Yesterday
(Treatment = 45, Control = 55). ‘M’ indicates the unconditional mean. ‘SD’ indicates the unconditional standard deviation.
a
two-tailed t-test p-value.
b
two-tailed p-value from an individual permutation test with 100,000 replications.
*** Significant at the 1 percent level.
** Significant at the 5 percent level.
*Significant at the 10 percent level.
doi:10.1371/journal.pone.0169829.t001
Day Reconstruction and Maternal Well-Being
PLOS ONE | DOI:10.1371/journal.pone.0169829 January 17, 2017 14 / 25
Note that only 9 participants across both groups report being either unsatisfied or very unsatis-
fied with their life overall, thus the small cell size should be noted when interpreting the results.
In addition, when ordered logit models are calculated using the original 4-point scale, there is
a statistical significance difference between the treatment and control group regarding satisfac-
tion with life as a parent in the unconditional and conditional models.
The treatment and control groups report comparable levels of parenting stress (PSI),
and approximately 10% report clinically significant levels. There are no significant treat-
ment effects for any of the PSI scores. In addition, 24% of the treatment group and 27% of
the control group meet the cut off for defensive responding suggesting that these partici-
pants may be positively biasing their responses based on their perception of socially desir-
able parenting experiences. Importantly, however, there are no significant differences
between the groups in terms of defensive responding, suggesting no evidence of systematic
mis-reporting.
Table 2. Treatment Effects for Experienced Well-being: Positive Affect.
M
TREATMENT
(SD)M
CONTROL
(SD)p
a
p
b
p
a
p
b
Unconditional Conditional
Overall
Positive affect 3.94 (0.96) 3.66 (0.95) 0.151 0.150 0.214 0.188
Positive affect during time spent with PFL Child 3.97 (1.02) 3.77 (1.00) 0.336 0.336 0.373 0.414
Positive affect during time spent without PFL child 3.84 (1.13) 3.48 (0.92) 0.088*0.090*0.184 0.122
Positive affect states
Happy 4.03 (1.00) 3.59 (1.12) 0.043** 0.041** 0.064*0.044**
Affectionate 3.75 (1.49) 3.43 (1.38) 0.271 0.273 0.530 0.430
Competent 4.40 (1.04) 4.18 (1.12) 0.324 0.320 0.402 0.408
In Control 4.25 (1.16) 4.04 (1.19) 0.379 0.378 0.432 0.444
Relaxed 3.24 (1.16) 3.04 (1.16) 0.410 0.409 0.322 0.302
Positive affect states during time spent with PFL child
Happy 3.99 (1.22) 3.59 (1.17) 0.094*0.096*0.091*0.108
Affectionate 4.25 (1.42) 3.98 (1.40) 0.340 0.341 0.562 0.588
Competent 4.34 (1.09) 4.13 (1.22) 0.358 0.353 0.393 0.412
In Control 4.25 (1.20) 4.13 (1.17) 0.607 0.607 0.756 0.761
Relaxed 2.94 (1.34) 3.00 (1.21) 0.834 0.836 0.910 0.960
Positive affect states during time spent without PFL child
Happy 3.98 (1.07) 3.50 (1.25) 0.045** 0.045** 0.074*0.038*
Affectionate 3.08 (1.89) 2.57 (1.59) 0.159 0.162 0.450 0.293
Competent 4.31 (1.40) 4.16 (1.15) 0.550 0.553 0.675 0.640
In Control 4.17 (1.44) 4.00 (1.29) 0.522 0.522 0.599 0.547
Relaxed 3.67 (1.59) 3.18 (1.27) 0.100 0.103 0.120 0.094*
Notes: The sample size is 101 (Treatment = 46, Control = 55), except when we restrict the analysis to time spend without the PFL child as 5 control
participants did not record any episodes without their PFL child, therefore n = 96 (Treatment = 46, Control = 50). ‘M’ indicates the unconditional mean. ‘SD’
indicates the unconditional standard deviation.
a
two-tailed t-test p-value.
b
two-tailed p-value from an individual permutation test with 100,000 replications.
*** Significant at the 1 percent level.
** Significant at the 5 percent level.
*Significant at the 10 percent level.
doi:10.1371/journal.pone.0169829.t002
Day Reconstruction and Maternal Well-Being
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Additional analysis
Stepdown analysis. Table 5 presents the unconditional and conditional stepdown results
for the measures upon which we identified significant differences in the individual tests. The
first p-value in the conditional mood yesterday stepdown family is significant following adjust-
ment for multiple comparisons, and is driven by the significant finding for the portion of day
spent in a positive mood. In contrast, the stepdown families for positive affect states for the
day as a whole or for episodes with and without their PFL child are not significant when the
unconditional and conditional stepdown procedure is applied.
Table 3. Treatment Effects for Experienced Well-being: Negative Affect.
M
TREATMENT
(SD)M
CONTROL
(SD)p
a
p
b
p
a
p
b
Unconditional Conditional
Overall
Negative affect 0.91 (0.79) 0.82 (0.76) 0.547 0.551 0.852 0.894
Negative affect during time spent with PFL child 0.98 (0.88) 0.82 (0.73) 0.309 0.323 0.852 0.658
Negative affect during time spent without PFL child 0.84 (0.97) 0.80 (0.92) 0.831 0.833 0.857 0.671
Negative affect states
Stressed 1.47 (1.25) 1.24 (1.08) 0.320 0.329 0.932 0.864
Irritated 1.29 (1.12) 1.08 (1.05) 0.338 0.343 0.734 0.805
Frustrated 1.26 (1.02) 1.10 (1.00) 0.422 0.426 0.866 0.812
Angry 0.66 (0.84) 0.55 (0.84) 0.504 0.510 0.826 0.972
Impatient 1.27 (1.15) 1.32 (1.02) 0.829 0.830 0.590 0.583
Depressed 0.23 (0.37) 0.28 (0.50) 0.627 0.622 0.177 0.196
Criticized 0.18 (0.40) 0.16 (0.36) 0.781 0.786 0.444 0.526
Negative affect states during time spent with PFL child
Stressed 1.61 (1.45) 1.25 (1.08) 0.155 0.167 0.570 0.438
Irritated 1.36 (1.22) 1.04 (0.98) 0.153 0.164 0.293 0.311
Frustrated 1.37 (1.19) 1.11 (1.00) 0.233 0.245 0.601 0.447
Angry 0.66 (0.87) 0.56 (0.85) 0.584 0.593 0.717 0.987
Impatient 1.43 (1.26) 1.36 (1.09) 0.783 0.787 0.854 0.910
Depressed 0.24 (0.53) 0.24 (0.49) 0.989 0.990 0.229 0.421
Criticised 0.22 (0.49) 0.17 (0.39) 0.600 0.611 0.529 0.712
Negative affect states during time spent without PFL child
Stressed 1.36 (1.61) 1.23 (1.31) 0.672 0.674 0.746 0.644
Irritated 1.16 (1.38) 1.03 (1.33) 0.634 0.636 0.977 0.836
Frustrated 1.10 (1.31) 1.07 (1.29) 0.895 0.896 0.827 0.671
Angry 0.70 (1.21) 0.58 (1.15) 0.620 0.625 0.945 0.993
Impatient 1.15 (1.46) 1.12 (1.29) 0.932 0.934 0.801 0.895
Depressed 0.26 (0.57) 0.44 (0.91) 0.255 0.256 0.244 0.176
Criticised 0.14 (0.58) 0.13 (0.34) 0.922 0.929 0.871 0.728
Notes: The sample size is 101 (Treatment = 46, Control = 55), except when we the restrict analysis to time spend without the PFL child as 5 control
participants did not record any episodes without their PFL child, therefore n = 96 (Treatment = 46, Control = 50). ‘M’ indicates the unconditional mean. ‘SD’
indicates the unconditional standard deviation.
a
two-tailed t-test p-value
b
two-tailed p-value from an individual permutation test with 100,000 replications.
*** Significant at the 1 percent level.
** Significant at the 5 percent level.
*Significant at the 10 percent level.
doi:10.1371/journal.pone.0169829.t003
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Time use. The few observed treatment effects may be driven by differences in time use
across the two groups. Yet, as shown in Table 6, the treatment group spend approximately the
same proportion of episodes with their PFL child (62%) as do the control group (66%). In
addition, there are no differences regarding the proportion of episodes spent caring for or
playing with their children. The conditional results show that the treatment group are signifi-
cantly more likely to spend an episode with their relatives and a higher proportion of their epi-
sodes in work, yet less than 6% of all episodes are spent at work. There are also no differences
in terms of daily activities (relaxing/socializing, housework/cooking, commuting, exercising).
Discussion
It has been proposed that aggregated measures of experienced affect can be utilized as a mea-
sure of policy effectiveness [3] and that such measures replace traditional quality of life ques-
tions in health care evaluations [80]. Yet, to date, no study has attempted to integrate these
insights into a formal policy evaluation. This paper examines the utility effects of a targeted
early intervention program using multiple measures of well-being. In sum, we find limited evi-
dence that the PFL intervention affects global measures of maternal well-being. However, the
intervention does generate higher levels of experienced positive affect using a Day Reconstruc-
tion Method. Specifically, participants in the treatment group experience higher levels of hap-
piness for the day overall and when they are with and without the PFL child. Participants also
report feeling more relaxed during episodes without the PFL child, yet these results do not sur-
vive the stepdown procedure. These results are consistent with the findings for positive mood
yesterday, where we observe significant treatment effects in the individual and stepdown
results, yet not during times spent with children. There are no treatment effects for negative
aspects of well-being irrespective of the measure used. Lastly, although higher proportions of
Table 4. Treatment Effects for Global Well-being: Life Satisfaction and Parenting Stress Index.
N (n
TREATMENT
/ n
CONTROL)
M
TREATMENT
(SD)M
CONTROL
(SD)p
a
p
b
p
a
p
b
Unconditional Conditional
Life Satisfaction
Satisfaction with Life as a Parent 100 (45/55) 0.98 (0.15) 0.89 (0.31) 0.126 0.118 0.190 0.160
Satisfaction with Home Life 100 (45/55) 0.96 (0.21) 0.89 (0.31) 0.251 0.234 0.303 0.319
Satisfaction with Life Overall 100 (45/55) 0.93 (0.25) 0.89 (0.31) 0.465 0.477 0.650 0.704
PSI subdomains
Parent-Child Dysfunctional Interactions 99 (45/54) 18.04 (5.44) 17.22 (5.40) 0.402 0.456 0.855 0.735
Difficult Child 94 (43/51) 22.42 (8.34) 22.18 (7.03) 0.944 0.881 0.605 0.697
Parental Distress 100 (45/55) 24.82 (8.39) 24.67 (8.50) 0.907 0.932 0.661 0.548
Total Parental Stress 93 (42/51) 64.52 (18.17) 64.02 (17.95) 0.888 0.894 0.641 0.646
Stress Cut-off 93 (42/51) 0.10 (0.30) 0.08 (0.27) 0.752 0.827 0.601 0.900
Defensive Responding 93 (42/51) 14.76 (5.24) 14.64 (5.05) 0.967 0.972 0.621 0.518
Defensive Responding Cut-off 93 (42/51) 0.24 (0.43) 0.27 (0.45) 0.731 0.694 0.980 0.945
Notes:N’ indicates the sample size. ‘M’ indicates the unconditional mean. ‘SD’ indicates the unconditional standard deviation.
a
two-tailed t-test p-value
b
two-tailed p-value from an individual permutation test with 100,000 replications.
*** Significant at the 1 percent level.
** Significant at the 5 percent level.
*Significant at the 10 percent level.
doi:10.1371/journal.pone.0169829.t004
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the treatment group report being satisfied with their lives, these differences did not reach
significance.
The lack of treatment effects on negative measures of well-being is broadly in keeping with
the HVP literature. Systematic reviews have found that home visiting is typically not effective
in ameliorating negative emotional states [29,35]. Thus our findings are consistent with the
view that targeted and intensive therapeutic supplements are needed in order for HVPs to alle-
viate negative states such as depression [35]. Notwithstanding this, our findings demonstrate
that a HVP may have an impact on some dimensions of positive affect, which questions the
prevailing assumption, based predominantly on deficit measures of well-being, that HVPs do
not influence parents’ emotional states [39].
While there are no differences in the amount of time participants spend with their children
in either group, the results suggest that the higher positive affect experienced by the treatment
group may be driven by differences in the quality of the episodes rather than the quantity of
episodes. Indeed the intervention aims to improve the quality and type of parent-child interac-
tions rather than the amount of time spent with the child. For example, many of the Tip Sheets
discuss the importance of reading to your child, talking to your child, and creating a secure
base. It is also possible that gains to maternal well-being, and happiness in particular, are
accrued indirectly, via the program’s identified impact on the children’s cognitive, emotional,
and physical health [5,6]. However, directionality may be obscured due to the dynamic and
bidirectional interplay between child and maternal well-being [81].
The PFL intervention aims to heighten parents’ awareness of being actively engaged when
interacting with their child. If such investment confers an increased effort on the parents,
treatment mothers may particularly value times when they are not actively being a parent. This
lends some supports to the finding that the treatment group feel more relaxed than the control
group when without the PFL child. It is also possible that, through Tip Sheets and mentor sup-
port, the mothers are encouraged to use their non-parenting time for self-care, relaxation, and
social relationships. These supports may result in positive emotional experiences as rich social
relationships are integral to optimizing happiness [13], and socializing and relaxing typically
receive the highest ratings of experienced positive affect on the DRM [3]. While there are no
Table 5. Stepdown Results.
Stepdown Test p
a
Stepdown Test p
b
Mood Yesterday
Portion of Day Spent in a Positive Mood ~ 0.066*
Positive affect states
Happy 0.138 0.146
Positive affect states during time spent with PFL child
Happy 0.294 ~
Positive affect states during time spent without PFL child
Happy 0.162 0.133
Relaxed ~ 0.279
Notes
a
two-tailed p-value from an unconditional stepdown permutation test with 100,000 replications.
b
two-tailed p-value from a conditional stepdown permutation test with 100,000 replications.
*** Significant at the 1 percent level.
** Significant at the 5 percent level.
*Significant at the 10 percent level.
doi:10.1371/journal.pone.0169829.t005
Day Reconstruction and Maternal Well-Being
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differences in time use between the two groups, it is possible that the quality of these non-par-
enting experiences differ in some unobserved way.
Another key question concerns the intervention’s effect on experienced positive affect and
assessments of yesterday’s mood, but not the global assessments of well-being such as life satis-
faction. It is possible that the DRM provides a more sensitive measure of well-being which
avoids the cognitive biases that impinge upon global assessments of life satisfaction. Such
biases may operate less intensively on measures of yesterday’s mood [62]. Another hypothesis
is that global and experienced well-being are independent constructs, as reflected in the recent
conceptual shift which recognizes experienced well-being and global well-being as distinct psy-
chological phenomena [61]. Applied to our study, the absence of treatment effects for global
well-being may be counterintuitive, if we believe that the life satisfaction question should have
encouraged participants to focus on their participation in the program, its association with
greater parenting competency, and anticipation of future benefits. Indeed, one study has
found that while spending time with children was not highly pleasurable, it was thought of as
rewarding [82]. Thus, the authors postulate that parenting may have a more positive influence
on global aspects of well-being by providing individuals with a sense of purpose, connection,
and contribution to personal goals. Interestingly, one other study has found that the cost of
parenthood—in this case monetary—appears to motivate parents to idealize global judgements
of how rewarding parenting is [83]. It is also possible that participants habituate quickly to
their circumstances [84]—in this case treatment status—and thus the effects on global well-
being may have dissipated over time as, on average, the participants have spent four years in
the program.
Given the absence of experimental studies examining the causal impact of policy interven-
tions on experienced well-being, it is difficult to give precise comparisons to the magnitude of
Table 6. Time Use Amongst Treatment and Control Groups.
%
TREATMENT
%
CONTROL
Unconditional p
a
Conditional p
b
Interaction
With PFL child 61.89 66.28 0.125 0.214
With partner 16.70 22.09 0.019** 0.244
With relatives 22.99 16.45 0.008*** 0.026**
Alone 9.49 10.89 0.445 0.217
Location
At home 66.60 64.95 0.564 0.554
At work 5.89 3.16 0.029** 0.045**
Activities
Looking after children 44.20 46.84 0.399 0.369
Playing with children 8.84 8.97 0.962 0.658
Relaxing/socializing 24.95 25.42 0.881 0.927
Housework/cooking 26.92 29.40 0.376 0.685
Commuting 12.77 13.95 0.540 0.598
Exercising 1.57 2.16 0.501 0.370
Notes: Unconditional percentages are reported.
a
two-tailed p-value from an individual unconditional permutation test with 100,000 replications.
b
two-tailed p-value from an individual conditional permutation test with 100,000 replications.
*** Significant at the 1 percent level.
** Significant at the 5 percent level.
*Significant at the 10 percent level.
doi:10.1371/journal.pone.0169829.t006
Day Reconstruction and Maternal Well-Being
PLOS ONE | DOI:10.1371/journal.pone.0169829 January 17, 2017 19 / 25
our results. Comparing our happiness effect (0.42 points more than average well-being) to the
well-being effects observed in the original non-experimental DRM study [3], we identify a sim-
ilar magnitude to the effect of commuting (.49 points less than average well-being) and being
alone (.48 points less than average). In addition, the treatment participants’ average levels of
happiness for times when they are without the study child (3.98), are very similar to those
reported in the original DRM sample of employed women (3.96) [79]. This suggests that the
treatment may raise the levels of well-being of a disadvantaged group closer to those that are
typical of the population.
While this study is the first to our knowledge to test for the causal impact of a policy
intervention on multiple measures of well-being, some methodological issues should be
acknowledged. The study relies on self-report measures which may be contaminated by
social desirability bias when participants are not blinded to their treatment status. How-
ever, we demonstrate that there are no systematic differences in social desirability between
the treatment and control groups according to the defensive responding validity measure
embedded within the PSI. An additional issue which is common in many trials is small
sample size. This issue is a particular concern in the present study as the sample in the sub-
study is smaller than in the original PFL trial. Yet we find that few individual characteristics
predict selection into the sub-study, and the randomization assumption of baseline equiva-
lence still holds in the reduced sample. In addition, the sample size is equivalent to seminal
studies of other early intervention programs, such as the Perry Preschool program and the
Abecedarian program. A discussion on the use of small samples in experimental trials may
be found in [10] and [24]. The permutation testing method also helps to address this issue.
A further concern is the risk of overstating the program’s impact due to multiple hypothe-
sis testing. We address this issue using the stepdown procedure and highlight the signifi-
cance of failing to account for this issue. The stepdown analysis shows that only the result
for mood yesterday remains significant after adjustment.
If the identified treatment effect for experienced positive mood is valid, this may confer
meaningful benefits for mothers. Evidence suggests that positive emotions create an upward
positive spiral in emotional well-being by enhancing an individual’s cognitive coping strategies
[85]. Over time a causal relationship may develop between positive affect and behaviors linked
to successful outcomes such as higher quality relationships, superior income and productivity,
greater community participation, and improved health and mortality [86,87]. Thus, the treat-
ment effect identified here may have important implications for the cost-benefit analysis of the
PFL program and similar HVPs in the future. A full cost-benefit analysis of the program will
be conducted when the final outcome data are available. Note that the majority of cost savings
(if realised) are likely to be derived from improvements in child outcomes than improvements
in parental well-being.
Using RCTs to examine the well-being effects of policy interventions is a growing area. Our
findings demonstrate the importance of measurement and conceptualization of well-being
and of inferential techniques. Further research is needed to reconcile differences on global ver-
sus experienced measures of well-being and on positive and negative affect. These issues are
important across many domains, including labor market and health interventions, where
there is also likely to be a psychic benefit of successful program outcomes on top of the core
measures being targeted.
Supporting Information
S1 Data.
(XLS)
Day Reconstruction and Maternal Well-Being
PLOS ONE | DOI:10.1371/journal.pone.0169829 January 17, 2017 20 / 25
S1 Protocol.
(DOC)
S2 Protocol.
(DOC)
S1 Table.
(DOCX)
S2 Table.
(DOCX)
Acknowledgments
We would like to thank all those who supported this research including the participating fami-
lies, the PFL intervention staff, project coordinator Judy Lovett, data collection Catherine
O’Melia, and the UCD Geary Institute Early Childhood Research Team. Comments from par-
ticipants at the “European Economic Association Mannheim 2015” conference, the “Measure-
ment and Determinants of Well-being” workshop at the University of Stirling, the “Society for
Research in Child Development, Developmental Methodology Meeting, San Diego”, and UCD
School of Economics seminar participants are gratefully acknowledged.
Author Contributions
Conceptualization: OD LD.
Data curation: NF.
Formal analysis: NF.
Funding acquisition: OD.
Investigation: COF.
Methodology: OD LD MD COF.
Project administration: OD COF.
Resources: OD LM MD.
Software: NF.
Supervision: OD.
Validation: OD.
Visualization: OD NF.
Writing – original draft: OD COF LD MD.
Writing – review & editing: OD LD COF NF MD.
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... Rights reserved. Letourneau et al., 2011;Berkule et al., 2014;Homem et al., 2015;Chang et al., 2015;Doyle et al., 2017;Boyd et al., 2019). Recruitment methods included consecutive invitation to potentially qualifying participants at hospitals and clinics or health centers (Bayer et al., 2010;Berkule et al., 2014;Chang et al., 2015), distribution of information via the usual media channels (Boyd et al., 2019;Connell et al., 1997;Doyle et al., 2017;Farris et al., 2013;Gross et al., 1995;Letourneau et al., 2011;Niccols, 2009) and from a larger parent study (Homem, et al., 2015). ...
... Letourneau et al., 2011;Berkule et al., 2014;Homem et al., 2015;Chang et al., 2015;Doyle et al., 2017;Boyd et al., 2019). Recruitment methods included consecutive invitation to potentially qualifying participants at hospitals and clinics or health centers (Bayer et al., 2010;Berkule et al., 2014;Chang et al., 2015), distribution of information via the usual media channels (Boyd et al., 2019;Connell et al., 1997;Doyle et al., 2017;Farris et al., 2013;Gross et al., 1995;Letourneau et al., 2011;Niccols, 2009) and from a larger parent study (Homem, et al., 2015). The duration of follow up ranged from 2 months (Boyd et al., 2019) to 5 years (Doyle et al., 2017). ...
... Recruitment methods included consecutive invitation to potentially qualifying participants at hospitals and clinics or health centers (Bayer et al., 2010;Berkule et al., 2014;Chang et al., 2015), distribution of information via the usual media channels (Boyd et al., 2019;Connell et al., 1997;Doyle et al., 2017;Farris et al., 2013;Gross et al., 1995;Letourneau et al., 2011;Niccols, 2009) and from a larger parent study (Homem, et al., 2015). The duration of follow up ranged from 2 months (Boyd et al., 2019) to 5 years (Doyle et al., 2017). After removing the outlier of 5 years, the mean duration of follow up was 7.5 months with a mode of 3 months. ...
Full-text available
Article
Purpose Perinatal mood and anxiety disorders can have far reaching negative impact on both maternal mental health and child growth and development. Multimodal group parenting programs have been shown to improve maternal mental health symptoms however, they are often costly to provide and not accessible to many mothers, especially those mothers suffering from mental health symptoms. Therefore, the authors sought to answer the following question by undertaking a systematic review of the literature: are parenting interventions aimed at improving maternal-child interaction also a way to address mental health symptoms (i.e. depression, anxiety, stress) in mothers? Methods The Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines were followed. An online platform that supports the systematic review process and quality assessment according to Cochrane guidelines, Covidence, was used in conjunction with an adapted extraction tool to identify relevant studies and extract data for analysis. Results 11 articles were included in the qualitative synthesis. There was great heterogeneity between study interventions and measurement of outcomes for maternal mental health symptoms which precluded meta-analysis. Conclusion Studies reviewed did not demonstrate consistent evidence to recommend that parenting interventions leads to improvement in maternal mental health symptoms for depression, anxiety or stress. However, there was evidence that participating in parenting programs does not worsen these symptoms and some encouraging evidence that alternative delivery methods, beyond face to face, could, with more research, lead to more financially feasible and sustainable models of delivery of these types of interventions in the future.
... Several recent programs to increase parental awareness of the importance of parenting skills have been directed towards fragile families. Research evaluating these programs shows that they have raised parental awareness, parenting skills and children's cognitive and socioemotional outcomes (Doyle et al. 2017, Doyle 2020, Wagner and Clayton 1999, Daly et al. 2014. ...
... Also unclear are the benefits for parents, e.g. reduction in parenting stress (Doyle et al., 2017;Hutchings et al., 2016) as well as if effects in parent outcomes lead to improvements for child development (Hurt et al., 2018). ...
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Abstract Background Many prevention programmes for families focus parental adversities and adverse childhood experiences. Effects of such programmes are often examined in clinical trials; there is less research on effects under naturalistic conditions. The aim of this study was to examine the longitudinal association between parenting stress and child's negative emotionality, its modification through targeted prevention programmes, and to investigate the effects in the general population. Methods Data were taken from a sample of n = 903 families with infants (mean age: 13.3 months) who participated in a baseline study (T1) and a follow-up study (T2) 2 years later. The survey included parental self-report measurements on parenting stress and child's negative emotionality (T1 and T2 each) and targeted prevention programmes (T1 only). An autoregressive cross-lagged panel design was used to analyse the association of parenting stress and the child's negative emotionality, including use of targeted prevention programmes as moderator. We also tested if targeted prevention programmes can reduce parenting stress or child's negative emotionality using Propensity Score Matching (PSM). Results Parenting stress at T1 affected children's negative emotionality at T2, but children's negative emotionality at T1 did not affect parenting stress at T2. When targeted prevention was included as moderator, the correlation disappeared among programme users. With PSM, there was no direct effect on parenting stress or child's negative emotionality. But a subsample of parents with high parenting stress at T1 who used targeted prevention at T1 reported less child's negative emotionality problems at T2 than parents who scored high in parenting stress but did not receive targeted prevention at T1. Conclusion Results suggest that the spillover from parenting stress to child's negative emotionality may be modified by prevention. Prevention programmes may help to build resources and have a direct positive effect on the child, especially for parents with high parenting stress.
... Also unclear are the benefits for parents, e.g. reduction in parenting stress (Doyle et al., 2017;Hutchings et al., 2016) as well as if effects in parent outcomes lead to improvements for child development (Hurt et al., 2018). ...
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Background: Many prevention programs for families focus parental adversities and adverse childhood experiences. Effects of such programs are often examined in clinical trials; there is less research on effects under naturalistic conditions. The aim of this study was to examine the longitudinal association between parenting stress and child's negative emotionality, its modification through targeted prevention programs and to investigate the effects in the general population. Methods: Data were taken from a sample of n=903 families with infants (mean age: 13.3 months) who participated in a baseline study (T1) and a follow-up study (T2) two years later. The survey included parental self-report measurements on parenting stress and child's negative emotionality (T1 and T2 each), and targeted prevention programs (T1 only). An autoregressive cross-lagged panel design was used to analyze the association of parenting stress and the child's negative emotionality, including use of targeted prevention programs as moderator. We also tested if targeted prevention programs can reduce parenting stress or child's negative emotionality using Propensity Score Matching (PSM). Results: Parenting stress at T1 affected children's negative emotionality at T2, but children's negative emotionality at T1 did not affect parenting stress at T2. When targeted prevention was included as moderator, the correlation disappeared among program users. With PSM, there was no direct effect on parenting stress or child's negative emotionality. But a subsample of parents with high parenting stress at T1 who used targeted prevention at T1 reported less child's negative emotionality problems at T2 than parents who scored high in parenting stress but did not receive targeted prevention at T1. Conclusion: Results suggest that the spillover from parenting stress to child's negative emotionality may be modified by prevention. Prevention programs may help to build resources and have a direct positive effect on the child, especially for parents with high parenting stress.
... Institutional management should take proactive steps to help HCWs with suspected burnout. Early intervention is important to improve positive well-being [47] and this could include the implementation of a recovery plan for such HCWs and the development of strategies for coping and selfcare. Through such efforts, the psychological well-being of HCWs can be protected during the current crisis. ...
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Background Burnout is defined as a syndrome resulting from chronic workplace stress that has not been successfully managed. It is characterised by feelings of energy depletion or exhaustion, increased mental distance from one’s job and reduced professional efficacy. The COVID-19 pandemic has created unexpected demands on healthcare systems worldwide and they have experienced numerous stressors. As the coping is one of the stressors management strategies that may affect burnout, this is a descriptive cross-sectional study aimed to estimate the frequency and level of burnout and its association with coping strategies among physicians and nurses in Saudi Arabia during the COVID-19 Pandemic using Copenhagen Burnout Inventory and Brief-COPE. Results Overall, 403 healthcare providers were recruited (85 physicians, 318 nurses). Personal, work-related and client-related burnout were detected among 67.5%, 68% and 58.3% of the respondents, respectively. The mean score for adaptive coping was (27.6 ± 10.3, median: 29 IQR: 14.0) out of 48, and the mean score for maladaptive coping was (14.2 ± 6.81, median: 14 IQR: 8.0) out of 36. Some factors associated with burnout were participants’ age group, professional position, number of family members and years of experience in the medical field. The personal, work-related and client-related burnout had inverse correlations with the overall adaptive coping category. Conclusion The frequency of burnout during the COVID-19 pandemic, particularly among nurses, was significant. Burnout was also frequent among both the younger age group and those with fewer years of experience. Some predictors were identified as having a close person infected with COVID-19, being assigned to treat COVID-19 patients, longer working hours, having sleeping hours affected by the pandemic and experiencing verbal or physical abuse from patients. In addition to a significant correlation between the adaptive coping category and the three burnout dimensions.
... Selective prevention is aimed at pregnant women at risk for developing a disorder, for example women with a history of psychopathology, pregnancy complications, adverse life events, or low social support (e.g. [12][13][14][15][16]). Previous reviews and metaanalyses have suggested that both indicated [17,18], as well as selective prevention [19][20][21] during the perinatal period are effective for the prevention of depression symptomatology. ...
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Article
Background There is sufficient meta-analytic evidence that antenatal interventions for women at risk (selective prevention) or for women with severe psychological symptoms (indicated prevention) are effective in reducing postpartum distress. However, women without risk or severe psychological symptoms might also experience distress. This meta-analysis focused on the effectiveness of preventive psychological interventions offered to universal populations of pregnant women on symptoms of depression, anxiety, and general stress. Paternal and infant outcomes were also included. Method We included 12 universal prevention studies in the meta-analysis, incorporating a total of 2559 pregnant women. Results Overall, ten studies included depression as an outcome measure, five studies included stress, and four studies anxiety. There was a moderate effect of preventive interventions implemented during pregnancy on the combined measure of maternal distress ( d = .52), on depressive symptoms (d = .50), and on stress (d = .52). The effect on anxiety (d = .30) was smaller. The effects were not associated with intervention timing, intervention type, intervention delivery mode, timing of post-test, and methodological quality. The number of studies including partner and/or infant outcomes was too low to assess their effectiveness. Conclusions This meta-analysis suggests that universal prevention during pregnancy is effective on decreasing symptoms of maternal distress compared to routine care, at least with regard to depression. While promising, the results with regard to anxiety and stress are based on a considerably lower number of studies, and should thus be interpreted with caution. More research is needed on preventing other types of maternal distress beyond depression. Furthermore, there is a lack of research with regard to paternal distress. Also, given the large variety in interventions, more research is needed on which elements of universal prevention work. Finally, as maternal distress symptoms can affect infant development, it is important to investigate whether the positive effects of the preventive interventions extend from mother to infant. Systematic review registration number International prospective register of systematic reviews (PROSPERO) registration number: CRD42018098861.
... Evidence suggests that parenting programs may not be sufficiently powerful in and of themselves to shift global indicators of distress. 38 Alternative measures of parental factors, such as parental self-efficacy, may be useful for future trials, as this Abbreviations: GAD-7, Generalized Anxiety Disorder-7; NA, not applicable; PHQ-9, Patient Health Questionnaire-9; RDAS, Revised Dyadic Adjustment Scale; UC, usual care; VIPP-SD, Video-feedback Intervention to promote Positive Parenting and Sensitive Discipline. a Parenting Scale: higher scores indicate more ineffective parenting strategies. PHQ-9: higher scores represent higher symptom severity. ...
Article
Importance Behavior problems are one of the most common mental health disorders in childhood and can undermine children’s health, education, and employment outcomes into adulthood. There are few effective interventions for early childhood. Objective To test the clinical effectiveness of a brief parenting intervention, the Video-feedback Intervention to promote Positive Parenting and Sensitive Discipline (VIPP-SD), in reducing behavior problems in children aged 12 to 36 months. Design, Setting, and Participants The Healthy Start, Happy Start study was a 2-group, parallel-group, researcher-blind, multisite randomized clinical trial conducted via health visiting services in 6 National Health Service trusts in England. Baseline and 5-month follow-up data were collected between July 30, 2015, and April 27, 2018. Of 818 eligible families, 227 declined to participate, and 300 were randomized into the trial. Target participants were caregivers of children who scored in the top 20% for behavior problems on the Strengths and Difficulties Questionnaire. Participants were randomly allocated on a 1:1 basis to receive either VIPP-SD (n = 151) or usual care (n = 149), stratified by site and number of participating caregivers. Analysis was performed on an intention-to-treat basis. Statistical analysis was performed from September 5, 2019, to January 17, 2020. Interventions All families continued to access usual care. Families allocated to VIPP-SD were offered 6 home-based video-feedback sessions of 1 to 2 hours’ duration every 2 weeks. Main Outcomes and Measures The primary outcome was the score on an early childhood version of the Preschool Parental Account of Children’s Symptoms, a semistructured interview of behavior symptoms, at 5 months after randomization. Secondary outcomes included caregiver-reported behavior problems on the Child Behavior Checklist and the Strengths and Difficulties Questionnaire. Results Among 300 participating children (163 boys [54%]; mean [SD] age, 23.0 [6.7] months), primary outcome data were available for 140 of 151 VIPP-SD participants (93%) and 146 of 149 usual care participants (98%). There was a mean difference in the total Preschool Parental Account of Children’s Symptoms score of 2.03 (95% CI, 0.06-4.01; P = .04; Cohen d = 0.20 [95% CI, 0.01-0.40]) between trial groups, with fewer behavior problems in the VIPP-SD group, particularly conduct symptoms (mean difference, 1.61 [95% CI, 0.44-2.78]; P = .007; d = 0.30 [95% CI, 0.08-0.51]). Other child behavior outcomes showed similar evidence favoring VIPP-SD. No treatment or trial-related adverse events were reported. Conclusions and Relevance This study found that VIPP-SD was effective in reducing symptoms of early behavior problems in young children when delivered in a routine health service context. Trial Registration isrctn.org Identifier: ISRCTN58327365
... To make sure participants answer the survey questions using their episodic memory, day reconstruction studies tend to focus on "yesterday" rather than longer periods such as "last week," which would make it more difficult for people to re-live what they have done and how they have felt in the same level of detail. The day reconstruction method has been used extensively in economic and psychological research (Daly et al., 2014;Delaney and Lades, 2017;Diener and Tay, 2014;Doyle et al., 2017;Knabe et al., 2010). It provides data comparable to other experience sampling methods, but places a lower burden on participants (Dockray et al., 2010;Kim et al., 2013;Sonnenberg et al., 2012). 1 Additionally, we measured participants general tendency to act proenvironmentally (GEN) using a list of 23 behaviours, such as energy conservation efforts or buying products with less packaging. ...
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Understanding the determinants of pro-environmental behaviour is key to addressing many environmental challenges. Economic theory and empirical evidence suggest that human behaviour is partly determined by people's economic preferences which therefore should predict individual differences in pro-environmental behaviour. In a pre-registered study, we elicit seven preference measures (risk taking, patience, present bias, altruism, positive reciprocity, negative reciprocity, and trust) and test whether they predict pro-environmental behaviour in everyday life measured using the day reconstruction method. We find that only altruism is significantly associated with everyday pro-environmental behaviour. This suggests that pro-social aspects of everyday pro-environmental behaviour are more salient to people than the riskiness and intertemporal structure of these behaviours. We also show in an exploratory analysis that different clusters of everyday pro-environmental behaviours are predicted by patience, positive reciprocity, and altruism, indicating that these considerations are relevant for some, but not other, pro-environmental behaviours.
Article
Background Socioeconomically disadvantaged parents experience high levels of stress, anxiety, and depression. Many interventions have been tested to reduce parental stress, but no meta-analysis has been conducted to quantitatively summarize the effects and explore the moderators of intervention effects among socioeconomically disadvantaged parents. Objective This meta-analysis aimed to (1) quantitatively examine the intervention effects of prior stress management interventions among socioeconomically disadvantaged parents on reducing stress, depression, and anxiety; and (2) explore the potential moderators of intervention effects. Methods Six databases, including CINAHL, PubMed, PsycINFO, Sociological Abstracts, Web of Science, and Cochrane, were searched in February 2021. After a two-step literature screening by two independent reviewers, 45 eligible articles were retained. Two evaluators independently assessed each eligible study's quality using the Evidence Project risk of bias tool. The Preferred Reporting Items for Systematic Reviews and Meta-Analyses statement guided the report. Meta-analyses (random-effects model) and moderation analyses (mixed-effects model) were performed. Results Previous stress management interventions had a small effect of -0.24 in reducing parental stress (95% confidence interval [CI]: -0.33, -0.15) with a 7.6-month follow-up effect of -0.12 (95% CI: -0.27, 0.04). The pooled effects on reducing depression were -0.15 (95% CI: -0.26, -0.04) with a 9-month follow-up effect of 0.02 (95% CI: -0.21, 0.26). Two studies measured anxiety, and the average effects were -0.03 (95% CI: -0.16, 0.11). Intervention effects on stress were significantly moderated by country (p = .005), study design (p < .001), and intervention duration (p = .030). Interventions conducted in developing countries (g = -0.52) had a significantly larger effect in reducing stress than those conducted in developed countries (g = -0.19). Studies using a quasi-experimental design (g = -0.47) resulted in a significantly greater effect in reducing stress than RCTs (g = -0.12). Interventions with a duration of 1–3 months (g = -0.36) had a greater effect in reducing stress than those with a longer duration (g = -0.11 for 3–6 months, -0.20 for >6 months). Intervention effects on reducing depression were significantly moderated by intervention component (p = .030). Cognitive behavioral therapy (g = -0.20) and mindfulness-based interventions (g = -0.16) resulted in greater effects in reducing depression than interventions focusing on parenting/life/self-care skills (g = 0.003). Conclusions Previous stress management interventions have short-term beneficial effects on reducing parental stress and depression, but long-term follow-up effects are limited. Short-duration (1–3 months) mindfulness-based interventions and cognitive behavioral therapy in clinical settings are recommended for socioeconomically disadvantaged parents to reduce stress and depression.
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Background: Behaviour problems emerge early in childhood and place children at risk for later psychopathology. Objectives: To evaluate the clinical effectiveness and cost-effectiveness of a parenting intervention to prevent enduring behaviour problems in young children. Design: A pragmatic, assessor-blinded, multisite, two-arm, parallel-group randomised controlled trial. Setting: Health visiting services in six NHS trusts in England. Participants: A total of 300 at-risk children aged 12-36 months and their parents/caregivers. Interventions: Families were allocated in a 1 : 1 ratio to six sessions of Video-feedback Intervention to promote Positive Parenting and Sensitive Discipline (VIPP-SD) plus usual care or usual care alone. Main outcome measures: The primary outcome was the Preschool Parental Account of Children's Symptoms, which is a structured interview of behaviour symptoms. Secondary outcomes included caregiver-reported total problems on the Child Behaviour Checklist and the Strengths and Difficulties Questionnaire. The intervention effect was estimated using linear regression. Health and social care service use was recorded using the Child and Adolescent Service Use Schedule and cost-effectiveness was explored using the Preschool Parental Account of Children's Symptoms. Results: In total, 300 families were randomised: 151 to VIPP-SD plus usual care and 149 to usual care alone. Follow-up data were available for 286 (VIPP-SD, n = 140; usual care, n = 146) participants and 282 (VIPP-SD, n = 140; usual care, n = 142) participants at 5 and 24 months, respectively. At the post-treatment (primary outcome) follow-up, a group difference of 2.03 on Preschool Parental Account of Children's Symptoms (95% confidence interval 0.06 to 4.01; p = 0.04) indicated a positive treatment effect on behaviour problems (Cohen's d = 0.20, 95% confidence interval 0.01 to 0.40). The effect was strongest for children's conduct [1.61, 95% confidence interval 0.44 to 2.78; p = 0.007 (d = 0.30, 95% confidence interval 0.08 to 0.51)] versus attention deficit hyperactivity disorder symptoms [0.29, 95% confidence interval -1.06 to 1.65; p = 0.67 (d = 0.05, 95% confidence interval -0.17 to 0.27)]. The Child Behaviour Checklist [3.24, 95% confidence interval -0.06 to 6.54; p = 0.05 (d = 0.15, 95% confidence interval 0.00 to 0.31)] and the Strengths and Difficulties Questionnaire [0.93, 95% confidence interval -0.03 to 1.9; p = 0.06 (d = 0.18, 95% confidence interval -0.01 to 0.36)] demonstrated similar positive treatment effects to those found for the Preschool Parental Account of Children's Symptoms. At 24 months, the group difference on the Preschool Parental Account of Children's Symptoms was 1.73 [95% confidence interval -0.24 to 3.71; p = 0.08 (d = 0.17, 95% confidence interval -0.02 to 0.37)]; the effect remained strongest for conduct [1.07, 95% confidence interval -0.06 to 2.20; p = 0.06 (d = 0.20, 95% confidence interval -0.01 to 0.42)] versus attention deficit hyperactivity disorder symptoms [0.62, 95% confidence interval -0.60 to 1.84; p = 0.32 (d = 0.10, 95% confidence interval -0.10 to 0.30)], with little evidence of an effect on the Child Behaviour Checklist and the Strengths and Difficulties Questionnaire. The primary economic analysis showed better outcomes in the VIPP-SD group at 24 months, but also higher costs than the usual-care group (adjusted mean difference £1450, 95% confidence interval £619 to £2281). No treatment- or trial-related adverse events were reported. The probability of VIPP-SD being cost-effective compared with usual care at the 24-month follow-up increased as willingness to pay for improvements on the Preschool Parental Account of Children's Symptoms increased, with VIPP-SD having the higher probability of being cost-effective at willingness-to-pay values above £800 per 1-point improvement on the Preschool Parental Account of Children's Symptoms. Limitations: The proportion of participants with graduate-level qualifications was higher than among the general public. Conclusions: VIPP-SD is effective in reducing behaviour problems in young children when delivered by health visiting teams. Most of the effect of VIPP-SD appears to be retained over 24 months. However, we can be less certain about its value for money. Trial registration: Current Controlled Trials ISRCTN58327365. Funding: This project was funded by the National Institute for Health Research (NIHR) Health Technology Assessment programme and will be published in full in Health Technology Assessment; Vol. 25, No. 29. See the NIHR Journals Library website for further project information.
Article
Presents an integrative theoretical framework to explain and to predict psychological changes achieved by different modes of treatment. This theory states that psychological procedures, whatever their form, alter the level and strength of self-efficacy. It is hypothesized that expectations of personal efficacy determine whether coping behavior will be initiated, how much effort will be expended, and how long it will be sustained in the face of obstacles and aversive experiences. Persistence in activities that are subjectively threatening but in fact relatively safe produces, through experiences of mastery, further enhancement of self-efficacy and corresponding reductions in defensive behavior. In the proposed model, expectations of personal efficacy are derived from 4 principal sources of information: performance accomplishments, vicarious experience, verbal persuasion, and physiological states. Factors influencing the cognitive processing of efficacy information arise from enactive, vicarious, exhortative, and emotive sources. The differential power of diverse therapeutic procedures is analyzed in terms of the postulated cognitive mechanism of operation. Findings are reported from microanalyses of enactive, vicarious, and emotive modes of treatment that support the hypothesized relationship between perceived self-efficacy and behavioral changes. (21/2 p ref)
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This paper is a practical guide (a toolkit) for researchers, students and practitioners wishing to introduce randomization as part of a research design in the field. It first covers the rationale for the use of randomization, as a solution to selection bias and a partial solution to publication biases. Second, it discusses various ways in which randomization can be practically introduced in a field setting. Third, it discusses design issues such as sample size requirements, stratification, level of randomization and data collection methods. Fourth, it discusses how to analyze data from randomized evaluations when there are departures from the basic framework. It reviews in particular how to handle imperfect compliance and externalities. Finally, it discusses some of the issues involved in drawing general conclusions from randomized evaluations, including the necessary use of theory as a guide when designing evaluations and interpreting results.
Chapter
Economists have a well-established framework for understanding the welfare consequences of taxing goods that don’t create externalities. Taxes create dead-weight loss by causing consumers to distort their consumption away from their preferred choices. This cost is weighed against the benefits of government revenue. As established in the seminal analysis of Becker and Murphy (1988), this argument applies equally well to both addictive and nonaddictive goods. The same type of revealed preference arguments that suggest that taxes reduce the welfare of consumers of nonaddictive goods can be extended to “rational addicts”: agents decide to smoke by trading off the long-term costs of consumption against the immediate pleasures of consuming, all the while taking into account the addictive properties of the good in question. This model therefore suggests that the only justification for taxing addictive goods is the interpersonal externalities associated with consumption of those goods.