Trends in Family Violence Are Not Causally Associated with
COVID-19 Stay-at-Home Orders: A Commentary
The unprecedented nature of the COVID-19 pandemic has tasked researchers
with describing COVID-19 spread, preventing transmission, finding
treatment courses, and evaluating the impact on society and public
behavior. Due to the rapid influx of scholarly articles processed by
journals and a surge in pre-print articles, research on COVID-19 has
swiftly been disseminated. In fewer than five months, Scopus has already
indexed more than 12,000 publications (Haghani & Bliemer, 2020), with
many journals still currently overwhelmed with submissions (Brainard,
2020). While the flood of information has provided scientists and the
public with necessary information, concerns have been raised about
robustness of the rushed review process. Consequently, a wave of
retractions in major journals has begun to appear (Retraction Watch,
2020).
One potential social impact of COVID-19 that quickly garnered worldwide
attention is family violence rates (Mlambo-Ngcuka, 2020).11We
refer to ‘family violence’ throughout this commentary. Our operational
definition for this construct includes child abuse, intimate partner
and domestic violence. There is reason to hypothesize that family
violence offenses would increase with policy interventions designed to
mitigate COVID-19 transmission, such as stay-at-home orders. Stress, and
the response to stressful situations, are risk factors for family
violence, including child abuse, domestic violence and intimate partner
violence (Capaldi et al., 2012). For example, with the high unemployment
rates occurring as a result of the pandemic, financial strain is a
common stressor in many households. There are many theoretical reasons
to suspect why this might occur, including unemployment and associated
financial strain (Komarovsky, 1940; Schneider et al., 2016), as well as
increased rates of substance use (Alexander & Ward, 2018; Reingle,
Jennings, Connell, Businelle & Chartier, 2014).
Another common stressor in the home is lack of social support. During
the COVID-19 pandemic, there was a notable breakdown in social support
networks and many states initiated mandatory stay-at-home (also called
shelter-in-place) executive orders, thus lengthening the time spent at
home for families (SafeGraph, 2020). Childcare facilities and schools
were almost universally closed, employees were laid off because of
declining business, and other employees were asked to work from home in
an attempt to contain the spread of the virus. Coupled with the
financial strain described above, it is conceivable that this increased
time at home with competing priorities (i.e., home schooling or
babysitting a child while working and maintaining other routine
household activities) could increase the likelihood of family violence
(Herman, 1992).
There has been an urgency to publish on the effect that such
stay-at-home measures have had on family violence to inform and better
adapt community-based responses to victimization. However, one major
negative implication of this is the inaccurate dissemination of results
to the lay audience. One such study, which was published in theAmerican Journal of Criminal Justice on June 14, 2020 (Piquero,
Riddell, Bishopp, Narvey, Reid & Piquero, 2020), studied the impact of
stay-at-home orders on family violence offenses in Dallas, Texas. This
study was widely featured on multiple news outlets months prior to
scientific publication or even acceptance in a peer-reviewed journal
(TCR Staff, 2020; Jam…). This study compared family violence
rates during the 83 days before the stay at home order was
enacted (Jenkins, 2020) to rates for just more than one month (n=35
days) after the stay-at-home order using secondary data from the Dallas
Police Department (DPD). News outlets quoted the study in question as
reporting a 12.5% increase in family violence incidents as a result of
the stay-at-home orders in Dallas County (an effect size that was not
presented in the study).
However, after closer inspection of the manuscript, there was no
statistically significant effect size of the stay at home order on
family violence. The effect size for the time before the stay-at-home
order was 1.4%, and the decline thereafter was 12%–neither
effect size was significant in the interrupted time series analysis
(beta coefficients were .36 and -2.49, respectively). The authors
conclude that “the implementation of the stay-at-home order is not
associated with a statistically significant increase in domestic
violence incidents, and there is not enough evidence to suggest an
upward trend in domestic violence incidents throughout the month after
the stay-at-home order went into effect” (Piquero et al. 2020, p. 11).
This is directly contradictory with the news coverage of the manuscript
ten days prior to the manuscript’s acceptance (Jaramillo,
2020).
In the same manuscript, the authors note that “some of that short-term
spike seems to be associated with what appears to be an upward trend of
domestic violence crimes that was already occurring prior to the
stay-at-home order [emphasis added by authors of this
commentary].” Contrary to this statement, an author of the manuscript
was quoted in a news article making a contrary point, “I think [the
increase in family violence is] strongly associated with the stay at
home order” (Fink, 2020). Given the data presented in the manuscript,
these contradictory claims are scientifically unjustified.
Another common negative implication of a rush to publish is
methodological limitations, calling into question the validity of the
study’s findings (despite their non-significance). Epidemiological
research suggests that even the most robust statistical analyses used to
assess the outcomes of public policy changes are insufficiently powered
to detect effect sizes of −/+15% (Hawley et al., 2019). According to
Hawley and colleagues (2019), thousands of time points would be
necessary to detect an effect size of 15%, indicating that the effect
sizes in this study were unlikely to ever be statistically significant.
The study also ignored seasonal trends in family violence by failing to
account for non-linear or seasonal effects, which are well established
in the scientific literature on violence, including family violence
(Anderson et al, 2000; Koutaniemi & Einiö, 2019). Using a secondary
data source from DPD, seasonal trends can easily be analyzed if robust
data cleaning techniques and appropriate statistical analyses are
conducted. It remains unclear why the authors of this study did not
account for these effects given the prescient seasonal effects in family
violence (and violence generally) that are well documented in the
literature.
Finally, inaccurate dissemination and methodology, when widely
distributed to news outlets, have the potential to impact stay-at-home
policies and potentially, cause harm. Stay-at-home orders have been
associated with a 60% reduction in COVID-19 cases three weeks after
their implementation, with rates increasing each week following their
enactment (Fowler, Hill, Obradovich, & Levin, 2020). The widespread
dissemination of inaccurate research findings described above have
important implications for policy and the virus mitigation efforts,
which might urge policymakers to terminate stay-at-home orders in an
effort to reduce family violence and other social risk factors. Changes
may ultimately result in more COVID-related deaths as stay-at-home
orders are prematurely and inappropriately lifted to prevent purported
injuries in the home. Therefore, the widespread propagation of these
claims in the absence of scientific evidence of an increase has great
potential to cause harm.
We believe that there is no clear link between family violence offenses
and stay at home orders. To demonstrate this, we present descriptive
data from the same police department studied in Piquero et al. (2020),
which provided us with the daily number of family violence incidents
(including child and elder abuse) from January 1-May 12, 2020, which we
aggregated weekly for presentation purposes. We also present three full
years of family violence incident data from DPD in an attempt to
visualize the effects of the stay at home order in light of prior year
cyclical trends in family violence.
The Figure below displays the average number of weekly family violence
incidents from week 1 (January 1-7) of each year to week 52 (December
24-31 of each year). These data suggest that 2020 trends were largely
similar to those observed in 2019 and 2018, with slightly fewer
incidents reported in January 2020 compared to prior years. Clear
seasonal trends are evident, and 2020 trends appear to mirror the trends
that were documented in prior years. An increase in family violence
incidents was observed between April 1-15 (weeks 14-16) each year.
***Insert Figure about here***
The time between April 1 and April 15 does not coincide with the
implementation of the stay at home executive order (March 23). Our
findings of clear seasonal effects are consistent with the scientific
literature on aggression generally and family violence specifically
(Anderson et al, 2000; Koutaniemi & Einiö, 2019). This is particularly
true given the lower rates of family violence observed in January 2020,
as any increase in the incidence rate could reflect an increase in
family violence severity and therefore, reporting, rather than an
increase in family violence incidence. On a surface level, our
descriptive data demonstrated that the effects of family violence noted
to occur in a temporally proximal manner with Dallas County’s
stay-at-home order were seasonal trends that occurred at roughly the
same time each year. These seasonal trends have been reported in prior
research on assaults generally and family violence specifically (Rotton
& Cohn, 2000; Rotton & Cohn, 2001); therefore, any future attempts to
suggest that stay-at-home orders cause an increase in family violence
should use multiple years of data and model seasonal trends (Leslie &
Wilson, 2020).
It is possible that elevated rates of family violence will occur,
although they may be delayed. Informed by the Centers for Disease
Control and Prevention’s continuum of pandemic phases models, as well as
SAMHSA’s research on coping after traumatic events (Centers for Disease
Control and Prevention, 2018; Substance Abuse and Mental Health Services
Administration, 2015), projections conducted by the Washington
University Department of Health predicted that behaviors indicative of
“acting out” (e.g., illicit behavior) are likely to occur between
three and six months after the initial outbreak (Mauseth et al., 2020).
This could be partially responsible for the violence and looting that
occurred during protests in response to police violence in June of 2020.
We might also expect to see elevations in family violence as the year
progresses. The Washington State report also noted that a second wave of
illness is expected to generate “large-scale social and economic
disruption” {Mauseth et al., p.5}. This indicates the need to prepare
for a widespread surge in family violence if an elevation in family
violence rates 3- to 6-months after the initial outbreak are detected.
The goal of this commentary was to prompt a conversation about the
implications of widely disseminating findings from behavioral science
publications related to COVID-19. As a case study, we discussed an
article by Piquero and colleagues, which omitted seasonal trends in
family violence, which are well established (Anderson et al, 2000;
Koutaniemi & Einiö, 2019) and identifiable with visual inspection of
the data from DPD (a multi-year version of the dataset used in Piquero
et al., 2020; Figure).
In conclusion, the authors of this commentary respectfully request that
scientists publishing policy-relevant findings engage in ethical media
engagement practices as well. Specifically, we would suggest that
authors of any scientific publication delay media engagement until the
peer review process is complete, and this includes dissemination of
pre-print manuscripts which have widely increased during COVID-19
(Brainard, 2020). We would also suggest that journalists comply with
media ethics guidelines (Society of Professional Journalists, 2014),
including to “verify information before releasing it”, “provide
access to source information” (the manuscript by Piquero et al., 2020
was not linked in any news article because it had not yet been accepted
for publication), and “avoid undercover or surreptitious methods of
collecting information”. In this case, there was a clear failure of
multiple reporters to verify the claims stated by Piquero et al. (2020),
which is a notable failure to maintain journalistic ethical standards.
The authors of this commentary urge the scientific community to engage
in a discussion related to the responsible dissemination of research
findings, especially those topics that have life and death policy
implications.