Totally 3 questions:

1. The first question should use 3-2-1 report formula when you finish reading ” article about question1″.

2.  

http://www.huffingtonpost.ca/ryan-meili/canada-health-act_b_9610424.html

 

This is the link about the article of question2.

3. Please give me in 18hours. 

4. 3-2-1 report and assignment 1 doc should give me separately.

PURPOSEFUL READING (3-2-1) REPORT Version 2.0
Lightly Adapted from a template by Geraldine Van Gyn.

Question 1: In your own words, what are the 3 most important concepts, ideas or issues in the
reading? Briefly explain why you chose them.

Concept 1 (In your own words) (2 marks)

Concept 2 (In your own words) (2 marks)

Concept 3 (In your own words) (2 marks)

Question 2: What are 2 concepts, ideas or issues in the article that you had difficulty
understanding, or that are missing but should have been included? In your own words, briefly
explain what you did to correct the situation (e.g. looked up an unfamiliar word or a missing
fact), and the result. Cite any sites or sources used in APA format.

Issue 1 (In your own words) (1 mark)

Citation 1 (in APA format) (1 mark)

Issue 2 (In your own words) (1 mark)

Citation 2 (in APA format) (1 mark)

Question 3: What is the main economic story of the reading? (Economics studies the allocation
of scarce resources.)

Story (In your own words) (2 marks)

The Public-Private Mix in the Delivery of Health-Care
Services: Its Relevance for Lower-Income Canadians

Gregory P. Marchildon1 & Sara Allin1,2

Published online: 29 July 2016
# Springer International Publishing 2016

Abstract This paper reviews and analyzes the implica-
tion of the public-private mix of financing and delivery
of health care in Canada for lower-income Canadians.
Based on the type of government stewardship and the
degree of state intervention, the Canadian health system
can be separated into three distinct layers: universal
hospital and physician services financed and regulated
by federal and provincial governments (BMedicare^);
mixed services, including prescription drugs and long-
term care, subject to some provincial stewardship and
subsidy; and privately funded and delivered services
such as dental care. Within Medicare financial barriers
to access have been removed; however, there is a grow-
ing trend toward private sector involvement in the de-
livery of services, and inequalities by income in the use
of physician services are high in Canada relative to
other high income countries. Moreover, the exclusion
of prescription drugs and long-term care from universal
health coverage in Canada, as well as the nearly exclu-
sively private dental market, has created significant ac-
cess issues for lower-income Canadians.

Keywords Canadian health system . Lower-income .

Public-private mix

Introduction: an Overall Health System Overview

Canada is a highly decentralized federation with a similarly
decentralized system of health administration and delivery.
Although the federal government plays an important role in
terms of national standard-setting in some areas of health care
and regulation of pharmaceuticals and health products, and for
the delivery of some health services to designated populations,
it is the provincial governments which are primarily responsi-
ble for how most health-care services are delivered to
Canadians, including low-income and marginalized groups.
By low-income, we generally refer to Canadians in lowest
income quartile of the population.

As illustrated in Table 1, there are three discernable layers
making up the Canadian health system when viewed through
the perspective of degree of state involvement. Each layer has
its own configuration of funding, administration, and delivery
arrangements. As a consequence, the public-private mix in
each of the three layers has quite different implications for
the delivery of health services to lower-income Canadians.

Table 1 purposely separates the factors of funding, admin-
istration, and regulation from service delivery to clarify the
following discussion (see Deber 2004). There are public and
private components in each. Before focusing on the public and
private components in health service delivery, it is worth set-
ting out some general propositions on the public-private di-
vide in funding, administration, and regulation.

Canada has a 70:30 split between public and private financ-
ing of healthcare. This 70:30 ratio is lower than the public-
private ratio of a majority of higher-income countries (CIHI
2015b). Canada, like all high-income welfare states, devotes
significant resources to health care. Table 2 compares all wel-
fare states that spent, through their central, regional, and local
governments, a minimum of US$2500 a year in 2013. These
are all countries in which universal health coverage is the

* Gregory P. Marchildon
greg.marchildon@utoronto.ca

1 Institute of Health Policy, Management and Evaluation, University of
Toronto, Toronto, ON, Canada

2 Canadian Institute for Health Information, Ottawa, ON, Canada

Glob Soc Welf (2016) 3:161–170
DOI 10.1007/s40609-016-0070-4

http://crossmark.crossref.org/dialog/?doi=10.1007/s40609-016-0070-4&domain=pdf

norm (or at least moving toward universal coverage as is the
case in the US) and where health care has become a more
expensive policy responsibility than those relating to educa-
tion or social assistance (welfare). It is generally assumed that
public financing of universal health coverage (UHC) is redis-
tributive—that UHC shifts resources from the healthy and
wealthy to the poor and sick. Sherry Glied (2008) performed
the calculation on Canadian Medicare and found that every $1
of tax funding would move between $0.23 and $0.26 toward
the lowest income quintile of the population and roughly
$0.50 into the two lowest income quintiles.

No different than other high-income welfare states, govern-
ments in Canada have created an intricate web of administra-
tion, law, and regulation to govern and manage universal
health coverage. There are two key aspects in the governance
of UHC in Canada. The first is the Canada Health Act, the
federal law that sets out five national standards with which
provincial governments are expected to comply in order to
receive their per capita shares of a cash transfer from the fed-
eral government (Marchildon 2013).

The second key governance aspect is a set of provincial
laws, regulations, and accompanying arrangements between
these governments and the medical profession that determine
how single-payer UHC is actually administered. The laws
prohibit or discourage the sale of private health insurance for
Medicare services (Flood and Archibald 2001), while the ar-
rangements prevent or discourage doctors from working both
sides of the public-private street (Flood and Haugen 2010).
The end result is that doctors are expected to opt out of the
UHC system entirely if they provide private services to pa-
tients who choose to pay privately.

Consistent with the three layers illustrated in Table 1,
the first section of this paper will summarize the delivery
of UHC services to low-income Canadians by a mix of
public and private providers. The second section will ex-
amine one key dimension of social care—institutional
(nursing home) long-term care, also a mixed sector in
terms of public and private delivery but with the balance
tilted more toward public finance but private delivery. This
is followed by an analysis of the implications of the public-
private mix in prescription drugs where private financing
edges out public financing but where delivery involves a
range of private actors from professionals (physicians and
pharmacists) to pharmaceutical manufacturers and re-
tailers. The final section deals with dental care, the most
private area of Canadian health care in terms of both
funding and delivery.

Table 1 Three layers of the Canadian health system based on degree of state intervention

Degree of state involvement Funding Administration and regulation Delivery

Major—universal health
coverage (Medicare)

Public taxation through the
general revenue funds of
federal and provincial
governments

Single-payer provincial systems.
Private self-regulating professions
under provincial legislative
frameworks

Private physician services, private
for-profit (very limited), not-for-
profit, and arm’s-length
organizations delivering
hospital services

Moderate (social care
and prescription
drugs)

Mix of public taxation, private
(mainly employment-based)
insurance and out-of-pocket
payments

Public services that are generally
welfare-based and targeted, and
private services regulated to varying
degrees by provincial governments

Private professional, private for-
profit, not-for profit, and public
arm’s-length facilities and
organizations

Minimal (dental and vision care,
alternative and complementary
medicines)

Private (mainly employment-
based) insurance and out-
of-pocket payments

Private ownership and control: private
professionals with self-regulation.
Limited state regulation

Private providers and private-for-
profit facilities and organizations

Source: adapted from Marchildon (2004, p. 63)

Table 2 High-income OECD member states in which total government
health spending exceeded US$2500 per year in 2013

OECD country
(rank based on spending)

Government spending per
capita ($US PPP for 2013)

1. Norway 4981

2. Netherlands 4495

3. United States 4198

4. Switzerland 4178

5. Sweden 4126

6. Denmark 3841

7. Germany 3677

8. Austria 3469

9. Belgium 3312

10. France 3247

11. Japan 3090

12. Canada 3074

13. Iceland 2968

14. United Kingdom 2802

15. New Zealand 2656

16. Australia 2614

17. Finland 2583

Source: OECD (2015)

162 Glob Soc Welf (2016) 3:161–170

The Delivery of Canadian Medicare Services

The area of greatest state intervention involves those health
services that are universally covered and free at the point of
access for all Canadians. Known colloquially as Medicare
(and not to be confused with similarly named programs in
the USA and Australia), UHC was introduced in two major
phases in the postwar decades. Originally implemented in the
province of Saskatchewan in 1947, a single-payer system of
universal hospital coverage was adopted in other provinces
between 1958 and 1961 in response to an offer of federal
cost-sharing and acceptance of national standards
(Marchildon 2012; Taylor 1987).

A similar evolution occurred for universal coverage of
medically necessary physician services. The government of
Saskatchewan piloted the first single-payer program for cov-
erage of medically necessary physician costs and then adopted
in all other provinces between 1968 and 1971, again in re-
sponse to an offer of federal cost-sharing and an acceptance
of key national standards (Naylor 1986). These standards in-
cluded the portability of provincial coverage and a strong ver-
sion of universality that required coverage to be provided on
uniform terms and conditions (Marchildon 2014). Although
many policy makers assumed at the time that UHC would
eventually be extended to health services beyond hospital
and physicians, this did not occur. As a consequence,
Canadian Medicare is generally defined as deep but nar-
row—a reference to the fact that there while there is no cost
to the user at the point of service, this deep coverage accom-
panied by national standards (including portability of cover-
age among provinces) has remained restricted to medically
necessary hospital (including in-hospital dental surgery), di-
agnostic and physician services.

As pointed out above, the national standards of Medicare
were reinforced at the provincial government level by the
passage of more detailed laws and regulations. There was
some policy path dependency in that provincial governments
implemented universal medical care coverage in the late
1960s and early 1970s in much the same way they had imple-
mented universal hospital coverage a decade earlier.

At the delivery level, this meant that all Canadians, irre-
spective of income, were to receive the same coverage, the
same quality of services on the same criteria of medical
necessity rather than ability to pay. This was intended to
be one-tier UHC in which all—including the very poor—
would receive the same services based on need. Indeed, the
main objective of Medicare as a national policy and provin-
cial program was to ensure that all Canadians would have
uniform access to medically necessary services and that no
one be discriminated against on the basis of income or other
factors (Romanow 2002). This one-tier system is protected
by the five funding criteria of the Canada Health Act de-
scribed in Table 3.

However, two major OECD studies of high-income coun-
tries, including Canada, which had similar objectives through
UHC, exhibited evidence of income-related differences in the
utilization of health services (Devaux 2016; van Doorslaer and
Masseria 2004). Both studies found significant differences by
income in the likelihood of visiting a primary care physician in a
year after adjusting for need, and an even greater difference by
income in the likelihood of visiting a specialist physician.
However, low-income groups used hospital services significant-
ly more than higher-income groups after adjusting for need (van
Doorslaer and Masseria 2004). While the majority of OECD
countries demonstrated significant income-related inequalities
in physician services, inequity in the probability of visiting a
GP and a specialist was among the highest in Canada (Devaux
2016). In other words, lower-income Canadians are significantly
less likely to report to visit a GP or a specialist in the past year
than higher-income Canadians in the same general level of
health, and this difference by income is higher in Canada than
in other comparable countries. In this literature, the term Bpro-
poor^ is used to describe the greater use (or probability of use) of
health care in the lower end of the income distribution, after
controlling for need, whereas a finding of Bpro-rich^ inequality
signals the reverse. Income is usually measured on a continuous
scale, so the findings do not point to specific income levels, but
rather to the extent that health care use is more concentrated in
the lower end (pro-poor) or the upper end (pro-rich) of the in-
come distribution of the population.

Table 3 Five Criteria of the Canada Health Act (1984)

Criteria Each provincial single-payer Medicare plan must:

Public
administration

Be administered and operated on a nonprofit
basis by a public authority

Comprehensiveness Cover all Medicare services provided by hospitals,
physicians, or dentists (restricted to inpatient
surgical dental services) and, where a provincial
law permits, similar or additional services
rendered by other health care providers

Universality Ensure entitlement to all Medicare health services
on uniform terms and conditions

Portability Not impose a minimum period of residence
(waiting period) in excess of 3 months for
new residents; pay for its own residents
visiting another province (or country in
the case of nonurgent services) with
reimbursement paid at the home rate of
province; and cover the waiting period for
those residents moving to another province
until the new province assumes responsibility
(within 3 months) for UHC

Accessibility Not impede or preclude, either directly or
indirectly, whether by charges made to
insured persons or otherwise, reasonable
access to Medicare services

Source: Adapted from Marchildon (2013, p. 28)

Glob Soc Welf (2016) 3:161–170 163

Studies within Canada help to shed some light on the rea-
son for the income-related inequalities in physician services
that are free at the point of use for all Canadians.

Allin’s (2008) study of equity of access in all Canadian
provinces found evidence of barriers for lower-income groups
in accessing an initial visit to primary care physicians after
adjusting for need, but with visits becoming pro-poor after
the initial visit. Her hypothesis is that while the initial visit is
patient-driven, subsequent visits are more physician-driven
and this produces a result in which access is more equally
distributed overall.

The pro-rich bias in the probability of the initial contact with
a GP is in part related to the heavy reliance on private finance
for prescription drugs, which are complementary to physician
services (Allin and Hurley 2009). In other words, people with
lower income are both less likely to hold private insurance for
prescription drugs and less able to afford to pay out-of-pocket
costs of medications; therefore, they may be deterred from
visiting a physician because of the expected costs of drugs
(Allin and Hurley 2009).

The pro-rich bias could also relate to the fact that many
Canadians do not have a regular family doctor, though few
studies have tested this explicitly. Survey data from 2014 indi-
cate less than 10 % of the population in Ontario report not to
have a family doctor, compared to 20 % of the populations in
Alberta and Saskatchewan, and 25 % in Quebec (CIHI 2015a).

As for specialist visits, an earlier study examined how spe-
cialist care favored higher-income—correlated with better ed-
ucated—Canadians (Dunlop et al. 2000). Both McGrail’s
(2008) British Columbia study and two pan-Canadian studies
confirmed a pro-rich bias in the utilization of specialist ser-
vices (Allin 2008; Asada and Kephart 2007). However, since
Canadians can only obtain specialist services via a referral
from a primary care physician, this barrier may be associated
with the pro-rich bias in getting a first visit with the physician
who can then refer to a specialist for the first time. In fact,
Allin (2008) found that the pro-rich specialist inequity was
rendered nonsignificant after the first specialist visit, except
in two provinces—Prince Edward Island and Alberta.

Even after adjusting for need, lower-income groups utilize
hospital services more than other income groups although
Allin’s pan-Canadian results by province show that this ineq-
uity is difficult to establish statistically based on admissions,
the number of nights spent in hospital, or the probability of
spending one night in hospital (Allin 2008). It is likely that
more extensive use of hospitals does not translate to better
care, and the higher concentration of hospital use in the lower
end of the income distribution may signal a lack of effective
primary care (Allin 2008). It is clear that more research is
required before it is even possible to speculate on the reasons
for any pro-poor inequity in the use of hospital care and in
particular to distinguish from potentially avoidable hospitali-
zations from needed hospital services.

While the literature on inequity in utilization of physician
services is quite large in Canada and, internationally, there has
been growing interest in examining inequalities by income in
other publicly funded services, such as preventive care, the
recent OECD study on inequalities by income included mea-
sures of cervical and breast cancer screening, and found sig-
nificant inequity by income in all OECD countries, with the
magnitude of inequity in Canada falling in the middle of the
pack (Devaux 2016). In Canada, a literature review on access
to cancer care found that income had the most consistent effect
on cancer screening rates, while age and geographical inequal-
ities were evident in end-of-life care (Maddison et al. 2011).
These patterns suggest that higher-income individuals are
more likely to take advantage of the provinces’ universal can-
cer screening programs.

Trends in Terms of the Public or Private Delivery
of Medicare

There has been a long-term shift from private nonprofit and
local government ownership to more provincial government
ownership and management of hospitals. This has been done
through the introduction of regional health authorities (RHAs)
in most provinces. These arm’s-length administrative bodies
were created under provincial statute in the early to mid-
1990s. RHAs were mandated to administer and organize the
delivery of a broad continuum of health services within spec-
ified geographic regions. Recent years have seen a trend to-
ward centralization as provincial governments reduced the
number of RHAs, increasing the size of the populations served
by each RHA. In three provinces, single health delivery orga-
nizations covering the entire provincial population have re-
placed the geographic-based RHAs.

However, whether decentralized or centralized, RHAs own
and manage most of the hospitals located within their respec-
tive borders. A few religious-based hospitals continue to have
independent ownership and management, but these organiza-
tions operate under contract with RHAs and are coordinated
as part of a larger health system. Before the 1990s, almost all
hospitals in Canada were owned and managed by private
(mainly nonprofit) organizations. Ontario is the only province
in which this structure continues. This ownership and man-
agement structure was not altered with the introduction of
Local Health Integration Networks (LHINs), which were then
made responsible for funding hospitals.

At the same time that hospitals have tended to become
more public in Canada, there has been a shift to more private
for-profit ownership of the facilities that conduct laboratory
and diagnostic testing to the point that the vast majority are
now owned and operated by private corporations. In addition,
there has been a trend toward private day surgery facilities for
simpler, nonurgent types of surgeries. These private facilities
mainly provide services under the terms of Medicare.

164 Glob Soc Welf (2016) 3:161–170

Physicians provide referrals for laboratory tests, X-ray, ad-
vanced diagnostics, and day surgery procedures. Patients then
obtain these services at a private clinic without a fee. The
private facilities are reimbursed directly by provincial author-
ities (in most provinces, by RHAs) for the tests.

The few exceptions are a handful of private non-Medicare
facilities or clinics concentrated mainly in Montreal, Calgary,
and Vancouver. These private clinics serve mainly non-
Medicare patients although there has been some controversy
when Medicare patients have used these facilities to avoid
public queues for elective (nonurgent) services and then have
attempted to be reimbursed through the public system.

In 1993–1994, for example, there was a major clash be-
tween the federal government and the provincial government
of Alberta over facility fees. Seven private eye surgery clinics,
two private abortion clinics, and two magnetic resonance im-
aging (MRI) centers began charging patients facility fees in
clear contravention of the Canada Health Act. Federal
Minister of Health Diane Marleau warned the government of
Alberta that the provincial government that Alberta would be
deducted the amount of these facility fees from its share of the
federal health transfer if the practice continued. Marleau stated
the basis of her concerns to the media: B… I’m deeply
concerned…with trends that are developing toward a two-tier
health system. Private clinics appear to run contrary to the
spirit of the Canada Health Act. They do create a two-tier
system, more accessible to the rich than to the poor^ (quoted
in Bhatia and Coleman 2003, p. 733).

Marleau was supported in her view by the provincial gov-
ernments supporting the policy intent of the Canada Health
Act. The most vocal of these was Saskatchewan’s social dem-
ocratic premier, Roy Romanow who stated that the govern-
ment members in Alberta were B…turning the clock as fast
they can [on Canadian Medicare]. Their solutions are simplis-
tic and they amount to one: punish the poor^ (quoted in Bhatia
and Coleman 2003, p. 733–4). The government of Alberta
refused to change its position and was subjected to a deduction
of $420,000 a month, a relatively small amount but one that
gained public attention and opposition in the province. Two
years later, the government backed down in the face of do-
mestic opposition and negotiated with the private clinics to
drop its user charges to patients (Bhatia and Coleman 2003).

In recent years, the debate concerning user charges by pri-
vate clinics has become part of a larger legal debate concerning
the Charter of Rights and Freedoms. In 2005, the Supreme
Court of Canada decided that provincial governments would
not be permitted to uphold legal prohibitions on private insur-
ance for nonurgent Medicare services if waiting times were
excessive (Flood 2007). Currently, there is a case before the
courts in British Columbia where a private surgical clinic has
argued that patients have a constitutional right of access to
private surgical services because of what it considers excessive
Medicare wait times for elective procedures.

While there have been important changes in the delivery of
hospital, laboratory, diagnostic, and day surgery Medicare ser-
vices, the one constant has been the private and independent
position of physicians. As pointed out decades ago by R.
David Naylor, universal medical care coverage was
established as a public payment but private practice system
in the 1960s, and it has remained the same ever since. Doctors
have the status of independent contractors that the vast major-
ity of physicians working in these public facilities remain
private professionals. While RHAs (and LHINs in Ontario)
are ostensibly responsible for ensuring the coordination and
continuity of health care and therefore in charge of organizing
services, provincial ministries of health remain responsible for
paying the physicians who deliver those services, creating
major challenges for the alignment of incentives (Grant and
Hurley 2013; Romanow 2002).

Indeed, the simple fact that the remuneration physicians
receive for diagnosing and treating patients in RHA or private
hospital facilities comes from provincial ministries of health
means that they remain highly independent of the organiza-
tions in which they conduct at least some of their work. While
this private arrangement for hospital-based physicians is not
unique to Canada, it is a rare arrangement. In the UK, for
example, almost all hospital-based consultants (i.e., special-
ists) are salaried and work for the government-owned hospi-
tals called NHS trusts (Boyle 2011).

While there have been no major comparative studies of the
governance and payment of specialists in higher-income
OECD countries, one recent study of six European countries
found pronounced differences among the countries in terms of
the percent of specialists exclusively self-employed, the per-
cent exclusively salaried and the percent working as both con-
tractors and employees. However, the spectrum ranged from
72 % exclusively self-employed (Belgium) to 82 % exclusive-
ly salaried (Denmark) as of 2010 (Kok et al. 2015). In England
where most specialists became salaried employees of a nation-
al hospital system that was created with the introduction of the
National Health Service (NHS) in 1948, only 4 % of special-
ists are exclusively self-employed. In The Netherlands, a
country that has had a long tradition of medical self-employ-
ment, the figure is only 43 % (Kok et al. 2015).

Although there is no definitive study on this subject in
Canada, the limited evidence indicates that the vast majority
of specialists are exclusively self-employed, well above the
72 % mark in Belgium. This means that Canadian specialists
are likely at the very extreme end of the spectrum in terms of
managing their affairs as private businesses. The one parallel
may be Australia where there is a long history of physician
independence and the majority of specialists are also self-
employed. However, it is important to note that independent
specialists in Australia and most European countries contract
with the hospital organizations with which they work thereby
establishing some direct accountability that is missing in the

Glob Soc Welf (2016) 3:161–170 165

Canadian case (Grant and Hurley 2013; Healey et al. 2006;
Schäfer et al. 2010).

Moreover, there is no sustained movement or trend in
Canada for RHAs or independent hospitals to hire specialists
either through contract or salary. Instead, the vast majority of
specialists receive remuneration directly from provincial min-
istries through agreed-upon fee schedules or alternative pay-
ment contracts and have little direct accountability relation-
ship with the hospitals or RHAs within which they provide
inpatient and outpatient care.

The way in which federal and provincial governments have
defined Bmedical care^ has meant that primary care and spe-
cialist doctors have Bsecured a virtual monopoly over public
sector payments for medical services and associated tests,^ a
description of Medicare in Australia (Healey et al. 2006, p. 57),
but one which applies equally well to Canada. Tuohy (1999)
has described this arrangement as a duopoly between the pro-
vincial governments as the sole payers of Medicare and doctors
as privileged provider of Medicare services. As a consequence,
the vast majority Canadian doctors remain private practitioners
to a greater proportion than most other OECD countries.

In the Canadian case, this duopoly has resulted in long-
standing compromises between provincial policy-makers
and organized medicine on the rules of the game. On the
one hand (in most provinces), physicians have the right to
opt out of Medicare. The historic quid pro quo is that opted
out physicians must truly opt out and must rely exclusively on
non-Medicare patients who are prepared to pay directly or
those patients referred for treatment through a separate social
insurance stream of provincial workers’ compensation board
(WCB) clients. At the same time, it is not the provincial gov-
ernment but the doctors themselves, through their own pro-
vincial self-regulatory organizations (the various provincial
colleges of physicians and surgeons), who administer this ar-
rangement by providing provincial Medicare billing numbers
to those doctors working within the Medicare payment system
and denying them to opted-out doctors.

Holding everything else constant, any judicial decision al-
tering these long-standing arrangements by creating new forms
of access to private services for those who have the ability to
pay or access private insurance is likely to have two results in
the short run. The first likely consequence would be to reduce
access to Medicare services for those less able to pay or access
private insurance (due to risk factors such as age or preexisting
conditions) by providing an incentive to physicians to focus on
privately funded patients, a phenomenon common in countries
such as Australia with dual practice (Duckett 2005).

Institutional Long-Term Care

There is a very limited literature on the policy evolution of
institutional long-term care (LTC) in Canada. In particular,

although it appears that provincial governments began to sub-
sidize LTC in the 1970s for those in need, there has been no
systematic comparison of provincial policies in this area. The
means test applied by most provincial governments is that the
provincial government provides for the clinical needs of high-
needs patients including 24-h nursing care and supervision.
However, LTC residents above a certain wealth or income
threshold must pay for their own accommodation and living
expenses in provincially approved LTC facilities.

Due to data limitations, it is almost impossible to calculate
in any precise way the public-private ratios for the financing
of institutional LTC. Moreover, it has been complicated in
recent years by the growth of private sector assisted living.
With the growth in public waiting lists for approved (i.e.,
provincially subsidized) LTC facilities, the private sector has
increasingly been providing high-needs care to residents able
to pay the full cost of both accommodation and clinical care.
Based on CIHI’s calculation for Bother institutions^—a cate-
gory largely made up of facility-based long-term care (LTC)
institutions—we know that the public-private ratio was rough-
ly 70:30 based on CIHI’s forecast for 2015 (CIHI 2015b). This
means that provincial government programs and subsidies for
LTC are substantial in all provinces.

Within the provincially regulated and subsidized LTC sec-
tor, there is a variation in ownership across the country, but
there has been a significant growth in the private for-profit
sector since 2000 (McGregor and Ronald 2011). The largest
private-for-profit market of provincially approved facilities is
in Ontario, where over half of LTC beds are in for-profit fa-
cilities, compared to 31 % in BC and only 8 % in
Saskatchewan (in 2008) (McGregor and Ronald 2011). The
implication of this shift in ownership over time for lower-
income Canadians requires further investigation; although
given the evidence suggesting poorer quality of care among
for-profit compared to public or not-for-profit facilities, this
trend has raised concerns about the overall quality of facility-
based care in Canada (McGregor and Ronald 2011).

A recent analysis of long-term care policies in three
Canadian provinces also documented increasing private sector
involvement in long-term care in two of the provinces
(Alberta and Ontario) in part in response to health care budget
constraints (in particular in the 1990s) and to address short-
ages of long-term care facilities by partnering with the private
sector (Palley 2013). These shortages persist and are evi-
denced by lengthy wait lists to enter facilities. For example,
in Ontario, the median wait to enter a LTC facility among
nonurgent community-dwelling individuals was 68 days in
2004/05 compared to 109 days in 2014/15 (Health Quality
Ontario 2016). At the same time, the publicly subsidized
home and community care services are limited; there is a
heavily reliance on both informal caregivers and private sector
providers that are paid out of pocket (Palley 2013; Williams
et al. 2016). Therefore, lower-income Canadians face financial

166 Glob Soc Welf (2016) 3:161–170

barriers to home and community services beyond the limited
publicly funded services for which they are deemed to be
entitled. Moreover, they may also face high costs of institu-
tional care in some provinces, like Alberta, where accommo-
dation and nonmedical expenses are not regulated (Palley
2013). In Ontario, the limited supply of personal care within
publicly funded facilities has led to an increasing reliance on
private caregivers to fill the gap for only those able to pay
(Daly et al. 2015).

To our knowledge, only one study to date has measured
income-related inequalities in access to long-term care facili-
ties in Canada (Um 2016). This study reviewed publicly avail-
able wait list information for each publicly funded long-term
care facility in Toronto, Canada’s largest city, and found wait
times for basic accommodation (rooms with two to four beds)
were about 3 months longer on average than those for private
accommodation. The implication of this discrepancy is that
people who can afford to pay the higher cost of private ac-
commodation ($2535.23 vs. $1774.81 CAD monthly) face
much shorter waits than those with lower income (Um 2016).

Prescription Drugs

One of the most criticized dimensions of Medicare is that,
unlike most other high-income industrialized countries,
UHC in Canada excludes pharmaceuticals unless provided
as part of inpatient care within a hospital. Historically, this
lack of public coverage posed a major financial barrier to
access to needed outpatient prescription drug therapies.
Private health insurance covering prescription drugs, dental
care, and vision care has long been part of employment-
based benefit packages in Canada, so a significant number
of Canadians in corporate, unionized, and professional envi-
ronments are covered. However, this created a gap in coverage
for those in low-paid employment, temporary or seasonal
work, retired persons, and the unemployed.

In the 1970s, provincial governments began addressing this
gap by creating provincial drug plans that targeted the very
poor—generally defined as those individuals receiving social
assistance—and older adults above retirement age (defined as
65 and older) and therefore no longer receiving employment
benefits. The current design of most provincial drug plans
continues to reflect this original policy purpose. For its part,
the federal government filled a similar gap for Indigenous
people living on reserves and Inuit living in the far north
through a program known as Non-Insured Health Benefits
(NIHB). Among the poorest and most marginalized citizens
of Canada, most NIHB beneficiaries were not part of the for-
mal economy and therefore unable to benefit from drug (or
dental) coverage under employment-based private health in-
surance plans.

Of the forecasted $29.2 billion spent on prescription drugs
in Canada in 2015, governments in Canada were responsible
for financing $12.6 billion (43 %) of prescription drug thera-
pies through public drug coverage and drug subsidy plans.
The remaining amount (57 %) is financed through private
health insurance (35 %), most often through employment ben-
efit plans, and 22 % out of pocket payment (CIHI 2015b).

However, in part, a consequence of these governments
having limited regulatory control of prescription drug pricing
and the power of pharmaceutical companies and interest
groups in influencing the drugs included in provincial formu-
laries in a fragmented policy environment, the current pro-
grams have grown rapidly in cost since at least the mid-
1970s (CIHI 2015b; Morgan et al. 2013). To address this
inefficiency as well as improve access, the evidence points
away from the status quo of public and private insurance ar-
rangements to a single-payer public system administered in
ways that parallel Medicare in Canada. However, difficult
changes in governance and administration are required to
achieve lower cost and universal coverage, and despite the
fiscal and equity arguments in favor of major reform, govern-
ment initiative at federal or provincial levels has remained
limited (Morgan et al. 2015a, b).

The impact of the exclusion of prescription drugs outside
from UHC on low-income Canadians is apparent. Among
Canadians who receive a prescription, 1 in 10 report cost-
related nonadherence, the odds of which significantly increase
for lower-income Canadians and those without prescription
drug insurance (Law et al. 2012). In the 2008
Commonwealth Fund survey of people with chronic condi-
tions, 22 % of Canadians with below-average income reported
not to fill a prescription or to skip doses because of costs in the
past 2 years, compared to less than 15 % of people with below
average income in France (14 %), the UK (10 %), and the
Netherlands (4 %) (Schoen et al. 2008).

The impact of not holding prescription coverage, which
disproportionately affects lower-income Canadians, is not on-
ly to use less needed medications for chronic conditions (e.g.,
in a study from Ontario; Kratzer et al. 2015) but also to reduce
the likelihood of seeking primary physician care when needed
(Allin and Hurley 2009). Moreover, even among those with
public coverage through a provincial prescription drug pro-
gram, the user charges and deductibles that are in place have
the effect of deterring use among people with lower income
(as evidenced in Quebec for example, Tamblyn et al. 2001,
and Ontario, Allin et al. 2013).

Dental Care

Canada has among the most private systems of dental care
relative to the high-income welfare states listed in Table 2.
Approximately 95 % of dental services are financed privately,

Glob Soc Welf (2016) 3:161–170 167

either through employment-based private health insurance or
out-of-pocket payments. Private dental practitioners are re-
sponsible for the delivery of almost all dental services in
Canada. Low-income Canadians have consistently faced con-
siderable financial barriers to access to both preventive and
curative dental care.

The policy response to this challenge has been twofold.
The first and most pronounced response has been to extend
coverage to those receiving provincial social assistance (wel-
fare). However, in most provinces, it is up to private dental
practitioners to decide whether to accept social assistance cli-
ents at reimbursement rates set by provincial governments.
Such interventions did not, and still do not, include the work-
ing poor. The federal government in turn has provided cover-
age for eligible First Nation individuals and Inuit under the
NIHB program discussed earlier. Originally, this was a re-
sponse to a situation where most NIHB beneficiaries did not
have access to employment-based private health insurance.

The second policy approach was to target school-aged chil-
dren in prevention and treatment programs directly delivered
by provincial governments through paraprofessionals.
However, the dental profession and governments with more
conservative and market ideologies have consistently opposed
this bolder policy approach (Mathu-Muju et al. 2013). As a
consequence, only two provincial governments have
attempted to establish such programs. In the 1970s, the
Saskatchewan government implemented a program covering
the entire population while the Manitoba government
established a smaller program targeting rural residents. Both
programs were implemented by social democratic govern-
ments and were subsequently terminated by more
conservative-leaning governments in the 1980s.

From its implementation in 1974 until its dismantlement in
1987, the Saskatchewan Dental Plan (SDP) provided a range
of dental prevention and treatment services to hundreds of
thousands of school children throughout the province of
Saskatchewan in Canada. Dental therapists served a total pro-
vincial population of just slightly less than 1 million residents
distributed in a vast geographical area (651,036 km2) consid-
erably larger than the state of California. At its peak, the SDP
had 150 dental therapists providing preventive and curative
dental therapy to 90 % of enrolled school children in
Saskatchewan (Nash et al. 2008). Although a universal pro-
gram, the SDP provided access to a generation of children
from low-income families and changed the trajectory of oral
health outcomes in the province.

In Canada, there have been smaller-scale initiatives in other
provinces and the northern territories, but these programs have
not been universal in nature and were generally based on a fee-
for-service (FFS) private practice model (Wolfson 1997).
These programs targeted subpopulations based upon income,
location, or beneficiary status as Bregistered Indians^ and el-
igible Inuit under the NIHB as discussed above. The only

policy intervention similar to the SDP was in Manitoba where
the provincial government established the school-based
Manitoba Children’s Dental Program, the range of which
was limited to targeted rural areas. This program operated
from 1976 to 1993 when it too was eliminated after years of
opposition by organized dentistry in the province (Nash et al.
2008). Indeed, the Canadian Dental Association and provin-
cial dental associations consistently opposed this public policy
alternative to the private practice model in all provinces.

Given the exclusion of dental care from UHC, it is not
surprising that there is consistent evidence of inequity by in-
come in the use of dental services. The 2007 Commonwealth
Fund international survey found 33 % of Canadians with
below-average income who needed dental care did not see a
dentist because of cost which was lower than in Australia,
New Zealand, and the USA but significantly higher than in
Germany, the Netherlands, and the UK (Schoen et al. 2007). A
significant pro-rich bias in dental care is evident across the 18
OECD countries studied, and the magnitude of inequity was
higher in Canada than all other countries except the USA
(Devaux 2016). In Canada, inequity by income appears to
be highest for preventive dental care (Grignon et al. 2010).
Given private insurance for dental care is mostly held by
higher-income Canadians (Bhatti et al. 2007), the variations
in coverage across provinces in part explain the variations in
the extent of income-related inequalities in dental care that is
observed (Allin 2008).

Conclusion

To better understand the nature of the public-private modes of
service delivery, the highly decentralized Canadian health sys-
tem is subdivided into three layers based on the nature of
government stewardship in the federation and the degree of
state of intervention. First, there is Medicare, which embraces
universally accessible hospital and physician services fi-
nanced and regulated by federal and provincial orders of gov-
ernment. Second, there are the mixed services—prescription
drugs and long-term care—subject to some state intervention
through targeted coverage policies which address gaps not
filled by the private sector. Finally, there are the private ser-
vices (e.g., dental care), which are almost entirely financing
and delivered privately. Each of these three layers was exam-
ined separately in order to minimize confusion and gain great-
er analytical clarity.

Although Medicare is the most public layer of the
Canadian health system, universal health coverage nonethe-
less presents some equity conundrums. In spite of physician
services being free at the point of use, income-related inequal-
ities favoring the rich appear to be significant in Canada, and
inequalities are actually larger in Canada than in other high-
income countries with universal health coverage. In part, the

168 Glob Soc Welf (2016) 3:161–170

inequalities in access to a GP relate to prescription drug ther-
apies (excluded from UHC) that often result from a physician
visit. In addition, pro-rich specialist access could be due to
inequitable referral patterns by GPs favoring higher-income
and higher-educated individuals who are better able to advo-
cate for themselves.

Illness prevention programs also present some challenges.
For example, there is a strong pro-rich bias in cancer screening
due to the tendency for higher-income individuals to take
advantage of such policies and programs.

There is also a growing trend toward private sector involve-
ment in Medicare in terms of the delivery laboratory, ad-
vanced diagnostic and ambulatory surgical services. When
forced to comply with the standards set by the Canada
Health Act as well as provincial rules and regulations
protecting Medicare, these private services have not posed a
major challenge to equity. However, when coupled with the
ability to jump public queues and user fees, these private ser-
vices can create a two tier system which ultimately delivers
less timely and lower quality services to low-income
Canadians.

When it comes to long-term care and prescription drugs,
Canadians live in a two tier world. Supply constraints for
publicly financed and delivered facility-based LTC mean that
Canadians with significant income can bypass the public sys-
tem by paying privately for private sector facilities which have
increasingly moved into higher needs care. Moreover, there
seems to be little planning or effort by provincial governments
to address the growing shortages of publicly subsidized LTC
facilities. In systems where the sector is heavily regulated
(e.g., in Quebec and Ontario), the publicly funded system is
accessible, but the supply remains very constrained. As a re-
sult, individuals who can afford to do so pay privately for
additional needed services, or to opt out of the public system
in order to bypass wait lists.

The case of prescription drugs is similar. Provincial drug
plans are meant to fill in the gaps left by employment-based
private health insurance, but the public plans impose financial
barriers through user charges. This policy negatively affects
access for the working poor and retirees. Fortunately, the
poorest of the poor—individuals receiving social assis-
tance—are generally exempt from such user fees. There has
been a pronounced trend in all provinces to provide cata-
strophic drug coverage. However, these policies leave in place
financial barriers to access that disproportionately affect
poorer Canadians, which in turn lead to nonadherence and
related adverse health outcomes.

Dental care is an almost exclusively private. As a conse-
quence, inequalities in use of dental care services are larger in
Canada than in all other high-income countries except the
USA. Most dental insurance is employment-based and con-
centrated in higher salaried occupational groups. Since there is
little government intervention to provide services and almost

no subsidization of dental insurance (except for targeted
groups such as eligible First Nation individuals and Inuit),
the result is much poorer oral health results for poorer
Canadians.

Even Medicare, the most public layer of Canadian health
care based on stewardship, financing, and administration, has
always had a large component of private delivery. However,
the introduction of private delivery for medically necessary
services operating outside the regulatory framework of
Medicare—such as what has occurred with advanced diagnos-
tics and ambulatory surgical services—could Bstretch^ the
availability of scarce human resources and create inequities
in terms of access. However, this still poses less of an issue
than the longstanding inequities found in the mixed and pri-
vate layers of health care in Canada. The lack of pharmaceu-
tical coverage and dental care coverage, as well as the costs
and availability of institutional (and noninstitutional) long-
term care, present major equity and access issues for many
lower-income Canadians. Such issues occur in areas where
the presence of a fee-for-service clinical practice and the high
degree of private sector Bmarketization^ are significant factors
with regard to the delivery of healthcare services.

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• The Public-Private Mix in the Delivery of Health-Care Services: Its Relevance for Lower-Income Canadians

Introduction: an Overall Health System Overview
The Delivery of Canadian Medicare Services
Trends in Terms of the Public or Private Delivery of Medicare
Institutional Long-Term Care
Prescription Drugs
Dental Care
Conclusion
References

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Media Psychology

ISSN: 1521-3269 (Print) 1532-785X (Online) Journal homepage: https://www.tandfonline.com/loi/hmep20

Everyday functioning-related cognitive correlates
of media multitasking: a mini meta-analysis

Wisnu Wiradhany & Janneke Koerts

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cognitive correlates of media multitasking: a mini meta-analysis, Media Psychology, DOI:
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Everyday functioning-related cognitive correlates of media
multitasking: a mini meta-analysis
Wisnu Wiradhany a and Janneke Koerts b

aDepartment of Experimental Psychology, University of Groningen, Groningen, the Netherlands;
bDepartment of Clinical and Developmental Neuropsychology, University of Groningen, Groningen, the
Netherlands

ABSTRACT
A recent meta-analysis has shown that media multitasking beha

–

vior, or consuming multiple streams of media simultaneously,
might not be associated with less efficient cognitive processing,
as measured with objective tests. Nevertheless, a growing num-
ber of studies have reported that media multitasking is corre-
lated with cognitive functioning in everyday situations, as
measured in self-reports. Here, in a series of mini meta-
analyses, we show that the self-reported correlates of media
multitasking can be categorized in at least four major themes.
Heavy media multitasking was associated with increasing pro-
blems with attention regulation (e.g., increased mind-wandering
and distractibility), behavior regulation (e.g., emotion regulation
and self-monitor), inhibition/impulsiveness (e.g., higher level of
impulsiveness and lower level of inhibition), and memory.
However, the pooled effect sizes were small (z =.16 to z = .22),
indicating that a large proportion of variance of media multi-
tasking behavior is still unaccounted for. Additionally, we wit-
nessed a high level of heterogeneity in the attention regulation
theme, which might indicate the presence of the risk of study
bias.

In recent years, the number of studies investigating the correlates of
habitual media multitasking behavior, i.e., consuming multiple streams of
media-related information simultaneously, have increased. These studies
investigate correlates of media multitaskers using both performance-based
and self-reported measures, and have presented an interesting contradic-
tion. On the one hand, the group of studies using performance-based
measures, that is, highly controlled psychophysics experiments with clear
instructions (e.g., to perform as quickly and as accurately as possible) and
clear beginning and end, has shown mixed results. Specifically, some
studies showed that Heavy Media Multitaskers (HMMs), compared to
Light Media Multitaskers (LMMs) displayed worse performance in differ-
ent objective, performance-based measures of cognition (Cain, Leonard,

CONTACT Wisnu Wiradhany w.wiradhany@rug.nl Department of Experimental Psychology, University of
Groningen, Grote Kruisstraat 2/1, 9712 TS Groningen, the Netherlands

MEDIA PSYCHOLOGY
https://doi.org/10.1080/15213269.2019.1685393

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Gabrieli, & Finn, 2016; Ophir, Nass, & Wagner, 2009; Ralph & Smilek,
2016), while others reported that HMMs performed better than LMMs
(Alzahabi & Becker, 2013; Baumgartner, Weeda, van der Heijden, &
Huizinga, 2014). Yet, others reported mixed findings and/or null results
(Cardoso-Leite et al., 2015; Gorman & Green, 2016; Minear, Brasher,
McCurdy, Lewis, & Younggren, 2013; Murphy, McLauchlan, & Lee, 2017;
Ralph, Thomson, Seli, Carriere, & Smilek, 2015; Wiradhany &
Nieuwenstein, 2017). With this mixed evidence, it is not surprising that
a recent review (van der Schuur, Baumgartner, Sumter, & Valkenburg,
2015) and a meta-analysis (Wiradhany & Nieuwenstein, 2017) have
shown that pooled together, the association between media multitasking
and performances on performance-based measures of cognition is weak.
Furthermore, the meta-analysis has shown that upon applying meta-
analytic correction, the pooled association between media multitasking
and performances on performance-based measures of cognition turned
out to be null.

On the other hand, there have been a growing number of studies showing
associations between frequent media multitasking and problems reported on
rating scales of cognition. Specifically, frequent media multitasking has been
associated with more self-reported attention lapses and mind-wandering
(Ralph, Thomson, Cheyne, & Smilek, 2013), higher levels of impulsiveness
(Cain et al., 2016; Magen, 2017; Minear et al., 2013; Sanbonmatsu, Strayer,
Medeiros-Ward, & Watson, 2013; Schutten, Stokes, & Arnell, 2017; Uncapher,
Thieu, & Wagner, 2016), a higher number of problems with executive functions
(Baumgartner et al., 2014; Magen, 2017), and more (severe) symptoms of
Attention Deficit/Hyperactivity Disorders or ADHD (Magen, 2017; Uncapher
et al., 2016). Together, these findings suggest that media multitasking is not
associated with performances on objective measures of cognition, but never-
theless, is associated with different aspects of everyday cognitive functioning.

In cognition research, it is common to use both performance-based and self-
reported methods for assessment as these two types of assessment often comple-
ment one another (e.g., Chan, Shum, Toulopoulou, & Chen, 2008). At the same
time, findings from both types of measurement might disagree with one another
for several reasons. To start, the two measures arguably estimate one’s ability to
function on different levels. Performance-based measures estimate one’s optimal
performance: These measures have explicit instructions and are administered
under highly standardized conditions. Accordingly, the results of these measures
would reflect the efficiency of cognitive processing of an individual (Stanovich,
2009; Toplak, West, & Stanovich, 2013). In contrast, self-reported measures of
the same construct estimate one’s typical performance: These measures probe
a wide range of everyday behaviors which are related with the construct which is
being estimated. Accordingly, the results of these measures would reflect the

2 W. WIRADHANY AND J. KOERTS

ability of an individual to execute a task in conditions in which no explicit
instructions or goals are given (Stanovich, 2009; Toplak et al., 2013).

Critically, it is possible for an individual to score low in one type of
measure but high in the other type and vice versa. In this light, the
International Classification of Functioning, Disability, and Health (ICF),
which is developed by the World Health Organization (World Health
Organization, 2001), draws a distinction between functions (i.e., the struc-
tural integrity of the body to allow for optimal use) and activities (i.e., the
life areas, tasks, and actions associated with an individual). One can have
an impairment on the activity level, but might perform well on the func-
tional level. For instance, individuals with dysexecutive symptoms might
report frequent problems in everyday situations, yet they perform relatively
well in an executive function test (Burgess et al., 2006). Similarly, impair-
ments on a functional level do not always necessarily result in impairments
on the activity level due to compensation and adaptation. For instance,
individuals with mild Alzheimer’s disease might perform poorly in an
objective test, yet they are able to perform their daily activities using
support from their environments (Farias, Harrell, Neumann, & Houtz,
2003). Accordingly, people who frequently media multitask might not
perform worse in performance-based measures of cognition, yet report
everyday problems associated with cognition due to the fact that laboratory
measures might capture some, but not all aspects of cognition or that they
measure cognition on a different level compared to self-reported measures.

Correlates of media multitasking

Due to the ubiquity of media devices in recent years (Lenhart, 2015;
Marius & Anggoro, 2014), the frequency and duration of media multi-
tasking behavior, consuming multiple streams of media information simul-
taneously, have increased dramatically (Carrier, Cheever, Rosen, Benitez, &
Chang, 2009; Rideout, Foehr, & Roberts, 2010; Roberts & Foehr, 2008).
This behavior is mainly characterized by rapid switches of attention
between different media streams. An observational study of concurrent
television and computer usage showed that, on average, participants
switched their attention 120 times within 27.5 min (Brasel & Gips, 2011).
Similarly, another observational study reported that contemporary office
workers spent on average 3 min on a task before switching to another
(González & Mark, 2004). Switching does not only happen between media
devices, but also between different media activities. For instance, Judd
(2013) reported from computer session logs that college students switched
between different tasks in a computer about 70% of the time and spent on
average 2.3 min on one task before switching to another.

MEDIA PSYCHOLOGY 3

With the high frequency of switching between different media streams, it is
likely for media multitasking behavior to disrupt other ongoing cognitive and
behavioral processes. With regard to cognitive processes, media multitasking
might disrupt one’s current train of thoughts, which may result in worse task
performance. In a study in which participants were asked to study an article
about influenza, participants recalled less information about the article in con-
ditions in which they were either forced to check their Facebook account or
allowed to check their Facebook account while studying the article (Kononova,
Joo, & Yuan, 2016). Other studies have shown that media-induced interruptions
might have no significant impact on task performance (Fox, Rosen, & Crawford,
2009; Mark, Gudith, & Klocke, 2008), but nevertheless, people who experienced
constant interruptions during work reported more stress and frustration at the
end of the day (Mark et al., 2008). With regard to behavioral processes, media
multitasking behavior might disrupt other everyday behavior patterns. For
instance, adolescents who reported higher level of media multitasking also
reported having fewer hours of sleep per night (Calamaro, Mason, & Ratcliffe,
2009). Similarly, in a longitudinal study, adolescents with a higher level of media
multitasking reported more sleeping problems at the time of the data collection,
3 months, and 6 months later (van der Schuur, Baumgartner, Sumter, &
Valkenburg, 2018).

The current study

Media multitasking behavior might interfere with different ongoing processes in
everyday situations. This behavior might not be correlated with performances
on objective measures of cognition (van der Schuur et al., 2015; Wiradhany &
Nieuwenstein, 2017), but nevertheless, it might have profound impact on every-
day cognitive functioning, as indicated by self-reported measures of cognition.
This article aims to examine and summarize the current body of literature on
media multitasking in order to create an overview of the different domains of
everyday cognitive functioning which might be correlated with media multi-
tasking behavior. The evidence was synthesized in a series of mini meta-analyses.
Additionally, we also examined the risk of bias across the findings and per-
formed a moderator analysis if risk of bias occurred.

Methods

Study selection

All studies which investigated correlates of self-reported measures of media multi-
tasking and cognition were considered for inclusion. Studies were identified in the
PsycInfo, ERIC, MEDLINE, SocINDEX, and CMMC databases, as well as
the Directory of Open Access Journals (DOAJ) database. A combination of the

4 W. WIRADHANY AND J. KOERTS

following keywords was entered in the search terms: media multitask* AND
(problem* OR executive* OR impuls* OR attention*)1. Together, the search yielded
130 results from the first set of databases and 68 results from the DOAJ database.

As Figure 1 shows, of the 198 studies identified, 40 were duplicates and
therefore removed. Of the 158 studies, only 43 pertained to the term “media
multitasking” (i.e., not only pertained to “media” or “multitasking” exclu-
sively) and were therefore considered for further screening. Of 43 studies
screened, we removed studies which did not meet the criteria below.

First, studies must have examined the association between measures of
media multitasking and self-report measures of cognition, or psychological
traits or mental-health issues related to cognition. Therefore, four review
articles (Aagaard, 2015; Carrier, Rosen, Cheever, & Lim, 2015; Lin, 2009; van
der Schuur et al., 2015), two meta-analysis (Jeong & Hwang, 2016;

Figure 1. A flow diagram showing the selection of study process.

MEDIA PSYCHOLOGY 5

Wiradhany & Nieuwenstein, 2017), one measurement validity article
(Baumgartner, Lemmens, Weeda, & Huizinga, 2017), 12 articles which only
included laboratory task performance measures (Alzahabi & Becker, 2013;
Alzahabi, Becker, & Hambrick, 2017; Cain & Mitroff, 2011; Edwards & Shin,
2017; Gorman & Green, 2016; Lui & Wong, 2012; Moisala et al., 2016;
Murphy et al., 2017; Ophir et al., 2009; Ralph & Smilek, 2016; Ralph et al.,
2015; Yap & Lim, 2013), two articles in which the level of media multitasking
was manipulated (Kazakova, Cauberghe, Pandelaere, & De Pelsmacker, 2015;
Lin, Robertson, & Lee, 2009), one article in which only a brain imaging
measure was used (Loh & Kanai, 2014) and two articles in which only media
multitasking behavior was observed (Loh, Tan, & Lim, 2016; Rigby, Brumby,
Gould, & Cox, 2017) were excluded from further eligibility assessment.

Second, since this study pertains to general media multitasking behavior
(i.e., not a specific combination of two media), only studies using a general
media multitasking measure were included. Therefore, one article in which
only a specific combination of media multitasking was used (Kononova,
Zasorina, Diveeva, Kokoeva, & Chelokyan, 2014) and one article (Wu,
2017) which measured the perception of media multitasking ability instead
of actual media multitasking frequency were removed. Thirdly, we removed
two articles that measured the association between media multitasking and
well-being or constructs which are related to well-being (Hatchel, Negriff, &
Subrahmanyam, 2018; Pea et al., 2012). Lastly, one article was excluded since
the relevant effect sizes could not be extracted from the published article
(Shih, 2013)2. In all, a total of 13 articles containing 15 independent studies3

were included for synthesis (Baumgartner, van der Schuur et al., 2017, 2014;
Cain et al., 2016; Cardoso-Leite et al., 2015; Duff, Yoon, Wang, & Anghelcev,
2014; Hadlington & Murphy, 2018; Magen, 2017; Minear et al., 2013; Ralph
et al., 2013; Sanbonmatsu et al., 2013; Schutten et al., 2017; Uncapher et al.,
2016; Yang & Zhu, 2016). Table 1 shows the measures of self-reported
functioning included in each study and the number of participants assessed.

Effect size selection and calculation

Effect sizes were selected from reported outcome measures which reflect
distinguishable constructs. For instance, a study examining the association
between media multitasking and measures of executive function would
report measures of attentional shifting, working memory, and inhibition,
which are separate constructs. Study findings related to these measures
would be regarded as individual effect sizes. In total, 48 unique effect sizes
were extracted from the studies listed in Table 1 and included in the final
series of mini meta-analysis.

Effect sizes were calculated in Fisher’s z, indicating the normalized correla-
tion coefficients between self-reported measures of media multitasking and

6 W. WIRADHANY AND J. KOERTS

Ta
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.2
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m
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56
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m
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ed
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n
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=
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(2
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30
3

Ba
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ve
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s
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e
(B
IS
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83
.2
3%

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m
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M

ag
e
=
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3

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n
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p
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(2
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13
9

Ba
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MEDIA PSYCHOLOGY 7

self-reported measures of cognition. A positive z indicates that frequent
media multitasking is associated with more (severe) issues and a negative
z indicates that frequent media multitasking is associated with less (severe)
issues. In most cases, the included studies reported Pearson’s product-
moment correlations (r) as measures of effect sizes. These r’s were converted
into Fisher’s z using formula 1 below (Borenstein, Hedges, Higgins, &
Rothstein, 2009):

z ¼ 0:5 � ln 1 þ r
1 � r

� �
(1)

In which r is the Pearson’s product-moment correlation.

Analysis

Categorization of findings
Since different studies featured in the meta-analysis and the featured rating
scales measured different domains of cognition, we grouped the respective
effect sizes into different categories based on the similarity and dissimilarity
between constructs. To illustrate, the Mindful Attention Awareness Scale
(MAAS; Brown & Ryan, 2003) and the self-monitoring subscales of the
Behavioral Ratings of Executive Functions (BRIEF; Gioia, Isquith, Guy, &
Kenworthy, 2000; Gioia, Isquith, Retzlaff, & Espy, 2002) infer a relatively
similar construct related to attention regulation, which is relatively dissimilar
to the construct related to forming precise information in memory inferred
by the Memory Failures Scale (MFS; Carriere, Cheyne, & Smilek, 2008).

To guide the categorization of our effect sizes, we first made a table of self-
report measures in Table 1 along with the goal of each individual measure
and some examples of its items. Considering the goal of the measure and its
items, we then looked into the literature to gain insights on how to group
them in a meaningful way. For instance, measures related to impulsiveness
such as the Barratt Impulsiveness Scale (BIS; Patton, Stanford, & Barratt,
1995), measures related to inhibition such as the BRIEF-Inhibition (Gioia
et al., 2002), and measures related to sensation seeking such as the Sensation-
Seeking Scale (SSS; Zuckerman, 1996) were group together under the over-
arching construct of impulsiveness/inhibition (e.g., Dalley, Everitt, &
Robbins, 2011). Some measures, such as the ADHD-Adult Self Report
Scale (ADHD-ASRS; Kessler et al., 2005) and the Cognitive Failure
Questionnaire (CFQ; Broadbent & Cooper, 1982) might have two or more
distinct underlying constructs; the former has attention and impulsiveness
components and the latter has attention, memory, and other components.
To ensure that our resulting categories were as independent from each other
as they can be, in the case of the ADHD-ASRS, we contacted the authors to
request additional data regarding the correlation between media

8 W. WIRADHANY AND J. KOERTS

multitasking and attention deficit and between media multitasking and
hyperactivity/impulsiveness separately. In the case of the CFQ, considering
that studies, especially recent ones were in disagreement with regard to the
underlying dimensions of CFQ (Bridger, Johnsen, & Brasher, 2013; Larson,
Alderton, Neideffer, & Underhill, 2011; Wallace, Kass, & Stanny, 2002), we
decided to categorize the effect sizes pertained to the general CFQ scores
twice: once in the attention regulation category and once in the memory
category. For all categories, the first author performed the categorizations
and the second author checked the resulted categories. Disagreements
between authors were resolved by consensus.

Using the categorization processes above, we identified four different
themes for correlates between media multitasking and self-reports of every-
day cognitive functioning, namely attention regulation, behavior regulation,
impulsiveness/inhibition, and memory. The attention regulation theme per-
tained to the set of cognitive abilities which help to boost information
processing. Traditionally, this includes the ability to react to important cues
in the environment (alerting of attention), select relevant from irrelevant
information (orienting of attention), and switch from one stimulus-response
task rule to another (executive attention; Petersen & Posner, 2012; Posner &
Petersen, 1990). More recently, our ability to suppress internally generated
task-unrelated thoughts (Christoff, Irving, Fox, Spreng, & Andrews-Hanna,
2016; Smallwood & Schooler, 2006) was also considered in this array of
cognitive processing-boosting ability. Accordingly, in this theme, we
included measures of attention orientation/selection (e.g., ADHD-ASRS –
Inattention subscale), distractibility (e.g., CFQ – distractibility subscale and
CFQ – Total), switching from one task to another (e.g., BRIEF – Shifting
subscale), and mind-wandering (e.g., MAAS, Mind-Wandering scale).

The impulsiveness/inhibition theme pertained to the ability to inhibit
premature thoughts and actions, and difficulties with this ability can be
exhibited behaviorally in one’s tendency to seek additional stimulations and
take risks (Dalley et al., 2011; Dalley & Robbins, 2017). Here, we included
measures which were related to inhibition (BRIEF-Inhibition), behavior
impulsiveness (e.g., BIS, ADHD-ASRS – Hyperactivity/impulsivity subscale),
and sensation-seeking (e.g., SSS).

The memory theme pertained to the ability to retain information do
mental work with information in memory (e.g., Diamond, 2013). This ability
has been considered to be relatively independent to attentional regulation, yet
it has been considered to play an important role in executive functioning
(Diamond, 2013; Engle, 2002; Engle & Kane, 2004). In this meta-analysis, this
theme included measures of working memory (e.g., BRIEF – Working
memory subscale), memory failures (e.g., Memory Failures Scale), and gen-
eral cognitive failures (e.g., CFQ – Total score).

MEDIA PSYCHOLOGY 9

Lastly, the behavior regulation theme pertained to the set of abilities which
is related to the volitional control of action. According to one taxonomy of
executive function (BRIEF; Gioia et al., 2002; Huizinga & Smidts, 2010),
behavior regulation is an umbrella term which includes task-switching and
inhibition as well. However, as discussed above, task-switching appears to be
more related to attention regulation (e.g., Petersen & Posner, 2012) while
inhibition, which is more internally driven, appears to be more related to
impulsiveness and risk-taking (e.g., Dalley et al., 2011). Accordingly, we
categorized task-switching and inhibition in the attention regulation and
impulsiveness/inhibition categories, respectively. Thus, what remains in our
behavior regulation theme were abilities that relate to volitional control of
action which are driven by external demands and situational factors (e.g., see
Tsukayama, Duckworth, & Kim, 2013). This theme included measures of
self-control (e.g., Domain-specific Impulsivity in School-age Children4;
Personal Problem-solving Inventory – Self-control subscale), emotion regu-
lation (e.g., BRIEF – Emotion regulation subscale), and self-monitoring (e.g.,
BRIEF – Self monitoring subscale).

Note that while we sought out to minimize overlaps between the themes and
categorize the findings as accurately as possible, the categorization remained
somewhat arbitrary as different theoretical models of cognitive function would
have both overlaps and distinctions of different sets of cognitive ability (e.g., see
Chan et al., 2008). For each theme, a random-effect model and a pooled effect
size were calculated to provide estimates of the magnitude of the correlation.

Random-effect model
Since the current meta-analysis featured different rating scales and outcome
measures, we constructed a random-effect model to estimate the pooled
effect size. This model assumes that the different scales had comparable,
but not identical effect sizes which are distributed around some mean that
reflected the true effect (Borenstein et al., 2009). In our case, we assumed that
the different outcomes measured different subsets of cognitive functioning.
Thus, the effects might vary from one function to another.

The random-effect model was constructed in R (R Core team, 2015) using
the metafor package (Viechtbauer, 2010). To account for variance inflation of
the pooled effect size due to the dependency of multiple outcome measures
from one study, we calculated the robust variance estimation (RVE; Hedges,
Tipton, & Johnson, 2010). RVE works by estimating the correlations between
dependent outcome measures and adjusting the standard error of the pooled
effect size based on these correlations (Hedges et al., 2010; Scammacca,
Roberts, & Stuebing, 2013).

10 W. WIRADHANY AND J. KOERTS

Heterogeneity and risk of bias
When significant between-studies heterogeneity was detected, we performed
a moderator analysis and a risk of bias analysis. The moderator analysis
assesses whether the between-studies heterogeneity can be explained by
shared characteristics of different subgroups of studies (Hedges & Pigott,
2004).

The risk of bias analysis tested whether the heterogeneity was stemming
from bias coming from the level of precision in each study. Under a presence
of bias, it is common for studies with smaller sample sizes to show an
overestimation of effect sizes due to sampling errors compared with studies
with bigger sample sizes, a phenomenon called small-study effect (Sterne,
Gavaghan, & Egger, 2000). A small-study effect might indicate the presence
of publication bias, since other studies with smaller sample sizes showing
underestimation of the effect ended up not being published (Ioannidis, 2005;
Ioannidis, Munafò, Fusar-Poli, Nosek, & David, 2014). As a formal inspec-
tion of small-study effects, we conducted an Egger’s test (Egger, Davey Smith,
Schneider, & Minder, 1997), in which a simple linear regression with effect
sizes as a measure of magnitude of study effect and sample sizes or standard
errors as measures of study precision is constructed.

Results

Attention regulation

Random-effect model
Figure 2 shows a forest plot for a group of self-report scales which measured
the association between media multitasking and constructs related to the
ability to regulate attention. The scales categorized in this theme included
Attentional Control (AC)-switching (e.g., “I am slow to switch from one task
to another,” Carriere, Seli, & Smilek, 2013), Attentional Control (AC)-
distractibility (e.g., “I have difficulties concentrating when there is music in
the room around me”, Carriere et al., 2013), ADHD-ASRS – Inattention (e.g.,
“How often do you have difficulty concentrating on what people are saying
to you even when they are speaking to you directly?”, Kessler et al., 2005),
MW – Spontaneous (e.g., “I find my thoughts wandering spontaneously”,
Carriere et al., 2008), MW – Deliberate (e.g., “I allow my thoughts to wander
on purpose”, Carriere et al., 2008), MAAS – Lapses only (e.g., “I do jobs or
tasks automatically, without being aware of what I’m doing”, Brown & Ryan,
2003), ARCES (e.g.,“I have gone to the fridge to get one thing (e.g., milk) and
taken something else (e.g., juice),” Carriere et al., 2008), BRIEF-Shift (e.g., “I
get stuck on one topic or activity,” Gioia et al., 2002); CFQ – Distractibility,
also with CFQ – total score (e.g., “Do you read something and find you

MEDIA PSYCHOLOGY 11

haven’t been thinking about it and must read it again?,” Broadbent &
Cooper, 1982).

Overall, the pooled effect size of the correlates between media multitasking
and self-reported problems related to attention regulation was small, yet
statistically significant, z = .162, 95% CI [.160, .164], p < .001. At the same time, however, a significant heterogeneity between the effect sizes was detected, I2 = 86.76%, Q(21) = 118.93, p < .001.

Heterogeneity & risk of bias analysis
To address the heterogeneity in the model, we performed moderator analyses
with two moderators. First, we added sex, as indicated by the proportion of
females in the study samples as a moderator. Second, we added age, as
indicated by the mean age of the study samples as a moderator. The two
moderators did not contribute to the unexplained variance in the model, F(1,
17) = 2.59, p = .125; F(1, 11) = 3.08, p = .107, respectively, indicating that the
heterogeneity could not be explained by differences in sex, and age.

As for the risk of bias, the Egger’s test showed no relationship between
effect size and study precision, z = −1.46, p = .144. This indicates that under
the presence of heterogeneity, effect sizes were stable across different studies
with different sample sizes.

Figure 2. Forest plot of the effect sizes (Fisher’s z) for studies measuring the association between
media multitasking and attention regulation. Error bars indicate 95% confidence intervals of the
means. AC: Attentional Control scale; ADHD-ASRS: Attention Deficit/Hyperactivity Disorder Adult
Self Report Scale; ARCES: Attention-Related Cognitive Error Scale; BRIEF: Behavior Rating
Inventory of Executive Function; CFQ: Cognitive Failure Questionnaire; MAAS: Mindful
Awareness Attention Scale; MW: Mind-Wandering scale.

12 W. WIRADHANY AND J. KOERTS

Impulsiveness – inhibition

Random-effect model
Figure 3 shows a forest plot for a group of self-report scales which measured
the association between media multitasking and constructs related to impul-
siveness and/or inhibition. The scales categorized in this theme included
ADHD-ASRS – hyperactivity (e.g., “How often do you fidget or squirm
with your hands or your feet when you have to sit down for a long time?”,
Kessler et al., 2005), BIS (e.g. “I do things without thinking”, Patton et al.,
1995), BRIEF-Inhibit (e.g., “I do not think before doing,” Gioia et al., 2002),
SSS, also the brief version; B-SSS (e.g., “I sometimes like to do things that are
a little frightening”, Zuckerman, 1996), and RCsB (e.g., “Sharing passwords
with friends and colleagues”).

Overall, the pooled effect size of the correlates between media multitasking
and self-reported problems related to impulsiveness and/or inhibition was
small, yet statistically significant, z = .219, 95% CI [.218, .219], p < .001. The between-studies heterogeneity was low, I2 < .001%, Q(14) = 9.82, p = .775, indicating that the effect was consistent across different studies.

Memory

Random-effect model
Figure 4 shows a forest plot for a group of self-report scales which measured
the association between media multitasking and constructs related to mem-
ory. The scales categorized in this theme included BRIEF-Working Memory

Figure 3. Forest plot of the effect sizes (Fisher’s z) for studies measuring the association between
media multitasking and impulsiveness and/or inhibition. Error bars indicate 95% confidence
intervals of the means. ADHD-ASRS: Attention Deficit/Hyperactivity Disorder – Adult Self Report
Scales; B-SSS: Brief Sensation-Seeking Scale; BIS: Barratt Impulsiveness Scale; BRIEF: Behavior
Rating Inventory of Executive Function; RCsB: Risky Cybersecurity Behavior scale; SSS: Sensation-
seeking Scale.

MEDIA PSYCHOLOGY 13

(e.g., “I have trouble remembering things, even for a few minutes,” Gioia
et al., 2002), CFQ (e.g., “Do you find you forget people’s names?”, Broadbent
& Cooper, 1982), and MFS (e.g., “I forget what I went to the supermarket to
buy”, Carriere et al., 2008).

Overall, the pooled effect size of the correlates between media multitasking
and self-reported problems related to memory was small, yet statistically
significant, z = .158, 95% CI [.156, .161], p < .001. The between-studies heterogeneity was low, I2 = 16.49%, Q(4) = 4.67, p = .323, indicating that the effect was consistent across different studies.

Behavior regulation

Random-effect model
Figure 5 shows a forest plot for a group of self-report scales which measured
the association between media multitasking and constructs related to the
ability to regulate behavior. The scales categorized in this theme included
Emotional Control (e.g. “Has outburst for little reason”, Gioia et al., 2002),
BRIEF-Initiate (e.g., “I need to be told to begin a task even when willing”),

Figure 4. Forest plot of the effect sizes (Fisher’s z) for studies measuring the association between
media multitasking and memory. Error bars indicate 95% confidence intervals of the means.
BRIEF: Behavior Rating Inventory of Executive Function; CFQ: Cognitive Failures Questionnaire;
MFS: Memory Failures Scale.

Figure 5. Forest plot of the effect sizes (Fisher’s z) for studies measuring the association between
media multitasking and behavior regulation. Error bars indicate 95% confidence intervals of the
means. BRIEF: Behavior Rating Inventory of Executive Function; DISC: Domain-specific Impulsivity
in School-age Children; PPSI: Personal Problem-solving Inventory.

14 W. WIRADHANY AND J. KOERTS

BRIEF-Organization of Materials (e.g., “I cannot find things in room or
school desk”), Plan/Organize, (e.g., “I become overwhelmed by large assign-
ments”), BRIEF-Self-monitor (e.g. “I am unaware of how my behavior affects
or bothers others”), BRIEF-Task-Monitor (e.g., “I make careless errors”),
DiSC (e.g., “I interrupted other people” Tsukayama et al., 2013), and PPSI-
Personal control (e.g., “Sometimes I do not stop and take time to deal with
my problems, but just kind of muddle ahead” Heppner & Petersen, 1982).

Overall, the pooled effect size of the correlates between media multitasking
and self-reported problems related to behavior regulation was small, yet
statistically significant, z = .192, 95% CI [.190, .193], p < .001. The between- studies heterogeneity was low, I2 = 6.67%, Q(8) = 5.69, p = .683, indicating that the effect was consistent across different studies.

General discussion

In this meta-analysis, we examined the correlates of media multitasking
behavior with different domains of everyday cognitive functioning in a series
of mini meta-analysis. The effect sizes were categorized into different themes
reflecting different domains of everyday cognitive functioning, based on the
similarities and dissimilarities between the reflected constructs. Overall, the
effect sizes can be categorized into four distinct themes. Pooled together,
frequent media multitasking had weak, but significant associations with
a decrease of attention regulation (z = .16), lower levels of inhibition/higher
levels of impulsiveness (z = .22), an increase of memory problems (z = .16), and
a decreased behavior regulation (z = .19).

Regarding the association between media multitasking and attention reg-
ulation, we found that heavy media multitasking was associated with higher
frequency of mind-wandering, higher distractibility, and more problems with
task switching. With regard to mind-wandering, this finding was somewhat
consistent with other findings in the literature which used objective mea-
sures. In an experiment in which participants were asked to memorize
materials from a video-recorded lecture, Loh et al. (2016) found that heavy
media multitaskers retained less information from the lecture, and this effect
could be explained by the increased tendency to mind-wander in this group.
However, at least one study showed a null correlation between media multi-
tasking and mind-wandering: heavy media multitaskers performed worse in
a metronome-response task, but they did not show a tendency to have
increased mind-wandering during the experiment (Ralph et al., 2015). With
regard to distractibility, other studies which used objective measures showed
that, for instance, heavy media multitaskers were less able to filter out
irrelevant information from their immediate environment (Cain & Mitroff,
2011; Ophir et al., 2009). However, a recent meta-analysis (Wiradhany &
Nieuwenstein, 2017) has shown that other studies have failed to replicate this

MEDIA PSYCHOLOGY 15

finding. Lastly, with regard to task-switching, other studies using objective
tests showed mixed evidence for the correlation between media multitasking
and task switching. Some studies found a negative correlation between media
multitasking and task performance (Ophir et al., 2009; Wiradhany &
Nieuwenstein, 2017, Exp., p. 1), others found positive correlations
(Alzahabi & Becker, 2013), yet others found null results (see Wiradhany &
Nieuwenstein, 2017, for a meta-analysis). Thus, it can be said that while
frequent media multitasking is associated with more problems with atten-
tional control in everyday situations, media multitasking might not directly
influence one’s ability to regulate attention, as measured by objective tests,
per se.

Heavier media multitasking was associated with increased impulsiveness/
decreased inhibition; heavier media multitaskers were associated with higher
scores in impulsiveness traits and they reported more (severe) symptoms of
hyperactivity/impulsivity. Heavier media multitasking was also associated
with higher scores in other traits which are related to impulsiveness, such
as sensation-seeking and risk-taking (Dalley et al., 2011; Whiteside & Lynam,
2001). This finding was consistent with findings using objective measures.
For instance, heavy media multitaskers were more likely to choose smaller,
immediate rewards instead of later, larger ones and they endorsed intuitive,
but incorrect answers of the Cognitive Reflection Test (Schutten et al., 2017).
Additionally, another study indicated that HMMs scored lower in a fluid
intelligence test due to them giving up earlier in the test (Minear et al., 2013).
Individuals with higher levels of sensation-seeking trait are characterized by
a higher stimulation threshold for optimal behavioral performance (Hoyle,
Stephenson, Palmgreen, Lorch, & Donohew, 2002; Zuckerman, 2007) and
a higher likelihood to act prematurely without foresight, which at times lead
to risk-taking behaviors (Dalley et al., 2011; Hoyle et al., 2002; Zuckerman,
2007). Indeed, consuming multiple streams of information has been shown
to promote a higher level of engagement (Bardhi, Rohm, & Sultan, 2010;
Wang & Tchernev, 2009) and to provide gratifications (Hwang, Kim, &
Jeong, 2014) which together provide stimulations for those who seek them.
Accordingly, people with higher levels of sensation-seeking and risk-taking
might media multitask to seek for additional stimulations.

Heavier media multitasking was associated with increased problems
related to memory. In this regard, one study using an objective measure,
namely a change-detection task has shown that HMMs had difficulties
retaining specific information in working memory, regardless of the presence
of distractors, and importantly, they performed more poorly in a later long-
term memory test for both relevant and irrelevant objects compared to
LMMs (Uncapher et al., 2016; but see Wiradhany, van Vugt, &
Nieuwenstein, 2019 for null results). Other studies have shown that
HMMs, compared to LMMs performed worse in a complex working memory

16 W. WIRADHANY AND J. KOERTS

test (Sanbonmatsu et al., 2013) and an N-back test (Cain et al., 2016; Ophir
et al., 2009; Ralph & Smilek, 2016; but see Cardoso-Leite et al., 2015;
Wiradhany & Nieuwenstein, 2017 for null results).

Lastly, regarding the association between media multitasking and behavior
regulation, we found that heavier media multitaskers had more difficulties to
adjust their thoughts, emotions, and actions to the situational demands. This
finding is in line with its counterpart in objective tasks, where studies have
found that HMMs performed worse in tasks in which they have to respond
to different cue-probe contingencies, such as the AXE-CPT task (Ophir et al.,
2009; Wiradhany & Nieuwenstein, 2017; but see Cardoso-Leite et al., 2015
for null results). However, there were mixed findings with regard to perfor-
mance of HMMs in a change-detection task in which distractor filtering was
involved, with one study showed that HMMs performed worse (Ophir et al.,
2009), while other, recent ones showed null findings (Cardoso-Leite et al.,
2015; Uncapher et al., 2016; Wiradhany & Nieuwenstein, 2017; Wiradhany
et al., 2019).

Collectively, we witnessed a discrepancy between the findings in this meta-
analysis and the findings in a previous meta-analysis (Wiradhany &
Nieuwenstein, 2017). In this meta-analysis, we found overall weak, but stable-
pooled correlations between media multitasking and self-reports of cognitive
functioning in everyday situations whereas in the previous meta-analysis, we
found an overall weak-pooled correlation, but the correlation became null
upon corrections. This discrepancy, as we previously mentioned, might exist
for several reasons. First, performance-based measures might capture some,
but not all aspects of everyday cognitive functioning. Consider the tests for
one’s ability to regulate attention, for instance. One group of researcher may
assess attention regulation using the perspective of mind-wandering to inves-
tigate the waxing and waning of attention (e.g., Christoff et al., 2016). Yet,
others assess attention regulation using the perspective of divided attention
(e.g., Moisala et al., 2016). The two perspectives might cover some, but not all
aspects of attention regulation, and in everyday situations one might need to
suppress both mind-wandering and distraction to regulate attention
properly. Second, performance-based measures are often designed to assess
one’s ability at a pathological level (Chan et al., 2008). For instance, as
a diagnostic tool to inquire whether one’s ability to regulate attention is clearly
impaired. Therefore, one interpretation of the weak correlations across all
themes would be that media multitasking behavior is associated with the
increased number of everyday problems related to cognition, but this does
not mean that media multitasking is associated with the presence of an
impairment in cognitive abilities. The weak correlations between media multi-
tasking and everyday cognitive functioning as shown in self-reports suggest
that performance-based measures might not be adequately sensitive to detect
everyday cognitive problems in media multitaskers.

MEDIA PSYCHOLOGY 17

Notes

on causality

Media multitasking behavior might precede, occur as a consequence, or have
a reciprocal relationship with everyday cognitive functioning. Currently, this
meta-analysis does not allow for disentangling the causal relationship
between the two. Preceding problems with cognition, media multitasking
behavior may promote a specific mode of processing information in the
environment (Lin, 2009. Specifically, heavy media multitaskers might develop
a breadth-biased focus of attention, due to constant exposures to media-
saturated environments. That is, they prefer to skim a large quantity of
information rather than deeply processing a small amount of information.
Consequently, adopting this mode of information processing might lead
media multitaskers to apply cognitive control processes such as thought-
monitoring and attention regulation less strictly. This might have profound
consequences. In an fMRI study; Moisala et al. (2016) found that in addition
to worse task performance in which participants had to attend to sentences in
one modality (e.g. auditory) while they had to ignore distractor sentences
presented in another modality (e.g. visual), HMMs, compared to LMMs also
have higher activations in the right superior and medial frontal gyri, and the
medial frontal gyrus. Increased activations in these areas have been linked to,
among others, increased top-down attentional control. Therefore, heavy
media multitaskers might require more effort in filtering distracting informa-
tion than light media multitaskers. Alternatively, it could also be the case that
media multitasking behavior leads to overreliance of exogenous control of
attention (i.e. from incoming notifications from media; Ralph et al., 2013).
Consequently, heavy media multitaskers train their endogenous control less
often and thus, experience more problems related to cognitive control.

Media multitasking behavior might also occur as a consequence of existing
problems with cognition. People with ADHD and people with problems with
behavior regulation and metacognition are more easily distracted and therefore
have a higher propensity to media multitask. Similarly, people with high levels
of sensation-seeking are more inclined to media multitask for stimulation-
seeking purposes. Relatedly, indicating that excessive media multitasking beha-
vior might be a result from a preexisting condition, studies have also shown
that individuals with smaller grey matter volumes in the Anterior Cingulate
Cortex (ACC) – a brain region which has been shown to be more active during
error and conflict detections (Botvinick, Braver, Barch, Carter, & Cohen, 2001;
Botvinick, Cohen, & Carter, 2004) – reported higher levels of media multi-
tasking (Loh & Kanai, 2014). Similarly, the increased activations of the brain
areas associated with top-down control in heavy media multitaskers (Moisala
et al., 2016) might also indicate that these areas function less efficiently in
heavy media multitaskers, compared to light media multitaskers.

18 W. WIRADHANY AND J. KOERTS

Lastly, media multitasking behavior might have a reciprocal relationship
with problems with cognition and vice versa. On this reciprocity, several
longitudinal studies have attempted to examine whether media multitasking
behavior and everyday-related problems are reinforcing each other over
a longer time period. The results of these studies showed that media multi-
tasking did not appear to have a reciprocal relationship with the occurrence
attentional problems (Baumgartner, van der Schuur, Lemmens, & Te Poel,
2017) 3 and 6 months later. Nevertheless, these studies showed that the
associations between media multitasking and attentional problems were
stable over time. That is, the correlation remained significant during the
first, second, and third periods of data collection. Together, this might
indicate that individuals have a stable level of media multitasking behavior
over time and similarly, the occurrence of some everyday-related problems is
also stable over time.

Limitation and future directions

The findings in our set of mini-meta-analyses are limited in several ways.
First, while the effects found in different groups of findings were somewhat
reliable across different studies, critically, the overall pooled effects were
weak, with z ranging from .16 to .22. Thus, most of the variance underlying
the media multitasking behavior is still unaccounted for. Additionally, while
we refer to the literature, our categorization of effect sizes remained some-
what subjective. This subjectivity might introduce bias and or contribute to
our level of within-theme heterogeneity. We witnessed a high level of hetero-
geneity in the attention regulation theme, and this high heterogeneity could
not be explained by our moderators. Arguably, this high level of heteroge-
neity might be driven by the effect sizes related to CFQ, which dimension-
ality is still being argued for in recent studies (e.g., Bridger et al., 2013). It
might be that the null and negative correlations in the CFQ-related effect
sizes were driven by the other dimensions of CFQ.

Third, the current meta-analysis focuses on studies pertained to everyday
cognitive functioning. However, media multitasking studies have gone
beyond the cognition-related themes, as some studies have investigated the
correlates between media multitasking and depression (Becker, Alzahabi, &
Hopwood, 2013), anxiety (Becker et al., 2013; Hatchel et al., 2018), creativity
and imagination (Duff et al., 2014), and well-being (Pea et al., 2012; Shih,
2013; Xu, Wang, & David, 2016). With regards to depression and anxiety,
heavy media multitasking was correlated with more (severe) depressive and
anxiety symptoms (Becker et al., 2013; Hatchel et al., 2018). This finding was
somewhat consistent with a recent nation-wide study which also showed that
individuals who use multiple social media platforms in daily life had higher
odds of having increased levels of depression and anxiety (Primack et al.,

MEDIA PSYCHOLOGY 19

2017). Furthermore, media multitasking was negatively correlated with ima-
gination, but it was positively correlated with creativity (Duff et al., 2014).
Lastly, the correlations between media multitasking and well-being were
somewhat mixed. In a large-scale study which involved 3461 8-12-year-old
girls, Pea et al. (2012) found that media multitasking was positively corre-
lated with social success, but it was negatively correlated with normalcy
feelings, positive feelings, and social stress. Shih (2013) found that media
multitasking was not correlated with well-being as assessed using two ver-
sions of self-report questionnaires which focused on well-being. While part
of these findings was discouraging, suggesting that media multitasking beha-
vior might have potential ramifications on other aspects of everyday func-
tioning beyond cognition, the other part, namely the positive correlations
with social success and creativity suggests that media multitasking behavior
might be beneficial as well. It could be interesting for future studies to further
examine the adaptive values of everyday media multitasking behavior, espe-
cially given that several longitudinal studies have indicated that media multi-
tasking behavior is stable over time (Baumgartner, van der Schuur et al.,
2017; van der Schuur et al., 2018).

Fourth and lastly, since all findings we synthesized in the meta-analysis
were correlational, it is still an open question whether media multitasking
behavior leads to, is an effect, or have a reciprocal relationship with the
occurrence of cognitive problems in everyday situations. Futures studies
might be interested in disentangling this association in a more controlled
manner.

Conclusion

In a series of mini meta-analyses, we categorized the correlates between
media multitasking and everyday cognitive functioning, as assessed using
self-reports, in four different themes. Heavier media multitasking was asso-
ciated with increased of levels of self-reported problems with attention
regulation, behavior regulation, impulsiveness/inhibition, and memory.
Together, media multitasking appears to be correlated with increasing pro-
blems everyday cognitive functioning. However, the overall small effects were
small, a high level of heterogeneity was detected in one theme, and a large
proportion of variance of media multitasking behavior is still unaccounted
for. Additionally, since most studies reported correlations, the causality
direction is still unclear.

Notes

1. To ensure that all possible relevant results have been included in the meta-analysis, in
addition to these keywords, we performed a search using more general keywords,

20 W. WIRADHANY AND J. KOERTS

namely media multitask* AND (cognition OR emotion OR trait). This search yielded no
additional results. Lists of the references found using our search terms can be found in
the supplementary materials of this article.

2. The author was contacted for requesting the relevant zero-order correlations not
reported in the article. Unfortunately, due to unforeseen circumstances, the original
dataset was no longer available. Nevertheless, we are thankful to Dr. Shui-I Shih for her
cooperation.

3. Two of the studies (Baumgartner, van der Schuur, et al., 2017) were longitudinal
studies with three waves each. All study waves were included (see Table 1).

4. Note that while this measure has impulsivity on its name, the scale was intended to
measure how an individual may act (e.g., suppressing their impulse) in situational
contexts (Tsukayama et al., 2013, p. 880). These authors also proposed a distinction
between domain-specific impulsivity, which is externally driven and measured by their
scale and domain-general impulsivity, which is more internally driven and measured by
other impulsivity scales such as the BIS.

Acknowledgments

This article was written as a part of the Ph. D. project of the first author, which is funded by
the Endowment Fund for Education (LPDP), Ministry of Finance, the Republic of Indonesia.
We thank Prof. Pedro Cardoso-Leite and Dr. Melina Uncapher for providing us additional
data regarding their ADHD findings.

Disclosure statement

No potential conflict of interest was reported by the authors.

Funding

This work was supported by the Indonesia Endowment Fund for Education;

ORCID

Wisnu Wiradhany http://orcid.org/0000-0001-8707-3146
Janneke Koerts http://orcid.org/0000-0002-2317-0171

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• Abstract

Correlates of media multitasking
The current study
Methods
Study selection
Effect size selection and calculation
Analysis
Categorization of findings
Random-effect model
Heterogeneity and risk of bias

Results
Attention regulation
Random-effect model
Heterogeneity & risk of bias analysis
Impulsiveness– inhibition
Random-effect model
Memory
Random-effect model
Behavior regulation
Random-effect model

General discussion
Notes on causality
Limitation and future directions
Conclusion
Notes
Acknowledgments
Disclosure statement
Funding
References

1

ECON 317 SPRING 2010 – INDIVIDUAL ASSIGNMENT 1

TO BE SUBMITTED VIA COURSESPACES BY 11:59 PM ON JANUARY 21st, 2020

Name (First, Family)

Last 3 digits of SID

TO SPEED UP MARKING, PLEASE ANSWER THE QUESTIONS IN THE FORMS AND SPACES PROVIDED. THE T.A. RESERVES THE RIGHT TO NOT MARK ANY QUESTIONS THAT ARE NOT ANSWERED IN THE EXPECTED LOCATIONS.

By submitting this assignment you agree to the following honor code, and understand that any violation of the honor code may lead to penalties including but not limited to a non-negotiable mark of zero on the assignment:

Honor Code: I guarantee that all the answers in this assignment are my own work. I have cited any outside sources that I used to create these answers in correct APA style.

Marking scheme –
Make sure you answer all the questions before handing this in
!

Question

Marks

1

a

12

2

a

3

b

3

3

a

3

Total

21

1. [Critique] Read the following article:

Marchildon, G. P. & Allin, S. (2016). The Public-Private Mix in the Delivery of Health-Care Services: Its Relevance for Lower-Income Canadians. Global Social Welfare, 3, pp. 161-170. Retrieved from https://link-springer-com.ezproxy.library.uvic.ca/article/10.1007%2Fs40609-016-0070-4

(The above link allows you to access the article for free whether you are on campus or not. If off-campus, log in to UVic when prompted.)

a. Write a 3-2-1 report on the article using the form provided on the course web site. (12 marks)

A note about 3-2-1 reports in this course:

For the ‘2’ part (2 things you didn’t understand and what you did to fix it), we need to see both what you found out, and the source you used to find that out, properly cited in APA format.

The paper you are asked to read for the assignment CANNOT be used as the source: it’s understood that you will make sure to understand everything within the article you are asked to read, by consulting the article itself. This part of the 3-2-1 report is meant to encourage you to consult outside sources to find things out that you CANNOT find out from the article itself.

While I would prefer that you use sources that, unlike Wikipedia, aren’t subject to constant editing and change, it’s fine to use Wikipedia or other such sources as long as you also include the date and time of access, so that readers can look up the state of the page as it was when you looked at it. (So, you’d add to the standard ‘Retrieved from’ part, ‘on January 3, 2020 at 11:59 AM’.)

Also, remember to include a summary, in your own words, of what you found. It’s not enough to say, ‘I didn’t know what a raccoon was, so I looked it up on Wikipedia.’ You need to tell us what you discovered about raccoons,
in your own words
, and you need to cite the source you looked the information up on.

2. [Theory] A 2016 article[footnoteRef:0] begins, “Extra-billing in Ontario, private MRIs in Saskatchewan and user fees in Quebec: violations of the Canada Health Act are on the rise across the country.” [0: Meili, R. (2016, April 4). It’s Time For The Federal Government To Enforce The Canada Health Act. The Huffington Post. Retrieved from http://www.huffingtonpost.ca/ryan-meili/canada-health-act_b_9610424.html
]

a. What pillar(s) of the Canada Health Act is/are violated by private MRIs in Saskatchewan, and in what way? Be specific. (3 marks)

Pillar(s) Violated: ___________________________________________________

Reasoning: _________________________________________________________

b. What pillar(s) of the Canada Health Act is/are violated by user fees for health care in Quebec, and in what way? Be specific. (3 marks)

Pillar(s) Violated: ___________________________________________________
Reasoning: _________________________________________________________

3. [Mini Meta Analysis] This is a simple question meant to help you understand what is expected of you in the group project. Group Assignment 1, due on January 31, will ask you to conduct a search for articles to use in your own mini meta analysis. This question asks you to familiarize yourself with how such searches are reported in published, peer-reviewed mini meta-analyses.

Start by accessing the following article:

Wiradhany, W. & Koerts, J. (2019). Everyday functioning-related cognitive correlates of media multitasking: a mini meta-analysis. Media Psychology. Retrieved from https://doi.org/10.1080/15213269.2019.1685393

(The article is open-access, so you should have no trouble accessing it, whether on or off campus.)

a. (3 marks) The published mini meta-analysis searched for studies in PsycInfo, ERIC, MEDLINE, SocINDEX, CMMC and DOAJ. For this question, use the search methods listed in the ‘Study selection’ section of the mini meta analysis to search for articles fitting the search criteria in Google Scholar ( https://scholar.google.ca/ ). Google Scholar is a very useful tool that searches through peer-reviewed academic literature.

In the space below, cite, in APA format, the first study in your search results that fits the criteria specified in the mini meta analysis. (Hint: This question can be answered VERY quickly. The method described in the very first paragraph of the ‘study selection’ section, on pages 4 and 5, should be enough for this assignment question – just make sure your top result is a study, and not a summary of studies, such as a review article, systematic summary or meta-analysis, and that it studies media multitasking, rather than just media OR multitasking.)