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\articletype{ARTICLE}
\jname{Journal of Child Language}
\jyear{2024}
\jvol{0}
%\jissue{1}
\jdoi{10.1017/S0000000020000010}

\copyrightline{\textcopyright\ The Author(s) 2024. This is an Open Access article, distributed under the terms of the Creative Commons Attribution licence (\url{http://creativecommons.org/licenses/by/4.0/}), which permits unrestricted re-use, distribution, and reproduction in any medium, provided the original work is
properly cited.}


\begin{document}


\begin{Frontmatter}

\title[Trends in the use of care among people aged 65-85 with cognitive impairment in the Netherlands]{Trends in the use of care among people aged 65--85 with cognitive impairment in the Netherlands}

\author*[1,2]{Mari Aaltonen\corresp{\email{mari.s.aaltonen@uta.fi}}}
\author[1,3]{Jani Raitanen}
\author[4]{Hannie Comijs}
\author[5]{Marjolein Broese van Groenou}

\authormark{Mari Aaltonen \textit{et al.}}



\address[1]{\orgname{Faculty of Social Sciences and Gerontology Research Center}, \orgname{University of Tampere}, \orgaddress{\city{Tampere}, \country{Finland}}}
\address[2]{\orgdiv{Institute for Advanced Social Research}, \orgname{University of Tampere}, \orgaddress{\city{Tampere}, \country{Finland}}}
\address[3]{\orgdiv{UKK-Institute for Health Promotion Research}, \orgaddress{\city{Tampere}, \country{Finland}}}
\address[4]{\orgdiv{Department of Psychiatry, Amsterdam Public Health
Research Institute}, \orgname{VU University Medical Centre and GGZ inGeest}, \orgaddress{\city{Amsterdam}, \country{The Netherlands}}}
\address[5]{\orgdiv{Department of Sociology}, \orgname{Vrije Universiteit Amsterdam}, \orgaddress{\city{Amsterdam}, \country{The Netherlands}}}

\received{04 May 2024}
\revised{10 May 2024}
\accepted{12 May 2024}

\abstract{Observation of long-term trends within countries is needed to increase insight into how
policy initiatives are reflected in the use of care over time in addition to individual determinants
of care use. In the past decades, Dutch care policies have favoured homecare and
reduced the availability of institutional care which extended the care responsibilities of formal
and informal care-givers at home. This study investigates the changes in the use of
informal and formal homecare, community services and residential care among cognitively
impaired older adults over time in the Netherlands. In addition, of special interest
here are the associations of the presence of a spouse, other family members or social network
with care use, and the interdependency between the use of different types of care.
The study employs the Longitudinal Aging Study Amsterdam (LASA) covering the
years 1992--2012, analysed with generalised estimating equations. The data consisted of
1,022 observations gathered from 813 respondents aged 65--85. The respondents were cognitively
impaired according to the age- and education-standardised Mini-Mental State
Examination score. The analyses took into account several individual determinants of
care use. The use of informal care and residential care decreased while the use of formal
homecare and community services remained the same. Simultaneously, the proportion of
those who did not use the studied care types increased. The contribution of partners in
informal care decreased. Informal care and formal homecare use increasingly became
complementary services}

\keywords{cognitive impairment; homecare services; informal care; residential care; trends, Longitudinal
Aging Study Amsterdam (LASA)}

\JEL{Q11; Q12; D81; M31}

\MSC{11J82; 11Y60; 33C20; 33C60}

\Abbrtn{AF: aerobic fitness, PTH: parathyroid hormone}


\end{Frontmatter}

\section{Introduction}
Let $M$ be an $n$-dimensional smooth compact Riemannian manifold with boundary \hbox{$\Sigma=\partial M$}.  The Steklov
eigenvalue problem on $M$ consists in finding all numbers $\sigma\in\mathbb{R}$ for which there exists a nonzero function $u \in C^\infty(M)$, which solves
\begin{equation}
        \Delta u = 0 \quad \text{in  $M$,}
%%        \partial_\nu u = \sigma u & \text{on  $\Sigma$.}
\end{equation}
Here, $\Delta$ is the Laplacian induced from the Riemannian metric $g$ on $M$, and $\partial_\nu$
is the outward pointing normal derivative along the boundary $\Sigma$. The Steklov eigenvalues
form an unbounded increasing sequence
$0 = \sigma_0 \leq \sigma_1 \leq \sigma_2 \leq \dots \to \infty$, each of which is repeated according to its multiplicity.
Note that if $M$ is connected, then $\sigma_1>0$.

Presidential scholars have long emphasised the role of the executive branch in
federal policymaking. Presidents develop policies formally through unilateral
action, but they also pursue their objectives in the legislative arena. Governors fill an
analogous role within their states. They manage the bureaucracy and help set the
policy agenda through speeches, calling special sessions or taking unilateral action.
I analyse factors that explain gubernatorial use of executive orders, and I consider how
these same executive orders influence statute adoption, using lesbian, gay, bisexual and
transgender (LGBT) employment protections as an illustrative case. Presidential scholars have long emphasised the role of the executive branch in
federal policymaking. Presidents develop policies formally through unilateral
action, but they also pursue their objectives in the legislative arena. Governors fill an
analogous role within their states. They manage the bureaucracy and help set the
policy agenda through speeches, calling special sessions or taking unilateral action.
I analyse factors that explain gubernatorial use of executive orders, and I consider how
these same executive orders influence statute adoption, using lesbian, gay, bisexual and
transgender (LGBT) employment protections as an illustrative case.

Presidential scholars have long emphasised the role of the executive branch in \cite{barclay03}
federal policymaking. Presidents develop policies formally through unilateral
action, but they also pursue their objectives in the legislative arena. Governors fill an
analogous role within their states. They manage the bureaucracy and help set the
policy agenda through speeches, calling special sessions or taking unilateral action.
I analyse factors that explain gubernatorial use of executive orders, and I consider how
these same executive orders influence statute adoption, using lesbian, gay, bisexual and
transgender (LGBT) employment protections as an illustrative case. Presidential scholars have long emphasised the role of the executive branch in
federal policymaking. Presidents develop policies formally through unilateral
action, but they also pursue their objectives in the legislative arena. Governors fill an
analogous role within their states. They manage the bureaucracy and help set the
policy agenda through speeches, calling special sessions or taking unilateral action.
I analyse factors that explain gubernatorial use of executive orders, and I consider how
these same executive orders influence statute adoption, using lesbian, gay, bisexual and
transgender (LGBT) employment protections as an illustrative case. They manage the bureaucracy and help set the
policy agenda through speeches, calling special sessions or taking unilateral action.
I analyse factors that explain gubernatorial use of executive orders, and I consider how
these same executive orders influence statute adoption, using lesbian, gay, bisexual and
transgender (LGBT) employment protections as an illustrative case.

Once data are disseminated, whatever contractual or other obligations are placed on those receiving \cite{berry90,berry99} the
data, the data are effectively out of a data providers' control. Data providers must be certain that the data
disseminated do not provide a risk of disclosure necessitating a reduction in the detail available, or they are
constrained to using a resource intensive auditing regime, and are likely to discover any data misuse only
after it has happened. Once data are disseminated, whatever contractual or other obligations are placed on those receiving the
data, the data are effectively out of a data providers' control. Data providers must be certain that the data
disseminated do not provide a risk of disclosure necessitating a reduction in the detail available, or they are
constrained to using a resource intensive auditing regime, and are likely to discover any data misuse only
after it has happened.

Presidential scholars have long emphasised the role of the executive branch in
federal policymaking. Presidents develop policies formally through unilateral
action, but they also pursue their objectives in the legislative arena. Governors fill an
analogous role within their states. They manage the bureaucracy and help set the
policy agenda through speeches, calling special sessions or taking unilateral action.
I analyse \nobreak factors that explain gubernatorial use of executive orders, and I consider how
these same \nobreak executive orders influence statute adoption, using lesbian, gay, bisexual and
transgender (LGBT) employment protections as an illustrative case. Presidential scholars have long emphasised the role of the executive branch in
federal\footnote{Governor Kate Brown of Oregon became governor in 2015, making her the first governor in the United
States to be openly LGBT while in office.} policymaking.

\section{Gubernatorial and presidential use of executive orders across the various states}

Presidents develop policies formally through unilateral
action, but they also pursue their objectives in the legislative arena. Governors fill an
analogous role within their states. They manage the bureaucracy and help set the
policy agenda through speeches, calling special sessions or taking unilateral action.
I analyse factors that explain gubernatorial use of executive orders, and I consider how
these same executive orders influence statute adoption, using lesbian, gay, bisexual and
transgender (LGBT) employment protections as an illustrative case.


\subsection{Presidential use of executive orders is largely consistent with expectations and previous literature}

The remainder of the findings is largely consistent \cite{berry98} with expectations and previous
literature. Diffusion plays a positive role on states adopting sexual orientation\footnote{The courts and various agencies also create their own form of policy. However, I focus primarily on executive orders and
their influence on statute adoption for this article.}
protections; yet, it is not statistically significant in explaining the adoption of
transgender-inclusive statutes. As anticipated, legislatures are more likely to adopt
both forms of legislation in states where the citizens are more liberal.


\subsubsection{Third level heading with two line text style format with two line text style format  with two line text style format}

They manage the bureaucracy and help set the
policy agenda through speeches, calling special sessions or taking unilateral action.
I analyse factors that explain gubernatorial use of executive orders, and I consider how
these same executive orders influence statute adoption, using lesbian, gay, bisexual and
transgender (LGBT) employment protections as an illustrative case.
The descriptive statistics were adjusted for age and gender, using analysis of variance in
every time period so that the changes in care use between the observation years would
not reflect age and gender differences in different time periods but rather the differences
between them.

\section*{Results}

\subsection*{Determinants of executive orders}

The probability
of a state adopting legislation protecting \cite{boehmke09} sexual orientation increases by a
factor of 1.11 for a one-unit increase in Liberal Citizen Ideology, and the probability
increases by a factor of 2.24 for a five-unit increase in citizen ideology. This effect is
even more pronounced for transgender protections. A one-unit increase in Liberal
Citizen Ideology increases the likelihood of adoption by a factor of 1.20, and the
probability increases by a factor of 2.44 for a five-unit increase in citizen ideology.
The findings regarding the Evangelical population hint at a similar conclusion.


\subsection*{Measurements}

\subsubsection*{Outcome variables}

A one-unit increase in Liberal
Citizen Ideology increases the likelihood of adoption by a factor of 1.20, and the
probability increases by a factor of 2.44 for a five-unit increase in citizen ideology.
The findings regarding the Evangelical population hint at a similar conclusion. A one-unit increase in Liberal
Citizen Ideology increases the likelihood of adoption by a factor of 1.20, and the
probability increases by a factor of 2.44 for a five-unit increase in citizen ideology.
\begin{unenumerate}
\item Phase 1: acute fever with enlargement of the spleen and liver;
\item Phase 2: acute enlargement of the spleen and liver, with a low fever;
\item Phase 3: cachexia, with no fever.
\end{unenumerate}
 A one-unit increase in Liberal
Citizen Ideology increases the likelihood of adoption by a factor of 1.20, and the
probability increases by a factor of 2.44 for a five-unit increase in citizen ideology (\weblink{Figure}{fig1}).



\section*{Estimation}

Using Multilevel Event History Analysis, with the state/year as the unit of analysis \cite{bolton15},
I evaluate the following:
\begin{enumerate}[2.]
\item The probability that a governor $i$ will issue an executive order protecting
LGBT employees in time $t$, given that no executive order is in place.

They manage the bureaucracy and help set the
policy agenda through speeches, calling special sessions or taking unilateral action.
\item The probability that the state legislature $i$ will adopt an LGBT-inclusive
employment nondiscrimination statute in time $t$, given that it has not
already done.
\end{enumerate}


\begin{figure}[!t]%
\FIG{\includegraphics[width=0.9\textwidth]{Fig}}
{\caption{This is a widefig. This is an example of long caption this is an example of long caption  this is an example of long caption this is an example of long caption.\fignote{\textit{Note:} All proportions are adjusted for the predisposing, enabling and need variables.}}\label{fig1}}
\end{figure}

\begin{figure}[!t]%
\FIG{\includegraphics[width=0.9\textwidth]{Fig}}
{\caption{This is an example of short caption this is an example of short caption.}
\label{fig2}}
\end{figure}


\noindent Multilevel modelling accounts for these differences and within-state patterns of adoption seen
throughout the years \cite{brewer07}. The effect of determinants that
lead to successful statute adoption of LGBT protections share common elements,
but differ based on the type of protections added – sexual orientation versus gender
identity in \weblink{Figure}{fig2}.
\begin{itemize}
\item The probability that a governor $i$ will issue an executive order protecting
LGBT employees in time $t$, given that no executive order is in place.

They manage the bureaucracy and help set the
policy agenda through speeches, calling special sessions or taking unilateral action.
\item The probability that the state legislature $i$ will adopt an LGBT-inclusive
employment nondiscrimination statute in time $t$, given that it has not
already done.
\begin{itemize}
\item The elderly living independently with a spouse enjoy greater subjective wellbeing
than those co-resident with their adult children, and this is more likely
to be the case for the elderly in Hong Kong than for those in mainland
China and Taiwan.
\item The presence of grandchildren is associated with the elderly's subjective wellbeing
to a lesser degree in Hong Kong than in mainland China and Taiwan
\end{itemize}
\end{itemize}
Multilevel modelling accounts for these differences and within-state patterns of adoption seen
throughout the years. The effect of determinants that
lead to successful statute adoption of LGBT protections share common elements,
but differ based on the type of protections added – sexual orientation versus gender
identity.
\begin{quote}
Consequently, governors
may elect to pursue legislation to adopt more expansive and enduring policies by
negotiating with the legislators first. Governors that see legislation as likely to pass
in the legislature, or governors with weaker institutional powers to dictate
administration policies, are especially likely to take this approach.
\end{quote}
A one-unit increase in Liberal
Citizen Ideology increases the likelihood of adoption by a factor of 1.20, and the
probability increases by a factor of 2.44 for a five-unit increase in citizen ideology. In addition to individual determinants of care, the allocation of care can also change
over time.


Executive orders
become appealing once more if efforts in the legislature fail because of a stalemate
or changing partisan dynamics later in the executive's tenure in \weblink{Table}{tab1}. This leads to the
following hypotheses:
\begin{description}[Alan:]
\item[LM:] I would like to ask you how you feel about your leg.
\item[Alan:] About what?
\item[LM:] Your leg.
\item[Alan:] What about it? Alright … Why? What’s up with it?
\end{description}
The final hypotheses test the strategic model applied to the state level, which asserts
that governors are more likely to issue executive orders when confronting unfavourable
political conditions in the legislature.
\begin{verse}
Driving to the nursing home\\
Ian, Eric, Mommy, Aunty, and me\\
Anxious, scared, feeling blue\\
Going to see my Grandpa.

Looking at him in the bed\\
Clutching my CD\\
Looking for the CD player\\
Ah, it’s over here.

Putting it in\\
Pressing play\\
Music in our ears.
\end{verse}




\begin{table}[t]
\TBL{\caption{Tables which are too long to fit,
should be written using the ``table*'' environment as shown here\label{tab1}}}
{\begin{fntable}\tabcolsep=11.3pt
\begin{tabular*}{\textwidth}{lcccccc}
\toprule
 \TCH{Projectile} & \TCH{Energy} & \TCH{$\sigma_{\mathit{calc}}$} & \TCH{$\sigma_{\mathit{expt}}$} &
\TCH{Energy} & \TCH{$\sigma_{\mathit{calc}}$} & \TCH{$\sigma_{\mathit{expt}}$} \\
\midrule
\TCH{Element 3}&990 A &1168 &$1547\pm12$ &780 A &1166 &$1239\pm100$\\\hline
{{Element 4}}&500 A &\hphantom{0}961 &$\hphantom{0}922\pm10$ &900 A &1268 &$1092\pm40\hphantom{0}$\\\hline
\TCH{Element 3}&990 A &1168 &$1547\pm12$ &780 A &1166 &$1239\pm100$\\\hline
{\TCH{Element 4\footnotemark[a]}}&500 A &\hphantom{0}961 &$\hphantom{0}922\pm10$ &900 A &1268 &$1092\pm40\hphantom{0}$\\\hline
\TCH{Element 3}&990 A &1168 &$1547\pm12$ &780 A &1166 &$1239\pm100$\\\hline
{\TCH{Element 4}}&500 A &\hphantom{0}961 &$\hphantom{0}922\pm10$ &900 A &1268 &$1092\pm40\hphantom{0}$\\\hline
\TCH{Element 3}&990 A &1168 &$1547\pm12$ &780 A &1166 &$1239\pm100$\\\hline
{\TCH{Element 4}}&500 A &\hphantom{0}961 &$\hphantom{0}922\pm10$ &900 A &1268 &$1092\pm40\hphantom{0}$\\
\botrule
\end{tabular*}%
\footnotetext[]{\textit{Note:} This is an example of table footnote this is an example of table footnote this is an example of table footnote this is an example of~table footnote this is an example of table footnote}
\footnotetext[a]{This is an example of table footnote}%
\end{fntable}}
\end{table}


The final covariates analyse social factors that influence gubernatorial use of
executive orders. These results differ across the models. Diffusion is not statistically
significant for the sexual orientation model, but reaches conventional
statistical significance for the analysis of gender identity protections. This
tentatively suggests that governors are more likely to issue executive orders as
more neighbouring states add similar protections. Governors are more likely to
issue executive orders to protect \nobreak sexual \nobreak orientation when the states are more
liberal, and composed of fewer Evangelicals. Both terms reach conventional
statistical significance.
These discrepancies may be related to the changing strategies of
governors and LGBT advocates in later years, or it may be a reflection of the late
adopters that added protections through executive orders, i.e. the remaining
governors in states that were still ``at risk'' of adopting transgender protections
were in more socially conservative states. Both models show that governors are
more likely to issue protections later into the time frame, and the variance across
the states is statistically significant.
\begin{Boxtext}
Diffusion plays an inconsistent role in policy adoption, but overall it seems that
the diffusion of pro-LGBT policies encourages the issuance of executive orders and
adoption of similar legislation. However, diffusion does not come up as statistically
significant and positive across the board, and thus caution should be taken when
examining its role in policy adoption. Governors used executive orders more
commonly to establish protections for sexual orientation, whereas legislation was
more prevalent for gender identity; therefore, this might explain why diffusion is
only statistically significant in those respective models. One possible explanation
for why diffusion of LGBT protections does not function as previous diffusion
studies suggest is because states consider several competing policies at once.
Throughout the time periods, states do not simply consider adopting one form of
the protections. Rather, neighbouring states adopt different variants of these
policies (sexual orientation or gender identity) through their executive and legislative
branches. This process cannot be captured in a single diffusion variable.
\end{Boxtext}

\begin{Backmatter}

\paragraph{Supplementary material} The supplementary material for this article can be found at \url{https://doi.org/10.1017/S0144686X18000752}

\paragraph{Acknowledgments}
The authors also wish to thank Lucie Laporte-Devylder, Jordan Zlatev, Georgios
Stampoulidis, Joost Van de Weijer, Katie Hoemann, and two anonymous reviewers for their invaluable
feedback and comments on earlier versions of this paper.

\paragraph{Author contributions}
\begin{contriblist}
\item[Joint first authors:] Text to be come later.
\item[Conceptualization:] Text to be come later.
\item[Data curation:] Text to be come later.
\item[Formal analysis:] Text to be come later.
\item[Funding acquisition:] Text to be come later.
\item[Investigation:] Text to be come later.
\item[Methodology:] Text to be come later.
\end{contriblist}

\paragraph{Funding statement}
This study was funded by the Deutsche Forschungsgemeinschaft (DFG) through the Collaborative Research Center 1252 Prominence in Language, and by Mobility Grants from Division 7, Research Management, University of Cologne, which we gratefully acknowledge.

\paragraph{Competing interests}
The authors declare none.

\paragraph{Ethical standards} The Longitudinal Aging Study Amsterdam (LASA) has received approval by the medical
ethics committee of the VU University Medical Center. Signed informed consent was obtained from all
study participants. For the present study, the permission to use data was obtained from the LASA steering
group using the official analysis proposal form (\url{http://www.lasa-vu.nl/data/availability_data/availability_data.htm}).

\begin{notes}
\item[1.] Surapong remained in the party and went on to become finance minister.
\item[2.] Interview with Dr. Piya Netrawichien, member of the “War Room” committee. He stated that Sudarat
was ``a good administrator. She studied hard and always asked questions. She worked very hard.''
\item[3.] Interview with author, 2007.
\item[4.] The core of their health platform for the 2001 elections was to expand the VHC program to cover all
Thais within three years. In addition, their platform included preventive policies, such as free physicals
and basic vaccinations. The internal party changes to policymaking are also observable: The Democrats
appointed Burunaj Samutharaks, a graduate of the Harvard School of Public Health, to be in charge of
their health policy, who was a key player in the drafting of the National Health Act and helped formulate
detailed policy for the party.
\item[5.] The second was a counterfactual scenario: I show that following the 1984 financial crisis, where there
were similar hits to health outcomes and thus the demand, that there was no response from any political
party in the health arena.
\end{notes}


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\begin{appendix}
\section*{Appendix 1. Description of self-organised maps}

Self-organised maps are generally used to classify and extract relationships between the different variables
that are related to a specific problem. Therefore, the objective was to cluster those residents with similar
characteristics in terms of their physical and cognitive conditions, and to assess if these were somehow
related to the use of physical restraints.

We conducted a non-supervised training. The analysis generated a spatial distribution of the residents
in a two-dimensional map formed by neurons. The size of the network or map was (20 $\times$ 10) and each neuron
was hexagonal with six neighbouring neurons. When running the analysis, the training begins and,
after several data interactions, residents were assigned to a neuron which had a weight vector that changed
during the competitive process. The procedure for placing a data vector on the map is to find the node with
the closest weight vector, for instance, by having the smallest metric distance to the data space vector. Based
on these distances, residents with equal characteristics were placed in the same neuron within the map;
those with common characteristics were grouped in the same area and consequently separated from
those that were not similar
\end{appendix}

\citethisarticle{{Aaltonen M, Raitanen R, Comijs H and van Groenou MB} (2022) Trends in the use of care among people aged 65--85 with cognitive impairment in the Netherlands. \textit{Journal of Child Language}, 1--8. \href{https://doi.org/10.1017/spq.2023.15}{10.1017/S0000000020000010}}


\end{Backmatter}

\end{document}
