\documentclass[10pt]{article}

\usepackage{fullpage}
\usepackage{setspace}
\usepackage{parskip}
\usepackage{titlesec}
\usepackage[section]{placeins}
\usepackage{xcolor}
\usepackage{breakcites}
\usepackage{lineno}
\usepackage{hyphenat}





\PassOptionsToPackage{hyphens}{url}
\usepackage[colorlinks = true,
            linkcolor = blue,
            urlcolor  = blue,
            citecolor = blue,
            anchorcolor = blue]{hyperref}
\usepackage{etoolbox}
\makeatletter
\patchcmd\@combinedblfloats{\box\@outputbox}{\unvbox\@outputbox}{}{%
  \errmessage{\noexpand\@combinedblfloats could not be patched}%
}%
\makeatother


\usepackage{natbib}




\renewenvironment{abstract}
  {{\bfseries\noindent{\abstractname}\par\nobreak}\footnotesize}
  {\bigskip}

\titlespacing{\section}{0pt}{*3}{*1}
\titlespacing{\subsection}{0pt}{*2}{*0.5}
\titlespacing{\subsubsection}{0pt}{*1.5}{0pt}


\usepackage{authblk}


\usepackage{graphicx}
\usepackage[space]{grffile}
\usepackage{latexsym}
\usepackage{textcomp}
\usepackage{longtable}
\usepackage{tabulary}
\usepackage{booktabs,array,multirow}
\usepackage{amsfonts,amsmath,amssymb}
\providecommand\citet{\cite}
\providecommand\citep{\cite}
\providecommand\citealt{\cite}
% You can conditionalize code for latexml or normal latex using this.
\newif\iflatexml\latexmlfalse
\providecommand{\tightlist}{\setlength{\itemsep}{0pt}\setlength{\parskip}{0pt}}%

\AtBeginDocument{\DeclareGraphicsExtensions{.pdf,.PDF,.eps,.EPS,.png,.PNG,.tif,.TIF,.jpg,.JPG,.jpeg,.JPEG}}

\usepackage[utf8]{inputenc}
\usepackage[T2A]{fontenc}
\usepackage[ngerman,polish,greek,english]{babel}



\usepackage{float}








\begin{document}

\title{Shifting interpretations in evidence and guidance in pain and opioids
research: A bibliometric analysis of a highly cited case series from
1986}



\author[1]{Sina Tafreshi}%
\author[2]{Adam Steiner}%
\author[3]{Abhimanyu Sud}%
\affil[1]{University of St Andrews}%
\affil[2]{McGill University}%
\affil[3]{University of Toronto Faculty of Medicine}%


\vspace{-1em}



  
  \date{June 10, 2024}


\begingroup
\let\center\flushleft
\let\endcenter\endflushleft
\maketitle
\endgroup





\selectlanguage{english}
\begin{abstract}
Rationale, aims, and objectives: Portenoy and Foley's 1986 landmark
study ``Chronic use of opioid analgesics in non-malignant pain: report
of 38 cases'' has been reproached for opening the floodgates of opioid
prescribing for chronic non-cancer pain and the attendant harms. This
influential article has been cited over 500 times in the scientific
literature over the last four decades. This study seeks to understand
the impact of Portenoy and Foley's article on subsequent discussions and
research about opioids. Methods: We conducted a multi-method
bibliometric analysis of all citations of this article from 1986 through
2019 using quantitative relational and qualitative content analysis to
determine how uses and interpretations of this case series and
associated prescribing guidance have changed over time, in relationship
to the evolution of the North American opioid crises. Results: Using
time series analysis, we identified three periods with distinct
interpretations and uses of the index study. In the first
``exploration'' period (1986-1996), the index study was well-received by
the scientific community and motivated further study of the effects of
opioids. In the second ``implementation'' period (1997-2003, coinciding
with the release of OxyContin\selectlanguage{ngerman}®), this study was used as evidence to
support widespread prescribing of opioid analgesics, even while it was
recognized that long-term effects had not yet been evaluated. The third
``reassessment'' period (2004-2019) focused on how opioid-related harms
had been overlooked, and in many cases these harms were directly
attributed to this study. Conclusion: These changes in interpretation
demonstrate shifting currents of the use and mobilization of evidence
regarding pain and opioids, and how these currents both impact and are
impacted by clinical practices and major sociohistorical phenomena such
as the opioid crisis. Researchers and clinicians must account for these
shifting dynamics when developing and interpreting scientific knowledge,
including in the form of clinical practice guidelines.%
\end{abstract}\selectlanguage{ngerman}%



\sloppy


Shifting interpretations in evidence and guidance in pain and opioids
research: A bibliometric analysis of a highly cited case series from
1986

\textbf{Running Title:} Shifting interpretations in opioids research

\emph{Authors:}

Sina Tafreshi

Adam Steiner

Abhimanyu Sud, MD

\emph{Author Affiliations}

Sina Tafreshi, BSc cand., University of St. Andrews

Adam Steiner, BA cand., McGill University

Abhimanyu Sud, MD, University of Toronto

\emph{Corresponding Author}

Abhimanyu Sud

Abhimanyu.sud@utoronto.ca

416 461 8252

1 Bridgepoint Drive, Toronto, ON M4M 2B5 Canada

\emph{Abstract:}

\textbf{Rationale, aims, and objectives:} Portenoy and Foley's 1986
landmark study ``Chronic use of opioid analgesics in non-malignant pain:
report of 38 cases'' has been reproached for opening the floodgates of
opioid prescribing for chronic non-cancer pain and the attendant harms.
This influential article has been cited over 500 times in the scientific
literature over the last four decades. This study seeks to understand
the impact of Portenoy and Foley's article on subsequent discussions and
research about opioids.

\textbf{Methods:} We conducted a multi-method bibliometric analysis of
all citations of this article from 1986 through 2019 using quantitative
relational and qualitative content analysis to determine how uses and
interpretations of this case series and associated prescribing guidance
have changed over time, in relationship to the evolution of the North
American opioid crises.

\textbf{Results:} Using time series analysis, we identified three
periods with distinct interpretations and uses of the index study. In
the first ``exploration'' period (1986-1996), the index study was
well-received by the scientific community and motivated further study of
the effects of opioids. In the second ``implementation'' period
(1997-2003, coinciding with the release of OxyContin\selectlanguage{ngerman}®), this study was
used as evidence to support widespread prescribing of opioid analgesics,
even while it was recognized that long-term effects had not yet been
evaluated. The third ``reassessment'' period (2004-2019) focused on how
opioid-related harms had been overlooked, and in many cases these harms
were directly attributed to this study.

\textbf{Conclusion:} These changes in interpretation demonstrate
shifting currents of the use and mobilization of evidence regarding pain
and opioids, and how these currents both impact and are impacted by
clinical practices and major sociohistorical phenomena such as the
opioid crisis. Researchers and clinicians must account for these
shifting dynamics when developing and interpreting scientific knowledge,
including in the form of clinical practice guidelines.

\textbf{Keywords:} Opioid Epidemic; Bibliometrics; Analgesics; Drug
Prescriptions; Practice Patterns, Physicians' (MeSH)

\emph{Introduction:}

The over-prescribing of opioids for chronic non-cancer pain has played
an important role in the development of the contemporary opioid crises
in high-income North America.\textsuperscript{1--3}In 2020, there were
6,214 and 81,000 opioid-related deaths in Canada\textsuperscript{4}and
the United States,\textsuperscript{5}respectively. The combined costs of
opioid use disorder and opioid overdoses in the United States were
estimated to total USD 1.021 trillion in 2017
alone.\textsuperscript{6}Historically, physicians had considered opioids
to be effective and important treatments primarily for managing cancer
pain. However, by the mid-1980s, scientific opinion started to shift
towards considering the use of opioids to manage chronic non-cancer
pain.\textsuperscript{7,8}Many have pointed specifically to Portenoy and
Foley's 1986 article, ``Chronic use of opioid analgesics in
non-malignant pain: report of 38 cases'', as a seminal study that opened
the door to mass opioid prescribing.\textsuperscript{2,3,9}

Portenoy and Foley's retrospective observational study of 38 patients
fitting the criteria of having ``non-malignant pain syndromes treated
with opioid analgesics for at least 6 months'' reported that only two
patients - both with histories of substance abuse or mental illness -
experienced management problems. They therefore concluded that opioids
could be ``an alternative therapy which may be more humane and provide
greater benefit at lesser risk than other approaches'' for the treatment
of chronic non-cancer pain.

While advocating for opioid prescribing to treat chronic pain, the 1986
study also presented opioid prescribing guidance. This included the
tenet that ``opioid maintenance therapy should be considered only after
all reasonable attempts at pain management have
failed.''\textsuperscript{10}In many ways, the specifics of this
guidance are similar to recent national guidelines published nearly four
decades later in the United States\textsuperscript{11}and
Canada.\textsuperscript{12}Even though the processes for producing these
guidelines differed, they arrived at similar conclusions regarding
prescribing opioids as a last resort, conducting risk-benefit analyses
prior to prescribing, considering the importance of multidisciplinary
care, and limiting doses.

Contemporary guidelines were developed as major clinical and policy
responses to mass harms from opioids, while Portenoy and Foley's
guidance, despite its concordance with contemporary guidance, has been
criticized as having initiated these very harms. This disconnect makes
us reconsider the contemporary framing of the Portenoy and Foley article
and raises important questions about how this paper has been cited,
used, and interpreted over time.

Our primary objectives for this study were to explore the following
questions:

What was the nature and magnitude of the impact of Portenoy and Foley's
1986 article on the subsequent scientific literature?

How were Portenoy and Foley's 1986 findings promoted, rejected, and
constructed by the medical and scientific communities over time? What
does this tell us about the evolution of pain and opioid prescribing
research and practice?

This will provide insight not only into historical driving forces of the
contemporary opioid crises, but also into historical and contemporary
currents in clinical epidemiology and clinical medicine, including where
the two are supposed to meet --- in the realm of evidence-based
practice.

\emph{Methods:}

A bibliometric analysis is well-suited to exploring our research
questions. We used relational content analysis, supported by time series
analysis and qualitative content analysis, to conduct a scientometric
study\textsuperscript{13}of all scientific citations of Portenoy and
Foley's 1986 article (the index study). The scientometric portion of our
study aimed to quantitatively identify specific trends presented by the
citing sources, allowing us to address our question regarding the impact
of the 1986 study on subsequent scientific literature. We conducted a
relational content analysis to synthesize quantitative and qualitative
data, as well as to explore complex models in the development of
historical scientific and medical thought.

\textbf{Data sources}

We used the Web of Science Core Collection (WoS, by Clarivate Analytics)
to collect all studies that cited the index study. WoS is commonly used
for bibliometric analyses,\textsuperscript{14}and we chose this database
over alternatives such as Scopus and Google Scholar because of the
availability of detailed citation metadata such as research areas,
article type, funding agencies, and countries of origin. We conducted a
search in June 2019 and then an update in July 2020 covering the period
from the publication of the index study through to the end of 2019. The
citation information for every article was collected into EndNote (by
Clarivate Analytics), which was used to retrieve full text records. The
remaining full text records were retrieved manually. We examined all the
retrieved full text articles to ensure that the index study was indeed
cited. Metadata collected from WoS were collected and managed using
Microsoft Excel (by Microsoft).

\textbf{Outcome measures}

\emph{Content analysis}

After collecting all of the citing sources, we conducted a relational
content analysis\textsuperscript{15}that explored the relationship
between Portenoy and Foley's 1986 article and each of the citing works.
While similar studies have focused on whether citations were affirmative
or negative,\textsuperscript{16}we expanded the scope of our study to
construct a more detailed analysis of the citation patterns in the
scientific literature. We identified five relevant outcomes: sign
(affirmational, negational, or neutral reference), accuracy of index
study citation, attribution of the index citation to driving the opioid
crisis, agenda-setting, and article type (Table 1).

\textless{}Table 1. Description and Definition of each
outcome\textgreater{}

\textbf{Data collection and analysis}

Three authors (A.S., S.T., and A. Su.) first conducted a calibration
exercise with 50 randomly selected records. We reviewed our
categorizations and identified any areas of disagreement to refine our
coding process. Then two authors (A.S. and S.T.) independently and in
duplicate assessed and categorized each citation against the index
citation using the definition of each outcome. These categorizations
were reconciled and any conflicts were discussed with a third author (A.
Su.). Metadata were also collected directly from WoS. These included
research area, article type, country of origin, and funding sources for
each article.

Proportions between categories were compared using Chi-squared or Fisher
Exact tests. All tests were two sided and p\textless{}0.05 was
considered statistically significant.

\emph{Time-Series Analysis}

Similar to the procedure of a recent analysis,\textsuperscript{17}we
then conducted time-series analyses to explore any time-based trends in
the number of articles published per year for each coded category.

A preliminary visual inspection of all the time-series plots identified
outstanding trends for further investigation. We used the Chow test to
test for the presence of structural break points in time series
data.\textsuperscript{18}Segmented regression of interrupted time series
analysis with AR(2) residuals were used to examine the sudden and
gradual change in the proportions of publications of interest at given
time points.\textsuperscript{19}

\emph{Qualitative Analysis}

Finally, the content and time-series analyses were supplemented by a
qualitative analysis. We noted a clear time-based trend in the
publication of citing articles in the anaesthesia field, which had three
publication peaks that stood out from the other research areas. We
purposively sampled all the articles from this field that were published
in each of the three peaks through the study period. These papers were
re-read and analyzed with a focus on the larger context of the citation
of the index study, as well as the general tone of the article towards
opioids and opioid prescribing for chronic non-cancer pain. Once each
paper was analyzed, attitudes towards opioid prescribing were summarized
for each peak year. These summaries were then compared to the
quantitative results in order to add depth and context to our overall
findings.

\emph{Results:}

In total, 523 articles were identified through WoS through the end of
2019, placing it in the 99.8th percentile of all scientific publications
in the WoS categories of anesthesiology, neurosciences, clinical
neurology, general \& internal medicine from 1986. Five hundred and
eleven (97.7\%) full text records were included in the analysis (Figure
1). The remaining 12 were either unretrievable (n=8), or were
erroneously identified by WoS as citing the index study (n=4). The
reviewers assessed English, French, and German articles in the original
language. Three other articles that were published in Polish,
Portuguese, and Spanish were reviewed using Google Translate, an online
translation software (by Google).

\textless{}Figure 1. Time series of citing papers published from
1986-2019\textgreater{}

\textbf{Time-Series Analysis:}

On visual inspection of the time-based distribution of each of the
outcomes (Supplementary File 1), we identified possibly significant
time-based trends only in the sign and attribution outcomes. Piecewise
linear regression of the sign and attribution time series identified two
definitive breakpoints that were consistent across both outcomes (Figure
2).

\textless{}Figure 2. Piecewise linear regression of the sign and
attribution time-series for citing papers published from 1986-2019
\textgreater{}

For affirmational and neutral citations, a breakpoint was identified in
1996, after which the rate decreased significantly (Figure 2a).
Non-attributive citations also had a breakpoint in 1996 (Figure 2b).

The time-series analysis for negational citations identified a
significant breakpoint in 2004 (Figure 2a). Following that year, the
number of negational citations substantially increased. Similarly, the
time-series analysis for citations that attribute the opioid crisis to
Portenoy's paper had a distinctive breakpoint in 2004 (Figure 2b). After
2004, many more papers cited Portenoy's paper as a motivating factor
behind the opioid crisis.

\textbf{Categorical Analysis:}

Given these two breakpoints, and our two endpoints of 1986 and 2019, we
categorized the data into three time-based groups: 1986-1996, 1997-2003,
and 2004-2019 (Table 2).

Overall, the largest proportion of citations were neutral (45.4\%). The
majority were accurate (78.9\%), non-attributive (78.3\%),
non-agenda-setting (59.9\%), and non-empirical articles (57.7\%).
Moreover, the majority of articles were published in the U.S. and Canada
(69.7\%). Articles were published in a wide range of research areas,
although papers were concentrated within the areas of neurosciences \&
neurology (22.6\%) anesthesiology (16.2\%), and general \& internal
medicine (15.3\%).

\textless{}Table 2. Categorical Bibliometric Data Across the Three Time
Periods\textgreater{}

\emph{Sign}

Categorically, there was a substantial and continuous decrease in
affirmational citations over the three periods (50.4\% to 38.6\% to
25.4\%). The decrease in affirmation from the first to the second
periods was driven by an increase in neutral articles while the decrease
in affirmation from the second to the third periods was driven by an
increase in negational articles. Agenda-setting was significantly higher
in negational (41.6\%) and neutral (48.3\%) articles than affirmational
(28.7\%) articles (Supplementary File 2).

\emph{Accuracy}

There was a consistent decrease in accuracy over the three periods
(88.2\% to 80.0\% to 73.8\%). There was also a consistent increase in
inaccurate citations over these periods (8.4\% to 13.6\% to 20.2\%).

\emph{Attribution}

There were no attributional articles in the 1986-1996 period and very
few (0.7\%) in the 1997-2003 period (Fig. 2b). There was a large spike
in attributional articles in the 2004-2019 period (43.7\%). Negational
articles (54.5\%) had the highest proportion of attribution, followed by
neutral (23.3\%), and affirmational (1.1\%) articles.

\emph{Agenda-setting}

The proportion of agenda-setting articles remained relatively constant
throughout the period of analysis (38.7\% to 36.4\% to 42.9\%). However,
over the three time periods, there was a reversal of the dominant sign
of the agenda-setting citations. In the first period, agenda-setting
citations were significantly more affirmational (37.0\%) than negational
(6.5\%), while in the third period, they were increasingly negational
(34.3\%) and less affirmational (17.6\%) (Supplementary File 2).

\emph{Article type}

The proportion of empirical articles peaked in the second period before
decreasing (from 47.1\% to 32.1\%) in the third period. Affirmational
non-empirical articles (53.6\%) were higher in proportion than
affirmational empirical articles (46.0\%) in the first period. However,
this difference was reversed in the third period, where affirmational
empirical articles (29.6\%) were higher in proportion than affirmational
non-empirical articles (23.4\%), (Supplemental digital content 1).
Empirical articles (52.9\%) were significantly more agenda-setting than
non-empirical articles (31.5\%) throughout all three periods.

\emph{Research area, country of origin, and funding source}

The proportion of neurosciences \& neurology and pharmacology \&
pharmacy articles decreased over time. Substance abuse articles were
uncommon in the first two periods before spiking in the third period.
The other research areas did not show a clear trend over the three time
periods. In all three periods, more papers were published in the US and
Canada than in the rest of the world. The proportion of papers published
in the US and Canada stayed relatively constant in the first two periods
before spiking in the third period. Most citing papers (79\%) had no
disclosed funding source. The largest funder of research was the
National Institute on Drug Abuse, which funded 35\% of citing articles
with known funding sources.

\textbf{Qualitative Analysis:}

Amongst the anaesthesia papers, we identified three distinctive peaks
that aligned with the middle of each of our three identified time
categories (Figure 3). We qualitatively assessed the six, seven and
eight anaesthesia papers that were published during the peak years of
1991, 2000, and 2010, respectively.

\textless{}Figure 3. Citing anesthesiology papers published from
1986-2019\textgreater{}

\emph{Sample 1: 1991}

Almost all papers published in 1991 acknowledged the controversy
surrounding opioid prescribing and expressed concern at the lack of
definitive scientific evidence about the long-term impacts of opioid
use.\textsuperscript{20--25}Most of these articles were empirical trials
(66.7\%), half of which were animal-based.The authors expressed an
interest in trying to better understand pain and pain prevention. These
articles generally cited the index paper's findings as a motivating
reason for their early-stage research.

Even though there were concerns about the lack of scientific evidence in
1991 for opioid prescribing, the majority of authors cited the index
study neutrally or affirmatively. This is exemplified by Brena, who
concludes that ``{[}at{]} the present level of information, a prudent
and unbiased course of action is mandatory. We must limit and resist the
use of opioids in non-malignant pain at the clinical level until
cross-validated empirical answers \ldots{} are
available.''\textsuperscript{21}

\emph{Sample 2: 2000}

Papers published in 2000\textsuperscript{26--32}generally acknowledged
concerns about opioid prescribing, but viewed them as a secondary
concern after treating pain. For example, Quang-Cantagrel writes that
the controversy about opioids ``results from confusion about pathologies
which could benefit from opioids and misconceptions about addiction and
tolerance that may result from long-term opioid
administration.''\textsuperscript{30}Similarly, Watson acknowledges that
``the use of opioids for neuropathic pain, generally when all else has
failed, remains contentious,'' but immediately goes on to write that
``opioids may be the only avenue of relief for many patients with severe
neuropathic pain.''\textsuperscript{32}

Anesthesiology articles published in 2000 were more supportive of
opioids for pain treatment (57.1\%) than they were in 1991. There was
common agreement that opioids can be safe and effective for short-term
treatment of non-cancer pain. Yet, there continued to be uncertainty and
disagreement about long-term effectiveness and risks of opioid treatment
for chronic pain. Covington writes that ``{[}w{]}hat we do not yet know
is what the effects will be of years, in fact decades, of opioid
treatment of intractable pain.''\textsuperscript{27}Only Mindach took a
strong stance against the index study and opioid prescribing in his
commentary, claiming that ``{[}n{]}ot a single convincing clinical study
could be found to prove the claimed absence of addiction in pain
patients.''\textsuperscript{29}Of note, this article was published in a
German, rather than an American or Canadian, journal.

\emph{Sample 3: 2010}

Anesthesiology papers published in 2010\textsuperscript{33--40}expressed
increasing skepticism about the effects of long-term opioid prescribing
and began documenting opioid-related harms. Most papers did not
necessarily report that opioids were ineffective for pain relief.
Instead, they pointed out that other negative consequences have been
overlooked. A study of patients who received opioids for chronic
non-cancer pain concluded ``that the range of possible harms from
{[}chronic opioid therapy{]} may be broader and of a different nature
than has been described in treatment
guidelines.''\textsuperscript{40}This is a widely shared sentiment in
most of the articles in this sample. For example, Jay writes that
``{[}t{]}he treatment of the CNCP patient with only narcotics is
problematic and most often leads to failure. The most appropriate
treatment is within an inter-disciplinary pain management
program.''\textsuperscript{34}This represents a significant change in
the tone of anesthesiology papers from 2000, when opioid prescribing was
generally advocated as a standalone solution for chronic non-cancer
pain.

\emph{Discussion:}

\textbf{Summary of findings}

Portenoy and Foley's study has been cited more than 500 times, placing
it amongst the most commonly cited articles from 1986. These citations
have not only been sustained over a period of four decades, but the
annual number of citations has continued to increase in recent years
demonstrating the continued and profound impact of this article on pain-
and opioid-related scholarship and practice. Besides these gross
measures of impact, we identified three distinct periods in which the
index study was interpreted and used by the scientific and clinical
communities. Building on Geels' sociotechnical analysis of the societal
embedding of psychotropic medications,\textsuperscript{41}we can frame
these three periods periods more specifically as waves
of\emph{exploration} , \emph{implementation} , and
\emph{reassessment}(Table 3). This framing emphasizes the importance of
sociohistorical context in determining how the index study has been
interpreted. An understanding of this process is important to both
practitioners and researchers as we attempt to interpret scientific
evidence to best inform prescribing practices and research agendas.

\textless{}Table 3. Summary of Findings by Period \textgreater{}

Citing articles from the first period (1986-1996) expressed concern at
the lack of scientific evidence for long-term opioid prescribing. The
articles published in this period were more accurate and affirmational
than the two subsequent periods. Compared to later interpretations of
the index study, these more accurately represented the actual
conclusions and prescribing guidance proposed by Portenoy and Foley.
This was a period of \emph{exploration} with a focus on increasing the
amount of evidence for opioid prescribing for chronic non-cancer pain.

However, this period of exploration concluded at our identified
breakpoint in 1997. Just a year before, OxyContin® was approved in the
United States, a drug that would go on to define the early American
opioid crisis. What had been a period of exploration quickly
transitioned into a period of \emph{implementation} during which sales
of OxyContin® skyrocketed from \$48M USD in 1996 to \$1.1B in
2000.\textsuperscript{42}In this second period (1997-2003), the
proportion of empirical articles reached its highest peak of the three
periods. At first glance, this signifies that concerns about the need
for more scientific evidence for opioids from the first period were
being addressed. However, our qualitative analysis suggests that this
empirical research focused mostly on the efficacy of short-term opioid
use, rather than providing details about long-term effects, either
negative or positive. This was coupled with a rise in inaccurate
citations demonstrating that interpretations began to stray further from
the substance of the index study. In the first \emph{exploration}
period, the index study was being accurately cited as impetus to seek
more evidence for opioid prescribing, but by this second
\emph{implementation} period it was increasingly being inaccurately
cited as evidence in support of regular opioid prescribing.

In other words, a push for increased opioid prescribing altered how
scientific evidence was interpreted. In their analysis on the societal
embedding of new technologies, Geels et al. write that ``innovators,
entrepreneurs or health advocates try to attract attention from sponsors
and lobby to create a favourable regulatory environment. Product
champions make optimistic, but diffuse promises about future
performance, societal benefits and profits.''\textsuperscript{41}In this
case, the index study was used to make ``diffuse promises'' that in many
cases were inaccurate. This misinterpretation is most obvious in how the
index study's recommendation of interdisciplinary treatment was largely
overlooked. While Portenoy and Foley originally noted that opioids
should be prescribed as part of an interdisciplinary treatment plan with
the ``concurrent use of ancillary cognitive/behavioural and physical
therapies,'' the promised benefits of opioids quickly overshadowed this
recommendation. According to Bernard et al., ``what was intended to be
multimodal care, however, became unidimensional care in most settings
with reliance almost completely on pharmacologic solutions to
pain.''\textsuperscript{43}The prospect of opioids as a one-step
solution for chronic pain prompted governmental and non-governmental
organizations to make opioids more accessible for chronic non-cancer
pain.\textsuperscript{43}This second period showed an increasingly
liberal and often inaccurate interpretation that was associated with
increasing opioid-related harms.

Between 2004 and 2019, opioid-related harms increasingly permeated North
American society. Whereas the previous periods explored and implemented
opioids as a solution for chronic pain, this latter period has been one
of concern and \emph{reassessment} . The number of papers that
attributed the opioid crisis to the index study grew exponentially.
Negative citations also grew significantly, making this by far the most
negational period. As opioids drew more ire from the scientific
community, so too did the index study. This tracks with Geels' model
that the ``peak of inflated expectations'' is often followed by a trough
of disillusionment in which ``there are some successes with the new
technology, but more failures.''\textsuperscript{41}This process is
exemplified by yet another rise in inaccurate citations in the third
period. However, these now grew alongside attributive and negational
citations. Whereas earlier inaccurate citations were affirmational and
encouraged liberal opioid prescribing practices, these later inaccurate
citations were negational and misinterpreted the index study as having
been a \emph{carte blanche} for opioid prescribing that incited the
crisis.

\textbf{Implications}

The timeline periods identified in this study accord strongly with other
studies which have demonstrated three phases of scientific communication
relating to opioid dose reduction and multidisciplinary
care\textsuperscript{17}and even mass media coverage of the opioid
crisis.\textsuperscript{44}The former study specifically identified a
cross-correlation with a two-year lag between opioid overdose deaths in
the US and scientific communication about opioids, clearly identifying a
two-way, push-pull relationship between clinical science and the opioid
crisis, a major sociohistorical phenomenon. These studies have
collectively identified the 2004 moment as a major inflection point in
perceptions and activity relating to opioid-related harms, but at the
same time have identified that this inflection is tied directly to
shifting norms and forces building over the preceding two decades.

Besides communicating outcomes of a series of cases related to opioid
prescribing, Foley and Portenoy's article also included substantive
clinical guidance for opioid prescribing for non-cancer pain. By
contemporary standards of evidence-based medicine, this guidance can
certainly be criticized regarding both the quality of the underlying
evidence but also on the opaque and likely idiosyncratic process through
which this guidance was developed. Yet, in the specifics of its content,
this guidance very much accords with contemporary clinical practice
guidelines for opioid prescribing, most of which were developed as
responses to overprescribing and its attendant
harms.\textsuperscript{11,12}We see here the dual possibilities outlined
by Timmermans and Berg\textsuperscript{45} of similar clinical guidance
being used to stake out new professional territory and expand medical
autonomy in the period of expansion in the mid-1980s versus holding
physicians accountable for their practices during our contemporary
period of reassessment (2004-2019). Rather than attending to guidance
content alone or even the processes of developing
guidance,\textsuperscript{46}this concordance draws our attention back
to the importance of sociohistorical context in determining how clinical
guidance is interpreted and utilized within health systems, and thus
influencing the ultimate impacts of this guidance. As the challenges
with the implementation of contemporary guidelines have
emphasized,\textsuperscript{47,48}understanding and accounting for this
contextual effect is a major challenge for future clinical practice
guidance in the complex area of opioid prescribing. Indeed, a plurality
of scientific approaches and perspectives are needed to provide
appropriate, context-sensitive guidance for clinicians and
policy-makers.\textsuperscript{49--51}These are particularly relevant in
this therapeutic area of opioid prescribing where processes for
developing revised clinical practice guidelines are currently
underway.\textsuperscript{52}

\textbf{Strengths}

To our knowledge, this is the first systematic study of the effects of
Portenoy and Foley's seminal 1986 article. By analyzing 511 full-text
citing articles, this study paints a detailed picture of the substantial
and ongoing scientific impact of the index study. We analyzed all
identified and retrievable articles regardless of country of origin or
language of publication allowing us to establish a global, rather than
only North American, understanding of the index study's impact. Finally,
this study uniquely combined bibliometrics, time-series analyses,
relational content analysis, and qualitative analysis. These multiple
analyses demonstrate strong concordance and thus strengthen our
confidence in the findings, and provide a deeper and broader
understanding of the evolution of opioid-related research between 1986
and 2019.

\textbf{Limitations}

The index study is only one of several seminal articles discussing
opioid treatment for chronic non-cancer pain that preceded the opioid
crisis. Therefore, our study does not capture the entire picture of
interpretations and reinterpretations of scientific knowledge
concurrently with the dynamics of the opioid crisis. Similar
examinations of other seminal articles would provide a more
comprehensive view. Furthermore, citing articles were only collected
from WoS. While this database is commonly used for bibliometric
analyses, a similar study using other databases such as Scopus or Google
Scholar may have yielded different outcomes and thus alternative
conclusions.

The coding of the citing articles would be subject to the biases and
idiosyncratic interpretations of the reviewers. We aimed to mitigate
these effects by using clear coding schema and coding independently and
in duplicate. However, there is still the possibility of the coding
procedure introducing unknown biases to this study.

\emph{Conclusion:}

This systematic analysis of 511 articles citing Portenoy and Foley's
1986 study demonstrates the winding evolution of its interpretation and
related impact on pain and opioid scholarship. A time-series analysis
identified three distinct periods of interpretation of the index study
which we labelled as periods of exploration, implementation, and
reassessment. These periods of interpretation align well with inflection
points identified by other studies and with major sociohistorical
phenomena related to pain management and opioid prescribing. This
illustrates both the fluidity of scientific interpretation in pain
medicine and research, and the importance of sociohistorical context to
this interpretation. Practitioners and researchers should be attuned to
this shifting nature of interpretation to better develop, critically
evaluate, and apply scientific knowledge. \emph{}

\emph{References:}

1. Makary MA, Overton HN, Wang P. Overprescribing is major contributor
to opioid crisis.\emph{BMJ}. 2017;359:j4792.

2. Kolodny A, Courtwright DT, Hwang CS, et al. The prescription opioid
and heroin crisis: a public health approach to an epidemic of addiction.
\emph{Annu Rev Public Health}. 2015;36:559-574.

3. Rummans TA, Burton MC, Dawson NL. How Good Intentions Contributed to
Bad Outcomes: The Opioid Crisis. \emph{Mayo Clin Proc}.
2018;93(3):344-350.

4. Opioid- and Stimulant-related Harms in Canada. Accessed August 30,
2021.
https://health-infobase.canada.ca/substance-related-harms/opioids-stimulants/

5. Overdose deaths accelerating during COVID-19. Published December 21,
2020. Accessed August 30, 2021.
https://www.cdc.gov/media/releases/2020/p1218-overdose-deaths-covid-19.html

6. Luo F, Li M, Florence C. State-Level Economic Costs of Opioid Use
Disorder and Fatal Opioid Overdose - United States, 2017. \emph{MMWR
Morb Mortal Wkly Rep}. 2021;70(15):541-546.

7. France RD, Urban BJ, Keefe FJ. Long-term use of narcotic analgesics
in chronic pain. \emph{Social Science \& Medicine}.
1984;19(12):1379-1382. doi:10.1016/0277-9536(84)90027-3

8. Taub A. Opioid analgesics in the treatment of chronic intractable
pain of non-neoplastic origin.\emph{Pain}. 1984;18:S204.

9. Meldrum M. Opioids' Long Shadow. \emph{AMA J Ethics}.
2020;22(1):E729-E734.

10. Portenoy RK, Foley KM. Chronic use of opioid analgesics in
non-malignant pain: report of 38 cases. \emph{Pain}. 1986;25(2):171-186.

11. Dowell D, Haegerich TM, Chou R. CDC Guideline for Prescribing
Opioids for Chronic Pain - United States, 2016. \emph{MMWR Recomm Rep}.
2016;65(1):1-49.

12. Busse JW, Craigie S, Juurlink DN, et al. Guideline for opioid
therapy and chronic noncancer pain. \emph{CMAJ}. 2017;189(18):E659-E666.

13. Leydesdorff L, Milojevi\selectlanguage{polish}ć \selectlanguage{english}S. Scientometrics. \emph{arXiv {[}csDL{]}}.
Published online August 22, 2012. http://arxiv.org/abs/1208.4566

14. Birkle C, Pendlebury DA, Schnell J, Adams J. Web of Science as a
data source for research on scientific and scholarly activity.
\emph{Quantitative Science Studies}. 2020;1(1):363-376.

15. Wilson V. Research methods: Content analysis. \emph{Evid Based Libr
Inf Pract}. 2016;11(1(S)):41.

16. Leung PTM, Macdonald EM, Stanbrook MB, Dhalla IA, Juurlink DN. A
1980 Letter on the Risk of Opioid Addiction. \emph{N Engl J Med}.
2017;376(22):2194-2195.

17. Sud A, Zlahtic E, Cheng D, Moinnedin R, Upshur R. Time series-based
bibliometric analysis of a systematic review of multidisciplinary care
for opioid dose reduction: exploring the origins of the North American
opioid crisis.\emph{Scientometrics}.

18. Chow GC. Tests of Equality Between Sets of Coefficients in Two
Linear Regressions.\emph{Econometrica}. 1960;28(3):591-605.

19. Wagner AK, Soumerai SB, Zhang F, Ross-Degnan D. Segmented regression
analysis of interrupted time series studies in medication use research.
\emph{J Clin Pharm Ther}. 2002;27(4):299-309.

20. Attal N, Chen YL, Kayser V, Guilbaud G. Behavioural evidence that
systemic morphine may modulate a phasic pain-related behaviour in a rat
model of peripheral mononeuropathy. \emph{Pain}. 1991;47(1):65-70.

21. Brena SF, Sanders SH. Opioids in nonmalignant pain: questions in
search of answers. \emph{Clin J Pain}. 1991;7(4):342-345; discussion
346-349.

22. Dubner R. A call for more science, not more rhetoric, regarding
opioids and neuropathic pain.\emph{Pain}. 1991;47(1):1-2.

23. Jazat F, Guilbaud G. The ``tonic'' pain-related behaviour seen in
mononeuropathic rats is modulated by morphine and naloxone. \emph{Pain}.
1991;44(1):97-102.

24. Kupers RC, Konings H, Adriaensen H, Gybels JM. Morphine
differentially affects the sensory and affective pain ratings in
neurogenic and idiopathic forms of pain.\emph{Pain}. 1991;47(1):5-12.

25. Yamamoto T, Yaksh TL. Spinal pharmacology of thermal hyperesthesia
induced by incomplete ligation of sciatic nerve. I. Opioid and nonopioid
receptors.\emph{Anesthesiology}. 1991;75(5):817-826.

26. Baron R. Neuropathic pain. The long path from mechanisms to
mechanism-based treatment.\emph{Anaesthesist}. 2000;49(5):373-386.

27. Covington EC. Opiophobia, opiophilia, opioagnosia. \emph{Pain Med}.
2000;1(3):217-223.

28. Fairbanks CA, Oanh Nguyen H, Grocholski BM, Wilcox GL. Moxonidine, a
Selective Imidazoline--\selectlanguage{greek}α\selectlanguage{english}2-Adrenergic Receptor Agonist, Produces Spinal
Synergistic Antihyperalgesia with Morphine in Nerve-injured
Mice.\emph{Anesthesiology}. 2000;93(3):765-773.
doi:10.1097/00000542-200009000-00026

29. Mindach M. No addiction in pain patients? Questions of a reading
physician. \emph{Schmerz}. 2000;14(3):186-191.

30. Quang-Cantagrel ND, Wallace MS, Magnuson SK. Opioid Substitution to
Improve the Effectiveness of Chronic Noncancer Pain Control: A Chart
Review.\emph{Anesthesia \& Analgesia}. 2000;90(4):933.

31. Taylor WF, Finkel AG, Robertson KR, et al. Methadone in the
treatment of chronic nonmalignant pain: a 2-year follow-up. \emph{Pain
Med}. 2000;1(3):254-259.

32. Watson CP. The treatment of neuropathic pain: antidepressants and
opioids. \emph{Clin J Pain}. 2000;16(2 Suppl):S49-S55.

33. Bailey JA, Hurley RW, Gold MS. Crossroads of pain and addiction.
\emph{Pain Med}. 2010;11(12):1803-1818.

34. Jay GW. Opioid Medications and Correct Medical Usage. In:
\emph{Clinician's Guide to Chronic Headache and Facial Pain}. CRC Press;
2010:235-258.

35. Kidner CL, Gatchel RJ, Mayer TG. MMPI disability profile is
associated with degree of opioid use in chronic work-related
musculoskeletal disorders. \emph{Clin J Pain}. 2010;26(1):9-15.

36. Koeppe J, Armon C, Lyda K, Nielsen C, Johnson S. Ongoing pain
despite aggressive opioid pain management among persons with HIV.
\emph{Clin J Pain}. 2010;26(3):190-198.

37. Laxmaiah Manchikanti M, Bert Fellows M, Hary Ailinani M. Therapeutic
use, abuse, and nonmedical use of opioids: a ten-year perspective.
\emph{Pain Physician}. 2010;13:401-435.

38. Rhodin A, Stridsberg M, Gordh T. Opioid endocrinopathy: a clinical
problem in patients with chronic pain and long-term oral opioid
treatment. \emph{Clin J Pain}. 2010;26(5):374-380.

39. Slater M-E, De Lima J, Campbell K, Lane L, Collins J. Opioids for
the management of severe chronic nonmalignant pain in children: a
retrospective 1-year practice survey in a children's hospital.
\emph{Pain Med}. 2010;11(2):207-214.

40. Sullivan MD, Von Korff M, Banta-Green C, Merrill JO, Saunders K.
Problems and concerns of patients receiving chronic opioid therapy for
chronic non-cancer pain.\emph{Pain}. 2010;149(2):345-353.

41. Geels FW, Pieters T, Snelders S. Cultural Enthusiasm, Resistance and
the Societal Embedding of New Technologies: Psychotropic Drugs in the
20th Century.\emph{Technology Analysis \& Strategic Management}.
2007;19(2):145-165.

42. Van Zee A. The promotion and marketing of oxycontin: commercial
triumph, public health tragedy.\emph{Am J Public Health}.
2009;99(2):221-227.

43. Bernard SA, Chelminski PR, Ives TJ, Ranapurwala SI. Management of
Pain in the United States-A Brief History and Implications for the
Opioid Epidemic. \emph{Health Serv Insights}. 2018;11:1178632918819440.

44. Webster F, Rice K, Sud A. A critical content analysis of media
reporting on opioids: The social construction of an epidemic. \emph{Soc
Sci Med}. 2020;244:112642.

45. Timmermans S, Berg M, Berg PAM. \emph{The Gold Standard: The
Challenge of Evidence-Based Medicine and Standardization in Health
Care}. Temple University Press; 2003.

46. Busse JW, Juurlink D, Guyatt GH. Addressing the limitations of the
CDC guideline for prescribing opioids for chronic noncancer pain.
\emph{CMAJ}. 2016;188(17-18):1210-1211.

47. Dowell D, Haegerich T, Chou R. No Shortcuts to Safer Opioid
Prescribing. \emph{N Engl J Med}. 2019;380(24):2285-2287.

48. Kroenke K, Alford DP, Argoff C, et al. Challenges with Implementing
the Centers for Disease Control and Prevention Opioid Guideline: A
Consensus Panel Report.\emph{Pain Med}. 2019;20(4):724-735.

49. Pawson R, Greenhalgh T, Harvey G, Walshe K. Realist review--a new
method of systematic review designed for complex policy interventions.
\emph{J Health Serv Res Policy}. 2005;10 Suppl 1:21-34.

50. Upshur REG. Do clinical guidelines still make sense? No. \emph{Ann
Fam Med}. 2014;12(3):202-203.

51. Sud A, Buchman D, Furlan A, Selby P, Spithoff S, Upshur R. Chronic
Pain and Opioid Prescribing: Three Ways for Navigating Complexity at the
Clinical-Population Health Interface. \emph{Am J Public Health}.

52. Process for updating the opioid prescribing guideline. Published
November 3, 2021. Accessed December 24, 2021.
https://www.cdc.gov/opioids/guideline-update/index.html

53. Stahl NA, Brozo WG, Simpson ML. Developing college vocabulary: A
content analysis of instructional materials. \emph{Reading Research and
Instruction}. 1987;26(3):203-221. doi:10.1080/19388078709557910

54. Thelwall M. Are classic references cited first? An analysis of
citation order within article sections. \emph{Scientometrics}.
2019;120(2):723-731.

\par\null



\textbf{Acknowledgements:}

The authors would like to thank Rahim Moineddin for supporting
statistical analysis and Darren Cheng for supporting figure and
manuscript formatting.

\par\null

\textbf{Conflict of interest statement:}

\par\null

The authors have no conflicts of interest to disclose. There was no
funding for this project.



\textbf{Table 1: \emph{Description and Definition of each outcome}}\selectlanguage{english}
\begin{longtable}[]{@{}llll@{}}
\toprule
\textbf{Variable} & \textbf{Description} & \textbf{Outcome} &
\textbf{Definition}\tabularnewline
\textbf{Sign} & Identified whether the citing article affirmatively,
negatively, or neutrally referred to the index study.. & Affirmation &
The article confirmed, supported, depended on, or was influenced by the
index study\tabularnewline
& & Negation & The article disputed, questioned, or negatively evaluated
the index study\tabularnewline
& & Neutral & The article took an undefined, non-promotional,
non-combative stance toward the index study\tabularnewline
\textbf{Accuracy} & Similar to past studies that categorized textual
evidence in order to examine varying perspectives in areas of interest
\textsuperscript{53}. & Accurate & The concordance of the presented
facts with information from the index study\tabularnewline
& & Inaccurate & The citation contained any extraneous, contrasting,
assumed, or misleading information in regard to the index
study\tabularnewline
& & Neither & The citation did not present enough information from the
index study to evaluate its accuracy\tabularnewline
\textbf{Attribution} & Assessed the perceived impact by the scientific
community of the index study on opioid prescribing practices, and thus
the opioid crisis. & Attributed & The citation implied or explicitly
linked the publication of the index study to the subsequent development
of the opioid-related harms\tabularnewline
& & Not Attributed & The citation did not mention the opioid crisis or
opioid related harms, and did not establish a link between the index
study and the opioid crisis\tabularnewline
\textbf{Agenda Setting} & Whether the index study was fundamental to the
motivation or design of the study at hand \textsuperscript{54}. & Agenda
Setting & The index study was cited in the Introduction or at the
beginning of sections (i.e. at the start of the Discussion) and cited as
a motivator for subsequent research\tabularnewline
& & Not Agenda Setting & The index study was not cited in the
Introduction, the start of any other section, and not cited as a
motivator\tabularnewline
\textbf{Article Type} & Identified the citing article as either
empirical or non-empirical research. & Empirical Articles & The article
was empirical (quantitative or qualitative) that included data
collection, including secondary analyses such as systematic
reviews\tabularnewline
& & Non-Empirical Articles & All other articles such as commentaries and
editorials that did not report new data or analyses\tabularnewline
\bottomrule
\end{longtable}

\emph{Description of sign, accuracy, attribution, agenda setting, and
article type along with a definition of each of their respective
outcomes. The definitions were used as guides to code each article in
the relational content analysis.}



\textbf{Table 2: \emph{Categorical Bibliometric Data Across the Three
Time Periods}}\selectlanguage{english}
\begin{longtable}[]{@{}lllllll@{}}
\toprule
\textbf{Variable} & \textbf{Outcome} & \textbf{Total (\%)} &
\textbf{Number (\%) Period 1 1986-1996} & \textbf{Number (\%) Period 2
1997-2003} & \textbf{Number (\%) Period 3 2004-2019} &
\textbf{p-value}\tabularnewline
\textbf{Sign} & Affirmation & 178 (34.8) & 60 (50.4) & 54 (38.6) & 64
(25.4) & \textless{}0.0001\tabularnewline
& Negation & 101 (19.8) & 6 (5) & 10 (7.1) & 85 (33.7) &\tabularnewline
& Neutral & 232 (45.4) & 53 (44.5) & 76 (54.3) & 103 (40.9)
&\tabularnewline
\textbf{Accuracy} & Accurate & 403 (78.9) & 105 (88.2) & 112 (80) & 186
(73.8) & 0.0240\tabularnewline
& Inaccurate & 80 (15.7) & 10 (8.4) & 19 (13.6) & 51 (20.2)
&\tabularnewline
& Neither & 28 (5.5) & 4 (3.4) & 9 (6.4) & 15 (6) &\tabularnewline
\textbf{Attribution} & Attributed & 111 (21.7) & 0 (0) & 1 (0.7) & 110
(43.7) & \textless{}0.0001\tabularnewline
& Not attributed & 400 (78.3) & 119 (100) & 139 (99.3) & 142 (56.3)
&\tabularnewline
\textbf{Agenda Setting} & Agenda setting & 205 (40.1) & 46 (38.7) & 51
(36.4) & 108 (42.9) & 0.4304\tabularnewline
& Not agenda setting & 306 (59.9) & 73 (61.3) & 89 (63.6) & 144 (57.1)
&\tabularnewline
\textbf{Article Type} & Empirical Research & 197 (38.5) & 50 (42) & 66
(47.1) & 81 (32.1) & 0.0094\tabularnewline
& Non-Empirical Research & 314 (61.5) & 69 (58) & 74 (52.9) & 171 (67.9)
&\tabularnewline
\textbf{Research Area} & Neurosciences \& Neurology & 179 (22.6) & 48
(27.1) & 55 (24.2) & 76 (19.6) & 0.0699\tabularnewline
& Anesthesiology & 128 (16.2) & 24 (13.6) & 44 (19.4) & 60 (15.5)
&\tabularnewline
& General \& Internal Medicine & 121 (15.3) & 24 (13.6) & 36 (15.9) & 61
(15.7) &\tabularnewline
& Pharmacology \& Pharmacy & 56 (7.1) & 18 (10.2) & 18 (7.9) & 20 (5.2)
&\tabularnewline
& Psychiatry & 39 (4.9) & 4 (2.3) & 13 (5.7) & 22 (5.7) &\tabularnewline
& Health Care Sciences \& Services & 36 (4.6) & 9 (5.1) & 10 (4.4) & 17
(4.4) &\tabularnewline
& Substance Abuse & 21 (2.7) & 3 (1.7) & 2 (0.9) & 16 (4.1)
&\tabularnewline
& Psychology & 19 (2.4) & 6 (3.4) & 4 (1.8) & 9 (2.3) &\tabularnewline
& Surgery & 14 (1.8) & 1 (0.6) & 4 (1.8) & 9 (2.3) &\tabularnewline
& Other & 179 (22.6) & 40 (22.6) & 41 (18.1) & 98 (25.3)
&\tabularnewline
\textbf{Country of Origin} & USA \& Canada & 371 (69.7) & 75 (62) & 86
(58.9) & 210 (79.3) & \textless{}0.0001\tabularnewline
& Rest of the world & 161 (30.3) & 46 (38) & 60 (41.1) & 55 (20.8)
&\tabularnewline
\bottomrule
\end{longtable}

\emph{Categorical bibliometric data for sign, accuracy, attribution,
agenda-setting, article type, research area, and country of origin.
Overall data and data by each of three Periods are displayed.}



\textbf{Table 3: \emph{Summary of Findings by Period}}\selectlanguage{english}
\begin{longtable}[]{@{}llll@{}}
\toprule
\textbf{Characteristic} & \textbf{Period of Exploration (1986-1996)} &
\textbf{Period of Implementation (1997-2003)} & \textbf{Period of
Reassessment (2004-2019)}\tabularnewline
\textbf{Dominant sign toward the index study} & Affirmation & Neutral &
Negation\tabularnewline
\textbf{Attribution of the index study to the opioid crisis} & Not
attributed & Not attributed & Attributed\tabularnewline
\textbf{Concern toward opioid risks} & Acknowledges the lack of
scientific evidence on the long-term effects of opioids & Little concern
for long term effects of opioids & Concern over the negative
consequences of opioids\tabularnewline
\textbf{Motivation of research} & Better understand the benefits and
risks of opioids & Gather evidence in support of opioid prescribing &
Reassess the negative consequences of opioids\tabularnewline
\bottomrule
\end{longtable}

\emph{Description of the main characteristics of each time period
identified via quantitative and qualitative analyses, including the
dominant sign toward index study, attribution of the index study to the
opioid crisis, concern toward opioid risks, and motivation of
research.~}

\emph{Figure Titles and Legends:}

Figure 1. Number of citing papers published from 1986-2019

\emph{A time series illustrating the annual number of citations of the
index study between 1986 and 2019.}

Figure 2. Time-series for citing papers published from 1986-2019

\emph{Two piecewise linear regressions with smoothed curves of
time-series for sign and attribution outcomes, demonstrating concordant
breakpoints in 1996 and 2004.}\selectlanguage{english}
\begin{figure}[H]
\begin{center}
\includegraphics[width=0.70\columnwidth]{figures/image1/image1}

\end{center}
\end{figure}

Figure 3. Citing anesthesiology papers published from 1986-2019

\emph{A time series illustrating the annual number of citing
anesthesiology papers published between 1986 and 2019. The ``sign'' of
the citations is shown for the three years of interest: 1991, 2000, and
2010.}\selectlanguage{english}
\begin{figure}[H]
\begin{center}
\includegraphics[width=0.70\columnwidth]{figures/image2/image2}

\end{center}
\end{figure}\selectlanguage{english}
\begin{figure}[H]
\begin{center}
\includegraphics[width=0.70\columnwidth]{figures/Portenoy-JECP-Fig1/Portenoy-JECP-Fig1}

\end{center}
\end{figure}\selectlanguage{english}
\begin{figure}[H]
\begin{center}
\includegraphics[width=0.70\columnwidth]{figures/Portenoy-JECP-Fig2/Portenoy-JECP-Fig2}

\end{center}
\end{figure}\selectlanguage{english}
\begin{figure}[H]
\begin{center}
\includegraphics[width=0.70\columnwidth]{figures/Portenoy-JECP-Fig2Legend/Portenoy-JECP-Fig2Legend}

\end{center}
\end{figure}\selectlanguage{english}
\begin{figure}[H]
\begin{center}
\includegraphics[width=0.70\columnwidth]{figures/Portenoy-JECP-Fig3/Portenoy-JECP-Fig3}

\end{center}
\end{figure}\selectlanguage{english}
\begin{figure}[H]
\begin{center}
\includegraphics[width=0.70\columnwidth]{figures/Portenoy-JECP-Fig3Legend/Portenoy-JECP-Fig3Legend}

\end{center}
\end{figure}

\selectlanguage{english}
\FloatBarrier
\end{document}

