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<front>
<journal-meta>
<journal-id journal-id-type="publisher-id">Front. Pharmacol.</journal-id>
<journal-title>Frontiers in Pharmacology</journal-title>
<abbrev-journal-title abbrev-type="pubmed">Front. Pharmacol.</abbrev-journal-title>
<issn pub-type="epub">1663-9812</issn>
<publisher>
<publisher-name>Frontiers Media S.A.</publisher-name>
</publisher>
</journal-meta>
<article-meta>
<article-id pub-id-type="publisher-id">1356059</article-id>
<article-id pub-id-type="doi">10.3389/fphar.2024.1356059</article-id>
<article-categories>
<subj-group subj-group-type="heading">
<subject>Pharmacology</subject>
<subj-group>
<subject>Review</subject>
</subj-group>
</subj-group>
</article-categories>
<title-group>
<article-title>What influences consumers&#x2019; online medication purchase intentions and behavior? A scoping review</article-title>
<alt-title alt-title-type="left-running-head">Limbu and Huhmann</alt-title>
<alt-title alt-title-type="right-running-head">
<ext-link ext-link-type="uri" xlink:href="https://doi.org/10.3389/fphar.2024.1356059">10.3389/fphar.2024.1356059</ext-link>
</alt-title>
</title-group>
<contrib-group>
<contrib contrib-type="author" corresp="yes">
<name>
<surname>Limbu</surname>
<given-names>Yam B.</given-names>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
</xref>
<xref ref-type="corresp" rid="c001">&#x2a;</xref>
<uri xlink:href="https://loop.frontiersin.org/people/2197376/overview"/>
<role content-type="https://credit.niso.org/contributor-roles/conceptualization/"/>
<role content-type="https://credit.niso.org/contributor-roles/data-curation/"/>
<role content-type="https://credit.niso.org/contributor-roles/formal-analysis/"/>
<role content-type="https://credit.niso.org/contributor-roles/investigation/"/>
<role content-type="https://credit.niso.org/contributor-roles/methodology/"/>
<role content-type="https://credit.niso.org/contributor-roles/visualization/"/>
<role content-type="https://credit.niso.org/contributor-roles/writing-original-draft/"/>
<role content-type="https://credit.niso.org/contributor-roles/Writing - review &#x26; editing/"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Huhmann</surname>
<given-names>Bruce A.</given-names>
</name>
<xref ref-type="aff" rid="aff2">
<sup>2</sup>
</xref>
<uri xlink:href="https://loop.frontiersin.org/people/2608275/overview"/>
<role content-type="https://credit.niso.org/contributor-roles/conceptualization/"/>
<role content-type="https://credit.niso.org/contributor-roles/data-curation/"/>
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<role content-type="https://credit.niso.org/contributor-roles/Writing - review &#x26; editing/"/>
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</contrib-group>
<aff id="aff1">
<sup>1</sup>
<institution>Department of Marketing, Montclair State University</institution>, <addr-line>Montclair</addr-line>, <addr-line>NJ</addr-line>, <country>United States</country>
</aff>
<aff id="aff2">
<sup>2</sup>
<institution>Department of Marketing, Virginia Commonwealth University</institution>, <addr-line>Richmond</addr-line>, <addr-line>VA</addr-line>, <country>United States</country>
</aff>
<author-notes>
<fn fn-type="edited-by">
<p>
<bold>Edited by:</bold> <ext-link ext-link-type="uri" xlink:href="https://loop.frontiersin.org/people/1635998/overview">Andr&#xe1;s Fittler</ext-link>, University of P&#xe9;cs, Hungary</p>
</fn>
<fn fn-type="edited-by">
<p>
<bold>Reviewed by:</bold> <ext-link ext-link-type="uri" xlink:href="https://loop.frontiersin.org/people/2612789/overview">Bernard Naughton</ext-link>, Trinity College Dublin, Ireland</p>
<p>
<ext-link ext-link-type="uri" xlink:href="https://loop.frontiersin.org/people/2376291/overview">M&#xe1;ty&#xe1;s K&#xe1;pl&#xe1;r</ext-link>, University of P&#xe9;cs, Hungary</p>
</fn>
<corresp id="c001">&#x2a;Correspondence: Yam B. Limbu, <email>limbuy@montclair.edu</email>
</corresp>
</author-notes>
<pub-date pub-type="epub">
<day>13</day>
<month>02</month>
<year>2024</year>
</pub-date>
<pub-date pub-type="collection">
<year>2024</year>
</pub-date>
<volume>15</volume>
<elocation-id>1356059</elocation-id>
<history>
<date date-type="received">
<day>15</day>
<month>12</month>
<year>2023</year>
</date>
<date date-type="accepted">
<day>01</day>
<month>02</month>
<year>2024</year>
</date>
</history>
<permissions>
<copyright-statement>Copyright &#xa9; 2024 Limbu and Huhmann.</copyright-statement>
<copyright-year>2024</copyright-year>
<copyright-holder>Limbu and Huhmann</copyright-holder>
<license xlink:href="http://creativecommons.org/licenses/by/4.0/">
<p>This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.</p>
</license>
</permissions>
<abstract>
<p>
<bold>Objective:</bold> Consumers increasingly buy pharmaceuticals online. No scoping review has been carried out to summarize and synthesize the studies that have identified drivers of consumers&#x2019; purchase intention and behavior from online pharmacies. Thus, we conducted a scoping review to explore the extent to which prior research has studied consumer purchase intentions and behavior related to online pharmacies, the drivers previously identified to explain consumers&#x2019; online pharmacy purchase intentions and behavior, and how these antecedents differ between OTC and prescription medications. Then, we identified gaps in the published literature to form a comprehensive theory-based agenda for future research.</p>
<p>
<bold>Methods:</bold> We searched PubMed, Web of Science, and Scopus to retrieve relevant studies published in English in peer-reviewed journals. The search strategy identified forty-eight eligible studies.</p>
<p>
<bold>Results:</bold> We identified twelve types of factors influencing purchase intentions and behaviors from online pharmacies: demographics, convenience, availability, price, evaluations of the purchase environment, information sources, internet usage, prior experience, perceived risk, health insurance, privacy, and product. Our analysis also revealed differences between OTC and prescription medications in drivers of purchase intentions and behaviors.</p>
<p>
<bold>Conclusion:</bold> While demographic factors tended to be the most often measured influences on intentions and behavior, their role was generally inconsistent, with many contradictory results. However, other factors (e.g., convenience, availability, lower prices, and favorable evaluations toward the purchase environment) more consistently enhanced online medication purchase intentions and behavior. An extensive agenda for future research is advanced.</p>
</abstract>
<kwd-group>
<kwd>online pharmacy</kwd>
<kwd>scoping review</kwd>
<kwd>over-the-counter (OTC) medication</kwd>
<kwd>prescription drug</kwd>
<kwd>purchase intention</kwd>
<kwd>purchase behavior</kwd>
</kwd-group>
<custom-meta-wrap>
<custom-meta>
<meta-name>section-at-acceptance</meta-name>
<meta-value>Drugs Outcomes Research and Policies</meta-value>
</custom-meta>
</custom-meta-wrap>
</article-meta>
</front>
<body>
<sec id="s1">
<title>1 Introduction</title>
<p>Consumers increasingly purchase products online; for example, rising from 53% of consumers in the United Kingdom (UK) in 2008 to 87% in 2020 (<xref ref-type="bibr" rid="B50">Office for National Statistics, 2020</xref>). Many consumers now prefer to purchase online, including 61.4% in the United States, 57.4% in the UK, 51.6% in Spain, 49.2% in France and Poland, and 47.8% in Australia and Germany (<xref ref-type="bibr" rid="B36">Klarna, 2023</xref>). In some countries, many consumers purchase drugs or health products online each year, for example, 43% in Germany, 39% in Mexico, 36% in the UK, 33% in the United States, and 27% in France (<xref ref-type="bibr" rid="B60">Statista Consumer Insights, 2023</xref>). Thus, many consumers are turning to online pharmacies to purchase medications.</p>
<p>A survey by the Alliance for Safe Online Pharmacies (2020) found that 35% of American consumers have purchased medication for themselves or someone in their care from an online pharmacy (also known as an e-pharmacy, internet pharmacy, or cyber pharmacy). Online pharmacies sell or dispense pharmaceutical drugs or other government-regulated medical treatments through the internet or electronic media (e.g., websites, social media, or mobile apps). Consumer purchases from online pharmacies continue to grow rapidly due to the convenience, accessibility, and cost savings that they provide (<xref ref-type="bibr" rid="B40">Limbu and Huhmann, 2023b</xref>). For example, purchases by Hungarian consumers from online pharmacies increased over tenfold between 2018 and 2020 (<xref ref-type="bibr" rid="B22">Fittler et al., 2022a</xref>). Online pharmacies have become a major healthcare resource for consumers, with global sales of US$98.8 billion in 2022, which is expected to reach US$353.9 billion annually by 2032, with a compound annual growth rate (CAGR) of 13.6%. In North America, consumer purchases from online pharmacies are projected to grow from US$39.4 in 2022 to US$138.9 in 2032, with a CAGR of 13.4% (<xref ref-type="bibr" rid="B27">Global Market Insights, 2023</xref>).</p>
<p>Online pharmacies include major corporations (e.g., Express Scripts Pharmacy, Walgreens, Amazon Pharmacy, and CVS), smaller independent pharmacies, and even illicit online pharmacies. Illicit online pharmacies violate regulations by selling counterfeit, adulterated, or unapproved drugs or dispensing prescription drugs without a valid prescription (<xref ref-type="bibr" rid="B39">Limbu and Huhmann, 2023a</xref>)</p>
<p>Research on online pharmacies has been growing. Reviews of online pharmacies show how the literature documents online pharmacy types and characteristics, the therapeutic classes and quality of drugs available, and risks to patients and public health (<xref ref-type="bibr" rid="B51">Orizio et al., 2011</xref>; <xref ref-type="bibr" rid="B45">Mackey and Nayyar, 2016</xref>; <xref ref-type="bibr" rid="B43">Long et al., 2022</xref>; <xref ref-type="bibr" rid="B39">Limbu and Huhmann, 2023a</xref>).</p>
<p>Despite a growing literature stream, a review has yet to be carried out to summarize and synthesize the studies that have examined factors predicting consumers&#x2019; online medicine purchase intentions and behavior. Only one review touches on consumer purchases (<xref ref-type="bibr" rid="B8">Almomani et al., 2023b</xref>). This narrative review of 17 studies identifies the prevalence of and reasons for prescription medicine purchases using any internet platform, including search engines, social media, and encrypted messaging applications; however, half the qualitative studies reviewed sampled pregnant women, which limits generalizability. Further, it solely focused on studies of prescription medication purchases published between 2012 and 2021. Although <xref ref-type="bibr" rid="B8">Almomani et al.&#x2019;s (2023b)</xref> review included any internet purchases of prescription medications, its narrow search terms missed many studies of online pharmacy purchases. In addition, it included no studies published prior to 2012 or after 2021. Our study reviews almost three times as many studies on online pharmacy purchases alone.</p>
<p>Thus, to better understand why consumers increasingly purchase from online pharmacies, including illicit online pharmacies, the current scoping review rigorously examines all qualitative and quantitative studies of consumers&#x2019; online medication purchase intentions and behavior. Unlike earlier reviews, we included studies of consumer purchases of both prescription and over-the-counter (OTC) medications to determine if the need for a prescription alters why consumers want to acquire medication online. Also, we did not constrain our review to studies published within a limited date range. This allowed us to show how research into this topic has changed over time. Thus, this scoping review provides a comprehensive understanding of the nature of research into consumers&#x2019; online medication purchases.</p>
<p>Moreover, our review makes an important distinction between influences on consumer purchase intentions and influences on actual purchase behavior. Although some assume purchase intentions predict actual purchase behavior, prior research in many disciplines has found that they are not the same. In fact, meta-analyses have found that intentions account for only 28% of the variance in behavior and that a moderate-to-large change in intentions only results in a small-to-moderate change in behavior (<xref ref-type="bibr" rid="B56">Sheeran, 2002</xref>; <xref ref-type="bibr" rid="B67">Webb and Sheeran, 2006</xref>). Variables that increase or reduce the relationship between purchase intentions and behavior include unexpected situations, social influence, type of product, intervening time, environmental context, consumers&#x2019; self-efficacy, and the receipt of new information (<xref ref-type="bibr" rid="B20">Cote et al., 1985</xref>; <xref ref-type="bibr" rid="B69">Morwitz et al., 2007</xref>; <xref ref-type="bibr" rid="B56">Sheeran, 2002</xref>; <xref ref-type="bibr" rid="B67">Webb and Sheeran, 2006</xref>). For example, a consumer may intend to purchase from an online pharmacy, but time or social influence may shift that purchase to a brick-and-mortar pharmacy. Alternatively, a consumer may not intend to purchase from an online pharmacy, but an unexpected situation (e.g., a web search for information on a drug revealing a lower price at an online pharmacy) may encourage online medication purchase behavior.</p>
<p>The current review addresses three key research questions: (1) to what extent have consumer purchase intentions and behavior been investigated as they relate to online pharmacies? (2) how do the antecedents of consumers&#x2019; online purchases differ between OTC and prescription medications? and (3) what factors have been identified in the published literature that help explain consumers&#x2019; online pharmacy purchase intentions and behavior?</p>
<p>Hence, our investigation aims to fill a research gap by systematically scoping a body of literature on this topic of growing interest to researchers in healthcare and public policy. In addition, we provide guidance for the direction of future research and the areas that remain uninvestigated or unstudied, as well as those that represent emerging topics that warrant greater investigation.</p>
</sec>
<sec sec-type="materials|methods" id="s2">
<title>2 Materials and methods</title>
<p>We carried out a scoping review, which is useful to map the literature on evolving or emerging fields or topics (<xref ref-type="bibr" rid="B48">Munn et al., 2018</xref>), such as the topic covered in the present study. This scoping review was coducted following the guidelines recommended by the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA), a commonly used reporting guidance for systematic reviews (<xref ref-type="bibr" rid="B38">Liberati et al., 2009</xref>). As such, this scoping review applies (<xref ref-type="bibr" rid="B12">Arksey and O&#x2019;Malley, 2005</xref>) five-step framework: (1) research question identification, (2) relevant study identification, (3) study selection via inclusion and exclusion criteria, (4) data charting and investigation, and (5) result presentation.</p>
<sec id="s2-1">
<title>2.1 Study identification</title>
<p>We searched PubMed, Web of Science, and Scopus to locate relevant articles. PubMed, one of the most commonly used search tools, is a leading database that covers biomedical and life sciences literature. Web of Science and Scopus are the two largest and most widely used bibliographic databases for searching multidisciplinary literature, as covered in our review.</p>
<p>To improve the retrieval of relevant articles, we used a wide range of search terms, such as online, internet, social media, pharmac&#x2a;, buy or purchas&#x2a;, and drug or medic&#x2a; for either medication or medicine. To locate more records from this interdisciplinary literature, we also used relevant synonyms and variants of search terms. As presented in <xref ref-type="table" rid="T1">Table 1</xref>, we generated various search strings to execute exhaustive queries in each database by combining two or more search terms with the Boolean operators &#x201c;AND&#x201d; and &#x201c;OR".</p>
<table-wrap id="T1" position="float">
<label>TABLE 1</label>
<caption>
<p>Search stratetegy</p>
</caption>
<table>
<thead valign="top">
<tr>
<th align="left">Database</th>
<th align="left">Search terms (Boolean operators)</th>
<th align="left">&#x23;Records</th>
</tr>
</thead>
<tbody valign="top">
<tr>
<td rowspan="2" align="left">PubMed</td>
<td align="left">(((((online [Title) OR (internet [Title)) AND (pharmac&#x2a;[Title)) AND (buy [Title)) OR (purchas&#x2a;[Title)) AND (drug [Title))</td>
<td rowspan="2" align="left">426</td>
</tr>
<tr>
<td align="left">(((((online [Title) OR (internet [Title)) AND (pharmac&#x2a;[Title)) AND (buy [Title)) OR (purchas&#x2a;[Title)) AND (medic&#x2a;[Title))</td>
</tr>
<tr>
<td rowspan="4" align="left">Web of Science</td>
<td align="left">(((((TI&#x3d;(online)) OR TI&#x3d;(internet)) AND TI&#x3d;(pharmac&#x2a;)) AND TI&#x3d;(buy)) OR TI&#x3d;(purchas&#x2a;)) AND TI&#x3d;(medic&#x2a;) and Review Article (Exclude&#x2013;Document Types) and Enriched Cited References and Article (Document Types) and Proceeding Paper (Exclude&#x2013;Document Types) and English (Languages)</td>
<td rowspan="4" align="left">486</td>
</tr>
<tr>
<td align="left">(((((TI&#x3d;(online)) OR TI&#x3d;(internet)) AND TI&#x3d;(pharmac&#x2a;)) AND TI&#x3d;(buy)) OR TI&#x3d;(purchas&#x2a;)) AND TI&#x3d;(drug) and Article (Document Types) and English (Languages) and Article or Early Access (Document Types)</td>
</tr>
<tr>
<td align="left">((((TI&#x3d;(social media)) AND TI&#x3d;(pharmac&#x2a;)) AND TI&#x3d;(buy)) OR TI&#x3d;(purchas&#x2a;)) AND TI&#x3d;(drug)) and Review Article (Exclude&#x2013;Document Types) and Enriched Cited References and Article (Document Types) and Proceeding Paper (Exclude&#x2013;Document Types) and English (Languages)</td>
</tr>
<tr>
<td align="left">((((TI&#x3d;(social media)) AND TI&#x3d;(pharmac&#x2a;)) AND TI&#x3d;(buy)) OR TI&#x3d;(purchas&#x2a;)) AND TI&#x3d;(medic&#x2a;)) and Review Article (Exclude&#x2013;Document Types) and Enriched Cited References and Article (Document Types) and Proceeding Paper (Exclude&#x2013;Document Types) and English (Languages)</td>
</tr>
<tr>
<td align="left">Scopus</td>
<td align="left">(TITLE-ABS-KEY (online) OR TITLE-ABS-KEY (internet) OR TITLE-ABS-KEY (social AND media) AND TITLE-ABS-KEY (pharmac&#x2a;) AND TITLE-ABS-KEY (buy) OR TITLE-ABS-KEY (purchas&#x2a;) AND TITLE-ABS-KEY (drug) AND TITLE-ABS-KEY (medic&#x2a;)) AND (LIMIT-TO DOCTYPE,&#x201c;ar&#x201d;)) AND (LIMIT-TO (LANGUAGE,&#x201c;English&#x201d;)) AND (LIMIT-TO (SRCTYPE,&#x201c;j"))</td>
<td align="left">258</td>
</tr>
</tbody>
</table>
</table-wrap>
</sec>
<sec id="s2-2">
<title>2.2 Inclusion and exclusion criteria</title>
<p>We limited the search criteria to exclude all literature irrelevant to our study, such as conference proceedings, grey literature, reviews, books, dissertations, and non-English articles. We included qualitative and quantitative studies of the determinants of medication purchase intentions and behavior over the Internet. Restrictions on the publication year and study population were not applied. The PRISMA flow diagram (see <xref ref-type="fig" rid="F1">Figure 1</xref>) shows the article selection process, which consists of four steps (i.e., identification, screening, eligibility, and selection). It summarizes the number of records identified, screened, and excluded, the reasons for exclusion, and the number of studies included in this review (<xref ref-type="bibr" rid="B38">Liberati et al., 2009</xref>).</p>
<fig id="F1" position="float">
<label>FIGURE 1</label>
<caption>
<p>PRISMA flow diagram showing inclusion and exclusion of studies.</p>
</caption>
<graphic xlink:href="fphar-15-1356059-g001.tif"/>
</fig>
<p>We retrieved 1,150 records from electronic databases, which consisted of 406 records from PubMed, 486 from Web of Science, and 258 from Scopus. After removing duplicates, 526 records were retained. Next, titles and abstracts were screened by two researchers independently. After screening titles and abstracts, 441 records that did not meet the inclusion criteria were eliminated. Finally, we assessed the remaining 85 full-text articles. Of these, 38 articles did not meet the eligibility criteria. Forty-seven studies were included in this scoping review.</p>
</sec>
<sec id="s2-3">
<title>2.3 Data extraction and analysis</title>
<p>All abstracts and full texts were screened and reviewed independently by two trained coders, who extracted data including authors, publication year, country, journal, population, sample size, research design, drug type, study objective, determinants of purchase intention and behavior, and key findings. Following <xref ref-type="bibr" rid="B12">Arksey and O&#x2019;Malley (2005)</xref>, the authors used an iterative method to synthesize the data by sorting prior research findings into key types of factors (i.e., data charting and investigation). IBM SPSS Statistics 27 was used to analyze the data.</p>
</sec>
</sec>
<sec sec-type="results" id="s3">
<title>3 Results</title>
<sec id="s3-1">
<title>3.1 Description of included studies</title>
<p>This study included forty-seven studies from twenty-nine countries, including nine studies conducted in the United States, five studies in Saudi Arabia, and three studies each in Australia, China, India, and the United Kindom (see <xref ref-type="table" rid="T2">Table 2</xref>). Twenty-one studies were carried out in Asia, eighteen studies in Europe, eleven studies in North America, three studies in Australia, and two studies in Africa. Interestingly, no research was carried out in South America.</p>
<table-wrap id="T2" position="float">
<label>TABLE 2</label>
<caption>
<p>Characteristics of studies included in this review.</p>
</caption>
<table>
<thead valign="top">
<tr>
<th align="left">Author(s)</th>
<th align="left">Year</th>
<th align="left">Country</th>
<th align="left">Journal</th>
<th align="left">Population</th>
<th align="left">Sample size</th>
<th align="left">Design</th>
<th align="left">Drug</th>
</tr>
</thead>
<tbody valign="top">
<tr>
<td align="left">Abanmy</td>
<td align="left">2017</td>
<td align="left">Saudi Arabia</td>
<td align="left">Saudi Pharmaceutical Journal</td>
<td align="left">Adults</td>
<td align="center">633</td>
<td align="left">Survey</td>
<td align="left">NS</td>
</tr>
<tr>
<td align="left">Adjie et al</td>
<td align="left">2023</td>
<td align="left">Indonesia</td>
<td align="left">Informatics in Medicine Unlocked</td>
<td align="left">Adults</td>
<td align="center">778</td>
<td align="left">Survey</td>
<td align="left">NS</td>
</tr>
<tr>
<td align="left">Ahmed et al</td>
<td align="left">2023</td>
<td align="left">Bangladesh</td>
<td align="left">International Journal of Healthcare Management</td>
<td align="left">Adults</td>
<td align="center">336</td>
<td align="left">Survey</td>
<td align="left">NS</td>
</tr>
<tr>
<td align="left">Alfahad et al</td>
<td align="left">2015</td>
<td align="left">Saudi Arabia</td>
<td align="left">Latin American Journal of Pharmacy</td>
<td align="left">Adults</td>
<td align="center">344</td>
<td align="left">Survey</td>
<td align="left">NS</td>
</tr>
<tr>
<td align="left">Alhabash et al</td>
<td align="left">2022</td>
<td align="left">United States</td>
<td align="left">International Journal of Environmental Research and Public Health</td>
<td align="left">Adults</td>
<td align="center">730</td>
<td align="left">Experiment</td>
<td align="left">Prescription</td>
</tr>
<tr>
<td align="left">Almohammed et al</td>
<td align="left">2023</td>
<td align="left">Saudi Arabia</td>
<td align="left">Saudi Pharmaceutical Journal</td>
<td align="left">Adults</td>
<td align="center">262</td>
<td align="left">Survey</td>
<td align="left">NS</td>
</tr>
<tr>
<td align="left">Almomani et al</td>
<td align="left">2023</td>
<td align="left">UK</td>
<td align="left">JMIR Formative Research</td>
<td align="left">Adults</td>
<td align="center">20</td>
<td align="left">Interview</td>
<td align="left">Prescription</td>
</tr>
<tr>
<td align="left">Alsadoun et al</td>
<td align="left">2023</td>
<td align="left">Saudi Arabia</td>
<td align="left">International Journal of Electronic Healthcare</td>
<td align="left">Adults</td>
<td align="center">NA</td>
<td align="left">Survey</td>
<td align="left">NS</td>
</tr>
<tr>
<td align="left">Alwhaibi et al</td>
<td align="left">2021</td>
<td align="left">Saudi Arabia</td>
<td align="left">Saudi Pharmaceutical Journal</td>
<td align="left">Adults</td>
<td align="center">643</td>
<td align="left">Survey</td>
<td align="left">Both</td>
</tr>
<tr>
<td align="left">Anis and Tan</td>
<td align="left">2023</td>
<td align="left">Malaysia</td>
<td align="left">International Journal of Healthcare Management</td>
<td align="left">Adults</td>
<td align="center">13</td>
<td align="left">Interview</td>
<td align="left">OTC</td>
</tr>
<tr>
<td align="left">Ashames et al</td>
<td align="left">2019</td>
<td align="left">UAE</td>
<td align="left">Journal of Pharmacy and Bioallied Sciences</td>
<td align="left">Adults</td>
<td align="center">528</td>
<td align="left">Survey</td>
<td align="left">Prescription</td>
</tr>
<tr>
<td align="left">Bansal et al</td>
<td align="left">2022</td>
<td align="left">India</td>
<td align="left">Indian Journal of Pharmacology</td>
<td align="left">Adults</td>
<td align="center">322</td>
<td align="left">Survey</td>
<td align="left">NS</td>
</tr>
<tr>
<td align="left">Brijnath et al</td>
<td align="left">2015</td>
<td align="left">Australia</td>
<td align="left">Patient</td>
<td align="left">Adults</td>
<td align="center">50</td>
<td align="left">Interview</td>
<td align="left">NS</td>
</tr>
<tr>
<td align="left">Bowman et al</td>
<td align="left">2020</td>
<td align="left">Malta</td>
<td align="left">Research in Social and Administrative Pharmacy</td>
<td align="left">Adults</td>
<td align="center">444</td>
<td align="left">Survey</td>
<td align="left">OTC</td>
</tr>
<tr>
<td align="left">Brown and Li</td>
<td align="left">2014</td>
<td align="left">United States</td>
<td align="left">Journal of the American Pharmacists Association</td>
<td align="left">Adults</td>
<td align="center">443</td>
<td align="left">Survey</td>
<td align="left">Prescription</td>
</tr>
<tr>
<td align="left">Cicero and Ellis</td>
<td align="left">2012</td>
<td align="left">United States</td>
<td align="left">Journal of Medical Internet Research</td>
<td align="left">Patients</td>
<td align="center">96</td>
<td align="left">Survey</td>
<td align="left">Prescription</td>
</tr>
<tr>
<td align="left">Cokro and Arfenda</td>
<td align="left">2023</td>
<td align="left">Indonesia</td>
<td align="left">Pharmacy Education</td>
<td align="left">Students</td>
<td align="center">95</td>
<td align="left">Survey</td>
<td align="left">OTC</td>
</tr>
<tr>
<td align="left">Desai et al</td>
<td align="left">2015</td>
<td align="left">United States</td>
<td align="left">Research in Social and Administrative Pharmacy</td>
<td align="left">Adults</td>
<td align="center">871</td>
<td align="left">Survey</td>
<td align="left">NS</td>
</tr>
<tr>
<td align="left">Fittler et al</td>
<td align="left">2018</td>
<td align="left">Hungary</td>
<td align="left">Journal of Medical Internet Research</td>
<td align="left">Patients</td>
<td align="center">1,055</td>
<td align="left">Survey</td>
<td align="left">NS</td>
</tr>
<tr>
<td align="left">Fittler et al</td>
<td align="left">2022</td>
<td align="left">Czech Republic, Hungary, Poland, Slovakia</td>
<td align="left">Frontiers in Pharmacology</td>
<td align="left">Adults</td>
<td align="center">2087</td>
<td align="left">Survey</td>
<td align="left">NS</td>
</tr>
<tr>
<td align="left">Gharaibeh et al</td>
<td align="left">2023</td>
<td align="left">Jordan</td>
<td align="left">BMJ Open</td>
<td align="left">Adults</td>
<td align="center">428</td>
<td align="left">Survey</td>
<td align="left">NS</td>
</tr>
<tr>
<td align="left">Hamdan</td>
<td align="left">2023</td>
<td align="left">Jordan</td>
<td align="left">Journal of Pharmaceutical Health Services Research</td>
<td align="left">Adults</td>
<td align="center">460</td>
<td align="left">Survey</td>
<td align="left">NS</td>
</tr>
<tr>
<td align="left">Han and Han</td>
<td align="left">2023</td>
<td align="left">China</td>
<td align="left">Frontiers in Public Health</td>
<td align="left">Adults</td>
<td align="center">414</td>
<td align="left">Survey</td>
<td align="left">NS</td>
</tr>
<tr>
<td align="left">Hawdon et al</td>
<td align="left">2022</td>
<td align="left">United States</td>
<td align="left">American Journal of Criminal Justice</td>
<td align="left">Adults</td>
<td align="center">1,101, 1,037, 1,250, 1,205</td>
<td align="left">Longitudinal Survey</td>
<td align="left">NS</td>
</tr>
<tr>
<td align="left">Holiday-Goodman et al</td>
<td align="left">2007</td>
<td align="left">United States</td>
<td align="left">Journal of Pharmacy Technology</td>
<td align="left">Adults</td>
<td align="center">91</td>
<td align="left">Survey</td>
<td align="left">Prescription</td>
</tr>
<tr>
<td align="left">Holtgrafe and Zentes</td>
<td align="left">2012</td>
<td align="left">Germany</td>
<td align="left">Health Informatics Journal</td>
<td align="left">Adults</td>
<td align="center">314</td>
<td align="left">Survey</td>
<td align="left">OTC</td>
</tr>
<tr>
<td align="left">Hu et al</td>
<td align="left">2021</td>
<td align="left">China</td>
<td align="left">Transformations in Business &#x26; Economics</td>
<td align="left">Adults</td>
<td align="center">202</td>
<td align="left">Survey</td>
<td align="left">OTC</td>
</tr>
<tr>
<td align="left">Ivanitskaya et al</td>
<td align="left">2010</td>
<td align="left">United States</td>
<td align="left">Journal of Medical Internet Research</td>
<td align="left">Students</td>
<td align="center">1914</td>
<td align="left">Survey</td>
<td align="left">Prescription</td>
</tr>
<tr>
<td align="left">Jairoun et al</td>
<td align="left">2021</td>
<td align="left">UAE</td>
<td align="left">Journal of Pharmaceutical Policy and Practice</td>
<td align="left">Adults</td>
<td align="center">131</td>
<td align="left">Survey</td>
<td align="left">Both</td>
</tr>
<tr>
<td align="left">Koenraadt and van de Ven</td>
<td align="left">2018</td>
<td align="left">Netherlands</td>
<td align="left">Drugs: Education, Prevention and Policy</td>
<td align="left">Adults</td>
<td align="center">158</td>
<td align="left">Survey</td>
<td align="left">Lifestyle drugs</td>
</tr>
<tr>
<td align="left">Little et al</td>
<td align="left">2020</td>
<td align="left">Australia, Canada, Ireland, Portugal, Sweden, UK</td>
<td align="left">Evidence Based Midwifery</td>
<td align="left">Pregnant women</td>
<td align="center">23</td>
<td align="left">Focus group</td>
<td align="left">NS</td>
</tr>
<tr>
<td align="left">Ma</td>
<td align="left">2021</td>
<td align="left">China</td>
<td align="left">Journal of Engineering and Technology Management</td>
<td align="left">Adults</td>
<td align="center">355</td>
<td align="left">Survey</td>
<td align="left">NS</td>
</tr>
<tr>
<td align="left">Mekawie and Hany</td>
<td align="left">2019</td>
<td align="left">Egypt</td>
<td align="left">Procedia Computer Science</td>
<td align="left">Adults</td>
<td align="center">210</td>
<td align="left">Survey</td>
<td align="left">OTC</td>
</tr>
<tr>
<td align="left">Moureaud et al</td>
<td align="left">2021</td>
<td align="left">United States</td>
<td align="left">Health Policy</td>
<td align="left">MTurk workers</td>
<td align="center">730</td>
<td align="left">Survey</td>
<td align="left">Prescription</td>
</tr>
<tr>
<td align="left">Ndem et al</td>
<td align="left">2019</td>
<td align="left">Nigeria</td>
<td align="left">Pharmacy Practice</td>
<td align="left">Adults</td>
<td align="center">500</td>
<td align="left">Survey</td>
<td align="left">NS</td>
</tr>
<tr>
<td align="left"/>
<td align="left"/>
<td align="left"/>
<td align="left"/>
<td align="left"/>
<td align="left"/>
<td align="left"/>
<td align="left"/>
</tr>
<tr>
<td align="left">Rajamma and Pelton</td>
<td align="left">2009</td>
<td align="left">United States</td>
<td align="left">Psychology &#x26; Marketing</td>
<td align="left">Baby Boomers</td>
<td align="center">350</td>
<td align="left">Survey</td>
<td align="left">Both</td>
</tr>
<tr>
<td align="left">Roblek et al</td>
<td align="left">2018</td>
<td align="left">Slovenia</td>
<td align="left">International Journal of Electronic Marketing and Retailing</td>
<td align="left">Adults</td>
<td align="center">378</td>
<td align="left">Survey</td>
<td align="left">OTC</td>
</tr>
<tr>
<td align="left">Sabbir et al</td>
<td align="left">2021</td>
<td align="left">Bangladesh</td>
<td align="left">Journal of Science and Technology Policy Management</td>
<td align="left">Young people</td>
<td align="center">285</td>
<td align="left">Survey</td>
<td align="left">NS</td>
</tr>
<tr>
<td align="left">Sinclair et al</td>
<td align="left">2018</td>
<td align="left">UK</td>
<td align="left">Journal of Advanced Nursing</td>
<td align="left">Pregnant women</td>
<td align="center">284</td>
<td align="left">Survey</td>
<td align="left">NS</td>
</tr>
<tr>
<td align="left">Soboleva et al</td>
<td align="left">2022</td>
<td align="left">Russia</td>
<td align="left">Journal of Advanced Pharmaceutical Technology &#x26; Research</td>
<td align="left">Adults</td>
<td align="center">3,789</td>
<td align="left">Survey</td>
<td align="left">NS</td>
</tr>
<tr>
<td align="left">Srivastava and Raina</td>
<td align="left">2020</td>
<td align="left">India</td>
<td align="left">International Journal of Pharmaceutical and Healthcare Marketing</td>
<td align="left">Adults</td>
<td align="center">184</td>
<td align="left">Survey</td>
<td align="left">NS</td>
</tr>
<tr>
<td align="left">Szekely et al</td>
<td align="left">2015</td>
<td align="left">Romania</td>
<td align="left">Farmacia</td>
<td align="left">Patients</td>
<td align="center">253</td>
<td align="left">Survey</td>
<td align="left">NS</td>
</tr>
<tr>
<td align="left">Tang et al</td>
<td align="left">2023</td>
<td align="left">Japan</td>
<td align="left">Frontiers in Digital Health</td>
<td align="left">Adults</td>
<td align="center">288</td>
<td align="left">Survey</td>
<td align="left">OTC</td>
</tr>
<tr>
<td align="left">Van Buskirk et al</td>
<td align="left">2016</td>
<td align="left">Australia</td>
<td align="left">International Journal of Drug Policy</td>
<td align="left">Adults</td>
<td align="center">66</td>
<td align="left">Survey</td>
<td align="left">NS</td>
</tr>
<tr>
<td align="left">Varghese Assin et al</td>
<td align="left">2022</td>
<td align="left">India</td>
<td align="left">Special Education</td>
<td align="left">Adults</td>
<td align="center">750</td>
<td align="left">Survey</td>
<td align="left">NS</td>
</tr>
<tr>
<td align="left">Vera-Mart&#xed;nez</td>
<td align="left">2023</td>
<td align="left">Mexico</td>
<td align="left">International Journal of Pharmaceutical and Healthcare Marketing</td>
<td align="left">Adults</td>
<td align="center">271</td>
<td align="left">Survey</td>
<td align="left">NS</td>
</tr>
<tr>
<td align="left">Wiedmann et al</td>
<td align="left">2010</td>
<td align="left">Germany</td>
<td align="left">Journal of Customer Behaviour</td>
<td align="left">Adults</td>
<td align="center">152</td>
<td align="left">Interview</td>
<td align="left">NS</td>
</tr>
</tbody>
</table>
<table-wrap-foot>
<fn>
<p>Note: OTC, over the counter; Both &#x3d; prescription and OTC; NS, not specified.</p>
</fn>
</table-wrap-foot>
</table-wrap>
<p>All studies, except a longitudinal study by <xref ref-type="bibr" rid="B30">Hawdon et al. (2022)</xref>, were cross-sectional. Forty-two studies employed survey methodology, four interviewed adult individuals, one used a focus group, and another conducted an experiment Three studies were published in the <italic>Journal of Medical Internet Research</italic>, and three appeared in the <italic>Saudi Pharmaceutical Journal</italic>. The included studies recruited 27,323 respondents, with an average sample size of 581.34 (standard deviation &#x3d; 651.23), ranging from 13 to 3,789. Thirty-seven studies focused on the general adult population, three on patients, two on women, two on students, and three on other populations. Eight studies focused on prescription drugs, eight studies on OTC medication, and the remainder either included both or did not specify.</p>
<p>
<xref ref-type="fig" rid="F2">Figure 2</xref> shows consistently few studies conducted on the topic until 2014. Four studies were published in 2015, then the publications sharply fell in 2016 and 2017. Beginning in 2018, we see a growing wave of publications peaking in 2023, with twelve studies.</p>
<fig id="F2" position="float">
<label>FIGURE 2</label>
<caption>
<p>Number of studies by year.</p>
</caption>
<graphic xlink:href="fphar-15-1356059-g002.tif"/>
</fig>
</sec>
<sec id="s3-2">
<title>3.2 Differences in influences between OTC and prescription drugs</title>
<p>Our analysis of prior studies revealed some differences between OTC and prescription medication in factors influencing online purchase intentions and behaviors. Intentions toward online purchases of prescription medications were primarily motivated by price, availability, convenience, and education. Prescription drug online purchase behavior was adversely affected by perceived risk. Purchase behavior was positively related to health insurance coverage, information sources, and convenience.</p>
<p>Most studies involving OTC medication studied purchase behavior. The major driving forces of consumer purchases of OTC medication online were information sources, availability, internet usage, and convenience. Evaluation of the purchase environment, information sources, and prior experience primarily influenced purchase intentions toward OTC medication online.</p>
</sec>
<sec id="s3-3">
<title>3.3 Factors influencing purchase intention and behavior from online pharmacies</title>
<sec id="s3-3-1">
<title>3.3.1 Demographics</title>
<p>As shown in <xref ref-type="table" rid="T3">Table 3</xref>, education, gender, and income were the most frequent demographic predictors of purchase intentions toward online pharmacies. However, the scoping review reveals some contradictory findings. Higher education was at times associated with increased purchase intentions (<xref ref-type="bibr" rid="B31">Holiday-Goodman et al., 2007</xref>; <xref ref-type="bibr" rid="B57">Sinclair et al., 2018</xref>; <xref ref-type="bibr" rid="B33">Hu et al., 2021</xref>). In contrast, another study indicated that individuals with lower education levels had greater intentions to purchase from an online pharmacy (<xref ref-type="bibr" rid="B34">Ivanitskaya et al., 2010</xref>). <xref ref-type="bibr" rid="B31">Holiday-Goodman et al. (2007)</xref> found that American males had greater intentions toward online pharmacy purchases than females. In contrast, <xref ref-type="bibr" rid="B33">Hu et al. (2021)</xref> showed that Chinese females had greater online purchase intentions for OTC medications online than did males. Higher incomes increased consumers&#x2019; online medicine purchase intentions (<xref ref-type="bibr" rid="B31">Holiday-Goodman et al., 2007</xref>; <xref ref-type="bibr" rid="B33">Hu et al., 2021</xref>). Online pharmacy purchase intentions also were greater among young, White, and married consumers (<xref ref-type="bibr" rid="B31">Holiday-Goodman et al., 2007</xref>).</p>
<table-wrap id="T3" position="float">
<label>TABLE 3</label>
<caption>
<p>Factors influencing purchase intention and behavior from online pharmacies.</p>
</caption>
<table>
<thead valign="top">
<tr>
<th align="left">Factors</th>
<th align="left">Intention</th>
<th align="left">Behavior</th>
</tr>
</thead>
<tbody valign="top">
<tr>
<td rowspan="13" align="left">Demographics</td>
<td align="left">Education (higher) <xref ref-type="bibr" rid="B31">Holiday-Goodman et al. (2007)</xref>; <xref ref-type="bibr" rid="B57">Sinclair et al. (2018)</xref>; <xref ref-type="bibr" rid="B33">Hu et al. (2021)</xref>
</td>
<td align="left">Age (older) <xref ref-type="bibr" rid="B17">Brown and Li, (2014)</xref>; <xref ref-type="bibr" rid="B21">Desai et al. (2015)</xref>; <xref ref-type="bibr" rid="B35">Jairoun et al. (2021)</xref>; <xref ref-type="bibr" rid="B58">Soboleva et al. (2022)</xref>; <xref ref-type="bibr" rid="B19">Cokro and Arfenda, (2023)</xref>
</td>
</tr>
<tr>
<td align="left">Education (lower) <xref ref-type="bibr" rid="B34">Ivanitskaya et al. (2010)</xref>
</td>
<td align="left">Age (younger) <xref ref-type="bibr" rid="B61">Szekely et al. (2015)</xref>; <xref ref-type="bibr" rid="B64">Van Buskirk et al. 2(016)</xref>; <xref ref-type="bibr" rid="B66">Vera-Mart&#xed;nez, (2023)</xref>
</td>
</tr>
<tr>
<td align="left">Gender (male) <xref ref-type="bibr" rid="B31">Holiday-Goodman et al. (2007)</xref>
</td>
<td align="left">Education (higher) <xref ref-type="bibr" rid="B52">Rajamma and Pelton, (2009)</xref>; <xref ref-type="bibr" rid="B17">Brown and Li, (2014)</xref>; <xref ref-type="bibr" rid="B53">Roblek et al. (2018)</xref>
</td>
</tr>
<tr>
<td align="left">Gender (female) <xref ref-type="bibr" rid="B33">Hu et al. (2021)</xref>
</td>
<td align="left">Education (high school) <xref ref-type="bibr" rid="B35">Jairoun et al. (2021)</xref>
</td>
</tr>
<tr>
<td align="left">Income (higher) <xref ref-type="bibr" rid="B31">Holiday-Goodman et al. (2007)</xref>; <xref ref-type="bibr" rid="B33">Hu et al. (2021)</xref>
</td>
<td align="left">Education (high school or university) <xref ref-type="bibr" rid="B61">Szekely et al. (2015)</xref>
</td>
</tr>
<tr>
<td align="left">Age (younger) <xref ref-type="bibr" rid="B31">Holiday-Goodman et al. (2007)</xref>
</td>
<td align="left">Gender (male) <xref ref-type="bibr" rid="B52">Rajamma and Pelton, (2009)</xref>; <xref ref-type="bibr" rid="B61">Szekely et al. (2015)</xref>; <xref ref-type="bibr" rid="B35">Jairoun et al. (2021)</xref>
</td>
</tr>
<tr>
<td align="left">Race (White) <xref ref-type="bibr" rid="B31">Holiday-Goodman et al. (2007)</xref>
</td>
<td align="left">Gender (female) <xref ref-type="bibr" rid="B58">Soboleva et al. (2022)</xref>
</td>
</tr>
<tr>
<td rowspan="6" align="left">Marital status (married) <xref ref-type="bibr" rid="B31">Holiday-Goodman et al. (2007)</xref>
</td>
<td align="left">Income (higher) <xref ref-type="bibr" rid="B52">Rajamma and Pelton, (2009)</xref>; <xref ref-type="bibr" rid="B17">Brown and Li, (2014)</xref>; <xref ref-type="bibr" rid="B21">Desai et al. (2015)</xref>; <xref ref-type="bibr" rid="B53">Roblek et al. (2018)</xref>
</td>
</tr>
<tr>
<td align="left">Race (White) <xref ref-type="bibr" rid="B17">Brown and Li, (2014)</xref>
</td>
</tr>
<tr>
<td align="left">
<italic>Race (Black) <xref ref-type="bibr" rid="B17">Brown and Li, (2014)</xref>
</italic>
</td>
</tr>
<tr>
<td align="left">Marital status (married) <xref ref-type="bibr" rid="B17">Brown and Li, (2014)</xref>
</td>
</tr>
<tr>
<td align="left">Marital status (single) <xref ref-type="bibr" rid="B35">Jairoun et al. (2021)</xref>
</td>
</tr>
<tr>
<td align="left">Location (urban area) <xref ref-type="bibr" rid="B53">Roblek et al. (2018)</xref>
</td>
</tr>
<tr>
<td rowspan="8" align="left">Convenience</td>
<td align="left">Fast delivery, choices of delivery times and address, reduced visit to the pharmacy, easy telephone access to the pharmacist for drug information <xref ref-type="bibr" rid="B4">Alfahad et al. (2015)</xref>
</td>
<td align="left">Convenience <xref ref-type="bibr" rid="B16">Brijnath et al. (2015)</xref>; <xref ref-type="bibr" rid="B1">Abanmy, (2017)</xref>; <xref ref-type="bibr" rid="B37">Koenraadt and van de Ven, (2018)</xref>; <xref ref-type="bibr" rid="B42">Little et al. (2020)</xref>; <xref ref-type="bibr" rid="B7">Almomani et al. (2023)</xref>; <xref ref-type="bibr" rid="B11">Anis and Tan, (2023)</xref>; <xref ref-type="bibr" rid="B62">Tang et al. (2023)</xref>
</td>
</tr>
<tr>
<td align="left">Perceived ease of use <xref ref-type="bibr" rid="B3">Ahmed et al. (2023)</xref>
</td>
<td align="left">Time saving <xref ref-type="bibr" rid="B6">Almohammed et al. (2023)</xref>; <xref ref-type="bibr" rid="B7">Almomani et al. (2023)</xref>
</td>
</tr>
<tr>
<td align="left">Home delivery <xref ref-type="bibr" rid="B3">Ahmed et al. (2023)</xref>
</td>
<td align="left">Easy access <xref ref-type="bibr" rid="B10">Alwhaibi et al. (2021)</xref>; <xref ref-type="bibr" rid="B7">Almomani et al. (2023)</xref>
</td>
</tr>
<tr>
<td align="left">Accessibility (cannot find a doctor who will prescribe, doctor will not prescribe enough, no other way to get it) <xref ref-type="bibr" rid="B18">Cicero and Ellis, (2012)</xref>
</td>
<td align="left">Bypassing gatekeepers <xref ref-type="bibr" rid="B7">Almomani et al. (2023)</xref>
</td>
</tr>
<tr>
<td align="left">Convenience <xref ref-type="bibr" rid="B31">Holiday-Goodman et al. (2007)</xref>
</td>
<td align="left">Home delivery <xref ref-type="bibr" rid="B37">Koenraadt and van de Ven, (2018)</xref>
</td>
</tr>
<tr>
<td rowspan="3" align="left">Consumer is a convenience-oriented rationalist toward online pharmacies <xref ref-type="bibr" rid="B68">Wiedmann et al. (2010)</xref>
</td>
<td align="left">Importance of rapid retrieval of information <xref ref-type="bibr" rid="B42">Little et al. (2020)</xref>
</td>
</tr>
<tr>
<td align="left">Price comparison <xref ref-type="bibr" rid="B42">Little et al. (2020)</xref>
</td>
</tr>
<tr>
<td align="left">Time-efficiency <xref ref-type="bibr" rid="B42">Little et al. (2020)</xref>
</td>
</tr>
<tr>
<td rowspan="5" align="left">Availability</td>
<td align="left">Unavailable in local market <xref ref-type="bibr" rid="B57">Sinclair et al. (2018)</xref>; <xref ref-type="bibr" rid="B13">Ashames et al. (2019)</xref>; <xref ref-type="bibr" rid="B14">Bansal et al. (2022)</xref>
</td>
<td align="left">Availability of various drug products and more options <xref ref-type="bibr" rid="B42">Little et al. (2020)</xref>; <xref ref-type="bibr" rid="B19">Cokro and Arfenda, (2023)</xref>
</td>
</tr>
<tr>
<td rowspan="4" align="left">Ability to get legitimate medicine from online pharmacies <xref ref-type="bibr" rid="B47">Moureaud et al. (2021)</xref>
</td>
<td align="left">Unavailable in local market <xref ref-type="bibr" rid="B1">Abanmy, (2017)</xref>; <xref ref-type="bibr" rid="B15">Bowman et al. (2020)</xref>
</td>
</tr>
<tr>
<td align="left">Wide-spread availability <xref ref-type="bibr" rid="B62">Tang et al. (2023)</xref>
</td>
</tr>
<tr>
<td align="left">Not for sale in the country <xref ref-type="bibr" rid="B37">Koenraadt and van de Ven, (2018)</xref>)</td>
</tr>
<tr>
<td align="left">24-h availability <xref ref-type="bibr" rid="B62">Tang et al. (2023)</xref>
</td>
</tr>
<tr>
<td rowspan="5" align="left">Price</td>
<td align="left">Differences in the prices <xref ref-type="bibr" rid="B14">Bansal et al. (2022)</xref>
</td>
<td align="left">Lower price <xref ref-type="bibr" rid="B16">Brijnath et al. (2015)</xref>; <xref ref-type="bibr" rid="B64">Van Buskirk et al. (2016)</xref>; <xref ref-type="bibr" rid="B1">Abanmy, (2017)</xref>; <xref ref-type="bibr" rid="B37">Koenraadt and van de Ven, (2018)</xref>; <xref ref-type="bibr" rid="B15">Bowman et al. (2020)</xref>; <xref ref-type="bibr" rid="B10">Alwhaibi et al. (2021)</xref>; <xref ref-type="bibr" rid="B6">Almohammed et al. (2023)</xref>; <xref ref-type="bibr" rid="B7">Almomani et al. (2023)</xref>
</td>
</tr>
<tr>
<td align="left">Lower price <xref ref-type="bibr" rid="B18">Cicero and Ellis, (2012)</xref>; <xref ref-type="bibr" rid="B57">Sinclair et al. (2018)</xref>; <xref ref-type="bibr" rid="B13">Ashames et al. (2019)</xref>; <xref ref-type="bibr" rid="B2">Adjie et al. (2023)</xref>
</td>
<td align="left">Cost-effectiveness <xref ref-type="bibr" rid="B42">Little et al. (2020)</xref>
</td>
</tr>
<tr>
<td align="left">Price value <xref ref-type="bibr" rid="B29">Han and Han, (2023)</xref>
</td>
<td align="left">
<italic>Higher price</italic> <xref ref-type="bibr" rid="B7">Almomani et al. (2023)</xref>
</td>
</tr>
<tr>
<td align="left">Deals <xref ref-type="bibr" rid="B47">Moureaud et al. (2021)</xref>
</td>
<td align="left">Offers and discounts <xref ref-type="bibr" rid="B6">Almohammed et al. (2023)</xref>
</td>
</tr>
<tr>
<td align="left"/>
<td align="left">Special offers <xref ref-type="bibr" rid="B42">Little et al. (2020)</xref>
</td>
</tr>
<tr>
<td rowspan="17" align="left">Evaluations of purchase environment</td>
<td align="left">Attitude toward online pharmacies <xref ref-type="bibr" rid="B33">Hu et al. (2021)</xref>; <xref ref-type="bibr" rid="B29">Han and Han, (2023)</xref>
</td>
<td align="left">Trust in buying OTC drugs online <xref ref-type="bibr" rid="B53">Roblek et al. (2018)</xref>
</td>
</tr>
<tr>
<td align="left">View pharmacy website design as attractive and useful <xref ref-type="bibr" rid="B33">Hu et al. (2021)</xref>
</td>
<td align="left">Trust in purchasing drugs from online resources <xref ref-type="bibr" rid="B26">Gharaibeh et al. (2023)</xref>
</td>
</tr>
<tr>
<td align="left">Emotional response to online pharmacies <xref ref-type="bibr" rid="B33">Hu et al. (2021)</xref>
</td>
<td align="left">Trust in online pharmacy websites <xref ref-type="bibr" rid="B7">Almomani et al. (2023)</xref>
</td>
</tr>
<tr>
<td align="left">Attitude toward online pharmacy logistics and distribution <xref ref-type="bibr" rid="B33">Hu et al. (2021)</xref>
</td>
<td rowspan="14" align="left">Perceived benefits of online drug purchasing <xref ref-type="bibr" rid="B26">Gharaibeh et al. (2023)</xref>
</td>
</tr>
<tr>
<td align="left">Perceived usefulness of online pharmacies <xref ref-type="bibr" rid="B44">Ma, (2021)</xref>
</td>
</tr>
<tr>
<td align="left">Perceived behavioral control <xref ref-type="bibr" rid="B29">Han and Han, (2023)</xref>
</td>
</tr>
<tr>
<td align="left">Trustworthiness of online pharmacies <xref ref-type="bibr" rid="B44">Ma, (2021)</xref>; <xref ref-type="bibr" rid="B54">Sabbir et al. (2021)</xref>
</td>
</tr>
<tr>
<td align="left">Trust in e-marketplace <xref ref-type="bibr" rid="B2">Adjie et al. (2023)</xref>
</td>
</tr>
<tr>
<td align="left">Trust in website technology <xref ref-type="bibr" rid="B9">Alsadoun et al. (2023)</xref>
</td>
</tr>
<tr>
<td align="left">Perceived trust in app-based medicine service <xref ref-type="bibr" rid="B3">Ahmed et al. (2023)</xref>
</td>
</tr>
<tr>
<td align="left">Perceived website system and service quality <xref ref-type="bibr" rid="B2">Adjie et al. (2023)</xref>
</td>
</tr>
<tr>
<td align="left">Online pharmacies provide a reliable source for purchases <xref ref-type="bibr" rid="B47">Moureaud et al. (2021)</xref>
</td>
</tr>
<tr>
<td align="left">Effort expectancy (usage of online pharmacy is simple, clear and justifiable) <xref ref-type="bibr" rid="B59">Srivastava and Raina, (2020)</xref>; <xref ref-type="bibr" rid="B54">Sabbir et al. (2021)</xref>
</td>
</tr>
<tr>
<td align="left">Facilitating conditions (organizational and technical infrastructures assist consumers to use online pharmacy) <xref ref-type="bibr" rid="B54">Sabbir et al. (2021)</xref>
</td>
</tr>
<tr>
<td align="left">Performance expectancy (i.e., usefulness of online pharmacies) <xref ref-type="bibr" rid="B59">Srivastava and Raina, (2020)</xref>; <xref ref-type="bibr" rid="B54">Sabbir et al. (2021)</xref>
</td>
</tr>
<tr>
<td align="left">Hedonic motivation (i.e., enjoy using online pharmacies) <xref ref-type="bibr" rid="B59">Srivastava and Raina, (2020)</xref>
</td>
</tr>
<tr>
<td align="left">Satisfaction with the e-marketplace <xref ref-type="bibr" rid="B2">Adjie et al. (2023)</xref>
</td>
</tr>
<tr>
<td rowspan="4" align="left">Internet usage</td>
<td rowspan="4" align="left">Time spent on internet <xref ref-type="bibr" rid="B25">Fittler et al. (2018)</xref>
</td>
<td align="left">Frequency of internet usage <xref ref-type="bibr" rid="B53">Roblek et al. (2018)</xref>
</td>
</tr>
<tr>
<td align="left">Frequency of usage of social media <xref ref-type="bibr" rid="B53">Roblek et al. (2018)</xref>
</td>
</tr>
<tr>
<td align="left">Preferred use of the internet as a source of OTC drug information <xref ref-type="bibr" rid="B32">Holtgrafe and Zentes, (2012)</xref>
</td>
</tr>
<tr>
<td align="left">Information surfers (people who gather information on the internet) <xref ref-type="bibr" rid="B66">Vera-Mart&#xed;nez, (2023)</xref>
</td>
</tr>
<tr>
<td rowspan="9" align="left">Information sources</td>
<td align="left">Word-of-mouth (WOM) online <xref ref-type="bibr" rid="B70">Lee et al. (2017)</xref> e-WOM (sharing on Facebook, comment posting on Facebook, Facebook friends&#x2019; likes) <xref ref-type="bibr" rid="B46">Mekawie and Hany, (2019)</xref>
</td>
<td align="left">Word-of-mouth from friends <xref ref-type="bibr" rid="B7">Almomani et al. (2023)</xref>
</td>
</tr>
<tr>
<td align="left">Drug information provided on website <xref ref-type="bibr" rid="B33">Hu et al. (2021)</xref>
</td>
<td align="left">Social media marketing <xref ref-type="bibr" rid="B11">Anis and Tan, (2023)</xref>
</td>
</tr>
<tr>
<td align="left">Information quality on e-pharmacy websites <xref ref-type="bibr" rid="B2">Adjie et al. (2023)</xref>
</td>
<td align="left">Influencers&#x2019; endorsement <xref ref-type="bibr" rid="B7">Almomani et al. (2023)</xref>
</td>
</tr>
<tr>
<td align="left">Recommended by family, friend, advertisers, or cultural sources <xref ref-type="bibr" rid="B33">Hu et al. (2021)</xref>
</td>
<td align="left">Information provided by suppliers <xref ref-type="bibr" rid="B19">Cokro and Arfenda, (2023)</xref>
</td>
</tr>
<tr>
<td align="left">Recommendations from others <xref ref-type="bibr" rid="B47">Moureaud et al. (2021)</xref>
</td>
<td align="left">Consumers&#x2019; reviews <xref ref-type="bibr" rid="B7">Almomani et al. (2023)</xref>; <xref ref-type="bibr" rid="B11">Anis and Tan, (2023)</xref>
</td>
</tr>
<tr>
<td align="left">Social influence (influence from friends and families) <xref ref-type="bibr" rid="B59">Srivastava and Raina, (2020)</xref>; <xref ref-type="bibr" rid="B54">Sabbir et al. (2021)</xref>
</td>
<td rowspan="2" align="left">Interactions with healthcare providers <xref ref-type="bibr" rid="B7">Almomani et al. (2023)</xref>; <xref ref-type="bibr" rid="B21">Desai et al. (2015)</xref>
</td>
</tr>
<tr>
<td rowspan="3" align="left">Subjective norms <xref ref-type="bibr" rid="B2">Adjie et al. (2023)</xref>; <xref ref-type="bibr" rid="B29">Han and Han, (2023)</xref>
</td>
</tr>
<tr>
<td align="left">Recommendations from experts or non-experts <xref ref-type="bibr" rid="B11">Anis and Tan, (2023)</xref>
</td>
</tr>
<tr>
<td align="left">
<italic>Powerful others health locus of control</italic> (influence of healthcare provider) <xref ref-type="bibr" rid="B52">Rajamma and Pelton, (2009)</xref>
</td>
</tr>
<tr>
<td rowspan="5" align="left">Perceived risk</td>
<td align="left">
<italic>Perceived risk</italic> <xref ref-type="bibr" rid="B33">Hu et al. (2021)</xref>
</td>
<td align="left">
<italic>Medicine safety concerns</italic> <xref ref-type="bibr" rid="B7">Almomani et al. (2023)</xref>
</td>
</tr>
<tr>
<td rowspan="4" align="left">
<italic>Perceived risk (financial risk, physical risk, source risk)</italic> <xref ref-type="bibr" rid="B65">Varghese Assin et al. (2022)</xref>
</td>
<td align="left">
<italic>Medicine quality concerns</italic> <xref ref-type="bibr" rid="B7">Almomani et al. (2023)</xref>
</td>
</tr>
<tr>
<td align="left">
<italic>Web-based payment</italic> <xref ref-type="bibr" rid="B7">Almomani et al. (2023)</xref>
</td>
</tr>
<tr>
<td align="left">
<italic>Lack of accountability</italic> <xref ref-type="bibr" rid="B7">Almomani et al. (2023)</xref>
</td>
</tr>
<tr>
<td align="left">
<italic>Engaging in an illegal behavior</italic> <xref ref-type="bibr" rid="B7">Almomani et al. (2023)</xref>
</td>
</tr>
<tr>
<td rowspan="7" align="left">Prior experience</td>
<td align="left">Prior experience of purchase good online <xref ref-type="bibr" rid="B25">Fittler et al. (2018)</xref>; <xref ref-type="bibr" rid="B49">Ndem et al. (2019)</xref>
</td>
<td rowspan="7" align="left">Personal experience <xref ref-type="bibr" rid="B11">Anis and Tan, (2023)</xref>
</td>
</tr>
<tr>
<td align="left">Comfort with the network transaction environment <xref ref-type="bibr" rid="B33">Hu et al. (2021)</xref>
</td>
</tr>
<tr>
<td align="left">Years of experience with online shopping <xref ref-type="bibr" rid="B33">Hu et al. (2021)</xref>
</td>
</tr>
<tr>
<td align="left">Greater health literacy (ability to find, understand, and use information needed to purchase from online pharmacies) <xref ref-type="bibr" rid="B54">Sabbir et al. (2021)</xref>
</td>
</tr>
<tr>
<td align="left">Lower electronic health literacy <xref ref-type="bibr" rid="B34">Ivanitskaya et al. (2010)</xref>
</td>
</tr>
<tr>
<td align="left">Awareness of online pharmacy website technology <xref ref-type="bibr" rid="B9">Alsadoun et al. (2023)</xref>
</td>
</tr>
<tr>
<td align="left">Consumer is an enthusiastic expert about online pharmacies <xref ref-type="bibr" rid="B68">Wiedmann et al. (2010)</xref>
</td>
</tr>
<tr>
<td rowspan="4" align="left">Health insurance</td>
<td rowspan="4" align="left">No healthcare coverage <xref ref-type="bibr" rid="B18">Cicero and Ellis, (2012)</xref>
</td>
<td align="left">Have higher health care expenditures <xref ref-type="bibr" rid="B17">Brown and Li, (2014)</xref>
</td>
</tr>
<tr>
<td align="left">More likely to be privately insured <xref ref-type="bibr" rid="B17">Brown and Li, (2014)</xref>
</td>
</tr>
<tr>
<td align="left">
<italic>Medicaid insurance coverage</italic> <xref ref-type="bibr" rid="B17">Brown and Li, (2014)</xref>
</td>
</tr>
<tr>
<td align="left">Health insurance coverage <xref ref-type="bibr" rid="B21">Desai et al. (2015)</xref>
</td>
</tr>
<tr>
<td rowspan="2" align="left">Privacy</td>
<td rowspan="2" align="left">Anonymity <xref ref-type="bibr" rid="B18">Cicero and Ellis, (2012)</xref>
</td>
<td align="left">More privacy <xref ref-type="bibr" rid="B10">Alwhaibi et al. (2021)</xref>; <xref ref-type="bibr" rid="B7">Almomani et al. (2023)</xref>
</td>
</tr>
<tr>
<td align="left">Do not want to discuss with doctor <xref ref-type="bibr" rid="B37">Koenraadt and van de Ven, (2018)</xref>
</td>
</tr>
<tr>
<td align="left">Product</td>
<td align="left">Product quality <xref ref-type="bibr" rid="B31">Holiday-Goodman et al. (2007)</xref>; <xref ref-type="bibr" rid="B64">Van Buskirk et al. (2016)</xref>
</td>
<td align="left">Product varieties <xref ref-type="bibr" rid="B10">Alwhaibi et al. (2021)</xref>; <xref ref-type="bibr" rid="B6">Almohammed et al. (2023)</xref>
</td>
</tr>
</tbody>
</table>
<table-wrap-foot>
<fn>
<p>Note: Italicized text indicates reported findings that are negatively related to purchase intention and behavior.</p>
</fn>
</table-wrap-foot>
</table-wrap>
<p>The most frequent demographic predictors of purchase behavior included age, education, gender, and income. Again, the evidence is contradictory. Five studies reported that more older consumers purchased from online pharmacies (Brown and Li, 2014; <xref ref-type="bibr" rid="B19">Cokro and Arfenda, 2023</xref>; <xref ref-type="bibr" rid="B21">Desai et al., 2015</xref>; <xref ref-type="bibr" rid="B35">Jairoun et al., 2021</xref>; <xref ref-type="bibr" rid="B58">Soboleva et al., 2022</xref>), whereas three studies found the opposite (<xref ref-type="bibr" rid="B61">Szekely et al., 2015</xref>; <xref ref-type="bibr" rid="B64">Van Buskirk et al., 2016</xref>; <xref ref-type="bibr" rid="B66">Vera-Mart&#xed;nez, 2023</xref>). In many studies, higher education was associated with increased purchase (e.g., <xref ref-type="bibr" rid="B52">Rajamma and Pelton, 2009</xref>; <xref ref-type="bibr" rid="B17">Brown and Li, 2014</xref>; <xref ref-type="bibr" rid="B61">Szekely et al., 2015</xref>; <xref ref-type="bibr" rid="B53">Roblek et al., 2018</xref>); however, <xref ref-type="bibr" rid="B35">Jairoun et al. (2021)</xref> found that consumers with less education were more likely to purchase medicine online. Three studies showed that males purchased medications online more frequently than females (<xref ref-type="bibr" rid="B52">Rajamma and Pelton, 2009</xref>; <xref ref-type="bibr" rid="B61">Szekely et al., 2015</xref>; <xref ref-type="bibr" rid="B35">Jairoun et al., 2021</xref>), whereas another study reported females as more likely to purchase online than males (<xref ref-type="bibr" rid="B58">Soboleva et al., 2022</xref>). Higher income was positively associated with increased medication purchases online (<xref ref-type="bibr" rid="B52">Rajamma and Pelton, 2009</xref>; <xref ref-type="bibr" rid="B17">Brown and Li, 2014</xref>; <xref ref-type="bibr" rid="B21">Desai et al., 2015</xref>; <xref ref-type="bibr" rid="B53">Roblek et al., 2018</xref>). <xref ref-type="bibr" rid="B17">Brown and Li (2014)</xref> found that black patients were associated with 53% lower odds of online pharmacy purchases than white patients. <xref ref-type="bibr" rid="B17">Brown and Li (2014)</xref> also reported that online pharmacy users were more likely to be married; however, <xref ref-type="bibr" rid="B35">Jairoun et al. (2021)</xref> found that single consumers purchased medication online more often than married consumers during the COVID-19 pandemic. OTC medicine was most often purchased online by young consumers living in urban areas than smaller settlements (<xref ref-type="bibr" rid="B53">Roblek et al., 2018</xref>).</p>
</sec>
<sec id="s3-3-2">
<title>3.3.2 Convenience</title>
<p>Convenience was a frequently demonstrated predictor of purchase intentions (<xref ref-type="bibr" rid="B31">Holiday-Goodman et al., 2007</xref>). Convenience-related factors, such as fast delivery, choices of delivery times and addresses, reduced visits to the pharmacy, and easy telephone access to the pharmacist for drug information were common reasons supporting intentions to purchase medications from online pharmacies (<xref ref-type="bibr" rid="B4">Alfahad et al., 2015</xref>). Other convenience-related factors that enhanced consumers&#x2019; willingness to buy medicine online were perceived ease of use of app-based medical services (<xref ref-type="bibr" rid="B3">Ahmed et al., 2023</xref>), home delivery (<xref ref-type="bibr" rid="B3">Ahmed et al., 2023</xref>), and accessibility of prescription medications (e.g., cannot find a physician who will prescribe, the physician will not prescribe enough, or no other way to get it) (<xref ref-type="bibr" rid="B18">Cicero and Ellis, 2012</xref>).</p>
<p>Convenience was also a dominant motivation for purchasing behavior. Consumers who bought medications online indicated that buying drugs online was more convenient (<xref ref-type="bibr" rid="B16">Brijnath et al., 2015</xref>; <xref ref-type="bibr" rid="B1">Abanmy, 2017</xref>; <xref ref-type="bibr" rid="B37">Koenraadt and van de Ven, 2018</xref>; <xref ref-type="bibr" rid="B42">Little et al., 2020</xref>; <xref ref-type="bibr" rid="B7">Almomani et al., 2023</xref>; <xref ref-type="bibr" rid="B11">Anis and Tan, 2023</xref>; <xref ref-type="bibr" rid="B62">Tang et al., 2023</xref>) and saved time (<xref ref-type="bibr" rid="B6">Almohammed et al., 2023</xref>; <xref ref-type="bibr" rid="B7">Almomani et al., 2023</xref>). Other convenience-related motivations included easy access (<xref ref-type="bibr" rid="B10">Alwhaibi et al., 2021</xref>; <xref ref-type="bibr" rid="B7">Almomani et al., 2023</xref>), bypassing gatekeepers (<xref ref-type="bibr" rid="B7">Almomani et al., 2023</xref>), home delivery (<xref ref-type="bibr" rid="B37">Koenraadt and van de Ven, 2018</xref>), the importance of rapid retrieval of information (<xref ref-type="bibr" rid="B42">Little et al., 2020</xref>), price comparison (<xref ref-type="bibr" rid="B42">Little et al., 2020</xref>), and time efficiency (<xref ref-type="bibr" rid="B42">Little et al., 2020</xref>).</p>
</sec>
<sec id="s3-3-3">
<title>3.3.3 Availability</title>
<p>Three studies reported that medication unavailability in the local market increased consumers&#x2019; intention to purchase over the Internet (<xref ref-type="bibr" rid="B57">Sinclair et al., 2018</xref>; <xref ref-type="bibr" rid="B13">Ashames et al., 2019</xref>; <xref ref-type="bibr" rid="B14">Bansal et al., 2022</xref>). <xref ref-type="bibr" rid="B47">Moureaud et al. (2021)</xref> found that getting legitimate medication was the most common reason that consumers intended to purchase medicine online.</p>
<p>The studies included in this review reveal that the availability of various drug products and more options (<xref ref-type="bibr" rid="B42">Little et al., 2020</xref>; <xref ref-type="bibr" rid="B19">Cokro and Arfenda, 2023</xref>), wide-spread availability (<xref ref-type="bibr" rid="B62">Tang et al., 2023</xref>), and 24-h availability (<xref ref-type="bibr" rid="B62">Tang et al., 2023</xref>) were primary motivators for purchasing medication online. Unavailability in the local market (<xref ref-type="bibr" rid="B1">Abanmy, 2017</xref>; <xref ref-type="bibr" rid="B15">Bowman et al., 2020</xref>) and drugs not for sale in a country (<xref ref-type="bibr" rid="B37">Koenraadt and van de Ven, 2018</xref>) were also positively related to increased purchase behavior.</p>
</sec>
<sec id="s3-3-4">
<title>3.3.4 Price</title>
<p>Pricing factors enhancing consumers&#x2019; purchase intentions toward drugs online included lower prices (<xref ref-type="bibr" rid="B18">Cicero and Ellis, 2012</xref>; <xref ref-type="bibr" rid="B57">Sinclair et al., 2018</xref>; <xref ref-type="bibr" rid="B13">Ashames et al., 2019</xref>; <xref ref-type="bibr" rid="B2">Adjie et al., 2023</xref>), differences in the prices (<xref ref-type="bibr" rid="B14">Bansal et al., 2022</xref>), and price value, which is the perceived benefits given the cost (<xref ref-type="bibr" rid="B29">Han and Han, 2023</xref>).</p>
<p>Several studies indicated that price significantly promoted medication purchases online. Nine studies found that lower prices were positively associated with increased purchase behavior (<xref ref-type="bibr" rid="B16">Brijnath et al., 2015</xref>; <xref ref-type="bibr" rid="B64">Van Buskirk et al., 2016</xref>; <xref ref-type="bibr" rid="B1">Abanmy, 2017</xref>; <xref ref-type="bibr" rid="B37">Koenraadt and van de Ven, 2018</xref>; <xref ref-type="bibr" rid="B15">Bowman et al., 2020</xref>; <xref ref-type="bibr" rid="B42">Little et al., 2020</xref>; <xref ref-type="bibr" rid="B10">Alwhaibi et al., 2021</xref>; <xref ref-type="bibr" rid="B6">Almohammed et al., 2023</xref>; <xref ref-type="bibr" rid="B7">Almomani et al., 2023</xref>). Similarly, another study found that higher prices were associated with decreased purchase behavior (<xref ref-type="bibr" rid="B7">Almomani et al., 2023</xref>).</p>
<p>In addition, some studies explored the effects of sales promotions, which reduced prices. Sales promotions such as deals, discounts, and special offers were common facilitators of intentions to purchase medicine online (<xref ref-type="bibr" rid="B42">Little et al., 2020</xref>; <xref ref-type="bibr" rid="B47">Moureaud et al., 2021</xref>; <xref ref-type="bibr" rid="B6">Almohammed et al., 2023</xref>).</p>
</sec>
<sec id="s3-3-5">
<title>3.3.5 Evaluations of purchase environment</title>
<p>Several studies examined the effects of consumers&#x2019; evaluations of the online medication purchase environment. Some purchase environment evaluations that enhanced consumers&#x2019; intentions to buy online included attitudes toward online pharmacies (<xref ref-type="bibr" rid="B33">Hu et al., 2021</xref>; <xref ref-type="bibr" rid="B29">Han and Han, 2023</xref>), emotional response to online pharmacies (<xref ref-type="bibr" rid="B33">Hu et al., 2021</xref>), attitude toward online pharmacy logistics and distribution (<xref ref-type="bibr" rid="B33">Hu et al., 2021</xref>), perceived usefulness of online pharmacies (<xref ref-type="bibr" rid="B44">Ma, 2021</xref>), perceived behavioral control (<xref ref-type="bibr" rid="B29">Han and Han, 2023</xref>), trustworthiness of online pharmacies (<xref ref-type="bibr" rid="B44">Ma, 2021</xref>; <xref ref-type="bibr" rid="B54">Sabbir et al., 2021</xref>), trust in the e-marketplace (<xref ref-type="bibr" rid="B2">Adjie et al., 2023</xref>), trust in website technology (<xref ref-type="bibr" rid="B9">Alsadoun et al., 2023</xref>), perceived trust in app-based medicine services (<xref ref-type="bibr" rid="B3">Ahmed et al., 2023</xref>), perception of pharmacy website design (<xref ref-type="bibr" rid="B33">Hu et al., 2021</xref>), perception of website system and service quality (<xref ref-type="bibr" rid="B2">Adjie et al., 2023</xref>), perception of online pharmacies as a reliable source for purchases (<xref ref-type="bibr" rid="B47">Moureaud et al., 2021</xref>), effort expectancy (i.e., online pharmacy is simple, clear and justifiable to use) (<xref ref-type="bibr" rid="B59">Srivastava and Raina, 2020</xref>; <xref ref-type="bibr" rid="B54">Sabbir et al., 2021</xref>), facilitating conditions (i.e., organizational and technical infrastructures assist consumers to use online pharmacy) (<xref ref-type="bibr" rid="B54">Sabbir et al., 2021</xref>), performance expectancy (i.e., usefulness of online pharmacies in achieving desired outcome) (<xref ref-type="bibr" rid="B59">Srivastava and Raina, 2020</xref>; <xref ref-type="bibr" rid="B54">Sabbir et al., 2021</xref>), hedonic motivation (i.e., enjoy using online pharmacies) (<xref ref-type="bibr" rid="B59">Srivastava and Raina, 2020</xref>), and satisfaction with the e-marketplace (<xref ref-type="bibr" rid="B2">Adjie et al., 2023</xref>).</p>
<p>Few studies explored purchase environment evaluations as determinants of purchase behavior. Consumers&#x2019; trust in buying OTC drugs online (<xref ref-type="bibr" rid="B53">Roblek et al., 2018</xref>), trust in purchasing drugs from online resources (<xref ref-type="bibr" rid="B26">Gharaibeh et al., 2023</xref>), trust in online pharmacy websites (<xref ref-type="bibr" rid="B7">Almomani et al., 2023</xref>), and perceived benefits of online drug purchasing (<xref ref-type="bibr" rid="B26">Gharaibeh et al., 2023</xref>) were positively associated with increased medication purchases online.</p>
</sec>
<sec id="s3-3-6">
<title>3.3.6 Internet usage</title>
<p>One study showed that people who spent more time online were more willing to purchase medication online (<xref ref-type="bibr" rid="B25">Fittler et al., 2018</xref>). Purchase behavior was influenced by frequency of internet usage (<xref ref-type="bibr" rid="B53">Roblek et al., 2018</xref>) and information-seeking behavior on the internet (<xref ref-type="bibr" rid="B66">Vera-Mart&#xed;nez, 2023</xref>) as well as frequency of social media usage (<xref ref-type="bibr" rid="B53">Roblek et al., 2018</xref>) and use of the internet as a source of OTC drug information (<xref ref-type="bibr" rid="B32">Holtgrafe and Zentes, 2012</xref>).</p>
</sec>
<sec id="s3-3-7">
<title>3.3.7 Information sources</title>
<p>Consumers&#x2019; intention to purchase medication online was enhanced by several information sources, including online word-of-mouth (<xref ref-type="bibr" rid="B70">Lee et al., 2017</xref>); social media word-of-mouth, such as sharing on Facebook and comments posted on Facebook (<xref ref-type="bibr" rid="B46">Mekawie and Hany, 2019</xref>); drug information provided on the website (<xref ref-type="bibr" rid="B33">Hu et al., 2021</xref>); information quality on e-pharmacy websites (<xref ref-type="bibr" rid="B2">Adjie et al., 2023</xref>); recommendations from family, friends, advertisers, or cultural sources (<xref ref-type="bibr" rid="B33">Hu et al., 2021</xref>); recommendations from others (<xref ref-type="bibr" rid="B47">Moureaud et al., 2021</xref>); social influence, such as interactions with or persuasion by friends and families (<xref ref-type="bibr" rid="B59">Srivastava and Raina, 2020</xref>; <xref ref-type="bibr" rid="B54">Sabbir et al., 2021</xref>); and subjective norms, which is the perceived social pressure or expectations regarding a behavior (<xref ref-type="bibr" rid="B2">Adjie et al., 2023</xref>; <xref ref-type="bibr" rid="B29">Han and Han, 2023</xref>).</p>
<p>Some information source-related factors enhancing purchase behavior included word-of-mouth from friends (<xref ref-type="bibr" rid="B7">Almomani et al., 2023</xref>), social media marketing (<xref ref-type="bibr" rid="B11">Anis and Tan, 2023</xref>), influencers&#x2019; endorsements (<xref ref-type="bibr" rid="B7">Almomani et al., 2023</xref>), information provided by suppliers (<xref ref-type="bibr" rid="B19">Cokro and Arfenda, 2023</xref>), reviews from other consumers (<xref ref-type="bibr" rid="B7">Almomani et al., 2023</xref>; <xref ref-type="bibr" rid="B11">Anis and Tan, 2023</xref>), and interactions with healthcare providers (<xref ref-type="bibr" rid="B21">Desai et al., 2015</xref>; <xref ref-type="bibr" rid="B7">Almomani et al., 2023</xref>).</p>
</sec>
<sec id="s3-3-8">
<title>3.3.8 Perceived risk</title>
<p>Perceived risk associated with the online purchase of drugs, such as privacy concern and uncertainty of drug quality, negatively impacts consumers&#x2019; purchase intentions (<xref ref-type="bibr" rid="B33">Hu et al., 2021</xref>). Three dimensions of perceived risk -- that is financial, physical, and source risks (i.e., concern about the credibility and reliability of online pharmacies) -- adversely affected consumers&#x2019; purchase intentions towards online pharmacies (<xref ref-type="bibr" rid="B65">Varghese Assin et al., 2022</xref>).</p>
<p>Consumers&#x2019; purchase behavior was negatively influenced by medicine safety concerns (<xref ref-type="bibr" rid="B7">Almomani et al., 2023</xref>), medicine quality concerns (<xref ref-type="bibr" rid="B7">Almomani et al., 2023</xref>), web-based payment (<xref ref-type="bibr" rid="B7">Almomani et al., 2023</xref>), lack of accountability (<xref ref-type="bibr" rid="B7">Almomani et al., 2023</xref>), and concerns that online purchases constitute engagement in illegal behavior (<xref ref-type="bibr" rid="B7">Almomani et al., 2023</xref>).</p>
</sec>
<sec id="s3-3-9">
<title>3.3.9 Prior experience</title>
<p>Research shows that prior experience of purchasing goods online (<xref ref-type="bibr" rid="B25">Fittler et al., 2018</xref>; <xref ref-type="bibr" rid="B49">Ndem et al., 2019</xref>); online shopping experience (<xref ref-type="bibr" rid="B33">Hu et al., 2021</xref>); comfort with the network transaction environment (<xref ref-type="bibr" rid="B33">Hu et al., 2021</xref>); greater health literacy, that is ability to find, understand, and use information needed to purchase from online pharmacies (<xref ref-type="bibr" rid="B54">Sabbir et al., 2021</xref>); lower electronic health literacy (<xref ref-type="bibr" rid="B34">Ivanitskaya et al., 2010</xref>); awareness of online pharmacy website technology (<xref ref-type="bibr" rid="B9">Alsadoun et al., 2023</xref>); and consumers&#x2019; expertise regarding online pharmacies (<xref ref-type="bibr" rid="B68">Wiedmann et al., 2010</xref>) were positively associated with purchase intentions. Personal experience also influenced OTC medication purchase behavior (<xref ref-type="bibr" rid="B11">Anis and Tan, 2023</xref>).</p>
</sec>
<sec id="s3-3-10">
<title>3.3.10 Health insurance</title>
<p>Research showed that people without health insurance coverage were more likely to demonstrate purchase intentions toward online pharmacies (<xref ref-type="bibr" rid="B18">Cicero and Ellis, 2012</xref>). Similarly, another study reported an inverse association between Medicaid insurance coverage and purchase behavior (<xref ref-type="bibr" rid="B17">Brown and Li, 2014</xref>). However, two other studies found that health insurance coverage motivated consumers to engage in online medication purchase behavior (<xref ref-type="bibr" rid="B17">Brown and Li, 2014</xref>; <xref ref-type="bibr" rid="B21">Desai et al., 2015</xref>).</p>
</sec>
<sec id="s3-3-11">
<title>3.3.11 Privacy</title>
<p>
<xref ref-type="bibr" rid="B18">Cicero and Ellis (2012)</xref> showed that perceived anonymity could be a primary reason that consumers intended to purchase from online pharmacies that dispensed Tramadol, a prescription medication, without a prescription. In terms of behavior, <xref ref-type="bibr" rid="B10">Alwhaibi et al. (2021)</xref> indicated that consumers are motivated to purchase online as it provides greater assurance of confidentiality and access to medicine. Similarly, consumers&#x2019; perceptions of privacy can influence their decision to buy some prescription medicines online (<xref ref-type="bibr" rid="B7">Almomani et al., 2023</xref>) as they may avoid embarrassment by obtaining their medicines without the need for face-to-face interactions or to state their illness when the shame of admitting a condition acts as a barrier to seeking care (e.g., disclosing sexual dysfunction or seeking slimming pills for weight loss). For example, many consumers bought sexual enhancers online because they did not want to discuss their condition with their physician (<xref ref-type="bibr" rid="B37">Koenraadt and van de Ven, 2018</xref>).</p>
</sec>
<sec id="s3-3-12">
<title>3.3.12 Product</title>
<p>As shown in <xref ref-type="table" rid="T3">Table 3</xref>, two studies reported a positive association between product quality and behavioral intentions (<xref ref-type="bibr" rid="B31">Holiday-Goodman et al., 2007</xref>; <xref ref-type="bibr" rid="B64">Van Buskirk et al., 2016</xref>). In two other studies, product variety motivated purchase behavior from online pharmacies (<xref ref-type="bibr" rid="B10">Alwhaibi et al., 2021</xref>; <xref ref-type="bibr" rid="B6">Almohammed et al., 2023</xref>).</p>
</sec>
</sec>
</sec>
<sec id="s4">
<title>4 Discussion and implications</title>
<p>This scoping review sought to understand the current landscape of empirical research on the drivers of consumer purchase intentions and usage behavior of online pharmacies. Scholarly interest in this topic has been growing exponentially over the last few years. Using rigorous scoping review methods, forty-eight articles published to date met the inclusion criteria, including 12 published in 2023.</p>
<p>Although we sought qualitative and quantitative studies that applied various methodological approaches, the existing literature was mostly limited to surveys. In terms of sample populations, however, the existing literature exhibits greater diversity in both population types (e.g., adults, patients, pregnant women) and geographic areas, such as Europe (e.g., Germany, Hungary, Ireland, Malta, Netherlands, Portugal, Romania, Russia, Slovenia, Sweden, and the UK), Asia (e.g., Bangladesh, India, China, and Taiwan), North America (Canada and the United States), the Arabian Peninsula (e.g., Saudi Arabia and the United Arab Emirates), Africa (e.g., Egypt and Nigeria), and Australia. However, Latin America has been ignored in the existing literature, including the major markets of Mexico, Brazil, Chile, Colombia, and Argentina.</p>
<p>This scoping review identified twelve general factors, which include many individual facilitators and inhibitors of consumer purchase intentions and behavior that have been studied so far (<xref ref-type="table" rid="T3">Table 3</xref>). Of these, the greatest amount of research has investigated the demographics of consumers who purchase or intend to purchase from online pharmacies. Due to the conflicting results, few implications can be gleaned from the prior research related to demographics or the role of health insurance coverage. However, higher-income consumers, White American consumers, and more educated consumers (in nine of ten studies) had higher online medication purchase intentions and behavior. The implication for researchers and practitioners from the income and education findings seems to be that greater financial and cognitive resources help consumers navigate the online environment to find medications for purchase. Policymakers seeking to dissuade purchases from rogue or illegitimate online pharmacies should target messages and campaigns to these demographic groups.</p>
<p>Convenience and availability factors more consistently influenced online medication purchase intentions and behavior. Consumers intended or chose to purchase from online pharmacies due to faster and more convenient delivery, ease of use and gathering information, accessibility, the ability to bypass healthcare providers or regulatory gatekeepers, availability outside of store hours, and access to medications unavailable locally. A practical implication for brick-and-mortar pharmacies is that enhancing their convenience (e.g., same day delivery, faster service at the pharmacy counter, or longer hours of operation) should help them better compete with online pharmacies.</p>
<p>Price was also a consistent influence on online medication purchase intentions and behavior. Factors that lowered prices or increased price savings and value received from online medicine purchases tended to attract consumers. Thus, a practical implication is that online pharmacies should emphasize price savings to continue to grow their share of consumers&#x2019; drug purchases. To better challenge online pharmacies, brick-and-mortar pharmacies should become more price competitive. A policy implication is that public policymakers and regulators attempting to control the illicit dispensing of medicine online should consider regulation reductions, subsidies, or other ways to lower prices through legitimate pharmacies.</p>
<p>Favorable evaluations of the purchase environment also consistently benefitted purchase intentions and behavior across many types of evaluations, such as attitudes, trust, emotional response, aesthetically pleasing and functional design evaluations, enjoyment, and satisfaction. Thus, it appears that many consumers who purchase from or intend to purchase from online pharmacies do so because they hold positive evaluations of those pharmacies. An important implication of this finding is that policymakers, regulators, and brick-and-mortar pharmacies interested in discouraging online medication purchases must engage in attitude change campaigns before expecting consumers who purchase online to alter their intentions or behavior. Attitude change can take time as it requires learning new information and responses through repeated exposure to counterinformation or social influence from family, friends, or trusted others, such as experts or celebrities.</p>
<p>This scoping review summarized prior research findings in which social influence and other information sources motivate online medication purchase intentions and behavior. Intentions and behavior were influenced by information and recommendations from expert sources, such as healthcare providers and websites with drug information; personal sources, such as friends and family; independent sources, such as social media influencers and reviews by other consumers; and non-personal sources, such as social media marketing. One implication is that pharmacists, healthcare providers, policymakers, and regulators should be able to indirectly influence consumer behavior toward online medicine purchases if they tap into the social and normative influence of one or more of these information sources.</p>
<p>Perceived financial, physical, or source risks inhibit online medicine purchase intentions and behavior, whereas greater health literacy and experience with online pharmacies, online shopping in general, and the internet or social media encourage online medicine purchasing. The benefits of online pharmacies (e.g., greater perceptions of anonymity or privacy, better perceived product quality, and more product variety) also encourage online medicine purchase intentions and behavior. An implication is that brick-and-mortar competitors or public policymakers should heighten consumer awareness of these risks if they wish to discourage consumer online medicine purchases. Further, legitimate online sellers can highlight risks to differentiate their verified online pharmacies from illicit or rogue online pharmacies.</p>
<p>Finally, this scoping review documented other factors that had been investigated sparingly (see <xref ref-type="app" rid="app1">Appendix A</xref>). For example, some studies have begun to investigate how consumer personality predisposes some consumers toward (e.g., greater purchase involvement, variety seeking, and openness) or against (e.g., objectivism) online medicine purchasing. Other studies have begun to investigate situational influences on consumer online medication purchase intentions and behavior (e.g., the COVID-19 pandemic). Individually, these other factors have been studied so rarely that it is difficult to confidently predict the general effect on purchase intentions and behavior without future research. These other influences are listed in the <xref ref-type="app" rid="app1">Appendix A</xref>.</p>
</sec>
<sec id="s5">
<title>5 Directions for future research</title>
<p>The analyzed literature indicates several gaps in the literature and future research directions that could be addressed. First, although this scoping review covers the vast majority of the literature published in English to date on consumers&#x2019; online medication purchase intentions and behavior, research interest in this topic is growing exponentially, with several new studies published each year. Thus, a systematic review or meta-analysis that incorporates the post-2023 studies will likely be able to be conducted within the next decade once sufficient research has been published. This should further our understanding of the factors that facilitate and inhibit online medication purchasing as well as help determine the relative strength of different influences.</p>
<p>Second, this scoping review found that the current state of research into the drivers of consumers&#x2019; online medication purchase intentions and behavior is methodologically limited. Most studies (87.5%) use a survey design. The remainder includes a handful of qualitative studies and a single experiment. Future research employing methods other than surveys (e.g., experiments, observational methods, and data analytics) can investigate research topics that are difficult to study via self-report methods. Similarly, future research should advance the understanding of online purchase drivers by using more generalizable and diverse samples, patient rather than general adult samples, and samples that permit cross-cultural comparisons. Future research could also investigate more complex models of potential drivers&#x2019; relationships with purchase intentions and/or behavior, such as mediation or moderation models that could resolve the conflicting evidence in prior research that this scoping review has uncovered and identify important boundary conditions on these effects.</p>
<p>Third, this scoping review finds that a vast majority of the prior research did not specify whether online purchases of OTC or prescription medication or both were being studied. Future research should specify this because the current review shows differences in the drivers of online OTC and prescription drug purchase intentions and behavior. In fact, due to the paucity of literature on this issue, future research is needed to more confidently delineate the drivers of consumers&#x2019; online purchase intentions and behavior for OTC <italic>versus</italic> prescription drugs.</p>
<p>Fourth, demographics (e.g., consumers&#x2019; age, gender, or educational attainment) are easy to measure but appear to be poor predictors of purchase intentions or behavior, given the large number of conflicting results related to demographic variables in the studies reviewed. As noted in previous reviews (<xref ref-type="bibr" rid="B63">Tugwell et al., 2008</xref>; <xref ref-type="bibr" rid="B55">Schmid et al., 2017</xref>; <xref ref-type="bibr" rid="B41">Limbu and Huhmann, 2023c</xref>), demographic variables are carrier variables that are not mechanisms causing changes in intentions or behavior but are instead associated to some degree with the prior experiences, predispositions, beliefs, attitudes, or characteristics that affect consumer response. Thus, rather than relying on demographics, future research should attempt to identify the underlying explanatory determinants to better predict purchase intentions and behavior from online pharmacies. Studies, including moderation or mediation tests, could also help better understand the mechanisms at work. Once the underlying explanatory determinants associated with a demographic variable such as age or gender have been identified, the indirectly related demographic variables can serve to identify likely target audiences for public health campaigns and patient education materials regarding online pharmacies.</p>
<p>Fifth, although this scoping review documents many influences that increase or decrease consumers&#x2019; purchase intentions and/or behavior, it also underscores the need for future research into uninvestigated and understudied influences. For example, psychographic variables, such as personality, perceptions, attitudes, beliefs, lifestyle, interests, and values, can offer the potential to identify deeper motivations and could better identify why some consumers buy medications online whereas others do not. To direct future research into other uninvestigated or underinvestigated areas, <xref ref-type="table" rid="T4">Table 4</xref> lists some research questions that warrant exploration to better understand the driving influences on consumer purchase intentions and behavior.</p>
<table-wrap id="T4" position="float">
<label>TABLE 4</label>
<caption>
<p>Future research agenda and research questions.</p>
</caption>
<table>
<thead valign="top">
<tr>
<th align="left">Drivers</th>
<th align="left">Concepts/theories</th>
<th align="left">Potential research questions</th>
</tr>
</thead>
<tbody valign="top">
<tr>
<td rowspan="8" align="left">Risk</td>
<td rowspan="3" align="left">Perceived risk</td>
<td align="left">How do differences in the degree of risk across specific medications, dosages, and efficacies impact consumers&#x2019; intentions to purchase online or their actual purchase behavior?</td>
</tr>
<tr>
<td align="left">To what degree do consumers perceive online purchases of medicine to involve different types of risk (e.g., financial or physical)? How much financial risk do they perceive and why (e.g., fraudulent charges after online medicine purchases or waste of money on ineffectual/fake drugs)? How much physical risk do they perceive and why (e.g., fake medicine purchased online harms health or is adulterated with opioids leading to addiction)? How much source risk do consumers perceive and why (e.g., personal information for online medication purchase used in spam emails/calls, invasion of privacy, or identity theft)?</td>
</tr>
<tr>
<td align="left">What is the nature and prevalence of adverse effects suffered by consumers who purchase medicine online? Does it differ across types of online pharmacies (e.g., chain, independent, and cost-plus legitimate pharmacies <italic>versus</italic> rogue/illicit pharmacies)?</td>
</tr>
<tr>
<td rowspan="2" align="left">Uncertainty avoidance</td>
<td align="left">How do consumers attempt to manage the risk of online medical purchases?</td>
</tr>
<tr>
<td align="left">How can public policymakers highlight the risks of illicit or rogue pharmacies in educational campaigns to decrease consumer purchases?</td>
</tr>
<tr>
<td align="left">Decision-making heuristics</td>
<td align="left">What heuristics and cues do consumers use to identify &#x201c;safe&#x201d; online medicine sources for purchase? Are these heuristics and cues accurate?</td>
</tr>
<tr>
<td rowspan="2" align="left">Regulatory focus theory</td>
<td align="left">What risks do medicine purchases online pose to healthcare providers? How prepared are they to address these risks, and how can educators better prepare medical and pharmaceutical students to better address the risks as future healthcare practitioners who are involved in monitoring and discussing online sources of medicine with patients?</td>
</tr>
<tr>
<td align="left">How do consumers&#x2019; online medication purchase intentions and behavior differ if they are primarily prevention-focused (focused on avoiding losses) or promotion-focused (focused on seeking gains)?</td>
</tr>
<tr>
<td rowspan="4" align="left">Benefits</td>
<td align="left">Manifest and latent motives</td>
<td align="left">How do the manifest motives (benefits that consumers freely admit seeking) differ from the latent motives (those that consumers do not want to admit or reveal to others) for online medication purchases?</td>
</tr>
<tr>
<td align="left">Benefits segmentation</td>
<td align="left">How are consumers&#x2019; online medicine purchase intentions and behavior impacted by the specific benefit sought (e.g., perceived anonymity, avoidance of embarrassment, cost savings, improved availability, greater autonomy, ability to self-diagnose/self-medicate, greater access, delivery to remote areas, or off-label usage)? How can traditional brick-and-mortar or legitimate online pharmacies better incorporate these benefits, and would doing so reduce consumer purchases from illicit online pharmacies? To what extent do consumers intend to purchase or purchase medicine specifically from illicit online pharmacies to seek these perceived benefits?</td>
</tr>
<tr>
<td rowspan="2" align="left">Product features, attributes, and benefits</td>
<td align="left">What benefits do consumers believe online medical purchases offer based on online pharmacies&#x2019; features and tangible attributes?</td>
</tr>
<tr>
<td align="left">How have closures of locations of large chain pharmacies (e.g., Rite-Aid and Walgreens) impacted consumers&#x2019; perceptions of online pharmacies offering benefits related to availability and convenience? Have such closures increased purchases from legitimate and illicit online pharmacies?</td>
</tr>
<tr>
<td rowspan="9" align="left">Learning</td>
<td rowspan="4" align="left">Information processing</td>
<td align="left">How is the proportion of consumers who intend to or have purchased medicine online affected by the degree of awareness of online sources of medicine or by information about them stored in memory?</td>
</tr>
<tr>
<td align="left">What types of information increase <italic>versus</italic> overcome consumer resistance to purchasing medications online?</td>
</tr>
<tr>
<td align="left">How can education campaigns best model the dangers of illicit online pharmacies to discourage consumer purchases from them?</td>
</tr>
<tr>
<td align="left">How does providing information about online pharmacies, their risks, or benefits by public health officials in public service advertising campaigns impact consumer purchase intentions and behavior?</td>
</tr>
<tr>
<td align="left">Vicarious learning/modelling</td>
<td align="left">How and to what extent does exposure to other consumers&#x2019; ratings and reviews available on online pharmacies impact consumer purchase intentions and behavior? How do these consumer ratings and reviews compare to healthcare providers&#x2019; professional opinions regarding outcomes, such as efficacy or side effects?</td>
</tr>
<tr>
<td rowspan="2" align="left">Cognitive learning</td>
<td align="left">What beliefs do consumers form based on exposure to other consumers&#x2019; ratings and reviews <italic>versus</italic> FDA-approved patient labeling?</td>
</tr>
<tr>
<td align="left">What types of information do healthcare providers communicate about purchasing medications online? How does this impact consumer beliefs, attitudes, and purchase intentions? What information would consumers find most useful to optimize purchase decisions?</td>
</tr>
<tr>
<td align="left">Cognitive capacity</td>
<td align="left">Consumers&#x2019; cognitive resources are limited; how does this impact their acquisition and retention of information from various sources (e.g., healthcare providers, FDA-approved patient labeling, or online ratings and reviews) and subsequent purchase intentions and behavior?</td>
</tr>
<tr>
<td align="left">Perceptual fluency</td>
<td align="left">Does making information presented by an online pharmacy easier to process and comprehend (e.g., bullet points <italic>versus</italic> paragraphs) increase purchase intentions and behavior toward that online pharmacy&#x2019;s medications?</td>
</tr>
<tr>
<td rowspan="7" align="left">Search</td>
<td rowspan="3" align="left">External information search</td>
<td align="left">Is there an inverse relationship between the amount of physician-provided information and online information search? What is the effect of each on online purchase intentions and behavior?</td>
</tr>
<tr>
<td align="left">Does the information provided in direct-to-consumer advertising encourage more extensive information searches and greater online purchase intentions and behavior? How does the effect differ between targeted consumers <italic>versus</italic> the unintended audience also exposed to the message, but with less medical need for the advertised drug?</td>
</tr>
<tr>
<td align="left">To what degree are expatriates likely to seek information about and purchase medicines from their home country versus their country of settlement? How does this impact online medical sales? What methods do expatriates use to locate and purchase medicines online from their home country?</td>
</tr>
<tr>
<td align="left">Involvement/personal relevance</td>
<td align="left">Greater involvement should increase information search as consumers attempt to improve purchase decision quality for more personally relevant decisions. Do the greater health consequences and costs of prescription than OTC medications increase involvement and, hence, information search? How does that affect the amount and type of information that consumers seek when making purchase decisions for a prescription <italic>versus</italic> an OTC medication?</td>
</tr>
<tr>
<td rowspan="2" align="left">Intrinsic <italic>versus</italic> extrinsic motivation</td>
<td align="left">Do chronic conditions, due to their ongoing nature, increase enduring involvement and, hence, search for information regarding online medicine purchases compared to acute conditions?</td>
</tr>
<tr>
<td align="left">To what degree do those with chronic diseases prefer to purchase medication online compared to healthy consumers or those with acute conditions? Does the greater frequency of purchasing, the cumulative cost, the difficulty traveling to or navigating a brick-and-mortar pharmacy, or some other factor mediate the relationship between chronic conditions and the greater likelihood of purchasing medications from online sources?</td>
</tr>
<tr>
<td align="left">Search engine optimization Search engine marketing</td>
<td align="left">How can legitimate online pharmacies and brick-and-mortar pharmacies better use search engine optimization and search engine marketing to encourage consumers to switch medication purchases from rogue sites to these legal sellers?</td>
</tr>
<tr>
<td rowspan="6" align="left">Situational influences</td>
<td align="left">Communication situation</td>
<td align="left">To what degree do consumers intend to or purchase medications via illicit online pharmacies following exposure to direct-to-consumer advertising? Do they first ask their physician for the advertised medication? If so, does a physician&#x2019;s refusal to prescribe increase or decrease consumers&#x2019; likelihood of purchasing the advertised medication online?</td>
</tr>
<tr>
<td rowspan="2" align="left">Purchase situation</td>
<td align="left">Does direct-to-consumer advertising of prescription medication impact online purchase intentions or behavior? Is the effect greater among consumer groups with fewer resources (e.g., financial resources or cognitive resources) or among vulnerable populations?</td>
</tr>
<tr>
<td align="left">What is the relationship between online medicine purchases and cross-border sales of medicine? To what degree do consumers travel to purchase medicine or receive medical care <italic>versus</italic> purchase medications online? What accounts for this behavior (e.g., immigration status, living in a borderland region, or medication availability or cost in the country of residence)? What leads consumers to choose online over cross-border medication purchases?</td>
</tr>
<tr>
<td align="left">Usage situation</td>
<td align="left">Are consumers without health insurance more likely to purchase from online pharmacies? If so, how can healthcare providers and public policymakers encourage purchases from legitimate rather than illicit online sources? Comparatively, how effective are different types of interventions (e.g., educational materials, lists of legitimate sources, healthcare provider recommendations)?</td>
</tr>
<tr>
<td align="left">Temporal perspective</td>
<td align="left">How does perceived time pressure impact consumers&#x2019; purchase intentions and behavior toward online <italic>versus</italic> brick-and-mortar pharmacies?</td>
</tr>
<tr>
<td align="left">Cognitive tax</td>
<td align="left">How do situations that introduce cognitive taxes, which reduce a consumer&#x2019;s cognitive capacity remaining for decision-making (e.g., poverty or illness), impact intentions and behavior toward online pharmacies, especially illicit ones that do not require prescriptions?</td>
</tr>
<tr>
<td rowspan="5" align="left">Familiarity</td>
<td align="left">Prior experience</td>
<td align="left">How does familiarity with purchasing other products online affect online medication purchase intentions and behavior? Do online medication purchase intentions and behavior differ depending on the types of products frequently purchased online?</td>
</tr>
<tr>
<td align="left">Consumer expertise</td>
<td align="left">How does familiarity with a brick-and-mortar chain or independent pharmacy affect consumer purchase intentions and behavior toward an affiliated online pharmacy?</td>
</tr>
<tr>
<td align="left">Objective and subjective knowledge</td>
<td align="left">Does trust, satisfaction with prior purchases, or liking mediate the relationship between online pharmacy familiarity and purchase intentions or behavior?</td>
</tr>
<tr>
<td align="left">Mere exposure</td>
<td rowspan="2" align="left">The Enrichment Hypothesis holds that increasing product experience develops consumers&#x2019; ability to attend to and retain relevant information about that product. How does familiarity-enhanced attention to and memory for relevant product information affect online medication purchase intentions and behavior? Does greater prior experience alter the distribution of consumers purchasing from legitimate <italic>versus</italic> illicit online pharmacies?</td>
</tr>
<tr>
<td align="left">Enrichment Hypothesis</td>
</tr>
<tr>
<td rowspan="2" align="left">Trust</td>
<td rowspan="2" align="left">Skepticism</td>
<td align="left">How do consultations with physicians and pharmacists associated with online pharmacies impact consumer trust and skepticism toward online pharmacies or purchase intentions and behavior? Does the modality of the consultation (e.g., email exchange, chat, or video conference) affect these relationships?</td>
</tr>
<tr>
<td align="left">How do shortages and supply chain disruptions affect online purchase intentions and behavior? Do consumers view online access to be sufficiently beneficial to overcome skepticism toward and build trust in online pharmacies, even illicit online sources?</td>
</tr>
<tr>
<td rowspan="5" align="left">Post-purchase evaluations</td>
<td rowspan="3" align="left">Customer satisfaction <italic>versus</italic> dissatisfaction</td>
<td align="left">Are consumers satisfied or dissatisfied with their online pharmacy purchases?</td>
</tr>
<tr>
<td align="left">How satisfied are consumers with the purchase process and the medications received following an online medication purchase?</td>
</tr>
<tr>
<td align="left">Does the degree of satisfaction differ across types of sources for online medication purchases (e.g., legitimate vs. illicit online pharmacy, cost-plus or traditional online pharmacy, chain or independent online pharmacy)?</td>
</tr>
<tr>
<td rowspan="2" align="left">Postpurchase dissonance</td>
<td align="left">What impact does post-purchase evaluation have on future purchase intentions and subsequent purchase behavior?</td>
</tr>
<tr>
<td align="left">How common is postpurchase dissonance following an online medication purchase? How does it affect future purchase intentions and behavior toward online pharmacies?</td>
</tr>
</tbody>
</table>
</table-wrap>
<p>Finally, the prior literature uncovered by this scoping review tends to be atheoretical and exhibits a general lack of definitions for key constructs posited as factors influencing consumer purchase intentions or behavior. To aid pharmacology researchers and investigators from other fields, the research questions in <xref ref-type="table" rid="T4">Table 4</xref> are linked to theories and well-defined constructs in the literature from psychology, consumer research, advertising, health communication, and marketing. For example, <xref ref-type="bibr" rid="B24">Fittler et al. (2022b)</xref> showed that unlicensed drug distributors use search engine results to redirect site visitors to illegal online pharmacies. Using the constructs from the marketing literature of search engine optimization and search engine marketing, how can legal sellers take action against these rogue sites and use search engine results to promote medication purchases from legitimate online and brick-and-mortar pharmacies? Future research should define the constructs studied and use these theories to establish consistent terminology that will ease comparison across studies to advance understanding of the underlying drivers of consumers&#x2019; online medication purchase intentions and behavior.</p>
</sec>
<sec sec-type="conclusion" id="s6">
<title>6 Conclusion</title>
<p>This scoping review examined studies of consumers&#x2019; online pharmacy purchase intentions and behavior. While demographic factors tended to be the most often measured influences on intentions and behavior, their role was generally inconsistent, with many contradictory results. However, other factors (e.g., convenience, availability, lower prices, favorable evaluations of the purchase environment, and supportive recommendations from others) more consistently enhanced online medication purchase intentions and behavior. These findings of our scoping review should aid verified online pharmacies and brick-and-mortar stores in understanding ways to encourage consumer medication purchases.</p>
<p>Further, our scoping review revealed a general lack of definitions for constructs studied and a paucity of theoretical justification as to why certain factors or individual influences should affect purchase intentions or behavior. This, combined with gaps in the existing literature, led us to develop an extensive agenda for future research to advance our understanding of the drivers of consumers&#x2019; intentions and behavior toward online pharmacy purchases. This research agenda should help future studies in this area move beyond descriptive analysis to theory-testing and discovering the underlying explanations of how specific influences affect online medication purchase intentions and behaviors. To accomplish this, these future research directions are based on theories and concepts developed in other areas focused on stimulating intentions or prompting behaviors (e.g., psychology, consumer research, advertising, health communication, and marketing). Investigating research questions based on this agenda should help healthcare providers, public policymakers, and regulators design more effective interventions to promote more positive individual patient and public health outcomes as well as benefit researchers interested in this topic of increasing interest and economic importance.</p>
</sec>
</body>
<back>
<sec id="s7">
<title>Author contributions</title>
<p>YL: Conceptualization, Data curation, Formal Analysis, Investigation, Methodology, Visualization, Writing&#x2013;original draft, Writing&#x2013;review and editing. BH: Conceptualization, Data curation, Investigation, Methodology, Validation, Writing&#x2013;original draft, Writing&#x2013;review and editing.</p>
</sec>
<sec sec-type="funding-information" id="s8">
<title>Funding</title>
<p>The author(s) declare that no financial support was received for the research, authorship, and/or publication of this article.</p>
</sec>
<sec sec-type="COI-statement" id="s9">
<title>Conflict of interest</title>
<p>The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.</p>
</sec>
<sec sec-type="disclaimer" id="s10">
<title>Publisher&#x2019;s note</title>
<p>All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.</p>
</sec>
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<app-group>
<app id="app1">
<title>Appendix A</title>
<p>Other influences on purchase intentions and behavior identified in prior research.</p>
<p>
<bold>Influences on purchase intentions.</bold>
</p>
<p>Openness to online medical purchase options (<xref ref-type="bibr" rid="B33">Hu et al., 2021</xref>)</p>
<p>Switching costs (<xref ref-type="bibr" rid="B2">Adjie et al., 2023</xref>)</p>
<p>Variety-seeking behavior (<xref ref-type="bibr" rid="B2">Adjie et al., 2023</xref>)</p>
<p>Fear appeal (<xref ref-type="bibr" rid="B5">Alhabash et al., 2022</xref>)</p>
<p>Involvement with online medical products (<xref ref-type="bibr" rid="B70">Lee et al., 2017</xref>)</p>
<p>
<bold>Influences on purchase behavior.</bold>
</p>
<p>
<italic>Objectivism</italic> (<xref ref-type="bibr" rid="B52">Rajamma and Pelton, 2009</xref>)</p>
<p>Variety seekers (<xref ref-type="bibr" rid="B66">Vera-Mart&#xed;nez, 2023</xref>)</p>
<p>
<italic>General barriers and website-specific barriers</italic> (<xref ref-type="bibr" rid="B7">Almomani et al., 2023</xref>)</p>
<p>Higher number of prescriptions (<xref ref-type="bibr" rid="B17">Brown and Li, 2014</xref>)</p>
<p>Have higher Charlson comorbidity index scores (<xref ref-type="bibr" rid="B17">Brown and Li, 2014</xref>)</p>
<p>Use of erectile dysfunction drugs (<xref ref-type="bibr" rid="B17">Brown and Li, 2014</xref>)</p>
<p>
<italic>Use of narcotic medications</italic> (<xref ref-type="bibr" rid="B17">Brown and Li, 2014</xref>)</p>
<p>
<italic>Satisfaction with pharmacists and physician</italic> (<xref ref-type="bibr" rid="B53">Roblek et al., 2018</xref>)</p>
<p>COVID-19 pandemic (<xref ref-type="bibr" rid="B22">Fittler et al., 2022a</xref>; <xref ref-type="bibr" rid="B30">Hawdon et al., 2022</xref>; <xref ref-type="bibr" rid="B11">Anis and Tan, 2023</xref>; <xref ref-type="bibr" rid="B28">Hamdan, 2023</xref>)</p>
<p>Pandemic-induced strain (<xref ref-type="bibr" rid="B30">Hawdon et al., 2022</xref>)</p>
<p>Note: Italicized text indicates reported findings that are negatively related to purchase intentions or behavior.</p>
</app>
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