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4 May 2026

18 Pages

Reassessing the Role of Google Scholar in PRISMA-Informed Systematic Reviews Through a Critical Analysis of Influential Research Identifying Its Limitations and Empirical Evidence

History of Medicine Program, Department of Psychiatry, Temerty Faculty of Medicine, University of Toronto, Toronto, ON M5S 1A1, Canada
Publications2026, 14(2), 29;https://doi.org/10.3390/publications14020029
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Abstract

There is contested use of Google Scholar as a primary database for PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-analyses) reviews. However, well-cited articles identify Google Scholar as insufficiently reliable and evaluate its use as supplementary. Subsequent systematic review searches have accepted this relegation of Google Scholar to supplementary status, citing these articles as the reason. This study questions this acceptance by (1) revealing the type of difficulties with Google Scholar identified in these well-cited publications compared with PRISMA guidelines, and (2) examining several PRISMA scoping review primary database searches performed by this author since 2023 for the adequacy of Google Scholar results compared with them. The results reveal that the reasons for considering Google Scholar a supplementary database regarding PRISMA status are not convincing, as they are unrelated to PRISMA guidelines for systematic reviews. Google Scholar returned the greatest number of included studies for the majority of post-2023 scoping reviews conducted by this author. These results demonstrate that the accepted advice to authors that Google Scholar should be a supplementary database is unsupported. Based on the results of this research, the suggestion is to accept Google Scholar as a primary database, comparable in all relevant ways to other primary databases for a PRISMA-style review.

1. Introduction

The status of Google Scholar following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines is unclear. The initial problem of clarity concerns defining Google Scholar. In 2022, two publications presented diametrically opposite viewpoints. The first defines Google Scholar as a specialized search engine (Aman et al., 2023). In contrast, the other states, “Google Scholar is both a database and a citation index, and systematic review teams often use Google Scholar for both reasons. For subject-based searching, Google Scholar is considered a database” (Rethlefsen & Page, 2022). Both accepted that Google Scholar crawls the vast database of scholarly literature, including academic publishers, repositories, and universities, to index journals, theses, books, pre-prints, technical reports, and court opinions (Singh et al., 2022). The question is, as a broad, interdisciplinary discovery means, rather than a curated bibliographic database (Shamsi et al., 2020), what is the proper relationship of Google Scholar to systematic reviews following PRISMA guidelines?
The PRISMA Statement, including its extensions, is a minimum set of evidence-based recommendations for systematic reviews encouraging comprehensive transparency in reporting (Sarkis-Onofre et al., 2021). Initially published in 2009, following a three-day meeting of 29 stakeholders in 2005 (Moher et al., 2009), the guidelines now also include scoping reviews and review protocols aiming to ensure accuracy and unambiguous reporting for all aspects of systematic reviews. The PRISMA guidelines help authors describe the exclusion criteria, the search process, and the outcomes (i.e., what researchers plan to do) in a review protocol (Page et al., 2021b). They represent the most-cited reporting guidelines in the biomedical literature (Schniedermann, 2022). An updated version, PRISMA2020, was published in 2021 (Page et al., 2021a). The number of systematic reviews following the PRISMA guidelines has increased substantially over the years (Hoffmann et al., 2021; Sarkis-Onofre et al., 2021).
The PRISMA guidelines for database suitability include the following. Of the well-cited publications directly associated with the PRISMA 2020 guidelines (Page et al., 2021a, 2021b), there are analyses, outcomes, sources, data, and studies that are primary; however, there is no description of the primary databases. According to these publications, the PRISMA guideline requirements are as follows: the description of the search strategy for each database is sufficient to allow another researcher to reproduce the results. This sufficiency requires identifying the database used, the search date, and the inclusion and exclusion criteria. Similarly to “primary”, “supplementary” is not a term used in relation to databases in (Page et al., 2021a, 2021b). What relegates a source to supplementary status is that it is a study not found in any database. These sources include hand searches, trial registries, or websites.
Because the PRISMA guidelines have become integral to the systematic review process, it is significant if Google Scholar—considered the most comprehensive (Martín-Martín et al., 2021)—is judged inadequate as a primary database. Yet, scholars’ assessments throughout most of its history have left no clear answer regarding its suitability as a database for systematic reviews. As noted in a Google Scholar search on 17 April 2026, the differing viewpoints throughout much of that time have received a comparable number of citations.
Google Scholar was released as a database in November 2004 (Kesselman & Barbara Watstein, 2005; Walters, 2007). One of the first articles about it was by librarians. It opened with these comments. “Handwringers worry that Google Scholar will drive our users away from libraries. They worry that students will gravitate to Google Scholar due to its name recognition and ease of use. They worry that Google Scholar will become their sole source of research information and that students will bypass libraries and librarians altogether” (Kesselman & Barbara Watstein, 2005). This 2005 article, cited by 46, concludes with the question, “Many individuals have raised the question, ‘what’s in it for Google?’” An additional 2005 article by two other librarians (cited by 32) is objective regarding the limitations of Google Scholar. “We are in agreement with those who have critiqued GS’s lack of authority control, lack of choices for sorting results, lack of controlled vocabulary, and lack of version control; Google’s unwillingness to specify what exactly GS indexes; the currency and completeness of its contents; and the uncertainty regarding the frequency with which it is updated. On the other hand, we were impressed by the degree to which GS manages to weed out non-scholarly materials, by its potential for resource discovery, by the quality and number of relevant results generated by GS in comparison with results generated in some research databases (for certain topics), and by its usability” (Adlington & Benda, 2005).
A 2008 publication, cited 239 times, highlights librarians’ immediate recognition of Google Scholar’s creation (Walters, 2007). By then, three years later, the view was that “citation counts reported by Google Scholar are not entirely reliable”. This 2008 publication notes that “Google staff have been unwilling to provide much information about Google Scholar’s selection algorithms, sorting (relevance) algorithms, content sources, or organizational partnerships.” Nevertheless, with these cautions, the 2008 author concluded objectively that “Google Scholar provides excellent coverage of at least one social science field, in both absolute and comparative terms. The results presented here suggest that the unconventional methods used to build the GS database have not adversely affected its coverage of the scholarly literature.”
Walters (2007) recognized the limitations of Google Scholar in a balanced manner. Yet by the next decade, several studies on Google Scholar focused on its limitations rather than its positive features. Although not the first of his works on Google Scholar (Jacsó, 2005, 2008a, 2008b, 2008c, 2009b, 2009a), by the 2010s Jacsó produced a series of publications whose titles focused on what he considered the irrationality of academic use of Google Scholar: “Metadata mega mess in Google Scholar” (Jacsó, 2010) with 214 citations, “Google Scholar duped and deduped–the aura of “robometrics”” (Jacsó, 2011) (57 citations), “Google Scholar Author Citation Tracker: is it too little, too late?” (Jacsó, 2012a) (59 citations), “Grim tales about the impact factor and the h-index in the Web of Science and the Journal Citation Reports databases” (Jacso, 2012) (35 citations), and “Using Google Scholar for journal impact factors and the h-index in nationwide publishing assessments in academia—siren songs and air-raid sirens” (Jacsó, 2012b) (56 citations). Jascó, as a library scientist, is clear on his distrust of Google Scholar. One quotation from a 2012 article provides an example. “Standardization of metadata has been one of the highlights in the field of library and information technology. Unfortunately, one of the basic principles in the development of Google Scholar was to create metadata elements from the data collected by its crawlers and processed by its parsers instead of using existing metadata that are provided by practically every publisher of scholarly journals. Their accuracy and consistency are incomparably better than the metadata crafted by Google Scholar” (Jacsó, 2012b). Another publication from this period goes even further than Jascó in his criticism of the database, stating that, “Regrettably, Jacsó’s work does not reveal all the errors in Google Scholar, although it does expose the most notorious and flagrant, a fact that has led to an improved service” (Orduna-Malea et al., 2017) (83 citations).
In contrast, other scholars during the 2010s were more positive in their assessment of Google Scholar. Gehanno et al. titled their research article on Google Scholar, “Is the coverage of google scholar enough to be used alone for systematic reviews” (Gehanno et al., 2013). They conclude the following. “The coverage of GS for the studies included in the systematic reviews is 100%. If the authors of the 29 systematic reviews had used only GS, no reference would have been missed. With some improvement in the research options, to increase its precision, GS could become the leading bibliographic database in medicine and could be used alone for systematic reviews.” In relative importance, this study supersedes the more negative assessment, with 470 citations. Yet, in a 2013 response to this publication, the reply was “No. Contrary to Gehanno et al.’s conclusions that GS ‘could even be used alone’, we found that GS was not up to the required search standard for systematic reviews” (Giustini & Kamel Boulos, 2013) (278 citations).
There was no clear resolution regarding the adequacy of Google Scholar in conducting a PRISMA-informed database search by the mid-2010s. Given the comparatively large number of citations to (Gehanno et al., 2013) (470), with its positive view of Google Scholar as a database, it appeared that the direction assessments of Google Scholar were heading was regarding a greater acceptance of it for systematic reviews. However, perhaps influenced by the later evaluation by (Giustini & Kamel Boulos, 2013) of (Gehanno et al., 2013), it was the generally negative evaluations of Google Scholar as a database that provided the foundation for the Gusenbauer articles. The publication of the critiques of Google Scholar by Gusenbauer and colleagues that soon followed changed the course of reliance on Google Scholar for PRISMA-style reviews to one that became substantially less accepting such that, some researchers now exclude Google Scholar from their search process, because of these critiques (Frandsen et al., 2025; Klopfenstein & Dampier, 2021), and one article asked, “Does Google Scholar count as a database or as an additional information source for the PRISMA 2020 flow diagram?”(Rethlefsen & Page, 2022).
In an article first online 10 November 2018 (Gusenbauer, 2019), authored by Michael Gusenbauer—cited 1068 times as of the 17 April 2026 Google Scholar search—the opening sentences state, “Information on the size of academic search engines and bibliographic databases (ASEBDs) is often outdated or entirely unavailable. Hence, it is difficult to assess the scope of specific databases, such as Google Scholar” (Gusenbauer, 2019). Thus, this article, which compares the sizes of 12 academic search engines, commences by singling out Google Scholar, preempting the research results. It is not surprising, therefore, that the title begins with the question “Google Scholar to overshadow them all?” It is a query alerting readers that Google Scholar is decidedly problematic.
Almost a year later, in an article cited 2940 times according to the Google Scholar search (Gusenbauer & Haddaway, 2020), Gusenbauer (in collaboration with Haddaway) asks the following: “Which academic search systems are suitable for systematic reviews or meta-analyses?”—investigating Google Scholar as the first database, followed by PubMed, “and 26 other resources”. This article states emphatically, “our findings demonstrate why Google Scholar is inappropriate as a principal search system. We call for database owners to recognize the requirements of evidence synthesis and for academic journals to reassess quality requirements for systematic reviews”. As such, within one year, Gusenbauer and colleagues had progressed to the point of making a clear statement advising academic journals to no longer accept Google Scholar as a primary database for systematic reviews.
Although cited less frequently than the previous article (107 times), another publication by Gusenbauer and Haddaway (Gusenbauer & Haddaway, 2021) clarifies what every researcher should know about searching. One point is that although Google Scholar is “very capable for targeted searches aimed at finding specific research articles,” it “fails miserably in systematic searches”. The reasons offered for this failure are its lack of transparency and reproducibility, as the method for selecting and ranking the results is unknown. This is the only one of Gusenbauer’s publications that also criticizes the researchers who use Google Scholar, referring to them as wanting to invest little effort into their search process because they act “intuitively”.
In an August 2021 publication (Gusenbauer, 2021) (cited 38 times), Gusenbauer asserts the following to researchers. “I claim that this googling mentality is only adequate for lookup searching, the type of searching Google and Google Scholar are predominantly geared towards. For exploratory and systematic searching, however, fast contentment with high-ranking results might be problematic as it reduces the quality of search outcomes”.
By 2024, in an article assessing Search Smart—a free website offering guidance to researchers regarding the databases most likely to be productive for their search—the reader is reminded by Gusenbauer “that some databases, like Google Scholar, are ranked at the very bottom because although they may cover a given type of record, the extent to which they cover it is unknown” (Gusenbauer, 2024) (cited 13 times). Later in that publication, the author laments, “Google Scholar, for example, has barely improved its functionality in recent years.”
In a span of less than six years, Gusenbauer advanced his advice from cautioning researchers about Google Scholar to recommending that it be a supplementary database, to stating that it is inappropriate, and then ranking it at the bottom as a search engine in key respects. The most recent of these publications (Gusenbauer & Gauster, 2025) has fewer citations than the two earliest works. Nevertheless, Gusenbauer’s views on Google Scholar as a poor database for systematic reviews have only intensified. An example is his most recent work with Gauster—there, Gusenbauer has offered the following advice to researchers on conducting a literature search for systematic reviews and meta-analyses. “One database that performs particularly poorly at keyword searches is Google Scholar (GS), where misinterpretations of Boolean search queries lead to relevant results being omitted” (Gusenbauer & Gauster, 2025) (cited 97 times).
Although there remains no clear indication of whether Google Scholar is acceptable as a primary database to search for systematic reviews, the significantly greater influence of Gusenbauer’s unfavorable view of Google Scholar has dissuaded some scholars from including it in PRISMA-style systematic reviews. As a result, the initial aim of this study is to examine and enumerate the problems Gusenbauer identified in his papers that led to the determination that Google Scholar should be considered a supplementary database for systematic reviews. Whether Gusenbauer’s views should be accepted will be examined through the second aim of this study: a comprehensive analysis of the results of scoping reviews following the PRISMA guidelines undertaken by this author between 2023 and 2025 to determine the value of Google Scholar as a database in this regard.
The outcomes of these two investigation methods are that the evidence Gusenbauer presents is irrelevant to conclude that Google Scholar should be a supplementary database when conducting a systematic review following the PRISMA guidelines. Support for this conclusion comes from examining the author’s previous scoping reviews and finding that, except for one, Google Scholar returns the most and the most relevant results. As such, the recommendation is to reconsider Google Scholar as acceptable only as a supplementary database in following the PRISMA guidelines.
The Results section of this work is organized into two distinct aspects. The first is a listing and analysis of all comments on Google Scholar in publications authored by Gusenbauer. A comparison of this assessment of Google Scholar with the scoping review results of this author published since 2023 regarding the role of the included Google Scholar reports in these scoping reviews represents the second phase. The Discussion section then considers (1) Gusenbauer’s criticisms of Google Scholar to determine their validity and (2) the effect of these criticisms on other scholars regarding their use of Google Scholar for systematic reviews. Addressing the limitations of this methodology and providing suggestions for future research directions follows, ending the Discussion section.

2. Materials and Methods

The materials of this study are from two source types. The first is the comments in Gusenbauer’s publications suggesting that Google Scholar should be considered a supplementary database in following PRISMA guidelines. The second source of materials is the scoping reviews by this author published since 2023.
The initial methodology involves searching for comments made by Gusenbauer on Google Scholar in his relevant publications and listing each of them. A Google Scholar search undertaken on 19 November 2025 and supplemented on 17 April 2026 identified these. The categorization of these comments is by their types. One researcher conducted this investigation, and the categorization compared these remarks with the requirements of the PRISMA guidelines (Page et al., 2021a, 2021b). This part of the study aims to present all the negative comments Gusenbauer made about the database.
The second part of the methodology involves examining this author’s published scoping reviews to enumerate the results by the databases searched. The returns of each database searched per publication are combined into a table to create the materials.
The reliance on the author’s own previously published scoping reviews represents a methodological limitation for such research. However, the reason for undertaking this study is that, upon becoming aware of and citing the Gusenbauer publications stating that Google Scholar should be used only as a supplementary database for PRISMA-style reviews, this author was intrigued to find that the search results did not appear to support the Gusenbauer concerns. As such, relying on the author’s publications, this methodology permits the reader to identify the same concerns of this author regarding the Gusenbauer advice about employing Google Scholar for such reviews. There is no claim made that this is an exhaustive examination of Gusenbauer, PRISMA guidelines, systematic reviews, or the details of the author’s publications. The method, instead, is chrononarratology (Birke et al., 2022), a historical method (Lim, 2025) of critical narrative inquiry (Pino Gavidia & Adu, 2022).
Generative artificial intelligence (GenAI) was not used in this paper to create text, data, or to assist in study design, data collection, analysis, or interpretation. In conducting the methods and analyzing the results, the author acted independently.

3. Results

This section divides the results of the two aspects of this study into the following subsections.

3.1. Limitations of Google Scholar, According to Gusenbauer’s Six Publications

The results presented in Table 1 are from searching each of (Gusenbauer, 2019, 2021, 2024; Gusenbauer & Gauster, 2025; Gusenbauer & Haddaway, 2020, 2021) for “Google Scholar”, and including all 46 statements that represent the database negatively. Four publications by Gusenbauer acknowledge Google Scholar as the largest and most used database by scholars (Gusenbauer, 2019, 2021; Gusenbauer & Haddaway, 2020, 2021). This point is also part of an additional study by Gusenbauer that concerns 56 bibliographic databases (Gusenbauer, 2022). However, rather than being considered a positive attribute of Google Scholar, these advantages are presented to demonstrate why understanding and acknowledging its limitations as a database is imperative for researchers. Table 1 reveals that criticisms of Google Scholar by Gusenbauer were, in some cases (such as 7), not entirely rational. The table presents that the two earlier publications by Gusenbauer make the most disparaging comments about Google Scholar. Unfortunately, these are also the most cited publications, as mentioned in the Introduction section of this study.
Table 1. Forty-six quotations by Gusenbauer found in his six publications that mention the limitations of Google Scholar (“X”), numbered in the order they appear. The marks beside the numbers indicate the type of comment. (Gusenbauer, 2019) = 1, (Gusenbauer & Haddaway, 2020) = 2, (Gusenbauer & Haddaway, 2021) = 3, (Gusenbauer, 2021) = 4, (Gusenbauer, 2024) = 5, (Gusenbauer & Gauster, 2025) = 6.
Table 2 accompanies Table 1 to explain the marks beside each numbered quotation. There are thirteen distinct Gusenbauer themes regarding the limitations of Google Scholar, recognized by this author in Table 2. They are listed in Table 2 by the order in which they appear chronologically. Five themes are unique to specific publications: (1) Difficult to assess the scope (Gusenbauer, 2019), (2) Not all documents are fully available (Gusenbauer & Haddaway, 2020), (3) Not curated (Gusenbauer & Haddaway, 2020), (4) Only allows searches of up to 256 characters (Gusenbauer & Haddaway, 2020), and (5) Does not natively support bulk exports (Gusenbauer, 2024). Two comments (1) that the database is imprecise (Gusenbauer, 2019; Gusenbauer & Haddaway, 2020), and (2) there has been no improvement in Google Scholar in recent years (Gusenbauer, 2021, 2024), are mentioned by two publications. Three works stipulate problems with three issues: (1) Google Scholar is trying to convince users of its capabilities (Gusenbauer, 2019, 2021; Gusenbauer & Haddaway, 2020), (2) it is secretive (Gusenbauer, 2019, 2024; Gusenbauer & Haddaway, 2020), and (3) it does not support Boolean search functionality (Gusenbauer, 2021; Gusenbauer & Gauster, 2025; Gusenbauer & Haddaway, 2020). Most of the negative comments are in the early publications alone. However, there are four criticisms of the database that extend to the recent publications: (1) It tries to convince users of its capabilities; (2) It is secretive; (3) It does not support Boolean search functionality; (4) There has been no improvement in recent years. There are three judgments of Google Scholar that Gusenbauer repeats frequently in individual publications and in more than one: It is (1) secretive, (2) imprecise, and (3) does not support Boolean search functionality.
Table 2. Summary of the thirteen types of comments in the quotations by Gusenbauer in his six publications from Table 1 that mention the limitations of Google Scholar, numbered by the order in which they appear. The mark indicates the type of comment recorded beside the comment number in Table 1. (Gusenbauer, 2019) = 1, (Gusenbauer & Haddaway, 2020) = 2, (Gusenbauer & Haddaway, 2021) = 3, (Gusenbauer, 2021) = 4, (Gusenbauer, 2024) = 5, (Gusenbauer & Gauster, 2025) = 6.
In considering the implications of disparaging claims about Google Scholar for systematic reviews by Gusenbauer, it is relevant to present the PRISMA guidelines for database suitability. Of the well-cited publications directly associated with the PRISMA 2020 guidelines (Page et al., 2021a, 2021b), there are analyses, outcomes, sources, data, and studies that are primary; however, there is no description of the primary databases. According to these publications, the PRISMA guideline requirements are as follows: the description of the search strategy for each database is sufficient to allow another researcher to reproduce the results. This sufficiency requires identifying the database used, the search date, and the inclusion and exclusion criteria. Similarly to “primary”, “supplementary” is not a term used in relation to databases in (Page et al., 2021a, 2021b). According to the guidelines, a source is relegated to supplementary status if it is a study not found in any database. These sources include hand searches, trial registries, or websites.
Given the nonexistence of a description of a primary database in the PRISMA guidelines, Gusenbauer’s conclusion that relegating Google Scholar to supplementary status has no grounding in the PRISMA guidelines. However, those guidelines, as presented in (Page et al., 2021a, 2021b), do necessitate that the search be comprehensive, reproducible, and transparent regarding its details. What to consider is whether any of the thirteen types of comments Gusenbauer makes in his six publications that mention the limitations of Google Scholar identify the database as lacking in comprehensiveness, reproducibility, or transparency. There is no such mention for comprehensiveness. In fact, four of the Gusenbauer publications (Gusenbauer, 2019, 2024; Gusenbauer & Haddaway, 2020, 2021) note that it is the most comprehensive academic search engine. Concerning reproducibility, the adequacy of Google Scholar search parameters for search replication is the point. Gusenbauer does not state that Google Scholar is lacking regarding search replication. The problem noted in (Gusenbauer, 2019) is that the returns are inconsistent and limited, causing a lack of validity. Yet, concurrently, this publication by Gusenbauer estimates that Google Scholar has access to 389 million records. This amount compares with just over 72 million for Scopus and almost 68 million for Web of Science—two databases Gusenbauer views as consistent, ample, and valid. As high counts can include noise (Bramer, 2016; Panda & Kaur, 2024), precision or relevance are not considered in comparing Google Scholar’s size to Scopus and Web of Science. However, given that Google Scholar is a half order of magnitude larger than these two databases, the comparison with them is misleading. By his ruling that Google Scholar is secretive, imprecise, inappropriately persuasive, and lacking support for Boolean search functionality, Gusenbauer implies (and states directly) that Google Scholar lacks transparency. However, according to PRISMA guidelines, transparency regards the search itself—not the database. It is the researcher who must be transparent by stating the name and date of the database searched, along with the inclusion and exclusion criteria. The concern that Google Scholar does not natively support bulk exports means the platform lacks a built-in feature to download or export large sets of search results into reference managers like EndNote, Zotero, or Mendeley. Although this problem is an inconvenience, it does not affect any of the comprehensiveness, reproducibility, or transparency of the database. As such, the limitations of Google Scholar pointed out by Gusenbauer are irrelevant to following the PRISMA guidelines—meaning the use of Google Scholar in this regard is comparable to other databases—ones Gusenbauer judges primary.

3.2. Results of the Scoping Reviews by This Author

According to PRISMA guidelines, the studies by Gusenbauer (Gusenbauer, 2019, 2021, 2024; Gusenbauer & Gauster, 2025; Gusenbauer & Haddaway, 2020, 2021) are unable to identify the type of limitations that render Google Scholar a supplementary database. However, it may be that Google Scholar is unable to return results for systematic reviews because it lacks Boolean functionality, for example. An examination by the author of eight of her scoping reviews, following PRISMA guidelines, tests whether Google Scholar returns relevant results for systematic reviews. Table 3 provides the outcome of this examination.
Table 3. Chronological results by database of the eight scoping reviews (#) published by the author between 2023 and 2025 that included searching Google Scholar, where “–” means there was no searching of the database.
Still, it is possible that, following the PRISMA exclusion process, the returns for assessment did not include those from Google Scholar. Table 4 provides the included results. For all but one (Nash, 2025e), Google Scholar was a database with included results. Additionally, without the Google Scholar search for (Nash, 2025b) and (Nash, 2025a), there would have been no included results. For (Nash, 2025d), there would have been only one included result from Web of Science. In every case but one, where Google Scholar was a source of included results (Nash, 2025c), it produced the most included results.
Table 4. Chronological inclusions by database of the eight scoping reviews (#) published by the author between 2023 and 2025 that included a Google Scholar search, where “–” means there was no searching of the database.
Regarding the results from Table 3 and Table 4, it is possible that Google Scholar was most effective in returning relevant results for seven of the eight publications because the topics covered by these scoping reviews were the same. Table 5 demonstrates that although there was some overlap, the topics of these papers varied considerably. Six of the scoping reviews focused on COVID-19. However, concerning these works, one highlighted self-directed learning (Nash, 2023b), another examined obsessive–compulsive disorder (OCD) (Nash, 2023a), a third focused on emergency medical care (EMC) (Nash, 2025d), a fourth on dysregulation of mood, energy, and social rhythms syndrome (DYMERS) (Nash, 2025a), a fifth assessed oncologists regarding burnout (Nash, 2025c), and the sixth reviewed burnout in relation to psychological flow (Nash, 2025b). There was only one paper in the Google Scholar searches that returned the most results and was not associated with COVID-19. That scoping review examined exercise, psychological flow, and self-directed learning (Nash, 2025f). The one publication for which Google Scholar did not return the greatest number of results concerned self-directed learning and consensus decision-making in the co-creation of virtual worlds (Nash, 2025e). The reason Google Scholar produced no included studies on this topic, when EBSCO, ProQuest, and Scopus did, is unknown.
Table 5. Chronological inclusions by manuscript content of the eight scoping reviews (#) published by the author between 2023 and 2025 that included a Google Scholar search (“X”,) where “–” means the study did not investigate the topic.

4. Discussion

Among Gusenbauer’s criticisms of Google Scholar, the most persistent and the only one evident in his latest publication is that the database does not support Boolean search functionality. Although the PRISMA guidelines do not require this type of functionality, the implication is that Google Scholar lacks a relevant means of search refinement. What Google Scholar does support is the use of quotation marks around terms to search for the exact phrase and eliminate automatic synonym/variation searching for a single word (Ileanu et al., 2019). In Table 3, (Nash, 2025b) is identified as including two Google Scholar searches. One returned 290 results, and the other 25 results. The keywords searched with 290 results were [Burnout psychological flow Csikszentmihalyi employees OR healthcare providers “COVID-19” since 2021]. Those that returned 25 results were [“burnout”, “psychological flow”, “Csikszentmihalyi”, employees OR healthcare providers, “COVID-19”, since 2021]. The results of both searches were retained for the study, as only 17 of the returns were common between them. This result indicates that using quotation marks is a meaningful way to refine a Google Scholar search process. The Boolean operator “OR” was included in this search, although it was not utilized as such by the database search process.
The power of using or not using quotation marks is relevant regarding a Google Scholar search. As an additional example, the most recent scoping review published by this author (Nash, 2025e) was the only one to lack results from Google Scholar as part of the included studies (see Table 4). The Google Scholar search for this study used quotation marks around each concept [“self-directed learning”, “mobile technology”, “co-creation”, “virtual worlds”, “2021–2025”, “no citations”]. The outcome of 12 returns for this search (see Table 3) was from 30 March 2025. This one was the only Google Scholar search for that study. However, performing the search on 4 December 2025 with no quotation marks among the keywords [self-directed learning mobile technology co-creation virtual worlds 2021–2025 no citations] produced “About 15,000 results” for publications since 2021. Placing quotation marks around only “self-directed learning”, a Google Scholar search on the same day produced “About 8340 results”. If quotation marks were around “mobile technology” alone, the returns were “About 2020 results”. With quotation marks around just “co-creation”, there were “About 1450 results”. Thus, quotation marks make a significant difference, and their type of use is relevant.
What is identifiable from the assessment of the scoping reviews by this author regarding Google Scholar is that, similar to the results of “Is the coverage of google scholar enough to be used alone for systematic reviews” (Gehanno et al., 2013), there is a retention of the 2013 conclusion. As previously quoted in the Introduction above, “The coverage of GS for the studies included in the systematic reviews is 100%. If the authors of the 29 systematic reviews had used only GS, no reference would have been missed. With some improvement in the research options, to increase its precision, GS could become the leading bibliographic database in medicine and could be used alone for systematic reviews.”
Still, the reason for undertaking this study was that Gusenbauer’s negative assessment of Google Scholar for PRISMA-type reviews influenced researchers to avoid Google Scholar in their systematic reviews. Therefore, there must be a demonstration that Gusenbauer’s negative assessments of Google Scholar were sufficient to stop researchers from including Google Scholar as a primary database when following the PRISMA process. As mentioned in the Introduction, (Frandsen et al., 2025; Klopfenstein & Dampier, 2021; Rethlefsen & Page, 2022) excluded Google Scholar from their search process based on the negative assessment of it in this regard. A 2021 publication on procedures for undertaking systematic reviews that refers directly to the PRISMA process states, “Google Scholar is subject to drawbacks that make it unsuitable as the main source of the actual literature search” (Foo et al., 2021). The citation supporting this claim is to the Gusenbauer and Haddaway 2020 publication (Gusenbauer & Haddaway, 2020). A PRISMA-style review from 2022 on designing digital technologies cites (Gusenbauer & Haddaway, 2020) as the reason for their selection of databases—a selection that does not include Google Scholar (de Busser et al., 2022). For a 2023 systematic review of pancreatic cancer, although the authors do not state directly their reason for not including Google Scholar, they cite (Gusenbauer & Haddaway, 2020) as the reason for their choice of databases to search (Gromny & Neubauer, 2023)
In contrast, one publication did use Google Scholar in their search but, in citing (Gusenbauer & Haddaway, 2020), noted that “This step also included the use of Google Scholar that, although deemed inappropriate as a central search system, can be considered an additional resource to make sure that relevant papers that fit this SR’s scope were also included” (Peixoto et al., 2021). This example demonstrates that, as a supplementary database, Gusenbauer was not against the use of Google Scholar. To another extent, Gusenbauer’s 2019 (Gusenbauer, 2019) and 2020 (Gusenbauer & Haddaway, 2020) publications, noting that Google Scholar has the most extensive reach of any database, were cited by several publications. In 2023, (Gusenbauer, 2019) was cited by (Van Der Merwe et al., 2023) and, in 2025, by (Solanki & Thomas, 2025). Both (Gusenbauer, 2019) and (Gusenbauer & Haddaway, 2020) were cited in 2024 by (Xu et al., 2024) and (Liu et al., 2024). In 2022, (Useche et al., 2022) cited (Gusenbauer & Haddaway, 2020) alone as did (Akoh, 2024) in 2024 and (Nguyen & Baker, 2023) in 2023. The reason for their citation was to substantiate the use of Google Scholar to conduct a PRISMA-style review. This outcome indicates that not all authors considered Gusenbauser’s results a deterrent to including Google Scholar in their database searches. In addition, the authors of the publications from 2024 (Xu et al., 2024) and 2025 (Solanki & Thomas, 2025) interpreted (Gusenbauer & Haddaway, 2020) as a positive recommendation to use Google Scholar for a PRISMA-style review because it accesses the grey literature. Another reason a 2023 publication (Nguyen & Baker, 2023) offers for using Google Scholar in a PRISMA-style review is that it is a crawler search engine, and, therefore, differs from other databases, citing (Gusenbauer & Haddaway, 2020) as the reason for the identification of this Google Scholar quality. Thus, what is seen as detrimental for primary database searches by (Gusenbauer, 2019) and (Gusenbauer & Haddaway, 2020) is reinterpreted by several authors in later systematic reviews as an asset. As such, although several authors were affected by Gusenbauer’s studies to omit Google Scholar from their PRISMA-style review, this was not the only response.
A limitation of this study is its single-author design, which includes a self-authored dataset lacking inter-rater reliability. For qualitative research, inter-rater reliability methods are used to improve the transparency and consistency of qualitative data analysis rigor when codes and constructs have been developed from data (Cole, 2024). Yet, as historical research, this work is neither a psychological nor a sociological study and thus does not necessitate these methodological requirements. Historical research based on single-author work remains the most common (Praus, 2025). Researcher (Baldwin et al., 2022), confirmation (Peters, 2022), or cognitive bias (Neal et al., 2022) may be the outcome. There is a mitigation of the potential biases in two ways: (1) a presentation of the direct quotations from Gusenbauer, and (2) Table 3, Table 4 and Table 5 contain all the relevant information regarding the author’s publications. As such, any researcher can fully examine the assessment made by the author. They have complete and transparent documentation.
An additional limitation is that the focus of this study is narrow. There is no detailed analysis of the vast body of critical literature regarding Google Scholar. Similarly, this work does not conduct an exhaustive search of the critical literature on systematic review criteria other than PRISMA, nor does it examine methodological details of database searches. Between the transparency requirements of systematic reviews and the methodological considerations of PRISMA, there is a difference. The focus of this analysis is methodological considerations regarding the PRISMA guidelines. Not considered are the transparency requirements for systematic reviews in general, which, for such reviews, may be of greater importance than adhering to the PRISMA guidelines.
A final limitation is that, although it represents a report regarding systematic reviews, this study itself is not a systematic review. The information provided in the Introduction on critiques of Google Scholar is selective and non-systematic. There are no clearly defined inclusion criteria, reproducible methods, or validation procedures. This weakens the robustness of the analysis. Nevertheless, the purpose of this study was a historical analysis of both Gusenbauser’s work on Google Scholar and this author’s scoping reviews. In this regard, it represents an essay, rather than a review.
Future research directions on this topic include reviewing the evidence presented by Gusenbauer and others who view Google Scholar as a supplementary database for systematic reviews, addressing the research question: “Are the limitations of Google Scholar sufficient to necessitate that it be considered a supplementary database in following PRISMA guidelines?” Regarding PRISMA guidelines, the aim is to demonstrate whether, in support of the findings of this article, Google Scholar can be considered a primary database for systematic reviews. The following question may address this: “Are PRISMA guidelines sufficient to identify the most relevant reports for a systematic review?” The suggestion is to undertake this work as a systematic review.

5. Conclusions

The claim by the authors of well-cited articles that Google Scholar is inappropriate as a primary database for following the PRISMA guidelines for systematic reviews is unsupported by an examination of quotations of these well-cited articles in comparison with the PRISMA guidelines. Additionally, this author’s analysis of Google Scholar relative to primary databases for scoping reviews demonstrated not only its adequacy for identifying included studies but also its superiority. Examining eight author-published scoping reviews accomplished this outcome. Based on these findings, the suggestion is to accept Google Scholar as a primary database, comparable in all relevant ways to other primary databases for a PRISMA-style review.

Funding

This research received no external funding.

Data Availability Statement

No new data were created.

Acknowledgments

The author takes full responsibility for the contents of this review.

Conflicts of Interest

The author declares no conflicts of interest.

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