The research question guides the review, and for a concept analysis, it must be broad and comprehensive [10,15]. The research question developed by the research team is “What is known from the existing literature about the concept of familiarity?”

For the review, 8 databases will be searched for relevant literature, including PubMed, CINAHL (Cumulative Index to Nursing and Allied Health Literature) Plus with full text, APA PsychInfo, Communication Source, EBSCO MegaFILE, Medline, Nursing & Allied Health Database, and ScienceDirect. Gray literature is not included in the review; however, reference list scanning will be completed during the literature screening procedure. Thus, literature outside of the search dates may be included if deemed relevant.

A challenge for this review is the pervasive use of the word and quantity of literature that may be located during the search. As suggested by Aromataris and Munn [15], the search terms must be both specific and broad to access relevant literature for full conceptualization while balancing the need for a manageable amount of literature for a review. The search parameters include the word “familiarity” in the abstract or title and from a peer-reviewed source from January 1, 2016, to 2022 (Textbox 1). The review was conducted late in 2021, and 2022 literature may be released and will be included in the scoping review. The search terms include “empathy and familiarity” OR “memory and familiarity” OR “recognition and familiarity” OR cognit* and familiarity” OR “spatial familiarity” OR “contextual familiarity” OR “personal familiarity” OR “belonging familiarity” OR “relationship and familiarity” OR “lack of anonymity and familiarity” OR “privacy and familiarity” OR “confidentiality and familiarity” OR “nurs* and familiarity” OR “medicine and familiarity” OR “social work and familiarity” OR “healthcare and familiarity” OR “rural and familiarity” OR “gaming and familiarity” OR “social media and familiarity” OR “culture and familiarity” OR “religion and familiarity” OR “spirit* and familiarity.” The search terms will be run in each of the selected databases using the asterisk symbol as an end-of-root-word-truncation mark. The identified literature will be imported to the Covidence software program with duplicate records removed.

The literature screening is composed of 2 separate reviews. Covidence software will be used to manage the scoping review with each citation independently reviewed by 2 research team members for eligibility. Eligibility will be determined using a 2-level process. Each title and abstract will be screened for eligibility; for citations deemed eligible, a full-text article review will be conducted. The scoping review is expected to locate a large body of literature, and eligibility criteria will be refined during the title and abstract screening process. In addition, reference list scanning will be used to locate relevant literature. The literature screening process is consistent with the screening strategy described by Aromataris and Munn [15].

The research team will have regular meetings (every 1-2 weeks) to discuss the project, refine eligibility criteria, and resolve conflicts on article eligibility. Resolution of disagreement on the eligibility of an article will occur during the full team meeting. The majority will decide eligibility. If the team is unable to establish consensus, the project leader will resolve the disagreement.

The research team has developed a draft charting table for data extraction (Textbox 2). Data will be charted using a descriptive method that aligns to the scoping review’s research question and extract descriptions, definitions, and other relevant findings on familiarity. Key to this review is to identify all the ways familiarity is used, both implicit and explicit, in the identified literature.

Aromataris and Munn [15] suggest that the draft charting table be piloted by each team member. For this review, each team member will trial the charting table by extracting data from 3 articles [15]. At the end of the trial, the research team will meet to determine the adequacy of the charting table and make modifications, if needed. Owing to the broad nature of the concept, the data charting process is considered iterative [15]. Thus, the charting table may be continually updated by the team, if deemed necessary, to fully understand the concept.

Similar to the literature screening process, selected articles will have data charted by 2 team members. Team members will independently extract data from the selected literature. In the event of disagreement on the data extracted, the research team will discuss at a full team meeting. The majority will decide data disagreements. If the team is unable to come to an agreement, the project leader will resolve the disagreement.

The data analysis will be guided by Walker and Avant’s [10] 8-step concept analysis process, starting with step 4:

Central to the process is to identify the defining attributes of familiarity, which reveal the characteristics of the concept [10]. For the analysis, each team member will independently review the data tables and begin to cluster data that offer broad insight into the concept of familiarity. The process is iterative as the team identifies phenomena and occurrences in the data. The defining attributes will be considered complete when each attribute can “stand alone” and fully capture the essence of the concept [10].

Identification of cases demonstrates what the concept is and what it is not in situational life examples. A model case will demonstrate familiarity using the defining attributes identified [10]. To delineate related concepts that may be close to familiarity, additional cases will be developed, including borderline, related, contrary, invented, and illegitimate cases [10].

Once clarity on the defining attributes is achieved, the antecedents and consequences will be identified. Antecedents are “those events or incidents that must occur or be in place prior to the occurrence of the concept” [10]; consequences are “those events or incidents that occur as a result of the occurrence of the concept—in other words, the outcomes of the concept” [10]. This portion of the analysis supports a theoretical understanding of how the concepts fit together.

The final part of the analysis is to identify the empirical referents or how familiarity is revealed in everyday life [10]. The empirical referents represent categories that will support the development of a measure [10].