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Research Paper Checklist

Research papers are hard. As tempting as it may be to just hand in your paper the second you finish that last citation, it is super important to review everything to make sure you don’t have any silly mistakes!

Use this 10-step checklist to make sure your paper is in top-notch form:

• Credit and cite all information from other sources.
• Place direct quotes from other sources between quotation marks.
• Add all appropriate in-text citations or footnotes.
• All in-text citations/footnotes have a matching citation in the bibliography.
• Alphabetize bibliography and check formatting/ capitalization of titles .
• The thesis statement (purpose of the paper) is clearly stated.
• The paper has a clear conclusion/closing statement.
• Check for spelling and grammatical errors.
• Check for slang words or contractions in writing.
• The title page is properly formatted (when required by your instructor).

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Research Paper Writing Checklist

• Writing Research Papers
• Writing Essays
• English Grammar
• M.Ed., Education Administration, University of Georgia
• B.A., History, Armstrong State University

A research paper checklist is an essential tool because the task of putting together a quality paper involves many steps. Nobody writes a perfect report in one sitting!

Before you get started on your project, you should review the checklist on ​ research ethics .

Later, once you have finished the final draft of your research paper, you can use this checklist to make sure that you have remembered all the details.

Research Paper Checklist

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• How to Write a 10-Page Research Paper
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• How to Narrow the Research Topic for Your Paper
• How to Develop a Research Paper Timeline
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• The Introductory Paragraph: Start Your Paper Off Right
• Research Note Cards
• Strategies for Writing a 20-Page Paper

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APA Style: APA Basics Checklist

Apa basics checklist.

Writing Center staff created this APA checklist to help students remember the basics of APA citations, reference lists, and style. It is not meant to be comprehensive, but students should use it as a reminder of the various APA rules that academic papers follow. If students are not sure what a particular item in the checklist refers to or entails, they should follow the link for more information. Have a question about APA? Ask OASIS .

• Citations follow APA guidelines as articulated in section 8.1 of the APA manual (7th edition).
• Sources used and cited in the paper are included in the reference list.
• The abbreviation “ et al. ” is punctuated appropriately.
• Author(s) and publication year are always included.
• A page or paragraph number is included for all quoted material, using the appropriate abbreviation: (p. xx) or (para. xx).
• The citation is included within the ending punctuation for the sentence.
• Authors of cited studies are included within the sentence.
• The publication year is included in parentheses immediately after the authors’ names.
• Publication years are included the first time a source is used in a paragraph; all subsequent uses of that same source do not include the publication year. Note: Rule starts over with a new paragraph.

Reference List

• The title of the list is centered and bolded.
• Each entry has an automatically formatted hanging indent .
• Each entry has the basic information (as available): author(s), publication year, title, and retrieval information.
• Punctuation: periods and commas
• Formatting: italics is used only when needed
• Parentheses and brackets: used only when needed
• Appropriate electronic information is included
• Past tense is used whenever literature or sources are talked about (i.e., Smith discussed).
• Serial commas are used for all lists of three or more items (i.e., lions, tigers, and bears).
• used to join words that work together to modify another word (i.e., evidenced-based practice);
• used to join “self” compounds (i.e., self-esteem); and
• not used with prefixes such as "non," "semi," "pre," "post", "anti," "multi," and "inter."
• Block quotations (of 40 or more words) are formatted as such.
• Headings follow proper APA style (i.e., Level 1 headings are centered and bolded).
• 10 and above are expressed using numerals,
• nine and below are expressed using words.
• expressing specific numbers and time use numerals, and
• expressing approximate time use words.
• Complex lists of items within a sentence or paragraph can use letters to separate the items.
• Bulleted and numbered lists are used for specific reasons.
• The third person editorial "we" is avoided (including "us ," "our ," and "you").
• Capitalization rules are followed (i.e., names of models and theories are not capitalized).
• Course paper template is used.
• Title page follows the template guidelines.
• Double spacing is used throughout the paper (including the reference list).
• Use one space after periods or other punctuation marks that end a sentence.

Didn't find what you need? Email us at [email protected] .

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Introduction

Overall guidelines, table(s), figure(s), appendix.

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These guidelines are adapted from the  student paper  specifications from  Publication Manual of the American Psychological Association  (7th ed.). 

• In the 7th edition, APA created a simplified version of their paper format for student papers, which omits previously required elements (sect. 2.2, p. 30). Items that APA states are not typically included in a student paper and are not, therefore, covered in this guide include: Running head, author note, and abstract.
• This guide is not exhaustive; refer to the Publication Manual for additional details and for specific details for professional papers.

Always defer to your professor or instructor’s guidelines for an assignment – it's essential that you understand their expectations and ask questions about any guidelines that are unclear or confusing. This includes whether they would like you to use the  student  or  professional  paper format.

• Margins:  1 inch on all sides
• Sans serif fonts: 11-point Calibri, 11-point Arial, or 10-point Lucida Sans Unicode
• Serif font: 12-point Times New Roman or 11-point Georgia
• Line Spacing:  Double-spaced, including title page, abstract, text, headings, block quotations, reference list, table and figure notes, and appendices. See p. 45 of the Publication Manual of the American Psychological Association  for exceptions.
• Indentation :  First line of each paragraph should be indented 0.5 in. Exceptions: Abstract and block quotes
• Alignment :  Left align all text.  Exceptions: headings (see section about headings.)
• Page numbers should appear in the upper right-hand corner of the header. 
• Use "View" → "Header" in Microsoft Word to set page numbering
• Formatting an APA 7th Edition Student Paper in Word (Video) This video shows you how to set-up your APA 7th edition student paper in Microsoft Word
• Formatting an APA 7th Edition Student Paper in Google Docs (Video) This video shows you how to set-up your APA 7th edition student paper in Google Docs
• Title of Paper : Centered on the page, bold.
• Author(s) : Centered on the page, underneath the title
• Author(s) Affiliation : Typically department and institution (e.g., Department of Psychology, Towson University), centered underneath author(s) name(s)
• Course Number and Name : E.g., PSYC314: Research Methods, centered underneath author affiliation
• Instructor Name : Confirm preferred name and honorific with your professor, centered underneath course number and name
• Due date : APA recommends spelling out the month, e.g., December 4, 2019, centered underneath instructor name

Note: Refer to the APA Publication Manual (7th ed) if your professor requires you to use the professional title page format. APA no longer requires elements such as the running head and author note for student papers.

The  body  of the paper "contains the authors' main contributions to the literature" ( APA Publication Manual  [7th ed], p. 39).

Components and structure of the paper vary depending on your assignment. For example, original research reports include the following sections: "Introduction," "Methods," "Results," and "Discussion."

Refer to the  APA Publication Manual  or your assignment instructions for the details about the type of information that is included in each section.

Most papers will use the following general guidelines:

• Starts on a new page after the title page or abstract
• Include the title of the paper as a Level 1 heading
• For instance, the "Methods" and "Results" section are equal, and they are both formatted as Level 1 headings. 
• If you discuss "Participants" and "Measures" in your "Methods" section, then you format each of those as Level 2 headings, and so on.
• Begin your text in a paragraph below the heading for Levels 1, 2, & 3. Begin the text of your paragraph in the same line with the headings for Levels 4 & 5.

• Starts on a new page
• The word "References" should appear centered on the page, capitalized, and in bold
• Use a hanging indent - the first line of each reference entry should be flush to the left side, all lines after the first line of each entry should be indented 0.5 inches from the left margin
• Double space all reference entries
• Alphabetize entries by the first authors' last names
• Two or more works by the same author should be ordered by publication date, with the oldest entry listed first. For additional order rules, see sections 9.44-9-49 in the  APA Manual  (7th ed.).
• Format reference entries according to type – refer to the citation examples on other pages within the APA Style Guide

Refer to the APA Publication Manual for guidelines related to formatting tables, figures, and appendices.

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Checklist for Research Papers

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• Do I have a sufficient number of sources?
• Are a significant number of my sources critical sources (e.g., from academic journals)?
• Are my sources integrated smoothly into the paper?
• Is there a dialogue between my own analysis of the text and the research I'm including?
• Is my own scholarly opinion strongly present in the research paper, rather than the paper reading like a review of the opinions of other scholars?
• Have I cited all sources I draw from?
• If my paper is a revision, have I considered the changes I want to make, the comments of my peers, and the instructor's comments towards the end of significantly improving on the previous version of this paper?

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Student Learning Center, University of California, Berkeley

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This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivs 3.0 Unported License.

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Research paper writing checklist

Use this to plan your steps in writing a research paper.

Everyone approaches their writing process in different creative ways, but there are some essential steps you have to follow.

No matter your level of familiarity with the topic or the challenges you may encounter along the way, following a strategic approach will help you speed up the process.

Below is a checklist that outlines a simple but effective strategy for writing a research article.

10 steps to writing an impactful paper

Get familiar with your subject and narrow the topic.

It is very important to understand what your lecturer, professor, or the journal is asking for before you start writing. It’s easy to ignore this step, but then wonder why you got a low grade or got rejected by a journal.

Take your time to understand your assignment or project. Have a thorough look at the instructions and requirements provided. It might be helpful to take notes and highlight points around the instructions for emphasis.

If you are writing your paper to submit to a journal, make sure you choose your target journal as your first step. This will help you have a good understanding of the journal’s requirements.

For help narrowing down your list of journals, here are  3 great tools and resources to help you identify the best home for your research .

Here’s also our  guide to learn more about the variety of different types of research articles . Its important to understand the uniqueness of your article.

Begin your research

After you have decided the direction you want to take your paper, it’s time to research the topic in detail. If you are writing to publish in a journal, then it’s also time to learn more about the journals you’re targeting.

Keep in mind that while you research, you may find information that makes you want to change your focus. In this case, make sure your paper answers the new question and is positioned to address your new focus.

You may not be able to read every material in detail so learn how to identify key points and arguments. Find reliable resources and explore the information you come across.

If you are planning to submit your paper to a journal, make sure you familiarize yourself with its  editorial policies and standards of reporting . This will cover everything from  how the journal conducts peer review  to the  process for submitting your article .

Organize your research

At this step you should have a list of sources that have influenced your viewpoint. People have different preferences on how to organize their research. Do what feels most effective for you.

Keep records and copies of all the information you obtain. This is the best step to sort the referencing and bibliographical information in your paper. Make sure you keep notes of where you found the information and how it relates to your research.

Form your thesis

Now that you understand your topic and how it fits your assignment or your target journal, it’s time to compose a thesis statement.

The purpose of your paper is to prove the validity of your thesis, so your thesis statement will provide clarity on how to control your idea. Your thesis statement will also guide your choice of resource materials.

Your thesis statement should be a short sentence that explains and proves the position of your paper to the reader.

Determine your article structure

After you have worked hard to create a specific thesis statement for your article, it may be helpful to organize your research with an outline. Creating an outline is about structuring your paper in a way that makes it easier for readers to understand your work.

Depending on your assignment, subject, research focus, journal choice and any number of considerations, the type of article you write could vary widely. If you were instructed to use a specific outline, be sure to follow the instructions.

Your outline should reflect the organizational format you have chosen for your paper. There’s no set formula for structuring your article, but our  Writing your paper free guide  has some hints and tips to get your started.

Choose your keywords

Using keywords in your paper helps others find your article easily, in a database or search engine. With ever-increasing volumes of information available digitally, finding relevant sources has become challenging.

So, picking your keywords wisely is worth your while. The more the content of an article reflects the keywords used, the higher it will appear on the results page.

Please read our  researcher’s guide to SEO  for more information on how to make your work more discoverable and more likely to be read (and perhaps cited) by other researchers.

Write up your draft

After you have completed your final article structure and chosen your keywords, you can start writing your first draft. Remember that you will write multiple drafts, so do not put too much pressure on the first one.

Understand that every step is unique, and as mentioned, the structure of your article and the sections it includes will depend on both the subject of study and the type of article you’re writing.

Read our guides to learn more on  how to write a journal article  and  how to write a review article . Make sure you understand the various  different types of research articles .

Edit and refine your paper

After you have completed your initial draft, take some time to congratulate yourself for reaching this significant milestone! But, the work is not finished yet. All writing has to be improved before submission. This is the time to make your paper as perfect as you possibly can.

Your paper will need to be edited for content and for grammar. Learn how to approach editing your paper with  our guide on research paper editing .

Also, consider using  subject-relevant experts to help edit your paper  to improve the quality and help you submit with confidence.

Review your final draft

The making of a good article is effective reviewing and editing, to make sure your ideas and findings are communicated clearly throughout.

For a host of tips on refining and editing your paper to make sure your core ideas and findings are clear,  download your Writing your paper free guide .

Check that you have followed instructions and included all requirements

This checklist is to help you along your research paper writing process. Make sure you read and understand the specific requirements and instructions that are specific to your paper.

It is a good idea to have  professional paper editors  review your work, to make sure you submit original content and that your work is formatted correctly and free of errors.

Expert help for your manuscript

Taylor & Francis Editing Services  offers a full range of pre-submission manuscript preparation services to help you improve the quality of your manuscript, so you can submit with confidence.

Related resources

Download your free guide to Writing your paper

Tools and resources for writing your paper

Guidance throughout your research publication journey

Check List for Research Papers

Statement of purpose, review of literature, transitions..

We have discussed the topic of code-switching in Swahili from what might be termed the point of view of the mechanics of code-switching; i.e. how it operates in Swahili; let us now examine its function in Swahili linguistic culture, i.e. why Swahili speakers choose to code-switch, and when. We will then show how code-switching is used in popular media, print advertising, and other genres.

No discussion of print-medium advertising in Swahili would be complete without a discussion of another, related phenomenon, which is the use of language(s) and varieties in comic books. Particularly instructive are Swahili renditions of Tarzan comics, which depict Tarzan as fluent in Swahili and English, while other characters are depicted only as speaking English inadequately.

"The work of Ferguson (Ferguson 1959:32) is crucial for our understanding of the concept of diglossia."

"No discussion of language maintenance would be complete without the work of Fishman (1959, 1960, 1963, 1966, 1972, [...])"

Most researchers on the subject of bilingualism accept the notion that one language or code will be dominant, i.e. they assume that individual speakers have more facility, or higher proficiency, in one language than in another; that is, the so-called balanced bilingual is a rare phenomenon. I will follow this practice, but will also point out examples where this has been shown to be problematical.

Which sounds better, `English's worldwide spread' or `the worldwide spread of English'? `The Queen of England's unruly children' vs. the unruly children of the Q of England'? Spelling problems are marked in margins etc. with "sp" Stylistic problems are given alternative suggestions. (sometimes marked in margin "awk" for awkward.) If some words or phrases are repeated or overused, the mark repet for `repetitious' may appear in the margin. If the symbol PP appears, it means "start a new paragraph". Content I stated at the beginning of the course ("Helpful Hints...") that I would like your paper to reflect issues and problems we have discussed in various ways during the class. I will not try to summarize these here, but I would like to see evidence that these ideas have been considered, and brought to bear on the material you are discussing. I do not expect you to parrot what others say, or what I have said; I expect you to contrast different ideas and weigh them; or bring two disparate opinions or approaches together and show how the conjunction of these ideas throws new light on the subject. Example: Much has been written about the status of French in France, and much has also been written about French attempts to control the corpus of Standard French. What has not often been made clear is how the French themselves do not usually distinguish between corpus and status issues, and that is what I wish to focus on in this paper. As such I introduce no new facts into the situation, but I do introduce a new interpretation of existing facts.

I have discussed in this paper how such issues as code-switching, code-shifting, and bilingualism in Swahili linguistic culture are manifested in print-medium advertising in East Africa. I have attempted to describe in a general way both the mechanics of these phenomena, as well as the social motivation for them, and how advertisers use these techniques for their own means in advertising.

In the process I have attempted to demonstrate that these phenomena are intricately interwoven with social forces identified by various writers as modernization, power-relations, and gender relations in East African society. They do not constitute in any way a failure of the linguistic code, but are in fact a manifestation of shifting identities in the culture.

My own contribution, if any, has been to bring in the work of A, B, and C, and relate their research to the ideas presented by X, Y, and Z, who are the acknowledged primary researchers in this field.

Example: In the process of this review, an attempt to define the role of language in the definition of ethnicity, I have to conclude that many researchers seem to define ethnicity in a circular or tautological way, i.e., as a constellation of factors involving language, race, descent, culture, history, etc. but often with one or more of these factors missing. Some researchers act as if ethnicity were a given, something that must be present in society, rather than a construct they themselves have invented. And, they often act as if all languages are equal in their impact on ethnicity, or as if any `language' at all would do for their definition of ethnicity , with no sense of the complexity of any one language. My conclusion, therefore, is that ethnicity is a problematical construct, and that in the society I examined, Eastern Rumelia, ethnicity indeed seems to involve a language factor, but having said this, I am unable to state what ethnicity actually means to the Rumelians. Perhaps this is a factor of the recent political shift in eastern Europe, but in any event, the concept of ethnicity seems to be in a very fluid state. Much more work, beyond the scope of this paper, is obviously required.

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Peer review checklists

Use this guide to write your reviewer report.

The checklists below are intended to help maximize your time, by being a useful guide while you carry out your peer review task.

When you use a peer review checklist, it will be easier to rate each of the parts in the paper you’re reviewing according to their strength. This will also make sure you don’t miss any critical steps in the process. 

Peer review expectations and requirements will vary between different subject areas and article types, which is why we’ve prepared a number of different checklists to guide you through the process. First, read our guide to writing your review report then, choose the most appropriate checklist for the work you’ve been asked to review.

Are you peer reviewing a PLS or PLSP? These guides might be useful too:

Plain Language Summary peer review guidelines

Plain Language Summary of Publication peer review guidelines

Before you begin

Have you read the general guidelines for peer reviewers ?

Do you understand the peer review process of the journal you’re reviewing for?

Do you know the journal’s aims and scope? 

Are you familiar with the journal’s instructions for authors?

If you are confident with your answers to the above questions, please read our step-by-step guide to writing your reviewer report. Then choose the checklist that is most suitable for the manuscript you’re reviewing. 

How to write a peer review report

Below is a step-by-step guide to help you review a manuscript and make your recommendation.

Research the journal

Visit the journal homepage on  Taylor & Francis Online and read the aims and scope and instructions for authors to get a sense of the journal’s scope and content. This will help you determine if the paper you’re reviewing is suitable for the journal or not.

Read the paper

While you read the paper remember to check over any tables, figures, or supplementary data. Bear in mind that the main factors you should provide advice on are:

The originality, presentation, and relevance of the manuscript’s subject matter to the readership of the journal.

The accuracy and validity of the methodology, and whether the conclusions are appropriately supported.

Write your report

There are two purposes for your report: to provide the editor with information to enable them to make a decision, and to provide feedback to the author to help improve their work.

It is often helpful to begin with a brief summary of the work and the main findings as you understand them, along with a summary of your overall opinion.

Being critical whilst remaining sensitive to the author isn’t always easy. A good rule is to direct your criticism towards the work carried out and avoid comments that may be interpreted as personal criticism of the author.

Here are a few things to consider when writing your report:

Your comments must be suitable to send to the author. Please make constructive suggestions, seek clarification on any unclear points, and ask for further elaboration. Remember that authors will welcome positive feedback as well as constructive criticism.

If the paper reports original research, comment on whether the methods are appropriate and whether the work was carried out to the standards expected within your field.

Note any aspects that you are unable to assess, whether this is due to lack of clarity or because it is outside your expertise.

You should make suggestions on how the author can improve clarity, conciseness, and the quality of the presentation.

Confirm whether you feel the subject of the paper is sufficiently interesting to justify its length. If you recommend shortening, mention specific areas where you think this is required.

It’s not the reviewer’s job to edit the paper for spelling, grammar, etc., but it is helpful if you can note specific points where the technical meaning is unclear.

You may disagree with the author’s opinions, but you should allow them to argue their case, provided their evidence supports it.

Reviewers are not expected to detect research integrity concerns in manuscripts, but your expertise may allow you to spot potential issues that editorial staff or the editor have missed. If you suspect misconduct, please let the publisher or the editor know as soon as possible.

Please consult the reviewer checklists below (where applicable) while reading the paper and writing your report:

Science, Technology, Engineering and Mathematics (STEM) research article checklist

Arts and humanities research article reviewer checklist

Clinical research article reviewer checklist

Non-research article reviewer checklist

Provide detailed feedback

Comments should be carefully worded so the author understands what actions they need to take to improve their paper, rather than just stating what is wrong.

Try to write simply and avoid rhetorical flourishes that may lead to misunderstandings. Also, avoid generalized or vague statements as well as negative comments which aren’t relevant or constructive.

Example of peer review comments

Please note that these are just examples of how you might provide feedback on an author’s work. You should, of course, always tailor your review to the paper in question and the specific requirements of the journal and the editor.

Positive comments

The manuscript is well-written in an engaging and lively style.

The level is appropriate to the journal’s readership.

The subject is very important, it’s currently something of a “hot topic”, and this study makes significant contributions.

This manuscript ticks all the boxes I have in mind for a paper in this journal. I have no hesitation in recommending that it be accepted for publication after a few typos and other minor details have been attended to.

Given the complexity involved, the author has produced many positive and welcome outcomes. The literature review offers a useful overview of current research and policy, and the resulting bibliography provides a very useful resource for current practitioners.

This is a well-written article that identifies an important gap.

While this study is largely confirmatory, it is still a useful and welcome contribution.

I have checked over the methods and the supplementary data, and I found the study to be well carried out and appropriately controlled, with no obvious errors.

Constructive feedback

The abstract is very lengthy and goes into detailed accounts that are best suited for the article’s main discussion sections. I suggest the author reduces this section to keep only the most important elements.

I would strongly advise the author to rewrite their introduction, analysis, and discussion to produce a more contextualized introduction to…

The authors have used X approach and therefore I would expect to see additional controls/an explanation of the ethical approvals/deposition of the data in a public database. It is essential that the authors provide this information.

Citations to several important articles need to be added, as follows …

The data shown in table 1 and figure 3 appear to indicate X, whereas the Results section states Y. The authors should carefully check …

This research reveals an interesting finding about … However, I would like to see more discussion of exactly what this finding means and its implications.

I would have wished to see more information on …

I don’t think that this article contains enough robust data to evidence the statement made on page X, lines Y–Z. This should be toned down.

This discussion could be expanded to explain…

The author could strengthen the paper by…

The paper would be significantly improved with the addition of more details about…

Unfortunately, I have identified a potential major flaw in the work, which I believe will be difficult to resolve unless the authors are able to do the following additional analyses …

To make this paper publishable, the author needs to respond to the following substantive points…

Linguistic alterations

This paper would benefit from some closer proofreading. It includes many linguistic errors (e.g. agreement of verbs) that at times make it difficult to follow. It may be useful to engage a professional English language editor following a restructuring of the paper.

The paper would benefit from stylistic changes to the way it has been written for a stronger, clearer, and more compelling argument.

There are a few sentences that need rephrasing for clarity.

Make a recommendation

Once you’ve read the paper and have assessed its quality, you may need to make an overall recommendation to the editor to help them make a decision. The specific options used by a journal will vary, but the key recommendations are:

Accept : The paper is suitable for publication in its current form.

Minor revision : The paper will be ready for publication after light revisions. Please list the revisions you would recommend the author makes.

Major revision : The paper needs substantial changes such as expanded data analysis, widening of the literature review, or rewriting sections of the text.

Reject : The paper isn’t suitable for publication in this journal, or the revisions needed are too extensive for the submission to continue being considered in its current form. It is helpful to the editor if you can explain (in confidential comments if necessary) whether your recommendation is based upon the level of advance or whether it is due to technical flaws.

When authors make revisions to their article, they are asked to include a list of changes and any comments for the reviewers.

The revised version may be assessed by the editor if only minor revisions were requested or may be returned to the original reviewers if available. You will then be asked to affirm whether the revisions are satisfactory.

STEM research article checklist

Arts and humanities reviewer checklist

Further resources

Reviewer training

Peer review and your career

FAQs during review

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The Essential Guide to Doing Your Research Project

Student resources, checklist for writing a literature review.

☑ Read quite a few good, relevant reviews

☑ Identified the variables in your study

☑ Developed a list of synonyms or alternates

☑ Placed variables in a Venn diagram

☑ Compiled/located citations with abstracts

☑ Read abstracts and culled all irrelevant articles

☑ Assessed whether you need to dig deeper or focus your review

☑ Systematically logged your relevant readings

☑ Read and annotated each relevant article

☑ Sorted and organized your annotations

☑ Developed a potential outline for your literature review

☑ Written purposefully

☑ Used the literature to back up your arguments

☑ Adopted an appropriate style and tone

☑ Gotten plenty of feedback

☑ Redrafted (maybe several times)

10-Point Manuscript Checklist to Ensure High-Quality Journal Submissions 

Preparing your manuscript for journal submission is possibly one of the most nerve-wracking steps in a researcher’s publishing journey. This is also the stage where most researchers make errors that can define the fate of their manuscript. To paraphrase renowned German physicist Werner Heisenberg, an expert is someone who knows some of the worst mistakes that can be made and how to avoid them. So we’ve learnt from the missteps of countless researchers and created an easy 10-point manuscript checklist for successful submissions. If you’re ready to submit your manuscript to a journal, be sure to tick these checks off your list before you proceed! 

1. Manuscript format

The first item on the manuscript checklist is formatting. Most journals have strict guidelines on the article format, so be sure to double check the layout, font type or size, spacing, margins, numbering and file type (Word/PDF/LaTeX) are aligned to your journal requirements. Also check if you meet the recommended word count for key elements like the Abstract or the Title. You should also run through the citations and references to ensure all in-text citations are included in references, which should be consistently styled and formatted appropriately.  

2. Manuscript structure

Ensure your manuscript is complete from title to structure, acknowledgements to footnotes. Each section has a specific objective, so ensure that there is no major repetition of information and data flows cohesively. Apart from following the recommended IMRAD structure for research articles, keep an eye on and refine your article structure by checking the appendix, footnotes, and other sections of your paper when using this manuscript checklist. 

3. Language and flow

A well-written manuscript has a higher chance of impressing journal editors and reviewers, and in turn your chance of acceptance. Improve your writing by avoiding jargon and grandiose language, keep the sentences simple and uncomplicated, focus on logic and flow to improve readability, check and correct spelling and grammar errors that could be misleading. Using this manuscript checklist to tick off all these points will help you deliver a polished piece that showcases your research effectively. 

4. Graphics

Present your scientific data effectively in clear, well-structured, detailed tables and figures. Ensure the tables and figures are clear and legible and don’t repeat information in text. Don’t make these visuals too long, instead include additional information in the appendix. Check and clean up your table titles, figures and graph legends, and image captions as this is something editors will check for. Finally, share these in the correct file type or format as requested by your target journal. 

5. Facts and details

The most common error is inconsistencies in the facts and details provided in your manuscript. So do a thorough check to ensure that the data and calculations or equations in your work are accurate. You should also check for consistency in how the numbers, symbols, units of measurement, citations and references are presented in your manuscript.  

6. Author information

Determining and being clear about the authors and the roles they play in writing a research paper is key, for example corresponding author, lead author, co-author, etc. At the time of journal submission, researchers are required to share all the relevant details about the authors, including their full names, designations, contribution made, and the full contact details of the corresponding author.  

7. Attribution and acknowledgement

You manuscript should acknowledge all sources of support received on the research project. If the study involves patients/subjects, you would need to submit proof of consent forms. While you need to ensure you properly quote or cite text taken from previously published papers, you will need to have written approvals if reproducing graphics or copyright material. Failure to correctly attribute or acknowledge these sources of information is considered an ethical violation.  

8. Conflict of interest

All types of submission to a journal will require a conflict of interest declaration, either mentioning conflicts of interest or confirming that there are none. Conflicts of interest in research are when competing financial, professional connections, or personal values and views can potentially impact a researcher’s objectivity. It’s mandatory to for authors to follow journal guidelines and declare all potential conflicts to ensure there smooth processing of a manuscript. 

9. Ethical compliance

Adhering to ethical guidelines is critical to ensure that your work is authentic, unbiased, free of errors, and something that can be trusted. Ethical compliance keeps researchers accountable and ensures there is no misconduct in conducting research or in the use of funds. Some of the important ethical declarations at the time of submission include statements of ethical approval from relevant boards or committees, disclosure of simultaneous submissions, and conflict of interest statements. 

10. Cover letter

Remember to round off your manuscript submission with a detailed, well-structured cover letter that showcases your findings. Your cover letter should include author information, highlight the impact and significance of your work, detail supplementary materials being submitted, disclose relevant ethical disclosures, and state why the journal should publish your work.  

If this seems like a lot, or you’re unsure how to get it right, turn to Paperpal for an in-depth check before you submit. Its robust AI engine evaluates your work, highlights problem areas based on key features all journal editors check for, and offers suggestions that help you improve your manuscript. Want to simplify and accelerate your submission process? See how Paperpal can help!  

Related Reads:

• Confusing Elements of a Research Paper That Trip Up Most Academics
• Good Publication Practices: 6 Essential Steps for Publication Success
• Top 5 Ethical Considerations in Research
• How to Find the Right Academic Editor and Proofreading Partner

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Research Paper Checklist

Ai generator.

When we think of research papers , we think of academic papers that students are tasked to write in order for them to pass the course or at least to pass the subject. A requirement for students when doing their research paper apart from a good research paper outline is a guide or a checklist. However, when we think of research papers, we rarely associate them with a checklist. The checklist helps students understand the positive and negative sides of their research paper. Many students, whether they are in high school or college, know that research papers are a must. What they may not associate the research paper with is the checklist that their professors often give out in order for the students to be guided. You may be wondering why a checklist is still necessary when writing a research paper. To get the answers you need, let’s take a look at the examples of a research paper checklist.

10+ Research Paper Checklist Examples

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11. Research Paper Grading Checklist

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What Is a Research Paper Checklist?

A checklist is a detailed tool that a variety of people may use for different reasons. It can be used by students, teachers, and even businessmen and women. As for a research paper checklist , we know that a research paper checklist is a kind of detailed tool that researchers use in order to coordinate their paper with what is being written in the checklist. It is also a helpful tool that helps guide the researchers to what they should be writing about. Consider a research paper checklist like that of an outline or a chapter outline , except the only difference is that you need only to tick the box when you are able to complete the assigned task. In addition to that, the importance of using a research paper checklist is it guides you to what you should be doing first to guide you to what should be done and how to do it. What to add and what to not forget.

How to Write a Research Paper Checklist

Getting ready to write your research paper? You would of course need a checklist to help you with that. We know that writing a research paper checklist from scratch may be a challenge especially if it is your first time writing a checklist. But not to worry, here are some steps to help you write out your research paper checklist.

1. Divide Your List Into Equal Parts

Dividing your drafted list into equal parts to make your checklist is one good thing for you to do. The list that is necessary for your checklist can be made into smaller parts for you to focus on. For example, you may place the first one as a title. The next would be the research outline format , etc.

2. Add the Information Needed

The information or the details that are needed based on the equal parts above would look like a few phrases or a single sentence, explaining what the researcher would need to do through the checklist.

3. Make Sure the Information Is Clear

Information that you write must at least be obvious or clear for the researcher to be doing. However, if you are going to be writing your own checklist, make sure you understand what you are placing and what you are supposed to be doing. As much as possible, use jargon that everyone can understand if you are working as a group and using the same checklist.

4. Place a Space for It to Be Ticked

Spaces are necessary when you make your checklist. To be able to tick the list, you have to make sure that you do not have to redo the same item or the same thing you listed again. It would also help you save time. Of course, it may depend on how you are going to do it. You may tick the box or simply crush out the entire sentence as a way to show it is done.

5. Proofread Your Checklist

Before you are able to use your research paper checklist, make sure to proofread them. Proofreading your checklist means you want to see if everything you would need is already present in the research paper checklist. It means that you want to see if there are things you may think about that you can use for your research paper checklist.

What is a research paper checklist?

A research paper checklist is a tool used that helps or caters to the things you need in order to make your research paper. The checklist consists of general to specific types of information that would help you complete your research paper.

How do you write a research paper checklist?

There are a lot of ways to write a research paper checklist. The most common thing you can do is to write down the necessary list and divide them into sections. These sections help by lessening the confusion and making it easier for you to do your entire checklist.

How can a research paper checklist help?

Research paper checklists help by giving you a list of the things you need to do in order to make your research paper a success.

Research papers are not an easy thing to do. There is no such thing as a perfect research paper that is being written out in a single sitting. This is why a lot of teachers or professors suggest or advise their students to make a research paper checklist. The checklist helps by guiding them in order to make the flow of writing easier.

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Checklist: Writing a Thesis or Dissertation

Published on August 30, 2022 by Shona McCombes . Revised on July 18, 2023.

Your thesis or dissertation is probably the longest academic text you’ve ever had to write, and there are a lot of different elements to keep in mind.

Use this simple checklist to make sure you’ve included all the essentials and submit your dissertation with confidence.

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Table of contents

Other interesting articles, checklist: dissertation.

My title page includes all information required by my university.

I have included acknowledgements thanking those who helped me.

My abstract provides a concise summary of the dissertation, giving the reader a clear idea of my key results or arguments.

I have created a table of contents to help the reader navigate my dissertation. It includes all chapter titles, but excludes the title page, acknowledgements, and abstract.

My introduction leads into my topic in an engaging way and shows the relevance of my research.

My introduction clearly defines the focus of my research, stating my research questions and research objectives .

My introduction includes an overview of the dissertation’s structure (reading guide).

I have conducted a literature review in which I (1) critically engage with sources, evaluating the strengths and weaknesses of existing research, (2) discuss patterns, themes, and debates in the literature, and (3) address a gap or show how my research contributes to existing research.

I have clearly outlined the theoretical framework of my research, explaining the theories and models that support my approach.

I have thoroughly described my methodology , explaining how I collected data and analyzed data.

I have concisely and objectively reported all relevant results .

I have (1) evaluated and interpreted the meaning of the results and (2) acknowledged any important limitations of the results in my discussion .

I have clearly stated the answer to my main research question in the conclusion .

I have clearly explained the implications of my conclusion, emphasizing what new insight my research has contributed.

I have provided relevant recommendations for further research or practice.

If relevant, I have included appendices with supplemental information.

I have included an in-text citation every time I use words, ideas, or information from a source.

I have listed every source in a reference list at the end of my dissertation.

I have consistently followed the rules of my chosen citation style .

I have followed all formatting guidelines provided by my university.

Congratulations!

The end is in sight—your dissertation is nearly ready to submit! Make sure it's perfectly polished with the help of a Scribbr editor.

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If you want to know more about AI for academic writing, AI tools, or research bias, make sure to check out some of our other articles with explanations and examples or go directly to our tools!

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McCombes, S. (2023, July 18). Checklist: Writing a Thesis or Dissertation. Scribbr. Retrieved September 3, 2024, from https://www.scribbr.com/dissertation/dissertation-checklist/

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19+ SAMPLE Research Paper Checklist in PDF

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Step 1: prepare the format, step 2: enumerate the requirements, step 3: include a time table, step 4: have the research paper checklist proofread, share this post on your network, you may also like these articles, 71+ sample inspection checklists in pdf | ms word | google docs | apple pages.

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• Published: 31 August 2024

Knowledge mapping and evolution of research on older adults’ technology acceptance: a bibliometric study from 2013 to 2023

• Xianru Shang   ORCID: orcid.org/0009-0000-8906-3216 1 ,
• Zijian Liu 1 ,
• Chen Gong 1 ,
• Zhigang Hu 1 ,
• Yuexuan Wu 1 &
• Chengliang Wang   ORCID: orcid.org/0000-0003-2208-3508 2  

Humanities and Social Sciences Communications volume  11 , Article number:  1115 ( 2024 ) Cite this article

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• Science, technology and society

The rapid expansion of information technology and the intensification of population aging are two prominent features of contemporary societal development. Investigating older adults’ acceptance and use of technology is key to facilitating their integration into an information-driven society. Given this context, the technology acceptance of older adults has emerged as a prioritized research topic, attracting widespread attention in the academic community. However, existing research remains fragmented and lacks a systematic framework. To address this gap, we employed bibliometric methods, utilizing the Web of Science Core Collection to conduct a comprehensive review of literature on older adults’ technology acceptance from 2013 to 2023. Utilizing VOSviewer and CiteSpace for data assessment and visualization, we created knowledge mappings of research on older adults’ technology acceptance. Our study employed multidimensional methods such as co-occurrence analysis, clustering, and burst analysis to: (1) reveal research dynamics, key journals, and domains in this field; (2) identify leading countries, their collaborative networks, and core research institutions and authors; (3) recognize the foundational knowledge system centered on theoretical model deepening, emerging technology applications, and research methods and evaluation, uncovering seminal literature and observing a shift from early theoretical and influential factor analyses to empirical studies focusing on individual factors and emerging technologies; (4) moreover, current research hotspots are primarily in the areas of factors influencing technology adoption, human-robot interaction experiences, mobile health management, and aging-in-place technology, highlighting the evolutionary context and quality distribution of research themes. Finally, we recommend that future research should deeply explore improvements in theoretical models, long-term usage, and user experience evaluation. Overall, this study presents a clear framework of existing research in the field of older adults’ technology acceptance, providing an important reference for future theoretical exploration and innovative applications.

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Introduction.

In contemporary society, the rapid development of information technology has been intricately intertwined with the intensifying trend of population aging. According to the latest United Nations forecast, by 2050, the global population aged 65 and above is expected to reach 1.6 billion, representing about 16% of the total global population (UN 2023 ). Given the significant challenges of global aging, there is increasing evidence that emerging technologies have significant potential to maintain health and independence for older adults in their home and healthcare environments (Barnard et al. 2013 ; Soar 2010 ; Vancea and Solé-Casals 2016 ). This includes, but is not limited to, enhancing residential safety with smart home technologies (Touqeer et al. 2021 ; Wang et al. 2022 ), improving living independence through wearable technologies (Perez et al. 2023 ), and increasing medical accessibility via telehealth services (Kruse et al. 2020 ). Technological innovations are redefining the lifestyles of older adults, encouraging a shift from passive to active participation (González et al. 2012 ; Mostaghel 2016 ). Nevertheless, the effective application and dissemination of technology still depends on user acceptance and usage intentions (Naseri et al. 2023 ; Wang et al. 2023a ; Xia et al. 2024 ; Yu et al. 2023 ). Particularly, older adults face numerous challenges in accepting and using new technologies. These challenges include not only physical and cognitive limitations but also a lack of technological experience, along with the influences of social and economic factors (Valk et al. 2018 ; Wilson et al. 2021 ).

User acceptance of technology is a significant focus within information systems (IS) research (Dai et al. 2024 ), with several models developed to explain and predict user behavior towards technology usage, including the Technology Acceptance Model (TAM) (Davis 1989 ), TAM2, TAM3, and the Unified Theory of Acceptance and Use of Technology (UTAUT) (Venkatesh et al. 2003 ). Older adults, as a group with unique needs, exhibit different behavioral patterns during technology acceptance than other user groups, and these uniquenesses include changes in cognitive abilities, as well as motivations, attitudes, and perceptions of the use of new technologies (Chen and Chan 2011 ). The continual expansion of technology introduces considerable challenges for older adults, rendering the understanding of their technology acceptance a research priority. Thus, conducting in-depth research into older adults’ acceptance of technology is critically important for enhancing their integration into the information society and improving their quality of life through technological advancements.

Reviewing relevant literature to identify research gaps helps further solidify the theoretical foundation of the research topic. However, many existing literature reviews primarily focus on the factors influencing older adults’ acceptance or intentions to use technology. For instance, Ma et al. ( 2021 ) conducted a comprehensive analysis of the determinants of older adults’ behavioral intentions to use technology; Liu et al. ( 2022 ) categorized key variables in studies of older adults’ technology acceptance, noting a shift in focus towards social and emotional factors; Yap et al. ( 2022 ) identified seven categories of antecedents affecting older adults’ use of technology from an analysis of 26 articles, including technological, psychological, social, personal, cost, behavioral, and environmental factors; Schroeder et al. ( 2023 ) extracted 119 influencing factors from 59 articles and further categorized these into six themes covering demographics, health status, and emotional awareness. Additionally, some studies focus on the application of specific technologies, such as Ferguson et al. ( 2021 ), who explored barriers and facilitators to older adults using wearable devices for heart monitoring, and He et al. ( 2022 ) and Baer et al. ( 2022 ), who each conducted in-depth investigations into the acceptance of social assistive robots and mobile nutrition and fitness apps, respectively. In summary, current literature reviews on older adults’ technology acceptance exhibit certain limitations. Due to the interdisciplinary nature and complex knowledge structure of this field, traditional literature reviews often rely on qualitative analysis, based on literature analysis and periodic summaries, which lack sufficient objectivity and comprehensiveness. Additionally, systematic research is relatively limited, lacking a macroscopic description of the research trajectory from a holistic perspective. Over the past decade, research on older adults’ technology acceptance has experienced rapid growth, with a significant increase in literature, necessitating the adoption of new methods to review and examine the developmental trends in this field (Chen 2006 ; Van Eck and Waltman 2010 ). Bibliometric analysis, as an effective quantitative research method, analyzes published literature through visualization, offering a viable approach to extracting patterns and insights from a large volume of papers, and has been widely applied in numerous scientific research fields (Achuthan et al. 2023 ; Liu and Duffy 2023 ). Therefore, this study will employ bibliometric methods to systematically analyze research articles related to older adults’ technology acceptance published in the Web of Science Core Collection from 2013 to 2023, aiming to understand the core issues and evolutionary trends in the field, and to provide valuable references for future related research. Specifically, this study aims to explore and answer the following questions:

RQ1: What are the research dynamics in the field of older adults’ technology acceptance over the past decade? What are the main academic journals and fields that publish studies related to older adults’ technology acceptance?

RQ2: How is the productivity in older adults’ technology acceptance research distributed among countries, institutions, and authors?

RQ3: What are the knowledge base and seminal literature in older adults’ technology acceptance research? How has the research theme progressed?

RQ4: What are the current hot topics and their evolutionary trajectories in older adults’ technology acceptance research? How is the quality of research distributed?

Methodology and materials

Research method.

In recent years, bibliometrics has become one of the crucial methods for analyzing literature reviews and is widely used in disciplinary and industrial intelligence analysis (Jing et al. 2023 ; Lin and Yu 2024a ; Wang et al. 2024a ; Xu et al. 2021 ). Bibliometric software facilitates the visualization analysis of extensive literature data, intuitively displaying the network relationships and evolutionary processes between knowledge units, and revealing the underlying knowledge structure and potential information (Chen et al. 2024 ; López-Robles et al. 2018 ; Wang et al. 2024c ). This method provides new insights into the current status and trends of specific research areas, along with quantitative evidence, thereby enhancing the objectivity and scientific validity of the research conclusions (Chen et al. 2023 ; Geng et al. 2024 ). VOSviewer and CiteSpace are two widely used bibliometric software tools in academia (Pan et al. 2018 ), recognized for their robust functionalities based on the JAVA platform. Although each has its unique features, combining these two software tools effectively constructs mapping relationships between literature knowledge units and clearly displays the macrostructure of the knowledge domains. Particularly, VOSviewer, with its excellent graphical representation capabilities, serves as an ideal tool for handling large datasets and precisely identifying the focal points and hotspots of research topics. Therefore, this study utilizes VOSviewer (version 1.6.19) and CiteSpace (version 6.1.R6), combined with in-depth literature analysis, to comprehensively examine and interpret the research theme of older adults’ technology acceptance through an integrated application of quantitative and qualitative methods.

Data source

Web of Science is a comprehensively recognized database in academia, featuring literature that has undergone rigorous peer review and editorial scrutiny (Lin and Yu 2024b ; Mongeon and Paul-Hus 2016 ; Pranckutė 2021 ). This study utilizes the Web of Science Core Collection as its data source, specifically including three major citation indices: Science Citation Index Expanded (SCIE), Social Sciences Citation Index (SSCI), and Arts & Humanities Citation Index (A&HCI). These indices encompass high-quality research literature in the fields of science, social sciences, and arts and humanities, ensuring the comprehensiveness and reliability of the data. We combined “older adults” with “technology acceptance” through thematic search, with the specific search strategy being: TS = (elder OR elderly OR aging OR ageing OR senile OR senior OR old people OR “older adult*”) AND TS = (“technology acceptance” OR “user acceptance” OR “consumer acceptance”). The time span of literature search is from 2013 to 2023, with the types limited to “Article” and “Review” and the language to “English”. Additionally, the search was completed by October 27, 2023, to avoid data discrepancies caused by database updates. The initial search yielded 764 journal articles. Given that searches often retrieve articles that are superficially relevant but actually non-compliant, manual screening post-search was essential to ensure the relevance of the literature (Chen et al. 2024 ). Through manual screening, articles significantly deviating from the research theme were eliminated and rigorously reviewed. Ultimately, this study obtained 500 valid sample articles from the Web of Science Core Collection. The complete PRISMA screening process is illustrated in Fig. 1 .

Presentation of the data culling process in detail.

Data standardization

Raw data exported from databases often contain multiple expressions of the same terminology (Nguyen and Hallinger 2020 ). To ensure the accuracy and consistency of data, it is necessary to standardize the raw data (Strotmann and Zhao 2012 ). This study follows the data standardization process proposed by Taskin and Al ( 2019 ), mainly executing the following operations:

(1) Standardization of author and institution names is conducted to address different name expressions for the same author. For instance, “Chan, Alan Hoi Shou” and “Chan, Alan H. S.” are considered the same author, and distinct authors with the same name are differentiated by adding identifiers. Diverse forms of institutional names are unified to address variations caused by name changes or abbreviations, such as standardizing “FRANKFURT UNIV APPL SCI” and “Frankfurt University of Applied Sciences,” as well as “Chinese University of Hong Kong” and “University of Hong Kong” to consistent names.

(2) Different expressions of journal names are unified. For example, “International Journal of Human-Computer Interaction” and “Int J Hum Comput Interact” are standardized to a single name. This ensures consistency in journal names and prevents misclassification of literature due to differing journal names. Additionally, it involves checking if the journals have undergone name changes in the past decade to prevent any impact on the analysis due to such changes.

(3) Keywords data are cleansed by removing words that do not directly pertain to specific research content (e.g., people, review), merging synonyms (e.g., “UX” and “User Experience,” “aging-in-place” and “aging in place”), and standardizing plural forms of keywords (e.g., “assistive technologies” and “assistive technology,” “social robots” and “social robot”). This reduces redundant information in knowledge mapping.

Bibliometric results and analysis

Distribution power (rq1), literature descriptive statistical analysis.

Table 1 presents a detailed descriptive statistical overview of the literature in the field of older adults’ technology acceptance. After deduplication using the CiteSpace software, this study confirmed a valid sample size of 500 articles. Authored by 1839 researchers, the documents encompass 792 research institutions across 54 countries and are published in 217 different academic journals. As of the search cutoff date, these articles have accumulated 13,829 citations, with an annual average of 1156 citations, and an average of 27.66 citations per article. The h-index, a composite metric of quantity and quality of scientific output (Kamrani et al. 2021 ), reached 60 in this study.

Trends in publications and disciplinary distribution

The number of publications and citations are significant indicators of the research field’s development, reflecting its continuity, attention, and impact (Ale Ebrahim et al. 2014 ). The ranking of annual publications and citations in the field of older adults’ technology acceptance studies is presented chronologically in Fig. 2A . The figure shows a clear upward trend in the amount of literature in this field. Between 2013 and 2017, the number of publications increased slowly and decreased in 2018. However, in 2019, the number of publications increased rapidly to 52 and reached a peak of 108 in 2022, which is 6.75 times higher than in 2013. In 2022, the frequency of document citations reached its highest point with 3466 citations, reflecting the widespread recognition and citation of research in this field. Moreover, the curve of the annual number of publications fits a quadratic function, with a goodness-of-fit R 2 of 0.9661, indicating that the number of future publications is expected to increase even more rapidly.

A Trends in trends in annual publications and citations (2013–2023). B Overlay analysis of the distribution of discipline fields.

Figure 2B shows that research on older adults’ technology acceptance involves the integration of multidisciplinary knowledge. According to Web of Science Categories, these 500 articles are distributed across 85 different disciplines. We have tabulated the top ten disciplines by publication volume (Table 2 ), which include Medical Informatics (75 articles, 15.00%), Health Care Sciences & Services (71 articles, 14.20%), Gerontology (61 articles, 12.20%), Public Environmental & Occupational Health (57 articles, 11.40%), and Geriatrics & Gerontology (52 articles, 10.40%), among others. The high output in these disciplines reflects the concentrated global academic interest in this comprehensive research topic. Additionally, interdisciplinary research approaches provide diverse perspectives and a solid theoretical foundation for studies on older adults’ technology acceptance, also paving the way for new research directions.

Knowledge flow analysis

A dual-map overlay is a CiteSpace map superimposed on top of a base map, which shows the interrelationships between journals in different domains, representing the publication and citation activities in each domain (Chen and Leydesdorff 2014 ). The overlay map reveals the link between the citing domain (on the left side) and the cited domain (on the right side), reflecting the knowledge flow of the discipline at the journal level (Leydesdorff and Rafols 2012 ). We utilize the in-built Z-score algorithm of the software to cluster the graph, as shown in Fig. 3 .

The left side shows the citing journal, and the right side shows the cited journal.

Figure 3 shows the distribution of citing journals clusters for older adults’ technology acceptance on the left side, while the right side refers to the main cited journals clusters. Two knowledge flow citation trajectories were obtained; they are presented by the color of the cited regions, and the thickness of these trajectories is proportional to the Z-score scaled frequency of citations (Chen et al. 2014 ). Within the cited regions, the most popular fields with the most records covered are “HEALTH, NURSING, MEDICINE” and “PSYCHOLOGY, EDUCATION, SOCIAL”, and the elliptical aspect ratio of these two fields stands out. Fields have prominent elliptical aspect ratios, highlighting their significant influence on older adults’ technology acceptance research. Additionally, the major citation trajectories originate in these two areas and progress to the frontier research area of “PSYCHOLOGY, EDUCATION, HEALTH”. It is worth noting that the citation trajectory from “PSYCHOLOGY, EDUCATION, SOCIAL” has a significant Z-value (z = 6.81), emphasizing the significance and impact of this development path. In the future, “MATHEMATICS, SYSTEMS, MATHEMATICAL”, “MOLECULAR, BIOLOGY, IMMUNOLOGY”, and “NEUROLOGY, SPORTS, OPHTHALMOLOGY” may become emerging fields. The fields of “MEDICINE, MEDICAL, CLINICAL” may be emerging areas of cutting-edge research.

Main research journals analysis

Table 3 provides statistics for the top ten journals by publication volume in the field of older adults’ technology acceptance. Together, these journals have published 137 articles, accounting for 27.40% of the total publications, indicating that there is no highly concentrated core group of journals in this field, with publications being relatively dispersed. Notably, Computers in Human Behavior , Journal of Medical Internet Research , and International Journal of Human-Computer Interaction each lead with 15 publications. In terms of citation metrics, International Journal of Medical Informatics and Computers in Human Behavior stand out significantly, with the former accumulating a total of 1,904 citations, averaging 211.56 citations per article, and the latter totaling 1,449 citations, with an average of 96.60 citations per article. These figures emphasize the academic authority and widespread impact of these journals within the research field.

Research power (RQ2)

Countries and collaborations analysis.

The analysis revealed the global research pattern for country distribution and collaboration (Chen et al. 2019 ). Figure 4A shows the network of national collaborations on older adults’ technology acceptance research. The size of the bubbles represents the amount of publications in each country, while the thickness of the connecting lines expresses the closeness of the collaboration among countries. Generally, this research subject has received extensive international attention, with China and the USA publishing far more than any other countries. China has established notable research collaborations with the USA, UK and Malaysia in this field, while other countries have collaborations, but the closeness is relatively low and scattered. Figure 4B shows the annual publication volume dynamics of the top ten countries in terms of total publications. Since 2017, China has consistently increased its annual publications, while the USA has remained relatively stable. In 2019, the volume of publications in each country increased significantly, this was largely due to the global outbreak of the COVID-19 pandemic, which has led to increased reliance on information technology among the elderly for medical consultations, online socialization, and health management (Sinha et al. 2021 ). This phenomenon has led to research advances in technology acceptance among older adults in various countries. Table 4 shows that the top ten countries account for 93.20% of the total cumulative number of publications, with each country having published more than 20 papers. Among these ten countries, all of them except China are developed countries, indicating that the research field of older adults’ technology acceptance has received general attention from developed countries. Currently, China and the USA were the leading countries in terms of publications with 111 and 104 respectively, accounting for 22.20% and 20.80%. The UK, Germany, Italy, and the Netherlands also made significant contributions. The USA and China ranked first and second in terms of the number of citations, while the Netherlands had the highest average citations, indicating the high impact and quality of its research. The UK has shown outstanding performance in international cooperation, while the USA highlights its significant academic influence in this field with the highest h-index value.

A National collaboration network. B Annual volume of publications in the top 10 countries.

Institutions and authors analysis

Analyzing the number of publications and citations can reveal an institution’s or author’s research strength and influence in a particular research area (Kwiek 2021 ). Tables 5 and 6 show the statistics of the institutions and authors whose publication counts are in the top ten, respectively. As shown in Table 5 , higher education institutions hold the main position in this research field. Among the top ten institutions, City University of Hong Kong and The University of Hong Kong from China lead with 14 and 9 publications, respectively. City University of Hong Kong has the highest h-index, highlighting its significant influence in the field. It is worth noting that Tilburg University in the Netherlands is not among the top five in terms of publications, but the high average citation count (130.14) of its literature demonstrates the high quality of its research.

After analyzing the authors’ output using Price’s Law (Redner 1998 ), the highest number of publications among the authors counted ( n  = 10) defines a publication threshold of 3 for core authors in this research area. As a result of quantitative screening, a total of 63 core authors were identified. Table 6 shows that Chen from Zhejiang University, China, Ziefle from RWTH Aachen University, Germany, and Rogers from Macquarie University, Australia, were the top three authors in terms of the number of publications, with 10, 9, and 8 articles, respectively. In terms of average citation rate, Peek and Wouters, both scholars from the Netherlands, have significantly higher rates than other scholars, with 183.2 and 152.67 respectively. This suggests that their research is of high quality and widely recognized. Additionally, Chen and Rogers have high h-indices in this field.

Knowledge base and theme progress (RQ3)

Research knowledge base.

Co-citation relationships occur when two documents are cited together (Zhang and Zhu 2022 ). Co-citation mapping uses references as nodes to represent the knowledge base of a subject area (Min et al. 2021). Figure 5A illustrates co-occurrence mapping in older adults’ technology acceptance research, where larger nodes signify higher co-citation frequencies. Co-citation cluster analysis can be used to explore knowledge structure and research boundaries (Hota et al. 2020 ; Shiau et al. 2023 ). The co-citation clustering mapping of older adults’ technology acceptance research literature (Fig. 5B ) shows that the Q value of the clustering result is 0.8129 (>0.3), and the average value of the weight S is 0.9391 (>0.7), indicating that the clusters are uniformly distributed with a significant and credible structure. This further proves that the boundaries of the research field are clear and there is significant differentiation in the field. The figure features 18 cluster labels, each associated with thematic color blocks corresponding to different time slices. Highlighted emerging research themes include #2 Smart Home Technology, #7 Social Live, and #10 Customer Service. Furthermore, the clustering labels extracted are primarily classified into three categories: theoretical model deepening, emerging technology applications, research methods and evaluation, as detailed in Table 7 .

A Co-citation analysis of references. B Clustering network analysis of references.

Seminal literature analysis

The top ten nodes in terms of co-citation frequency were selected for further analysis. Table 8 displays the corresponding node information. Studies were categorized into four main groups based on content analysis. (1) Research focusing on specific technology usage by older adults includes studies by Peek et al. ( 2014 ), Ma et al. ( 2016 ), Hoque and Sorwar ( 2017 ), and Li et al. ( 2019 ), who investigated the factors influencing the use of e-technology, smartphones, mHealth, and smart wearables, respectively. (2) Concerning the development of theoretical models of technology acceptance, Chen and Chan ( 2014 ) introduced the Senior Technology Acceptance Model (STAM), and Macedo ( 2017 ) analyzed the predictive power of UTAUT2 in explaining older adults’ intentional behaviors and information technology usage. (3) In exploring older adults’ information technology adoption and behavior, Lee and Coughlin ( 2015 ) emphasized that the adoption of technology by older adults is a multifactorial process that includes performance, price, value, usability, affordability, accessibility, technical support, social support, emotion, independence, experience, and confidence. Yusif et al. ( 2016 ) conducted a literature review examining the key barriers affecting older adults’ adoption of assistive technology, including factors such as privacy, trust, functionality/added value, cost, and stigma. (4) From the perspective of research into older adults’ technology acceptance, Mitzner et al. ( 2019 ) assessed the long-term usage of computer systems designed for the elderly, whereas Guner and Acarturk ( 2020 ) compared information technology usage and acceptance between older and younger adults. The breadth and prevalence of this literature make it a vital reference for researchers in the field, also providing new perspectives and inspiration for future research directions.

Research thematic progress

Burst citation is a node of literature that guides the sudden change in dosage, which usually represents a prominent development or major change in a particular field, with innovative and forward-looking qualities. By analyzing the emergent literature, it is often easy to understand the dynamics of the subject area, mapping the emerging thematic change (Chen et al. 2022 ). Figure 6 shows the burst citation mapping in the field of older adults’ technology acceptance research, with burst citations represented by red nodes (Fig. 6A ). For the ten papers with the highest burst intensity (Fig. 6B ), this study will conduct further analysis in conjunction with literature review.

A Burst detection of co-citation. B The top 10 references with the strongest citation bursts.

As shown in Fig. 6 , Mitzner et al. ( 2010 ) broke the stereotype that older adults are fearful of technology, found that they actually have positive attitudes toward technology, and emphasized the centrality of ease of use and usefulness in the process of technology acceptance. This finding provides an important foundation for subsequent research. During the same period, Wagner et al. ( 2010 ) conducted theory-deepening and applied research on technology acceptance among older adults. The research focused on older adults’ interactions with computers from the perspective of Social Cognitive Theory (SCT). This expanded the understanding of technology acceptance, particularly regarding the relationship between behavior, environment, and other SCT elements. In addition, Pan and Jordan-Marsh ( 2010 ) extended the TAM to examine the interactions among predictors of perceived usefulness, perceived ease of use, subjective norm, and convenience conditions when older adults use the Internet, taking into account the moderating roles of gender and age. Heerink et al. ( 2010 ) adapted and extended the UTAUT, constructed a technology acceptance model specifically designed for older users’ acceptance of assistive social agents, and validated it using controlled experiments and longitudinal data, explaining intention to use by combining functional assessment and social interaction variables.

Then the research theme shifted to an in-depth analysis of the factors influencing technology acceptance among older adults. Two papers with high burst strengths emerged during this period: Peek et al. ( 2014 ) (Strength = 12.04), Chen and Chan ( 2014 ) (Strength = 9.81). Through a systematic literature review and empirical study, Peek STM and Chen K, among others, identified multidimensional factors that influence older adults’ technology acceptance. Peek et al. ( 2014 ) analyzed literature on the acceptance of in-home care technology among older adults and identified six factors that influence their acceptance: concerns about technology, expected benefits, technology needs, technology alternatives, social influences, and older adult characteristics, with a focus on differences between pre- and post-implementation factors. Chen and Chan ( 2014 ) constructed the STAM by administering a questionnaire to 1012 older adults and adding eight important factors, including technology anxiety, self-efficacy, cognitive ability, and physical function, based on the TAM. This enriches the theoretical foundation of the field. In addition, Braun ( 2013 ) highlighted the role of perceived usefulness, trust in social networks, and frequency of Internet use in older adults’ use of social networks, while ease of use and social pressure were not significant influences. These findings contribute to the study of older adults’ technology acceptance within specific technology application domains.

Recent research has focused on empirical studies of personal factors and emerging technologies. Ma et al. ( 2016 ) identified key personal factors affecting smartphone acceptance among older adults through structured questionnaires and face-to-face interviews with 120 participants. The study found that cost, self-satisfaction, and convenience were important factors influencing perceived usefulness and ease of use. This study offers empirical evidence to comprehend the main factors that drive smartphone acceptance among Chinese older adults. Additionally, Yusif et al. ( 2016 ) presented an overview of the obstacles that hinder older adults’ acceptance of assistive technologies, focusing on privacy, trust, and functionality.

In summary, research on older adults’ technology acceptance has shifted from early theoretical deepening and analysis of influencing factors to empirical studies in the areas of personal factors and emerging technologies, which have greatly enriched the theoretical basis of older adults’ technology acceptance and provided practical guidance for the design of emerging technology products.

Research hotspots, evolutionary trends, and quality distribution (RQ4)

Core keywords analysis.

Keywords concise the main idea and core of the literature, and are a refined summary of the research content (Huang et al. 2021 ). In CiteSpace, nodes with a centrality value greater than 0.1 are considered to be critical nodes. Analyzing keywords with high frequency and centrality helps to visualize the hot topics in the research field (Park et al. 2018 ). The merged keywords were imported into CiteSpace, and the top 10 keywords were counted and sorted by frequency and centrality respectively, as shown in Table 9 . The results show that the keyword “TAM” has the highest frequency (92), followed by “UTAUT” (24), which reflects that the in-depth study of the existing technology acceptance model and its theoretical expansion occupy a central position in research related to older adults’ technology acceptance. Furthermore, the terms ‘assistive technology’ and ‘virtual reality’ are both high-frequency and high-centrality terms (frequency = 17, centrality = 0.10), indicating that the research on assistive technology and virtual reality for older adults is the focus of current academic attention.

Research hotspots analysis

Using VOSviewer for keyword co-occurrence analysis organizes keywords into groups or clusters based on their intrinsic connections and frequencies, clearly highlighting the research field’s hot topics. The connectivity among keywords reveals correlations between different topics. To ensure accuracy, the analysis only considered the authors’ keywords. Subsequently, the keywords were filtered by setting the keyword frequency to 5 to obtain the keyword clustering map of the research on older adults’ technology acceptance research keyword clustering mapping (Fig. 7 ), combined with the keyword co-occurrence clustering network (Fig. 7A ) and the corresponding density situation (Fig. 7B ) to make a detailed analysis of the following four groups of clustered themes.

A Co-occurrence clustering network. B Keyword density.

Cluster #1—Research on the factors influencing technology adoption among older adults is a prominent topic, covering age, gender, self-efficacy, attitude, and and intention to use (Berkowsky et al. 2017 ; Wang et al. 2017 ). It also examined older adults’ attitudes towards and acceptance of digital health technologies (Ahmad and Mozelius, 2022 ). Moreover, the COVID-19 pandemic, significantly impacting older adults’ technology attitudes and usage, has underscored the study’s importance and urgency. Therefore, it is crucial to conduct in-depth studies on how older adults accept, adopt, and effectively use new technologies, to address their needs and help them overcome the digital divide within digital inclusion. This will improve their quality of life and healthcare experiences.

Cluster #2—Research focuses on how older adults interact with assistive technologies, especially assistive robots and health monitoring devices, emphasizing trust, usability, and user experience as crucial factors (Halim et al. 2022 ). Moreover, health monitoring technologies effectively track and manage health issues common in older adults, like dementia and mild cognitive impairment (Lussier et al. 2018 ; Piau et al. 2019 ). Interactive exercise games and virtual reality have been deployed to encourage more physical and cognitive engagement among older adults (Campo-Prieto et al. 2021 ). Personalized and innovative technology significantly enhances older adults’ participation, improving their health and well-being.

Cluster #3—Optimizing health management for older adults using mobile technology. With the development of mobile health (mHealth) and health information technology, mobile applications, smartphones, and smart wearable devices have become effective tools to help older users better manage chronic conditions, conduct real-time health monitoring, and even receive telehealth services (Dupuis and Tsotsos 2018 ; Olmedo-Aguirre et al. 2022 ; Kim et al. 2014 ). Additionally, these technologies can mitigate the problem of healthcare resource inequality, especially in developing countries. Older adults’ acceptance and use of these technologies are significantly influenced by their behavioral intentions, motivational factors, and self-management skills. These internal motivational factors, along with external factors, jointly affect older adults’ performance in health management and quality of life.

Cluster #4—Research on technology-assisted home care for older adults is gaining popularity. Environmentally assisted living enhances older adults’ independence and comfort at home, offering essential support and security. This has a crucial impact on promoting healthy aging (Friesen et al. 2016 ; Wahlroos et al. 2023 ). The smart home is a core application in this field, providing a range of solutions that facilitate independent living for the elderly in a highly integrated and user-friendly manner. This fulfills different dimensions of living and health needs (Majumder et al. 2017 ). Moreover, eHealth offers accurate and personalized health management and healthcare services for older adults (Delmastro et al. 2018 ), ensuring their needs are met at home. Research in this field often employs qualitative methods and structural equation modeling to fully understand older adults’ needs and experiences at home and analyze factors influencing technology adoption.

Evolutionary trends analysis

To gain a deeper understanding of the evolutionary trends in research hotspots within the field of older adults’ technology acceptance, we conducted a statistical analysis of the average appearance times of keywords, using CiteSpace to generate the time-zone evolution mapping (Fig. 8 ) and burst keywords. The time-zone mapping visually displays the evolution of keywords over time, intuitively reflecting the frequency and initial appearance of keywords in research, commonly used to identify trends in research topics (Jing et al. 2024a ; Kumar et al. 2021 ). Table 10 lists the top 15 keywords by burst strength, with the red sections indicating high-frequency citations and their burst strength in specific years. These burst keywords reveal the focus and trends of research themes over different periods (Kleinberg 2002 ). Combining insights from the time-zone mapping and burst keywords provides more objective and accurate research insights (Wang et al. 2023b ).

Reflecting the frequency and time of first appearance of keywords in the study.

An integrated analysis of Fig. 8 and Table 10 shows that early research on older adults’ technology acceptance primarily focused on factors such as perceived usefulness, ease of use, and attitudes towards information technology, including their use of computers and the internet (Pan and Jordan-Marsh 2010 ), as well as differences in technology use between older adults and other age groups (Guner and Acarturk 2020 ). Subsequently, the research focus expanded to improving the quality of life for older adults, exploring how technology can optimize health management and enhance the possibility of independent living, emphasizing the significant role of technology in improving the quality of life for the elderly. With ongoing technological advancements, recent research has shifted towards areas such as “virtual reality,” “telehealth,” and “human-robot interaction,” with a focus on the user experience of older adults (Halim et al. 2022 ). The appearance of keywords such as “physical activity” and “exercise” highlights the value of technology in promoting physical activity and health among older adults. This phase of research tends to make cutting-edge technology genuinely serve the practical needs of older adults, achieving its widespread application in daily life. Additionally, research has focused on expanding and quantifying theoretical models of older adults’ technology acceptance, involving keywords such as “perceived risk”, “validation” and “UTAUT”.

In summary, from 2013 to 2023, the field of older adults’ technology acceptance has evolved from initial explorations of influencing factors, to comprehensive enhancements in quality of life and health management, and further to the application and deepening of theoretical models and cutting-edge technologies. This research not only reflects the diversity and complexity of the field but also demonstrates a comprehensive and in-depth understanding of older adults’ interactions with technology across various life scenarios and needs.

Research quality distribution

To reveal the distribution of research quality in the field of older adults’ technology acceptance, a strategic diagram analysis is employed to calculate and illustrate the internal development and interrelationships among various research themes (Xie et al. 2020 ). The strategic diagram uses Centrality as the X-axis and Density as the Y-axis to divide into four quadrants, where the X-axis represents the strength of the connection between thematic clusters and other themes, with higher values indicating a central position in the research field; the Y-axis indicates the level of development within the thematic clusters, with higher values denoting a more mature and widely recognized field (Li and Zhou 2020 ).

Through cluster analysis and manual verification, this study categorized 61 core keywords (Frequency ≥5) into 11 thematic clusters. Subsequently, based on the keywords covered by each thematic cluster, the research themes and their directions for each cluster were summarized (Table 11 ), and the centrality and density coordinates for each cluster were precisely calculated (Table 12 ). Finally, a strategic diagram of the older adults’ technology acceptance research field was constructed (Fig. 9 ). Based on the distribution of thematic clusters across the quadrants in the strategic diagram, the structure and developmental trends of the field were interpreted.

Classification and visualization of theme clusters based on density and centrality.

As illustrated in Fig. 9 , (1) the theme clusters of #3 Usage Experience and #4 Assisted Living Technology are in the first quadrant, characterized by high centrality and density. Their internal cohesion and close links with other themes indicate their mature development, systematic research content or directions have been formed, and they have a significant influence on other themes. These themes play a central role in the field of older adults’ technology acceptance and have promising prospects. (2) The theme clusters of #6 Smart Devices, #9 Theoretical Models, and #10 Mobile Health Applications are in the second quadrant, with higher density but lower centrality. These themes have strong internal connections but weaker external links, indicating that these three themes have received widespread attention from researchers and have been the subject of related research, but more as self-contained systems and exhibit independence. Therefore, future research should further explore in-depth cooperation and cross-application with other themes. (3) The theme clusters of #7 Human-Robot Interaction, #8 Characteristics of the Elderly, and #11 Research Methods are in the third quadrant, with lower centrality and density. These themes are loosely connected internally and have weak links with others, indicating their developmental immaturity. Compared to other topics, they belong to the lower attention edge and niche themes, and there is a need for further investigation. (4) The theme clusters of #1 Digital Healthcare Technology, #2 Psychological Factors, and #5 Socio-Cultural Factors are located in the fourth quadrant, with high centrality but low density. Although closely associated with other research themes, the internal cohesion within these clusters is relatively weak. This suggests that while these themes are closely linked to other research areas, their own development remains underdeveloped, indicating a core immaturity. Nevertheless, these themes are crucial within the research domain of elderly technology acceptance and possess significant potential for future exploration.

Discussion on distribution power (RQ1)

Over the past decade, academic interest and influence in the area of older adults’ technology acceptance have significantly increased. This trend is evidenced by a quantitative analysis of publication and citation volumes, particularly noticeable in 2019 and 2022, where there was a substantial rise in both metrics. The rise is closely linked to the widespread adoption of emerging technologies such as smart homes, wearable devices, and telemedicine among older adults. While these technologies have enhanced their quality of life, they also pose numerous challenges, sparking extensive research into their acceptance, usage behaviors, and influencing factors among the older adults (Pirzada et al. 2022 ; Garcia Reyes et al. 2023 ). Furthermore, the COVID-19 pandemic led to a surge in technology demand among older adults, especially in areas like medical consultation, online socialization, and health management, further highlighting the importance and challenges of technology. Health risks and social isolation have compelled older adults to rely on technology for daily activities, accelerating its adoption and application within this demographic. This phenomenon has made technology acceptance a critical issue, driving societal and academic focus on the study of technology acceptance among older adults.

The flow of knowledge at the level of high-output disciplines and journals, along with the primary publishing outlets, indicates the highly interdisciplinary nature of research into older adults’ technology acceptance. This reflects the complexity and breadth of issues related to older adults’ technology acceptance, necessitating the integration of multidisciplinary knowledge and approaches. Currently, research is primarily focused on medical health and human-computer interaction, demonstrating academic interest in improving health and quality of life for older adults and addressing the urgent needs related to their interactions with technology. In the field of medical health, research aims to provide advanced and innovative healthcare technologies and services to meet the challenges of an aging population while improving the quality of life for older adults (Abdi et al. 2020 ; Wilson et al. 2021 ). In the field of human-computer interaction, research is focused on developing smarter and more user-friendly interaction models to meet the needs of older adults in the digital age, enabling them to actively participate in social activities and enjoy a higher quality of life (Sayago, 2019 ). These studies are crucial for addressing the challenges faced by aging societies, providing increased support and opportunities for the health, welfare, and social participation of older adults.

Discussion on research power (RQ2)

This study analyzes leading countries and collaboration networks, core institutions and authors, revealing the global research landscape and distribution of research strength in the field of older adults’ technology acceptance, and presents quantitative data on global research trends. From the analysis of country distribution and collaborations, China and the USA hold dominant positions in this field, with developed countries like the UK, Germany, Italy, and the Netherlands also excelling in international cooperation and research influence. The significant investment in technological research and the focus on the technological needs of older adults by many developed countries reflect their rapidly aging societies, policy support, and resource allocation.

China is the only developing country that has become a major contributor in this field, indicating its growing research capabilities and high priority given to aging societies and technological innovation. Additionally, China has close collaborations with countries such as USA, the UK, and Malaysia, driven not only by technological research needs but also by shared challenges and complementarities in aging issues among these nations. For instance, the UK has extensive experience in social welfare and aging research, providing valuable theoretical guidance and practical experience. International collaborations, aimed at addressing the challenges of aging, integrate the strengths of various countries, advancing in-depth and widespread development in the research of technology acceptance among older adults.

At the institutional and author level, City University of Hong Kong leads in publication volume, with research teams led by Chan and Chen demonstrating significant academic activity and contributions. Their research primarily focuses on older adults’ acceptance and usage behaviors of various technologies, including smartphones, smart wearables, and social robots (Chen et al. 2015 ; Li et al. 2019 ; Ma et al. 2016 ). These studies, targeting specific needs and product characteristics of older adults, have developed new models of technology acceptance based on existing frameworks, enhancing the integration of these technologies into their daily lives and laying a foundation for further advancements in the field. Although Tilburg University has a smaller publication output, it holds significant influence in the field of older adults’ technology acceptance. Particularly, the high citation rate of Peek’s studies highlights their excellence in research. Peek extensively explored older adults’ acceptance and usage of home care technologies, revealing the complexity and dynamics of their technology use behaviors. His research spans from identifying systemic influencing factors (Peek et al. 2014 ; Peek et al. 2016 ), emphasizing familial impacts (Luijkx et al. 2015 ), to constructing comprehensive models (Peek et al. 2017 ), and examining the dynamics of long-term usage (Peek et al. 2019 ), fully reflecting the evolving technology landscape and the changing needs of older adults. Additionally, the ongoing contributions of researchers like Ziefle, Rogers, and Wouters in the field of older adults’ technology acceptance demonstrate their research influence and leadership. These researchers have significantly enriched the knowledge base in this area with their diverse perspectives. For instance, Ziefle has uncovered the complex attitudes of older adults towards technology usage, especially the trade-offs between privacy and security, and how different types of activities affect their privacy needs (Maidhof et al. 2023 ; Mujirishvili et al. 2023 ; Schomakers and Ziefle 2023 ; Wilkowska et al. 2022 ), reflecting a deep exploration and ongoing innovation in the field of older adults’ technology acceptance.

Discussion on knowledge base and thematic progress (RQ3)

Through co-citation analysis and systematic review of seminal literature, this study reveals the knowledge foundation and thematic progress in the field of older adults’ technology acceptance. Co-citation networks and cluster analyses illustrate the structural themes of the research, delineating the differentiation and boundaries within this field. Additionally, burst detection analysis offers a valuable perspective for understanding the thematic evolution in the field of technology acceptance among older adults. The development and innovation of theoretical models are foundational to this research. Researchers enhance the explanatory power of constructed models by deepening and expanding existing technology acceptance theories to address theoretical limitations. For instance, Heerink et al. ( 2010 ) modified and expanded the UTAUT model by integrating functional assessment and social interaction variables to create the almere model. This model significantly enhances the ability to explain the intentions of older users in utilizing assistive social agents and improves the explanation of actual usage behaviors. Additionally, Chen and Chan ( 2014 ) extended the TAM to include age-related health and capability features of older adults, creating the STAM, which substantially improves predictions of older adults’ technology usage behaviors. Personal attributes, health and capability features, and facilitating conditions have a direct impact on technology acceptance. These factors more effectively predict older adults’ technology usage behaviors than traditional attitudinal factors.

With the advancement of technology and the application of emerging technologies, new research topics have emerged, increasingly focusing on older adults’ acceptance and use of these technologies. Prior to this, the study by Mitzner et al. ( 2010 ) challenged the stereotype of older adults’ conservative attitudes towards technology, highlighting the central roles of usability and usefulness in the technology acceptance process. This discovery laid an important foundation for subsequent research. Research fields such as “smart home technology,” “social life,” and “customer service” are emerging, indicating a shift in focus towards the practical and social applications of technology in older adults’ lives. Research not only focuses on the technology itself but also on how these technologies integrate into older adults’ daily lives and how they can improve the quality of life through technology. For instance, studies such as those by Ma et al. ( 2016 ), Hoque and Sorwar ( 2017 ), and Li et al. ( 2019 ) have explored factors influencing older adults’ use of smartphones, mHealth, and smart wearable devices.

Furthermore, the diversification of research methodologies and innovation in evaluation techniques, such as the use of mixed methods, structural equation modeling (SEM), and neural network (NN) approaches, have enhanced the rigor and reliability of the findings, enabling more precise identification of the factors and mechanisms influencing technology acceptance. Talukder et al. ( 2020 ) employed an effective multimethodological strategy by integrating SEM and NN to leverage the complementary strengths of both approaches, thus overcoming their individual limitations and more accurately analyzing and predicting older adults’ acceptance of wearable health technologies (WHT). SEM is utilized to assess the determinants’ impact on the adoption of WHT, while neural network models validate SEM outcomes and predict the significance of key determinants. This combined approach not only boosts the models’ reliability and explanatory power but also provides a nuanced understanding of the motivations and barriers behind older adults’ acceptance of WHT, offering deep research insights.

Overall, co-citation analysis of the literature in the field of older adults’ technology acceptance has uncovered deeper theoretical modeling and empirical studies on emerging technologies, while emphasizing the importance of research methodological and evaluation innovations in understanding complex social science issues. These findings are crucial for guiding the design and marketing strategies of future technology products, especially in the rapidly growing market of older adults.

Discussion on research hotspots and evolutionary trends (RQ4)

By analyzing core keywords, we can gain deep insights into the hot topics, evolutionary trends, and quality distribution of research in the field of older adults’ technology acceptance. The frequent occurrence of the keywords “TAM” and “UTAUT” indicates that the applicability and theoretical extension of existing technology acceptance models among older adults remain a focal point in academia. This phenomenon underscores the enduring influence of the studies by Davis ( 1989 ) and Venkatesh et al. ( 2003 ), whose models provide a robust theoretical framework for explaining and predicting older adults’ acceptance and usage of emerging technologies. With the widespread application of artificial intelligence (AI) and big data technologies, these theoretical models have incorporated new variables such as perceived risk, trust, and privacy issues (Amin et al. 2024 ; Chen et al. 2024 ; Jing et al. 2024b ; Seibert et al. 2021 ; Wang et al. 2024b ), advancing the theoretical depth and empirical research in this field.

Keyword co-occurrence cluster analysis has revealed multiple research hotspots in the field, including factors influencing technology adoption, interactive experiences between older adults and assistive technologies, the application of mobile health technology in health management, and technology-assisted home care. These studies primarily focus on enhancing the quality of life and health management of older adults through emerging technologies, particularly in the areas of ambient assisted living, smart health monitoring, and intelligent medical care. In these domains, the role of AI technology is increasingly significant (Qian et al. 2021 ; Ho 2020 ). With the evolution of next-generation information technologies, AI is increasingly integrated into elder care systems, offering intelligent, efficient, and personalized service solutions by analyzing the lifestyles and health conditions of older adults. This integration aims to enhance older adults’ quality of life in aspects such as health monitoring and alerts, rehabilitation assistance, daily health management, and emotional support (Lee et al. 2023 ). A survey indicates that 83% of older adults prefer AI-driven solutions when selecting smart products, demonstrating the increasing acceptance of AI in elder care (Zhao and Li 2024 ). Integrating AI into elder care presents both opportunities and challenges, particularly in terms of user acceptance, trust, and long-term usage effects, which warrant further exploration (Mhlanga 2023 ). These studies will help better understand the profound impact of AI technology on the lifestyles of older adults and provide critical references for optimizing AI-driven elder care services.

The Time-zone evolution mapping and burst keyword analysis further reveal the evolutionary trends of research hotspots. Early studies focused on basic technology acceptance models and user perceptions, later expanding to include quality of life and health management. In recent years, research has increasingly focused on cutting-edge technologies such as virtual reality, telehealth, and human-robot interaction, with a concurrent emphasis on the user experience of older adults. This evolutionary process demonstrates a deepening shift from theoretical models to practical applications, underscoring the significant role of technology in enhancing the quality of life for older adults. Furthermore, the strategic coordinate mapping analysis clearly demonstrates the development and mutual influence of different research themes. High centrality and density in the themes of Usage Experience and Assisted Living Technology indicate their mature research status and significant impact on other themes. The themes of Smart Devices, Theoretical Models, and Mobile Health Applications demonstrate self-contained research trends. The themes of Human-Robot Interaction, Characteristics of the Elderly, and Research Methods are not yet mature, but they hold potential for development. Themes of Digital Healthcare Technology, Psychological Factors, and Socio-Cultural Factors are closely related to other themes, displaying core immaturity but significant potential.

In summary, the research hotspots in the field of older adults’ technology acceptance are diverse and dynamic, demonstrating the academic community’s profound understanding of how older adults interact with technology across various life contexts and needs. Under the influence of AI and big data, research should continue to focus on the application of emerging technologies among older adults, exploring in depth how they adapt to and effectively use these technologies. This not only enhances the quality of life and healthcare experiences for older adults but also drives ongoing innovation and development in this field.

Research agenda

Based on the above research findings, to further understand and promote technology acceptance and usage among older adults, we recommend future studies focus on refining theoretical models, exploring long-term usage, and assessing user experience in the following detailed aspects:

Refinement and validation of specific technology acceptance models for older adults: Future research should focus on developing and validating technology acceptance models based on individual characteristics, particularly considering variations in technology acceptance among older adults across different educational levels and cultural backgrounds. This includes factors such as age, gender, educational background, and cultural differences. Additionally, research should examine how well specific technologies, such as wearable devices and mobile health applications, meet the needs of older adults. Building on existing theoretical models, this research should integrate insights from multiple disciplines such as psychology, sociology, design, and engineering through interdisciplinary collaboration to create more accurate and comprehensive models, which should then be validated in relevant contexts.

Deepening the exploration of the relationship between long-term technology use and quality of life among older adults: The acceptance and use of technology by users is a complex and dynamic process (Seuwou et al. 2016 ). Existing research predominantly focuses on older adults’ initial acceptance or short-term use of new technologies; however, the impact of long-term use on their quality of life and health is more significant. Future research should focus on the evolution of older adults’ experiences and needs during long-term technology usage, and the enduring effects of technology on their social interactions, mental health, and life satisfaction. Through longitudinal studies and qualitative analysis, this research reveals the specific needs and challenges of older adults in long-term technology use, providing a basis for developing technologies and strategies that better meet their requirements. This understanding aids in comprehensively assessing the impact of technology on older adults’ quality of life and guiding the optimization and improvement of technological products.

Evaluating the Importance of User Experience in Research on Older Adults’ Technology Acceptance: Understanding the mechanisms of information technology acceptance and use is central to human-computer interaction research. Although technology acceptance models and user experience models differ in objectives, they share many potential intersections. Technology acceptance research focuses on structured prediction and assessment, while user experience research concentrates on interpreting design impacts and new frameworks. Integrating user experience to assess older adults’ acceptance of technology products and systems is crucial (Codfrey et al. 2022 ; Wang et al. 2019 ), particularly for older users, where specific product designs should emphasize practicality and usability (Fisk et al. 2020 ). Researchers need to explore innovative age-appropriate design methods to enhance older adults’ usage experience. This includes studying older users’ actual usage preferences and behaviors, optimizing user interfaces, and interaction designs. Integrating feedback from older adults to tailor products to their needs can further promote their acceptance and continued use of technology products.

Conclusions

This study conducted a systematic review of the literature on older adults’ technology acceptance over the past decade through bibliometric analysis, focusing on the distribution power, research power, knowledge base and theme progress, research hotspots, evolutionary trends, and quality distribution. Using a combination of quantitative and qualitative methods, this study has reached the following conclusions:

Technology acceptance among older adults has become a hot topic in the international academic community, involving the integration of knowledge across multiple disciplines, including Medical Informatics, Health Care Sciences Services, and Ergonomics. In terms of journals, “PSYCHOLOGY, EDUCATION, HEALTH” represents a leading field, with key publications including Computers in Human Behavior , Journal of Medical Internet Research , and International Journal of Human-Computer Interaction . These journals possess significant academic authority and extensive influence in the field.

Research on technology acceptance among older adults is particularly active in developed countries, with China and USA publishing significantly more than other nations. The Netherlands leads in high average citation rates, indicating the depth and impact of its research. Meanwhile, the UK stands out in terms of international collaboration. At the institutional level, City University of Hong Kong and The University of Hong Kong in China are in leading positions. Tilburg University in the Netherlands demonstrates exceptional research quality through its high average citation count. At the author level, Chen from China has the highest number of publications, while Peek from the Netherlands has the highest average citation count.

Co-citation analysis of references indicates that the knowledge base in this field is divided into three main categories: theoretical model deepening, emerging technology applications, and research methods and evaluation. Seminal literature focuses on four areas: specific technology use by older adults, expansion of theoretical models of technology acceptance, information technology adoption behavior, and research perspectives. Research themes have evolved from initial theoretical deepening and analysis of influencing factors to empirical studies on individual factors and emerging technologies.

Keyword analysis indicates that TAM and UTAUT are the most frequently occurring terms, while “assistive technology” and “virtual reality” are focal points with high frequency and centrality. Keyword clustering analysis reveals that research hotspots are concentrated on the influencing factors of technology adoption, human-robot interaction experiences, mobile health management, and technology for aging in place. Time-zone evolution mapping and burst keyword analysis have revealed the research evolution from preliminary exploration of influencing factors, to enhancements in quality of life and health management, and onto advanced technology applications and deepening of theoretical models. Furthermore, analysis of research quality distribution indicates that Usage Experience and Assisted Living Technology have become core topics, while Smart Devices, Theoretical Models, and Mobile Health Applications point towards future research directions.

Through this study, we have systematically reviewed the dynamics, core issues, and evolutionary trends in the field of older adults’ technology acceptance, constructing a comprehensive Knowledge Mapping of the domain and presenting a clear framework of existing research. This not only lays the foundation for subsequent theoretical discussions and innovative applications in the field but also provides an important reference for relevant scholars.

Limitations

To our knowledge, this is the first bibliometric analysis concerning technology acceptance among older adults, and we adhered strictly to bibliometric standards throughout our research. However, this study relies on the Web of Science Core Collection, and while its authority and breadth are widely recognized, this choice may have missed relevant literature published in other significant databases such as PubMed, Scopus, and Google Scholar, potentially overlooking some critical academic contributions. Moreover, given that our analysis was confined to literature in English, it may not reflect studies published in other languages, somewhat limiting the global representativeness of our data sample.

It is noteworthy that with the rapid development of AI technology, its increasingly widespread application in elderly care services is significantly transforming traditional care models. AI is profoundly altering the lifestyles of the elderly, from health monitoring and smart diagnostics to intelligent home systems and personalized care, significantly enhancing their quality of life and health care standards. The potential for AI technology within the elderly population is immense, and research in this area is rapidly expanding. However, due to the restrictive nature of the search terms used in this study, it did not fully cover research in this critical area, particularly in addressing key issues such as trust, privacy, and ethics.

Consequently, future research should not only expand data sources, incorporating multilingual and multidatabase literature, but also particularly focus on exploring older adults’ acceptance of AI technology and its applications, in order to construct a more comprehensive academic landscape of older adults’ technology acceptance, thereby enriching and extending the knowledge system and academic trends in this field.

Data availability

The datasets analyzed during the current study are available in the Dataverse repository: https://doi.org/10.7910/DVN/6K0GJH .

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Acknowledgements

This research was supported by the Social Science Foundation of Shaanxi Province in China (Grant No. 2023J014).

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Xianru Shang, Zijian Liu, Chen Gong, Zhigang Hu & Yuexuan Wu

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Conceptualization, XS, YW, CW; methodology, XS, ZL, CG, CW; software, XS, CG, YW; writing-original draft preparation, XS, CW; writing-review and editing, XS, CG, ZH, CW; supervision, ZL, ZH, CW; project administration, ZL, ZH, CW; funding acquisition, XS, CG. All authors read and approved the final manuscript. All authors have read and approved the re-submission of the manuscript.

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Shang, X., Liu, Z., Gong, C. et al. Knowledge mapping and evolution of research on older adults’ technology acceptance: a bibliometric study from 2013 to 2023. Humanit Soc Sci Commun 11 , 1115 (2024). https://doi.org/10.1057/s41599-024-03658-2

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Received : 20 June 2024

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DOI : https://doi.org/10.1057/s41599-024-03658-2

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