Anchors
| Anchor text | Ref. domains ▾ | Top DR | Ref. pages | Links to target | Dofollow links |
|---|---|---|---|---|---|
| JMIR Formative Research 4125 articles | 26 | — | 0 | 8040 | 8040 100% |
| END | 22 | — | 0 | 838 | 838 100% |
| Download XML | 22 | — | 0 | 838 | 838 100% |
| RIS | 22 | — | 0 | 838 | 838 100% |
| BibTex | 22 | — | 0 | 838 | 838 100% |
| Download PDF | 22 | — | 0 | 838 | 838 100% |
| JMIR Formative Research | 20 | — | 0 | 2062 | 2061 100% |
| FREE Full text | 19 | — | 0 | 265 | 265 100% |
| JMIR Formative Research 4127 articles | 18 | — | 0 | 1913 | 1913 100% |
| 7 | — | 0 | 9 | 8 88.9% | |
| study | 5 | — | 0 | 9 | 9 100% |
| Low Risk Perception of Harm From Substance Use and Sexual Behaviors Among Online Help–Seeking Sexual and Gender Minoritized People in San Francisco, California: Cross-Sectional Survey | 4 | — | 0 | 4 | 4 100% |
| JMIR Formative Research 4122 articles | 4 | — | 0 | 176 | 176 100% |
| Exploring the Preferences and Behavioral Trends of e-Patients in Psychosomatics Towards Telemedicine During and Post COVID-19 Pandemic: Cross-Sectional Analysis | 3 | — | 0 | 3 | 3 100% |
| The Role of Health in the Technology Acceptance Model Among Low-Income Asian American Older Adults: Cross-Sectional Survey Analysis | 3 | — | 0 | 3 | 3 100% |
| Evaluating the Efficacy of AI-Based Interactive Assessments Using Large Language Models for Depression Screening: Development and Usability Study | 3 | — | 0 | 4 | 4 100% |
| A Peer-Led, Narrative-Based, and Mobile-Supported Intervention in Opioid Use Disorder: Multiphase Qualitative and Longitudinal Observational Study | 3 | — | 0 | 3 | 3 100% |
| Young People’s Satisfaction With and Perceived Impact of a Multichannel Mental Health Helpline During and After COVID-19 Pandemic: Mixed Methods Analysis of Cross-Sectional Survey Data | 3 | — | 0 | 5 | 5 100% |
| Optimization of a Quality Improvement Tool for Cancer Diagnosis in Primary Care: Qualitative Study | 3 | — | 0 | 3 | 3 100% |
| Support Community Formation on a Mobile App for People Living With HIV and Substance Use Disorder: A Computer-Mediated Discourse Analysis | 3 | — | 0 | 3 | 3 100% |
| paper | 3 | — | 0 | 3 | 3 100% |
| Developing a Customizable Texting Intervention for Diabetes Self-Management: Participatory Design Approach | 3 | — | 0 | 4 | 4 100% |
| Survey Evaluation of the Role of Social Media and Social Support for Transgender, Nonbinary, and Intersex People: Observational Study | 2 | — | 0 | 2 | 2 100% |
| Canadian Professional Association Resources on Diet and Tooth Decay: Website Content Analysis | 2 | — | 0 | 3 | 3 100% |
| Preferences on Governance Models for Mental Health Data: Qualitative Study With Young People | 2 | — | 0 | 2 | 2 100% |
| The Impact of a Digital Peer-Supported App on Daily Steps and Lifestyle Changes Among Individuals With Prediabetes and Early-Stage Type 2 Diabetes: Prospective, Nonrandomized Controlled Trial | 2 | — | 0 | 2 | 2 100% |
| A Couples-Based Intervention (Ghya Bharari Ekatra) for the Primary Prevention of Intimate Partner Violence in India: Pilot Feasibility and Acceptability Study | 2 | — | 0 | 2 | 2 100% |
| Identification of Hypertension in Electronic Health Records Through Computable Phenotype Development and Validation for Use in Public Health Surveillance: Retrospective Study | 2 | — | 0 | 2 | 2 100% |
| Development and Validation of the Kazakhstan Version of the Questionnaire Based on the Telehealth Usability Questionnaire and Model for Assessment of Telemedicine Models for Evaluating the Usability and Effectiveness of Telemedicine Services Among Physicians: Multiphase Cross-Sectional Study | 2 | — | 0 | 3 | 3 100% |
| mHealth Technology Experiences of Middle-Aged and Older Individuals With Visual Impairments: Cross-Sectional Interview Study | 2 | — | 0 | 2 | 2 100% |
| Pro- and Antifluoride Use Messages on YouTube in Japan: Content Analysis | 2 | — | 0 | 4 | 4 100% |
| Assessing the Readability and Quality of Web-Based Resources on Exercise Stress Testing: Cross-Sectional Readability and Quality Analysis | 2 | — | 0 | 3 | 3 100% |
| Use of and Attitudes Toward Technology Among Young People Living With HIV in San Francisco: Cross-Sectional Study | 2 | — | 0 | 2 | 2 100% |
| Evaluation of Psychological Resources of Young Adults With Type 1 Diabetes Mellitus During the Transition From Pediatric to Adult Diabetes Clinics: Multicenter Cross-sectional Study | 2 | — | 0 | 2 | 2 100% |
| Exploring the Acceptability, Appropriateness, and Utility of a Digital Single-Session Intervention (Project SOLVE-NZ) for Adolescent Mental Health in New Zealand: Interview Study Among Students and Teachers | 2 | — | 0 | 3 | 3 100% |
| JMIR Publications | 2 | — | 0 | 2 | 2 100% |
| Requirements and Use Cases for eHealth Solutions in Flexible Assertive Community Treatment Teams: Design Science Study | 2 | — | 0 | 3 | 3 100% |
| Reach, Engagement, and Acceptability of a Subclinical Telehealth Service for Spanish-Speaking Adults: Retrospective Mixed Methods Pilot Study | 2 | — | 0 | 3 | 3 100% |
| Engagement and Acceptability of Acceptance and Commitment Therapy in Daily Life in Early Psychosis: Secondary Findings From a Multicenter Randomized Controlled Trial | 2 | — | 0 | 2 | 2 100% |
| Impact of the Practice of Playing Video Games on Technical Skills Development in Preclinical Dental Education: Preliminary Cross-Sectional Observational Study | 2 | — | 0 | 2 | 2 100% |
| Designing a Case Management Mobile Health App for Violence Intervention Programs: Mixed Methods Human-Centered Design Study | 2 | — | 0 | 3 | 3 100% |
| Development of a Social Media Campaign to Support HIV Prevention and Care Among Transgender Latina Women: Community-Engaged Mixed Methods Feasibility Pilot Study | 2 | — | 0 | 2 | 2 100% |
| Feasibility and User Experience of an AI-Supported mHealth Intervention for Remote Life Goal Setting Based on Flow Theory: Exploratory Within-Participant Study | 2 | — | 0 | 3 | 3 100% |
| Preferences for an Experience Sampling Method–Based Tool as an Adjunct to Usual Treatment in Patients With Problem Substance Use: Qualitative Study | 2 | — | 0 | 2 | 2 100% |
| Associations Between Online Search Trends and Outpatient Visits for Common Medical Symptoms in the United States from 2004 to 2019: Time Series Ecological Study | 2 | — | 0 | 3 | 3 100% |
| Assessing Health Data Security Risks in Global Health Partnerships: Development of a Conceptual Framework | 2 | — | 0 | 2 | 2 100% |
| Firearm Violence and Health in Policymaker Discourse: Mixed Methods Social Media Analysis | 2 | — | 0 | 4 | 4 100% |
| Research | 2 | — | 0 | 2 | 2 100% |
| Assessing Digital Phenotyping for App Recommendations and Sustained Engagement: Cohort Study | 2 | — | 0 | 2 | 2 100% |
| Read more | 2 | — | 0 | 2 | 2 100% |
Frequently Asked Questions
What anchor texts are used to link to formative.jmir.org?
This page shows all anchor texts found in backlinks pointing to formative.jmir.org, sorted by the number of referring domains using each anchor. Anchor texts range from branded terms (like the domain name itself) to keyword-rich phrases that describe the linked content. The distribution of anchor texts reveals how other websites perceive and describe formative.jmir.org.
What is anchor text?
Anchor text is the visible, clickable text in a hyperlink. Search engines use anchor text as a signal to understand what the linked page is about. For example, if many sites link to a page using the anchor text "best running shoes," search engines infer that the page is relevant to that topic. Anchor text appears in several forms: exact-match (contains target keywords), branded (uses the company or domain name), generic (like "click here"), and naked URLs.
Why is anchor text analysis important for SEO?
Anchor text analysis helps identify potential SEO risks and opportunities. A natural backlink profile has diverse anchor texts including branded terms, generic phrases, and topic-relevant keywords. Over-optimization, where too many backlinks use the same exact-match keyword anchor, can trigger search engine penalties. Conversely, understanding which anchors drive the most authority (measured by referring domain count and DR) helps prioritize link building efforts.
How many unique anchor texts does formative.jmir.org have?
The anchor text report for formative.jmir.org displays all distinct anchor texts grouped by their hash. Each row shows how many unique referring domains use that anchor, the total number of links, and the dofollow percentage. A high number of unique anchors generally indicates a healthy, natural backlink profile with diverse link sources.