<?xml version="1.0" encoding="UTF-8"?><!DOCTYPE article PUBLIC "-//NLM//DTD Journal Publishing DTD v2.0 20040830//EN" "journalpublishing.dtd"><article xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink" dtd-version="2.0" xml:lang="en" article-type="research-article"><front><journal-meta><journal-id journal-id-type="nlm-ta">JMIR Hum Factors</journal-id><journal-id journal-id-type="publisher-id">humanfactors</journal-id><journal-id journal-id-type="index">6</journal-id><journal-title>JMIR Human Factors</journal-title><abbrev-journal-title>JMIR Hum Factors</abbrev-journal-title><issn pub-type="epub">2292-9495</issn><publisher><publisher-name>JMIR Publications</publisher-name><publisher-loc>Toronto, Canada</publisher-loc></publisher></journal-meta><article-meta><article-id pub-id-type="publisher-id">v13i1e75935</article-id><article-id pub-id-type="doi">10.2196/75935</article-id><article-categories><subj-group subj-group-type="heading"><subject>Original Paper</subject></subj-group></article-categories><title-group><article-title>Factors Influencing User Satisfaction in Accessing Health Data: Cross-Sectional Survey of United Kingdom Adults</article-title></title-group><contrib-group><contrib contrib-type="author" corresp="yes"><name name-style="western"><surname>Xenou</surname><given-names>Maria</given-names></name><degrees>BSc, MSc</degrees><xref ref-type="aff" rid="aff1">1</xref></contrib><contrib contrib-type="author"><name name-style="western"><surname>Al-Ubaydli</surname><given-names>Omar</given-names></name><degrees>BSc, MSc, PhD</degrees><xref ref-type="aff" rid="aff2">2</xref></contrib></contrib-group><aff id="aff1"><institution>UCL Institute of Health Informatics, University College London</institution><addr-line>222 Euston Rd, London</addr-line><addr-line>London</addr-line><country>United Kingdom</country></aff><aff id="aff2"><institution>Department of Economics and Mercatus Center, George Mason University</institution><addr-line>4400 University Drive</addr-line><addr-line>Fairfax</addr-line><addr-line>VA</addr-line><country>United States</country></aff><contrib-group><contrib contrib-type="editor"><name name-style="western"><surname>Gooch</surname><given-names>Daniel</given-names></name></contrib></contrib-group><contrib-group><contrib contrib-type="reviewer"><name name-style="western"><surname>Mircheva</surname><given-names>Iskra</given-names></name></contrib><contrib contrib-type="reviewer"><name name-style="western"><surname>Agrawal</surname><given-names>Lavlin</given-names></name></contrib></contrib-group><author-notes><corresp>Correspondence to Maria Xenou, BSc, MSc, UCL Institute of Health Informatics, University College London, 222 Euston Rd, London, London, NW1 2DA, United Kingdom, 44 2035495969; <email>maria.xenou.20@ucl.ac.uk</email></corresp></author-notes><pub-date pub-type="collection"><year>2026</year></pub-date><pub-date pub-type="epub"><day>6</day><month>4</month><year>2026</year></pub-date><volume>13</volume><elocation-id>e75935</elocation-id><history><date date-type="received"><day>13</day><month>04</month><year>2025</year></date><date date-type="rev-recd"><day>10</day><month>02</month><year>2026</year></date><date date-type="accepted"><day>10</day><month>02</month><year>2026</year></date></history><copyright-statement>&#x00A9; Maria Xenou, Omar Al-Ubaydli. Originally published in JMIR Human Factors (<ext-link ext-link-type="uri" xlink:href="https://humanfactors.jmir.org">https://humanfactors.jmir.org</ext-link>), 6.4.2026. </copyright-statement><copyright-year>2026</copyright-year><license license-type="open-access" xlink:href="https://creativecommons.org/licenses/by/4.0/"><p>This is an open-access article distributed under the terms of the Creative Commons Attribution License (<ext-link ext-link-type="uri" xlink:href="https://creativecommons.org/licenses/by/4.0/">https://creativecommons.org/licenses/by/4.0/</ext-link>), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in JMIR Human Factors, is properly cited. The complete bibliographic information, a link to the original publication on <ext-link ext-link-type="uri" xlink:href="https://humanfactors.jmir.org">https://humanfactors.jmir.org</ext-link>, as well as this copyright and license information must be included.</p></license><self-uri xlink:type="simple" xlink:href="https://humanfactors.jmir.org/2026/1/e75935"/><abstract><sec><title>Background</title><p>While patient health records (PHRs) are becoming ubiquitous, nationwide evidence on the drivers of user satisfaction in the United Kingdom remains scarce.</p></sec><sec><title>Objective</title><p>This study aimed to quantify determinants of PHR user satisfaction in a nationally representative sample of United Kingdom adults and to contrast real-world experiences with hypothetical expectations among individuals without PHR exposure.</p></sec><sec sec-type="methods"><title>Methods</title><p>We conducted a cross-sectional online survey in March 2022 using stratified quota sampling (eg, age, sex, ethnicity) through the Prolific platform. Of 1001 respondents, 533 (53%) were female (mean age 41, SD13) years, 468 (47%) reported previous PHR use (&#x201C;experienced&#x201D; cohort), and 533 (53%) respondents did not (&#x201C;hypothetical&#x201D; cohort). Primary outcomes were five satisfaction items (5-point Likert), overall PHR evaluation (0&#x2010;100), and stated/anticipated PHR functions. Two-sample <italic>t</italic>-tests with unequal variances examined between-group differences; multivariate analysis of variance (MANOVA) assessed demographic equivalence. Significance was set at <italic>P</italic>&#x003C;.05.</p></sec><sec sec-type="results"><title>Results</title><p>Respondents with PHR experience rated their record easy-to-use in 79% (370/468) of cases versus an anticipated 93% (498/533) among nonusers (<italic>P</italic>&#x003C;.001). Experienced users rated appointment-scheduling time-saving at 68% (319/468) compared with 72% (387/533) of nonusers (<italic>P</italic>=.17). Mean overall evaluation scores were 71.0&#x202F;(SD 19.5) versus 74.2&#x202F;(SD 18.6) (t&#x2089;&#x2089;&#x2087;=2.25, <italic>P</italic>=.02). MANOVA confirmed demographic balance (Wilks &#x039B;=.99, F&#x2087;,&#x2089;&#x2089;&#x2083;=1.48, <italic>P</italic>=.18). Preferred functions across cohorts were viewing personal health information (experience 81%, hypothetical 90%) and lab results (50% vs 76%). Users lacking experience consistently over-estimated future use of carer-related functions (eg, children&#x2019;s data: 36% vs 12%, <italic>P</italic>&#x003C;.001).</p></sec><sec sec-type="conclusions"><title>Conclusions</title><p>Adults in the United Kingdom value PHRs primarily for personal data access and scheduling convenience. Nonusers displayed optimistic expectations about carer-related features and breadth of functionality, indicating an information gap. Enhancing transparency about current capabilities and expanding features that facilitate caregiving could increase satisfaction and adoption.</p></sec></abstract><kwd-group><kwd>patient health record</kwd><kwd>user satisfaction</kwd><kwd>national survey</kwd><kwd>digital health</kwd><kwd>United Kingdom</kwd></kwd-group></article-meta></front><body><sec id="s1" sec-type="intro"><title>Introduction</title><sec id="s1-1"><title>Background</title><p>Electronic access to health information is integral to patient-centered care [<xref ref-type="bibr" rid="ref1">1</xref>]. In the United Kingdom, 73% of adults go online first for health information [<xref ref-type="bibr" rid="ref2">2</xref>], and the National Health Service (NHS) aims to universalize digital data access under the ethos of &#x201C;no decision about me without me&#x201D; [<xref ref-type="bibr" rid="ref3">3</xref>]. People may view clinical data through provider-tethered electronic medical records (EMRs) or untethered patient health records (PHRs) [<xref ref-type="bibr" rid="ref4">4</xref>-<xref ref-type="bibr" rid="ref6">6</xref>]. PHRs allow patients to <italic>access, manage, and share</italic> their complete longitudinal health data independently of any single institution [<xref ref-type="bibr" rid="ref6">6</xref>]. Evidence suggests PHRs can reduce costs and improve outcomes by empowering self-care [<xref ref-type="bibr" rid="ref4">4</xref>,<xref ref-type="bibr" rid="ref7">7</xref>,<xref ref-type="bibr" rid="ref8">8</xref>], yet utilization and satisfaction remain variable [<xref ref-type="bibr" rid="ref9">9</xref>].</p><p>The NHS app, launched nationally in 2019, now exceeds 22 &#x202F;million registered users and represents most United Kingdom adults&#x2019; first exposure to a PHR ecosystem [<xref ref-type="bibr" rid="ref10">10</xref>,<xref ref-type="bibr" rid="ref11">11</xref>]. Previous research shows that activated patients can achieve higher levels of self-care and satisfaction by sharing all clinical notes with their clinical team, reducing their clinical workload, and improving the health information exchange [<xref ref-type="bibr" rid="ref10">10</xref>,<xref ref-type="bibr" rid="ref11">11</xref>]. A recent Canadian study surveyed national PHR users and highlighted time savings, reduced clinic visits, and high satisfaction [<xref ref-type="bibr" rid="ref12">12</xref>]. They concluded that PHR users showed positive patient satisfaction, a measured decrease of appointment rates, and a decrease in their usage of the Canadian health system.</p><p>Comparable United Kingdom-wide data&#x2014;including insights from individuals without PHR experience&#x2014;are lacking. Understanding expectations and perceived utility among both groups is critical as PHR functions expand.</p><p>In the United Kingdom, digital access to personal health data has expanded rapidly. Approximately 73% of adults use the internet as their main health information source [<xref ref-type="bibr" rid="ref13">13</xref>-<xref ref-type="bibr" rid="ref15">15</xref>]. Despite the growing adoption of such tools, research on PHR user satisfaction in the United Kingdom remains limited and often focuses on small, nonrepresentative samples [<xref ref-type="bibr" rid="ref16">16</xref>].</p></sec><sec id="s1-2"><title>Objectives</title><p>We sought to (1) identify determinants of PHR user satisfaction in a nationally representative sample of United Kingdom adults [<xref ref-type="bibr" rid="ref17">17</xref>] and (2) compare perceptions between adults with real-world PHR experience and those expressing hypothetical expectations.</p></sec></sec><sec id="s2" sec-type="methods"><title>Methods</title><sec id="s2-1"><title>Design and Setting</title><p>We explicitly identify the study as a <italic>descriptive, cross-sectional survey</italic>. Data were collected online between 23&#x2010;25 March 2022. Informed electronic consent was obtained.</p></sec><sec id="s2-2"><title>Participants and Sampling</title><p>Because the survey assessed attitudes toward PHRs, it was essential to provide respondents with a clear understanding of what a PHR is. Accordingly, participants were shown a lay definition adapted from the Canadian study [<xref ref-type="bibr" rid="ref12">12</xref>]. Approximately half of respondents had real experience with a PHR&#x2014;most commonly the NHS app, which enables access to medical records, vaccination status, appointments, and prescriptions [<xref ref-type="bibr" rid="ref18">18</xref>-<xref ref-type="bibr" rid="ref20">20</xref>]. Other PHR systems integrated with the NHS App were also represented among users.</p><p>Participants were recruited via Prolific Academic [<xref ref-type="bibr" rid="ref21">21</xref>], which maintains a United Kingdom participant panel. Using Prolific&#x2019;s <italic>nationally representative</italic> option, we enforced quota stratification on age (six census bands), sex (male/female), and ethnicity (five ONS categories) to mirror 2021 United Kingdom Census proportions. Inclusion criteria were age&#x202F;&#x2265;&#x202F;18&#x202F;years and United Kingdom residence. A total of 1001 adults satisfied the quotas, resulting in margin-of-error&#x00B1;3&#x202F;percentage-points at the 95% confidence level.</p><p>In addition to age, sex, and ethnicity, no further stratification variables (such as education level or household income) were available within the nationally representative Prolific panel profiles at the time of recruitment. Quotas were therefore restricted to Office for National Statistics census categories for age, sex, and ethnicity. The resulting sample distributions across these strata are reported in <xref ref-type="supplementary-material" rid="app1">Multimedia Appendix 1</xref>.</p></sec><sec id="s2-3"><title>Survey Instrument</title><p>The questionnaire replicated the Canadian instrument [<xref ref-type="bibr" rid="ref12">12</xref>] with United Kingdom contextual modifications (eg, &#x201C;accident and emergency&#x201D; replacing &#x201C;emergency room&#x201D;). Two parallel versions were administered: an experience-based version for respondents confirming prior PHR use and a hypothetical version with isomorphic wording framed as &#x201C;If you had a PHR&#x2026;.&#x201D; Sections covered (1) user satisfaction (5 items), (2) utility (12 items), (3) impact, and (4) demographics. The full instrument is now provided as a Survey Instrument <xref ref-type="supplementary-material" rid="app2">Multimedia Appendix 2</xref> .</p></sec><sec id="s2-4"><title>Statistical Analysis</title><p>Categorical variables (eg, gender, age group) were converted to dummy indicators. No missing data were observed. Between-group differences in satisfaction, utility, and impact outcomes were examined using independent two-sample t-tests with unequal variances (<xref ref-type="supplementary-material" rid="app1">Multimedia Appendix 1</xref>). A multivariate analysis of variance (MANOVA) was conducted solely to assess demographic equivalence between respondents with and without prior PHR experience, using gender and age-band indicators as joint dependent variables. MANOVA was not used for outcome analysis.</p><p>All statistical tests used two-tailed p-values, with <italic>P</italic>&#x003C;.05 considered significant. MANOVA assessed demographic equivalence across seven covariates (gender + six age bands). All analyses used STATA (version 17.0; StataCorp LLC), with <italic>&#x03B1;</italic>=.05.</p></sec><sec id="s2-5"><title>Ethical Considerations</title><p>The study is classified as a service evaluation per NHS REC guidance and is therefore exempt from formal NHS ethics review [<xref ref-type="bibr" rid="ref22">22</xref>].</p></sec></sec><sec id="s3" sec-type="results"><title>Results</title><sec id="s3-1"><title>Participant Characteristics</title><p>Data collection occurred between March 25, and April 5, 2022. A total of 1001 adults completed the survey (completion rate=99%). <xref ref-type="table" rid="table1">Table 1</xref> compares sample demographics with 2021 Census benchmarks; deviations were &#x003C;5 &#x202F;percentage points for all strata except adults aged&#x202F;&#x2265;&#x202F;60 years (60&#x2010;69: &#x2212;6&#x202F;pp;&#x2265;70: &#x2212;8&#x202F;pp).</p><table-wrap id="t1" position="float"><label>Table 1.</label><caption><p>Participant demographics by sample [experienced-based versus hypothetical].</p></caption><table id="table1" frame="hsides" rules="groups"><thead><tr><td align="left" valign="bottom">Characteristics</td><td align="left" valign="bottom">Experience-based sample (n=468), n (%)</td><td align="left" valign="bottom">Hypothetical sample (n=533), n (%)</td><td align="left" valign="bottom">Nationally representative sample (2021), %</td></tr></thead><tbody><tr><td align="left" valign="top">Gender</td><td align="left" valign="top"/><td align="left" valign="top"/><td align="left" valign="top"/></tr><tr><td align="left" valign="top"><named-content content-type="indent">&#x00A0;&#x00A0;&#x00A0;&#x00A0;</named-content>Female</td><td align="left" valign="top">247 (53)</td><td align="left" valign="top">255 (48)</td><td align="left" valign="top">51</td></tr><tr><td align="left" valign="top"><named-content content-type="indent">&#x00A0;&#x00A0;&#x00A0;&#x00A0;</named-content>Male</td><td align="left" valign="top">217 (46)</td><td align="left" valign="top">263 (49)</td><td align="left" valign="top">49</td></tr><tr><td align="left" valign="top"><named-content content-type="indent">&#x00A0;&#x00A0;&#x00A0;&#x00A0;</named-content>Other</td><td align="left" valign="top">4 (1)</td><td align="left" valign="top">15 (3)</td><td align="left" valign="top">&#x2014;<sup><xref ref-type="table-fn" rid="table1fn1">a</xref></sup></td></tr><tr><td align="left" valign="top">Age</td><td align="left" valign="top"/><td align="left" valign="top"/><td align="left" valign="top"/></tr><tr><td align="left" valign="top"><named-content content-type="indent">&#x00A0;&#x00A0;&#x00A0;&#x00A0;</named-content>18&#x2010;29</td><td align="left" valign="top">107 (23)</td><td align="left" valign="top">93 (17)</td><td align="left" valign="top">18</td></tr><tr><td align="left" valign="top"><named-content content-type="indent">&#x00A0;&#x00A0;&#x00A0;&#x00A0;</named-content>30&#x2010;39</td><td align="left" valign="top">93 (20)</td><td align="left" valign="top">100 (19)</td><td align="left" valign="top">17</td></tr><tr><td align="left" valign="top"><named-content content-type="indent">&#x00A0;&#x00A0;&#x00A0;&#x00A0;</named-content>40&#x2010;49</td><td align="left" valign="top">82 (18)</td><td align="left" valign="top">86 (16)</td><td align="left" valign="top">16</td></tr><tr><td align="left" valign="top"><named-content content-type="indent">&#x00A0;&#x00A0;&#x00A0;&#x00A0;</named-content>50&#x2010;59</td><td align="left" valign="top">86 (18)</td><td align="left" valign="top">114 (21)</td><td align="left" valign="top">18</td></tr><tr><td align="left" valign="top"><named-content content-type="indent">&#x00A0;&#x00A0;&#x00A0;&#x00A0;</named-content>60&#x2010;69</td><td align="left" valign="top">85 (18)</td><td align="left" valign="top">116 (22)</td><td align="left" valign="top">14</td></tr><tr><td align="left" valign="top"><named-content content-type="indent">&#x00A0;&#x00A0;&#x00A0;&#x00A0;</named-content>70+</td><td align="left" valign="top">15 (3)</td><td align="left" valign="top">24 (5)</td><td align="left" valign="top">17</td></tr><tr><td align="left" valign="top">Comfort with computers</td><td align="left" valign="top"/><td align="left" valign="top"/><td align="left" valign="top"/></tr><tr><td align="left" valign="top"><named-content content-type="indent">&#x00A0;&#x00A0;&#x00A0;&#x00A0;</named-content>Completely comfortable</td><td align="left" valign="top">11 (2)</td><td align="left" valign="top">15 (3)</td><td align="left" valign="top">&#x2014;</td></tr><tr><td align="left" valign="top"><named-content content-type="indent">&#x00A0;&#x00A0;&#x00A0;&#x00A0;</named-content>Comfortable</td><td align="left" valign="top">3 (1)</td><td align="left" valign="top">3 (1)</td><td align="left" valign="top">&#x2014;</td></tr><tr><td align="left" valign="top"><named-content content-type="indent">&#x00A0;&#x00A0;&#x00A0;&#x00A0;</named-content>Neutral</td><td align="left" valign="top">9 (2)</td><td align="left" valign="top">22 (4)</td><td align="left" valign="top">&#x2014;</td></tr><tr><td align="left" valign="top"><named-content content-type="indent">&#x00A0;&#x00A0;&#x00A0;&#x00A0;</named-content>Uncomfortable</td><td align="left" valign="top">112 (24)</td><td align="left" valign="top">185 (35)</td><td align="left" valign="top">&#x2014;</td></tr><tr><td align="left" valign="top"><named-content content-type="indent">&#x00A0;&#x00A0;&#x00A0;&#x00A0;</named-content>Completely uncomfortable</td><td align="left" valign="top">333 (71)</td><td align="left" valign="top">308 (58)</td><td align="left" valign="top">&#x2014;</td></tr></tbody></table><table-wrap-foot><fn id="table1fn1"><p><sup>a</sup>Not available.</p></fn></table-wrap-foot></table-wrap><p>A MANOVA assessing joint differences in sex and age distribution between respondents with and without prior PHR experience showed no statistically significant multivariate differences (Wilks&#x2019; &#x039B;=0.99; F&#x2086;,&#x2089;&#x2089;&#x2084;=1.48; <italic>P</italic>=.18), indicating demographic balance between cohorts.</p></sec><sec id="s3-2"><title>Satisfaction, Impact and Utility</title><p>Among participants with PHR experience, 79% (370/468) agreed their PHR was easy to use and 68% (319/468) reported it saved time scheduling appointments. For those without experience, 99% (528/533) stated they would use a PHR to access personal health information and 72% (387/533) expected time savings. Ease of communication with care providers was reported by 60% (283/468) of experienced users versus 75% (398/533) of nonusers (<italic>P</italic>=.01).</p><p>PHR use reportedly avoided a clinic visit for 42% and an Accident and Emergency visit for 4% of experienced users. Hypothetical avoidance estimates were 32% and 9% among nonusers.</p></sec><sec id="s3-3"><title>Impact on Healthcare Use</title><p>Forty-two per cent (200/468) of experienced users indicated their PHR helped avoid at least one clinic visit, and 4% (19/468) avoided an emergency-room visit. Among nonusers, 32% (193/533) anticipated avoiding a clinic visit and 9% (47/533) an emergency visit.</p></sec><sec id="s3-4"><title>Preferred Features and Cost Savings</title><p>Experienced users most valued: viewing their own health information 81% (377/468); viewing lab results 50% (233/468); and scheduling appointments 47% (220/468). Nonusers prioritized: viewing health information 90% (479/533); lab results 76% (405/533); and appointment scheduling 58% (309/533). Cost savings most often related to time off work (40% (187/468) vs 57% (303/533), petrol/gasoline (30% (140/468) vs 52% (278/533), and parking (21% (98/468) vs 34% (181/533).</p></sec><sec id="s3-5"><title>Experience-Based vs Hypothetical Comparisons</title><p><xref ref-type="table" rid="table2">Table 2</xref> presents mean differences across 35 survey items. Nonusers significantly over-estimated future use for caregiving data access (eg, child records: &#x0394; =+24 &#x202F;pp, <italic>P</italic>&#x003C;.001). Despite these discrepancies, overall evaluation scores were similar (71 vs 74, <italic>P</italic>=.02). Specifically, three main differences emerged:</p><list list-type="order"><list-item><p>Nonusers over-estimated the extent to which they would use PHRs for family members&#x2019; data (eg, children: 36% vs 12%, <italic>P</italic>=.01).</p></list-item><list-item><p>They over-estimated available functionality, such as preclinic forms (55% vs 18%, <italic>P</italic>=.01).</p></list-item><list-item><p>Despite this, overall satisfaction scores were comparable (74 vs 71 out of 100, <italic>P</italic>=.01).</p></list-item></list><table-wrap id="t2" position="float"><label>Table 2.</label><caption><p><bold>P</bold>articipant views on PHRs (experienced-based versus hypothetical).</p></caption><table id="table2" frame="hsides" rules="groups"><thead><tr><td align="left" valign="bottom">Participant responses</td><td align="left" valign="bottom">Experience-based sample (n=468)</td><td align="left" valign="bottom">Hypothetical sample (n=533)</td></tr></thead><tbody><tr><td align="left" valign="top">Requested improvement (scale 0 to 4), mean (SD)</td><td align="left" valign="top"/><td align="left" valign="top">&#x2014;<sup><xref ref-type="table-fn" rid="table2fn1">a</xref></sup></td></tr><tr><td align="left" valign="top"><named-content content-type="indent">&#x00A0;&#x00A0;&#x00A0;&#x00A0;</named-content>Less cumbersome login authentication</td><td align="left" valign="top">2.6 (1.0)</td><td align="left" valign="top">&#x2014;</td></tr><tr><td align="left" valign="top"><named-content content-type="indent">&#x00A0;&#x00A0;&#x00A0;&#x00A0;</named-content>More data about my health</td><td align="left" valign="top">3.1 (0.8)</td><td align="left" valign="top">&#x2014;</td></tr><tr><td align="left" valign="top"><named-content content-type="indent">&#x00A0;&#x00A0;&#x00A0;&#x00A0;</named-content>Access to lab and diagnostic imaging results</td><td align="left" valign="top">3.1 (0.8)</td><td align="left" valign="top">&#x2014;</td></tr><tr><td align="left" valign="top"><named-content content-type="indent">&#x00A0;&#x00A0;&#x00A0;&#x00A0;</named-content>Access to data that would allow avoiding care visit</td><td align="left" valign="top">3.1 (0.8)</td><td align="left" valign="top">&#x2014;</td></tr><tr><td align="left" valign="top"><named-content content-type="indent">&#x00A0;&#x00A0;&#x00A0;&#x00A0;</named-content>Question answered via secure message</td><td align="left" valign="top">2.9 (0.9)</td><td align="left" valign="top">&#x2014;</td></tr><tr><td align="left" valign="top"><named-content content-type="indent">&#x00A0;&#x00A0;&#x00A0;&#x00A0;</named-content>General convenience and less waiting in clinic</td><td align="left" valign="top">3.2 (0.8)</td><td align="left" valign="top">&#x2014;</td></tr><tr><td align="left" valign="top">Most preferred features, n (%)</td><td align="left" valign="top">n=468</td><td align="left" valign="top">n=533</td></tr><tr><td align="left" valign="top"><named-content content-type="indent">&#x00A0;&#x00A0;&#x00A0;&#x00A0;</named-content>Ease of communication with family&#x2019;s care providers</td><td align="left" valign="top">68 (15)</td><td align="left" valign="top">165 (31)</td></tr><tr><td align="left" valign="top"><named-content content-type="indent">&#x00A0;&#x00A0;&#x00A0;&#x00A0;</named-content>Ease of scheduling appointments</td><td align="left" valign="top">220 (47)</td><td align="left" valign="top">309 (58)</td></tr><tr><td align="left" valign="top"><named-content content-type="indent">&#x00A0;&#x00A0;&#x00A0;&#x00A0;</named-content>Like to view own lab results</td><td align="left" valign="top">233 (50)</td><td align="left" valign="top">405 (76)</td></tr><tr><td align="left" valign="top"><named-content content-type="indent">&#x00A0;&#x00A0;&#x00A0;&#x00A0;</named-content>Like to view own health information</td><td align="left" valign="top">377 (81)</td><td align="left" valign="top">479 (90)</td></tr><tr><td align="left" valign="top"><named-content content-type="indent">&#x00A0;&#x00A0;&#x00A0;&#x00A0;</named-content>Like to view health information of carees</td><td align="left" valign="top">57 (12)</td><td align="left" valign="top">180 (34)</td></tr><tr><td align="left" valign="top"><named-content content-type="indent">&#x00A0;&#x00A0;&#x00A0;&#x00A0;</named-content>Like to fill out pre-appointment clinical questionnaire</td><td align="left" valign="top">83 (18)</td><td align="left" valign="top">291 (55)</td></tr><tr><td align="left" valign="top"><named-content content-type="indent">&#x00A0;&#x00A0;&#x00A0;&#x00A0;</named-content>Like to record blood pressure for care providers</td><td align="left" valign="top">31 (7)</td><td align="left" valign="top">151 (28)</td></tr><tr><td align="left" valign="top"><named-content content-type="indent">&#x00A0;&#x00A0;&#x00A0;&#x00A0;</named-content>Like to record glucose level for care providers</td><td align="left" valign="top">5 (1)</td><td align="left" valign="top">105 (20)</td></tr><tr><td align="left" valign="top"><named-content content-type="indent">&#x00A0;&#x00A0;&#x00A0;&#x00A0;</named-content>Other</td><td align="left" valign="top">17 (4)</td><td align="left" valign="top">16 (3)</td></tr><tr><td align="left" valign="top">Factors reported in self-reported avoidance of clinic visit, n (%)</td><td align="left" valign="top">n=468</td><td align="left" valign="top">n=533</td></tr><tr><td align="left" valign="top"><named-content content-type="indent">&#x00A0;&#x00A0;&#x00A0;&#x00A0;</named-content>Imaging results discussed by secure message</td><td align="left" valign="top">85 (18)</td><td align="left" valign="top">&#x2014;</td></tr><tr><td align="left" valign="top"><named-content content-type="indent">&#x00A0;&#x00A0;&#x00A0;&#x00A0;</named-content>Question asked by message was answered</td><td align="left" valign="top">117 (25)</td><td align="left" valign="top">&#x2014;</td></tr><tr><td align="left" valign="top"><named-content content-type="indent">&#x00A0;&#x00A0;&#x00A0;&#x00A0;</named-content>Other</td><td align="left" valign="top">20 (4)</td><td align="left" valign="top">&#x2014;</td></tr><tr><td align="left" valign="top">Cost saving by avoiding clinic visit, n (%)</td><td align="left" valign="top">n=468</td><td align="left" valign="top">n= 533</td></tr><tr><td align="left" valign="top"><named-content content-type="indent">&#x00A0;&#x00A0;&#x00A0;&#x00A0;</named-content>Petrol (gasoline)</td><td align="left" valign="top">140 (30)</td><td align="left" valign="top">278 (52)</td></tr><tr><td align="left" valign="top"><named-content content-type="indent">&#x00A0;&#x00A0;&#x00A0;&#x00A0;</named-content>Time off work</td><td align="left" valign="top">187 (40)</td><td align="left" valign="top">3063 (57)</td></tr><tr><td align="left" valign="top"><named-content content-type="indent">&#x00A0;&#x00A0;&#x00A0;&#x00A0;</named-content>Getting childcare</td><td align="left" valign="top">32 (7)</td><td align="left" valign="top">70 (13)</td></tr><tr><td align="left" valign="top"><named-content content-type="indent">&#x00A0;&#x00A0;&#x00A0;&#x00A0;</named-content>Parking</td><td align="left" valign="top">98 (21)</td><td align="left" valign="top">181 (34)</td></tr><tr><td align="left" valign="top"><named-content content-type="indent">&#x00A0;&#x00A0;&#x00A0;&#x00A0;</named-content>Taxi</td><td align="left" valign="top">29 (6)</td><td align="left" valign="top">78 (15)</td></tr><tr><td align="left" valign="top"><named-content content-type="indent">&#x00A0;&#x00A0;&#x00A0;&#x00A0;</named-content>Other</td><td align="left" valign="top">28 (6)</td><td align="left" valign="top">65 (12)</td></tr></tbody></table><table-wrap-foot><fn id="table2fn1"><p><sup>a</sup>Not available.</p></fn></table-wrap-foot></table-wrap><p><xref ref-type="table" rid="table3">Table 3</xref> shows the sample mean for both groups across the different variables, along with the significance level from the aforementioned 2-sample <italic>t</italic>-test. There are three main findings associated with these results.</p><table-wrap id="t3" position="float"><label>Table 3.</label><caption><p>Sample means by group [experienced-based versus hypothetical] with significance level of 2-sample t-test.</p></caption><table id="table3" frame="hsides" rules="groups"><thead><tr><td align="left" valign="bottom">Variable</td><td align="left" valign="bottom">Hypothetical</td><td align="left" valign="bottom">Experience-based</td><td align="left" valign="bottom">Significance</td></tr></thead><tbody><tr><td align="left" valign="top">Use PHR<sup><xref ref-type="table-fn" rid="table3fn1">a</xref></sup> to access my health information</td><td align="left" valign="top">99%</td><td align="left" valign="top">96%</td><td align="left" valign="top">1%</td></tr><tr><td align="left" valign="top">Use PHR to access children&#x2019;s health information</td><td align="left" valign="top">36%</td><td align="left" valign="top">12%</td><td align="left" valign="top">1%</td></tr><tr><td align="left" valign="top">Use PHR to access care health information</td><td align="left" valign="top">32%</td><td align="left" valign="top">9%</td><td align="left" valign="top">1%</td></tr><tr><td align="left" valign="top">Use PHR to access someone else&#x2019;s health information</td><td align="left" valign="top">2%</td><td align="left" valign="top">4%</td><td align="left" valign="top">None</td></tr><tr><td align="left" valign="top">PHRs ease communication with family care providers</td><td align="left" valign="top">31%</td><td align="left" valign="top">15%</td><td align="left" valign="top">1%</td></tr><tr><td align="left" valign="top">PHRs ease scheduling appointments for self/family</td><td align="left" valign="top">58%</td><td align="left" valign="top">47%</td><td align="left" valign="top">1%</td></tr><tr><td align="left" valign="top">PHRs enable viewing own lab results</td><td align="left" valign="top">76%</td><td align="left" valign="top">50%</td><td align="left" valign="top">1%</td></tr><tr><td align="left" valign="top">PHRs enable viewing own health information</td><td align="left" valign="top">90%</td><td align="left" valign="top">81%</td><td align="left" valign="top">1%</td></tr><tr><td align="left" valign="top">PHRs enable viewing care health information</td><td align="left" valign="top">34%</td><td align="left" valign="top">12%</td><td align="left" valign="top">1%</td></tr><tr><td align="left" valign="top">PHRs enable filling out pre-appt clinical questionnaire</td><td align="left" valign="top">55%</td><td align="left" valign="top">18%</td><td align="left" valign="top">1%</td></tr><tr><td align="left" valign="top">PHRs enable recording BP for care providers</td><td align="left" valign="top">28%</td><td align="left" valign="top">7%</td><td align="left" valign="top">1%</td></tr><tr><td align="left" valign="top">PHRs enable recording glucose for care providers</td><td align="left" valign="top">20%</td><td align="left" valign="top">1%</td><td align="left" valign="top">1%</td></tr><tr><td align="left" valign="top">PHRs enable something else</td><td align="left" valign="top">3%</td><td align="left" valign="top">4%</td><td align="left" valign="top">None</td></tr><tr><td align="left" valign="top">PHRs are easy to use</td><td align="left" valign="top">76%</td><td align="left" valign="top">41%</td><td align="left" valign="top">1%</td></tr><tr><td align="left" valign="top">PHRs save time when scheduling appointments</td><td align="left" valign="top">87%</td><td align="left" valign="top">76%</td><td align="left" valign="top">10%</td></tr><tr><td align="left" valign="top">PHRs allow for more convenient communication with care providers</td><td align="left" valign="top">89%</td><td align="left" valign="top">61%</td><td align="left" valign="top">1%</td></tr><tr><td align="left" valign="top">PHR helpfulness rating 0&#x2010;100</td><td align="left" valign="top">74</td><td align="left" valign="top">71</td><td align="left" valign="top">5%</td></tr><tr><td align="left" valign="top">PHR benefit depends on volume of health data</td><td align="left" valign="top">1.00</td><td align="left" valign="top">1.01</td><td align="left" valign="top">None</td></tr><tr><td align="left" valign="top">PHR login frequency depends on volume of health data</td><td align="left" valign="top">0.47</td><td align="left" valign="top">0.72</td><td align="left" valign="top">1%</td></tr><tr><td align="left" valign="top">PHR benefit depends on promptness of data</td><td align="left" valign="top">0.96</td><td align="left" valign="top">0.93</td><td align="left" valign="top">None</td></tr><tr><td align="left" valign="top">PHR login frequency depends on promptness of data</td><td align="left" valign="top">0.58</td><td align="left" valign="top">0.71</td><td align="left" valign="top">5%</td></tr><tr><td align="left" valign="top">PHR has enabled self/family avoiding ER visit</td><td align="left" valign="top">9%</td><td align="left" valign="top">4%</td><td align="left" valign="top">1%</td></tr><tr><td align="left" valign="top">PHR has not enabled self/family avoiding clinic visit</td><td align="left" valign="top">64%</td><td align="left" valign="top">57%</td><td align="left" valign="top">5%</td></tr><tr><td align="left" valign="top">PHR allowing clinic visit avoidance saved petrol</td><td align="left" valign="top">52%</td><td align="left" valign="top">30%</td><td align="left" valign="top">1%</td></tr><tr><td align="left" valign="top">PHR allowing clinic visit avoidance saved work leave</td><td align="left" valign="top">57%</td><td align="left" valign="top">40%</td><td align="left" valign="top">1%</td></tr><tr><td align="left" valign="top">PHR allowing clinic visit avoidance saved childcare</td><td align="left" valign="top">13%</td><td align="left" valign="top">7%</td><td align="left" valign="top">1%</td></tr><tr><td align="left" valign="top">PHR allowing clinic visit avoidance saved parking</td><td align="left" valign="top">34%</td><td align="left" valign="top">21%</td><td align="left" valign="top">1%</td></tr><tr><td align="left" valign="top">PHR allowing clinic visit avoidance saved taxi</td><td align="left" valign="top">15%</td><td align="left" valign="top">6%</td><td align="left" valign="top">1%</td></tr><tr><td align="left" valign="top">PHR allowing clinic visit avoidance saved other</td><td align="left" valign="top">12%</td><td align="left" valign="top">6%</td><td align="left" valign="top">1%</td></tr><tr><td align="left" valign="top">PHR access from desktop/laptop</td><td align="left" valign="top">76%</td><td align="left" valign="top">51%</td><td align="left" valign="top">1%</td></tr><tr><td align="left" valign="top">PHR access from smartphone</td><td align="left" valign="top">64%</td><td align="left" valign="top">62%</td><td align="left" valign="top">None</td></tr><tr><td align="left" valign="top">PHR access from tablet</td><td align="left" valign="top">25%</td><td align="left" valign="top">12%</td><td align="left" valign="top">1%</td></tr><tr><td align="left" valign="top">PHR access no preference</td><td align="left" valign="top">6%</td><td align="left" valign="top">1%</td><td align="left" valign="top">1%</td></tr></tbody></table><table-wrap-foot><fn id="table3fn1"><p><sup>a</sup>PHR: patient health record.</p></fn></table-wrap-foot></table-wrap></sec></sec><sec id="s4" sec-type="discussion"><title>Discussion</title><sec id="s4-1"><title>Principal Findings</title><p>This study examined factors influencing user satisfaction with PHRs among a nationally representative sample of adults in the United Kingdom. Two groups were compared&#x2014;those with PHR experience and those without&#x2014;to explore both lived and hypothetical perspectives on digital health record use. Demographically, the groups were comparable, indicating that observed differences in satisfaction and expectations primarily reflect PHR exposure rather than underlying population differences.</p><p>Overall, adults in the United Kingdom expressed strong support for access to their personal health information. Experienced users reported that PHRs were generally easy to use, time-saving, and useful for managing appointments, while nonusers anticipated similar benefits if they had access. These findings are consistent with evidence from other contexts demonstrating that PHR adoption enhances satisfaction, engagement, and communication with health care providers [<xref ref-type="bibr" rid="ref4">4</xref>,<xref ref-type="bibr" rid="ref6">6</xref>,<xref ref-type="bibr" rid="ref12">12</xref>,<xref ref-type="bibr" rid="ref13">13</xref>]. The results also mirror those from Canada [<xref ref-type="bibr" rid="ref12">12</xref>], where PHR access was associated with improved efficiency and reduced appointment rates. However, users in the United Kingdom rated usability slightly lower than Canadian respondents, which may reflect differences in the maturity of the platforms, user training, and integration across healthcare systems [<xref ref-type="bibr" rid="ref2">2</xref>,<xref ref-type="bibr" rid="ref5">5</xref>,<xref ref-type="bibr" rid="ref20">20</xref>].</p></sec><sec id="s4-2"><title>Comparison With Prior Work</title><p>Our results align with prior literature indicating that PHR usability, data accessibility, and perceived time savings are central determinants of satisfaction [<xref ref-type="bibr" rid="ref3">3</xref>,<xref ref-type="bibr" rid="ref4">4</xref>,<xref ref-type="bibr" rid="ref6">6</xref>,<xref ref-type="bibr" rid="ref17">17</xref>]. Participants with PHR experience valued the ability to view their own health and laboratory information, schedule appointments, and communicate with care providers&#x2014;features frequently cited as key enablers of digital engagement [<xref ref-type="bibr" rid="ref6">6</xref>,<xref ref-type="bibr" rid="ref9">9</xref>,<xref ref-type="bibr" rid="ref16">16</xref>]. These findings correspond with previous systematic reviews highlighting that patient portals improve convenience and empower users to manage their own health [<xref ref-type="bibr" rid="ref4">4</xref>,<xref ref-type="bibr" rid="ref5">5</xref>,<xref ref-type="bibr" rid="ref7">7</xref>]. In contrast, our respondents rated United Kingdom systems slightly less favorably than those in comparable studies from Canada or the United States, suggesting ongoing challenges related to user interface design and interoperability within the NHS infrastructure [<xref ref-type="bibr" rid="ref2">2</xref>,<xref ref-type="bibr" rid="ref15">15</xref>,<xref ref-type="bibr" rid="ref20">20</xref>].</p><p>Participants without prior experience tended to overestimate potential benefits and functionalities, a trend documented in earlier research on digital health optimism and hypothetical bias [<xref ref-type="bibr" rid="ref10">10</xref>,<xref ref-type="bibr" rid="ref15">15</xref>,<xref ref-type="bibr" rid="ref16">16</xref>]. Woods et al [<xref ref-type="bibr" rid="ref10">10</xref>] and Cunningham et al [<xref ref-type="bibr" rid="ref16">16</xref>] found similar patterns of expectation inflation among new users of health portals, often due to limited understanding of actual system capabilities. Such insights underscore the importance of managing user expectations during onboarding and designing transparent communication strategies to clarify what PHRs can&#x2014;and cannot&#x2014;do.</p><p>In line with other studies, both experienced and hypothetical users viewed PHRs as tools that could reduce unnecessary clinical visits and associated costs such as travel, parking, and time off work [<xref ref-type="bibr" rid="ref12">12</xref>,<xref ref-type="bibr" rid="ref13">13</xref>,<xref ref-type="bibr" rid="ref17">17</xref>]. This perception supports previous evidence that digital access to records can improve service efficiency and convenience for patients [<xref ref-type="bibr" rid="ref4">4</xref>,<xref ref-type="bibr" rid="ref7">7</xref>,<xref ref-type="bibr" rid="ref9">9</xref>]. However, real-world data often indicate more modest effects, emphasizing the need for longitudinal studies assessing actual behavioral and economic outcomes [<xref ref-type="bibr" rid="ref4">4</xref>,<xref ref-type="bibr" rid="ref5">5</xref>].</p><p>Those with PHR experience expressed a desire for expanded functionality, greater interoperability, and simplified authentication&#x2014;issues also raised by Turner et al [<xref ref-type="bibr" rid="ref17">17</xref>] and Schneider et al [<xref ref-type="bibr" rid="ref8">8</xref>], who highlighted the importance of usability and integration with existing clinical workflows. Improved personalisation, data richness, and accessibility were repeatedly mentioned, echoing prior calls for more inclusive and user-centered portal design [<xref ref-type="bibr" rid="ref3">3</xref>,<xref ref-type="bibr" rid="ref6">6</xref>,<xref ref-type="bibr" rid="ref9">9</xref>,<xref ref-type="bibr" rid="ref23">23</xref>].</p><p>From a policy perspective, the comparison between users and nonusers contributes new insights to the literature. While most previous studies focus solely on active users, our inclusion of a nationally representative sample allows for broader generalization. This approach complements earlier research that used local or condition-specific samples [<xref ref-type="bibr" rid="ref8">8</xref>,<xref ref-type="bibr" rid="ref16">16</xref>,<xref ref-type="bibr" rid="ref17">17</xref>]. As digital transformation accelerates across the NHS, understanding perceptions among both users and nonusers is crucial for equitable and scalable implementation [<xref ref-type="bibr" rid="ref15">15</xref>,<xref ref-type="bibr" rid="ref18">18</xref>,<xref ref-type="bibr" rid="ref20">20</xref>].</p><p>Finally, our findings align with recent studies demonstrating that both system and patient factors strongly predict portal use and satisfaction. Agrawal et al [<xref ref-type="bibr" rid="ref24">24</xref>] reported that usability, system reliability, and patient demographics influence electronic medical record engagement. Ndabu et al [<xref ref-type="bibr" rid="ref23">23</xref>] observed that access type and age group significantly affect portal breadth of use, highlighting digital literacy and inclusivity as enduring challenges. Moreover, Whittemore et al [<xref ref-type="bibr" rid="ref25">25</xref>] showed that targeted interventions can increase patient portal use among adults with type 2 diabetes, particularly when support is localized and tailored to patient needs. Collectively, these studies reinforce our conclusion that user experience, accessibility, and system design remain the primary drivers of satisfaction and long-term adoption.</p></sec><sec id="s4-3"><title>Strengths and Limitations</title><p>Strengths include national representativeness and parallel assessment of users and nonusers. This is among the first nationally representative analyses of PHR satisfaction in the United Kingdom. It uniquely contrasts real and hypothetical users, offering insights into both actual experiences and potential barriers to uptake.</p><p>In terms of the limitations, first, the study&#x2019;s cross-sectional design limits causal inference. Second, older age groups (60&#x2010;69 and &#x2265; 70 y) were under-represented in the sample, which may affect generalizability, particularly regarding digital literacy and accessibility. Third, hypothetical responses may reflect &#x201C;hypothetical bias,&#x201D; where participants without prior experience imagine more positive outcomes. Fourth, participation was voluntary, raising the possibility of self-selection bias toward more digitally engaged individuals. Finally, all measures were self-reported, and experience was not verified independently. Future research could employ longitudinal designs and link survey data with usage metrics to validate self-reports.</p><p>Second, education level and household income were not available as stratification or analytic variables within the nationally representative panel profiles used for recruitment. As socioeconomic status may influence digital access, health literacy, and engagement with patient-facing technologies, future studies should incorporate education and income measures where feasible to further refine equity-related insights.</p></sec><sec id="s4-4"><title>Conclusions</title><p>United Kingdom adults&#x2014;both users and nonusers&#x2014;demonstrate a strong interest in accessing their health data electronically. Experienced users report time and cost savings, while nonusers anticipate similar benefits. However, nonusers&#x2019; expectations often exceed current system capabilities, highlighting opportunities for continued system improvement and patient education. Ongoing evaluation of the NHS App and similar platforms will be crucial to achieving equitable, efficient, and user-centered digital health access in the United Kingdom.</p></sec></sec></body><back><ack><p>We thank all survey participants. No external funding was received.</p></ack><notes><sec><title>Funding</title><p>The authors declared no financial support was received for this work.</p></sec></notes><fn-group><fn fn-type="conflict"><p>OA is a board member and shareholder of Patients Know Best; direct family members are also shareholders.</p></fn></fn-group><glossary><title>Abbreviations</title><def-list><def-item><term id="abb1">EMR</term><def><p>electronic medical record</p></def></def-item><def-item><term id="abb2">MANOVA</term><def><p>multivariate analysis of variance</p></def></def-item><def-item><term id="abb3">NHS</term><def><p>National Health Service</p></def></def-item><def-item><term id="abb4">PHR</term><def><p>patient health record</p></def></def-item></def-list></glossary><ref-list><title>References</title><ref id="ref1"><label>1</label><nlm-citation citation-type="report"><person-group person-group-type="author"><collab>Canada Health Infoway</collab></person-group><article-title>Patient access to health information</article-title><access-date>2022-02-01</access-date><comment><ext-link ext-link-type="uri" xlink:href="https://insights.infoway-inforoute.ca/2022-patient-access-to-health-information/">https://insights.infoway-inforoute.ca/2022-patient-access-to-health-information/</ext-link></comment></nlm-citation></ref><ref id="ref2"><label>2</label><nlm-citation citation-type="journal"><person-group person-group-type="author"><name name-style="western"><surname>Rigby</surname><given-names>M</given-names> </name><name name-style="western"><surname>Georgiou</surname><given-names>A</given-names> </name><name name-style="western"><surname>Hypp&#x00F6;nen</surname><given-names>H</given-names> </name><etal/></person-group><article-title>Patient portals as a means of information and communication technology support to patient- centric care coordination - the missing evidence and the challenges of evaluation. 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