Journal of Occupational and Environmental Medicine

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name="wkhealth_issue" content="8" /><meta name="wkhealth_article_publication_date" content="April 19, 2024" /><meta name="wkhealth_volume" content="66" /><meta name="wkhealth_ovid_accession_number" content="00043764-202408000-00003" /><meta name="wkhealth_issn" content="1076-2752" /><meta name="wkhealth_title" content="Unmet Mental Health Needs Among California Workers Since the Start of the COVID-19 Pandemic" /><meta name="wkhealth_authors" content="Gibb, Kathryn;Bui, David P.;Cox, Jonah;Watmore, Nichole;Vergara, Ximena P." /><meta name="wkhealth_doi" content="10.1097/JOM.0000000000003123" /><meta name="wkhealth_abstract_html_url" content="https://journals.lww.com/joem/abstract/2024/08000/unmet_mental_health_needs_among_california_workers.3.aspx" /><meta name="wkhealth_fulltext_html_url" content="https://journals.lww.com/joem/fulltext/2024/08000/unmet_mental_health_needs_among_california_workers.3.aspx" /><meta name="wkhealth_toc_section" content="ORIGINAL ARTICLES" /><meta name="wkhealth_toc_sub_section" /><meta name="wkhealth_eJpId" content="joem:2024:08000:00003" /><meta name="wkhealth_firstpage" content="622" /><meta name="wkhealth_date" content="August 2024" /><meta name="wkhealth_pdf_url" content="https://journals.lww.com/joem/_layouts/15/oaks.journals/downloadpdf.aspx?trckng_src_pg=Other&an=00043764-202408000-00003" /><meta name="Description" content="Objective We sought to identify worker groups with high prevalence of unmet mental health needs t" /><meta property="og:site_name" content="LWW" /><meta property="og:type" content="article" /><meta property="og:title" content="Unmet Mental Health Needs Among California Workers Since... : Journal of Occupational and Environmental Medicine" /><meta property="og:description" content="he start of the COVID-19 pandemic using the California Health Interview Survey data from 2013 to 2021. Results In 2021, 23.4% (confidence interval: 22.4 to 24.4) reported unmet mental health needs, an absolute increase of 3.9% from 2019. Relative increases were highest among workers in the information industries (prevalence ratio: 1.89, confidence interval: 1.4 to 2.5) and older workers (prevalence ratio: 1.27, CI: 0.9 to 1.8). Increases in needing help were not met with comparable increases in seeking care. Conclusions Unmet mental health needs increased for California workers during the pandemic. Employers should dedicate resources and implement strategies to increase access to care and promote worker well-being...." /><meta property="og:image" content="https://images.journals.lww.com/joem/SocialThumb.00043764-202408000-00003.F1.jpeg" /><meta property="og:image:width" content="1200" /><meta property="og:image:height" content="631" /><meta property="og:url" content="https://journals.lww.com/joem/fulltext/2024/08000/unmet_mental_health_needs_among_california_workers.3.aspx" /><meta property="twitter:card" content="summary" /><meta name="robots" content="index, follow, noarchive" /><meta name="WT.sv" content="ZUSE1PEJPWEB06" /><meta name="Title" content="Journal of Occupational and Environmental Medicine" /><style id="SPThemeHideForms" type="text/css">body {opacity:0 !important}</style>  <link href="https://fonts.googleapis.com/css?family=Arvo:400,400i,700|Fira+Sans:300,300i,400,400i,500,500i,600,600i,700,700i&display=swap" rel="stylesheet" /> <script> // temporary workaround for Bug 316328:[Stage][Registration][Regression 05.04] - Omniture events are not displayed for article viewer page // prevents JS exception in Adobe launch.js caused by situation when wkhealth_institution_type meta tag is present while wkhealth_institution_name tag is not in the page head // see this check in Adobe launch.js: null != document.querySelector("meta[name='wkhealth_institution_name']") ... // TODO: implement proper code fix after release 05.04.00 deployment var wkhealth_institution_type = document.querySelector("meta[name='wkhealth_institution_type']"); var wkhealth_institution_name = document.querySelector("meta[name='wkhealth_institution_name']"); console.warn(wkhealth_institution_type); console.warn(wkhealth_institution_name); if (wkhealth_institution_type && !wkhealth_institution_name) { console.warn('Workaround in release 05.04.00 - removing wkhealth_institution_type meta tag if wkhealth_institution_name is not present'); wkhealth_institution_type.remove(); } </script> 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Bui, Jonah Cox, et al', '66', '8', 'Copyright \u00A9 2024 American College of Occupational and Environmental Medicine', '00043764-202408000-00003', '', true, ''); } </script> <div id="ArticleContainer"> <article id="ej-article-view" class="js-article-view ej-article-view" xmlns:ssr="http://ssr-eus-go-csi.cloudapp.net/v1/assets" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:xhtml="http://www.w3.org/1999/xhtml"><section class="ejp-r-article-subsection"><div class="ejp-r-article-subsection__text">ORIGINAL ARTICLES</div></section><header class="ejp-article-header"><h1 class="ejp-article-title">Unmet Mental Health Needs Among California Workers Since the Start of the COVID-19 Pandemic</h1></header><section id="ejp-article-authors"><p id="P7"><i class="wki icon-orcid" onclick="javascript:ToolTip_Orcid('Gibb, Kathryn MPH', 'https://orcid.org/0000-0002-6044-5867');" onmouseover="javascript:ToolTip_Orcid('Gibb, Kathryn MPH', 'https://orcid.org/0000-0002-6044-5867');"></i>Gibb, Kathryn MPH; <i class="wki icon-orcid" onclick="javascript:ToolTip_Orcid('Bui, David P. PhD', 'https://orcid.org/0000-0003-0861-0850');" onmouseover="javascript:ToolTip_Orcid('Bui, David P. PhD', 'https://orcid.org/0000-0003-0861-0850');"></i>Bui, David P. PhD; <i class="wki icon-orcid" onclick="javascript:ToolTip_Orcid('Cox, Jonah PhD', 'https://orcid.org/0000-0001-7044-9645');" onmouseover="javascript:ToolTip_Orcid('Cox, Jonah PhD', 'https://orcid.org/0000-0001-7044-9645');"></i>Cox, Jonah PhD; <i class="wki icon-orcid" onclick="javascript:ToolTip_Orcid('Watmore, Nichole MPH', 'https://orcid.org/0009-0002-9969-514X');" onmouseover="javascript:ToolTip_Orcid('Watmore, Nichole MPH', 'https://orcid.org/0009-0002-9969-514X');"></i>Watmore, Nichole MPH; <i class="wki icon-orcid" onclick="javascript:ToolTip_Orcid('Vergara, Ximena P. PhD', 'https://orcid.org/0000-0002-7719-8399');" onmouseover="javascript:ToolTip_Orcid('Vergara, Ximena P. PhD', 'https://orcid.org/0000-0002-7719-8399');"></i>Vergara, Ximena P. PhD</p><section><a href="#" id="ejp-article-authors-link"> Author Information <i class="wk-icon-arrow-down-r"></i></a></section></section><section id="ejp-article-authors-info" class="ejp-article-authors-info ejp-article-authors-info--hidden"><div class="ejp-article-authors-info-holder"> <p id="">From the Occupational Health Branch, California Department of Public Health, Richmond California (K.G., D.P.B., X.P.V.); Heluna Health, City of Industry, California (D.P.B., X.P.V.); and Injury and Violence Prevention Branch, California Department of Public Health, Sacramento, California (J.C., N.W.).</p> <p id="">Institution at Which the Work Was Performed: Occupational Health Branch, California Department of Public Health, Richmond, CA.</p> <p id="">This project was supported by the California Department of Public Health, with funding from the Centers for Disease Control and Prevention, Epidemiology and Laboratory Capacity for Infectious Diseases, Cooperative Agreement Number 6 NU50CK000539.</p> <p id="">Conflict of interest: None declared.</p> <p id="">Author Contributions: Kathryn Gibb, David Bui, and Ximena Vergara conceptualized the study design and analysis plan. Kathryn Gibb and David Bui analyzed the data. Kathryn Gibb, David Bui, Jonah Cox, and Nichole Watmore interpreted the results. Kathryn Gibb drafted the manuscript. David Bui, Jonah Cox, Nichole Watmore, and Ximena Vergara provided feedback and edited the manuscript. Ximena Vergara supervised the work. All authors reviewed, revised, and approved the manuscript. Kathryn Gibb agrees to be accountable for investigating and resolving questions related to the accuracy and integrity of the work.</p> <p id="">Data Availability: The California Department of Public Health does not have permission to release our funder file data. Aggregate-level, public use files of CHIS data can be accessed through the ASK CHIS Web site.</p> <p id="">Disclaimer: The findings and conclusions in this article are those of the authors and do not necessarily represent the views or opinions of the California Department of Public Health or the California Health and Human Services Agency.</p> <p id="">Ethical Considerations: The California Health and Human Services Agency's Committee for the Protection of Human Subjects determined this project to be nonresearch because the activities involved public health practice/surveillance.</p> <p id="corr1">Address correspondence to: Kathryn Gibb, MPH, Occupational Health Branch, California Department of Public Health, 850 Marina Bay Pkwy, Bldg. P-3, Richmond, CA 94804 (<span><a href="/cdn-cgi/l/email-protection#214c40484d554e1b6a40554953584f0f6648434361424551490f42400f464e57" onclick="javascript:window.open('mailto:mailto:Kathryn.Gibb@cdph.ca.gov');return false"><span class="__cf_email__" data-cfemail="3873594c504a4156167f515a5a785b5c4850165b59165f574e">[email protected]</span></a></span>).</p> </div></section><section id="article-journal-info"><div class="ej-journal-info"><span class="ej-journal-name">Journal of Occupational and Environmental Medicine </span><span id="ej-journal-date-volume-issue-pg"><a href="/joem/toc/2024/08000">66(8):p 622-629, August 2024.</a></span><span> | </span><span class="ej-journal-doi">DOI: </span>10.1097/JOM.0000000000003123</div></section><section id="ejp-article-indicators" class="ejp-article-indicators"><ul class="ejp-article-indicators__list"> <li id="ej-article-indicators-free" class="ejp-article-indicators__list-item" onmouseover="javascript:Tooltip_Free()" onmouseout="javascript:Tooltip_MouseOut()"><span class="ejp-indicator">Free</span></li> <li id="ej-article-indicators-imageabstract" class="ejp-article-indicators__list-item" onmouseover="javascript:Tooltip_ImageAbstract()" onmouseout="javascript:Tooltip_MouseOut()"><span class="ejp-indicator">Infographic</span></li> </ul><button id="openArticleMetricsPopupButton" type="button" class="wk-button wk-button-ghost wk-button-icon-left ejp-article-metrics-btn" data-articleMetricsEndpoint="//services.journals.lww.com/IntegrationServices/ArticleMetricsService.svc" data-articleMetricsDetailsUrl="https://wolterskluwer.altmetric.com/details/" data-doi="10.1097/JOM.0000000000003123" data-suiteId="vrs_woltere_journalsglobalvrs" data-articlePublicationDate="2024-04-19" data-articlePublicationDateString="April 19, 2024" data-receivedDate="" data-revisionReceivedDate="" data-acceptedDate="" data-crossrefRefLinkRoot="https://doi.org/" data-medlineRefLinkRoot="http://www.ncbi.nlm.nih.gov/pubmed/" data-pubMedId="38640942"><i class="wk-icon-filled-chart-r"></i><i class="wk-icon-filled-chart-white-r"></i> Metrics </button></section><section class="ejp-article-tabs" id="abstractWrap"><div class="ejp-article-tabs__tablist" role="tablist" aria-label="Tabs"><button class="ejp-article-tabs__tablist-item" role="tab" aria-selected="false" aria-controls="panel1" id="tab1" tabIndex="0">Abstract</button><button class="ejp-article-tabs__tablist-item" role="tab" aria-selected="false" aria-controls="panel2" id="tab2" tabIndex="0">In Brief</button><hr class="ejp-article-tabs__tablist-slider" style="left: 0;"> </div> <div class="ejp-article-tabs__tabpanel" id="panel1" role="tabpanel" aria-labelledby="tab1"> <div id="article-abstract-content1"> <div class="ejp-article-text-abstract"> <h3>Objective </h3> <p>We sought to identify worker groups with high prevalence of unmet mental health needs to inform employer benefits programs and outreach to increase access to care.</p> <h3>Methods </h3> <p>We conducted a repeated cross-sectional study to understand unmet mental health needs among workers since the start of the COVID-19 pandemic using the California Health Interview Survey data from 2013 to 2021.</p> <h3>Results </h3> <p>In 2021, 23.4% (confidence interval: 22.4 to 24.4) reported unmet mental health needs, an absolute increase of 3.9% from 2019. Relative increases were highest among workers in the information industries (prevalence ratio: 1.89, confidence interval: 1.4 to 2.5) and older workers (prevalence ratio: 1.27, CI: 0.9 to 1.8). Increases in needing help were not met with comparable increases in seeking care.</p> <h3>Conclusions </h3> <p>Unmet mental health needs increased for California workers during the pandemic. Employers should dedicate resources and implement strategies to increase access to care and promote worker well-being.</p> </div> <div class="ejp-article-graphical-abstract" id=""> <div class="ejp-article-graphical-abstract-container"> <p id="JCL-P-12"><section class="ejp-r-article-images"><figure class="ejp-r-article-images__figure"><a href="/_layouts/oaks.journals/ImageView.aspx?k=joem:2024:08000:00003&i=ga&year=2024&issue=08000&article=00003" target="_blank" class="ejp-r-article-images__image-link"><img class="ejp-r-article-images__img js-lazy-load lazy-load" src="javascript:void(0);" data-src="https://images.journals.lww.com/joem/GAPreview.00043764-202408000-00003.ga.jpeg" data-srcset="https://images.journals.lww.com/joem/GAPreview@2.00043764-202408000-00003.ga.jpeg 2x" srcset="" alt="Abstract"></a></figure></section><a class="ejp-article-graphical-abstract__export-link" href="/_layouts/OAKS.Journals/ImageInfoService.svc/GetImagePptx/joem/2024/08000/00003/ga" aria-label="Download image graphical abstract as ppt"><i class="icon-powerpoint"></i> Export </a></p> </div> </div> </div> </div> <div class="ejp-article-tabs__tabpanel" id="panel2" role="tabpanel" aria-labelledby="tab2" hidden=""> <div id="article-abstract-content2"> <p>This article on unmet mental health needs among California workers sheds light on the changes in mental health needs and service utilization since the start of the pandemic. This article reminds occupational medicine clinicians that mental health is a key component of worker well-being.</p> </div> </div></section><div class="ejp-fulltext-content js-ejp-fulltext-content"><section id="ArticleBody"><article class="article-boxed-text"><h4 class="ejp-article-outline-heading" data-level="3" id="JCL5">LEARNING OUTCOMES</h4> <ul id="JCL5-2" class="wk-article__list wk-article__list--bullet"> <li class="wk-article__list-item wk-article__list-item--bullet">Upon reviewing this article, readers will understand how unmet mental health needs have changed among California workers during the COVID-19 pandemic.</li> <li class="wk-article__list-item wk-article__list-item--bullet">Upon reviewing this article, readers will be able to describe disparities in unmet mental health needs among California workers in different industries and demographic groups.</li> </ul></article><p id="JCL-P-15">The role of mental health in worker well-being has garnered increasing attention in recent years.<sup><a class="ejp-citation-link js-ejp-citation-link" data-reference-links="bib1">1</a></sup> Work-related stressors, job insecurity, and inadequate work-life balance can contribute to the poor mental health of workers.<sup><a class="ejp-citation-link js-ejp-citation-link" data-reference-links="bib2 bib3 bib4">2–4</a></sup> The COVID-19 pandemic introduced new challenges for workers; in addition to risk of exposure to the SARS-CoV-2 virus at work and elsewhere, the pandemic led to economic instability, social isolation due to remote work, and changes in work environments, all of which impacted workers’ mental health.<sup><a class="ejp-citation-link js-ejp-citation-link" data-reference-links="bib3 bib5 bib6 bib7 bib8">3,5–8</a></sup> While the pandemic exacerbated mental health issues, it also reduced access to services; intermittent clinic closures and stay-at-home orders in conjunction with provider shortages disrupted access to mental health care.<sup><a class="ejp-citation-link js-ejp-citation-link" data-reference-links="bib9 bib10 bib11">9–11</a></sup> Patients often delayed seeking elective care, possibly due to fear of contracting COVID-19 in health care settings.<sup><a class="ejp-citation-link js-ejp-citation-link" data-reference-links="bib12 bib13">12,13</a></sup> Although telehealth services emerged as a viable alternative to in-person services, disparities in technology access, including reliable Internet connectivity, and disparities in flexible work arrangements likely magnified existing inequities in access to care.<sup><a class="ejp-citation-link js-ejp-citation-link" data-reference-links="bib14 bib15">14,15</a></sup> Moreover, pandemic-related layoffs led to loss of employer-based health insurance, and lack of behavioral health care insurance coverage can be a barrier to accessing affordable mental health care services.<sup><a class="ejp-citation-link js-ejp-citation-link" data-reference-links="bib16">16</a></sup></p> <p id="JCL-P-16">Existing unmet mental health needs likely worsened due to pandemic-related barriers to care. Prepandemic findings suggest that approximately 6% of US adults were unable to get needed mental health treatment, with cost being a barrier for approximately a third of adults with unmet need.<sup><a class="ejp-citation-link js-ejp-citation-link" data-reference-links="bib17">17</a></sup> Sociodemographic differences in need of and access to mental health care services have been described elsewhere<sup><a class="ejp-citation-link js-ejp-citation-link" data-reference-links="bib18">18</a></sup>; it is possible that disparities in unmet need exist across worker groups. The consequences of unmet mental health needs can be severe, including more serious mental health issues, increased health care costs, and work-related factors such as decreased productivity.<sup><a class="ejp-citation-link js-ejp-citation-link" data-reference-links="bib19">19</a></sup> For workers, when mental health issues go untreated, there is potential for increased absenteeism, burnout, higher turnover, productivity loss, and decreased job performance.<sup><a class="ejp-citation-link js-ejp-citation-link" data-reference-links="bib20 bib21">20,21</a></sup></p> <p id="JCL-P-17">Despite the mental health impacts of the COVID-19 pandemic, little is known about which worker groups have sought care for mental, emotional, or alcohol and drug problems during the pandemic. Although there is some evidence that essential workers experienced increased rates of anxiety and depression,<sup><a class="ejp-citation-link js-ejp-citation-link" data-reference-links="bib7 bib22 bib23">7,22,23</a></sup> it remains unclear whether these workers sought mental health care. The burden of poor mental health and access to care may not be evenly distributed among workers. Addressing worker disparities in mental health outcomes and access to services requires understanding the distribution of unmet mental health needs by worker group. Understanding which occupations and industries have the greatest unmet need for mental health services can inform employer benefits programs and worker outreach about access to care. We sought to address this knowledge gap by examining the extent of unmet mental health needs among California workers since the start of the COVID-19 pandemic using the California Health Interview Survey (CHIS) data. We evaluated the prevalence of unmet mental health needs among California workers and examined changes associated with the COVID-19 pandemic.</p> <h2 class="ejp-article-outline-heading" data-level="1" id="JCL6">METHODS</h2> <p id="JCL-P-18">We conducted a repeated cross-sectional study using data from CHIS from 2013 to 2021. CHIS is the largest state health survey in the country and monitors the health of Californians over time. Over 20,000 Californians are interviewed per year. CHIS is a Web and telephone survey that is designed to be representative of California’s residential, noninstitutionalized population. CHIS collects data annually on a range of health topics and has collected industry and occupation data since 2013. Additional details on survey methodology, sampling, and questionnaires can be found on the University of California, Los Angeles Center for Health Policy Web site.<sup><a class="ejp-citation-link js-ejp-citation-link" data-reference-links="bib24">24</a></sup></p> <p id="JCL-P-19">Our study population was California workers, defined as adult respondents who said that they currently or usually work at the time of survey, including both full-time and part-time workers, from 2013 to 2021. We excluded military workers from our analyses, as CHIS is not designed to sample individuals residing in institutional settings, including military bases. CHIS is uniquely positioned to track mental health care services utilization, as CHIS asks whether respondents sought care from a primary care provider or other professional for mental, emotional, drug, or alcohol problems. In addition, CHIS has indicators for psychological distress and asks whether respondents felt they needed to see a professional for a mental, emotional, drug, or alcohol problem.</p> <p id="JCL-P-20">Our outcome of unmet mental health need was defined as those who either perceived needing help or who reported moderate to severe psychological distress in the past year and who responded “no” to the care-seeking questions. We created our unmet need outcome by integrating four different CHIS variables. We identified respondents with mental health need based on whether respondents reported “yes” to “Was there ever a time during the past 12 months when you felt that you might need to see a professional because of problems with your mental health, emotions, or nerves or your use of alcohol or drugs?” or whether respondents reported moderate to severe psychological distress in the past year. Reporting psychological distress in the past year was assessed by respondent values for the Kessler Scale (K6), a validated measure of psychological distress. We defined moderate to severe psychological distress as a K6 value of >8, as was defined in another CHIS publication<sup><a class="ejp-citation-link js-ejp-citation-link" data-reference-links="bib25">25</a></sup> as having a mental health need. We used the following two CHIS questions to determine whether respondents sought help for concerns: “In the past 12 months, have you seen your primary care physician or general practitioner for problems with your mental health, emotions, nerves, or your use of alcohol or drugs?” “In the past 12 months have you seen any other professional, such as a counselor, psychiatrist, or social worker for problems with your mental health, emotions, nerves, or your use of alcohol or drugs?”</p> <p id="JCL-P-21">We assessed the prevalence of unmet mental health needs by demographic variables including sex (male, female), age (18 to 29, 30 to 44, 45 to 64, 65+), race/ethnicity (Hispanic, non-Hispanic [NH] White, NH Black, NH Asian, other), disability, insurance status, annual household income, educational attainment, and industry and occupation major group categories (Census 2010 classification schema). Other race comprised American Indian/Alaska Native, Native Hawaiian/Pacific Islander, and two or more races; we collapsed these categories due to small cell sizes.</p> <p id="JCL-P-22">We created a binary pandemic indicator variable; CHIS data from 2020 and 2021 were deemed pandemic years, whereas CHIS data from 2013 to 2019 were considered nonpandemic.</p> <h3 class="ejp-article-outline-heading" data-level="2" id="JCL7">Statistical Analysis</h3> <p id="JCL-P-23">We used replicate survey weights provided by CHIS and jackknife method variance estimation to calculate standard errors and prevalence estimates. We generated survey-weighted annual prevalence estimates and Korn-Graubard 95% confidence intervals (CIs) for each mental health outcome and demographic group. All of the estimates we present are weighted unless specified otherwise.</p> <p id="JCL-P-24">To assess the impact of the COVID-19 pandemic on unmet mental health needs, we applied previously described methods<sup><a class="ejp-citation-link js-ejp-citation-link" data-reference-links="bib7">7</a></sup> to examine the absolute changes in prevalence of unmet needs from 2019 to 2021 for all adults. We used survey-weighted <em xmlns:mrws="http://webservices.ovid.com/mrws/1.0">t</em> tests to assess changes by working status, industry, occupation, and other demographic groups. Because changes in unmet mental health needs may have been influenced by historical trends, we employed trend-adjusted quasi-Poisson regression models to account for previous trends to estimate the change in unmet mental health needs due to the COVID-19 pandemic.<sup><a class="ejp-citation-link js-ejp-citation-link" data-reference-links="bib7">7</a></sup> In our models, the count of unmet mental health needs was our dependent variable, and our pandemic indicator variable was our independent variable. Time (ie, trend) was modeled quadratically (if there was evidence on nonlinear trend) or linearly in final models, which we determined using log-likelihood ratio tests. When our time trend coefficients were not statistically significant (<em xmlns:mrws="http://webservices.ovid.com/mrws/1.0">P</em> > 0.05), indicating no trend, we report results from an intercept only model. The pandemic indicator coefficient, when exponentiated, is interpreted as an adjusted prevalence ratio (PR), estimating the relative change in prevalence of unmet mental health needs during pandemic years of 2020 to 2021, compared with the prevalence we would expect to see had prepandemic (2013 to 2019) trends continued. We report PRs adjusted for prepandemic trends with 95% CI for all outcomes.</p> <h3 class="ejp-article-outline-heading" data-level="2" id="JCL8">Priority Industry Groups</h3> <p id="JCL-P-25">To frame our results, we defined priority industry groups as those with a higher-than-average prevalence of unmet mental health needs in 2021 and that experienced increases (PR > 1) from 2019 after adjusting for prepandemic trends. Statistical analyses were conducted using R statistical software (v 4.1.0) and the R “survey” package.<sup><a class="ejp-citation-link js-ejp-citation-link" data-reference-links="bib26">26</a></sup></p> <h3 class="ejp-article-outline-heading" data-level="2" id="JCL9">Ethical Considerations</h3> <p id="JCL-P-26">The California Health and Human Services Agency’s Committee for the Protection of Human Subjects determined this project to be nonresearch because the activities involved public health practice/surveillance.</p> <h2 class="ejp-article-outline-heading" data-level="1" id="JCL10">RESULTS</h2> <p id="JCL-P-27">CHIS surveyed 193,221 respondents from 2013 to 2021, of which 102,766 were workers. The sociodemographic characteristics of our study population in 2020 and 2021 can be found in <a href="#T1">Table 1</a>. Compared with nonworkers, workers were predominantly male and Hispanic/Latino, had earned at least a college degree, and came from high-income households (<a href="#T1">Table 1</a>).</p> <div class="wk-clearfix-article-table"></div> <div class="article-table"><a id="T1"></a><div class="article-table-title"><span>TABLE 1 - </span> Sociodemographic Characteristics of Study Population<em class="fa fa-arrows-alt expand-button js-expand-table-event" aria-label="expand table"></em><div class="clearfix"></div> </div> <div class="scroll-message"></div> <div class="dummy-scroll"> <div></div> </div> <div class="article-table-body"> <div class="article-table-container"> <table> <thead xmlns="http://www.w3.org/1999/xhtml"> <tr valign="top"> <th rowspan="4" colspan="1" /> <th align="center" colspan="4" rowspan="1">COVID-19 Pandemic Years</th> </tr> <tr valign="top"> <th align="center" colspan="2" rowspan="1">2020</th> <th align="center" colspan="2" rowspan="1">2021</th> </tr> <tr valign="top"> <th align="center" rowspan="1" colspan="1">Workers</th> <th align="center" rowspan="1" colspan="1">Nonworkers</th> <th align="center" rowspan="1" colspan="1">Workers</th> <th align="center" rowspan="1" colspan="1">Nonworkers</th> </tr> <tr valign="top"> <th align="center" rowspan="1" colspan="1">Weighted % (CI)</th> <th align="center" rowspan="1" colspan="1">Weighted % (CI)</th> <th align="center" rowspan="1" colspan="1">Weighted % (CI)</th> <th align="center" rowspan="1" colspan="1">Weighted % (CI)</th> </tr> </thead> <tbody xmlns="http://www.w3.org/1999/xhtml"> <tr valign="top"> <td align="left" rowspan="1" colspan="1"> <b>Unweighted n</b> </td> <td align="center" rowspan="1" colspan="1">12,982</td> <td align="center" rowspan="1" colspan="1">8967</td> <td align="center" rowspan="1" colspan="1">15,063</td> <td align="center" rowspan="1" colspan="1">9390</td> </tr> <tr valign="top"> <td align="left" rowspan="1" colspan="1"> <b>Weighted n (CI), millions</b> </td> <td align="char" char="(" rowspan="1" colspan="1">19.7 (19.4–19.9)</td> <td align="char" char="(" rowspan="1" colspan="1">10 (9.8–10.3)</td> <td align="char" char="(" rowspan="1" colspan="1">18.9 (18.6–19.1)</td> <td align="char" char="(" rowspan="1" colspan="1">10.7 (10.5–11)</td> </tr> <tr valign="top"> <td align="left" rowspan="1" colspan="1"> <b>Age, y</b> </td> <td rowspan="1" colspan="1" /> <td rowspan="1" colspan="1" /> <td rowspan="1" colspan="1" /> <td rowspan="1" colspan="1" /> </tr> <tr valign="top"> <td align="left" rowspan="1" colspan="1"> 18–29</td> <td align="char" char="(" rowspan="1" colspan="1">22.5 (22–23)</td> <td align="char" char="(" rowspan="1" colspan="1">18.7 (17.6–19.8)</td> <td align="char" char="(" rowspan="1" colspan="1">23.6 (23–24.1)</td> <td align="char" char="(" rowspan="1" colspan="1">19 (18–20.1)</td> </tr> <tr valign="top"> <td align="left" rowspan="1" colspan="1"> 30–44</td> <td align="char" char="(" rowspan="1" colspan="1">33.9 (33.4–34.5)</td> <td align="char" char="(" rowspan="1" colspan="1">10.7 (9.7–11.7)</td> <td align="char" char="(" rowspan="1" colspan="1">32.2 (31.6–32.8)</td> <td align="char" char="(" rowspan="1" colspan="1">12.2 (11.2–13.2)</td> </tr> <tr valign="top"> <td align="left" rowspan="1" colspan="1"> 45–64</td> <td align="char" char="(" rowspan="1" colspan="1">36.8 (36.2–37.5)</td> <td align="char" char="(" rowspan="1" colspan="1">21.7 (20.6–22.8)</td> <td align="char" char="(" rowspan="1" colspan="1">36.8 (36.3–37.4)</td> <td align="char" char="(" rowspan="1" colspan="1">23.6 (22.6–24.6)</td> </tr> <tr valign="top"> <td align="left" rowspan="1" colspan="1"> 65+</td> <td align="char" char="(" rowspan="1" colspan="1">6.7 (6.3–7.1)</td> <td align="char" char="(" rowspan="1" colspan="1">48.9 (47.6–50.2)</td> <td align="char" char="(" rowspan="1" colspan="1">7.4 (7.0–7.8)</td> <td align="char" char="(" rowspan="1" colspan="1">45.2 (44.2–46.1)</td> </tr> <tr valign="top"> <td align="left" rowspan="1" colspan="1"> <b>Sex</b> </td> <td rowspan="1" colspan="1" /> <td rowspan="1" colspan="1" /> <td rowspan="1" colspan="1" /> <td rowspan="1" colspan="1" /> </tr> <tr valign="top"> <td align="left" rowspan="1" colspan="1"> Male</td> <td align="char" char="(" rowspan="1" colspan="1">52.8 (52.2–53.4)</td> <td align="char" char="(" rowspan="1" colspan="1">41.8 (40.6–43)</td> <td align="char" char="(" rowspan="1" colspan="1">52.8 (52.2–53.5)</td> <td align="char" char="(" rowspan="1" colspan="1">42.3 (41.2–43.5)</td> </tr> <tr valign="top"> <td align="left" rowspan="1" colspan="1"> Female</td> <td align="char" char="(" rowspan="1" colspan="1">47.2 (46.6–47.8)</td> <td align="char" char="(" rowspan="1" colspan="1">58.2 (57–59.4)</td> <td align="char" char="(" rowspan="1" colspan="1">47.2 (46.5–47.8)</td> <td align="char" char="(" rowspan="1" colspan="1">57.7 (56.5–58.8)</td> </tr> <tr valign="top"> <td align="left" rowspan="1" colspan="1"> <b>Race/ethnicity</b> </td> <td rowspan="1" colspan="1" /> <td rowspan="1" colspan="1" /> <td rowspan="1" colspan="1" /> <td rowspan="1" colspan="1" /> </tr> <tr valign="top"> <td align="left" rowspan="1" colspan="1"> Hispanic/Latino</td> <td align="char" char="(" rowspan="1" colspan="1">41.8 (41–42.5)</td> <td align="char" char="(" rowspan="1" colspan="1">34.3 (32.8–35.8)</td> <td align="char" char="(" rowspan="1" colspan="1">38.6 (37.9–39.3)</td> <td align="char" char="(" rowspan="1" colspan="1">34.2 (33–35.4)</td> </tr> <tr valign="top"> <td align="left" rowspan="1" colspan="1"> White, NH</td> <td align="char" char="(" rowspan="1" colspan="1">35.6 (35–36.1)</td> <td align="char" char="(" rowspan="1" colspan="1">43.9 (42.7–45.2)</td> <td align="char" char="(" rowspan="1" colspan="1">38.1 (37.5–38.7)</td> <td align="char" char="(" rowspan="1" colspan="1">44.7 (43.6–45.8)</td> </tr> <tr valign="top"> <td align="left" rowspan="1" colspan="1"> Black, NH</td> <td align="char" char="(" rowspan="1" colspan="1">5.2 (4.8–5.6)</td> <td align="char" char="(" rowspan="1" colspan="1">6.1 (5.3–6.8)</td> <td align="char" char="(" rowspan="1" colspan="1">5.4 (5.1–5.8)</td> <td align="char" char="(" rowspan="1" colspan="1">5.8 (5.2–6.4)</td> </tr> <tr valign="top"> <td align="left" rowspan="1" colspan="1"> Asian, NH</td> <td align="char" char="(" rowspan="1" colspan="1">13.7 (13.2–14.2)</td> <td align="char" char="(" rowspan="1" colspan="1">12.5 (11.5–13.6)</td> <td align="char" char="(" rowspan="1" colspan="1">14.5 (14.1–15.0)</td> <td align="char" char="(" rowspan="1" colspan="1">12.6 (11.9–13.4)</td> </tr> <tr valign="top"> <td align="left" rowspan="1" colspan="1"> AI/AN, NH/PI, 2+, NH</td> <td align="char" char="(" rowspan="1" colspan="1">3.8 (3.5–4.1)</td> <td align="char" char="(" rowspan="1" colspan="1">3.1 (2.5–3.7)</td> <td align="char" char="(" rowspan="1" colspan="1">3.4 (3.1–3.6)</td> <td align="char" char="(" rowspan="1" colspan="1">2.7 (2.3–3.1)</td> </tr> <tr valign="top"> <td align="left" rowspan="1" colspan="1"> <b>Highest education</b> </td> <td rowspan="1" colspan="1" /> <td rowspan="1" colspan="1" /> <td rowspan="1" colspan="1" /> <td rowspan="1" colspan="1" /> </tr> <tr valign="top"> <td align="left" rowspan="1" colspan="1"> Less than high school</td> <td align="char" char="(" rowspan="1" colspan="1">12.9 (12.1–13.6)</td> <td align="char" char="(" rowspan="1" colspan="1">19.7 (18.5–20.8)</td> <td align="char" char="(" rowspan="1" colspan="1">12.5 (11.8–13.1)</td> <td align="char" char="(" rowspan="1" colspan="1">18.7 (17.6–19.7)</td> </tr> <tr valign="top"> <td align="left" rowspan="1" colspan="1"> Grade 12/high school diploma</td> <td align="char" char="(" rowspan="1" colspan="1">19.1 (18.3–19.8)</td> <td align="char" char="(" rowspan="1" colspan="1">27.3 (25.8–28.7)</td> <td align="char" char="(" rowspan="1" colspan="1">18.6 (18.0–19.3)</td> <td align="char" char="(" rowspan="1" colspan="1">27.8 (26.8–28.9)</td> </tr> <tr valign="top"> <td align="left" rowspan="1" colspan="1"> Some college or AA degree</td> <td align="char" char="(" rowspan="1" colspan="1">21.2 (20.3–22)</td> <td align="char" char="(" rowspan="1" colspan="1">23.5 (22.3–24.6)</td> <td align="char" char="(" rowspan="1" colspan="1">20.2 (19.3–21)</td> <td align="char" char="(" rowspan="1" colspan="1">22.4 (21.5–23.3)</td> </tr> <tr valign="top"> <td align="left" rowspan="1" colspan="1"> BA or BS degree/some graduate school</td> <td align="char" char="(" rowspan="1" colspan="1">28 (27–29)</td> <td align="char" char="(" rowspan="1" colspan="1">18.7 (17.6–19.7)</td> <td align="char" char="(" rowspan="1" colspan="1">27.9 (27.1–28.7)</td> <td align="char" char="(" rowspan="1" colspan="1">19.5 (18.6–20.4)</td> </tr> <tr valign="top"> <td align="left" rowspan="1" colspan="1"> Master’s degree or higher</td> <td align="char" char="(" rowspan="1" colspan="1">18.9 (18.1–19.7)</td> <td align="char" char="(" rowspan="1" colspan="1">10.9 (10.3–11.6)</td> <td align="char" char="(" rowspan="1" colspan="1">20.8 (20.1–21.6)</td> <td align="char" char="(" rowspan="1" colspan="1">11.6 (10.8–12.3)</td> </tr> <tr valign="top"> <td align="left" rowspan="1" colspan="1"> <b>Annual household income, $</b> </td> <td rowspan="1" colspan="1" /> <td rowspan="1" colspan="1" /> <td rowspan="1" colspan="1" /> <td rowspan="1" colspan="1" /> </tr> <tr valign="top"> <td align="left" rowspan="1" colspan="1"> <20,000</td> <td align="char" char="(" rowspan="1" colspan="1">9.4 (8.5–10.2)</td> <td align="char" char="(" rowspan="1" colspan="1">20.1 (18.7–21.5)</td> <td align="char" char="(" rowspan="1" colspan="1">9.1 (8.4–9.8)</td> <td align="char" char="(" rowspan="1" colspan="1">21.4 (20.3–22.5)</td> </tr> <tr valign="top"> <td align="left" rowspan="1" colspan="1"> 20,000–39,999</td> <td align="char" char="(" rowspan="1" colspan="1">13.7 (12.7–14.8)</td> <td align="char" char="(" rowspan="1" colspan="1">22.4 (20.8–24)</td> <td align="char" char="(" rowspan="1" colspan="1">14.2 (13.4–15)</td> <td align="char" char="(" rowspan="1" colspan="1">20.6 (19.4–21.7)</td> </tr> <tr valign="top"> <td align="left" rowspan="1" colspan="1"> 40,000–74,999</td> <td align="char" char="(" rowspan="1" colspan="1">21.7 (20.5–22.9)</td> <td align="char" char="(" rowspan="1" colspan="1">22.6 (21.4–23.8)</td> <td align="char" char="(" rowspan="1" colspan="1">20.5 (19.7–21.3)</td> <td align="char" char="(" rowspan="1" colspan="1">23.4 (22.2–24.7)</td> </tr> <tr valign="top"> <td align="left" rowspan="1" colspan="1"> 75,000–99,999</td> <td align="char" char="(" rowspan="1" colspan="1">12.5 (11.6–13.4)</td> <td align="char" char="(" rowspan="1" colspan="1">10.5 (9.5–11.6)</td> <td align="char" char="(" rowspan="1" colspan="1">11.4 (10.7–12.1)</td> <td align="char" char="(" rowspan="1" colspan="1">10.3 (9.5–11.1)</td> </tr> <tr valign="top"> <td align="left" rowspan="1" colspan="1"> 100,000-129,999</td> <td align="char" char="(" rowspan="1" colspan="1">13.5 (12.6–14.4)</td> <td align="char" char="(" rowspan="1" colspan="1">9.9 (8.9–11)</td> <td align="char" char="(" rowspan="1" colspan="1">12.3 (11.7–13)</td> <td align="char" char="(" rowspan="1" colspan="1">9.3 (8.4–10.3)</td> </tr> <tr valign="top"> <td align="left" rowspan="1" colspan="1"> 130,000+</td> <td align="char" char="(" rowspan="1" colspan="1">29.2 (28.3–30)</td> <td align="char" char="(" rowspan="1" colspan="1">14.5 (13.4–15.5)</td> <td align="char" char="(" rowspan="1" colspan="1">32.4 (31.5–33.3)</td> <td align="char" char="(" rowspan="1" colspan="1">15 (14.1–15.9)</td> </tr> <tr valign="top"> <td align="left" rowspan="1" colspan="1"> <b>Disability</b> </td> <td rowspan="1" colspan="1" /> <td rowspan="1" colspan="1" /> <td rowspan="1" colspan="1" /> <td rowspan="1" colspan="1" /> </tr> <tr valign="top"> <td align="left" rowspan="1" colspan="1"> Blind/deaf or has severe vision/hearing problem</td> <td align="char" char="(" rowspan="1" colspan="1">3.4 (2.9–4)</td> <td align="char" char="(" rowspan="1" colspan="1">10.7 (9.7–11.7)</td> <td align="char" char="(" rowspan="1" colspan="1">3.6 (3.2–4)</td> <td align="char" char="(" rowspan="1" colspan="1">10.4 (9.3–11.4)</td> </tr> <tr valign="top"> <td align="left" rowspan="1" colspan="1"> <b>Main industry (2010 census codes)</b> </td> <td rowspan="1" colspan="1" /> <td rowspan="1" colspan="1" /> <td rowspan="1" colspan="1" /> <td rowspan="1" colspan="1" /> </tr> <tr valign="top"> <td align="left" rowspan="1" colspan="1"> Agriculture, forestry, fishing, hunting, and mining</td> <td align="char" char="(" rowspan="1" colspan="1">1.5 (1.1–1.8)</td> <td align="center" rowspan="1" colspan="1">—</td> <td align="char" char="(" rowspan="1" colspan="1">1.4 (1.1–1.8)</td> <td align="center" rowspan="1" colspan="1">—</td> </tr> <tr valign="top"> <td align="left" rowspan="1" colspan="1"> Construction</td> <td align="char" char="(" rowspan="1" colspan="1">5 (4.4–5.7)</td> <td align="center" rowspan="1" colspan="1">—</td> <td align="char" char="(" rowspan="1" colspan="1">5 (4.4–5.6)</td> <td align="center" rowspan="1" colspan="1">—</td> </tr> <tr valign="top"> <td align="left" rowspan="1" colspan="1"> Manufacturing</td> <td align="char" char="(" rowspan="1" colspan="1">8.4 (7.5–9.2)</td> <td align="center" rowspan="1" colspan="1">—</td> <td align="char" char="(" rowspan="1" colspan="1">8.6 (8–9.1)</td> <td align="center" rowspan="1" colspan="1">—</td> </tr> <tr valign="top"> <td align="left" rowspan="1" colspan="1"> Wholesale trade</td> <td align="char" char="(" rowspan="1" colspan="1">1.9 (1.6–2.3)</td> <td align="center" rowspan="1" colspan="1">—</td> <td align="char" char="(" rowspan="1" colspan="1">1.9 (1.6–2.2)</td> <td align="center" rowspan="1" colspan="1">—</td> </tr> <tr valign="top"> <td align="left" rowspan="1" colspan="1"> Retail trade</td> <td align="char" char="(" rowspan="1" colspan="1">8.4 (7.7–9.2)</td> <td align="center" rowspan="1" colspan="1">—</td> <td align="char" char="(" rowspan="1" colspan="1">8.3 (7.8–8.9)</td> <td align="center" rowspan="1" colspan="1">—</td> </tr> <tr valign="top"> <td align="left" rowspan="1" colspan="1"> Transportation, warehousing, and utilities</td> <td align="char" char="(" rowspan="1" colspan="1">4.9 (4.3–5.5)</td> <td align="center" rowspan="1" colspan="1">—</td> <td align="char" char="(" rowspan="1" colspan="1">5.4 (4.9–5.9)</td> <td align="center" rowspan="1" colspan="1">—</td> </tr> <tr valign="top"> <td align="left" rowspan="1" colspan="1"> Information</td> <td align="char" char="(" rowspan="1" colspan="1">2.5 (2.2–2.8)</td> <td align="center" rowspan="1" colspan="1">—</td> <td align="char" char="(" rowspan="1" colspan="1">2.8 (2.4–3.1)</td> <td align="center" rowspan="1" colspan="1">—</td> </tr> <tr valign="top"> <td align="left" rowspan="1" colspan="1"> Finance and insurance, real estate, rental, and leasing</td> <td align="char" char="(" rowspan="1" colspan="1">5.5 (5–6)</td> <td align="center" rowspan="1" colspan="1">—</td> <td align="char" char="(" rowspan="1" colspan="1">4.8 (4.4–5.2)</td> <td align="center" rowspan="1" colspan="1">—</td> </tr> <tr valign="top"> <td align="left" rowspan="1" colspan="1"> Professional, scientific, management, and administrative and waste management services</td> <td align="char" char="(" rowspan="1" colspan="1">16.5 (15.4–17.5)</td> <td align="center" rowspan="1" colspan="1">—</td> <td align="char" char="(" rowspan="1" colspan="1">16.9 (16.2–17.6)</td> <td align="center" rowspan="1" colspan="1">—</td> </tr> <tr valign="top"> <td align="left" rowspan="1" colspan="1"> Educational services, health care, and social Assistance</td> <td align="char" char="(" rowspan="1" colspan="1">24.2 (23.3–25.2)</td> <td align="center" rowspan="1" colspan="1">—</td> <td align="char" char="(" rowspan="1" colspan="1">25 (24.1–26)</td> <td align="center" rowspan="1" colspan="1">—</td> </tr> <tr valign="top"> <td align="left" rowspan="1" colspan="1"> Arts, entertainment, recreation, accommodation, and food services</td> <td align="char" char="(" rowspan="1" colspan="1">7.4 (6.6–8.2)</td> <td align="center" rowspan="1" colspan="1">—</td> <td align="char" char="(" rowspan="1" colspan="1">7.3 (6.7–8)</td> <td align="center" rowspan="1" colspan="1">—</td> </tr> <tr valign="top"> <td align="left" rowspan="1" colspan="1"> Other services, except public administration</td> <td align="char" char="(" rowspan="1" colspan="1">4.4 (3.8–5)</td> <td align="center" rowspan="1" colspan="1">—</td> <td align="char" char="(" rowspan="1" colspan="1">4.8 (4.3–5.3)</td> <td align="center" rowspan="1" colspan="1">—</td> </tr> <tr valign="top"> <td align="left" rowspan="1" colspan="1"> Public administration</td> <td align="char" char="(" rowspan="1" colspan="1">6.3 (5.8–6.9)</td> <td align="center" rowspan="1" colspan="1">—</td> <td align="char" char="(" rowspan="1" colspan="1">5.8 (5.3–6.3)</td> <td align="center" rowspan="1" colspan="1">—</td> </tr> <tr valign="top"> <td align="left" rowspan="1" colspan="1"> <b>Main occupation (2010 census codes)</b> </td> <td rowspan="1" colspan="1" /> <td rowspan="1" colspan="1" /> <td rowspan="1" colspan="1" /> <td rowspan="1" colspan="1" /> </tr> <tr valign="top"> <td align="left" rowspan="1" colspan="1"> Management, business, and financial occupations</td> <td align="char" char="(" rowspan="1" colspan="1">14.4 (13.5–15.3)</td> <td align="center" rowspan="1" colspan="1">—</td> <td align="char" char="(" rowspan="1" colspan="1">14.5 (13.9–15.1)</td> <td align="center" rowspan="1" colspan="1">—</td> </tr> <tr valign="top"> <td align="left" rowspan="1" colspan="1"> Computer, engineering, and science occupations</td> <td align="char" char="(" rowspan="1" colspan="1">10.6 (9.9–11.3)</td> <td align="center" rowspan="1" colspan="1">—</td> <td align="char" char="(" rowspan="1" colspan="1">11.9 (11.2–12.6)</td> <td align="center" rowspan="1" colspan="1">—</td> </tr> <tr valign="top"> <td align="left" rowspan="1" colspan="1"> Education, legal, community service, arts, and media occupations</td> <td align="char" char="(" rowspan="1" colspan="1">13.3 (12.5–14)</td> <td align="center" rowspan="1" colspan="1">—</td> <td align="char" char="(" rowspan="1" colspan="1">13.8 (13.1–14.5)</td> <td align="center" rowspan="1" colspan="1">—</td> </tr> <tr valign="top"> <td align="left" rowspan="1" colspan="1"> Health care practitioners and technical occupations</td> <td align="char" char="(" rowspan="1" colspan="1">5.1 (4.6–5.6)</td> <td align="center" rowspan="1" colspan="1">—</td> <td align="char" char="(" rowspan="1" colspan="1">5.6 (5.2–6)</td> <td align="center" rowspan="1" colspan="1">—</td> </tr> <tr valign="top"> <td align="left" rowspan="1" colspan="1"> Service occupations</td> <td align="char" char="(" rowspan="1" colspan="1">16.6 (15.3–17.8)</td> <td align="center" rowspan="1" colspan="1">—</td> <td align="char" char="(" rowspan="1" colspan="1">15.2 (14.3–16.2)</td> <td align="center" rowspan="1" colspan="1">—</td> </tr> <tr valign="top"> <td align="left" rowspan="1" colspan="1"> Sales and related occupations</td> <td align="char" char="(" rowspan="1" colspan="1">7.6 (6.9–8.2)</td> <td align="center" rowspan="1" colspan="1">—</td> <td align="char" char="(" rowspan="1" colspan="1">7 (6.4–7.6)</td> <td align="center" rowspan="1" colspan="1">—</td> </tr> <tr valign="top"> <td align="left" rowspan="1" colspan="1"> Office and administrative support occupations</td> <td align="char" char="(" rowspan="1" colspan="1">11.9 (11.1–12.7)</td> <td align="center" rowspan="1" colspan="1">—</td> <td align="char" char="(" rowspan="1" colspan="1">12.4 (11.6–13.2)</td> <td align="center" rowspan="1" colspan="1">—</td> </tr> <tr valign="top"> <td align="left" rowspan="1" colspan="1"> Farming, fishing, and forestry occupations</td> <td align="char" char="(" rowspan="1" colspan="1">0.9 (0.6–1.2)</td> <td align="center" rowspan="1" colspan="1">—</td> <td align="char" char="(" rowspan="1" colspan="1">0.8 (0.5–1)</td> <td align="center" rowspan="1" colspan="1">—</td> </tr> <tr valign="top"> <td align="left" rowspan="1" colspan="1"> Construction and extraction occupations</td> <td align="char" char="(" rowspan="1" colspan="1">3.7 (3–4.3)</td> <td align="center" rowspan="1" colspan="1">—</td> <td align="char" char="(" rowspan="1" colspan="1">3.6 (3.1–4.1)</td> <td align="center" rowspan="1" colspan="1">—</td> </tr> <tr valign="top"> <td align="left" rowspan="1" colspan="1"> Installation, maintenance, and repair occupations</td> <td align="char" char="(" rowspan="1" colspan="1">2.5 (1.9–3)</td> <td align="center" rowspan="1" colspan="1">—</td> <td align="char" char="(" rowspan="1" colspan="1">2 (1.7–2.4)</td> <td align="center" rowspan="1" colspan="1">—</td> </tr> <tr valign="top"> <td align="left" rowspan="1" colspan="1"> Production occupations</td> <td align="char" char="(" rowspan="1" colspan="1">4.8 (4.1–5.5)</td> <td align="center" rowspan="1" colspan="1">—</td> <td align="char" char="(" rowspan="1" colspan="1">4.3 (3.8–4.7)</td> <td align="center" rowspan="1" colspan="1">—</td> </tr> <tr valign="top"> <td align="left" rowspan="1" colspan="1"> Transportation and material moving occupations</td> <td align="char" char="(" rowspan="1" colspan="1">5.5 (4.9–6.1)</td> <td align="center" rowspan="1" colspan="1">—</td> <td align="char" char="(" rowspan="1" colspan="1">5.7 (5.1–6.3)</td> <td align="center" rowspan="1" colspan="1">—</td> </tr> </tbody> </table> <div class="article-table-descriptions"> <div class="article-table-descriptions-content"><span id=""><div class="dib">AI/AN, American Indian/Alaska Native; CI, confidence interval; NH, non-Hispanic; PI, Pacific Islander.</div></span></div> </div> </div> </div> </div><br><p id="JCL-P-28">In 2021, over a third of California workers either perceived needing care or reported moderate to severe psychological distress (38.5%, CI: 37.5 to 39.5), a 6.6% (CI: 5.0 to 8.2) absolute increase from 2019. The prevalence of all workers who sought care from a primary care provider or professional for mental, emotional, drug, or alcohol concerns in 2021 was 17.2% (CI: 16.3 to 18.1), a 2.7% (CI: 1.4 to 3.9) absolute increase from 2019. Notably, not all respondents who sought care for a mental, emotional, drug, or alcohol problem had reported a perceived need or moderate to severe psychological distress; 15.1% (CI: 14.3 to 15.9) of all workers perceived needing care or reported moderate to severe psychological distress and sought care for those concerns. <a href="javascript:void(0)" onclick="javascript:showSlideShowByImageID('F1', '00043764-202408000-00003');">Figure 1</a> shows trends in the prevalence of workers needing help and those workers who needed help but sought care from 2013 to 2021 in California. Increases in the prevalence of needing help from 2018 onward were not met with comparable increases of those workers seeking care (which remained relatively flat), thereby driving increases in unmet needs.</p><section class="ejp-r-article-images"><figure class="ejp-r-article-images__figure"><a href="javascript:void(0)" class="ejp-r-article-images__image-link" onclick="showSlideShowByImageID('F1', '00043764-202408000-00003')"><img class="ejp-r-article-images__img js-lazy-load lazy-load" src="javascript:void(0);" data-src="https://images.journals.lww.com/joem/ArticleViewerPreview.00043764-202408000-00003.F1.jpeg" data-srcset="https://images.journals.lww.com/joem/ArticleViewerPreview@2.00043764-202408000-00003.F1.jpeg 2x" srcset="" alt="F1"></a><figcaption class="ejp-r-article-images__figcaption"><a href="javascript:void(0)" class="ejp-r-article-images__figcaption-link" onclick="showSlideShowByImageID('F1', '00043764-202408000-00003')">FIGURE 1: </a><div class="ejp-r-article-images__figcaption-text">Unmet need trends among California workers. Trends in percentage of workers who needed help, workers who needed help but sought care, and workers who needed help but did not seek care.</div></figcaption></figure></section><h3 class="ejp-article-outline-heading" data-level="2" id="JCL11">Unmet Needs</h3> <p id="JCL-P-29">In 2021, 23.4% (CI: 22.4 to 24.4) of all workers reported unmet mental health needs, an increase from 19.5% (CI:18.4 to 20.6) in 2019. However, after adjusting for prior trends, the prevalence of unmet mental health needs was 18% lower than expected during 2020 to 2021 than in prepandemic years (PR: 0.82, CI: 0.72 to 0.92).</p> <p id="JCL-P-30">Nearly a third of workers in information industries (31.9%, CI: 25.6 to 38.7) and the Arts, entertainment, recreation, and accommodation industries (31.0%, CI: 26.7 to 35.6) reported unmet mental health needs in 2021. The prevalence of unmet mental health needs among workers in the information industries was nearly two times (PR: 1.89) higher in 2020 to 2021 than the expected prevalence had prepandemic trends continued; this was the greatest relative increase in unmet mental health needs by industry group (<a href="#T2">Table 2</a>). Other industry groups with high relative increases in unmet mental health needs were the wholesale trade (PR: 1.64, CI: 1.1 to 2.4) and manufacturing industries (PR: 1.53, CI: 1.3 to 1.8). The greatest absolute increases in unmet mental health needs from 2019 to 2021 were among workers in the retail trade (7.0%, CI: 0.8% to 13.3%); professional, scientific, management, and administrative and waste management services (4%, CI: 0.5% to 7.9%); and public administration industries (3%, CI: 0.4% to 6.3%) (<a href="#T2">Table 2</a>). Information; wholesale trade; retail trade; and professional, scientific, management, and administrative and waste management services industries were identified as priority groups determined by a PR > 1 and greater than average prevalence in 2021 (<a href="javascript:void(0)" onclick="javascript:showSlideShowByImageID('F2', '00043764-202408000-00003');">Fig. 2</a>).</p> <div class="wk-clearfix-article-table"></div> <div class="article-table"><a id="T2"></a><div class="article-table-title"><span>TABLE 2 - </span> Unmet Mental Health Needs in Working Adults<em class="fa fa-arrows-alt expand-button js-expand-table-event" aria-label="expand table"></em><div class="clearfix"></div> </div> <div class="scroll-message"></div> <div class="dummy-scroll"> <div></div> </div> <div class="article-table-body"> <div class="article-table-container"> <table> <thead xmlns="http://www.w3.org/1999/xhtml"> <tr valign="top"> <th rowspan="2" colspan="1" /> <th align="center" colspan="4" rowspan="1">Unmet Need (Reported Needing Help or Reported Moderate to Severe Distress and Did Not Seek Help)</th> </tr> <tr valign="top"> <th align="center" rowspan="1" colspan="1">Prevalence in 2019, % (95% CI)</th> <th align="center" rowspan="1" colspan="1">Absolute Change 2019–2021, % (95% CI)</th> <th align="center" rowspan="1" colspan="1">Trend Adjusted Prevalence Ratio (95% CI)</th> <th align="center" rowspan="1" colspan="1">Model Type</th> </tr> </thead> <tbody xmlns="http://www.w3.org/1999/xhtml"> <tr valign="top"> <td align="left" rowspan="1" colspan="1">All workers</td> <td align="char" char="(" rowspan="1" colspan="1">19.48 (18.4, 20.6)</td> <td align="char" char="(" rowspan="1" colspan="1">3.92 (2.4, 5.4)</td> <td align="char" char="(" rowspan="1" colspan="1">0.82 (0.7, 0.9)</td> <td align="center" rowspan="1" colspan="1">*</td> </tr> <tr valign="top"> <td align="left" rowspan="1" colspan="1">Age</td> <td rowspan="1" colspan="1" /> <td rowspan="1" colspan="1" /> <td rowspan="1" colspan="1" /> <td rowspan="1" colspan="1" /> </tr> <tr valign="top"> <td align="left" rowspan="1" colspan="1"> 18–29</td> <td align="char" char="(" rowspan="1" colspan="1">33.86 (30.7, 37.1)</td> <td align="char" char="(" rowspan="1" colspan="1">1.37 (−2.8, 5.5)</td> <td align="char" char="(" rowspan="1" colspan="1">0.78 (0.6, 1)</td> <td align="center" rowspan="1" colspan="1">*</td> </tr> <tr valign="top"> <td align="left" rowspan="1" colspan="1"> 30–44</td> <td align="char" char="(" rowspan="1" colspan="1">18.50 (17.0, 20.1)</td> <td align="char" char="(" rowspan="1" colspan="1">6.05 (3.9, 8.2)</td> <td align="char" char="(" rowspan="1" colspan="1">1.14 (1, 1.3)</td> <td align="center" rowspan="1" colspan="1">†</td> </tr> <tr valign="top"> <td align="left" rowspan="1" colspan="1"> 45–64</td> <td align="char" char="(" rowspan="1" colspan="1">12.65 (11.4, 14.0)</td> <td align="char" char="(" rowspan="1" colspan="1">4.68 (2.9, 6.5)</td> <td align="char" char="(" rowspan="1" colspan="1">1.21 (1, 1.4)</td> <td align="center" rowspan="1" colspan="1">†</td> </tr> <tr valign="top"> <td align="left" rowspan="1" colspan="1"> 65+</td> <td align="char" char="(" rowspan="1" colspan="1">8.52 (6.2, 11.4)</td> <td align="char" char="(" rowspan="1" colspan="1">2.37 (−1.1, 5.8)</td> <td align="char" char="(" rowspan="1" colspan="1">1.27 (0.9, 1.8)</td> <td align="center" rowspan="1" colspan="1">‡</td> </tr> <tr valign="top"> <td align="left" rowspan="1" colspan="1">Sex</td> <td rowspan="1" colspan="1" /> <td rowspan="1" colspan="1" /> <td rowspan="1" colspan="1" /> <td rowspan="1" colspan="1" /> </tr> <tr valign="top"> <td align="left" rowspan="1" colspan="1"> Male</td> <td align="char" char="(" rowspan="1" colspan="1">17.94 (16.4, 19.5)</td> <td align="char" char="(" rowspan="1" colspan="1">3.24 (1.3, 5.2)</td> <td align="char" char="(" rowspan="1" colspan="1">0.97 (0.9, 1.1)</td> <td align="center" rowspan="1" colspan="1">†</td> </tr> <tr valign="top"> <td align="left" rowspan="1" colspan="1"> Female</td> <td align="char" char="(" rowspan="1" colspan="1">21.26 (19.7, 22.9)</td> <td align="char" char="(" rowspan="1" colspan="1">4.62 (2.6, 6.7)</td> <td align="char" char="(" rowspan="1" colspan="1">0.82 (0.7, 1)</td> <td align="center" rowspan="1" colspan="1">*</td> </tr> <tr valign="top"> <td align="left" rowspan="1" colspan="1">Race/ethnicity</td> <td rowspan="1" colspan="1" /> <td rowspan="1" colspan="1" /> <td rowspan="1" colspan="1" /> <td rowspan="1" colspan="1" /> </tr> <tr valign="top"> <td align="left" rowspan="1" colspan="1"> Hispanic/Latino</td> <td align="char" char="(" rowspan="1" colspan="1">20.74 (18.6, 23.0)</td> <td align="char" char="(" rowspan="1" colspan="1">2.82 (0.2, 5.5)</td> <td align="char" char="(" rowspan="1" colspan="1">0.77 (0.6, 1)</td> <td align="center" rowspan="1" colspan="1">*</td> </tr> <tr valign="top"> <td align="left" rowspan="1" colspan="1"> White, NH</td> <td align="char" char="(" rowspan="1" colspan="1">17.72 (16.3, 19.2)</td> <td align="char" char="(" rowspan="1" colspan="1">5.79 (3.8, 7.8)</td> <td align="char" char="(" rowspan="1" colspan="1">1.13 (1, 1.3)</td> <td align="center" rowspan="1" colspan="1">†</td> </tr> <tr valign="top"> <td align="left" rowspan="1" colspan="1"> Black, NH</td> <td align="char" char="(" rowspan="1" colspan="1">20.12 (15.3, 25.6)</td> <td align="char" char="(" rowspan="1" colspan="1">−1.36 (−7.6, 4.9)</td> <td align="char" char="(" rowspan="1" colspan="1">0.99 (0.8, 1.2)</td> <td align="center" rowspan="1" colspan="1">‡</td> </tr> <tr valign="top"> <td align="left" rowspan="1" colspan="1"> Asian, NH</td> <td align="char" char="(" rowspan="1" colspan="1">18.06 (15.0, 21.4)</td> <td align="char" char="(" rowspan="1" colspan="1">5.52 (1.6, 9.4)</td> <td align="char" char="(" rowspan="1" colspan="1">1.06 (0.8, 1.3)</td> <td align="center" rowspan="1" colspan="1">†</td> </tr> <tr valign="top"> <td align="left" rowspan="1" colspan="1"> Other (AI/AN, NH/PI, 2+, NH)</td> <td align="char" char="(" rowspan="1" colspan="1">27.05 (20.2, 34.8)</td> <td align="char" char="(" rowspan="1" colspan="1">0 (−8.6, 8.6)</td> <td align="char" char="(" rowspan="1" colspan="1">1.18 (0.9, 1.5)</td> <td align="center" rowspan="1" colspan="1">‡</td> </tr> <tr valign="top"> <td align="left" rowspan="1" colspan="1">Highest education</td> <td rowspan="1" colspan="1" /> <td rowspan="1" colspan="1" /> <td rowspan="1" colspan="1" /> <td rowspan="1" colspan="1" /> </tr> <tr valign="top"> <td align="left" rowspan="1" colspan="1"> Less than high school</td> <td align="char" char="(" rowspan="1" colspan="1">14.98 (11.3, 19.3)</td> <td align="char" char="(" rowspan="1" colspan="1">4.3 (−0.7, 9.3)</td> <td align="char" char="(" rowspan="1" colspan="1">1.24 (1, 1.5)</td> <td align="center" rowspan="1" colspan="1">‡</td> </tr> <tr valign="top"> <td align="left" rowspan="1" colspan="1"> Grade 12/high school diploma</td> <td align="char" char="(" rowspan="1" colspan="1">18.58 (15.6, 21.8)</td> <td align="char" char="(" rowspan="1" colspan="1">4.62 (0.5, 8.7)</td> <td align="char" char="(" rowspan="1" colspan="1">1.3 (1.2, 1.5)</td> <td align="center" rowspan="1" colspan="1">‡</td> </tr> <tr valign="top"> <td align="left" rowspan="1" colspan="1"> Some college or AA degree</td> <td align="char" char="(" rowspan="1" colspan="1">22.18 (20.0, 24.5)</td> <td align="char" char="(" rowspan="1" colspan="1">4.18 (1.2, 7.2)</td> <td align="char" char="(" rowspan="1" colspan="1">0.92 (0.8, 1.1)</td> <td align="center" rowspan="1" colspan="1">†</td> </tr> <tr valign="top"> <td align="left" rowspan="1" colspan="1"> BA or BS degree/some graduate school</td> <td align="char" char="(" rowspan="1" colspan="1">21.53 (19.8, 23.4)</td> <td align="char" char="(" rowspan="1" colspan="1">2.92 (0.5, 5.3)</td> <td align="char" char="(" rowspan="1" colspan="1">0.82 (0.7, 1)</td> <td align="center" rowspan="1" colspan="1">*</td> </tr> <tr valign="top"> <td align="left" rowspan="1" colspan="1"> Master’s degree or higher</td> <td align="char" char="(" rowspan="1" colspan="1">17.29 (15.3, 19.4)</td> <td align="char" char="(" rowspan="1" colspan="1">4.49 (1.9, 7.1)</td> <td align="char" char="(" rowspan="1" colspan="1">1 (0.8, 1.2)</td> <td align="center" rowspan="1" colspan="1">†</td> </tr> <tr valign="top"> <td align="left" rowspan="1" colspan="1">Annual household income</td> <td rowspan="1" colspan="1" /> <td rowspan="1" colspan="1" /> <td rowspan="1" colspan="1" /> <td rowspan="1" colspan="1" /> </tr> <tr valign="top"> <td align="left" rowspan="1" colspan="1"> <20,000</td> <td align="char" char="(" rowspan="1" colspan="1">27.17 (23.4, 31.2)</td> <td align="char" char="(" rowspan="1" colspan="1">−3.4 (−8.3, 1.5)</td> <td align="char" char="(" rowspan="1" colspan="1">0.86 (0.7, 1.1)</td> <td align="center" rowspan="1" colspan="1">†</td> </tr> <tr valign="top"> <td align="left" rowspan="1" colspan="1"> 20,000–39,999</td> <td align="char" char="(" rowspan="1" colspan="1">21.82 (18.5, 25.4)</td> <td align="char" char="(" rowspan="1" colspan="1">3.89 (−0.4, 8.2)</td> <td align="char" char="(" rowspan="1" colspan="1">0.96 (0.7, 1.3)</td> <td align="center" rowspan="1" colspan="1">*</td> </tr> <tr valign="top"> <td align="left" rowspan="1" colspan="1"> 40,000–74,999</td> <td align="char" char="(" rowspan="1" colspan="1">21.01 (18.6, 23.6)</td> <td align="char" char="(" rowspan="1" colspan="1">4.97 (1.6, 8.3)</td> <td align="char" char="(" rowspan="1" colspan="1">0.95 (0.8, 1.1)</td> <td align="center" rowspan="1" colspan="1">†</td> </tr> <tr valign="top"> <td align="left" rowspan="1" colspan="1"> 75,000–99,999</td> <td align="char" char="(" rowspan="1" colspan="1">19.09 (16.2, 22.3)</td> <td align="char" char="(" rowspan="1" colspan="1">4.59 (0.4, 8.8)</td> <td align="char" char="(" rowspan="1" colspan="1">1.06 (0.8, 1.3)</td> <td align="center" rowspan="1" colspan="1">†</td> </tr> <tr valign="top"> <td align="left" rowspan="1" colspan="1"> 100,000–129,999</td> <td align="char" char="(" rowspan="1" colspan="1">16.98 (14.5, 19.7)</td> <td align="char" char="(" rowspan="1" colspan="1">4.45 (1, 7.9)</td> <td align="char" char="(" rowspan="1" colspan="1">0.95 (0.8, 1.2)</td> <td align="center" rowspan="1" colspan="1">†</td> </tr> <tr valign="top"> <td align="left" rowspan="1" colspan="1"> 130,000+</td> <td align="char" char="(" rowspan="1" colspan="1">15.51 (13.9, 17.2)</td> <td align="char" char="(" rowspan="1" colspan="1">5.8 (3.7, 7.9)</td> <td align="char" char="(" rowspan="1" colspan="1">1.08 (0.9, 1.3)</td> <td align="center" rowspan="1" colspan="1">†</td> </tr> <tr valign="top"> <td align="left" rowspan="1" colspan="1">Disability</td> <td rowspan="1" colspan="1" /> <td rowspan="1" colspan="1" /> <td rowspan="1" colspan="1" /> <td rowspan="1" colspan="1" /> </tr> <tr valign="top"> <td align="left" rowspan="1" colspan="1">Blind/deaf or has severe vision/hearing problem</td> <td align="char" char="(" rowspan="1" colspan="1">16.77 (10.8, 24.3)</td> <td align="char" char="(" rowspan="1" colspan="1">8.29 (−0.3, 16.9)</td> <td align="char" char="(" rowspan="1" colspan="1">1.38 (1.1, 1.8)</td> <td align="center" rowspan="1" colspan="1">‡</td> </tr> <tr valign="top"> <td align="left" rowspan="1" colspan="1">Not blind/deaf or has severe vision/hearing problem</td> <td align="char" char="(" rowspan="1" colspan="1">19.57 (18.5, 20.7)</td> <td align="char" char="(" rowspan="1" colspan="1">3.77 (2.2, 5.3)</td> <td align="char" char="(" rowspan="1" colspan="1">0.79 (0.7, 0.9)</td> <td align="center" rowspan="1" colspan="1">*</td> </tr> <tr valign="top"> <td align="left" rowspan="1" colspan="1"> Difficulty concentrating§</td> <td align="char" char="(" rowspan="1" colspan="1">38.86 (33.0, 44.9)</td> <td align="center" rowspan="1" colspan="1">—</td> <td align="center" rowspan="1" colspan="1">—</td> <td align="center" rowspan="1" colspan="1">—</td> </tr> <tr valign="top"> <td align="left" rowspan="1" colspan="1"> Denied difficulty concentrating§</td> <td align="char" char="(" rowspan="1" colspan="1">18.22 (17.1, 19.4)</td> <td align="center" rowspan="1" colspan="1">—</td> <td align="center" rowspan="1" colspan="1">—</td> <td align="center" rowspan="1" colspan="1">—</td> </tr> <tr valign="top"> <td align="left" rowspan="1" colspan="1"> Difficulty dressing or bathing§</td> <td align="char" char="(" rowspan="1" colspan="1">29.95 (15.5, 48.0)</td> <td align="center" rowspan="1" colspan="1">—</td> <td align="center" rowspan="1" colspan="1">—</td> <td align="center" rowspan="1" colspan="1">—</td> </tr> <tr valign="top"> <td align="left" rowspan="1" colspan="1"> Denied difficulty dressing or bathing§</td> <td align="char" char="(" rowspan="1" colspan="1">19.40 (18.3, 20.5)</td> <td align="center" rowspan="1" colspan="1">—</td> <td align="center" rowspan="1" colspan="1">—</td> <td align="center" rowspan="1" colspan="1">—</td> </tr> <tr valign="top"> <td align="left" rowspan="1" colspan="1"> Difficulty doing errands alone§</td> <td align="char" char="(" rowspan="1" colspan="1">35.12 (24.2, 47.3)</td> <td align="center" rowspan="1" colspan="1">—</td> <td align="center" rowspan="1" colspan="1">—</td> <td align="center" rowspan="1" colspan="1">—</td> </tr> <tr valign="top"> <td align="left" rowspan="1" colspan="1"> Denied difficulty doing errands alone§</td> <td align="char" char="(" rowspan="1" colspan="1">19.05 (18.0, 20.1)</td> <td align="center" rowspan="1" colspan="1">—</td> <td align="center" rowspan="1" colspan="1">—</td> <td align="center" rowspan="1" colspan="1">—</td> </tr> <tr valign="top"> <td align="left" rowspan="1" colspan="1"> Any of the above disabilities</td> <td align="char" char="(" rowspan="1" colspan="1">31.59 (26.9, 36.6)</td> <td align="center" rowspan="1" colspan="1">—</td> <td align="center" rowspan="1" colspan="1">—</td> <td align="center" rowspan="1" colspan="1">—</td> </tr> <tr valign="top"> <td align="left" rowspan="1" colspan="1">Insurance status</td> <td rowspan="1" colspan="1" /> <td rowspan="1" colspan="1" /> <td rowspan="1" colspan="1" /> <td rowspan="1" colspan="1" /> </tr> <tr valign="top"> <td align="left" rowspan="1" colspan="1"> Currently uninsured</td> <td align="char" char="(" rowspan="1" colspan="1">25.70 (21.0, 30.9)</td> <td align="char" char="(" rowspan="1" colspan="1">2.14 (−4.2, 8.5)</td> <td align="char" char="(" rowspan="1" colspan="1">0.85 (0.7, 1.1)</td> <td align="center" rowspan="1" colspan="1">†</td> </tr> <tr valign="top"> <td align="left" rowspan="1" colspan="1"> Uninsured any of the past 12 mo</td> <td align="char" char="(" rowspan="1" colspan="1">28.72 (21.8, 36.4)</td> <td align="char" char="(" rowspan="1" colspan="1">2.11 (−6.8, 11)</td> <td align="char" char="(" rowspan="1" colspan="1">1.04 (0.8, 1.4)</td> <td align="center" rowspan="1" colspan="1">†</td> </tr> <tr valign="top"> <td align="left" rowspan="1" colspan="1"> Insured all of the past 12 mo</td> <td align="char" char="(" rowspan="1" colspan="1">18.34 (17.2, 19.5)</td> <td align="char" char="(" rowspan="1" colspan="1">4.31 (2.8, 5.8)</td> <td align="char" char="(" rowspan="1" colspan="1">0.82 (0.7, 0.9)</td> <td align="center" rowspan="1" colspan="1">*</td> </tr> <tr valign="top"> <td align="left" rowspan="1" colspan="1">Main industry (2010 census codes)</td> <td rowspan="1" colspan="1" /> <td rowspan="1" colspan="1" /> <td rowspan="1" colspan="1" /> <td rowspan="1" colspan="1" /> </tr> <tr valign="top"> <td align="left" rowspan="1" colspan="1"> Agriculture, forestry, fishing, hunting, and mining</td> <td align="char" char="(" rowspan="1" colspan="1">18.11 (10.3, 28.4)</td> <td align="char" char="(" rowspan="1" colspan="1">−0.36 (−11.6, 10.9)</td> <td align="char" char="(" rowspan="1" colspan="1">0.62 (0.3, 1.3)</td> <td align="center" rowspan="1" colspan="1">†</td> </tr> <tr valign="top"> <td align="left" rowspan="1" colspan="1"> Construction</td> <td align="char" char="(" rowspan="1" colspan="1">18.1 (13.5, 23.5)</td> <td align="char" char="(" rowspan="1" colspan="1">1.09 (−5.5, 7.7)</td> <td align="char" char="(" rowspan="1" colspan="1">0.44 (0.2, 0.8)</td> <td align="center" rowspan="1" colspan="1">*</td> </tr> <tr valign="top"> <td align="left" rowspan="1" colspan="1"> Manufacturing</td> <td align="char" char="(" rowspan="1" colspan="1">16.08 (12.4, 20.3)</td> <td align="char" char="(" rowspan="1" colspan="1">3.34 (−1.5, 8.2)</td> <td align="char" char="(" rowspan="1" colspan="1">1.53 (1.3, 1.8)</td> <td align="center" rowspan="1" colspan="1">‡</td> </tr> <tr valign="top"> <td align="left" rowspan="1" colspan="1"> Wholesale trade</td> <td align="char" char="(" rowspan="1" colspan="1">16.41 (6.4, 32)</td> <td align="char" char="(" rowspan="1" colspan="1">7.6 (−6.3, 21.5)</td> <td align="char" char="(" rowspan="1" colspan="1">1.64 (1.1, 2.4)</td> <td align="center" rowspan="1" colspan="1">‡</td> </tr> <tr valign="top"> <td align="left" rowspan="1" colspan="1"> Retail trade</td> <td align="char" char="(" rowspan="1" colspan="1">21.59 (17, 26.8)</td> <td align="char" char="(" rowspan="1" colspan="1">7.07 (0.8, 13.3)</td> <td align="char" char="(" rowspan="1" colspan="1">1.37 (1.2, 1.6)</td> <td align="center" rowspan="1" colspan="1">‡</td> </tr> <tr valign="top"> <td align="left" rowspan="1" colspan="1"> Transportation, warehousing, and utilities</td> <td align="char" char="(" rowspan="1" colspan="1">14.57 (10.3, 19.7)</td> <td align="char" char="(" rowspan="1" colspan="1">0.92 (−5.3, 7.1)</td> <td align="char" char="(" rowspan="1" colspan="1">1.35 (1, 1.8)</td> <td align="center" rowspan="1" colspan="1">‡</td> </tr> <tr valign="top"> <td align="left" rowspan="1" colspan="1"> Information</td> <td align="char" char="(" rowspan="1" colspan="1">23.99 (15.6, 34.1)</td> <td align="char" char="(" rowspan="1" colspan="1">7.91 (−2.9, 18.7)</td> <td align="char" char="(" rowspan="1" colspan="1">1.89 (1.4, 2.5)</td> <td align="center" rowspan="1" colspan="1">‡</td> </tr> <tr valign="top"> <td align="left" rowspan="1" colspan="1"> Finance and insurance, real estate, rental, and leasing</td> <td align="char" char="(" rowspan="1" colspan="1">16.95 (13, 21.6)</td> <td align="char" char="(" rowspan="1" colspan="1">4.02 (−1.2, 9.3)</td> <td align="char" char="(" rowspan="1" colspan="1">1 (0.7, 1.4)</td> <td align="center" rowspan="1" colspan="1">†</td> </tr> <tr valign="top"> <td align="left" rowspan="1" colspan="1"> Professional, scientific, management, and administrative and waste management services</td> <td align="char" char="(" rowspan="1" colspan="1">19.33 (16.4, 22.5)</td> <td align="char" char="(" rowspan="1" colspan="1">4.17 (0.5, 7.9)</td> <td align="char" char="(" rowspan="1" colspan="1">1.02 (0.8, 1.3)</td> <td align="center" rowspan="1" colspan="1">†</td> </tr> <tr valign="top"> <td align="left" rowspan="1" colspan="1"> Educational services, health care, and social assistance</td> <td align="char" char="(" rowspan="1" colspan="1">20.98 (18.6, 23.5)</td> <td align="char" char="(" rowspan="1" colspan="1">3.35 (0.4, 6.3)</td> <td align="char" char="(" rowspan="1" colspan="1">0.62 (0.5, 0.8)</td> <td align="center" rowspan="1" colspan="1">*</td> </tr> <tr valign="top"> <td align="left" rowspan="1" colspan="1"> Arts, entertainment, recreation, accommodation, and food services</td> <td align="char" char="(" rowspan="1" colspan="1">26.55 (22.1, 31.4)</td> <td align="char" char="(" rowspan="1" colspan="1">4.44 (−2, 10.8)</td> <td align="char" char="(" rowspan="1" colspan="1">0.97 (0.7, 1.3)</td> <td align="center" rowspan="1" colspan="1">†</td> </tr> <tr valign="top"> <td align="left" rowspan="1" colspan="1"> Other services, except public administration</td> <td align="char" char="(" rowspan="1" colspan="1">19.42 (13.6, 26.3)</td> <td align="char" char="(" rowspan="1" colspan="1">−4.23 (−11.2, 2.7)</td> <td align="char" char="(" rowspan="1" colspan="1">1.09 (0.9, 1.4)</td> <td align="center" rowspan="1" colspan="1">‡</td> </tr> <tr valign="top"> <td align="left" rowspan="1" colspan="1"> Public administration</td> <td align="char" char="(" rowspan="1" colspan="1">16.05 (11.9, 20.9)</td> <td align="char" char="(" rowspan="1" colspan="1">4.64 (−1, 10.3)</td> <td align="char" char="(" rowspan="1" colspan="1">1.09 (0.7, 1.6)</td> <td align="center" rowspan="1" colspan="1">†</td> </tr> <tr valign="top"> <td align="left" rowspan="1" colspan="1">Main occupation (2010 census codes)</td> <td rowspan="1" colspan="1" /> <td rowspan="1" colspan="1" /> <td rowspan="1" colspan="1" /> <td rowspan="1" colspan="1" /> </tr> <tr valign="top"> <td align="left" rowspan="1" colspan="1"> Management, business, and financial occupations</td> <td align="char" char="(" rowspan="1" colspan="1">16.46 (14.5, 18.5)</td> <td align="char" char="(" rowspan="1" colspan="1">7.44 (4.4, 10.5)</td> <td align="char" char="(" rowspan="1" colspan="1">1.08 (0.9, 1.3)</td> <td align="center" rowspan="1" colspan="1">†</td> </tr> <tr valign="top"> <td align="left" rowspan="1" colspan="1"> Computer, engineering, and science occupations</td> <td align="char" char="(" rowspan="1" colspan="1">22.42 (18.8, 26.4)</td> <td align="char" char="(" rowspan="1" colspan="1">1.44 (−2.8, 5.7)</td> <td align="char" char="(" rowspan="1" colspan="1">0.84 (0.7, 1.1)</td> <td align="center" rowspan="1" colspan="1">†</td> </tr> <tr valign="top"> <td align="left" rowspan="1" colspan="1"> Education, legal, community service, arts, and media occupations</td> <td align="char" char="(" rowspan="1" colspan="1">22.58 (19.6, 25.8)</td> <td align="char" char="(" rowspan="1" colspan="1">2.92 (−0.8, 6.7)</td> <td align="char" char="(" rowspan="1" colspan="1">1.01 (0.8, 1.3)</td> <td align="center" rowspan="1" colspan="1">†</td> </tr> <tr valign="top"> <td align="left" rowspan="1" colspan="1"> Health care practitioners and technical occupations</td> <td align="char" char="(" rowspan="1" colspan="1">18.27 (14.6, 22.4)</td> <td align="char" char="(" rowspan="1" colspan="1">−0.01 (−5, 5)</td> <td align="char" char="(" rowspan="1" colspan="1">0.86 (0.6, 1.3)</td> <td align="center" rowspan="1" colspan="1">†</td> </tr> <tr valign="top"> <td align="left" rowspan="1" colspan="1"> Service occupations</td> <td align="char" char="(" rowspan="1" colspan="1">21.9 (18.6, 25.5)</td> <td align="char" char="(" rowspan="1" colspan="1">2.17 (−2.1, 6.5)</td> <td align="char" char="(" rowspan="1" colspan="1">1.01 (0.8, 1.3)</td> <td align="center" rowspan="1" colspan="1">†</td> </tr> <tr valign="top"> <td align="left" rowspan="1" colspan="1"> Sales and related occupations</td> <td align="char" char="(" rowspan="1" colspan="1">16.3 (11.8, 21.7)</td> <td align="char" char="(" rowspan="1" colspan="1">10.22 (3.6, 16.9)</td> <td align="char" char="(" rowspan="1" colspan="1">1.53 (1.3, 1.8)</td> <td align="char" char="(" rowspan="1" colspan="1">‡</td> </tr> <tr valign="top"> <td align="left" rowspan="1" colspan="1"> Office and administrative support occupations</td> <td align="char" char="(" rowspan="1" colspan="1">21.23 (18.1, 24.6)</td> <td align="char" char="(" rowspan="1" colspan="1">3.02 (−1.1, 7.1)</td> <td align="char" char="(" rowspan="1" colspan="1">0.96 (0.8, 1.2)</td> <td align="char" char="(" rowspan="1" colspan="1">†</td> </tr> <tr valign="top"> <td align="left" rowspan="1" colspan="1"> Farming, fishing, and forestry occupations</td> <td align="char" char="(" rowspan="1" colspan="1">2.03 (0.2, 7.2)</td> <td align="char" char="(" rowspan="1" colspan="1">6.85 (−1.8, 15.5)</td> <td align="char" char="(" rowspan="1" colspan="1">0.77 (0.4, 1.6)</td> <td align="char" char="(" rowspan="1" colspan="1">‡</td> </tr> <tr valign="top"> <td align="left" rowspan="1" colspan="1"> Construction and extraction occupations</td> <td align="char" char="(" rowspan="1" colspan="1">18.3 (12.2, 25.8)</td> <td align="char" char="(" rowspan="1" colspan="1">0.68 (−7.8, 9.1)</td> <td align="char" char="(" rowspan="1" colspan="1">1.27 (0.9, 1.7)</td> <td align="char" char="(" rowspan="1" colspan="1">‡</td> </tr> <tr valign="top"> <td align="left" rowspan="1" colspan="1"> Installation, maintenance, and repair occupations</td> <td align="char" char="(" rowspan="1" colspan="1">12.48 (5.2, 24)</td> <td align="char" char="(" rowspan="1" colspan="1">0.25 (−9.3, 9.7)</td> <td align="char" char="(" rowspan="1" colspan="1">1.07 (0.7, 1.5)</td> <td align="char" char="(" rowspan="1" colspan="1">‡</td> </tr> <tr valign="top"> <td align="left" rowspan="1" colspan="1"> Production occupations</td> <td align="char" char="(" rowspan="1" colspan="1">10.76 (7.6, 14.7)</td> <td align="char" char="(" rowspan="1" colspan="1">8.03 (2.8, 13.3)</td> <td align="char" char="(" rowspan="1" colspan="1">1.43 (1.1, 1.8)</td> <td align="char" char="(" rowspan="1" colspan="1">‡</td> </tr> <tr valign="top"> <td align="left" rowspan="1" colspan="1"> Transportation and material moving occupations</td> <td align="char" char="(" rowspan="1" colspan="1">21.6 (16.9, 26.9)</td> <td align="char" char="(" rowspan="1" colspan="1">−2.78 (−9.4, 3.9)</td> <td align="char" char="(" rowspan="1" colspan="1">0.88 (0.6, 1.3)</td> <td align="char" char="(" rowspan="1" colspan="1">†</td> </tr> </tbody> </table> <div class="article-table-descriptions"> <div class="article-table-descriptions-content"><span id=""><div class="dib">*Quadratic.</div></span><span id=""><div class="dib">†Linear.</div></span><span id=""><div class="dib">‡Intercept.</div></span><span id=""><div class="dib">§Difficulty concentrating, dressing/bathing, and doing errands were not available 2013–2018 or in 2021.</div></span><span id=""><div class="dib">CI, confidence interval; NH, non-Hispanic; PI, Pacific Islander.</div></span></div> </div> </div> </div> </div><br><section class="ejp-r-article-images"><figure class="ejp-r-article-images__figure"><a href="javascript:void(0)" class="ejp-r-article-images__image-link" onclick="showSlideShowByImageID('F2', '00043764-202408000-00003')"><img class="ejp-r-article-images__img js-lazy-load lazy-load" src="javascript:void(0);" data-src="https://images.journals.lww.com/joem/ArticleViewerPreview.00043764-202408000-00003.F2.jpeg" data-srcset="https://images.journals.lww.com/joem/ArticleViewerPreview@2.00043764-202408000-00003.F2.jpeg 2x" srcset="" alt="F2"></a><figcaption class="ejp-r-article-images__figcaption"><a href="javascript:void(0)" class="ejp-r-article-images__figcaption-link" onclick="showSlideShowByImageID('F2', '00043764-202408000-00003')">FIGURE 2: </a><div class="ejp-r-article-images__figcaption-text">Priority industry groups. Adjusted prevalence ratios and prevalence of unmet mental health needs in 2021 by industry group. Priority industry groups are noted in red.</div></figcaption></figure></section><p id="JCL-P-31">By occupation group, the greatest prevalence of unmet mental health needs in 2021 was among workers in sales and related (27%, CI: 22.0% to 31.5%) and education, legal, community service, and art (26%, CI: 23.2% to 27.9%) occupations. Compared with other occupation groups, sales and related occupations had the greatest absolute increase in unmet mental health needs, with a 10.2% (CI: 3.6% to 16.9%) increase from 2019. Production occupations also had an 8% (CI: 2.8% to 13.3%) absolute increase in unmet mental health needs from 2019 to 2021.</p> <h3 class="ejp-article-outline-heading" data-level="2" id="JCL12">Other Worker Groups</h3> <p id="JCL-P-32">We also observed disparities in unmet mental health needs by age and sex. More than a third of workers aged 18 to 29 years had unmet mental health needs in 2021 (35%, CI: 32.5% to 38.1%), 10 percentage points higher than any other age group. However, after adjusting for prepandemic trends, the greatest relative increases in unmet mental health needs were among workers ages 65+ years (PR: 1.27, CI: 0.9 to 1.8) and 45 to 64 years (PR: 1.21, CI: 1.0 to 1.4). Over a quarter of women had unmet mental health needs in 2021 (26%, CI: 24.5% to 27.3%), compared with 21% (CI: 19.9% to 22.5%) of men, representing a 3% (CI: 1% to 5%) and 5% (CI: 3% to 7%) absolute increase from 2019, respectively.</p> <p id="JCL-P-33">Workers reporting a severe vision or hearing problem had a high prevalence of unmet mental health needs during the pandemic. In 2021, a quarter (25%, CI: 19.5 to 31.4) of these workers had unmet mental health needs, and in the pandemic years of 2020 to 2021, the prevalence was 38% greater than expected after adjusting for prepandemic trends (PR: 1.38, CI: 1.1 to 1.8). Lastly, workers who are currently insured but did not have insurance for the entire last 12 months had a higher prevalence of unmet mental health needs (31%, CI: 25.4% to 36.6%) compared with those who have been insured for all of the past 12 months (23%, 21.7% to 23.6%) and those currently uninsured (28%, CI: 23.7% to 32.3%).</p> <h2 class="ejp-article-outline-heading" data-level="1" id="JCL13">DISCUSSION</h2> <p id="JCL-P-34">In this study, we assessed changes in unmet mental health needs among California workers since the start of the COVID-19 pandemic. The prevalence of unmet mental health needs among workers was high in California and increased through 2021, particularly for certain worker groups. Our adjusted analyses found that the observed prevalence of unmet mental health needs for all workers during the pandemic was lower than the expected prevalence had prepandemic trends continued. Although the pandemic may not have impacted unmet mental health needs as much as we would have expected for workers overall, the prevalence of unmet mental health needs still increased and remained high for certain worker groups. Workers in the information; wholesale trade; retail trade; and professional, scientific, management, and administrative and waste management services industries, as well as women workers, older workers, and disabled workers had high unmet mental health needs during the pandemic. Pandemic conditions may have exacerbated unmet mental health needs among these worker groups.</p> <p id="JCL-P-35">We found that workers in the information; wholesale trade; retail trade; and professional, scientific, management, and administrative and waste management services industries experienced high prevalence and increases in unmet mental health needs during the pandemic. In addition, workers in manufacturing industries experienced a large increase in unmet needs. Workers in wholesale and retail trade were impacted by COVID-19 restrictions including shelter-in-place orders, which caused waves of business closures and reopenings. As a result, workers in these sectors may have faced job uncertainty and financial instability.<sup><a class="ejp-citation-link js-ejp-citation-link" data-reference-links="bib27">27</a></sup> Many of these industries were deemed essential; for those that remained open, workers in public-facing industries were confronted with new workplace stressors such as unpredictable customer behavior and atypical or increased work hours along with traditional stressors such as workplace violence.<sup><a class="ejp-citation-link js-ejp-citation-link" data-reference-links="bib28 bib29">28,29</a></sup> A large number of COVID-19 outbreaks occurred among wholesale and retail industries; outbreaks and concerns over being exposed may have also contributed to stress among workers in these industries.<sup><a class="ejp-citation-link js-ejp-citation-link" data-reference-links="bib27 bib30 bib31">27,30,31</a></sup> These factors, along with reduced access to insurance or care, may have increased unmet mental health needs. Some workers in information and professional, scientific, management, and administrative and waste management services industries may have shifted to remote work, which could lead to increased isolation.<sup><a class="ejp-citation-link js-ejp-citation-link" data-reference-links="bib32">32</a></sup> Information industries comprise broadcasting, publishing, motion pictures, and data processing; many of these industries saw large cuts in revenues, faced interruptions,<sup><a class="ejp-citation-link js-ejp-citation-link" data-reference-links="bib33">33</a></sup> and often communicated rapidly changing information to the public, all of which may have increased stress among these workers.</p> <p id="JCL-P-36">Although the absolute increase in unmet mental health needs since the start of the pandemic was greater among men than women, our analysis suggests that the prevalence of unmet mental health needs is still greater among women compared with men in 2021. Similar trends have been described in earlier years elsewhere,<sup><a class="ejp-citation-link js-ejp-citation-link" data-reference-links="bib34">34</a></sup> and findings from Australia suggest that women delayed seeking care for mental health during the pandemic.<sup><a class="ejp-citation-link js-ejp-citation-link" data-reference-links="bib35">35</a></sup> Prior work has suggested that pandemic-related school closures and transitions to remote work exacerbated traditional gender roles within households, with many women juggling multiple responsibilities including childcare and ongoing work commitments.<sup><a class="ejp-citation-link js-ejp-citation-link" data-reference-links="bib36">36</a></sup> Moreover, women were more likely to face job losses, reduced working hours, and financial insecurity during the pandemic.<sup><a class="ejp-citation-link js-ejp-citation-link" data-reference-links="bib36">36</a></sup> Women also comprise the majority of caretaking occupations in the United States, including domestic workers and health care workers, which often have disproportionate risk of exposure to SARS-CoV-2.<sup><a class="ejp-citation-link js-ejp-citation-link" data-reference-links="bib36">36</a></sup> Increased risk of exposure to SARS-CoV-2 paired with financial and time constraints may have worsened women’s mental health, but also limited working women’s ability to access mental health care services during the pandemic.</p> <p id="JCL-P-37">Our findings were similar to Vahratian et al., which found that unmet mental health needs in the United States increased from 2020 to 2021, with the largest prevalence of unmet need among those aged 18 to 29 years.<sup><a class="ejp-citation-link js-ejp-citation-link" data-reference-links="bib8">8</a></sup> Whereas younger workers had the highest prevalence of unmet mental health needs in 2021, we found older workers had the greatest increases in unmet mental health needs after adjusting for prepandemic trends. Older workers may have been socially isolated or more susceptible to severe illness, leading to higher levels of anxiety about the risk of COVID-19. Yet, older individuals are often the least likely to access telehealth services.<sup><a class="ejp-citation-link js-ejp-citation-link" data-reference-links="bib37">37</a></sup> We also found a large percentage of workers living with severe vision or hearing disabilities had unmet mental health needs. Our findings are similar to those of Zhong et al, who found unmet mental health need among individuals with vision disabilities.<sup><a class="ejp-citation-link js-ejp-citation-link" data-reference-links="bib38">38</a></sup> However, studies on the mental health of people living with vision and hearing disabilities are limited. Barriers to accessing care may be more pronounced for this worker population. For example, the absence of sign language interpreters or materials in accessible formats may impede effective communication with mental health care professionals.<sup><a class="ejp-citation-link js-ejp-citation-link" data-reference-links="bib39">39</a></sup> Although CHIS did not collect 2021 data on difficulty concentrating, dressing or bathing, or doing errands alone, workers with these challenges had some of the highest prevalence of unmet mental health needs in 2019 and 2020. The lack of research and data on mental health needs of workers with disabilities is a large gap in the literature that warrants further attention.</p> <p id="JCL-P-38">Our study has multiple limitations. CHIS is not designed to be representative by industry or occupation and may not be representative of workers overall in California, which limits generalizability. Moreover, CHIS industry and occupation data are only available at the major group level, which prevents us from examining changes in unmet mental health needs at a more granular level. Major industry and occupation groups comprise multiple industries and occupations; prevalence of unmet mental health need likely varies within these groups by detailed industries and occupations. In addition, CHIS is a cross-sectional survey and does not follow the same individuals over time. Psychological distress; perceived need for an emotional, mental, drug, or alcohol problem; and seeking care for mental health issues were likely underreported given stigma surrounding mental health in the United States. Moreover, the CHIS measures used for mental health services utilization are not externally validated (ie, with insurance claims or clinical data) and are subject to social desirability bias. Our study also does not examine why workers did not seek care for emotional, mental, drug, or alcohol problems. Care-seeking behavior may be driven by changes in insurance status or other non–COVID-19–related factors, including stigma, low perceived treatment effectiveness, and structural barriers including cost and lack of transportation.<sup><a class="ejp-citation-link js-ejp-citation-link" data-reference-links="bib40 bib41 bib42 bib43">40–43</a></sup> In addition, mental health concerns may go untreated due to patients not recognizing needing mental health services.<sup><a class="ejp-citation-link js-ejp-citation-link" data-reference-links="bib21">21</a></sup> Some of our results had large confidence intervals, likely because of small sample sizes within certain worker groups. Lastly, this analysis is only through 2021; unmet mental health needs may have changed since then during the COVID-19 pandemic.</p> <p id="JCL-P-39">Understanding unmet mental health needs can inform opportunities for prevention and early intervention of mental health issues before they become more severe. However, the evidence behind mental health interventions for workers is limited and has predominantly focused on health care workers.<sup><a class="ejp-citation-link js-ejp-citation-link" data-reference-links="bib44 bib45">44,45</a></sup> Additional research on the effectiveness of mental health interventions for workers is needed. Employers in priority industry groups can consider dedicating additional resources toward employee assistance programs that center on mental health care services, including free telehealth counseling, which may increase access for individuals with logistical barriers and mobility difficulties.<sup><a class="ejp-citation-link js-ejp-citation-link" data-reference-links="bib46">46</a></sup> Although some employers provide access to mental health–related smartphone applications or digital mental health interventions, limited data exist on engagement metrics with these apps and their effectiveness on improving mental health.<sup><a class="ejp-citation-link js-ejp-citation-link" data-reference-links="bib47 bib48">47,48</a></sup> In addition, targeted messaging around access to paid sick leave for mental health days may encourage workers to access care, whereas flexible work arrangements and reasonable working hours may reduce stress for workers.<sup><a class="ejp-citation-link js-ejp-citation-link" data-reference-links="bib1 bib49">1,49</a></sup> Employers can consider opportunities to facilitate social interaction to combat feelings of isolation. Lastly, employers can conduct regular assessments to identify sources of stress and work-related mental health concerns and use these data to inform future decision-making. Employers may be motivated to provide support for employees, as there is evidence that employees experiencing depression who receive help may have higher productivity than those who do not receive help.<sup><a class="ejp-citation-link js-ejp-citation-link" data-reference-links="bib50">50</a></sup></p> <h2 class="ejp-article-outline-heading" data-level="1" id="JCL14">CONCLUSION</h2> <p id="JCL-P-40">Unmet mental health needs remain a concern for California workers. Our findings suggest that workers in information industries and older workers experienced the greatest increases in unmet mental health needs during the pandemic. In addition, younger workers, women workers, and workers with disabilities have a high prevalence of unmet mental health needs that warrants further attention. Continued investment in accessible and comprehensive mental health services will be critical to promoting mental well-being among workers.</p></section><section id="article-references" class="article-references js-article-references"><h2 class="ejp-article-outline-heading" data-level="1" id="JCL-L-1">REFERENCES</h2> <div id="bib1" class="article-references__item js-article-reference">1. Office of the Surgeon General. 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