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<?covid-19-tdm?>
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  <front>
    <journal-meta>
      <journal-id journal-id-type="publisher-id">JMH</journal-id>
      <journal-id journal-id-type="nlm-ta">JMIR Ment Health</journal-id>
      <journal-title>JMIR Mental Health</journal-title>
      <issn pub-type="epub">2368-7959</issn>
      <publisher>
        <publisher-name>JMIR Publications</publisher-name>
        <publisher-loc>Toronto, Canada</publisher-loc>
      </publisher>
    </journal-meta>
    <article-meta>
      <article-id pub-id-type="publisher-id">v8i8e29419</article-id>
      <article-id pub-id-type="pmid">34347622</article-id>
      <article-id pub-id-type="doi">10.2196/29419</article-id>
      <article-categories>
        <subj-group subj-group-type="heading">
          <subject>Original Paper</subject>
        </subj-group>
        <subj-group subj-group-type="article-type">
          <subject>Original Paper</subject>
        </subj-group>
      </article-categories>
      <title-group>
        <article-title>The Persistence of the Impact of COVID-19–Related Distress, Mood Inertia, and Loneliness on Mental Health During a Postlockdown Period in Germany: An Ecological Momentary Assessment Study</article-title>
      </title-group>
      <contrib-group>
        <contrib contrib-type="editor">
          <name>
            <surname>Torous</surname>
            <given-names>John</given-names>
          </name>
        </contrib>
      </contrib-group>
      <contrib-group>
        <contrib contrib-type="reviewer">
          <name>
            <surname>Lotto</surname>
            <given-names>Matheus</given-names>
          </name>
        </contrib>
        <contrib contrib-type="reviewer">
          <name>
            <surname>Teles</surname>
            <given-names>Ariel</given-names>
          </name>
        </contrib>
      </contrib-group>
      <contrib-group>
        <contrib id="contrib1" contrib-type="author">
          <name name-style="western">
            <surname>Haucke</surname>
            <given-names>Matthias</given-names>
          </name>
          <degrees>BSc, MSc</degrees>
          <xref rid="aff1" ref-type="aff">1</xref>
          <xref rid="aff2" ref-type="aff">2</xref>
          <ext-link ext-link-type="orcid">https://orcid.org/0000-0002-8761-1124</ext-link>
        </contrib>
        <contrib id="contrib2" contrib-type="author" corresp="yes" equal-contrib="yes">
          <name name-style="western">
            <surname>Liu</surname>
            <given-names>Shuyan</given-names>
          </name>
          <degrees>BA, MSc, PhD</degrees>
          <xref rid="aff1" ref-type="aff">1</xref>
          <address>
            <institution>Department of Psychiatry and Psychotherapy</institution>
            <institution>Charité – Universitätsmedizin Berlin</institution>
            <institution>Campus Charité Mitte</institution>
            <addr-line>Charitéplatz 1</addr-line>
            <addr-line>Berlin</addr-line>
            <country>Germany</country>
            <phone>49 30450517002</phone>
            <email>siyan908@hotmail.com</email>
          </address>
          <ext-link ext-link-type="orcid">https://orcid.org/0000-0002-6948-5734</ext-link>
        </contrib>
        <contrib id="contrib3" contrib-type="author" equal-contrib="yes">
          <name name-style="western">
            <surname>Heinzel</surname>
            <given-names>Stephan</given-names>
          </name>
          <degrees>Dipl-Psych, PhD</degrees>
          <xref rid="aff2" ref-type="aff">2</xref>
          <ext-link ext-link-type="orcid">https://orcid.org/0000-0003-2325-900X</ext-link>
        </contrib>
      </contrib-group>
      <aff id="aff1">
        <label>1</label>
        <institution>Department of Psychiatry and Psychotherapy</institution>
        <institution>Charité – Universitätsmedizin Berlin</institution>
        <institution>Campus Charité Mitte</institution>
        <addr-line>Berlin</addr-line>
        <country>Germany</country>
      </aff>
      <aff id="aff2">
        <label>2</label>
        <institution>Department of Education and Psychology</institution>
        <institution>Clinical Psychology and Psychotherapy</institution>
        <institution>Freie Universität Berlin</institution>
        <addr-line>Berlin</addr-line>
        <country>Germany</country>
      </aff>
      <author-notes>
        <corresp>Corresponding Author: Shuyan Liu <email>siyan908@hotmail.com</email></corresp>
      </author-notes>
      <pub-date pub-type="collection">
        <month>8</month>
        <year>2021</year>
      </pub-date>
      <pub-date pub-type="epub">
        <day>26</day>
        <month>8</month>
        <year>2021</year>
      </pub-date>
      <volume>8</volume>
      <issue>8</issue>
      <elocation-id>e29419</elocation-id>
      <history>
        <date date-type="received">
          <day>6</day>
          <month>4</month>
          <year>2021</year>
        </date>
        <date date-type="rev-request">
          <day>4</day>
          <month>5</month>
          <year>2021</year>
        </date>
        <date date-type="rev-recd">
          <day>24</day>
          <month>5</month>
          <year>2021</year>
        </date>
        <date date-type="accepted">
          <day>18</day>
          <month>7</month>
          <year>2021</year>
        </date>
      </history>
      <copyright-statement>©Matthias Haucke, Shuyan Liu, Stephan Heinzel. Originally published in JMIR Mental Health (https://mental.jmir.org), 26.08.2021.</copyright-statement>
      <copyright-year>2021</copyright-year>
      <license license-type="open-access" xlink:href="https://creativecommons.org/licenses/by/4.0/">
        <p>This is an open-access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in JMIR Mental Health, is properly cited. The complete bibliographic information, a link to the original publication on https://mental.jmir.org/, as well as this copyright and license information must be included.</p>
      </license>
      <self-uri xlink:href="https://mental.jmir.org/2021/8/e29419" xlink:type="simple"/>
      <abstract>
        <sec sec-type="background">
          <title>Background</title>
          <p>The first wave of the COVID-19 pandemic in early 2020 increased mental health problems globally. However, little is known about mental health problems during a low-incidence period of the pandemic without strict public health measures.</p>
        </sec>
        <sec sec-type="objective">
          <title>Objective</title>
          <p>We aim to investigate whether COVID-19–related risk factors for mental health problems persist beyond lockdown measures. We targeted a vulnerable population that is at risk of developing low mental health and assessed their daily dynamics of mood and emotion regulation after a strict lockdown.</p>
        </sec>
        <sec sec-type="methods">
          <title>Methods</title>
          <p>During a postlockdown period in Germany (between August 8, 2020, and November 1, 2020), we conducted an ecological momentary assessment with 131 participants who experienced at least mild COVID-19–related distress and loneliness. To estimate negative mood inertia, we built a lag-1 three-level autoregressive model.</p>
        </sec>
        <sec sec-type="results">
          <title>Results</title>
          <p>We found that information exposure and active daily COVID-19 cases did not have an impact on negative mood amid a postlockdown period. However, there was a day-to-day carryover effect of negative mood. In addition, worrying about COVID-19, feeling restricted by COVID-19, and feeling lonely increased negative mood.</p>
        </sec>
        <sec sec-type="conclusions">
          <title>Conclusions</title>
          <p>The mental health of a vulnerable population is still challenged by COVID-19–related stressors after the lifting of a strict lockdown. This study highlights the need to protect mental health during postpandemic periods.</p>
        </sec>
      </abstract>
      <kwd-group>
        <kwd>COVID-19</kwd>
        <kwd>outbreaks</kwd>
        <kwd>epidemics</kwd>
        <kwd>pandemics</kwd>
        <kwd>psychological responses and emotional well-being</kwd>
        <kwd>ecological momentary assessment</kwd>
        <kwd>risk and protective factors</kwd>
        <kwd>low incidence and restrictions</kwd>
      </kwd-group>
    </article-meta>
  </front>
  <body>
    <sec sec-type="introduction">
      <title>Introduction</title>
      <p>The COVID-19 pandemic and its associated socioeconomic consequences increased global mental health problems [<xref ref-type="bibr" rid="ref1">1</xref>,<xref ref-type="bibr" rid="ref2">2</xref>]. Negative mental health outcomes of the COVID-19 pandemic are associated with fear of becoming infected [<xref ref-type="bibr" rid="ref3">3</xref>,<xref ref-type="bibr" rid="ref4">4</xref>] and various mitigation strategies to curb the spread of COVID-19 (eg, curfews and restrictions to public life). These measures can disrupt regular routines, impair mood homeostasis [<xref ref-type="bibr" rid="ref5">5</xref>-<xref ref-type="bibr" rid="ref7">7</xref>], and impose economic hardship (eg, income loss and unemployment) [<xref ref-type="bibr" rid="ref8">8</xref>], which can fuel anxiety, depression, and loneliness [<xref ref-type="bibr" rid="ref9">9</xref>-<xref ref-type="bibr" rid="ref12">12</xref>]. However, it is unclear whether these effects continue after lockdown measures have been eased. As variants emerge and cause sudden spikes in COVID-19 case numbers (eg, the B.1.1.7 variant in the United Kingdom in late 2020), fear of getting infected and/or another lockdown could persist. Moreover, after the pandemic and lockdown measures end, socioeconomic uncertainty remains [<xref ref-type="bibr" rid="ref13">13</xref>]. Chronic psychological distress and social isolation are risk factors for developing mental disorders such as psychosis, substance abuse disorder, and affective disorder [<xref ref-type="bibr" rid="ref14">14</xref>-<xref ref-type="bibr" rid="ref17">17</xref>]. To investigate whether COVID-19–related stressors remain beyond lockdown measures, we set up an ecological momentary assessment (EMA) study in Germany during a postlockdown period. We focus on a group at high risk of poor mental health: those who experienced at least mild psychological distress and loneliness amid the COVID-19 pandemic. We expect a carryover effect of negative mood from one measurement to the next (mood inertia) and assume that COVID-19–related stressors (ie, momentary COVID-19–related worry, COVID-19 information seeking and perceived restriction, loneliness, and daily reported COVID-19 cases) result in an increase in momentary negative mood (<xref ref-type="supplementary-material" rid="app1">Multimedia Appendix 1</xref>).</p>
    </sec>
    <sec sec-type="methods">
      <title>Methods</title>
      <sec>
        <title>Study Design and Sampling</title>
        <p>We conducted an EMA that involves repeated sampling of individuals’ current behaviors and experiences in real time and in their natural environments [<xref ref-type="bibr" rid="ref18">18</xref>] during a postlockdown period (from August 8, 2020, to November 1, 2020) in Germany, when restrictions were lenient (eg, no private or public meeting restrictions, reopening of most leisure facilities, bars, and catering facilities; see <xref ref-type="supplementary-material" rid="app1">Multimedia Appendix 1</xref>). EMA aims to minimize recall bias, maximize ecological validity, and approximate temporal causality (ie, Granger causality) and allows researchers to study microprocesses that influence behavior in real-world contexts [<xref ref-type="bibr" rid="ref19">19</xref>]. Participants were recruited via online advertisements on universities’ websites, Twitter, and eBay classifieds. Participants had to fill in an online prequestionnaire on the Siuvo Intelligent Psychological Assessment Platform. After an initial contact via phone or email, we sent participants our study information, informed consent, and a QR code (to install a smartphone app) by mail.</p>
        <p>We targeted vulnerable individuals who reported at least mild psychological distress and sometimes felt lonely amid the COVID-19 pandemic. We used the COVID-19 Peritraumatic Distress Index (CPDI [<xref ref-type="bibr" rid="ref20">20</xref>]; cutoff score=28, indicating mild distress) questionnaire and the short-form version of the UCLA Loneliness Scale (ULS-8 [<xref ref-type="bibr" rid="ref21">21</xref>]; cutoff score=16, indicating mild loneliness), respectively. Other inclusion criteria were being at least 18 years of age, not working night shifts, not currently infected with COVID-19, using an Android smartphone, and speaking fluent German. The CPDI was designed to evaluate changes in mental health status, cognitive skills, avoidance and compulsive behavior, physical symptoms, and loss of social functioning due to the COVID-19 pandemic. The questionnaire has been previously validated in a sample in Germany [<xref ref-type="bibr" rid="ref20">20</xref>].</p>
      </sec>
      <sec>
        <title>Data Collection</title>
        <p>We used a smartphone app called “movisensXS” (movisens GmbH), which was developed for research purposes. The app is compliant with the General Data Protection Regulation (European Union) and Berlin Data Protection Act (Berliner Datenschutzgesetz – BlnDSG). Participants completed a 20-minute baseline assessment, followed by 7 consecutive days in which they received 8 randomized prompts between 8 AM and 10 PM. The study procedure was approved by the Ethics Committees of Charité – Universitätsmedizin Berlin (ref: EA2/143/20) and Freie Universität Berlin (ref: 030/2020).</p>
      </sec>
      <sec>
        <title>Measurements</title>
        <p>To quantify COVID-19–related distress, we measured worries about the COVID-19 pandemic, perceived restrictions due to the COVID-19 pandemic, COVID-19 information exposure, and feelings of loneliness. Finally, we measured respondents’ momentary negative mood (anxiety, depression, fatigue, stress, and unhappiness). All questions were measured on a visual analogue scale ranging from 0 (not at all) to 100 (very much). To account for the steady increase in active COVID-19 cases in Germany during the time of measurement [<xref ref-type="bibr" rid="ref22">22</xref>], we included daily COVID-19 cases as a predictor in our analysis. Our smartphone study consisted of a sociodemographic assessment (ie, age, gender, years of education) and the EMA. The exact EMA items can be found in <xref ref-type="supplementary-material" rid="app1">Multimedia Appendix 1</xref> and online at [<xref ref-type="bibr" rid="ref23">23</xref>].</p>
      </sec>
      <sec>
        <title>Statistical Analysis</title>
        <p>All statistical analyses were conducted in R (version 3.5.3; R Foundation for Statistical Computing [<xref ref-type="bibr" rid="ref24">24</xref>]). To consider the hierarchical data structure and autoregressive parameters, we performed model selection using autoregressive (AR) multilevel models with the dependent variable negative mood. We followed the approach by Haan-Rietdijk et al [<xref ref-type="bibr" rid="ref25">25</xref>]; details about the model selection procedure can be found in <xref ref-type="supplementary-material" rid="app1">Multimedia Appendix 1</xref> and online at [<xref ref-type="bibr" rid="ref23">23</xref>].</p>
      </sec>
    </sec>
    <sec sec-type="results">
      <title>Results</title>
      <p>We assessed 775 people for eligibility in an online questionnaire. The final sample size was 131 (18%; recruitment flow is shown in <xref rid="figure1" ref-type="fig">Figure 1</xref> and sample characteristics are shown in <xref ref-type="table" rid="table1">Table 1</xref>; for power estimation, see <xref ref-type="supplementary-material" rid="app1">Multimedia Appendix 1</xref>). No participant filled in less than 28 (50%) of the daily questionnaires, while 40 (&#60;0.01%) of the total sent daily questionnaires were not answered by the participants.</p>
      <fig id="figure1" position="float">
        <label>Figure 1</label>
        <caption>
          <p>Recruitment flow.</p>
        </caption>
        <graphic xlink:href="mental_v8i8e29419_fig1.png" alt-version="no" mimetype="image" position="float" xlink:type="simple"/>
      </fig>
      <table-wrap position="float" id="table1">
        <label>Table 1</label>
        <caption>
          <p>Demographics and sample characteristics.</p>
        </caption>
        <table width="1000" cellpadding="5" cellspacing="0" border="1" rules="groups" frame="hsides">
          <col width="500"/>
          <col width="500"/>
          <thead>
            <tr valign="top">
              <td>Parameter</td>
              <td>Values</td>
            </tr>
          </thead>
          <tbody>
            <tr valign="top">
              <td>COVID-19 Peritraumatic Distress Index score, mean (SD)</td>
              <td>48.42 (16.31)</td>
            </tr>
            <tr valign="top">
              <td>UCLA Loneliness Scale score, mean (SD)</td>
              <td>22 (4.03)</td>
            </tr>
            <tr valign="top">
              <td>Education (in years), mean (SD)</td>
              <td>15.08 (3.66)</td>
            </tr>
            <tr valign="top">
              <td>Age (in years), mean (SD)</td>
              <td>31.62 (10.76)</td>
            </tr>
            <tr valign="top">
              <td>Gender, n (%)</td>
              <td>Male: 49 (37); female: 82 (63)</td>
            </tr>
          </tbody>
        </table>
      </table-wrap>
      <p>We used a lag-1 three-level AR model, which allows us to separate the variance of negative mood scores into variance at the person level (level 3), variance at the day level (level 2), and variance at the questionnaire level (level 1). We created two lagged variables, a within-day centered predictor at questionnaire level and a within-person centered lagged predictor at the day level. The very first beep of each day (ie, the time period between the previous day’s beep and next day’s beep) was excluded from the analysis to remove possible unexplained carryover effects resulting from the night (eg, lack of sleep). This model includes mood inertias, COVID-19 worries, COVID-19 information seeking, perceived restrictions, and loneliness during the last hour, as well as daily active COVID-19 cases as random effects. The momentary negative mood score was built by averaging momentary feelings of fatigue, anxiety, depression, unhappiness, and stress. A graphical check indicated a positive skew of negative mood; therefore, we performed a square root transformation on this variable. The analysis script can be found online at [<xref ref-type="bibr" rid="ref23">23</xref>].</p>
      <p>We found that loneliness (<italic>b</italic>=.022, t<sub>3713.83</sub>=18.68, <italic>P</italic>&#60;.001), COVID-19 perceived restriction (<italic>b</italic>=.005, t<sub>129.84</sub>=3.65, <italic>P</italic>&#60;.001), COVID-19–related worry (<italic>b</italic>=.005, t<sub>132.74</sub>=2.87, <italic>P</italic>=.001), and day-to-day mood inertia (<italic>b</italic>=.078, t<sub>134.58</sub>=3.96, <italic>P</italic>=.001) increased negative mood scores. Active daily COVID-19 case numbers (<italic>b</italic>&#60;.001, t<sub>92.17</sub>=–0.27, <italic>P</italic>=.87), COVID-19–related information seeking (<italic>b</italic>&#60;.001, t<sub>88.41</sub>=0.73, <italic>P</italic>=.47), and moment-to-moment inertia (<italic>b</italic>=.015, t<sub>42.19</sub>=0.17, <italic>P</italic>=.87) did not increase negative mood scores (see <xref rid="figure2" ref-type="fig">Figure 2</xref>).</p>
      <fig id="figure2" position="float">
        <label>Figure 2</label>
        <caption>
          <p>Loneliness, COVID-19 worries, feelings of restriction, and day-to-day mood inertia increased negative mood. Moment-to-moment mood inertia, active COVID-19 cases, and COVID-19 information seeking did not increase negative mood. *<italic>P</italic>&#60;.05, **<italic>P</italic>&#60;.01, ***<italic>P</italic>&#60;.0001 (two-tailed). N=131.</p>
        </caption>
        <graphic xlink:href="mental_v8i8e29419_fig2.png" alt-version="no" mimetype="image" position="float" xlink:type="simple"/>
      </fig>
    </sec>
    <sec sec-type="discussion">
      <title>Discussion</title>
      <sec>
        <title>Principal Findings</title>
        <p>We found that negative effects of the COVID-19 pandemic on mental health outlast lockdown measures. In line with findings from the first COVID-19 wave [<xref ref-type="bibr" rid="ref8">8</xref>,<xref ref-type="bibr" rid="ref26">26</xref>-<xref ref-type="bibr" rid="ref30">30</xref>], we found that loneliness, worrying about COVID-19, and perceived restriction increased negative mood during a postlockdown period. Similar to the Ebola pandemic [<xref ref-type="bibr" rid="ref31">31</xref>], possible reasons for the lasting effect of the COVID-19 pandemic might be worries about the negative economic consequences, concern about resurgence of the virus, struggles to rebuild social networks, and/or deliberately withdrawing from social contacts to avoid infection.</p>
        <p>Furthermore, we found a negative carryover effect of mood between days (mood inertia), indicating dysfunctional mood regulation. Restrictive policies during the COVID-19 pandemic can impact mental health, possibly due to impaired mood homeostasis (ie, failure to positively regulate mood via mood-modifying activities) [<xref ref-type="bibr" rid="ref7">7</xref>]. Importantly, our results show that even when the acute threat and restrictive measures are less pronounced, negative daily mood inertia remains.</p>
        <p>Neither COVID-19 information seeking nor active COVID-19 cases increased negative mood. This contrasts with previous findings from lockdown periods [<xref ref-type="bibr" rid="ref6">6</xref>,<xref ref-type="bibr" rid="ref32">32</xref>]. For example, an EMA study during the first lockdown in Germany and Austria reported increased perceived COVID-19–related restrictions that were positively associated with increased daily news consumption, especially in individuals living alone [<xref ref-type="bibr" rid="ref32">32</xref>]. In addition, an EMA study conducted in New Jersey in the United States between April 24 and May 26, 2020, showed that undergraduates felt more anxious about COVID-19 on days when the number of new cases and deaths due to COVID-19 were higher [<xref ref-type="bibr" rid="ref6">6</xref>]. Our opposing finding might be caused by the relatively low domestic case numbers and associated news during the postlockdown period. Moreover, negative COVID-19 news might have less impact on mood over the course of the pandemic as people get accustomed to it.</p>
      </sec>
      <sec>
        <title>Limitations</title>
        <p>We did not make explicit comparisons to participant status before the COVID-19 outbreak or to a control group, which limits generalizability to other populations. Furthermore, we did not measure adaptability, which has been associated with positive mood (eg, optimism and satisfaction) [<xref ref-type="bibr" rid="ref33">33</xref>]. Finally, we did not assess the nature of COVID-19 worries and reasons for feeling restricted.</p>
      </sec>
      <sec>
        <title>Conclusions</title>
        <p>Even if cases are low and lockdown policies are lenient, mental health is still challenged by COVID-19–related stressors. Although information exposure to COVID-19 and daily COVID-19 cases had no impact on mood, we found a day-to-day carryover effect of negative mood. Moreover, COVID-19–related restriction, worry about COVID-19, and loneliness increased negative mood. Thus, the negative impact of the COVID-19 pandemic on mental health outlasts lockdown measures and mental health challenges will likely continue after the pandemic.</p>
      </sec>
    </sec>
  </body>
  <back>
    <app-group>
      <supplementary-material id="app1">
        <label>Multimedia Appendix 1</label>
        <p>Supplementary materials.</p>
        <media xlink:href="mental_v8i8e29419_app1.docx" xlink:title="DOCX File , 29 KB"/>
      </supplementary-material>
    </app-group>
    <glossary>
      <title>Abbreviations</title>
      <def-list>
        <def-item>
          <term id="abb1">AR</term>
          <def>
            <p>autoregressive</p>
          </def>
        </def-item>
        <def-item>
          <term id="abb2">CPDI</term>
          <def>
            <p>COVID-19 Peritraumatic Distress Index</p>
          </def>
        </def-item>
        <def-item>
          <term id="abb3">EMA</term>
          <def>
            <p>ecological momentary assessment</p>
          </def>
        </def-item>
        <def-item>
          <term id="abb4">ULS-8</term>
          <def>
            <p>short-form UCLA Loneliness Scale</p>
          </def>
        </def-item>
      </def-list>
    </glossary>
    <ack>
      <p>This research was supported by the Berlin University Alliance (grant to SL and SH).</p>
    </ack>
    <fn-group>
      <fn fn-type="conflict">
        <p>None declared.</p>
      </fn>
    </fn-group>
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