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The Cognitive Emotion Regulation Questionnaire-Short Specific to the COVID-19 Pandemic

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Title: The Cognitive Emotion Regulation Questionnaire-Short Specific to the COVID-19 Pandemic
Language: English
Authors: Frondozo, Cherry E. (ORCID 0000-0002-2001-1159), Mendoza, Norman B. (ORCID 0000-0003-0344-0709), Dizon, John Ian Wilzon T. (ORCID 0000-0002-4912-7390), Buenconsejo, Jet U. (ORCID 0000-0003-3777-8601)
Source: Measurement and Evaluation in Counseling and Development. 2023 56(3):225-240.
Availability: Routledge. Available from: Taylor & Francis, Ltd. 530 Walnut Street Suite 850, Philadelphia, PA 19106. Tel: 800-354-1420; Tel: 215-625-8900; Fax: 215-207-0050; Web site: http://www.tandf.co.uk/journals
Peer Reviewed: Y
Page Count: 16
Publication Date: 2023
Document Type: Journal Articles
Reports - Research
Descriptors: Cognitive Processes, Emotional Response, Self Management, Questionnaires, COVID-19, Pandemics, Adults, Foreign Countries, Test Validity, Gender Differences, Age Differences, Stress Variables, Affective Measures, Factor Analysis
Geographic Terms: Philippines
Assessment and Survey Identifiers: Positive and Negative Affect Schedule
DOI: 10.1080/07481756.2022.2102506
ISSN: 0748-1756
1947-6302
Abstract: The factor structure, measurement invariance, and external validity of the Cognitive Emotion Regulation Questionnaire-short (CERQ-short) specific to the COVID-19 pandemic was examined using data from 3,788 adult Filipinos. The nine-factor CERQ-short was confirmed and was tested invariant across gender and age groups. The CERQ factors correlate theoretically with stress and affect.
Abstractor: As Provided
Entry Date: 2023
Accession Number: EJ1395653
Database: ERIC
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  Value: <anid>AN0164958272;mev01jul.23;2023Jul19.05:03;v2.2.500</anid> <title id="AN0164958272-1">The Cognitive Emotion Regulation Questionnaire-Short Specific to the COVID-19 Pandemic </title> <p>The factor structure, measurement invariance, and external validity of the Cognitive Emotion Regulation Questionnaire-short (CERQ-short) specific to the COVID-19 pandemic was examined using data from 3,788 adult Filipinos. The nine-factor CERQ-short was confirmed and was tested invariant across gender and age groups. The CERQ factors correlate theoretically with stress and affect.</p> <p>Keywords: Cognitive emotion regulation; CERQ-short; measurement invariance; COVID-19</p> <p>The coronavirus disease 2019 (COVID-19) pandemic has brought tremendous disruptions in people's lives worldwide. Most recent global estimates indicate that there are more than 245 million confirmed cases and more than 4.9 million recorded deaths due to the virus (World Health Organization, [<reflink idref="bib60" id="ref1">60</reflink>]). The pandemic has affected several important aspects of the lives of individuals, including physical health (Tison et al., [<reflink idref="bib56" id="ref2">56</reflink>]), socio-economic issues (Nicola et al., [<reflink idref="bib39" id="ref3">39</reflink>]), and mental health outcomes (Brooks et al., [<reflink idref="bib7" id="ref4">7</reflink>]; Shigemura et al., [<reflink idref="bib54" id="ref5">54</reflink>]), such as anxiety and depression (Bendau et al., [<reflink idref="bib4" id="ref6">4</reflink>]; Bernado et al., [<reflink idref="bib6" id="ref7">6</reflink>]; Bernado and Mendoza, [<reflink idref="bib5" id="ref8">5</reflink>]; Li et al., [<reflink idref="bib32" id="ref9">32</reflink>]; Mendoza et al., [<reflink idref="bib37" id="ref10">37</reflink>]; Mendoza & Dizon, [<reflink idref="bib36" id="ref11">36</reflink>]; Salari et al., [<reflink idref="bib50" id="ref12">50</reflink>]; Shah et al., [<reflink idref="bib53" id="ref13">53</reflink>]). A key psychological mechanism that can amplify or buffer how stressors impact psychological outcomes is emotion regulation.</p> <p>Previous research suggests that emotion regulation plays an important role in people's adaptation to stressful life events (Bahlinger et al., [<reflink idref="bib2" id="ref14">2</reflink>]; McRae & Gross, [<reflink idref="bib35" id="ref15">35</reflink>]; Preuss et al., [<reflink idref="bib44" id="ref16">44</reflink>]). One specific emotion regulation strategy is cognitive emotion regulation (CER) which is characterized as the voluntary mental strategies that enables one to cope with emotionally arousing information or experience (Garnefski et al., [<reflink idref="bib17" id="ref17">17</reflink>]; Ochsner & Gross, [<reflink idref="bib40" id="ref18">40</reflink>]). Recently, cognitive emotion regulation strategies are also linked with mental health and well-being outcomes amidst the COVID-19 pandemic (Jungmann & Witthöft, [<reflink idref="bib30" id="ref19">30</reflink>]; Lábadi et al., [<reflink idref="bib31" id="ref20">31</reflink>]; Muñoz-Navarro et al., [<reflink idref="bib38" id="ref21">38</reflink>]; Panayiotou et al., [<reflink idref="bib42" id="ref22">42</reflink>]; Riaz et al., [<reflink idref="bib46" id="ref23">46</reflink>]). The importance of such strategies in how individuals cope with the resurgence of the pandemic globally calls for the reliable and valid assessment of the same.</p> <p>A widely used measure of cognitive emotion regulation strategies is the Cognitive Emotion Regulation Questionnaire-short (CERQ-short; Garnefski & Kraaij, [<reflink idref="bib18" id="ref24">18</reflink>]). The CERQ-short is an 18-item instrument which consists of nine subscales: <emph>Self-blame, Other-blame, Rumination, Catastrophizing, Putting into Perspective, Positive Refocusing, Positive Appraisal, Acceptance,</emph> and <emph>Planning</emph>. The development of the CERQ-short was deemed necessary considering the need for a brief screening instrument among psychiatric patients, and for inclusion to large self-report researches. The nine dimensions of the CERQ-short can also be categorized into adaptive and less adaptive strategies. The less adaptive strategies measured by CERQ, such as self-blame, rumination, catastrophizing, were consistently positively associated with negative emotions such as loneliness (Gubler et al., [<reflink idref="bib23" id="ref25">23</reflink>]), anxiety (Jungmann & Witthöft, [<reflink idref="bib30" id="ref26">30</reflink>]; Muñoz-Navarro et al., [<reflink idref="bib38" id="ref27">38</reflink>]; Orgilés et al., [<reflink idref="bib41" id="ref28">41</reflink>]), and depression (Orgilés et al., [<reflink idref="bib41" id="ref29">41</reflink>]). The adaptive strategies such as positive refocusing, positive appraisal, planning, and putting into perspective were found to be inversely related to negative emotions and cognitions (d'Acremont & Van der Linden, [<reflink idref="bib11" id="ref30">11</reflink>]; Garnefski et al., 2002; Garnefski & Kraaij, [<reflink idref="bib19" id="ref31">19</reflink>]; Gubler et al., [<reflink idref="bib23" id="ref32">23</reflink>]; Jungmann & Witthöft, [<reflink idref="bib30" id="ref33">30</reflink>]; Martin & Dahlen, [<reflink idref="bib34" id="ref34">34</reflink>]; Muñoz-Navarro et al., [<reflink idref="bib38" id="ref35">38</reflink>]; Orgilés et al., [<reflink idref="bib41" id="ref36">41</reflink>]; Sakakibara & Kitahara, [<reflink idref="bib49" id="ref37">49</reflink>]).</p> <p>The CERQ-short has already been validated in several samples worldwide (Cakmak & Cevik, [<reflink idref="bib8" id="ref38">8</reflink>]; de Castro Araujo et al., [<reflink idref="bib12" id="ref39">12</reflink>]; Garnefski & Kraaij, [<reflink idref="bib18" id="ref40">18</reflink>]; Ireland et al., [<reflink idref="bib27" id="ref41">27</reflink>]; Orgilés et al., [<reflink idref="bib41" id="ref42">41</reflink>]; Propheta & van Zyl, [<reflink idref="bib45" id="ref43">45</reflink>]) and has been used as a measure of cognitive emotion regulation strategies during the COVID-19 health crisis (Gubler et al., [<reflink idref="bib23" id="ref44">23</reflink>]; Jungmann & Witthöft, [<reflink idref="bib30" id="ref45">30</reflink>]; Muñoz-Navarro et al., [<reflink idref="bib38" id="ref46">38</reflink>]). No published study has examined the measurement invariance of the factor structure of the CERQ-short during the pandemic, especially in a non-Western, lower- and middle-income context. Given the emotional and psychological toll brought by the global pandemic, evaluating how individuals use cognitive emotion regulation strategies are important not only to accurately assess one's emotion regulation strategies but also to help professionals develop proper intervention models in sustainably managing the mental health effects of the pandemic. Therefore, the present study aims to adapt the CERQ-items to develop a COVID-19-specific CERQ-short and examine its score reliability, validity (i.e., construct and criterion-related validity), factor structure, and measurement invariance (i.e., configural, metric, scalar, and strict) using data from adults collected in the Philippines from March to July 2020—during the onset of the pandemic.</p> <hd id="AN0164958272-2">The CERQ-Short</hd> <p>The CERQ-short (Garnefski & Kraaij, [<reflink idref="bib18" id="ref47">18</reflink>]) is an 18-item self-report scale of cognitive coping or cognitive emotion regulation strategies for general populations. It originated from the 36-item CERQ (Garnefski et al., [<reflink idref="bib20" id="ref48">20</reflink>]). The CERQ-short was designed to assess an individual's cognitive emotion regulation strategies by asking questions that pertain to negative or unpleasant events that one had experienced. The CERQ-short particularly asks questions such as "<emph>I feel that I am the one who is responsible for what happened"</emph> and "<emph>I keep thinking about how terrible it is what I have experienced"</emph> to which individuals can respond using the scale responses ranging from "<emph>Almost never (<reflink idref="bib1" id="ref49">1</reflink>)"</emph> to "<emph>Almost always (<reflink idref="bib5" id="ref50">5</reflink>)</emph>." The CERQ-short subscale scores can be obtained by summing up the items that correspond to each subscale. The total score of each subscale ranges from 2 to 10, with higher scores indicating the most frequently used cognitive strategy. Scores from the scale have been validated in a mixed adult and student general samples in the Netherlands (Garnefski & Kraaij, [<reflink idref="bib18" id="ref51">18</reflink>]), Brazil (de Castro Araujo et al., [<reflink idref="bib12" id="ref52">12</reflink>]), Australia (Ireland et al., [<reflink idref="bib27" id="ref53">27</reflink>]); children samples in Spain (Orgilés et al., [<reflink idref="bib41" id="ref54">41</reflink>]); and university student samples in South Africa (Propheta & van Zyl, [<reflink idref="bib45" id="ref55">45</reflink>]) and Turkey (Cakmak & Cevik, [<reflink idref="bib8" id="ref56">8</reflink>]). Although the CERQ-short yields valid and reliable scores across different contexts, previous validation studies were primarily focused on Western and some Middle Eastern and Oceania countries. Moreso, none so far has adapted the CERQ-short to a specific domain or context that is the COVID-19 pandemic.</p> <p>Gender and age differences in the use of different cognitive emotion regulation strategies were found (Garnefski et al., [<reflink idref="bib21" id="ref57">21</reflink>]; Santos et al., [<reflink idref="bib51" id="ref58">51</reflink>]), though results were inconsistent (Carvajal et al., [<reflink idref="bib9" id="ref59">9</reflink>]; Theurel & Gentaz, [<reflink idref="bib55" id="ref60">55</reflink>]). In addition, validation studies on the CERQ-short had adequate invariance across age and gender (Santos et al., [<reflink idref="bib52" id="ref61">52</reflink>]), however, measurement invariance of the scores of the adapted scale for the COVID-19 pandemic has not yet been tested.</p> <p>This study aims to adapt and evaluate the psychometric properties of the data from a COVID-specific CERQ-short. Specifically, we aimed to test the internal reliability, factor structure (nine-factor structure vs. hierarchical structure), measurement invariance, and criterion-related validity of the scores from the adapted scale. We used data from 3,877 adults collected during the early onset of the COVID-19 pandemic in the Philippines to: (a) conduct confirmatory factor analysis in testing the nine-factor structure of the COVID-specific CERQ-short against its hierarchical structure composed of adaptive and less adaptive second-order factors; (b) test the measurement invariance (configural, metric, scalar, strict invariance) of the superior CERQ-short factor structure across gender and age groups; and (c) examine the correlation of CERQ-short factor scores with stress, negative affect, and positive affect to demonstrate criterion-related validity.</p> <hd id="AN0164958272-3">Methods</hd> <p></p> <hd id="AN0164958272-4">Participants</hd> <p>A total of 3,877 Filipino adults aged 18 to 73 years old (<emph>M</emph> = 29.64; <emph>SD</emph> = 9.02) participated in an Internet-based survey launched from March to June 2020. The majority of the respondents were females (74.85%), single (74.44%), and employed (57.21%) at that time. Nearly half of the respondents were from the country's capital, Metro Manila (44.93%). The details of the demographic groups are found in Table 1.</p> <p>Table 1. Demographic Characteristics of the Sample (n = 3,877).</p> <p> <ephtml> <table><thead><tr><td /><td>Group</td><td>N</td><td>%</td></tr></thead><tbody valign="top"><tr><td>Gender</td><td>Male</td><td char=".">975</td><td char=".">25.15</td></tr><tr><td /><td>Female</td><td char=".">2,902</td><td char=".">74.85</td></tr><tr><td>Civil status</td><td>Single</td><td char=".">2,886</td><td char=".">74.44</td></tr><tr><td /><td>Married/cohabiting</td><td char=".">866</td><td char=".">22.34</td></tr><tr><td /><td>Others</td><td char=".">125</td><td char=".">3.22</td></tr><tr><td>Locale</td><td>Capital (Manila)</td><td char=".">1,742</td><td char=".">44.93</td></tr><tr><td /><td>Other regions:</td><td char=".">2,135</td><td char=".">55.07</td></tr><tr><td /><td>Region 1—Ilocos Region</td><td char=".">101</td><td char=".">2.61</td></tr><tr><td /><td>Region 2—Cagayan Valley</td><td char=".">40</td><td char=".">1.03</td></tr><tr><td /><td>Region 3—Central Luzon</td><td char=".">529</td><td char=".">13.64</td></tr><tr><td /><td>Region 4-A—CALABARZON</td><td char=".">698</td><td char=".">18.00</td></tr><tr><td /><td>Region 4-B—MIMOROPA</td><td char=".">40</td><td char=".">1.03</td></tr><tr><td /><td>Region 5—Bicol Region</td><td char=".">110</td><td char=".">2.84</td></tr><tr><td /><td>Region 6—Western Visayas</td><td char=".">98</td><td char=".">2.53</td></tr><tr><td /><td>Region 7—Central Visayas</td><td char=".">98</td><td char=".">2.53</td></tr><tr><td /><td>Region 8—Eastern Visayas</td><td char=".">31</td><td char=".">0.80</td></tr><tr><td /><td>Region 9—Zamboanga Peninsula</td><td char=".">23</td><td char=".">0.59</td></tr><tr><td /><td>Region 10—Northern Mindanao</td><td char=".">28</td><td char=".">0.72</td></tr><tr><td /><td>Region 11—Davao Region</td><td char=".">44</td><td char=".">1.13</td></tr><tr><td /><td>Region 12—SOCCSKSARGEN</td><td char=".">28</td><td char=".">0.72</td></tr><tr><td /><td>Region 13—CARAGA</td><td char=".">17</td><td char=".">0.44</td></tr><tr><td /><td>CAR (Cordillera Administrative Region)</td><td char=".">81</td><td char=".">2.09</td></tr><tr><td /><td>BARMM (Bangsamoro Autonomous Region in Muslim Mindanao)</td><td char=".">5</td><td char=".">0.13</td></tr><tr><td /><td>Others</td><td char=".">164</td><td char=".">4.23</td></tr><tr><td>Demographic group</td><td>Students</td><td char=".">876</td><td char=".">22.59</td></tr><tr><td /><td>Employees</td><td char=".">2,218</td><td char=".">57.21</td></tr><tr><td /><td>Unemployed at the time of survey</td><td char=".">209</td><td char=".">5.39</td></tr><tr><td /><td>Frontline workers</td><td char=".">130</td><td char=".">3.35</td></tr><tr><td /><td>Others</td><td char=".">444</td><td char=".">11.45</td></tr></tbody></table> </ephtml> </p> <hd id="AN0164958272-5">Procedures</hd> <p>The instruments administered in this study were part of this online self-screener survey conducted during the COVID-19 outbreak in the Philippines in March to July 2020. Two psychologists from a nonprofit organization registered with the National Youth Commission in the Philippines examined and approved the ethics, measures, and procedures used in the study. The study procedures adhere to the 1964 Helsinki Declaration and its revisions, as well as comparable ethical requirements for research involving human participants. All participants were asked for informed consent, and those who refused were directed to an exit page with information on mental health support and referrals to care. We did not collect any personal identifying information from the respondents. Respondents were given links to COVID-19 information and mental health services after completing the survey. The procedures related to the adaptation of the CERQ-short specific to the COVID-19 pandemic are written below.</p> <hd id="AN0164958272-6">Measures</hd> <p></p> <hd id="AN0164958272-7">Cognitive Emotion Regulation amid COVID-19</hd> <p>We adapted the CERQ-short (Garnefski & Kraaij, [<reflink idref="bib18" id="ref62">18</reflink>]) in measuring cognitive emotion regulation strategies specific for COVID-19. The adapted version was also in English. The context-specific adaptation of the CERQ-short is embedded within the instruction, and the original 18 items of the CERQ-short were adapted. For instance, an item under the planning subscale "<emph>I continually think how horrible the situation has been</emph>" was adapted to "<emph>I continually think how horrible the COVID-19 pandemic has been</emph>." For an item under the rumination subscale, the item "<emph>I am preoccupied with what I think and feel about what I have experienced</emph>" was adapted to "<emph>I am preoccupied with what I think and feel about the spread of COVID-19 virus</emph>." We sought permission from the original authors to adapt the scale and it was granted. The CERQ-short instructions and items were adapted and reviewed by three licensed mental health professionals (i.e., psychometricians) in the Philippines. The adapted CERQ-short was consequently pilot tested to 10 respondents for readability, ease of understanding, and applicability. Minor revisions were applied to the instrument following feedback from the pilot test. The internal consistencies of the subscales (α =.69 to.91) were found to be within the acceptable range of.68 to.86 set by the original authors of the scale (Garnefski & Kraaij, [<reflink idref="bib18" id="ref63">18</reflink>]) and other psychometric guidelines (Hair et al., [<reflink idref="bib24" id="ref64">24</reflink>]). Similar to the original CERQ-short scale, participants responded to the items on a scale of 1 <emph>(almost) never</emph> to 5 <emph>(almost) always</emph>. The sum of item scores for each subscale is taken to derive the subscale scores. Higher scores indicate a more frequent use of the specific emotion regulation strategy.</p> <hd id="AN0164958272-8">Positive and Negative Affect</hd> <p>The Positive and Negative Affect Schedule (PANAS; Watson et al., [<reflink idref="bib59" id="ref65">59</reflink>]) was used to measure positive and negative emotions. Participants rated ten emotion items based on the extent of how they felt each emotion in the past week, from a scale of 1 (<emph>very slightly or not at all</emph>) to 5 (<emph>extremely</emph>). Scores from both the positive emotions subscale (α =.87) and negative emotions subscale (α =.84) displayed adequate internal consistency in the current sample.</p> <hd id="AN0164958272-9">Stress Symptoms—Stress Subscale (DASS-S)</hd> <p>We used the 7-item stress subscale of DASS-21 (Lovibond & Lovibond, [<reflink idref="bib33" id="ref66">33</reflink>]). The DASS-S includes items measuring irritability, tension, and a tendency for heightened reactions to overly stressful events for a non-clinical sample (Antony et al., [<reflink idref="bib1" id="ref67">1</reflink>]). Participants rated items on a response scale from 0 (<emph>never</emph>) to 3 (<emph>almost always</emph>), based on how much the items applied to them in the past week. DASS-S scores had adequate internal reliability in this study (α =.88).</p> <hd id="AN0164958272-10">Data Analysis</hd> <p>Descriptive statistics, including testing normality assumptions, were conducted. Incomplete responses were treated as null responses and were subject to listwise deletion. The sample in this study has no missing data. Although the nine-factor structure was established in previous research (Ireland et al., [<reflink idref="bib27" id="ref68">27</reflink>]; Propheta & van Zyi, [<reflink idref="bib45" id="ref69">45</reflink>]), due the large sample size, we opted to randomly split the data and run a complementary exploratory factor analysis (EFA) and confirmatory factor analysis (CFA) to have a more robust testing of the CERQ-Short's factor structure.</p> <p>EFA with an oblique rotation (i.e., oblimin) was conducted to explore the underlying structure of the items. To examine the potential number of factors of the CERQ-Short, we used parallel analysis scree plot. Depending on the result of the parallel analysis, we also further evaluated the model fit indices of the suggested number of factors, to determine the most optimal factor structure (see Finch, [<reflink idref="bib16" id="ref70">16</reflink>]). The standardized loadings from the pattern matrix of the EFA factor structure were interpreted using a factor loading cutoff of at least.40 and no cross-loading (i.e., item loading >.30 in other factors). The correlation and internal consistency of the factors were also computed.</p> <p>CFA in R lavaan package (Rosseel, [<reflink idref="bib48" id="ref71">48</reflink>]) was used to test the nine-factor structure of the CERQ-Short. We also tested a unidimensional structure for comparison and a hierarchical model where the nine first-order factors were loaded under two-second order factors: adaptive factors (i.e., acceptance, planning, positive refocusing, positive reappraisal, and putting into perspective) and less adaptive factors (i.e., self-blaming, other blaming, rumination, and catastrophizing). This procedure was implemented by Feliu-Soler et al. ([<reflink idref="bib13" id="ref72">13</reflink>]) in the full CERQ scale to whether CERQ factors can be evaluated as adaptive and less adaptive cognitive regulations of emotions. We used the maximum likelihood estimator with robust standard errors, and a Satorra-Bentler scaled test statistic (SBχ<sups>2</sups>) to test the CFA. However, since a non-significant result is difficult to obtain with larger samples, other fit indices, including comparative fit index (<emph>CFI</emph>), Tucker-Lewis index (<emph>TLI</emph>), root mean square error of approximation (<emph>RMSEA</emph>), standardized root mean square residual (<emph>SRMR</emph>) were also used to evaluate goodness-of-fit (Barrett, [<reflink idref="bib3" id="ref73">3</reflink>]). Models with <emph>CFI</emph> and <emph>TLI</emph> >.90 and <emph>RMSEA</emph> <.08 were deemed to have an adequate fit for the data (Hu & Bentler, [<reflink idref="bib25" id="ref74">25</reflink>]), while <emph>SRMR</emph> <.08 was deemed as a good fit to the data (Hu & Bentler, [<reflink idref="bib26" id="ref75">26</reflink>]).</p> <p>To test measurement invariance, multigroup CFA was used to test models according to groups formed by key demographic characteristics (i.e., gender and age). Multigroup CFA was conducted using equaltestMI (Jiang & Mai, [<reflink idref="bib29" id="ref76">29</reflink>]). To determine measurement invariance, we followed Chen's ([<reflink idref="bib10" id="ref77">10</reflink>]) recommendations for samples greater than 300: a change of <emph>CFI</emph> (Δ<emph>CFI</emph>) that is less than or equal to.01, supplemented by a change of <emph>RMSEA</emph> (Δ<emph>RMSEA</emph>) that is less than or equal to.015 or a change in <emph>SRMR</emph> (Δ<emph>SRMR</emph>) that is less than or equal to.03 will indicate invariance. The initial multigroup CFA model for each group allowed all factor loadings, uniqueness, and correlations to be freely estimated. Configural, metric, scalar, and strict invariance were subsequently tested by constraining factor structure, factor loadings, intercepts, and errors, respectively. Finally, to test for criterion-related validity, we evaluated how the CERQ factors correlate to stress, negative affect, and positive affect.</p> <hd id="AN0164958272-11">Results</hd> <p></p> <hd id="AN0164958272-12">Preliminary Analyses</hd> <p>Table 2 presents the bivariate correlations and reliability coefficients of the nine CERQ factors as well as the adaptive (i.e., Acceptance, Planning, Positive Refocusing, Positive Reappraisal, and Putting into Perspective) and less adaptive (i.e., Self-blaming, Other Blaming, Rumination, and Catastrophizing) strategies.</p> <p>Table 2. Subscale and Factor Intercorrelations, Reliability Coefficients, and Descriptive and Normality Statistics.</p> <p> <ephtml> <table><thead><tr><td /><td>CERQ factors</td><td>STR</td><td>NA</td><td>PA</td><td char=".">1</td><td char=".">2</td><td char=".">3</td><td char=".">4</td><td char=".">5</td><td char=".">6</td><td char=".">7</td><td char=".">8</td><td char=".">9</td><td char=".">10</td><td char=".">11</td></tr></thead><tbody valign="top"><tr><td char=".">1</td><td>Adaptive</td><td char=".">−.26*</td><td char=".">−.25*</td><td char=".">.54*</td><td>(0.83)</td><td /><td /><td /><td /><td /><td /><td /><td /><td /><td /></tr><tr><td char=".">2</td><td>Less adaptive</td><td char=".">.41*</td><td char=".">.46*</td><td char=".">−.07*</td><td char=".">0.06*</td><td>(0.80)</td><td /><td /><td /><td /><td /><td /><td /><td /><td /></tr><tr><td char=".">3</td><td>Self-blame</td><td char=".">.08*</td><td char=".">.10*</td><td char=".">.11*</td><td char=".">0.15*</td><td char=".">0.44*</td><td>(0.69)</td><td /><td /><td /><td /><td /><td /><td /><td /></tr><tr><td char=".">4</td><td>Other blame</td><td char=".">.24*</td><td char=".">.28*</td><td char=".">−.07*</td><td char=".">0.02</td><td char=".">0.73*</td><td char=".">0.15*</td><td>(0.91)</td><td /><td /><td /><td /><td /><td /><td /></tr><tr><td char=".">5</td><td>Rumination</td><td char=".">.37*</td><td char=".">.40*</td><td char=".">−.04*</td><td char=".">0.09*</td><td char=".">0.76*</td><td char=".">0.18*</td><td char=".">0.32*</td><td>(0.79)</td><td /><td /><td /><td /><td /><td /></tr><tr><td char=".">6</td><td>Catastrophizing</td><td char=".">.42*</td><td char=".">.46*</td><td char=".">−.15*</td><td char=".">−0.05*</td><td char=".">0.81*</td><td char=".">0.13*</td><td char=".">0.44*</td><td char=".">0.60*</td><td>(0.89)</td><td /><td /><td /><td /><td /></tr><tr><td char=".">7</td><td>Acceptance</td><td char=".">.03</td><td char=".">.02</td><td char=".">.09*</td><td char=".">0.52*</td><td char=".">0.18*</td><td char=".">0.05*</td><td char=".">0.08**</td><td char=".">0.26*</td><td char=".">0.11*</td><td>(0.86)</td><td /><td /><td /><td /></tr><tr><td char=".">8</td><td>Planning</td><td char=".">−.12*</td><td char=".">−.10*</td><td char=".">.43*</td><td char=".">0.70*</td><td char=".">0.17*</td><td char=".">0.14*</td><td char=".">0.09*</td><td char=".">0.19*</td><td char=".">0.10*</td><td char=".">0.16*</td><td>(0.77)</td><td /><td /><td /></tr><tr><td char=".">9</td><td>Refocusing</td><td char=".">−.32*</td><td char=".">−.31*</td><td char=".">.43*</td><td char=".">0.68*</td><td char=".">−0.11*</td><td char=".">0.07*</td><td char=".">−0.05*</td><td char=".">−0.11*</td><td char=".">−0.18*</td><td char=".">0.17*</td><td char=".">0.38*</td><td>(0.80)</td><td /><td /></tr><tr><td char=".">10</td><td>Reappraisal</td><td char=".">−.30*</td><td char=".">−.25*</td><td char=".">.53*</td><td char=".">0.80*</td><td char=".">0.04**</td><td char=".">0.10*</td><td char=".">0.01</td><td char=".">0.06*</td><td char=".">−0.02</td><td char=".">0.23*</td><td char=".">0.57*</td><td char=".">0.44*</td><td>(0.84)</td><td /></tr><tr><td char=".">11</td><td>PIP</td><td char=".">−.21*</td><td char=".">−.21*</td><td char=".">.37*</td><td char=".">0.70*</td><td char=".">−0.09*</td><td char=".">0.13*</td><td char=".">−0.07*</td><td char=".">−0.07*</td><td char=".">−0.18*</td><td char=".">0.18*</td><td char=".">0.31*</td><td char=".">0.37*</td><td char=".">0.48*</td><td>(0.79)</td></tr><tr><td /><td>Mean</td><td char=".">8.78</td><td char=".">13.66</td><td char=".">14.44</td><td char=".">31.88</td><td char=".">21.31</td><td char=".">2.93</td><td char=".">6.12</td><td char=".">5.95</td><td char=".">6.30</td><td char=".">7.15</td><td char=".">6.25</td><td char=".">6.17</td><td char=".">6.98</td><td char=".">5.33</td></tr><tr><td /><td>SD</td><td char=".">5.14</td><td char=".">4.93</td><td char=".">4.72</td><td char=".">7.70</td><td char=".">6.11</td><td char=".">6.12</td><td char=".">2.50</td><td char=".">2.18</td><td char=".">2.34</td><td char=".">2.33</td><td char=".">2.16</td><td char=".">2.12</td><td char=".">2.33</td><td char=".">2.39</td></tr><tr><td /><td>Skewness</td><td char=".">0.28</td><td char=".">0.12</td><td char=".">0.14</td><td char=".">0.12</td><td char=".">0.27</td><td char=".">2.14</td><td char=".">0.10</td><td char=".">0.19</td><td char=".">0.07</td><td char=".">−0.36</td><td char=".">0.07</td><td char=".">0.18</td><td char=".">−0.30</td><td char=".">0.34</td></tr><tr><td /><td>Kurtosis</td><td char=".">−0.64</td><td char=".">−0.88</td><td char=".">−0.59</td><td char=".">−0.59</td><td char=".">−0.32</td><td char=".">4.57</td><td char=".">−1.12</td><td char=".">−0.83</td><td char=".">−1.08</td><td char=".">−0.92</td><td char=".">−0.84</td><td char=".">−0.89</td><td char=".">−0.99</td><td char=".">−0.91</td></tr></tbody></table> </ephtml> </p> <p>1 <emph>Note</emph>. Correlations between CERQ factors to stress (STR), negative affect (NA), and positive affect (PA) are indicators for criterion-related validity; parentheses in diagonals are internal reliability ratings (Cronbach's alpha); PIP = putting into perspective.</p> <p>2 *<0.001, **<0.01.</p> <hd id="AN0164958272-13">Exploratory Factor Analysis</hd> <p>Using the first randomly selected half of the sample (<emph>n</emph> = 1938), the Kaiser-Meyer-Olkin (KMO) =.76 and the Barlett's test of sphericity χ<sups>2</sups> (<reflink idref="bib153" id="ref78">153</reflink>) = 16,996.85, <emph>p</emph> <.001 indicating that the sample is adequate for factor analysis. The parallel analysis suggests seven factors although the scree plot visually suggests the possibility of nine factors. To resolve the optimal number of factors for the EFA, we evaluated the model fit indices of the seven-factor and nine-factor structure. This method is used to determine the optimal number of factors for EFA (see Finch, [<reflink idref="bib16" id="ref79">16</reflink>]). Comparing the EFA fit indices, results suggest that the nine-factor structure [χ<sups>2</sups> (<reflink idref="bib27" id="ref80">27</reflink>) = 31.03, <emph>CFI</emph> =.999, <emph>TLI</emph> =.999, <emph>RMSEA</emph> =.01, <emph>SRMR</emph> =.00] has a better model fit than the seven-factor structure [χ<sups>2</sups> (<reflink idref="bib48" id="ref81">48</reflink>) = 938.04, <emph>CFI</emph> =.947, <emph>TLI</emph> =.831, <emph>RMSEA</emph> =.10, <emph>SRMR</emph> =.03]. Table 3 shows the items that loaded on each factor, which were aligned with the original nine-factor structure of the CERQ-Short. All items had a factor loading greater than.40 and none of the items cross-loaded on other factors. The nine factors accounted for a cumulative variance of 72%.</p> <p>Table 3. Pattern Matrix of the Exploratory Factor Analysis with Oblique Rotation.</p> <p> <ephtml> <table><thead><tr><td>CERQ-Short Items</td><td>Other-Blame</td><td>Catastrophizing</td><td>Acceptance</td><td>Reappraise</td><td>Refocus</td><td>Putting into Perspective</td><td>Rumination</td><td>Self-Blame</td><td>Planning</td></tr></thead><tbody valign="top"><tr><td char=".">1. I often think about how I feel about the spread of COVID-19.</td><td char=".">−0.01</td><td char=".">0.15</td><td char=".">0.17</td><td char=".">0.01</td><td char=".">0.00</td><td char=".">0.00</td><td><bold>0.57</bold></td><td char=".">−0.01</td><td char=".">0.07</td></tr><tr><td char=".">2. I am preoccupied with what I think and feel about the spread of COVID-19 virus.</td><td char=".">0.02</td><td char=".">−0.01</td><td char=".">−0.03</td><td char=".">0.01</td><td char=".">0.00</td><td char=".">−0.01</td><td><bold>0.94</bold></td><td char=".">0.01</td><td char=".">−0.01</td></tr><tr><td char=".">3. I think of pleasant things that have nothing to do with the spread of COVID-19.</td><td char=".">0.00</td><td char=".">0.00</td><td char=".">0.01</td><td char=".">−0.04</td><td><bold>0.86</bold></td><td char=".">−0.01</td><td char=".">0.07</td><td char=".">−0.02</td><td char=".">−0.02</td></tr><tr><td char=".">4. I think of something nice instead of the spread of COVID-19.</td><td char=".">0.01</td><td char=".">−0.01</td><td char=".">−0.01</td><td char=".">0.06</td><td><bold>0.77</bold></td><td char=".">0.02</td><td char=".">−0.10</td><td char=".">0.02</td><td char=".">0.04</td></tr><tr><td char=".">5. I think about how to change the situation surrounding the pandemic.</td><td char=".">0.02</td><td char=".">0.01</td><td char=".">0.00</td><td char=".">−0.06</td><td char=".">−0.01</td><td char=".">0.02</td><td char=".">0.02</td><td char=".">0.00</td><td><bold>0.83</bold></td></tr><tr><td char=".">6. I think about a plan of what I can do best.</td><td char=".">−0.02</td><td char=".">−0.01</td><td char=".">0.01</td><td char=".">0.18</td><td char=".">0.05</td><td char=".">0.00</td><td char=".">−0.02</td><td char=".">0.02</td><td><bold>0.66</bold></td></tr><tr><td char=".">7. I think I can learn something from the situation.</td><td char=".">0.00</td><td char=".">0.01</td><td char=".">0.02</td><td><bold>0.91</bold></td><td char=".">−0.01</td><td char=".">−0.04</td><td char=".">−0.01</td><td char=".">0.00</td><td char=".">0.02</td></tr><tr><td char=".">8. I think that I can become a stronger person as a result of what has happened during the pandemic.</td><td char=".">0.00</td><td char=".">−0.03</td><td char=".">−0.02</td><td><bold>0.72</bold></td><td char=".">0.06</td><td char=".">0.13</td><td char=".">0.04</td><td char=".">0.00</td><td char=".">0.02</td></tr><tr><td char=".">9. I think that the pandemic hasn't been too bad compared to other things.</td><td char=".">−0.03</td><td char=".">−0.07</td><td char=".">−0.01</td><td char=".">−0.01</td><td char=".">0.02</td><td><bold>0.80</bold></td><td char=".">0.03</td><td char=".">0.01</td><td char=".">0.06</td></tr><tr><td char=".">10. I tell myself that there are worse things in life.</td><td char=".">0.03</td><td char=".">0.06</td><td char=".">0.03</td><td char=".">0.03</td><td char=".">−0.01</td><td><bold>0.78</bold></td><td char=".">−0.04</td><td char=".">0.00</td><td char=".">−0.04</td></tr><tr><td char=".">11. I keep thinking about how terrible the spread of COVID-19 is.</td><td char=".">−0.03</td><td><bold>0.96</bold></td><td char=".">0.01</td><td char=".">0.01</td><td char=".">0.02</td><td char=".">0.02</td><td char=".">−0.01</td><td char=".">−0.01</td><td char=".">0.00</td></tr><tr><td char=".">12. I continually think how horrible the COVID-19 situation has been.</td><td char=".">0.00</td><td><bold>0.81</bold></td><td char=".">−0.02</td><td char=".">−0.01</td><td char=".">−0.03</td><td char=".">−0.03</td><td char=".">0.05</td><td char=".">0.02</td><td char=".">0.01</td></tr><tr><td char=".">13. I feel that others are responsible for the spread of COVID-19.</td><td><bold>0.88</bold></td><td char=".">0.02</td><td char=".">0.00</td><td char=".">0.01</td><td char=".">0.00</td><td char=".">−0.03</td><td char=".">0.00</td><td char=".">0.02</td><td char=".">0.02</td></tr><tr><td char=".">14. I feel that basically the cause lies with others.</td><td><bold>0.95</bold></td><td char=".">−0.02</td><td char=".">0.00</td><td char=".">0.00</td><td char=".">0.00</td><td char=".">0.02</td><td char=".">0.01</td><td char=".">−0.02</td><td char=".">−0.01</td></tr><tr><td char=".">15. I feel that I am the one who is responsible for the spread of COVID-19.</td><td char=".">0.00</td><td char=".">−0.01</td><td char=".">0.01</td><td char=".">−0.03</td><td char=".">−0.01</td><td char=".">−0.01</td><td char=".">−0.01</td><td><bold>0.88</bold></td><td char=".">0.02</td></tr><tr><td char=".">16. I think that basically the cause of the spread of COVID-19 must lie within myself.</td><td char=".">0.01</td><td char=".">0.02</td><td char=".">−0.02</td><td char=".">0.07</td><td char=".">0.02</td><td char=".">0.04</td><td char=".">0.04</td><td><bold>0.61</bold></td><td char=".">−0.05</td></tr><tr><td char=".">17. I think that I have to accept the spread of COVID-19.</td><td char=".">0.02</td><td char=".">0.02</td><td><bold>0.85</bold></td><td char=".">−0.02</td><td char=".">−0.02</td><td char=".">0.02</td><td char=".">0.01</td><td char=".">−0.01</td><td char=".">−0.01</td></tr><tr><td char=".">18. I think that I have to accept the pandemic situation.</td><td char=".">−0.01</td><td char=".">−0.03</td><td><bold>0.90</bold></td><td char=".">0.02</td><td char=".">0.02</td><td char=".">−0.01</td><td char=".">−0.01</td><td char=".">0.01</td><td char=".">0.01</td></tr><tr><td>Cumulative variance explained</td><td char=".">0.09</td><td char=".">0.19</td><td char=".">0.28</td><td char=".">0.36</td><td char=".">0.44</td><td char=".">0.52</td><td char=".">0.59</td><td char=".">0.65</td><td char=".">0.72</td></tr><tr><td>Eigenvalues/Sums of Squares loadings</td><td char=".">1.70</td><td char=".">1.69</td><td char=".">1.60</td><td char=".">1.54</td><td char=".">1.40</td><td char=".">1.35</td><td char=".">1.32</td><td char=".">1.16</td><td char=".">1.23</td></tr></tbody></table> </ephtml> </p> <hd id="AN0164958272-14">Confirmatory Factor Analysis</hd> <p>We used the remaining randomly selected half of the sample (<emph>n</emph> = 1939) for CFA. The unidimensional factor structure had poor fit to the data (see Table 4), to test for the factor structure that fit the data best, we compared the nine-factor model with the hierarchical model. To reiterate, the nine-factor measurement model has nine intercorrelated latent variables with two manifest items each (see Figure 1). On the other hand, the hierarchical measurement model has nine first-order latent variables (i.e., nine CERQ factors) that are defined by two intercorrelated second-order latent variables (i.e., adaptive and less adaptive strategies), where the indicators are related to the two second-order latent variables via the nine first-order latent variables (see Figure 2). Table 4 shows that both the nine-factor model [SBχ<sups>2</sups>(<reflink idref="bib99" id="ref82">99</reflink>) = 395.849; <emph>CFI</emph> =.968; <emph>TLI</emph> =.979; <emph>RMSEA</emph> =.04; <emph>SRMR</emph> =.03] and the hierarchical model [SBχ<sups>2</sups>(<reflink idref="bib125" id="ref83">125</reflink>) = 904.737; <emph>CFI</emph> =.934; <emph>TLI</emph> = 946; <emph>RMSEA</emph> =.06; <emph>SRMR</emph> =.08] have excellent fit to the data. However, the Akaike Information Criterion (<emph>AIC</emph>) and Bayesian Information Criterion (<emph>BIC</emph>) values of the competing models show that the nine-factor model (<emph>AIC</emph> = 95,219; <emph>BIC</emph> = 95,720) has lower values suggesting its advantage over the hierarchical model (<emph>AIC</emph> = 95,742; <emph>BIC</emph> = 96,098).</p> <p>PHOTO (COLOR): Figure 1. Nine-factor structure of the COVID-specific CERQ-short. Note. SlB = Self-blame, OtB = Others-blame, Rmn = Rumination, Cts = Catastrophizing, Acc = Acceptance, Pln = Planning, Rfc = Refocusing, Rpp = Reappraisal, PiP = Putting things into perspective. The covariances of the non-orthogonal latent factors are not presented for figure parsimony. Please refer to Table 2 for subscale intercorrelations.</p> <p>Graph: Figure 2. Hierarchical factor structure of the COVID-specific CERQ-short with less adaptive and adaptive second order factors. Note. MlA = Less or maladaptive strategies, Adp = Adaptive strategies, SlB = Self-blame, OtB = Others-blame, Rmn = Rumination, Cts = Catastrophizing, Acc = Acceptance, Pln = Planning, Rfc = Refocusing, Rpp = Reappraisal, PiP = Putting things into perspective.</p> <p>Table 4. Model Fit Indices Supporting the CERQ-Short's Nine-Factor Model and Its Measurement Invariance across Gender and Age.</p> <p> <ephtml> <table><thead><tr><td>Measurement Models</td><td>SBχ <italic><sup>2</sup></italic></td><td>df</td><td>CFI</td><td>TLI</td><td>RMSEA</td><td>SRMR</td><td>Δ CFI</td><td>Δ RMSEA</td><td>Δ SRMR</td><td>Invariance</td></tr></thead><tbody valign="top"><tr><td>Unidimensional CERQ</td><td char=".">11985.2</td><td char=".">135</td><td char=".">0.284</td><td char=".">0.189</td><td char=".">0.213</td><td char=".">0.192</td><td>–</td><td>–</td><td>–</td><td>–</td></tr><tr><td char=".">9-factor model CERQ</td><td char=".">395.849</td><td char=".">99</td><td char=".">0.968</td><td char=".">0.979</td><td char=".">0.042</td><td char=".">0.031</td><td>–</td><td>–</td><td>–</td><td>–</td></tr><tr><td>Hierarchical CERQ</td><td char=".">904.737</td><td char=".">125</td><td char=".">0.934</td><td char=".">0.946</td><td char=".">0.061</td><td char=".">0.075</td><td>–</td><td>–</td><td>–</td><td>–</td></tr><tr><td><italic>Across gender</italic></td></tr><tr><td char=".">9 Factor—Men</td><td char=".">166.788</td><td char=".">99</td><td char=".">0.971</td><td char=".">0.981</td><td char=".">0.041</td><td char=".">0.034</td><td>–</td><td>–</td><td>–</td><td>–</td></tr><tr><td char=".">9 Factor—Women</td><td char=".">304.775</td><td char=".">99</td><td char=".">0.970</td><td char=".">0.981</td><td char=".">0.040</td><td char=".">0.031</td><td>–</td><td>–</td><td>–</td><td>–</td></tr><tr><td char=".">9 Factor—Configural</td><td char=".">471.904</td><td char=".">198</td><td char=".">0.971</td><td char=".">0.981</td><td char=".">0.040</td><td char=".">0.032</td><td>–</td><td>–</td><td>–</td><td>Invariant</td></tr><tr><td char=".">9 Factor—Metric</td><td char=".">484.807</td><td char=".">207</td><td char=".">0.972</td><td char=".">0.981</td><td char=".">0.040</td><td char=".">0.032</td><td char=".">0.001</td><td char=".">0.000</td><td char=".">0.000</td><td>Invariant</td></tr><tr><td char=".">9 Factor—Scalar</td><td char=".">493.365</td><td char=".">216</td><td char=".">0.973</td><td char=".">0.981</td><td char=".">0.039</td><td char=".">0.032</td><td char=".">0.001</td><td char=".">−0.001</td><td char=".">0.000</td><td>Invariant</td></tr><tr><td char=".">9 Factor—Strict</td><td char=".">487.661</td><td char=".">234</td><td char=".">0.976</td><td char=".">0.982</td><td char=".">0.036</td><td char=".">0.033</td><td char=".">0.003</td><td char=".">−0.003</td><td char=".">0.001</td><td>Invariant</td></tr><tr><td><italic>Across age groups</italic></td></tr><tr><td char=".">9 Factor—Lower Median Age</td><td char=".">280.200</td><td char=".">99</td><td char=".">0.963</td><td char=".">0.976</td><td char=".">0.047</td><td char=".">0.033</td><td>–</td><td>–</td><td>–</td><td>–</td></tr><tr><td char=".">9 Factor—Higher Median Age</td><td char=".">240.242</td><td char=".">99</td><td char=".">0.969</td><td char=".">0.980</td><td char=".">0.040</td><td char=".">0.032</td><td>–</td><td>–</td><td>–</td><td>–</td></tr><tr><td char=".">9 Factor—Configural</td><td char=".">520.371</td><td char=".">198</td><td char=".">0.966</td><td char=".">0.978</td><td char=".">0.044</td><td char=".">0.033</td><td>–</td><td>–</td><td>–</td><td>Invariant</td></tr><tr><td char=".">9 Factor—Metric</td><td char=".">533.383</td><td char=".">207</td><td char=".">0.967</td><td char=".">0.978</td><td char=".">0.043</td><td char=".">0.033</td><td char=".">0.001</td><td char=".">−0.001</td><td char=".">0.042</td><td>Invariant</td></tr><tr><td char=".">9 Factor—Scalar</td><td char=".">604.879</td><td char=".">216</td><td char=".">0.963</td><td char=".">0.974</td><td char=".">0.046</td><td char=".">0.034</td><td char=".">−0.004</td><td char=".">0.003</td><td char=".">−0.034</td><td>Invariant</td></tr><tr><td char=".">9 Factor—Strict</td><td char=".">717.080</td><td char=".">234</td><td char=".">0.955</td><td char=".">0.966</td><td char=".">0.050</td><td char=".">0.037</td><td char=".">−0.008</td><td char=".">0.004</td><td char=".">−0.003</td><td>Invariant</td></tr></tbody></table> </ephtml> </p> <p>3 <emph>Note</emph>. All SBχ<sups>2</sups> are significant at <emph>p</emph> < 0.001.</p> <hd id="AN0164958272-15">Measurement Invariance</hd> <p>Examining the measurement invariance of the nine-factor measurement model, the results of the multigroup CFA show the nine-factor structure of CERQ-short is invariant across gender and age groups. No significant change in <emph>CFI</emph> and <emph>RMSEA</emph> or <emph>SRMR</emph> values was found in comparing the nine-factor model between males (<emph>n</emph> = 473) and females (<emph>n</emph> = 1,466) and those under the upper median age bracket (26 years old and below; <emph>n</emph> = 941) and lower median age bracket (27 years old and above; <emph>n</emph> = 998), following data from the Philippine census (Philippine Statistics Authority, [<reflink idref="bib43" id="ref84">43</reflink>]). The configural model (constraining factor structure across groups) had good fit to the data across gender and age groups. The metric model (constraining all factor loadings across groups) had good fit to the data and had no meaningful difference from the configural model. The scalar model, which constrains all item intercepts, also had good fit to the data and also had no meaningful difference when compared to the metric model. Finally, the strict model, which constrains all item errors, had good fit to the data and also had no meaningful difference when compared to the scalar model. Overall, the results suggest evidence for measurement invariance of the nine-factor of the CERQ-short given the consistent model fit indices despite the increasing levels of model constraints.</p> <hd id="AN0164958272-16">Criterion-Related Evidence for Construct Validity</hd> <p>Given the validity of the nine-factor measurement model of CERQ-short, we conducted bivariate correlation analyses to establish convergent and discriminant validity using stress, negative affect, and positive affect. As shown in Table 2, all factors of CERQ-short showed expected relations with stress and negative affect except for acceptance, which showed no significant relations with the negative criterion variables. Catastrophizing was positively correlated with stress (<emph>r</emph> =.419, <emph>p</emph> <.001) and negative affect (<emph>r</emph> =.458, <emph>p</emph> <.001), with moderate strength. All factors of CERQ-short showed expected correlations with positive affect except for self-blaming (<emph>r</emph> =.113, <emph>p</emph> <.001), with weak strength. Both adaptive and less adaptive subscalesof the CERQ-short showed expected associations with stress, negative affect, and positive affect.</p> <hd id="AN0164958272-17">Discussion</hd> <p>This study adapted the CERQ-short to a specific context i.e., COVID-19 pandemic, and evaluated the data's psychometric properties among a sample of Filipino respondents. We found support for the data's internal reliability and its construct and criterion-related validity. The nine-factor structure of the CERQ-short had a better model fit than its hierarchical counterpart, despite the latter having good fit to the data. This suggests that the nine-factor structure of the CERQ-short is applicable when assessing cognitive emotion regulation. We then evaluated the measurement invariance of the nine-factor model of the CERQ-short, which held across increasingly constrained tests of gender and age invariance with no meaningful change in <emph>CFI</emph>, <emph>RMSEA</emph> or <emph>SRMR</emph> values for the configural, metric, scalar, and strict invariance tests, demonstrating robust measurement invariance. The nine factors of the CERQ-short are also theoretically correlated with stress, negative affect, and positive affect, demonstrating criterion-related validity.</p> <p>The study findings supporting the nine-factor structure of the CERQ-short is aligned with previous validation studies (Ireland et al., [<reflink idref="bib27" id="ref85">27</reflink>]; Orgilés et al., [<reflink idref="bib41" id="ref86">41</reflink>]; Propheta & van Zyl, [<reflink idref="bib45" id="ref87">45</reflink>]). In addition, the hierarchical factor structure was similarly supported, which is in contrast with previous studies where the hierarchical factor structure did not yield a good fit (Propheta & van Zyl, [<reflink idref="bib45" id="ref88">45</reflink>]). Further, this study also found good internal consistency for scores on all subscale measures, contrary to previous studies where low reliability was found in specific CER subscales (see Orgilés et al., [<reflink idref="bib41" id="ref89">41</reflink>]; Propheta & van Zyl, [<reflink idref="bib45" id="ref90">45</reflink>]). Overall, our findings support the adapted CERQ-short's reliability, validity, and applicability in evaluating CER strategies of adults specifically in the context of the COVID-19 pandemic.</p> <p>Although the data from CERQ-short was found to have consistent reliability and validity in this study, we also found low/atheoretical factor loadings for self-blame and acceptance subscales. Similar results were found in investigations using the CERQ-short. One study found that including self-blame as a less adaptive emotion regulation strategy in predicting anxiety and depression resulted in a worse fitting model (Muñoz-Navarro et al., [<reflink idref="bib38" id="ref91">38</reflink>]). This inconsistency could be due to the context of a global pandemic, which is generally perceived as a situation that is beyond individuals' control. Likewise, previous studies found similar results for acceptance during the COVID-19 pandemic, where items may be construed as indicators of despair and resignation (Rodríguez-Sabiote et al., [<reflink idref="bib47" id="ref92">47</reflink>]). In general, the association of acceptance with mental health outcomes during the COVID-19 pandemic has been inconsistent, either as a mitigating factor for depressive symptoms (Wang et al., [<reflink idref="bib58" id="ref93">58</reflink>]) or an ineffective coping strategy (Jarego et al., [<reflink idref="bib28" id="ref94">28</reflink>]; Zacher & Rudolph, [<reflink idref="bib61" id="ref95">61</reflink>]).</p> <p>The study also found that cognitive reappraisal strategies such as planning, refocusing, reappraisal, and perspective taking are correlated with higher levels of positive emotions and decreased negative emotions, while other-blaming, rumination, and catastrophizing were positively associated with negative emotions and stress. This is consistent with emotion regulation studies which show that changing one's perspective and refocusing on the positive aspects of a situation improve mood, and promote positive emotions (Fernández Cruz et al., [<reflink idref="bib15" id="ref96">15</reflink>]; Jarego et al., [<reflink idref="bib28" id="ref97">28</reflink>]; Muñoz-Navarro et al., [<reflink idref="bib38" id="ref98">38</reflink>]). Constantly worrying about one's situation also decreases one's mood and increases stress (Orgilés et al., [<reflink idref="bib41" id="ref99">41</reflink>]; Vinter et al., [<reflink idref="bib57" id="ref100">57</reflink>]).</p> <hd id="AN0164958272-18">Implications for Counseling Practice</hd> <p>This study contributes to the existing literature on emotion regulation since it was able to establish that the nine-factor CERQ-short could be used to assess individual differences in cognitive emotion regulation strategies. Given the scale's utility in assessing emotion regulation strategies for individuals responding to distressing events, such as natural disasters (Felix et al., [<reflink idref="bib14" id="ref101">14</reflink>]), and everyday stressors (Vinter et al., [<reflink idref="bib57" id="ref102">57</reflink>]), the validation of the CERQ-short specific to the COVID-19 pandemic contributes to the utility and applicability of the instrument, particularly among counseling practitioners in low- and middle-income countries such as the Philippines. Psychologists, counselors, and other mental health professionals may utilize the adapted CERQ-short in helping clients identify adaptive and less adaptive coping strategies amid the on-going health crisis. Less adaptive CER strategies could be the target or focus of cognitive-based psychotherapeutic interventions (e.g., cognitive behavior therapy), while counselors may assist clients develop more healthy forms of CER techniques.</p> <p>Although a number of studies have examined general cognitive emotion regulation strategies as predictors of emotional reactions to the COVID-19 pandemic (Muñoz-Navarro et al., [<reflink idref="bib38" id="ref103">38</reflink>]; Wang et al., [<reflink idref="bib58" id="ref104">58</reflink>]), the present study is among the first to adapt the CERQ-short specific to the pandemic and consequently examined its psychometric properties. Theoretically, a key contribution of the study was that the two comparable factor structures of the CERQ-short (i.e., nine-factor structure and hierarchical factor structure) both have adequate model fit. Although the nine-factor structure had significantly better model fit indices, the hierarchical model also holds substantive implications for future hypotheses testing and identification of adaptive and less adaptive CER strategies for interventions. Such a finding provides support to the applicability of both the nine-factor structure and the hierarchical factor structure of the CERQ-short often used in previous studies. Practical implications include the finding on the measurement invariance of the CERQ-short for gender and age, which provides support for the practical utility of the CERQ-short across demographic groups.</p> <hd id="AN0164958272-19">Limitations and Directions for Future Research</hd> <p>Although the present results clearly support the reliability and validity of the data from the CERQ-short scores in the context of the COVID-19 pandemic, we find it appropriate to recognize potential study limitations and future research directions. First, the cross-sectional nature of data did not allow other reliability tests (e.g., test-retest). Future research may utilize longitudinal research designs to examine test-retest reliability. Secondly, despite the large sample size, the majority of the participants are from the capital of the Philippines. The generalizability of the study can improve by extending the sample to other regions in the country and other English-speaking contexts. Third, this study validates the CERQ-short in the context of COVID-19 without examining the comparison of the scale with the full CERQ. Hence this study would not be able to establish whether the CERQ-short is better than the full CERQ. Future researchers may consider administering the full CERQ to examine specific differences in the psychometric properties of both formats. The adapted CERQ has shown validity among Filipino respondents. However, further examination is warranted for its applicability in other contexts affected by COVID-19. Finally, the pilot testing of the adapted instrument was only administered to 10 respondents. Future work can consider increasing this to closer to 30 to get a better sense of the adapted instruments' reliability prior to actual data collection.</p> <hd id="AN0164958272-20">Conclusion</hd> <p>This study demonstrated the score reliability and validity of the CERQ-short in assessing cognitive emotion regulation specific to the COVID-19 pandemic. Amid the growing uncertainties and challenges of the pandemic, along with its resurgence with newly discovered variants, it is important to evaluate the adaptive and less adaptive cognitive emotion regulation strategies that individuals use during stressful situations. Efforts can be made to identify factors that can promote adaptive cognitive emotion regulation strategies and mitigate the less adaptive strategies. We found evidence to support reliability and validity of the adapted CERQ-short, which can be used to assess cognitive emotion regulation strategies across gender and age among Filipinos, especially in the context of public health crises like the COVID-19 pandemic.</p> <hd id="AN0164958272-21">Data Availability Statement</hd> <p>The data that support the findings of this study are available from the corresponding author upon reasonable request.</p> <hd id="AN0164958272-22">Disclosure Statement</hd> <p>No potential conflict of interest was reported by the authors.</p> <ref id="AN0164958272-23"> <title> References </title> <blist> <bibl id="bib1" idref="ref49" type="bt">1</bibl> <bibtext> Antony, M. M., Bieling, P. J., Cox, B. J., Enns, M. W., & Swinson, R. P. (1998). Psychometric properties of the 42-item and 21-item versions of the Depression Anxiety Stress Scales in clinical groups and a community sample. Psychological Assessment, 10 (2), 176 – 181. https://doi.org/10.1037/1040-3590.10.2.176</bibtext> </blist> <blist> <bibl id="bib2" idref="ref14" type="bt">2</bibl> <bibtext> Bahlinger, K., Lincoln, T. M., Krkovic, K., & Clamor, A. (2020). Linking psychophysiological adaptation, emotion regulation, and subjective stress to the occurrence of paranoia in daily life. Journal of Psychiatric Research, 130 (July), 152 – 159. https://doi.org/10.1016/j.jpsychires.2020.07.021</bibtext> </blist> <blist> <bibl id="bib3" idref="ref73" type="bt">3</bibl> <bibtext> Barrett, P. (2007). Structural equation modelling: Adjudging model fit. Personality and Individual Differences, 42 (5), 815 – 824. https://doi.org/10.1016/j.paid.2006.09.018</bibtext> </blist> <blist> <bibl id="bib4" idref="ref6" type="bt">4</bibl> <bibtext> Bendau, A., Petzold, M. B., Pyrkosch, L., Mascarell Maricic, L., Betzler, F., Rogoll, J., Große, J., Ströhle, A., & Plag, J. (2020). Associations between COVID-19 related media consumption and symptoms of anxiety, depression and COVID-19 related fear in the general population in Germany. European Archives of Psychiatry and Clinical Neuroscience, 271 (2), 283 – 291. https://doi.org/10.1007/s00406-020-01171-6</bibtext> </blist> <blist> <bibl id="bib5" idref="ref8" type="bt">5</bibl> <bibtext> Bernado, A. B. I., & Mendoza, N. B. (2021). Measuring hope during the COVID-19 outbreak in the Philippines: Development and validation of the state locus-of-Hope scale short form in Filipino. Current Psychology, 40 (11), 1 – 10. https://doi.org/10.1007/s12144-020-00887-x</bibtext> </blist> <blist> <bibl id="bib6" idref="ref7" type="bt">6</bibl> <bibtext> Bernado, A. B. I., Mendoza, N. B., Simon, P. D., Cunanan, A. L. P., Dizon, J. I. W. T., Tarroja, M. C. H., Balajadia-Alcala, M. A., & Saplala, J. E. G. (2020). Coronavirus Pandemic Anxiety Scale (CPAS-11): Development and initial validation. Current Psychology, 1 – 9. https://doi.org/10.1007/s12144-020-01193-2</bibtext> </blist> <blist> <bibl id="bib7" idref="ref4" type="bt">7</bibl> <bibtext> Brooks, S. K., Webster, R. K., Smith, L. E., Woodland, L., Wessely, S., Greenberg, N., & Rubin, G. J. (2020). The psychological impact of quarantine and how to reduce it: Rapid review of the evidence. The Lancet, 395 (10227), 912 – 920. https://doi.org/10.1016/S0140-6736(20)30460-8</bibtext> </blist> <blist> <bibl id="bib8" idref="ref38" type="bt">8</bibl> <bibtext> Cakmak, A. F., & Cevik, E. I. (2010). Cognitive Emotion Regulation Questionnaire: Development of Turkish version of 18-item short form. African Journal of Business Management, 4 (10), 2097 – 2102.</bibtext> </blist> <blist> <bibl id="bib9" idref="ref59" type="bt">9</bibl> <bibtext> Carvajal, B. P., Molina-Martínez, M. Á., Fernández-Fernández, V., Paniagua-Granados, T., Lasa-Aristu, A., & Luque-Reca, O. (2022). Psychometric properties of the Cognitive Emotion Regulation Questionnaire (CERQ) in Spanish older adults. Aging & Mental Health, 26 (2), 413 – 422. https://doi.org/10.1080/13607863.2020.1870207</bibtext> </blist> <blist> <bibtext> Chen, F. F. (2007). Sensitivity of goodness of fit indexes to lack of measurement invariance. Structural Equation Modeling, 14 (3), 464 – 504. https://doi.org/10.1080/10705510701301834</bibtext> </blist> <blist> <bibtext> d'Acremont, M., & Van der Linden, M. (2007). How is impulsivity related to depression in adolescence? Evidence from a French validation of the Cognitive Emotion Regulation Questionnaire. Journal of Adolescence, 30 (2), 271 – 282. https://doi.org/10.1016/j.adolescence.2006.02.007</bibtext> </blist> <blist> <bibtext> de Castro Araujo, A. P., Nunes Gadelha, M. J., & Pimenteira de Melo, R. L. (2020). Evidence of validity, reliability and psychometric parameters of the items of the Cognitive Emotion Regulation Questionnaire-Short (CERQ-Short). Psico-USF, 25 (3), 547 – 559. https://doi.org/10.1590/1413-82712020250312</bibtext> </blist> <blist> <bibtext> Feliu-Soler, A., Reche-Camba, E., Borràs, X., Pérez-Aranda, A., Andrés-Rodríguez, L., Peñarrubia-María, M. T., Navarro-Gil, M., García-Campayo, J., Bellón, J. A., & Luciano, J. V. (2017). Psychometric properties of the Cognitive Emotion Regulation Questionnaire (CERQ) in patients with fibromyalgia syndrome. Frontiers in Psychology, 8 (December), 2075. https://doi.org/10.3389/fpsyg.2017.02075</bibtext> </blist> <blist> <bibtext> Felix, E., Afifi, T., Kia-Keating, M., Brown, L., Afifi, W., & Reyes, G. (2015). Family functioning and posttraumatic growth among parents and youth following wildfire disasters. The American Journal of Orthopsychiatry, 85 (2), 191 – 200. https://doi.org/10.1037/ort0000054</bibtext> </blist> <blist> <bibtext> Fernández Cruz, M., Álvarez Rodríguez, J., Ávalos Ruiz, I., Cuevas López, M., de Barros Camargo, C., Díaz Rosas, F., González Castellón, E., González González, D., Hernández Fernández, A., Ibáñez Cubillas, P., & Lizarte Simón, E. J. (2020). Evaluation of the emotional and cognitive regulation of young people in a lockdown situation due to the Covid-19 pandemic. Frontiers in Psychology, 11 (October), 565503. https://doi.org/10.3389/fpsyg.2020.565503</bibtext> </blist> <blist> <bibtext> Finch, W. H. (2020). Using fit statistic differences to determine the optimal number of factors to retain in an exploratory factor analysis. Educational and Psychological Measurement, 80 (2), 217 – 241. https://doi.org/10.1177/0013164419865769</bibtext> </blist> <blist> <bibtext> Garnefski, N., Koopman, H., Kraaij, V., & ten Cate, R. (2009). Brief report: Cognitive emotion regulation strategies and psychological adjustment in adolescents with a chronic disease. Journal of Adolescence, 32 (2), 449 – 454. https://doi.org/10.1016/j.adolescence.2008.01.003</bibtext> </blist> <blist> <bibtext> Garnefski, N., & Kraaij, V. (2006a). Cognitive Emotion Regulation Questionnaire: Development of a short 18-item version (CERQ-short). Personality and Individual Differences, 41 (6), 1045 – 1053. https://doi.org/10.1016/j.paid.2006.04.010</bibtext> </blist> <blist> <bibtext> Garnefski, N., & Kraaij, V. (2006b). Relationships between cognitive emotion regulation strategies and depressive symptoms: A comparative study of five specific samples. Personality and Individual Differences, 40 (8), 1659 – 1669. https://doi.org/10.1016/j.paid.2005.12.009</bibtext> </blist> <blist> <bibtext> Garnefski, N., Kraaij, V., & Spinhoven, P. (2001). Negative life events, cognitive emotion regulation and emotional problems. Personality and Individual Differences, 30 (8), 1311 – 1327. https://doi.org/10.1016/S0191-8869(00)00113-6</bibtext> </blist> <blist> <bibtext> Garnefski, N., Teerds, J., Kraaij, V., Legerstee, J., & van den Kommer, T. (2004). Cognitive emotion regulation strategies and depressive symptoms: Differences between males and females. Personality and Individual Differences, 36 (2), 267 – 276. https://doi.org/10.1016/S0191-8869(03)00083-7</bibtext> </blist> <blist> <bibtext> Garnefski, N., Van Den Kommer, T., Kraaij, V., Teerds, J., Legerstee, J., & Onstein, E. (2002). The relationship between cognitive emotion regulation strategies and emotional problems: Comparison between a clinical and a non-clinical sample. European Journal of Personality, 16 (5), 403 – 420. https://doi.org/10.1002/per.458</bibtext> </blist> <blist> <bibtext> Gubler, D. A., Makowski, L. M., Troche, S. J., & Schlegel, K. (2021). Loneliness and well-being during the Covid-19 pandemic: Associations with personality and emotion regulation. Journal of Happiness Studies, 22 (5), 2323 – 2342. https://doi.org/10.1007/s10902-020-00326-5</bibtext> </blist> <blist> <bibtext> Hair, J. F., Babin, B. J., Anderson, R. E., & Black, W. C. (2014). Multivariate data analysis (7th ed.). Pearson.</bibtext> </blist> <blist> <bibtext> Hu, L.-T., & Bentler, P. M. (1995). Evaluating model fit. In R. H. Hoyle (Ed.), Structural equation modeling: Concepts, issues, and applications. Sage Publications, Inc.</bibtext> </blist> <blist> <bibtext> Hu, L.-T., & Bentler, P. M. (1999). Cutoff criteria for fit indexes in covariance structure analysis: Conventional criteria versus new alternatives. Structural Equation Modeling, 6 (1), 1 – 55. https://doi.org/10.1080/10705519909540118</bibtext> </blist> <blist> <bibtext> Ireland, M. J., Clough, B. A., & Day, J. J. (2017). The cognitive emotion regulation questionnaire: Factorial, convergent, and criterion validity analyses of the full and short versions. Personality and Individual Differences, 110, 90 – 95. https://doi.org/10.1016/j.paid.2017.01.035</bibtext> </blist> <blist> <bibtext> Jarego, M., Pimenta, F., Pais-Ribeiro, J., Costa, R. M., Patrão, I., Coelho, L., & Ferreira-Valente, A. (2021). Do coping responses predict better/poorer mental health in Portuguese adults during Portugal's national lockdown associated with the COVID-19? Personality and Individual Differences, 175 (November 2020), 110698. https://doi.org/10.1016/j.paid.2021.110698</bibtext> </blist> <blist> <bibtext> Jiang, G., Mai, Y. (2020). equaltestMI: Examine measurement invariance via equivalence testing and projection method. R Package Version 0.6.0. https://cran.r-project.org/web/packages/equaltestMI/index.html</bibtext> </blist> <blist> <bibtext> Jungmann, S. M., & Witthöft, M. (2020). Health anxiety, cyberchondria, and coping in the current COVID-19 pandemic: Which factors are related to coronavirus anxiety? Journal of Anxiety Disorders, 73, 102239. https://doi.org/10.1016/j.janxdis.2020.102239</bibtext> </blist> <blist> <bibtext> Lábadi, B., Arató, N., Budai, T., Inhóf, O., Stecina, D. T., Sík, A., & Zsidó, A. N. (2021). Psychological well-being and coping strategies of elderly people during the COVID-19 pandemic in Hungary. Aging and Mental Health, 26 (3), 570 – 577. Advance online publication. https://doi.org/10.1080/13607863.2021.1902469</bibtext> </blist> <blist> <bibtext> Li, H. Y., Cao, H., Leung, D. Y. P., & Mak, Y. W. (2020). The psychological impacts of a COVID-19 outbreak on college students in China: A longitudinal study. International Journal of Environmental Research and Public Health, 17 (3933). Advance online publication. https://doi.org/10.1157/13090384</bibtext> </blist> <blist> <bibtext> Lovibond, P. F., & Lovibond, S. H. (1995). The structure of negative emotional states: Comparison of the Depression Anxiety Stress Scales (DASS) with the Beck Depression and Anxiety Inventories. Behaviour Research and Therapy, 33 (3), 335 – 343. https://doi.org/10.1016/0005-7967(94)00075-U</bibtext> </blist> <blist> <bibtext> Martin, R. C., & Dahlen, E. R. (2005). Cognitive emotion regulation in the prediction of depression, anxiety, stress, and anger. Personality and Individual Differences, 39 (7), 1249 – 1260. https://doi.org/10.1016/j.paid.2005.06.004</bibtext> </blist> <blist> <bibtext> McRae, K., & Gross, J. J. (2020). Emotion regulation. Emotion, 20 (1), 1 – 9. https://doi.org/10.1037/emo0000703</bibtext> </blist> <blist> <bibtext> Mendoza, N. B., & Dizon, J. I. W. T. (2022). Prevalence of severe anxiety in the Philippines amid the COVID-19 outbreak. Journal of Loss and Trauma, 1 – 3. Advance online publication. https://doi.org/10.1080/15325024.2021.2023298</bibtext> </blist> <blist> <bibtext> Mendoza, N. B., Frondozo, C. E., Dizon, J. I. W. T., & Buenconsejo, J. U. (2022). The factor structure and measurement invariance of the PHQ-4 and the prevalence of depression and anxiety in a Southeast Asian context amid the COVID-19 pandemic. Current Psychology. Advance online publication. https://doi.org/10.1007/s12144-022-02833-5</bibtext> </blist> <blist> <bibtext> Muñoz-Navarro, R., Malonda, E., Llorca-Mestre, A., Cano-Vindel, A., & Fernández-Berrocal, P. (2021). Worry about COVID-19 contagion and general anxiety: Moderation and mediation effects of cognitive emotion regulation. Journal of Psychiatric Research, 137 (August 2020), 311 – 318. https://doi.org/10.1016/j.jpsychires.2021.03.004</bibtext> </blist> <blist> <bibtext> Nicola, M., Alsafi, Z., Sohrabi, C., Kerwan, A., Al-Jabir, A., Iosifidis, C., Agha, M., & Agha, R. (2020). The socio-economic implications of the coronavirus pandemic (COVID-19): A review. International Journal of Surgery, 78 (March), 185 – 193. https://doi.org/10.1016/j.ijsu.2020.04.018</bibtext> </blist> <blist> <bibtext> Ochsner, K. N., & Gross, J. J. (2005). The cognitive control of emotion. Trends in Cognitive Sciences, 9 (5), 242 – 249. https://doi.org/10.1016/j.tics.2005.03.010</bibtext> </blist> <blist> <bibtext> Orgilés, M., Morales, A., Fernández-Martínez, I., Melero, S., & Espada, J. P. (2019). Validation of the short version of the Cognitive Emotion Regulation Questionnaire for Spanish children. Journal of Child Health Care, 23 (1), 87 – 101. https://doi.org/10.1177/1367493518777306</bibtext> </blist> <blist> <bibtext> Panayiotou, G., Panteli, M., & Leonidou, C. (2021). Coping with the invisible enemy: The role of emotion regulation and awareness in quality of life during the COVID-19 pandemic. Journal of Contextual Behavioral Science, 19 (October 2020), 17 – 27. https://doi.org/10.1016/j.jcbs.2020.11.002</bibtext> </blist> <blist> <bibtext> Philippine Statistics Authority. (2017). Philippine population surpassed the 100 million mark (Results from the 2015 Census of Population). https://psa.gov.ph/content/philippine-population-surpassed-100-million-mark-results-2015-census-population</bibtext> </blist> <blist> <bibtext> Preuss, H., Capito, K., van Eickels, R. L., Zemp, M., & Kolar, D. R. (2021). Cognitive reappraisal and self-compassion as emotion regulation strategies for parents during COVID-19: An online randomized controlled trial. Internet Interventions, 24, 100388. https://doi.org/10.1016/j.invent.2021.100388</bibtext> </blist> <blist> <bibtext> Propheta, I., & van Zyl, C. J. J. (2019). Measuring cognitive emotion regulation in South Africa using the Cognitive Emotion Regulation Questionnaire-short form. African Journal of Psychological Assessment, 1 (1), 1 – 6. https://doi.org/10.4102/ajopa.v1i0.9</bibtext> </blist> <blist> <bibtext> Riaz, M., Abid, M., & Bano, Z. (2021). Psychological problems in general population during COVID-19 pandemic in Pakistan: Role of cognitive emotion regulation. Annals of Medicine, 53 (1), 189 – 196. https://doi.org/10.1080/07853890.2020.1853216</bibtext> </blist> <blist> <bibtext> Rodríguez-Sabiote, C., Ibáñez-Cubillas, P., López-Rodríguez, S., & Álvarez-Rodríguez, J. (2021). Psychometric properties of the Spanish version of the Cognitive Emotional Regulation Difficulties Questionnaire (CERQ) in higher education students in times of Covid-19. Frontiers in Psychology, 12 (June), 695147. https://doi.org/10.3389/fpsyg.2021.695147</bibtext> </blist> <blist> <bibtext> Rosseel, Y. (2012). Lavaan: An R package for structural equation modeling and more. Version 0.5–12 (BETA). Journal of Statistical Software, 48 (2), 1 – 36. <ulink href="http://cran.r-project.org/">http://cran.r-project.org/</ulink>. https://doi.org/10.18637/jss.v048.i02</bibtext> </blist> <blist> <bibtext> Sakakibara, R., & Kitahara, M. (2016). The relationship between Cognitive Emotion Regulation Questionnaire (CERQ) and depression, anxiety: Meta-analysis. Shinrigaku Kenkyu, 87 (2), 179 – 185. https://doi.org/10.4992/jjpsy.87.15302</bibtext> </blist> <blist> <bibtext> Salari, N., Hosseinian-Far, A., Jalali, R., Vaisi-Raygani, A., Rasoulpoor, S., Mohammadi, M., Rasoulpoor, S., & Khaledi-Paveh, B. (2020). Prevalence of stress, anxiety, depression among the general population during the COVID-19 pandemic: A systematic review and meta-analysis. Globalization and Health, 16, 57. https://doi.org/10.1186/s12992-020-00589-w</bibtext> </blist> <blist> <bibtext> Santos, A. C., Simões, C., Cefai, C., Freitas, E., & Arriaga, P. (2021a). Emotion regulation and student engagement: Age and gender differences during adolescence. International Journal of Educational Research, 109 (March), 101830. https://doi.org/10.1016/j.ijer.2021.101830</bibtext> </blist> <blist> <bibtext> Santos, A. C., Simões, C., Daniel, J. R., & Arriaga, P. (2021b). Portuguese validation of the Cognitive Emotion Regulation Questionnaire short version in youth: Validity, reliability and invariance across gender and age. European Journal of Developmental Psychology, 1 – 16. https://doi.org/10.1080/17405629.2021.2011201</bibtext> </blist> <blist> <bibtext> Shah, S. M. A., Mohammad, D., Qureshi, M. F. H., Abbas, M. Z., & Aleem, S. (2021). Prevalence, psychological responses and associated correlates of depression, anxiety and stress in a global population, during the coronavirus disease (COVID-19) pandemic. Community Mental Health Journal, 57 (1), 101 – 110. https://doi.org/10.1007/s10597-020-00728-y</bibtext> </blist> <blist> <bibtext> Shigemura, J., Ursano, R. J., Morganstein, J. C., Kurosawa, M., & Benedek, D. M. (2020). Public responses to the novel 2019 coronavirus (2019-nCoV) in Japan: Mental health consequences and target populations. Psychiatry and Clinical Neurosciences, 74 (4), 281 – 282. https://doi.org/10.1111/pcn.12988</bibtext> </blist> <blist> <bibtext> Theurel, A., & Gentaz, E. (2018). The regulation of emotions in adolescents: Age differences and emotion-specific patterns. PLoS One, 13 (6), e0195501. https://doi.org/10.1371/journal.pone.0195501</bibtext> </blist> <blist> <bibtext> Tison, G. H., Avram, R., Kuhar, P., Abreau, S., Marcus, G. M., Pletcher, M. J., & Olgin, J. E. (2020). Worldwide effect of COVID-19 on physical activity: A descriptive study. Annals of Internal Medicine, 173 (9), 767 – 770. https://doi.org/10.7326/M20-2665</bibtext> </blist> <blist> <bibtext> Vinter, K., Aus, K., & Arro, G. (2021). Adolescent girls' and boys' academic burnout and its associations with cognitive emotion regulation strategies. Educational Psychology, 41 (8), 1061 – 1077. https://doi.org/10.1080/01443410.2020.1855631</bibtext> </blist> <blist> <bibtext> Wang, Q. Q., Fang, Y. Y., Huang, H. L., Lv, W. J., Wang, X. X., Yang, T. T., Yuan, J. M., Gao, Y., Qian, R. L., & Zhang, Y. H. (2021). Anxiety, depression and cognitive emotion regulation strategies in Chinese nurses during the COVID-19 outbreak. Journal of Nursing Management, 29 (5), 1263 – 1274. https://doi.org/10.1111/jonm.13265</bibtext> </blist> <blist> <bibtext> Watson, D., Clark, L. A., & Tellegen, A. (1988). Development and validation of brief measures of positive and negative affect: The PANAS scales. Journal of Personality and Social Psychology, 54 (6), 1063 – 1070. https://doi.org/10.1037/0022-3514.54.6.1063</bibtext> </blist> <blist> <bibtext> World Health Organization. (2021). WHO Coronavirus (COVID-19) dashboard. https://covid19.who.int/table</bibtext> </blist> <blist> <bibtext> Zacher, H., & Rudolph, C. W. (2021). Individual differences and changes in subjective wellbeing during the early stages of the COVID-19 pandemic. American Psychologist, 76 (1), 50 – 62. https://doi.org/10.1037/amp0000702</bibtext> </blist> </ref> <aug> <p>By Cherry E. Frondozo; Norman B. Mendoza; John Ian Wilzon T. Dizon and Jet U. Buenconsejo</p> <p>Reported by Author; Author; Author; Author</p> <p></p> <p>Cherry E. Frondozo is a PhD candidate from the Department of Curriculum and Instruction at the Education University of Hong Kong. Her research focuses on emotions and emotion regulation in assessment contexts.</p> <p>Norman B. Mendoza is a PhD candidate from the Department of Curriculum and Instruction at the Education University of Hong Kong. He will soon commence his RGC Postdoctoral Fellowship in the same university. His research is focused on the psychosocial mechanisms that influence students' self-directed learning practices and the adaptive school outcomes such practices predict.</p> <p>John Ian Wilzon T. Dizon is an Assistant Professor at the Department of Psychology of the Angeles University Foundation and an incoming Research Assistant at the Bau Institute of Medical and Health Sciences Education, LKS Faculty of Medicine at the University of Hong Kong. His research interests include suicide research, mental health, and well-being outcomes.</p> <p>Jet U. Buenconsejo is a PhD candidate from the Department of Special Education and Counselling of the Education University of Hong Kong, working on research projects related to Positive Youth Development. As a psychometrician and psychologist in the Philippines, he handled youth and adult cases with psychosocial concerns.</p> </aug> <nolink nlid="nl1" bibid="bib60" firstref="ref1"></nolink> <nolink nlid="nl2" bibid="bib56" firstref="ref2"></nolink> <nolink nlid="nl3" bibid="bib39" firstref="ref3"></nolink> <nolink nlid="nl4" bibid="bib54" firstref="ref5"></nolink> <nolink nlid="nl5" bibid="bib32" firstref="ref9"></nolink> <nolink nlid="nl6" bibid="bib37" firstref="ref10"></nolink> <nolink nlid="nl7" bibid="bib36" firstref="ref11"></nolink> <nolink nlid="nl8" bibid="bib50" firstref="ref12"></nolink> <nolink nlid="nl9" bibid="bib53" firstref="ref13"></nolink> <nolink nlid="nl10" bibid="bib35" firstref="ref15"></nolink> <nolink nlid="nl11" bibid="bib44" firstref="ref16"></nolink> <nolink nlid="nl12" bibid="bib17" firstref="ref17"></nolink> <nolink nlid="nl13" bibid="bib40" firstref="ref18"></nolink> <nolink nlid="nl14" bibid="bib30" firstref="ref19"></nolink> <nolink nlid="nl15" bibid="bib31" firstref="ref20"></nolink> <nolink nlid="nl16" bibid="bib38" firstref="ref21"></nolink> <nolink nlid="nl17" bibid="bib42" firstref="ref22"></nolink> <nolink nlid="nl18" bibid="bib46" firstref="ref23"></nolink> <nolink nlid="nl19" bibid="bib18" firstref="ref24"></nolink> <nolink nlid="nl20" bibid="bib23" firstref="ref25"></nolink> <nolink nlid="nl21" bibid="bib41" firstref="ref28"></nolink> <nolink nlid="nl22" bibid="bib11" firstref="ref30"></nolink> <nolink nlid="nl23" bibid="bib19" firstref="ref31"></nolink> <nolink nlid="nl24" bibid="bib34" firstref="ref34"></nolink> <nolink nlid="nl25" bibid="bib49" firstref="ref37"></nolink> <nolink nlid="nl26" bibid="bib12" firstref="ref39"></nolink> <nolink nlid="nl27" bibid="bib27" firstref="ref41"></nolink> <nolink nlid="nl28" bibid="bib45" firstref="ref43"></nolink> <nolink nlid="nl29" bibid="bib20" firstref="ref48"></nolink> <nolink nlid="nl30" bibid="bib21" firstref="ref57"></nolink> <nolink nlid="nl31" bibid="bib51" firstref="ref58"></nolink> <nolink nlid="nl32" bibid="bib55" firstref="ref60"></nolink> <nolink nlid="nl33" bibid="bib52" firstref="ref61"></nolink> <nolink nlid="nl34" bibid="bib24" firstref="ref64"></nolink> <nolink nlid="nl35" bibid="bib59" firstref="ref65"></nolink> <nolink nlid="nl36" bibid="bib33" firstref="ref66"></nolink> <nolink nlid="nl37" bibid="bib16" firstref="ref70"></nolink> <nolink nlid="nl38" bibid="bib48" firstref="ref71"></nolink> <nolink nlid="nl39" bibid="bib13" firstref="ref72"></nolink> <nolink nlid="nl40" bibid="bib25" firstref="ref74"></nolink> <nolink nlid="nl41" bibid="bib26" firstref="ref75"></nolink> <nolink nlid="nl42" bibid="bib29" firstref="ref76"></nolink> <nolink nlid="nl43" bibid="bib10" firstref="ref77"></nolink> <nolink nlid="nl44" bibid="bib153" firstref="ref78"></nolink> <nolink nlid="nl45" bibid="bib99" firstref="ref82"></nolink> <nolink nlid="nl46" bibid="bib125" firstref="ref83"></nolink> <nolink nlid="nl47" bibid="bib43" firstref="ref84"></nolink> <nolink nlid="nl48" bibid="bib47" firstref="ref92"></nolink> <nolink nlid="nl49" bibid="bib58" firstref="ref93"></nolink> <nolink nlid="nl50" bibid="bib28" firstref="ref94"></nolink> <nolink nlid="nl51" bibid="bib61" firstref="ref95"></nolink> <nolink nlid="nl52" bibid="bib15" firstref="ref96"></nolink> <nolink nlid="nl53" bibid="bib57" firstref="ref100"></nolink> <nolink nlid="nl54" bibid="bib14" firstref="ref101"></nolink>
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  Data: The Cognitive Emotion Regulation Questionnaire-Short Specific to the COVID-19 Pandemic
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  Data: <searchLink fieldCode="AR" term="%22Frondozo%2C+Cherry+E%2E%22">Frondozo, Cherry E.</searchLink> (ORCID <externalLink term="http://orcid.org/0000-0002-2001-1159">0000-0002-2001-1159</externalLink>)<br /><searchLink fieldCode="AR" term="%22Mendoza%2C+Norman+B%2E%22">Mendoza, Norman B.</searchLink> (ORCID <externalLink term="http://orcid.org/0000-0003-0344-0709">0000-0003-0344-0709</externalLink>)<br /><searchLink fieldCode="AR" term="%22Dizon%2C+John+Ian+Wilzon+T%2E%22">Dizon, John Ian Wilzon T.</searchLink> (ORCID <externalLink term="http://orcid.org/0000-0002-4912-7390">0000-0002-4912-7390</externalLink>)<br /><searchLink fieldCode="AR" term="%22Buenconsejo%2C+Jet+U%2E%22">Buenconsejo, Jet U.</searchLink> (ORCID <externalLink term="http://orcid.org/0000-0003-3777-8601">0000-0003-3777-8601</externalLink>)
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  Data: <searchLink fieldCode="SO" term="%22Measurement+and+Evaluation+in+Counseling+and+Development%22"><i>Measurement and Evaluation in Counseling and Development</i></searchLink>. 2023 56(3):225-240.
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  Data: Routledge. Available from: Taylor & Francis, Ltd. 530 Walnut Street Suite 850, Philadelphia, PA 19106. Tel: 800-354-1420; Tel: 215-625-8900; Fax: 215-207-0050; Web site: http://www.tandf.co.uk/journals
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  Data: 16
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  Data: 2023
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  Data: Journal Articles<br />Reports - Research
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  Data: <searchLink fieldCode="DE" term="%22Cognitive+Processes%22">Cognitive Processes</searchLink><br /><searchLink fieldCode="DE" term="%22Emotional+Response%22">Emotional Response</searchLink><br /><searchLink fieldCode="DE" term="%22Self+Management%22">Self Management</searchLink><br /><searchLink fieldCode="DE" term="%22Questionnaires%22">Questionnaires</searchLink><br /><searchLink fieldCode="DE" term="%22COVID-19%22">COVID-19</searchLink><br /><searchLink fieldCode="DE" term="%22Pandemics%22">Pandemics</searchLink><br /><searchLink fieldCode="DE" term="%22Adults%22">Adults</searchLink><br /><searchLink fieldCode="DE" term="%22Foreign+Countries%22">Foreign Countries</searchLink><br /><searchLink fieldCode="DE" term="%22Test+Validity%22">Test Validity</searchLink><br /><searchLink fieldCode="DE" term="%22Gender+Differences%22">Gender Differences</searchLink><br /><searchLink fieldCode="DE" term="%22Age+Differences%22">Age Differences</searchLink><br /><searchLink fieldCode="DE" term="%22Stress+Variables%22">Stress Variables</searchLink><br /><searchLink fieldCode="DE" term="%22Affective+Measures%22">Affective Measures</searchLink><br /><searchLink fieldCode="DE" term="%22Factor+Analysis%22">Factor Analysis</searchLink>
– Name: Subject
  Label: Geographic Terms
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  Data: <searchLink fieldCode="DE" term="%22Philippines%22">Philippines</searchLink>
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  Data: <searchLink fieldCode="SU" term="%22Positive+and+Negative+Affect+Schedule%22">Positive and Negative Affect Schedule</searchLink>
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  Data: 10.1080/07481756.2022.2102506
– Name: ISSN
  Label: ISSN
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  Data: 0748-1756<br />1947-6302
– Name: Abstract
  Label: Abstract
  Group: Ab
  Data: The factor structure, measurement invariance, and external validity of the Cognitive Emotion Regulation Questionnaire-short (CERQ-short) specific to the COVID-19 pandemic was examined using data from 3,788 adult Filipinos. The nine-factor CERQ-short was confirmed and was tested invariant across gender and age groups. The CERQ factors correlate theoretically with stress and affect.
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  Data: 2023
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  Data: EJ1395653
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RecordInfo BibRecord:
  BibEntity:
    Identifiers:
      – Type: doi
        Value: 10.1080/07481756.2022.2102506
    Languages:
      – Text: English
    PhysicalDescription:
      Pagination:
        PageCount: 16
        StartPage: 225
    Subjects:
      – SubjectFull: Cognitive Processes
        Type: general
      – SubjectFull: Emotional Response
        Type: general
      – SubjectFull: Self Management
        Type: general
      – SubjectFull: Questionnaires
        Type: general
      – SubjectFull: COVID-19
        Type: general
      – SubjectFull: Pandemics
        Type: general
      – SubjectFull: Adults
        Type: general
      – SubjectFull: Foreign Countries
        Type: general
      – SubjectFull: Test Validity
        Type: general
      – SubjectFull: Gender Differences
        Type: general
      – SubjectFull: Age Differences
        Type: general
      – SubjectFull: Stress Variables
        Type: general
      – SubjectFull: Affective Measures
        Type: general
      – SubjectFull: Factor Analysis
        Type: general
      – SubjectFull: Philippines
        Type: general
      – SubjectFull: Positive and Negative Affect Schedule
        Type: general
    Titles:
      – TitleFull: The Cognitive Emotion Regulation Questionnaire-Short Specific to the COVID-19 Pandemic
        Type: main
  BibRelationships:
    HasContributorRelationships:
      – PersonEntity:
          Name:
            NameFull: Frondozo, Cherry E.
      – PersonEntity:
          Name:
            NameFull: Mendoza, Norman B.
      – PersonEntity:
          Name:
            NameFull: Dizon, John Ian Wilzon T.
      – PersonEntity:
          Name:
            NameFull: Buenconsejo, Jet U.
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          Dates:
            – D: 01
              M: 01
              Type: published
              Y: 2023
          Identifiers:
            – Type: issn-print
              Value: 0748-1756
            – Type: issn-electronic
              Value: 1947-6302
          Numbering:
            – Type: volume
              Value: 56
            – Type: issue
              Value: 3
          Titles:
            – TitleFull: Measurement and Evaluation in Counseling and Development
              Type: main
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