COVID-19 is a serious worldwide health emergency that is affecting many nations. The financial standing and mental health of women are negatively impacted by such widespread epidemics. Thus, the purpose of this study was to evaluate, among married women in Bangladesh during the COVID-19 pandemic, the level of women’s economic empowerment and mental health and related determinants. The author used secondary research from numerous published research articles, review articles, and published international and national reports like the World Health Organization (WHO), UNDP, and United Nations (UN) to examine women’s economic empowerment and mental health during the COVID-19 pandemic. The COVID-19 condition made it more common for women to experience loneliness, melancholy, anxiety, and sleep disruption. Women face the greatest risk because they make up 70% of the healthcare workforce and work in caregiving facilities. According to COVID-19, the primary causes of poor mental health in Bangladesh were being unemployed, being obese, lack of concealing, and having no family. Bangladesh’s patriarchal family system and physical weakness of women leads to increased mental disorders, workplace dangers, abuse, exploitation, harassment, and physical harm during crises and quarantine. This will promote women’s economic empowerment and improve mental health conditions. For this reason, more research about these vulnerable populations is required.

Monira Parvin Moon

Md. Shajahan Kabir

Md. Monjurul Islam

Farhana Arefeen Mila

Md. Sazzadur Rahman Sarker

Women’s Economic Empowerment and Mental Health in the COVID-19 Pandemic

<i>Introduction</i>. Stigma is noted to be one of the greatest barriers to the recovery of persons with mental health problems. Stigma has been acknowledged as both an individual and a social orchestration that has an overpowering impact on the social standing of marginalized persons in a society. This study examined the extant literature to ascertain if any evidence(s) suggested a relationship between perceived public attitudes, religious and cultural beliefs, and structural violence in perpetuating stigma against persons with mental illness. <i>Method</i>. We applied a five-step scoping review framework by Arksey and O’Malley to examine evidence in the literature that suggests relationships between perceptions, religious and cultural beliefs, and structural violence in perpetuating stigma. The researchers systematically conducted a literature search from six databases, including CINAHL, Ovid MEDLINE(R), ProQuest Dissertations & Theses Global, Sociology Collection, PsycINFO, and Sociological Abstracts, using search terms that included stigma, mental illness, perception, religious and cultural beliefs, and structural violence. <i>Results</i>. An initial search in six databases yielded 1223 articles. Checking in the Google Search engine yielded 30 more articles. After removing 25 duplicates, 1198 articles remained for title and abstract screening. After a full-text review, 1143 articles were removed. Overall, 30 articles were selected for data extraction. Thematic analysis of the extracted data resulted in three main themes. These include perceptions about mental illness, perceptions about stigma and discrimination, and forms of stigma perception. <i>Conclusion</i>. This study revealed that individual perceptions of public attitudes contributed to their construction of stigma. It is incumbent on everyone to play their part in mitigating all the negative outcomes that stigma brings, especially to persons with mental illness.

Sebastian Gyamfi

Cheryl Forchuk

Richard Booth

Isaac Luginaah

Enablers of Mental Illness Stigma: A Scoping Review of Individual Perceptions

<i>Background</i>. Cardiovascular disease (CVD) and depression are the leading causes of disability in the U.S. Using electronic health record data, we describe the CVD burden among persons with mental illness enrolled in the Penn State Psychiatry Clinical Assessment and Rating Evaluation System (PCARES) Registry between 2015 and 2020. <i>Methods</i>. CVD burden assessment included prevalence of CVD conditions (any major CVD or individual CVD risk factors), indicated medication prescriptions for CVD risk factors, and mean levels of body mass index (BMI, kg/m<sup>2</sup>), glycosylated hemoglobin (HbA1C, %), glucose (mg/dl), and lipids (mg/dl). We compared the CVD burden between the PCARES sample to a representative sample of adults from the U.S. general population (NHANES 2013-2016) using one-sample chi-square/<span class="nowrap"><svg xmlns:xlink="http://www.w3.org/1999/xlink" xmlns="http://www.w3.org/2000/svg" style="vertical-align:-0.2063999pt" id="M1" height="8.02022pt" version="1.1" viewBox="-0.0498162 -7.81382 4.54925 8.02022" width="4.54925pt"><g transform="matrix(.013,0,0,-0.013,0,0)"><path id="g113-117" d="M324 430H196L233 583L223 592L145 529L120 430H54L29 396L31 388H111L56 126C33 15 54 -12 77 -12C137 -12 214 57 250 95L233 119C208 92 155 59 138 59C126 59 120 70 131 125L186 390L298 394L324 430Z"/></g></svg>-</span>tests for proportions/means. The CVD burden in NHANES participants was adjusted to PCARES age, race, and sex statistics. <i>Results</i>. The PCARES sample (<span class="inline_break"><svg xmlns:xlink="http://www.w3.org/1999/xlink" xmlns="http://www.w3.org/2000/svg" width="22.173pt" style="vertical-align:-0.2064009pt" id="M2" height="8.8423pt" version="1.1" viewBox="-0.0498162 -8.6359 22.173 8.8423"><g transform="matrix(.013,0,0,-0.013,0,0)"><path id="g113-79" d="M822 650H589L583 622C660 617 677 607 674 561C672 534 664 481 647 390L600 137H596L273 650H126L120 622C176 620 194 615 207 594C221 571 225 557 214 504L161 257C141 166 129 112 121 85C108 42 83 30 29 28L23 0H260L266 28C193 33 173 42 176 89C178 122 186 172 202 255L256 527H259L583 -8H612L690 390C708 481 720 535 728 558C744 603 756 619 816 622L822 650Z"/></g><g transform="matrix(.013,0,0,-0.013,14.542,0)"><path id="g117-34" d="M535 323V373H52V323H535ZM535 138V188H52V138H535Z"/></g></svg><span class="irelop"/><span class="nowrap"><svg xmlns:xlink="http://www.w3.org/1999/xlink" xmlns="http://www.w3.org/2000/svg" width="25.219pt" style="vertical-align:-0.2064009pt" height="8.8423pt" version="1.1" viewBox="25.7551838 -8.6359 25.219 8.8423"><g transform="matrix(.013,0,0,-0.013,25.805,0)"><path id="g113-52" d="M285 378C315 398 338 416 353 432C373 451 384 474 384 503C384 579 325 635 236 635H235C182 635 136 610 108 579L65 516L85 496C110 533 150 575 205 575C258 575 300 543 300 481C300 407 232 369 141 339L147 310C163 315 188 321 211 321C268 321 338 284 338 192C338 94 288 40 217 40C160 40 119 68 93 91C85 98 77 97 69 91C60 84 47 71 46 58C44 46 48 35 62 22C75 10 116 -12 162 -12C234 -12 424 62 424 224C424 297 373 359 285 376V378Z"/></g><g transform="matrix(.013,0,0,-0.013,32.045,0)"><path id="g113-54" d="M153 550H386L412 615L406 623H120L82 318C104 327 142 338 184 338C294 338 347 275 347 187C347 112 305 39 221 39C160 39 119 71 97 89C88 97 80 96 71 90C59 80 50 67 49 57C48 45 52 36 66 23C80 9 123 -12 169 -12C221 -11 288 15 342 59C403 109 431 165 431 225C431 308 366 395 238 395C212 395 165 379 127 364L153 550Z"/></g><g transform="matrix(.013,0,0,-0.013,38.285,0)"><use xlink:href="#g113-54"/></g><g transform="matrix(.013,0,0,-0.013,44.526,0)"><path id="g113-55" d="M137 343C167 482 260 545 321 574C357 591 397 603 429 609L423 641C382 634 335 622 295 608C189 570 37 457 37 238C37 84 125 -12 242 -12C362 -12 447 89 447 209C447 311 374 393 267 393C247 393 226 386 204 376L137 343ZM227 337C318 337 361 256 361 173C361 105 336 22 258 22C176 22 126 120 126 240C126 266 127 291 132 310C155 323 189 337 227 337Z"/></g></svg>)</span></span> had a mean (SE) age of 42.4 (0.3) years and comprised 63.0% women, 85.0% non-Hispanic Caucasians, and 41.0% with major depressive disorder. CVD burden was higher in the PCARES sample compared to NHANES participants for any major CVD (8.6% vs. 4.6%), diabetes (18.4% vs. 10.4%), BMI (30.3 vs. 28.3), HbA1C (6.1 vs. 5.6), cholesterol (185.6 vs. 181.7), triglycerides (153.3 vs. 136.1), and indicated antihypertensive (94.3% vs. 76.9%) and cholesterol-lowering (49.5% vs. 36.7%) medications (Bonferroni-corrected <span class="inline_break"><svg xmlns:xlink="http://www.w3.org/1999/xlink" xmlns="http://www.w3.org/2000/svg" width="18.973pt" style="vertical-align:-3.42938pt" id="M3" height="11.7782pt" version="1.1" viewBox="-0.0498162 -8.34882 18.973 11.7782"><g transform="matrix(.013,0,0,-0.013,0,0)"><path id="g113-113" d="M570 304C570 398 525 448 414 448C385 448 343 445 312 434L329 511L321 518C297 504 262 482 244 460L233 411C195 397 159 381 128 358L135 332C160 347 189 360 224 373L111 -147C97 -210 84 -218 17 -231L13 -257L254 -247L259 -218L233 -216C183 -212 177 -202 189 -142L218 -1C238 -10 266 -12 283 -12C351 3 429 48 483 105C543 168 570 242 570 304ZM482 289C482 161 380 33 304 33C278 33 248 51 233 69L303 396C326 400 352 403 369 403C428 403 482 380 482 289Z"/></g><g transform="matrix(.013,0,0,-0.013,11.342,0)"><use xlink:href="#g117-34"/></g></svg><span class="irelop"/><svg xmlns:xlink="http://www.w3.org/1999/xlink" xmlns="http://www.w3.org/2000/svg" width="21.921pt" style="vertical-align:-3.42938pt" height="11.7782pt" version="1.1" viewBox="22.555183800000002 -8.34882 21.921 11.7782"><g transform="matrix(.013,0,0,-0.013,22.605,0)"><path id="g113-49" d="M241 635C89 635 35 457 35 312C35 153 89 -12 240 -12C390 -12 443 166 443 312C443 466 390 635 241 635ZM238 602C329 602 354 454 354 312C354 172 330 22 240 22C152 22 124 173 124 313S148 602 238 602Z"/></g><g transform="matrix(.013,0,0,-0.013,28.845,0)"><path id="g113-47" d="M113 -12C146 -12 170 11 170 46C170 78 146 103 114 103S58 78 58 46C58 11 82 -12 113 -12Z"/></g><g transform="matrix(.013,0,0,-0.013,31.809,0)"><use xlink:href="#g113-49"/></g><g transform="matrix(.013,0,0,-0.013,38.049,0)"><use xlink:href="#g113-52"/></g></svg></span> for each outcome). The CVD burden was lower in the PCARES sample compared to NHANES participants for hypertension (45.9% vs. 50.4%), dyslipidemia (43.2% vs. 61.9%), HDL-C (48.4 vs. 41.4), and LDL-C (107.9 vs. 112.0) (Bonferroni-corrected <span class="inline_break"><svg xmlns:xlink="http://www.w3.org/1999/xlink" xmlns="http://www.w3.org/2000/svg" width="18.973pt" style="vertical-align:-3.42938pt" id="M4" height="11.7782pt" version="1.1" viewBox="-0.0498162 -8.34882 18.973 11.7782"><g transform="matrix(.013,0,0,-0.013,0,0)"><use xlink:href="#g113-113"/></g><g transform="matrix(.013,0,0,-0.013,11.342,0)"><use xlink:href="#g117-34"/></g></svg><span class="irelop"/><svg xmlns:xlink="http://www.w3.org/1999/xlink" xmlns="http://www.w3.org/2000/svg" width="21.921pt" style="vertical-align:-3.42938pt" height="11.7782pt" version="1.1" viewBox="22.555183800000002 -8.34882 21.921 11.7782"><g transform="matrix(.013,0,0,-0.013,22.605,0)"><use xlink:href="#g113-49"/></g><g transform="matrix(.013,0,0,-0.013,28.845,0)"><use xlink:href="#g113-47"/></g><g transform="matrix(.013,0,0,-0.013,31.809,0)"><use xlink:href="#g113-49"/></g><g transform="matrix(.013,0,0,-0.013,38.049,0)"><use xlink:href="#g113-52"/></g></svg></span> for each outcome). Glucose levels (110.9 vs. 111.9) and indicated antidiabetic medications (87.4% vs. 86.6%) were similar in the two samples (<span class="inline_break"><svg xmlns:xlink="http://www.w3.org/1999/xlink" xmlns="http://www.w3.org/2000/svg" width="18.973pt" style="vertical-align:-3.42938pt" id="M5" height="11.7782pt" version="1.1" viewBox="-0.0498162 -8.34882 18.973 11.7782"><g transform="matrix(.013,0,0,-0.013,0,0)"><use xlink:href="#g113-113"/></g><g transform="matrix(.013,0,0,-0.013,11.342,0)"><path id="g117-92" d="M512 230V281L75 514V456L453 256V254L75 55V-3L512 230Z"/></g></svg><span class="irelop"/><span class="nowrap"><svg xmlns:xlink="http://www.w3.org/1999/xlink" xmlns="http://www.w3.org/2000/svg" width="21.921pt" style="vertical-align:-3.42938pt" height="11.7782pt" version="1.1" viewBox="22.555183800000002 -8.34882 21.921 11.7782"><g transform="matrix(.013,0,0,-0.013,22.605,0)"><use xlink:href="#g113-49"/></g><g transform="matrix(.013,0,0,-0.013,28.845,0)"><use xlink:href="#g113-47"/></g><g transform="matrix(.013,0,0,-0.013,31.809,0)"><use xlink:href="#g113-49"/></g><g transform="matrix(.013,0,0,-0.013,38.049,0)"><use xlink:href="#g113-54"/></g></svg>).</span></span> <i>Conclusions</i>. The CVD burden was higher in persons with mental illness compared to the U.S. general population. Integrated mental and physical healthcare services could reduce long-term disability among persons with mental illness.

Radha Dhingra

Fan He

Erika F. H. Saunders

Daniel A. Waschbusch

Amanda M. Pearl

Edward O. Bixler

Jody L. Greaney

Alison R. Swigart

Laila Al-Shaar

Vernon M. Chinchilli

Jeff D. Yanosky

Duanping Liao

Cardiovascular Disease Burden in Persons with Mental Illness: Comparison between a U.S. Psychiatry Outpatient Sample and a U.S. General Population Sample

<i>Background</i>. The COVID-19 pandemic is by far the most significant public health crisis in the 21st century, arousing many psychological concerns like post-traumatic stress disorder (PTSD). <i>Aims</i>. This study is aimed at revealing gender differences and similarities in PTSD symptoms among Chinese adults during COVID-19 pandemic. <i>Methods</i>. Data used in this study were from an online cross-sectional study conducted in February 2020 via a web-based platform. We analyzed data from 558 Chinese adults (334 men and 224 women) with PCL-5 scores over the PTSD criteria. A network analysis was performed to explore the structure of PTSD symptoms for subgroups of men and women. <i>Results</i>. The results showed intrusive thoughts and emotional cue reactivity, together with negative beliefs and negative trauma-related emotions, presented strong positive connections in both men and women. A negative connection between intrusive thoughts and self-destructive/reckless behavior existed among women but not men. Regarding centrality symptoms, women and men had flashbacks and self-destructive/reckless behavior in common, but with differential orders. The most central symptom of PTSD was self-destructive/reckless behavior for women and difficulty concentrating for men. <i>Conclusion</i>. We urge that self-destructive/reckless behaviors and flashbacks, as potential core symptoms of COVID-19-related PTSD, be given more attention in future pandemic-related psychiatric intervention programs.

Fan Yang

Xiaohan Liu

Bo Zhang

Mingqi Fu

Ning Huang

Cheng Zhen

Jing Guo

A Network Analysis of Gender Differences in PTSD Symptoms among Chinese Adults during COVID-19 Pandemic

<i>Background</i>. Healthcare workers during the COVID-19 pandemic played an effective role in providing preventive and curative measures. Scientific evidence confirmed that the outbreak of this disease has caused numerous psychological problems such as pre- and posttraumatic stress disorder (PTSD), anxiety, depression, and anger at a global level. This study is aimed at investigating the general health of healthcare workers and its relationship with anxiety, anger, and posttraumatic stress disorder during the outbreak of COVID-19. <i>Methods</i>. This research was a cross-sectional study conducted on 455 healthcare workers of four teaching hospitals in Kerman, southeast of Iran. The convenience sampling method was used. The research tools included the 12-Item General Health Questionnaire (GHQ-12), the Impact of Event Scale-Revised (IES-R), the trait anxiety section of State-Trait Anxiety Inventory (STAI), and the trait anger section of Trait-State Anger Expression Inventory 2 (STAXI-2). Data analysis was done in IBM SPSS Statistics version 25 and using Pearson’s correlation tests, independent <span class="nowrap"><svg xmlns:xlink="http://www.w3.org/1999/xlink" xmlns="http://www.w3.org/2000/svg" style="vertical-align:-0.2063999pt" id="M1" height="8.02022pt" version="1.1" viewBox="-0.0498162 -7.81382 4.54925 8.02022" width="4.54925pt"><g transform="matrix(.013,0,0,-0.013,0,0)"><path id="g113-117" d="M324 430H196L233 583L223 592L145 529L120 430H54L29 396L31 388H111L56 126C33 15 54 -12 77 -12C137 -12 214 57 250 95L233 119C208 92 155 59 138 59C126 59 120 70 131 125L186 390L298 394L324 430Z"/></g></svg>-</span>test, ANOVA, and multivariate linear regression. <i>Results</i>. 28.1% (<span class="inline_break"><svg xmlns:xlink="http://www.w3.org/1999/xlink" xmlns="http://www.w3.org/2000/svg" width="17.789pt" style="vertical-align:-0.2063904pt" id="M2" height="8.55521pt" version="1.1" viewBox="-0.0498162 -8.34882 17.789 8.55521"><g transform="matrix(.013,0,0,-0.013,0,0)"><path id="g113-111" d="M495 86L479 114C446 82 419 66 409 66C401 66 401 72 406 97C420 166 436 231 453 297C489 435 454 448 428 448C406 448 384 439 354 422C305 394 222 327 161 247H159L183 345C200 415 194 448 173 448C143 448 82 410 23 351L38 325C64 349 95 371 105 371C111 371 116 365 109 336L25 -4L31 -12C50 -4 77 3 107 9C119 69 132 122 145 168C197 254 321 381 370 381C387 381 393 374 378 305L329 95C309 17 320 -12 345 -12C372 -12 430 19 495 86Z"/></g><g transform="matrix(.013,0,0,-0.013,10.158,0)"><path id="g117-34" d="M535 323V373H52V323H535ZM535 138V188H52V138H535Z"/></g></svg><span class="irelop"/><span class="nowrap"><svg xmlns:xlink="http://www.w3.org/1999/xlink" xmlns="http://www.w3.org/2000/svg" width="18.943pt" style="vertical-align:-0.2063904pt" height="8.55521pt" version="1.1" viewBox="21.3711838 -8.34882 18.943 8.55521"><g transform="matrix(.013,0,0,-0.013,21.421,0)"><path id="g113-50" d="M384 0V27C293 34 287 42 287 114V635C232 613 172 594 109 583V559L157 557C201 555 205 550 205 499V114C205 42 199 34 109 27V0H384Z"/></g><g transform="matrix(.013,0,0,-0.013,27.661,0)"><path id="g113-51" d="M412 140C382 77 369 73 315 73H129L270 222C362 320 402 379 402 466C402 571 322 635 234 635C177 635 130 609 99 576L42 495L64 475C90 514 133 568 201 568C274 568 318 519 318 435C318 349 255 267 193 193C144 135 87 78 32 23V0H405C417 45 427 89 440 131L412 140Z"/></g><g transform="matrix(.013,0,0,-0.013,33.901,0)"><path id="g113-57" d="M249 635C141 635 70 555 70 471C70 401 114 353 179 316C143 294 106 267 90 252C68 231 45 202 45 157C45 50 130 -12 237 -12C322 -12 435 52 435 169C435 256 372 304 303 343C349 374 375 398 383 407C401 429 411 458 411 487C411 569 344 635 249 635ZM238 603C285 603 337 567 337 482C337 422 310 385 276 358C205 393 145 426 145 500C145 552 179 603 238 603ZM248 20C183 20 125 70 125 163C125 218 158 268 206 300C284 261 355 217 355 143C355 66 308 20 248 20Z"/></g></svg>)</span></span> of the participants had mental health disorders. The mean score of anxiety was <span class="inline_break"><svg xmlns:xlink="http://www.w3.org/1999/xlink" xmlns="http://www.w3.org/2000/svg" width="38.463pt" style="vertical-align:-0.3499298pt" id="M3" height="8.69875pt" version="1.1" viewBox="-0.0498162 -8.34882 38.463 8.69875"><g transform="matrix(.013,0,0,-0.013,0,0)"><path id="g113-53" d="M456 178V225H360V632H320C217 496 115 347 20 206V178H280V106C280 40 276 34 189 27V0H445V27C364 34 360 39 360 106V178H456ZM280 225H82C149 335 214 431 278 520H280V225Z"/></g><g transform="matrix(.013,0,0,-0.013,6.24,0)"><path id="g113-52" d="M285 378C315 398 338 416 353 432C373 451 384 474 384 503C384 579 325 635 236 635H235C182 635 136 610 108 579L65 516L85 496C110 533 150 575 205 575C258 575 300 543 300 481C300 407 232 369 141 339L147 310C163 315 188 321 211 321C268 321 338 284 338 192C338 94 288 40 217 40C160 40 119 68 93 91C85 98 77 97 69 91C60 84 47 71 46 58C44 46 48 35 62 22C75 10 116 -12 162 -12C234 -12 424 62 424 224C424 297 373 359 285 376V378Z"/></g><g transform="matrix(.013,0,0,-0.013,12.48,0)"><path id="g113-47" d="M113 -12C146 -12 170 11 170 46C170 78 146 103 114 103S58 78 58 46C58 11 82 -12 113 -12Z"/></g><g transform="matrix(.013,0,0,-0.013,15.444,0)"><path id="g113-58" d="M244 635C114 635 38 519 38 422C38 317 111 240 217 240C236 240 255 244 277 256L345 292C311 140 203 39 59 15L64 -15C89 -15 150 -5 204 17C339 72 440 202 440 386C440 521 368 635 244 635ZM228 602C326 602 352 479 352 390C352 370 351 347 348 324C327 308 293 296 258 296C174 296 124 369 124 458C124 517 152 602 228 602Z"/></g><g transform="matrix(.013,0,0,-0.013,21.686,0)"><use xlink:href="#g113-58"/></g><g transform="matrix(.013,0,0,-0.013,30.832,0)"><path id="g117-37" d="M535 290V340H323V533H265V340H52V290H265V84H323V290H535ZM535 -22V28H52V-22H535Z"/></g></svg><span class="ibiop"/><svg xmlns:xlink="http://www.w3.org/1999/xlink" xmlns="http://www.w3.org/2000/svg" width="21.995pt" style="vertical-align:-0.3499298pt" height="8.69875pt" version="1.1" viewBox="41.3191838 -8.34882 21.995 8.69875"><g transform="matrix(.013,0,0,-0.013,41.369,0)"><use xlink:href="#g113-58"/></g><g transform="matrix(.013,0,0,-0.013,47.61,0)"><use xlink:href="#g113-47"/></g><g transform="matrix(.013,0,0,-0.013,50.574,0)"><use xlink:href="#g113-51"/></g><g transform="matrix(.013,0,0,-0.013,56.814,0)"><use xlink:href="#g113-53"/></g></svg></span> which was at moderate to high level of anxiety. The mean score of anger was <span class="inline_break"><svg xmlns:xlink="http://www.w3.org/1999/xlink" xmlns="http://www.w3.org/2000/svg" width="38.461pt" style="vertical-align:-0.3499298pt" id="M4" height="8.69875pt" version="1.1" viewBox="-0.0498162 -8.34882 38.461 8.69875"><g transform="matrix(.013,0,0,-0.013,0,0)"><use xlink:href="#g113-50"/></g><g transform="matrix(.013,0,0,-0.013,6.24,0)"><use xlink:href="#g113-57"/></g><g transform="matrix(.013,0,0,-0.013,12.48,0)"><use xlink:href="#g113-47"/></g><g transform="matrix(.013,0,0,-0.013,15.444,0)"><path id="g113-55" d="M137 343C167 482 260 545 321 574C357 591 397 603 429 609L423 641C382 634 335 622 295 608C189 570 37 457 37 238C37 84 125 -12 242 -12C362 -12 447 89 447 209C447 311 374 393 267 393C247 393 226 386 204 376L137 343ZM227 337C318 337 361 256 361 173C361 105 336 22 258 22C176 22 126 120 126 240C126 266 127 291 132 310C155 323 189 337 227 337Z"/></g><g transform="matrix(.013,0,0,-0.013,21.684,0)"><path id="g113-54" d="M153 550H386L412 615L406 623H120L82 318C104 327 142 338 184 338C294 338 347 275 347 187C347 112 305 39 221 39C160 39 119 71 97 89C88 97 80 96 71 90C59 80 50 67 49 57C48 45 52 36 66 23C80 9 123 -12 169 -12C221 -11 288 15 342 59C403 109 431 165 431 225C431 308 366 395 238 395C212 395 165 379 127 364L153 550Z"/></g><g transform="matrix(.013,0,0,-0.013,30.83,0)"><use xlink:href="#g117-37"/></g></svg><span class="ibiop"/><svg xmlns:xlink="http://www.w3.org/1999/xlink" xmlns="http://www.w3.org/2000/svg" width="21.998pt" style="vertical-align:-0.3499298pt" height="8.69875pt" version="1.1" viewBox="41.3161838 -8.34882 21.998 8.69875"><g transform="matrix(.013,0,0,-0.013,41.366,0)"><use xlink:href="#g113-54"/></g><g transform="matrix(.013,0,0,-0.013,47.607,0)"><use xlink:href="#g113-47"/></g><g transform="matrix(.013,0,0,-0.013,50.571,0)"><path id="g113-56" d="M447 623H65C61 580 56 530 47 475H76C100 541 106 550 172 550H388C308 376 196 170 91 -1L98 -12L172 -2C268 204 360 408 455 611L447 623Z"/></g><g transform="matrix(.013,0,0,-0.013,56.813,0)"><use xlink:href="#g113-51"/></g></svg></span> which was at the moderate level. The mean score of PTSD was <span class="inline_break"><svg xmlns:xlink="http://www.w3.org/1999/xlink" xmlns="http://www.w3.org/2000/svg" width="38.465pt" style="vertical-align:-0.3499298pt" id="M5" height="8.69875pt" version="1.1" viewBox="-0.0498162 -8.34882 38.465 8.69875"><g transform="matrix(.013,0,0,-0.013,0,0)"><use xlink:href="#g113-52"/></g><g transform="matrix(.013,0,0,-0.013,6.24,0)"><use xlink:href="#g113-53"/></g><g transform="matrix(.013,0,0,-0.013,12.48,0)"><use xlink:href="#g113-47"/></g><g transform="matrix(.013,0,0,-0.013,15.444,0)"><use xlink:href="#g113-56"/></g><g transform="matrix(.013,0,0,-0.013,21.687,0)"><use xlink:href="#g113-56"/></g><g transform="matrix(.013,0,0,-0.013,30.834,0)"><use xlink:href="#g117-37"/></g></svg><span class="ibiop"/><svg xmlns:xlink="http://www.w3.org/1999/xlink" xmlns="http://www.w3.org/2000/svg" width="28.257pt" style="vertical-align:-0.3499298pt" height="8.69875pt" version="1.1" viewBox="41.3211838 -8.34882 28.257 8.69875"><g transform="matrix(.013,0,0,-0.013,41.371,0)"><use xlink:href="#g113-50"/></g><g transform="matrix(.013,0,0,-0.013,47.611,0)"><use xlink:href="#g113-54"/></g><g transform="matrix(.013,0,0,-0.013,53.851,0)"><use xlink:href="#g113-47"/></g><g transform="matrix(.013,0,0,-0.013,56.815,0)"><use xlink:href="#g113-51"/></g><g transform="matrix(.013,0,0,-0.013,63.055,0)"><use xlink:href="#g113-53"/></g></svg></span> which was less than the midpoint of the questionnaire, i.e., the score of 44. The results of the multiple linear regression model that showed anxiety, anger, gender, and hospital were predictors of mental health (<span class="inline_break"><svg xmlns:xlink="http://www.w3.org/1999/xlink" xmlns="http://www.w3.org/2000/svg" width="19.289pt" style="vertical-align:-0.6370001pt" id="M6" height="9.2729pt" version="1.1" viewBox="-0.0498162 -8.6359 19.289 9.2729"><g transform="matrix(.013,0,0,-0.013,0,0)"><path id="g113-81" d="M600 480C600 590 528 650 384 650H143L137 622C222 614 225 607 210 531L130 127C113 41 106 36 23 28L17 0H294L300 28C204 36 195 42 212 127L243 284L314 263C327 263 339 263 352 264C465 271 600 337 600 480ZM508 481C508 351 402 304 329 304C289 304 265 311 250 317L295 559C302 594 310 606 323 611C335 616 350 619 367 619C455 619 508 573 508 481Z"/></g><g transform="matrix(.013,0,0,-0.013,11.658,0)"><path id="g117-91" d="M512 -3V55L134 254V256L512 456V514L75 281V230L512 -3Z"/></g></svg><span class="irelop"/><span class="nowrap"><svg xmlns:xlink="http://www.w3.org/1999/xlink" xmlns="http://www.w3.org/2000/svg" width="21.918pt" style="vertical-align:-0.6370001pt" height="9.2729pt" version="1.1" viewBox="22.8711838 -8.6359 21.918 9.2729"><g transform="matrix(.013,0,0,-0.013,22.921,0)"><path id="g113-49" d="M241 635C89 635 35 457 35 312C35 153 89 -12 240 -12C390 -12 443 166 443 312C443 466 390 635 241 635ZM238 602C329 602 354 454 354 312C354 172 330 22 240 22C152 22 124 173 124 313S148 602 238 602Z"/></g><g transform="matrix(.013,0,0,-0.013,29.161,0)"><use xlink:href="#g113-47"/></g><g transform="matrix(.013,0,0,-0.013,32.125,0)"><use xlink:href="#g113-49"/></g><g transform="matrix(.013,0,0,-0.013,38.365,0)"><use xlink:href="#g113-54"/></g></svg>).</span></span> <i>Conclusion</i>. The results of the present study showed that about a quarter of the healthcare workers faced with the COVID-19 pandemic had mental health disorders and suffered from moderate to high anxiety, moderate anger, and PTSD. It was also observed in this study that there was a weak to moderate significant correlation between general health and anxiety, anger, and PTSD in healthcare workers. So, healthcare workers need a lot of social and psychological support.

Alireza Malakoutikhah

Leila Ahmadi Lari

Pooya Baharloo

Rasmieh Al-Amer

Mohamed Alnaiem

Hossein Khaluei

Mahlagha Dehghan

Healthcare Workers’ General Health and Its Relation with Anxiety, Anger, and Posttraumatic Stress Disorder during COVID-19 Outbreak in Southeast Iran

Over the past few years, malingered psychosis has had a progressive occurrence since a great deal of attention has been directed to the closures of long-stay psychiatric institutions and care in the community. Therefore, malingered psychosis needs to be identified to conduct precise forensic assessments and prevent miscarriages of justice and misuse of restricted healthcare resources. Although, over the past decades, researchers have introduced a number of workable psychometric strategies and tools for diagnosing true psychosis, it is still sometimes challenging to differentiate between true and malingered psychosis. Hence, identifying reliable and innovative diagnostic alternatives seems crucial. Accordingly, a summary of gathered evidence is provided by the present review for enhancing future evaluation of oropharyngeal microbiome composition as a practical indicator for diagnosing true psychosis in a forensic psychiatric setting. As per the systematic search terms (namely, “diagnostic marker,” “oropharyngeal microbiome,” “forensic psychiatric setting,” “psychosis,” and “oropharyngeal microbiota”), relevant English publications were searched from January 1, 1980, to September 15, 2023, in Scopus, the Web of Science, Embase, Cochrane Library, PubMed, and Google Scholar databases. Finally, eight articles were included in the present review. Also, we adopted the narrative technique so that the material synthesis leads to a cohesive and compelling story. The results revealed that the periodontal disease and saliva microbiome were possibly associated with true psychosis. Thus, since oropharyngeal microbial compositions are highly different among healthy controls and patients with true psychosis, future research can take advantage of saliva to differentiate between fake and true fake psychosis throughout the initial stages of forensic psychiatric assessment. As a substrate of interest, saliva could also be used for characterizing the various stages of psychosis under a forensic psychiatric setting.

Mohsen Khosravi

Domenico De Berardis

Sahel Sarabandi

Sakineh Mazloom

Amir Adibi

Negin Javan

Zahra Ghiasi

Mohammad Nafeli

Negar Rahmanian

An Update Review to Cast Light on the Possible Role of Altered Oropharyngeal Microbiota in Differentiating True Psychosis from Malingered Psychosis in a Forensic Psychiatric Setting

About this journal

<p><em>Mental Illness</em>&nbsp;is an online-only, international, Open Access peer-reviewed journal which publishes scientific papers concerning the latest advances in the diagnosis and treatment of mental illness. All psychiatry-related manuscripts are welcome.</p>


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<p>Chief Editor Prof Domenico De Berardis is based at the ASL 4 of Teramo, Italy, and is currently researching alexithymia, schizophrenia, bipolar and anxiety disorders.</p>


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Mental Illness is an online-only, international, Open Access peer-reviewed journal which publishes scientific papers concerning the latest advances in the diagnosis and treatment of mental illness. All psychiatry-related manuscripts are welcome.

Mental Illness