Childhood physical abuse victims more likely to experience poor physical and mental health

Childhood physical abuse victims more likely to experience poor physical and mental health

More mature older people who had been bodily abused as little ones had been appreciably extra possible to build persistent pain and long-term bodily disease in later lifetime in accordance to a freshly-released examine by College of Toronto researchers. They were also two times as most likely to create melancholy and stress and anxiety issues compared to all those without having this early trauma.

“Unfortunately, our findings recommend that the traumatic knowledge of childhood physical abuse can affect each actual physical and mental health several a long time afterwards. It also underlines the importance of assessing for adverse childhood experiences among people of all ages, which include older grownups,” claimed Anna Buhrmann, who began this investigate for her undergraduate thesis in the Bachelor of Arts and Science software at McMaster College, Hamilton, Ontario and is a investigation assistant at the Institute of Life Program & Getting old at the College of Toronto.

The bodily health problems that made bundled diabetic issues, most cancers, migraines, arthritis, heart ailment, diabetic issues, and serious-obstructive pulmonary sickness (COPD). The one-way links amongst childhood abuse and poor bodily and mental wellbeing persisted even just after accounting for money, schooling, using tobacco, binge drinking, and other brings about of bad wellbeing.

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Well being experts serving older grownups need to have to be mindful that it is hardly ever as well late to refer people today for counseling. A promising intervention, cognitive behavioral remedy [CBT], has been examined and identified successful at cutting down submit-traumatic pressure dysfunction and depressive and panic indications between survivors of childhood abuse.”

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Esme Fuller-Thomson, Research Co-Creator and Professor, Supervisor of Buhrmann’s Thesis Study, College of Toronto

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Fuller-Thomson is Director of the Institute of Lifestyle System & Getting older at the College of Toronto’s Aspect-Inwentash School of Social Do the job.

It was not doable for the cross-sectional examine to decide the distinct pathways by means of which experiencing physical abuse as a youngster influences an individual’s wellness afterwards in life. Present-day research propose that childhood actual physical abuse consequences several physiological improvements, which includes the dysregulation of methods that regulate the reaction of the physique to tension.

Potential prospective exploration investigating disruptions to these techniques that are previously joined to several bodily and psychological sicknesses, these kinds of as abnormal ranges of cortisol, may perhaps support to lose light on the working experience of childhood abuse victims.

The knowledge for this research had been drawn from a agent sample of grown ups aged 60 and more mature in the Canadian province of British Columbia. It in contrast 409 older grown ups who described a historical past of childhood actual physical abuse to 4,659 of their friends who reported they experienced not been bodily abused all through their youth. The knowledge had been drawn from the Canadian Group Well being Study.

Source:

Journal reference:

Buhrmann, A S & Fuller-T, E (2022) Poorer actual physical and mental wellness among older grown ups a long time soon after dealing with childhood physical abuse. Ageing and Overall health Exploration. doi.org/10.1016/j.ahr.2022.100088

A systematic review of health sciences students’ online learning during the COVID-19 pandemic | BMC Medical Education

A systematic review of health sciences students’ online learning during the COVID-19 pandemic | BMC Medical Education
  • Dhawan S. Online learning: a panacea in the time of COVID-19 crisis. J Educ Technol Syst. 2020;49:5–22.

    Article 

    Google Scholar
     

  • El Said GR. How did the COVID-19 pandemic affect higher education learning experience? An empirical investigation of learners’ academic performance at a university in a developing country. Adv Human Computer Interact. 2021;2021:1–10.

    Article 

    Google Scholar
     

  • Kessler G. Introduction to teaching and technology. TESOL Encycl English Lang Teach. 2018;1:1–20.


    Google Scholar
     

  • Kusmaryono I, Jupriyanto J, Kusumaningsih W. A systematic literature review on the effectiveness of distance learning: problems, opportunities, challenges, and predictions. Int J Educ. 2021;14:62–9.

    Article 

    Google Scholar
     

  • Ismaili Y. Evaluation of students’ attitude toward distance learning during the pandemic (Covid-19): a case study of ELTE university. Horiz. 2021;29:17–30.

    Article 

    Google Scholar
     

  • Aguilera-Hermida AP. College students’ use and acceptance of emergency online learning due to COVID-19. Int J Educ Res Open. 2020;1:100011.

    Article 

    Google Scholar
     

  • Cojocariu V-M, Lazar I, Nedeff V, Lazar G. SWOT anlysis of e-learning educational services from the perspective of their beneficiaries. Procedia Soc Behav Sci. 2014;116:1999–2003.

    Article 

    Google Scholar
     

  • Pokhrel S, Chhetri R. A literature review on impact of COVID-19 pandemic on teaching and learning. 2021;8:133–41.https://doi.org/10.1177/2347631120983481

  • Hurlbut AR. Online vs. traditional learning in teacher education: a comparison of student progress. Am J Distance Educ. 2018;32:248–66.

    Article 

    Google Scholar
     

  • Sintema EJ. Effect of COVID-19 on the performance of grade 12 students: implications for STEM education. Eurasia J Math Sci Technol Educ. 2020;16:1–6.

    Article 

    Google Scholar
     

  • Şen HŞ. The attitudes of university students towards learning. Procedia-Social Behav Sci. 2013;83:947.

    Article 

    Google Scholar
     

  • Alberti S, Motta P, Ferri P, Bonetti L. The effectiveness of team-based learning in nursing education: a systematic review. Nurse Educ Today. 2021;97:104721.

    Article 

    Google Scholar
     

  • Azeem M, Mahmood N, Khalil-ur-Rehman, Afzal MT, Muhammad N, Idrees M. Development of an attitude scale to measure pre-service teachers attitude towards the teaching profession. Int J Learn. 2009;16:175–88.

  • Heitmann H, Wagner P, Fischer E, Gartmeier M, Schmidt-Graf F. Effectiveness of non-bedside teaching during the COVID-19 pandemic: a quasi-experimental study. BMC Med Educ. 2022;22:1–7.

    Article 

    Google Scholar
     

  • Hannay M, Newvine T. Perceptions of distance learning: a comparison of online and traditional learning. J online Learn Teach. 2006;2:1–11.


    Google Scholar
     

  • Kemp N, Grieve R. Face-to-face or face-to-screen? Undergraduates’ opinions and test performance in classroom vs. online learning. Front Psychol. 2014;5:1278.


    Google Scholar
     

  • Mukhtar K, Javed K, Arooj M, Sethi A. Advantages, Limitations and Recommendations for online learning during COVID-19 pandemic era. Pakistan J Med Sci. 2020;36:S27.


    Google Scholar
     

  • Kmet LM, Cook LS, Lee RC. Standard quality assessment criteria for evaluating primary research papers from a variety of fields. 2004.


    Google Scholar
     

  • Khalil R, Mansour AE, Fadda WA, Almisnid K, Aldamegh M, Al-Nafeesah A, et al. The sudden transition to synchronized online learning during the COVID-19 pandemic in Saudi Arabia: a qualitative study exploring medical students’ perspectives. BMC Med Educ. 2020;20(1):285.

    Article 

    Google Scholar
     

  • Suliman WA, Abu-Moghli FA, Khalaf I, Zumot AF, Nabolsi M. Experiences of nursing students under the unprecedented abrupt online learning format forced by the national curfew due to COVID-19: a qualitative research study. Nurse Educ Today. 2021;100:104829.

    Article 

    Google Scholar
     

  • Khan AM, Patra S, Vaney N, Mehndiratta M, Chauhan R. Rapid transition to online practical classes in preclinical subjects during COVID-19: experience from a medical college in North India. Med J Armed Forces India. 2021;77:S161–7.

    Article 

    Google Scholar
     

  • Langegård U, Kiani K, Nielsen SJ, Svensson PA. Nursing students’ experiences of a pedagogical transition from campus learning to distance learning using digital tools. BMC Nurs. 2021;20:23.

    Article 

    Google Scholar
     

  • Caton JB, Chung S, Adeniji N, Hom J, Brar K, Gallant A, et al. Student engagement in the online classroom: comparing preclinical medical student question-asking behaviors in a videoconference versus in-person learning environment. FASEB BioAdvances. 2021;3:110–7.

    Article 

    Google Scholar
     

  • Suppan M, Stuby L, Carrera E, Cottet P, Koka A, Assal F, et al. Asynchronous distance learning of the national institutes of health stroke scale during the COVID-19 pandemic (e-learning vs video): randomized controlled trial. J Med Internet Res. 2021;23:e23594.

    Article 

    Google Scholar
     

  • Atli K, Selman W, Ray A. A comprehensive multicomponent neurosurgical course with use of virtual reality: modernizing the medical classroom. J Surg Educ. 2021;78:1350–6.

    Article 

    Google Scholar
     

  • Co M, Chung PHY, Chu KM. Online teaching of basic surgical skills to medical students during the COVID-19 pandemic: a case–control study. Surg Today. 2021;51:1404–9.

    Article 

    Google Scholar
     

  • Olum R, Atulinda L, Kigozi E, Nassozi DR, Mulekwa A, Bongomin F, et al. Medical education and E-learning during COVID-19 pandemic: awareness, attitudes, preferences, and barriers among undergraduate medicine and nursing students at Makerere University. Uganda J Med Educ Curric Dev. 2020;7:2382120520973212.


    Google Scholar
     

  • Sawarkar G, Sawarkar P, Kuchewar V. Ayurveda students’ perception toward online learning during the COVID-19 pandemic. J Educ Health Promot. 2020;9:342.

    Article 

    Google Scholar
     

  • Jaap A, Dewar A, Duncan C, Fairhurst K, Hope D, Kluth D. Effect of remote online exam delivery on student experience and performance in applied knowledge tests. BMC Med Educ. 2021;21:86.

    Article 

    Google Scholar
     

  • Martinez L, Holley A, Brown S, Abid A. Addressing the rapidly increasing need for telemedicine education for future physicians. PRiMER. 2020;4:16.

    Article 

    Google Scholar
     

  • Schoenfeld-Tacher RM, Dorman DC. Effect of delivery format on student outcomes and perceptions of a veterinary medicine course: Synchronous versus asynchronous learning. Vet Sci. 2021;8:1–14.


    Google Scholar
     

  • Jiménez-Rodríguez D, Arrogante O. Simulated video consultations as a learning tool in undergraduate nursing: students’ perceptions. Healthc. 2020;8:280.

    Article 

    Google Scholar
     

  • Al-Balas M, Al-Balas HI, Jaber HM, Obeidat K, Al-Balas H, Aborajooh EA, et al. Distance learning in clinical medical education amid COVID-19 pandemic in Jordan: current situation, challenges, and perspectives. BMC Med Educ. 2020;20:1–7.

    Article 

    Google Scholar
     

  • Alqurshi A. Investigating the impact of COVID-19 lockdown on pharmaceutical education in Saudi Arabia – a call for a remote teaching contingency strategy. Saudi Pharm J. 2020;28:1075–83.

    Article 

    Google Scholar
     

  • Alsoufi A, Alsuyihili A, Msherghi A, Elhadi A, Atiyah H, Ashini A, et al. Impact of the COVID-19 pandemic on medical education: medical students’ knowledge, attitudes, and practices regarding electronic learning. PLoS One. 2020;15(11):e0242905.

    Article 

    Google Scholar
     

  • Amir LR, Tanti I, Maharani DA, Wimardhani YS, Julia V, Sulijaya B, et al. Student perspective of classroom and distance learning during COVID-19 pandemic in the undergraduate dental study program Universitas Indonesia. BMC Med Educ. 2020;20:392.

    Article 

    Google Scholar
     

  • Anwar A, Mansoor H, Faisal D, Khan HS. E-Learning amid the COVID-19 lockdown: standpoint of medical and dental undergraduates. Pakistan J Med Sci. 2021;37:217.


    Google Scholar
     

  • Bączek M, Zagańczyk-Bączek M, Szpringer M, Jaroszyński A, Wożakowska-Kapłon B. Students’ perception of online learning during the COVID-19 pandemic: a survey study of Polish medical students. Medicine (Baltimore). 2021;100:e24821.

    Article 

    Google Scholar
     

  • Chandrasinghe PC, Siriwardana RC, Kumarage SK, Munasinghe BNL, Weerasuriya A, Tillakaratne S, et al. A novel structure for online surgical undergraduate teaching during the COVID-19 pandemic. BMC Med Educ. 2020;20(1):324.

    Article 

    Google Scholar
     

  • Coffey CS, MacDonald BV, Shahrvini B, Baxter SL, Lander L. Student perspectives on remote medical education in clinical core clerkships during the COVID-19 pandemic. Med Sci Educ. 2020;30:1577–84.

    Article 

    Google Scholar
     

  • De Ponti R, Marazzato J, Maresca AM, Rovera F, Carcano G, Ferrario MM. Pre-graduation medical training including virtual reality during COVID-19 pandemic: a report on students’ perception. BMC Med Educ. 2020;20(1):332.

    Article 

    Google Scholar
     

  • Dost S, Hossain A, Shehab M, Abdelwahed A, Al-Nusair L. Perceptions of medical students towards online teaching during the COVID-19 pandemic: a national cross-sectional survey of 2721 UK medical students. BMJ Open. 2020;10:e042378.

    Article 

    Google Scholar
     

  • Elsalem L, Al-Azzam N, Jum’ah AA, Obeidat N. Remote E-exams during Covid-19 pandemic: A cross-sectional study of students’ preferences and academic dishonesty in faculties of medical sciences. Ann Med Surg. 2021;62:326–33.

    Article 

    Google Scholar
     

  • Guiter GE, Sapia S, Wright AI, Hutchins GGA, Arayssi T. Development of a remote online collaborative medical school pathology curriculum with clinical correlations, across several international sites, through the Covid-19 pandemic. Med Sci Educ. 2021;31:549–56.

    Article 

    Google Scholar
     

  • Gupta S, Dabas A, Swarnim S, Mishra D. Medical education during COVID-19 associated lockdown: faculty and students’ perspective. Med J Armed Forces India. 2021;77:S79-84.

    Article 

    Google Scholar
     

  • Ibrahim NK, Al Raddadi R, AlDarmasi M, Al Ghamdi A, Gaddoury M, AlBar HM, et al. Medical students’ acceptance and perceptions of e-learning during the Covid-19 closure time in King Abdulaziz University. Jeddah J Infect Public Health. 2021;14:17–23.

    Article 

    Google Scholar
     

  • Jiménez-Rodríguez D, Torres Navarro M del M, Plaza del Pino FJ, Arrogante O. Simulated nursing video consultations: an innovative proposal during Covid-19 confinement. Clin Simul Nurs. 2020;48:29–37.

  • Kim JW, Myung SJ, Yoon HB, Moon SH, Ryu H, Yim JJ. How medical education survives and evolves during COVID-19: our experience and future direction. PLoS One. 2020;15(12):e0243958.

    Article 

    Google Scholar
     

  • Kumar A, Al Ansari A, Kamel Shehata M, Yousif Tayem Y, Khalil Arekat M, Mohammed Kamal A, et al. Evaluation of curricular adaptations using digital transformation in a medical school in arabian gulf during the COVID-19 pandemic. J Microsc Ultrastruct. 2020;8:186–92.

    Article 

    Google Scholar
     

  • Mahdy MAA. The impact of COVID-19 pandemic on the academic performance of veterinary medical students. Front Vet Sci. 2020;7:594261.

    Article 

    Google Scholar
     

  • Menon UK, Gopalakrishnan S, Unni CSN, Ramachandran R, Baby P, Sasidharan A, et al. Perceptions of undergraduate medical students regarding institutional online teaching-learning programme. Med J Armed Forces India. 2021;77:S227–33.

    Article 

    Google Scholar
     

  • Merson C, Gonzalez FJN, Orth E, Adams A, McLean A. Back in the saddle: student response to remote online equine science classes. Transl Anim Sci. 2020;4:txaa218.

    Article 

    Google Scholar
     

  • Muflih S, Abuhammad S, Al-Azzam S, Alzoubi KH, Muflih M, Karasneh R. Online learning for undergraduate health professional education during COVID-19: Jordanian medical students’ attitudes and perceptions. Heliyon. 2021;7:e08031.

    Article 

    Google Scholar
     

  • Puljak L, Čivljak M, Haramina A, Mališa S, Čavić D, Klinec D, et al. Attitudes and concerns of undergraduate university health sciences students in Croatia regarding complete switch to e-learning during COVID-19 pandemic: a survey. BMC Med Educ. 2020;20:416.

    Article 

    Google Scholar
     

  • Rajab MH, Gazal AM, Alkattan K. Challenges to online medical education during the COVID-19 pandemic. Cureus. 2020;12:e8966.


    Google Scholar
     

  • Sandhaus Y, Kushnir T, Ashkenazi S. Electronic distance learning of pre-clinical studies during the COVID-19 pandemic: a preliminary study of medical student responses and potential future impact. Isr Med Assoc J. 2020;22:489–93.


    Google Scholar
     

  • Shahrvini B, Baxter SL, Coffey CS, MacDonald BV, Lander L. Pre-clinical remote undergraduate medical education during the COVID-19 pandemic: a survey study. BMC Med Educ. 2021;21:13.

    Article 

    Google Scholar
     

  • Sindiani AM, Obeidat N, Alshdaifat E, Elsalem L, Alwani MM, Rawashdeh H, et al. Distance education during the COVID-19 outbreak: a cross-sectional study among medical students in North of Jordan. Ann Med Surg. 2020;59:186–94.

    Article 

    Google Scholar
     

  • Tigaa RA, Sonawane SL. An international perspective: teaching chemistry and engaging students during the COVID-19 pandemic. J Chem Educ. 2020;97:3318–21.

    Article 

    Google Scholar
     

  • Tuma F, Nassar AK, Kamel MK, Knowlton LM, Jawad NK. Students and faculty perception of distance medical education outcomes in resource-constrained system during COVID-19 pandemic. A cross-sectional study. Ann Med Surg. 2021;62:377–82.

    Article 

    Google Scholar
     

  • Wang K, Zhang L, Ye L. A nationwide survey of online teaching strategies in dental education in China. J Dent Educ. 2021;85:128–34.

    Article 

    Google Scholar
     

  • Yoo H, Kim D, Lee YM, Rhyu IJ. Adaptations in anatomy education during COVID-19. J Korean Med Sci. 2021;36:1–12.

    Article 

    Google Scholar
     

  • Wang C, Xie A, Wang W, Wu H. Association between medical students’ prior experiences and perceptions of formal online education developed in response to COVID-19: a cross-sectional study in China. BMJ Open. 2020;10:e041886.

    Article 

    Google Scholar
     

  • JunodPerron N, Dominicé Dao M, Rieder A, Sommer J, Audétat M-C. Online Synchronous clinical communication training during the Covid-19 pandemic. Adv Med Educ Pract. 2020;11:1029–36.

    Article 

    Google Scholar
     

  • Al-Taweel FB, Abdulkareem AA, Gul SS, Alshami ML. Evaluation of technology-based learning by dental students during the pandemic outbreak of coronavirus disease 2019. Eur J Dent Educ. 2021;25:183–90.

    Article 

    Google Scholar
     

  • Bolatov AK, Seisembekov TZ, Askarova AZ, Baikanova RK, Smailova DS, Fabbro E. Online-learning due to COVID-19 improved mental health among medical students. Med Sci Educ. 2021;31:183–92.

    Article 

    Google Scholar
     

  • Co M, Chu K. Distant surgical teaching during COVID-19-a pilot study on final year medical students. Surg Pract. 2020;24:105–9.

    Article 

    Google Scholar
     

  • Dutta S, Ambwani S, Lal H, Ram K, Mishra G, Kumar T, et al. The satisfaction level of undergraduate medical and nursing students regarding distant preclinical and clinical teaching amidst covid-19 across India. Adv Med Educ Pract. 2021;12:113–22.

    Article 

    Google Scholar
     

  • Elzainy A, El Sadik A, Al AW. Experience of e-learning and online assessment during the COVID-19 pandemic at the College of Medicine, Qassim University. J Taibah Univ Med Sci. 2020;15:456–62.


    Google Scholar
     

  • Fischbeck S, Hardt J, Malkewitz C, Petrowski K. Evaluation of a digitized physician-patient-communication course evaluated by preclinical medical students: a replacement for classroom education? GMS J Med Educ. 2020;37:1–8.


    Google Scholar
     

  • Higgins R, Murphy F, Hogg P. The impact of teaching experimental research on-line: research-informed teaching and COVID-19. Radiography. 2021;27:539–45.

    Article 

    Google Scholar
     

  • Kaliyadan F, ElZorkany K, Al WF. An online dermatology teaching module for undergraduate medical students amidst the COVID-19 pandemic: an experience and suggestions for the future. Indian Dermatol Online J. 2020;11:944–7.

    Article 

    Google Scholar
     

  • Kalleny N. Advantages of Kahoot! Game-based formative assessments along with methods of its use and application during the COVID-19 pandemic in various live learning sessions. J Microsc Ultrastruct. 2020;8:175–85.

    Article 

    Google Scholar
     

  • Khalaf K, El-Kishawi M, Moufti MA, Al Kawas S. Introducing a comprehensive high-stake online exam to final-year dental students during the COVID-19 pandemic and evaluation of its effectiveness. Med Educ Online. 2020;25:1826861.

    Article 

    Google Scholar
     

  • Liu Q, Sun W, Du C, Yang L, Yuan N, Cui H, et al. Medical morphology training using the Xuexi Tong platform during the COVID-19 pandemic: development and validation of a web-based teaching approach. JMIR Med Inform. 2021;9:e24497.

    Article 

    Google Scholar
     

  • Schlenz MA, Schmidt A, Wöstmann B, Krämer N, Schulz-Weidner N. Students’ and lecturers’ perspective on the implementation of online learning in dental education due to SARS-CoV-2 (COVID-19): a cross-sectional study. BMC Med Educ. 2020;20(1):354.

    Article 

    Google Scholar
     

  • Steehler AJ, Pettitt-Schieber B, Studer MB, Mahendran G, Pettitt BJ, Henriquez OA. Implementation and evaluation of a virtual elective in otolaryngology in the time of COVID-19. Otolaryngol Head Neck Surg. 2021;164(3):556–61.

    Article 

    Google Scholar
     

  • Zhang Q, He YJ, Zhu YH, Dai MC, Pan MM, Wu JQ, et al. The evaluation of online course of Traditional Chinese Medicine for MBBS international students during the COVID-19 epidemic period. Integr Med Res. 2020;9:100449.

    Article 

    Google Scholar
     

  • Afonso N, Kelekar A, Alangaden A. “I have a cough”: an interactive virtual respiratory case-based module. MedEdPORTAL J Teach Learn Resour. 2020;16:11058.


    Google Scholar
     

  • Amer M, Nemenqani D. Successful use of virtual microscopy in the assessment of practical histology during pandemic COVID-19: A descriptive study. J Microsc Ultrastruct. 2020;8:156–61.

    Article 

    Google Scholar
     

  • Alkhowailed MS, Rasheed Z, Shariq A, Elzainy A, El Sadik A, Alkhamiss A, et al. Digitalization plan in medical education during COVID-19 lockdown. Informatics Med Unlocked. 2020;20:100432.

    Article 

    Google Scholar
     

  • Choi B, Jegatheeswaran L, Minocha A, Alhilani M, Nakhoul M, Mutengesa E. The impact of the COVID-19 pandemic on final year medical students in the United Kingdom: a national survey. BMC Med Educ. 2020;20:1–11.

    Article 

    Google Scholar
     

  • Nguyen T. The effectiveness of online learning: beyond no significant difference and future horizons. MERLOT J Online Learn Teach. 2015;11:309–19.


    Google Scholar
     

  • Cheng M, Taylor J, Williams J, Tong K. Student satisfaction and perceptions of quality: testing the linkages for PhD students. High Educ Res Dev. 2016;35:1153–66.

    Article 

    Google Scholar
     

  • Stone C, Freeman E, Dyment JE, Muir T, Milthorpe N. Equal or equitable?: The role of flexibility within online education. Aust Int J Rural Educ. 2019;29:26–40.


    Google Scholar
     

  • Gustiani S. Students’motivation in online learning during covid-19 pandemic era: a case study. Holistics. 2020;12:23–40.


    Google Scholar
     

  • Alvermann DE, Rezak AT, Mallozzi CA, Boatright MD, Jackson DF. Reflective practice in an online literacy course: lessons learned from attempts to fuse reading and science instruction. Teach Coll Rec. 2011;113:27–56.

    Article 

    Google Scholar
     

  • Pedro J, Abodeeb-Gentile T, Courtney A. Reflecting on literacy practices: using reflective strategies in online discussion and written reflective summaries. J Digit Learn Teach Educ. 2012;29:39–47.

    Article 

    Google Scholar
     

  • Jones SH. Benefits and challenges of online education for clinical social work: three examples. Clin Soc Work J. 2015;43:225–35.

    Article 

    Google Scholar
     

  • Coman C, Țîru LG, Meseșan-Schmitz L, Stanciu C, Bularca MC. Online teaching and learning in higher education during the coronavirus pandemic: students’ perspective. Sustainability. 2020;12:10367.

    Article 

    Google Scholar
     

  • Bahnson J, Olejnikova L. Are recorded lectures better than live lectures for teaching students legal research. Law Libr J. 2017;109:205.


    Google Scholar
     

  • Alawamleh M, Al-Twait LM, Al-Saht GR. The effect of online learning on communication between instructors and students during Covid-19 pandemic. Asian Educ Dev Stud. 2020;11(2):380–400.

    Article 

    Google Scholar
     

  • Saminathan V. Problems of Online Classes. Int J Acad Res Reflectoor. 2021;9 January:1–4. https://www.researchgate.net/publication/348447927.

  • Chan MMK, Yu DSF, Lam VSF, Wong JYH. Online clinical training in the COVID-19 pandemic. Clin Teach. 2020;17(4):445–6.

    Article 

    Google Scholar
     

  • Ramos-Morcillo AJ, Leal-Costa C, Moral-García JE, Ruzafa-Martínez M. Experiences of nursing students during the abrupt change from face-to-face to e-learning education during the first month of confinement due to COVID-19 in Spain. Int J Environ Res Public Health. 2020;17:5519.

    Article 

    Google Scholar
     

  • Sitzmann T, Ely K, Bell BS, Bauer KN. The effects of technical difficulties on learning and attrition during online training. J Exp Psychol Appl. 2010;16:281.

    Article 

    Google Scholar
     

  • Fawaz M, Samaha A. E‐learning: depression, anxiety, and stress symptomatology among Lebanese university students during COVID‐19 quarantine. Nursing forum: Wiley Online Library; 2021. p. 52–7.


    Google Scholar
     

  • Oluwalola FK. Effect of emotion on distance e-learning—the fear of technology. Int J Soc Sci Humanit. 2015;5:966–70.

    Article 

    Google Scholar
     

  • Aliyyah RR, Rachmadtullah R, Samsudin A, Syaodih E, Nurtanto M, Tambunan ARS. The perceptions of primary school teachers of online learning during the COVID-19 pandemic period: a case study in Indonesia. J Ethn Cult Stud. 2020;7:90–109.

    Article 

    Google Scholar
     

  • Sari M, Ilhamdaniah MT. Time management during Covid-19 pandemic. 2021. https://www.atlantis-press.com/proceedings/tvet-20/125952246.

    Book 

    Google Scholar
     

  • Ilgaz H, Afacan AG. Providing online exams for online learners: Does it really matter for them? Educ Inf Technol. 2020;25:1255–69.

    Article 

    Google Scholar
     

  • Gonzalez T, De La Rubia MA, Hincz KP, Comas-Lopez M, Subirats L, Fort S, et al. Influence of COVID-19 confinement on students’ performance in higher education. PLoS One. 2020;15:e0239490.

    Article 

    Google Scholar
     

  • Schmidt SJ. Distracted learning: big problem and golden opportunity. J Food Sci Educ. 2020;19:278–91.

    Article 

    Google Scholar
     

  • Barrot JS, Llenares II, Del Rosario LS. Students’ online learning challenges during the pandemic and how they cope with them: the case of the Philippines. Educ Inf Technol. 2021;26:7321–38.

    Article 

    Google Scholar
     

  • Pelikan ER, Lüftenegger M, Holzer J, Korlat S, Spiel C, Schober B. Learning during COVID-19: the role of self-regulated learning, motivation, and procrastination for perceived competence. Zeitschrift für Erziehungswiss. 2021;24:393–418.

    Article 

    Google Scholar
     

  • Gormley GJ, Collins K, Boohan M, Bickle IC, Stevenson M. Is there a place for e-learning in clinical skills? A survey of undergraduate medical students’ experiences and attitudes. Med Teach. 2009;31:e6-12.

    Article 

    Google Scholar
     

  • Rodrigues PD, Vethamani ME. The impact of online learning in the development of speaking skills. J Interdiscip Res Educ. 2015;5(1):43–67.


    Google Scholar
     

  • Muflih S, Abuhammad S, Karasneh R, Al-Azzam S, Alzoubi K, Muflih M. Online education for undergraduate health professional education during the COVID-19 pandemic: attitudes, barriers, and ethical issues. Res Sq. 2020;3:1–17.


    Google Scholar
     

  • Diwanji S. Number of internet users in India 2015–2023. Statista. 2020. https://www.statista.com/statistics/255146/number-ofinternet-users-in-india/

  • Siddes M, Veerabhadrappa BP. Online education in India: issues and challenges. EPRA Int J Econ Bus Manag Stud. 2020;7:74–7.


    Google Scholar
     

  • Sharma D, Singh A. E-learning in India duringcovid-19: challenges and opportunities. Eur J Mol Clin Med. 2021;7:2020.


    Google Scholar
     

  • Aljaraideh Y, Al BK. Jordanian students’ barriers of utilizing online learning: a survey study. Int Educ Stud. 2019;12:99–108.

    Article 

    Google Scholar
     

  • Levin KA. Study design III: cross-sectional studies. Evid Based Dent. 2006;7:24–5.

    Article 

    Google Scholar
     

  • Stang A. Randomisierte kontrollierte Studien—unverzichtbar in der klinischen Forschung. Dtsch Arzteblatt-Arztliche Mitteilungen-Ausgabe A. 2011;108:661.


    Google Scholar
     

  • Local experts, students shed light on pandemic’s effects on mental health

    Local experts, students shed light on pandemic’s effects on mental health

    For more than an hour, four Thomas Jefferson Middle School students, slightly tired from an early wakeup call and recent standardized testing, said they felt fine after everything they experienced over the course of the COVID-19 pandemic. 

    They were looking forward to the end of the school year, they liked being back in school with friends, and while they may have been a little stressed with distance learning, they said they hadn’t experienced depression or anxiety during the last two years.

    Then, they were asked if they had experienced any loss over the last two years. Each of them had or nearly had: An uncle who died from COVID-19 in Mexico. Another late uncle who loved the Raiders. A grandmother figure who died a month ago. A grandmother who fell gravely ill from COVID-19 and recovered. Another grandmother who is battling cancer. 

    Finally, their emotions poured out. Tears were shed. 

    Eighth grader D’Artagnan Leon-Montano found out he lost his uncle in the middle of the night when he heard sobs around the house. “I never heard my mom crying, and that night I heard her cry.” To honor his uncle, he never takes off his Raiders hat. 

    Online education and the mental health of faculty during the COVID-19 pandemic in Japan

    Online education and the mental health of faculty during the COVID-19 pandemic in Japan

    The doing the job natural environment of college faculty improved speedily for the duration of the COVID-19 pandemic. School associates were being questioned to change from in-individual instruction to instructing lessons on the web in a pretty short interval of time, as portion of endeavours to stop the spread of the COVID-19 pandemic15. From this backdrop, this examine investigated the mental overall health of Japanese school customers who taught lessons on-line for the duration of the COVID-19 pandemic, to discover hazard variables for bad mental health and fitness and reduce the development of psychological ailment in the future. Even though other reports have examined the mental wellbeing of college students all through the COVID-19 pandemic3,10,11,12, rather couple scientific studies have centered on the psychological well being of school associates in universities. Accordingly, our review contributes to the literature by furnishing new conclusions on the matter.

    Initial, we investigated the true problem of the faculty’s psychological overall health prior to the COVID-19 pandemic. Even just before the outbreak of the pandemic, it had been noted that school members in universities have weak mental overall health as opposed to customers of other professions18. We used the WHO-5 to measure the psychological health and fitness of faculty customers and then calculated the proportion of school at threat of psychological ailment (total WHO-5 score < 13). The results revealed that 15.3{e4f787673fbda589a16c4acddca5ba6fa1cbf0bc0eb53f36e5f8309f6ee846cf} of faculty members had been at risk of developing a mental illness, even before the COVID-19 pandemic. Another investigation of mental health among Japanese faculty reports that 10.2{e4f787673fbda589a16c4acddca5ba6fa1cbf0bc0eb53f36e5f8309f6ee846cf} of faculty members were at risk for mental illness prior to the pandemic33. Compared to this result, the at-risk group was larger in our sample. Lee et al.34 also used the WHO-5 to assess the mental health risks of various occupations. They reported that 13.2{e4f787673fbda589a16c4acddca5ba6fa1cbf0bc0eb53f36e5f8309f6ee846cf} of management/professionals were at risk of developing mental illnesses. In the context of their findings, the proportion of faculty members at the risk of developing a mental illness is comparatively high, thus demonstrating that the mental health of faculty members in universities is inherently worse than that of workers in the management/professional field. Lee et al.34 also reported that the proportion of office workers at the risk of mental illness was 12.9{e4f787673fbda589a16c4acddca5ba6fa1cbf0bc0eb53f36e5f8309f6ee846cf}. Thus, the proportion of faculty members at the risk of developing mental illness exceeded that of office workers. It is quantitatively evident that the mental health of faculty members in universities had been worse than that of workers in other occupations, even before the COVID-19 pandemic.

    Next, we focused on the WHO-5 scores of faculty members before and during the COVID-19 pandemic, which revealed that the mental health of faculty members worsened during the pandemic. The proportion at risk of mental illness was 15.3{e4f787673fbda589a16c4acddca5ba6fa1cbf0bc0eb53f36e5f8309f6ee846cf} before the COVID-19 pandemic, but nearly doubled to 33.5{e4f787673fbda589a16c4acddca5ba6fa1cbf0bc0eb53f36e5f8309f6ee846cf} during that period. We speculated that this large increase was due to lifestyle and work-related changes, including remote work, a lack of face-to-face communication, and the shift to online instruction in a very short period of time. In particular, the sudden transition to teaching classes online involved a very heavy workload, accompanied by unforeseen financial and time costs35.

    In addition, we hypothesized that the dramatic decline observed in the mental health of many faculty members could be attributed to four risk factors: the number of classes taught online, the time needed to prepare for those classes, challenges related to the technology needed to conduct classes online, and the level of satisfaction with support services provided by the university. Our results suggest that two of these were significant risk factors for the poor mental health among faculty members. The first risk factor was related to technology. Faculty members who reported having difficulty using the required technology were more susceptible to poorer mental health. The second risk factor was the level of satisfaction with the university support services. Faculty members who reported higher levels of satisfaction with university support services maintained good mental health despite the unforeseen shift in the mode of instruction. When faculty members first began teaching their classes online, many of them were not familiar with the online conferencing software, lacked the required equipment (e.g., webcams, high-quality microphones), and received limited, if any, training on online content delivery36. Furthermore, the lack of relevant IT skills and experience made it difficult for these individuals to adapt to teaching classes online17. Faculty members who lacked IT skills had to redesign their courses and learn IT skills simultaneously. In this situation, it is speculated that faculty members who had difficulty in using IT felt a substantial burden and decline in their mental health.

    In addition, the results revealed that the amount of satisfaction with university support services for online teaching was related to good mental health. To reduce difficulty in using IT, it is important to ensure that the working environment of the faculty satisfies the needs of the faculty who must use unfamiliar technology to teach classes online37. According to Wang and Li37, the needs of the faculty broadly refer to the support that universities must provide for faculty members to effectively use new technology (organizational level) and the technology that helps them meet the objectives of their job (technological level). It also involves assistance from their colleagues, which helps them effectively use technology at work (people level). The administrative support services for online teaching satisfied all the requirements listed above. For example, the university provided social support such as consultations with university IT staff, who explained how to use the software and equipment needed for online instruction, as well as technical support such as providing equipment and writing manuals for some software. Satisfaction with this comprehensive support provided by the university might have reduced the faculty members’ difficulty in using IT, and consequently, improved their mental health.

    Our results also showed that both the number of classes taught online and class preparation time were weak predictors of mental health among faculty during the COVID-19 pandemic, as compared to challenges related to the technology needed to conduct classes online. This result suggests that the psychological burden of dealing with unfamiliar technology, rather than the workload resulting from online classes, including the long preparation time, had a substantially negative effect on the mental health of faculty members.

    The workload for faculty members can be broadly divided into three categories: teaching, research, and service. Faculty members are required to strike an appropriate balance between the three. According to Zey-Ferrell and Baker38, faculty members recognize that teaching is the main component of their work. Their study investigated 503 faculty members, and found that although 92.1{e4f787673fbda589a16c4acddca5ba6fa1cbf0bc0eb53f36e5f8309f6ee846cf} had strong expectations from themselves about teaching, such ideal self-expectations were incongruent with what they actually did. Furthermore, there are a few serious stressors for faculty members, including heavy workloads and anxiety related to securing funding for their research, but the most serious was excessively high self-expectations39,40. Taking these findings into consideration, it is possible that during the COVID-19 pandemic, faculty members placed high expectations on themselves, aiming to provide high-quality lessons online and had to simultaneously deal with the unfamiliar technology needed to conduct classes online. Such circumstances can be reasonably expected to cause stress, which leads to poor mental health.

    In Japan, some university classes were held in person after the lockdown was lifted. However, many courses continue to be conducted online. Some faculty members consider the shift to online teaching to be a positive challenge or at least useful for developing certain competencies17. A previous study also revealed that online classes can be useful, effective, and have a positive influence on student performance41. Furthermore, with online classes, faculty members and students do not need to spend time and money to commute, and there is less drain on university resources. This leads to benefits such as conserving the time and energy of the faculty and saving university resources42. Based on these findings, we assume that online classes will become a normal part of university education, and that faculty members will therefore continue to teach classes online to some extent. Accordingly, universities will need to provide both technical and social support to reduce faculty members’ difficulty in using IT and maintain their mental health.

    We established the effect of teaching classes online during the COVID-19 pandemic on the mental health of faculty members in universities, but there were some limitations to our research, related to sampling and measurement. As sampling issue, we first acknowledge that the number of participants in our study was quite limited, and included only Japanese faculty members. The extent of the COVID-19 infection and government countermeasures differ across countries. In addition, the utilization of online services to deliver course instructions in the setting of higher education varied according to country, before the COVID-19 pandemic. Therefore, the results may not be generalizable to other countries. Furthermore, depending on the major (e.g., medical science and nursing science), some practical subjects may have been more difficult than others to adapt to online instruction. This study investigated a Japanese university specializing in social science therefore, the results may not be generalizable to other institutions of higher education. Accordingly, we need to widen the scope of participants to include faculty members from various departments and institutions in more countries in future research. Finally, due to missing data, we could not investigate gender differences. The switch to online education and remote work may have affected women and men differently. For example, previous research suggests that during COVID-19, women carried a heavier load in the provision of childcare43. Therefore, future research should look deeper into gender differences in mental health among academic staff during the pandemic.

    As for measurement issues, mental health before the pandemic was reported retrospectively, so memory biases could have affected participants’ evaluations, rendering them unreliable. Even so, retrospectively evaluated average well-being in our study was similar to that reported in previous studies employing the Japanese version of WHO-544, therefore retrospection might not have critically affected participants’ evaluations. In addition, because we measured difficulty in using IT devices and satisfaction with university support services with one item each, our results should be interpreted with caution. To provide a more detailed image of the problems causing poor mental health among faculty teaching online, validated scales measuring different aspects of university support (e.g. technical vs social support) and IT difficulty (e.g. lack of expertise in using IT vs stress produced by technical problems, etc.), alongside longitudinal assessments of well-being should be used in future research.

    Our research focused on the first year of the COVID-19 pandemic, during which most faculty members in universities were required to shift to teaching their classes online. Accordingly, these faculty members had to adapt their lessons for online instruction in a very short period of time. In fact, many faculty members were required to set up equipment and learn the necessary IT skills, and in many cases, redesign the content of their lessons in just a month. Accordingly, they might have felt overloaded. More than a year after the outbreak, the work of adapting lessons for online instruction is mostly complete, and thus, the burden on the faculty may be less severe in the future. This change might ultimately have a positive effect on the mental health of faculty members. Regardless, the results of this study demonstrate the need to continuously monitor the mental health of faculty members who must teach classes online in universities.

    This study has focused on the mental health of university faculty, but our findings may possibly be applicable to other occupations as well. The COVID-19 pandemic has been found to cause psychological stress for people working in various occupations, with new work-styles such as telework and remote work being identified as the primary cause of such stress45. In addition, it has been shown that during the COVID-19 pandemic utilizing IT has become more important and the need to use IT has become more frequent in comparison to pre-pandemic times46. This situation of work-styles changing due to the pandemic and mental health worsening due to increased use of IT may be viewed as similar to the situation experienced by university faculty. Therefore, the findings of this study may possibly be applied to other occupations as well, in order to explain the cause of the deterioration of mental health from the perspective of degree of familiarity with IT use and satisfaction with company support, thus clarifying the kind of support that companies must offer to promote the continuation of telework.

    Perspectives From the National Institutes of Health on Multidimensional Mental Health Disparities Research: A Framework for Advancing the Field

    Perspectives From the National Institutes of Health on Multidimensional Mental Health Disparities Research: A Framework for Advancing the Field

    There is ample research documenting the existence and persistence of mental health and mental health care disparities over the past several decades (1). For example, research consistently suggests that there are racial and ethnic differences in prevalence of some mental disorders (e.g., compared to non-Hispanic Whites, Blacks/African Americans have higher rates of diagnosed schizophrenia [2] and American Indians/Alaska Natives have higher rates of posttraumatic stress disorder [3]). Across diagnostic categories, racial and ethnic minority individuals have more severe and persistent impairment than non-Hispanic White individuals (4, 5). Similarly, compared to cisgender heterosexual individuals, sexual and gender minorities have higher rates of depression symptoms and suicidal behaviors (6). Despite efforts to address mental health and mental health care disparities, there remains a significant gap between our ability to document, investigate, and understand mental health disparities and their causes and to translate this research knowledge into interventions that meaningfully reduce disparities in clinical and health care outcomes.

    The National Institute on Minority Health and Health Disparities (NIMHD) Health Disparities Research Framework (hereafter “the framework”) is intended to encourage a comprehensive approach to understanding and addressing health disparities with respect to race/ethnicity, socioeconomic status, sexual and gender minority status, and rural versus urban residence (7, 8). The framework, which is an extension of the socioecological model, consists of two dimensions: domains of influence on health (biological, behavioral, physical and built environment, sociocultural environment, health care system) that occur at different levels of influence on health (individual, interpersonal, community, societal). The individual cells of the framework each represent categories of potential determinants of health disparities and/or intervention targets to address health disparities.

    Much of the focus in mental health disparities research, including research supported by the National Institutes of Health (NIH), has been either on single cells of the framework (e.g., individual-level biological determinants), single levels of influence (e.g., individual-level biological and behavioral determinants), or single domains of influence (e.g., lack of access to mental health care as the primary driver of disparities). However, this approach does not take into account the complex interaction of structural and social determinants of mental health that create mental health disparities. Thus, addressing mental health disparities requires research that explores factors at multiple levels of influence, particularly beyond the individual level. Such research should prioritize an understanding of how community, social, and structural factors, including structural racism and discrimination, impact individual-, community-, and population-level mental health outcomes. In addition, research that examines how domains and levels of influence interact across multiple levels (i.e., cell×cell interactions) is necessary to better approximate the real-world complexities of how interconnected determinants impact the mental health of individuals, families, communities, and populations.

    To encourage mental health disparities research that uses a multidimensional approach and to provide researchers with a more tailored approach than other existing disparities frameworks and models, we offer an adaptation of the framework specific to mental health disparities (Figure 1). The examples provided within the cells of the framework are intended to be illustrative rather than exhaustive. This adapted framework is similar to other frameworks and models that describe social determinants of health (SDOH), such as those by the U.S. Department of Health and Human Services Healthy People 2030 (9) or the World Health Organization (10). What distinguishes this framework is that it includes both general SDOH and determinants that may be specific to mental health to promote a more comprehensive view of mental health disparities. In addition, the adapted framework emphasizes the simultaneous examination of both domains and levels of influence to provide an organizational structure with which to identify or conceptualize relevant determinants and generate appropriate strategies to address them.

    FIGURE 1.

    FIGURE 1. An adaptation of the National Institute on Minority Health and Health Disparities Research Framework for mental health disparities

    As a hypothetical example, suppose researchers and community partners wish to develop an intervention to improve help-seeking to address high rates of depression and posttraumatic stress disorder in a local Hmong population. The team views health literacy as the key feature driving low levels of help-seeking, but they also identify other relevant determinants, including lack of health insurance, food insecurity, lack of transportation, and lack of availability of Hmong-speaking providers. It becomes clear to the team that a health information–focused intervention alone is unlikely to result in improved help-seeking unless these structural barriers to accessing mental health care are also addressed. We are not suggesting that determinants in all cells of the framework must always be included to address health disparities, but we highlight the importance of examining the constellation of determinants relevant to the specific disparities being studied, and the need to intervene at the appropriate levels to have a sustained impact. The availability of a framework that emphasizes multidomain, multilevel determinants of health does not ensure that research approaches and interventions will successfully address mental health disparities—this depends upon how researchers and stakeholders apply and implement the framework.

    Based on the concept of generations of health disparities research (11), we describe examples of three types of mental health disparities research in which the adapted framework may be implemented and that address SDOH. Note that research to document mental health disparities is not included here if does not also examine mechanisms or determinants of those disparities, or if SDOH are measured but included only as control variables in analyses. Although this research progression may be a natural evolution, we argue that the highly incremental research that has characterized much of the health disparities field is not necessary to replicate for mental health disparities, given that this foundational work is often relevant across health conditions and outcomes.

    First Generation: Understanding How SDOH Cause, Sustain, or Mitigate Mental Health Disparities

    This body of research moves beyond individual-level determinants of mental health disparities (e.g., lack of awareness of mental health problems, lack of health insurance) to identify higher-level social and structural factors that contribute to or mitigate health disparities. Factors such as family and community cohesion, population density, neighborhood-level disadvantage, neighborhood safety and community violence, community social climate, and community and national-level racism and discrimination have all been found to be associated with individual and community-level mental health symptoms and distress (12). This work is critical in identifying modifiable intervention targets that have potential to reduce mental health disparities. Because the social and policy landscape is constantly changing with respect to impacts on minoritized and marginalized populations, this work will always be needed. However, the current distribution, where most mental health disparities research reflects observational research to document and understand disparities, needs to be shifted more toward intervention and action. For example, a recent portfolio analysis conducted by the NIH Office of Disease Prevention of new NIH-funded extramural projects from fiscal year 2012 to 2019 (13) found that about two-thirds of prevention projects were observational, while randomized intervention studies accounted for less than one-fifth of projects, and this proportion declined over time. In addition, only 3.5{e4f787673fbda589a16c4acddca5ba6fa1cbf0bc0eb53f36e5f8309f6ee846cf} of prevention projects included a randomized intervention to address a leading risk factor for death and disability in populations experiencing health disparities. Prevention research specific to mental health outcomes accounted for less than 8{e4f787673fbda589a16c4acddca5ba6fa1cbf0bc0eb53f36e5f8309f6ee846cf} of projects in fiscal year 2019 and mirrored these overall patterns (13).

    Second Generation: Evaluating Interventions That Help Individuals Address SDOH or Mitigate Their Impact

    This body of research recognizes that the unique experiences of minoritized and marginalized populations need to be acknowledged and addressed in the context of mental health interventions and care. Examples include 1) coping-focused interventions to help individuals manage or reduce distress associated with racism or other forms of discrimination, poverty, unemployment, family separations, and other challenging life circumstances (14, 15); 2) trauma-informed interventions that tailor services for individuals exposed to early or chronic traumatic events or poverty-related stressors (1618); and 3) patient navigation or service linkage interventions that connect individuals to needed health and social services and/or address access barriers to facilitate engagement in care (19, 20). Such interventions, although a critical component of health and mental health care, only address the consequences of societal inequities and do not directly affect the systems and structures that cause and sustain mental health disparities. In isolation, these interventions will not be sufficient to reduce or eliminate mental disparities at the population level. However, based on our observation of applications submitted to NIH, interventions to help individuals or populations mitigate the impact of SDOH rather than changing the SDOH directly remain common.

    Third Generation: Evaluating Interventions That Directly Impact SDOH to Produce Lasting Changes for Communities and Populations

    Notably, this area seems to be characterized by more articles calling for social and structural interventions (21, 22) than articles describing the results from actual social and structural interventions (23), and the latter are particularly rare in the mental health field. To address mental health disparities, interventions must move beyond an individual-level treatment-focused model of mental health to emphasize families, organizations, and communities and encompass prevention and sustainable change. Examples of such interventions include medical-legal partnerships in which clinicians and legal personnel work to address discrimination or unfair practices related to housing, education, criminal justice, or other domains (24); alternatives to incarceration for individuals with severe mental illness charged with minor offenses (25); and the implementation of evidence-based depression treatment in faith-based settings (26). However, many structural interventions addressing SDOH have not been rigorously evaluated, and few studies have examined the impact of interventions on disparities (21). Although critically needed, research evaluating these types of interventions has many challenges. Balancing methodological rigor with feasibility and acceptability of study designs can be an issue that requires thoughtful communication and collaboration between research and community collaborators. Studies can be costly to execute, as testing interventions at organizational, neighborhood, or community levels requires these settings to be the unit of analysis rather than the individual, necessitating the inclusion of multiple sites or locations. Interventions addressing SDOH (e.g., racism and discrimination) are likely to have nonspecific outcomes relevant to a range of health conditions, which may pose a challenge to funders who prefer interventions to address disease-specific determinants of health leading to disease-specific outcomes. Despite these many challenges, such interventions hold the greatest promise for eliminating mental health disparities and achieving mental health equity.

    On an encouraging note, NIH is beginning to emphasize the need for interventions that move beyond addressing SDOH at the individual level in recent funding opportunity announcements. Topics have included maternal mortality and morbidity (27), structural racism and discrimination (28), family- and community-level interventions (29, 30), physical activity (31), opioid misuse (32), HIV (33), firearm morbidity and mortality (34), and suicide and suicidal ideation and behaviors (35). Although these funding opportunities may include mental health determinants and outcomes, additional targeted opportunities from NIH and other funders of mental health research and services that are explicitly focused on SDOH and mental health disparities are likely needed to make significant progress in this area.

    Taken together, this review suggests several important implications for mental health disparities research and clinical practices aimed at reducing disparities. First, this review highlights the opportunity for researchers to use and build upon the proffered mental health disparities framework to mechanistically explore SDOH that can subsequently inform appropriately framed and tailored interventions to reduce disparities. Second, from a clinical perspective, this review points to the importance of establishing a continuum of care to address mental health disparities, which includes both mental health promotion and prevention interventions among marginalized and minoritized populations. Development of interventions aimed at the promotion and prevention end of the mental health continuum of care would facilitate addressing the social and structural factors that have been identified as significant drivers of mental health disparities, including SDOH, and would increase the ultimate reach and range of intervention.

    Office of Disease Prevention, NIH, Bethesda, Md. (Alvidrez); Office for Disparities Research and Workforce Diversity, NIMH, Bethesda, Md. (Barksdale); National Institute on Minority Health and Health Disparities, NIH, Bethesda, Md. (Barksdale).

    The views expressed in this article represent those of the authors and do not necessarily represent the views of NIH.

    The authors report no financial relationships with commercial interests.

    References

    1. US Department of Health and Human Services: Publications and Reports of the Surgeon General, in Mental Health: Culture, Race, and Ethnicity: A Supplement to Mental Health: A Report of the Surgeon General. Rockville, Md, Substance Abuse and Mental Health Services Administration, 2001Google Scholar

    2. Gara MA, Vega WA, Arndt S, et al.: Influence of patient race and ethnicity on clinical assessment in patients with affective disorders. Arch Gen Psychiatry 2012; 69:593–600Crossref, MedlineGoogle Scholar

    3. Gone JP, Trimble JE: American Indian and Alaska Native mental health: diverse perspectives on enduring disparities. Annu Rev Clin Psychol 2012; 8:131–160Crossref, MedlineGoogle Scholar

    4. Vilsaint CL, NeMoyer A, Fillbrunn M, et al.: Racial/ethnic differences in 12-month prevalence and persistence of mood, anxiety, and substance use disorders: variation by nativity and socioeconomic status. Compr Psychiatry 2019; 89:52–60Crossref, MedlineGoogle Scholar

    5. Breslau J, Kendler KS, Su M, et al.: Lifetime risk and persistence of psychiatric disorders across ethnic groups in the United States. Psychol Med 2005; 35:317–327Crossref, MedlineGoogle Scholar

    6. King M, Semlyen J, Tai SS, et al.: A systematic review of mental disorder, suicide, and deliberate self harm in lesbian, gay, and bisexual people. BMC Psychiatry 2008; 8:70Crossref, MedlineGoogle Scholar

    7. Alvidrez J, Castille D, Laude-Sharp M, et al.: The National Institute on Minority Health and Health Disparities Research Framework. Am J Public Health 2019; 109:S16–S20Crossref, MedlineGoogle Scholar

    8. National Institute on Minority Health and Health Disparities: NIMHD Research Framework. 2017. nimhd.nih.gov/researchFrameworkGoogle Scholar

    9. Healthy People 2030, US Department of Health and Human Services, Office of Disease Prevention and Health Promotion. health.gov/healthypeople/objectives-and-data/social-determinants-healthGoogle Scholar

    10. World Health Organization: Social determinants of health: overview. www.who.int/health-topics/social-determinants-of-health#tab=tab_1Google Scholar

    11. Thomas SB, Quinn SC, Butler J, et al.: Toward a fourth generation of disparities research to achieve health equity. Annu Rev Public Health 2011; 32:399–416Crossref, MedlineGoogle Scholar

    12. Alegría M, NeMoyer A, Falgàs Bagué I, et al.: Social determinants of mental health: where we are and where we need to go. Curr Psychiatry Rep 2018; 20:95Crossref, MedlineGoogle Scholar

    13. Murray DM, Ganoza LF, Vargas AJ, et al.: New NIH primary and secondary prevention research during 2012–2019. Am J Prev Med 2021; 60:e261–e268Crossref, MedlineGoogle Scholar

    14. Miller MJ, Keum BT, Thai CJ, et al.: Practice recommendations for addressing racism: a content analysis of the counseling psychology literature. J Couns Psychol 2018; 65:669–680Crossref, MedlineGoogle Scholar

    15. Woods-Giscombé CL, Gaylord SA: The cultural relevance of mindfulness meditation as a health intervention for African Americans: implications for reducing stress-related health disparities. J Holist Nurs 2014; 32:147–160Crossref, MedlineGoogle Scholar

    16. Meléndez Guevara AM, Lindstrom Johnson S, Elam K, et al.: Culturally responsive trauma-informed services: a multilevel perspective from practitioners serving Latinx children and families. Community Ment Health J 2021; 57:325–339Crossref, MedlineGoogle Scholar

    17. Stolbach BC, Anam S: Racial and ethnic health disparities and trauma-informed care for children exposed to community violence. Pediatr Ann 2017; 46:e377–e381Crossref, MedlineGoogle Scholar

    18. Brotman LM, Dawson-McClure S, Kamboukos D, et al.: Effects of ParentCorps in prekindergarten on child mental health and academic performance: follow-up of a randomized clinical trial through 8 years of age. JAMA Pediatr 2016; 170:1149–1155Crossref, MedlineGoogle Scholar

    19. Barnett ML, Gonzalez A, Miranda J, et al.: Mobilizing community health workers to address mental health disparities for underserved populations: a systematic review. Adm Policy Ment Health 2018; 45:195–211Crossref, MedlineGoogle Scholar

    20. Bridges AJ, Andrews AR III, Villalobos BT, et al.: Does integrated behavioral health care reduce mental health disparities for Latinos? Initial findings. J Lat Psychol 2014; 2:37–53Crossref, MedlineGoogle Scholar

    21. Brown AF, Ma GX, Miranda J, et al.: Structural interventions to reduce and eliminate health disparities. Am J Public Health 2019; 109:S72–S78Crossref, MedlineGoogle Scholar

    22. Shim RS, Compton MT: Addressing the social determinants of mental health: if not now, when? If not us, who? Psychiatr Serv 2018; 69:844–846LinkGoogle Scholar

    23. Thornton RL, Glover CM, Cené CW, et al.: Evaluating strategies for reducing health disparities by addressing the social determinants of health. Health Aff (Millwood) 2016; 35:1416–1423Crossref, MedlineGoogle Scholar

    24. Paul EG, Curran M, Tobin Tyler E: The medical-legal partnership approach to teaching social determinants of health and structural competency in residency programs. Acad Med 2017; 92:292–298Crossref, MedlineGoogle Scholar

    25. Castillo EG, Ijadi-Maghsoodi R, Shadravan S, et al.: Community interventions to promote mental health and social equity. Curr Psychiatry Rep 2019; 21:35Crossref, MedlineGoogle Scholar

    26. Hankerson SH, Wells K, Sullivan MA, et al.: Partnering with African American churches to create a community coalition for mental health. Ethn Dis 2018; 28:467–474Crossref, MedlineGoogle Scholar

    27. National Institutes of Health: RFA-MD-20-008, Addressing Racial Disparities in Maternal Mortality and Morbidity (R01 Clinical Trial Optional). 2020. grants.nih.gov/grants/guide/rfa-files/RFA-MD-20-008.htmlGoogle Scholar

    28. National Institutes of Health: RFA-MD-21-004, Understanding and Addressing the Impact of Structural Racism and Discrimination on Minority Health and Health Disparities (R01 Clinical Trial Optional). 2021. grants.nih.gov/grants/guide/rfa-files/rfa-md-21-004.htmlGoogle Scholar

    29. National Institutes of Health: PAR-21-358, Risk and Protective Factors of Family Health and Family Level Interventions (R01 Clinical Trial Optional). 2021. grants.nih.gov/grants/guide/pa-files/PAR-21-358.htmlGoogle Scholar

    30. National Institutes of Health: RFA-MD-22-007, Community Level Interventions to Improve Minority Health and Reduce Health Disparities (R01 Clinical Trial Optional). 2022. grants.nih.gov/grants/guide/rfa-files/RFA-MD-22-007.htmlGoogle Scholar

    31. National Institutes of Health: NOT-OD-21-087, Notice of Special Interest (NOSI): Developing and Testing Multilevel Physical Activity Interventions to Improve Health and Well-Being. 2021. grants.nih.gov/grants/guide/notice-files/NOT-OD-21-087.htmlGoogle Scholar

    32. National Institutes of Health: RFA-DA-22-036, NIH HEAL Initiative: Preventing Opioid Misuse and Co-Occurring Conditions by Intervening on Social Determinants (R01 Clinical Trials Optional). 2021. grants.nih.gov/grants/guide/rfa-files/RFA-DA-22-036.htmlGoogle Scholar

    33. National Institutes of Health: NOT-MD-21-014, Notice of Special Interest (NOSI): Multi-Level HIV Prevention Interventions for Individuals at the Highest Risk of HIV Infection. 2021. grants.nih.gov/grants/guide/notice-files/NOT-MD-21-014.htmlGoogle Scholar

    34. National Institutes of Health: NOT-OD-21-059, Notice of Intent to Publish Funding Opportunity Announcements for Research on Firearm Injury and Mortality Prevention. 2022. grants.nih.gov/grants/guide/notice-files/NOT-OD-21-059.htmlGoogle Scholar

    35. National Institutes of Health: RFA-MH-21-187, Systems-Level Risk Detection and Interventions to Reduce Suicide, Ideation, and Behaviors in Youth From Underserved Populations (R01 Clinical Trial Optional). 2021. grants.nih.gov/grants/guide/rfa-files/RFA-MH-21-187.htmlGoogle Scholar

    Minor in Mind-Body Studies > Physical Education & Mind Body Health > USC Dana and David Dornsife College of Letters, Arts and Sciences

    Minor in Mind-Body Studies > Physical Education & Mind Body Health > USC Dana and David Dornsife College of Letters, Arts and Sciences

    Description: Learners will discover the interconnectedness of system and brain wellbeing by means of an experiential, interdisciplinary analyze that blends principle, investigation, and follow. Offered as a result of the Bodily Education & Head Human body Health and fitness, core coursework features foundations in yoga, mindfulness, and tension management for a thorough technique to healthful residing. Interdisciplinary coursework examines psychological and physical health for a multi-dimensional watch of head-entire body consciousness and link. This slight is developed for students who want to increase a dimension of wellbeing to their particular and academic lives. It is notably suited for those people with job passions in well being treatment, bodily treatment, psychology, or social get the job done.

    For additional information and facts about the Brain-Entire body Research small, please speak to Linda Yaron Weston at [email protected].

      

    Required Coursework (20 units): Pupils will comprehensive a mixture of experiential lessons in Physical Education & Thoughts System Wellness, as nicely as principle and study-primarily based interdisciplinary electives. 

    Core Classes (3 models)

    PHED 120a: Yoga – 1 unit

    PHED 119: Introduction to Mindfulness – 2 models OR

    PHED 160: Stress Management for Healthful Dwelling – 2 units

     

    Upper-Division Courses  (Opt for 12 models)

    BAEP 472: The Science of Peak Efficiency – 2 models

    DANC 362: Pilates Mat Coaching – 2 models

    GERO 411L: Physiology, Nourishment, and Growing older – 2 units

    HBIO 301L: Human Anatomy – 4 units

    HBIO 309: The Human Device – 4 models

    HBIO 401L: Physiology of Motion – 4 models

    MKT 404: Pleasure and Wellbeing in the Market – 4 models

    OT 325: The Mind: Head, Physique, and Self – 4 models

    PSYC 339Lg: Origin of the Head – 4 units

    REL 340: Introduction to Indian Philosophy – 4 units

     

    Electives* (Opt for 5 units)

    PHED 106a: Bodily Conditioning – 1 device

    PHED 110: Swimming – 1 unit

    PHED 118: Rest for Peak Overall performance – 2 units

    PHED 119: Introduction to Mindfulness – 2 units

    PHED 120b: Yoga B – 1 device

    PHED 122: Kundalini Yoga and Meditation – 1 unit

    PHED 123: Yoga Treatment – 2 models

    PHED 124: Walking for Exercise – 1 unit

    PHED 134: Hiking – 1 unit

    PHED 160: Strain Administration for Healthier Residing – 2 units

    PHED 163: Well being Coaching – 3 units

    PHED 299: Yoga and Meditation Immersion in Tulum, Mexico – 2 units

    * Maximum 4 PHED activity models authorized at USC. Minor courses PHED 118, 119, 123, 160, 163 are exempt from this rule.

     

    Studying Targets:

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    1. Examine the interconnectedness of human body and intellect throughout disciplines for a comprehensive approach to psychological, bodily, social, and collective wellbeing.
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    3. Make and sustain a personal meditation apply, use aware respiration tactics, and utilize balanced residing methods to nutrition, exercise, sleep, and strain resilience.
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    5. Deepen self-awareness of alignment and human body mechanics for amplified toughness, harmony, and flexibility — and self-consciousness as a basis for psychological wellness and psychological literacy.
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    7. Investigate what it indicates to practice contentment, resilience, consent, and wellbeing, recognizing diverse bodies, identities, views, and sociocultural encounters.
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    9. Implement mindful recognition in each day life, which includes as it relates to:
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      1. final decision generating and trouble solving.
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      3. interpersonal associations and communication.
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      5. job-readiness, time administration, intention placing, and exploring what it means to have a conscious and purposeful partnership with technologies.
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