File Download
There are no files associated with this item.
Links for fulltext
(May Require Subscription)
- Publisher Website: 10.1016/j.psychres.2021.113773
- Scopus: eid_2-s2.0-85100265098
- PMID: 33545423
- WOS: WOS:000634552600035
- Find via
Supplementary
- Citations:
- Appears in Collections:
Article: Prospective prediction of PTSD and depressive symptoms during social unrest and COVID-19 using a brief online tool
Title | Prospective prediction of PTSD and depressive symptoms during social unrest and COVID-19 using a brief online tool |
---|---|
Authors | |
Keywords | PTSD symptoms Depressive symptoms Trauma exposure COVID-19 Mass screening |
Issue Date | 2021 |
Publisher | Elsevier Ireland Ltd. The Journal's web site is located at http://www.elsevier.com/locate/psychres |
Citation | Psychiatry Research, 2021, v. 298, p. article no. 113773 How to Cite? |
Abstract | Large-scale protracted population stressors, such as social unrest and the coronavirus disease 2019 (COVID-19), are associated with increased symptoms of post-traumatic stress disorder (PTSD) and depression. Cost-effective mental health screening is prerequisite for timely intervention. We developed an online tool to identify prospective predictors of PTSD and depressive symptoms in the context of co-occurring social unrest and COVID-19 in Hong Kong. 150 participants completed baseline and follow-up assessments, with a median duration of 29 days. Three logistic regression models were constructed to assess its discriminative power in predicting PTSD and depressive symptoms at one month. Receiver-operating characteristic analysis was performed for each model to determine their optimal decision thresholds. Sensitivity and specificity of the models were 87.1% and 53.8% for probable PTSD, 77.5% and 63.3% for high-risk depressive symptoms, and 44.7% and 96.4% for no significant depressive symptoms. The models performed well in discriminating outcomes (AUCs range: 0.769–0.811). Probable PTSD was predicted by social unrest-related traumatic events, high rumination, and low resilience. Rumination and resilience also predicted high-risk and no significant depressive symptoms, with COVID-19-related events also predicting no significant depression risk. Accessible screening of probable mental health outcomes with good predictive capability may be important for early intervention opportunities. |
Persistent Identifier | http://hdl.handle.net/10722/299783 |
ISSN | 2023 Impact Factor: 4.2 2023 SCImago Journal Rankings: 2.189 |
ISI Accession Number ID |
DC Field | Value | Language |
---|---|---|
dc.contributor.author | WONG, SMY | - |
dc.contributor.author | Hui, CLM | - |
dc.contributor.author | Wong, CSM | - |
dc.contributor.author | Suen, YN | - |
dc.contributor.author | Chan, SKW | - |
dc.contributor.author | Lee, EHM | - |
dc.contributor.author | Chang, WC | - |
dc.contributor.author | Chen, EYH | - |
dc.date.accessioned | 2021-05-26T03:28:59Z | - |
dc.date.available | 2021-05-26T03:28:59Z | - |
dc.date.issued | 2021 | - |
dc.identifier.citation | Psychiatry Research, 2021, v. 298, p. article no. 113773 | - |
dc.identifier.issn | 0165-1781 | - |
dc.identifier.uri | http://hdl.handle.net/10722/299783 | - |
dc.description.abstract | Large-scale protracted population stressors, such as social unrest and the coronavirus disease 2019 (COVID-19), are associated with increased symptoms of post-traumatic stress disorder (PTSD) and depression. Cost-effective mental health screening is prerequisite for timely intervention. We developed an online tool to identify prospective predictors of PTSD and depressive symptoms in the context of co-occurring social unrest and COVID-19 in Hong Kong. 150 participants completed baseline and follow-up assessments, with a median duration of 29 days. Three logistic regression models were constructed to assess its discriminative power in predicting PTSD and depressive symptoms at one month. Receiver-operating characteristic analysis was performed for each model to determine their optimal decision thresholds. Sensitivity and specificity of the models were 87.1% and 53.8% for probable PTSD, 77.5% and 63.3% for high-risk depressive symptoms, and 44.7% and 96.4% for no significant depressive symptoms. The models performed well in discriminating outcomes (AUCs range: 0.769–0.811). Probable PTSD was predicted by social unrest-related traumatic events, high rumination, and low resilience. Rumination and resilience also predicted high-risk and no significant depressive symptoms, with COVID-19-related events also predicting no significant depression risk. Accessible screening of probable mental health outcomes with good predictive capability may be important for early intervention opportunities. | - |
dc.language | eng | - |
dc.publisher | Elsevier Ireland Ltd. The Journal's web site is located at http://www.elsevier.com/locate/psychres | - |
dc.relation.ispartof | Psychiatry Research | - |
dc.subject | PTSD symptoms | - |
dc.subject | Depressive symptoms | - |
dc.subject | Trauma exposure | - |
dc.subject | COVID-19 | - |
dc.subject | Mass screening | - |
dc.title | Prospective prediction of PTSD and depressive symptoms during social unrest and COVID-19 using a brief online tool | - |
dc.type | Article | - |
dc.identifier.email | Hui, CLM: christyh@hku.hk | - |
dc.identifier.email | Wong, CSM: wongcsm@hku.hk | - |
dc.identifier.email | Suen, YN: suenyn@hku.hk | - |
dc.identifier.email | Chan, SKW: kwsherry@hku.hk | - |
dc.identifier.email | Lee, EHM: edwinlhm@hku.hk | - |
dc.identifier.email | Chang, WC: changwc@hku.hk | - |
dc.identifier.email | Chen, EYH: eyhchen@hku.hk | - |
dc.identifier.authority | Hui, CLM=rp01993 | - |
dc.identifier.authority | Wong, CSM=rp02625 | - |
dc.identifier.authority | Suen, YN=rp02481 | - |
dc.identifier.authority | Chan, SKW=rp00539 | - |
dc.identifier.authority | Lee, EHM=rp01575 | - |
dc.identifier.authority | Chang, WC=rp01465 | - |
dc.identifier.authority | Chen, EYH=rp00392 | - |
dc.description.nature | link_to_subscribed_fulltext | - |
dc.identifier.doi | 10.1016/j.psychres.2021.113773 | - |
dc.identifier.pmid | 33545423 | - |
dc.identifier.scopus | eid_2-s2.0-85100265098 | - |
dc.identifier.hkuros | 322502 | - |
dc.identifier.volume | 298 | - |
dc.identifier.spage | article no. 113773 | - |
dc.identifier.epage | article no. 113773 | - |
dc.identifier.isi | WOS:000634552600035 | - |
dc.publisher.place | Ireland | - |