{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,12]],"date-time":"2026-06-12T07:37:53Z","timestamp":1781249873635,"version":"3.54.1"},"reference-count":56,"publisher":"Wiley","issue":"4","license":[{"start":{"date-parts":[[2026,4,10]],"date-time":"2026-04-10T00:00:00Z","timestamp":1775779200000},"content-version":"vor","delay-in-days":9,"URL":"http:\/\/creativecommons.org\/licenses\/by-nc\/4.0\/"},{"start":{"date-parts":[[2026,4,1]],"date-time":"2026-04-01T00:00:00Z","timestamp":1775001600000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/doi.wiley.com\/10.1002\/tdm_license_1.1"}],"content-domain":{"domain":["onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["Alcohol, Clinical and Experimental Research"],"published-print":{"date-parts":[[2026,4]]},"abstract":"<jats:title>ABSTRACT<\/jats:title>\n                  <jats:sec>\n                    <jats:title>Background<\/jats:title>\n                    <jats:p>The COVID\u201019 pandemic disrupted face\u2010to\u2010face alcohol and other drug (AOD) treatment services and prompted greater use of telehealth. This study measured the impact of COVID\u201019 on outpatient treatment episodes before, during, and after stay\u2010at\u2010home orders were introduced.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>This observational study used routinely collected data from community\u2010based non\u2010government AOD services in New South Wales (NSW), Australia across 4\u2009years (209 7\u2010day intervals from January 1, 2019\u2013January 2, 2023). Interrupted time\u2010series analyses with seasonal autoregressive integrated moving average (ARIMA) modeling estimated weekly changes in outpatient treatment episodes associated with stay\u2010at\u2010home (lockdown) orders, including (1) commencements, (2) planned cessations, and (3) unplanned cessations. Episode counts were also examined by gender (male, female), age group (&lt;\u200925\u2009years, 25\u201359\u2009years, \u2265\u200960\u2009years), principal drug of concern (alcohol, amphetamines, cannabinoids, opioids, and other), and location (metropolitan and non\u2010metropolitan).<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>\n                      There were no significant level or trend changes in the overall number of\n                      <jats:italic>episode commencements<\/jats:italic>\n                      (ARIMA (2,0,0)(1,0,0), lockdown one: \u03b2_level\u2009=\u2009\u2212814.85,\n                      <jats:italic>p<\/jats:italic>\n                      \u2009=\u20090.098; \u03b2_slope\u2009=\u200911.14,\n                      <jats:italic>p<\/jats:italic>\n                      \u2009=\u20090.127; lockdown two: \u03b2_level\u2009=\u2009317.3,\n                      <jats:italic>p<\/jats:italic>\n                      \u2009=\u20090.427; \u03b2_slope\u2009=\u2009\u22123.47,\n                      <jats:italic>p<\/jats:italic>\n                      \u2009=\u20090.237),\n                      <jats:italic>planned cessations<\/jats:italic>\n                      (ARIMA (1,0,0)(0,0,1), lockdown one: \u03b2_level\u2009=\u2009\u2212142.1,\n                      <jats:italic>p<\/jats:italic>\n                      \u2009=\u20090.66; \u03b2_slope\u2009=\u20091.16,\n                      <jats:italic>p<\/jats:italic>\n                      \u2009=\u20090.808; lockdown two: \u03b2_level\u2009=\u2009\u2212199.07,\n                      <jats:italic>p<\/jats:italic>\n                      \u2009=\u20090.432; \u03b2_slope\u2009=\u20090.18,\n                      <jats:italic>p<\/jats:italic>\n                      \u2009=\u20090.932), or\n                      <jats:italic>unplanned cessations<\/jats:italic>\n                      (ARIMA (1,0,0), lockdown one: \u03b2_level\u2009=\u2009\u221292.4,\n                      <jats:italic>p<\/jats:italic>\n                      \u2009=\u20090.717; \u03b2_slope\u2009=\u20091.4,\n                      <jats:italic>p<\/jats:italic>\n                      \u2009=\u20090.711; lockdown two: \u03b2_level\u2009=\u2009\u2212121.19,\n                      <jats:italic>p<\/jats:italic>\n                      \u2009=\u20090.563; \u03b2_slope\u2009=\u20090.53,\n                      <jats:italic>p<\/jats:italic>\n                      \u2009=\u20090.732) in outpatient non\u2010government AOD services at either lockdown. For subgroups, during lockdown one, commencements per week increased for metropolitan participants (ARIMA (1,0,0) \u03b2_level\u2009=\u2009\u2212725.12,\n                      <jats:italic>p<\/jats:italic>\n                      \u2009=\u20090.024; \u03b2_slope\u2009=\u200910.07,\n                      <jats:italic>p<\/jats:italic>\n                      \u2009=\u20090.035) and those with amphetamines (ARIMA(3,0,0)(1,0,0) \u03b2_level\u2009=\u2009\u2212338.44,\n                      <jats:italic>p<\/jats:italic>\n                      \u2009=\u20090.036; \u03b2_slope\u2009=\u20094.68,\n                      <jats:italic>p<\/jats:italic>\n                      \u2009=\u20090.05) as their principal drug of concern.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusions<\/jats:title>\n                    <jats:p>The introduction of COVID\u201019 lockdown measures did not appear to adversely impact the number of NSW non\u2010government AOD outpatient treatment episodes delivered nor the likelihood of unplanned dropout. Our findings illustrate the likely role of telehealth in sustaining (and for some groups, perhaps temporarily increasing) AOD service provision during the COVID\u201019 pandemic. This highlights the sector's resilience in sustaining care under challenging circumstances.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1111\/acer.70298","type":"journal-article","created":{"date-parts":[[2026,4,11]],"date-time":"2026-04-11T06:00:31Z","timestamp":1775887231000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["Using Routinely Collected Data From the Network of Alcohol and Other Drugs Agencies Database to Evaluate the Impact of\n                    <scp>COVID<\/scp>\n                    \u201019 Lockdowns on Trends in Service Delivery in Outpatient Non\u2010Government Alcohol and Other Drug Treatment Services"],"prefix":"10.1111","volume":"50","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-9031-2117","authenticated-orcid":false,"given":"Alison K.","family":"Beck","sequence":"first","affiliation":[{"name":"School of Psychology, Faculty of Arts, Social Sciences and Humanities University of 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