J Shanghai Jiaotong Univ Sci ›› 2022, Vol. 27 ›› Issue (2): 144-152.doi: 10.1007/s12204-021-2391-4
• Medicine-Engineering Interdisciplinary Research • Previous Articles Next Articles
WU Xiaojun1 (吴萧俊), DU Jiang1(杜江), JIANG Haifeng1 (江海峰), ZHAO Min1,2,3 (赵敏)
Received:
2021-03-08
Online:
2022-03-28
Published:
2022-05-02
CLC Number:
WU Xiaojun (吴萧俊), DU Jiang (杜江), JIANG Haifeng (江海峰), ZHAO Min (赵敏). Application of Digital Medicine in Addiction[J]. J Shanghai Jiaotong Univ Sci, 2022, 27(2): 144-152.
[12] | KMIEC J, SUFFOLETTO B. Implementations of a text-message intervention to increase linkage from the emergency department to outpatient treatment for substance use disorders [J]. Journal of Substance Abuse Treatment, 2019, 100: 39-44. |
[1] | WHO. World Drug Report 2020 [EB/OL]. [2021-03-08]. https://wdr.unodc.org/wdr2020/index.html. |
[13] | YANG Y S, RYU G W, CHOI M. Methodological strategies for ecological momentary assessment to evaluate mood and stress in adult patients using mobile phones: Systematic review [J]. JMIR MHealth and UHealth, 2019, 7(4): e11215. |
[2] | HUANG Y Q, WANG Y, WANG H, et al. Prevalence of mental disorders in China: A cross-sectional epidemiological study [J]. The Lancet Psychiatry, 2019,6(3): 211-224. |
[14] | LUKASIEWICZ M, FARENG M, BENYAMINA A, et al. Ecological momentary assessment in addiction [J].Expert Review of Neurotherapeutics, 2007, 7(8): 939-950. |
[3] | WHO. WHO Guideline: Recommendations on digital interventions for health system strengthening [EB/OL]. [2021-03-08]. https://www.who.int/reproductivehealth/publications/digital-interventions-health-system-strengthening. |
[15] | SCOTT C K, DENNISML, GUSTAFSON D H. Using ecological momentary assessments to predict relapse after adult substance use treatment [J]. Addictive Behaviors,2018, 82: 72-78. |
[4] | MARSCH L A, CAMPBELL A, CAMPBELL C, et al. The application of digital health to the assessment and treatment of substance use disorders: The past,current, and future role of the National Drug Abuse Treatment Clinical Trials Network [J]. Journal of Substance Abuse Treatment, 2020, 112: 4-11. |
[16] | SERRE F, FATSEAS M, DENIS C, et al. Predictors of craving and substance use among patients with alcohol,tobacco, cannabis or opiate addictions: Commonalities and specificities across substances [J]. Addictive Behaviors, 2018, 83: 123-129. |
[5] | QURESHI O, ENDALE T, RYAN G, et al. Barriers and drivers to service delivery in global mental health projects [J]. International Journal of Mental Health Systems, 2021, 15(1): 14. |
[6] | China Internet Network Information Center. The 47th Statistical Report on China’s Internet Development [EB/OL]. [2021-03-08]. http://www.cnnic.net.cn/hlwfzyj/hlwxzbg/hlwtjbg/202102/t20210203 71361.htm (in Chinese). |
[17] | COOPER M R, CASE K R, H′EBERT E T, et al.Characterizing ENDS use in young adults with ecological momentary assessment: Results from a pilot study[J]. Addictive Behaviors, 2019, 91: 30-36. |
[7] | GUINART D, DE FILIPPIS R, ROSSON S, et al. Development and validation of a computerized adaptive assessment tool for discrimination and measurement of psychotic symptoms [J]. Schizophrenia Bulletin, 2021,47(3): 644-652. |
[18] | SINGH N B, BJ¨ORLING E A. A review of EMA assessment period reporting for mood variables in substance use research: Expanding existing EMA guidelines [J]. Addictive Behaviors, 2019, 94: 133-146. |
[8] | KUMAR P C, CLELAND C M, GOUREVITCH M N,et al. Accuracy of the Audio Computer Assisted Self Interview version of the Alcohol, Smoking and Substance Involvement Screening Test (ACASI ASSIST) for identifying unhealthy substance use and substance use disorders in primary care patients [J]. Drug and Alcohol Dependence, 2016, 165: 38-44. |
[19] | BERTZ J W, EPSTEIN D H, PRESTON K L. Combining ecological momentary assessment with objective,ambulatory measures of behavior and physiology in substance-use research [J]. Addictive Behaviors,2018, 83: 5-17. |
[9] | SCHWARTZ R P,MCNEELY J, WU L T, et al. Identifying substance misuse in primary care: TAPS Tool compared to the WHO ASSIST [J]. Journal of Substance Abuse Treatment, 2017, 76: 69-76. |
[20] | AMINIKHANGHAHI S, SCHMITTEREDGECOMBE M, COOK D J. Context-aware delivery of ecological momentary assessment [J]. IEEE Journal of Biomedical and Health Informatics, 2020,24(4): 1206-1214. |
[10] | GIBBONS R D, ALEGRIA M, MARKLE S, et al. Development of a computerized adaptive substance use disorder scale for screening and measurement: The CAT-SUD [J]. Addiction, 2020, 115(7): 1382-1394. |
[21] | HSU M, AHERN D K, SUZUKI J. Digital phenotyping to enhance substance use treatment during the COVID-19 pandemic [J]. JMIR Mental Health, 2020,7(10): e21814. |
[11] | HO J, FONG C K, ISKANDER A, et al. Digital psychosocial assessment: An efficient and effective screening tool [J]. Journal of Paediatrics and Child Health,2020, 56(4): 521-531. |
[22] | BERGMAN B G, WU W Y, MARSCH L A, et al. Associations between substance use and instagram participation to inform social network-based screening models: Multimodal cross-sectional study [J]. Journal of Medical Internet Research, 2020, 22(9): e21916. |
[12] | KMIEC J, SUFFOLETTO B. Implementations of a text-message intervention to increase linkage from the emergency department to outpatient treatment for substance use disorders [J]. Journal of Substance Abuse Treatment, 2019, 100: 39-44. |
[23] | CARREIRO S, CHAI P R, CAREY J, et al. mHealth for the detection and intervention in adolescent and young adult substance use disorder [J]. Current Addiction Reports, 2018, 5(2): 110-119. |
[13] | YANG Y S, RYU G W, CHOI M. Methodological strategies for ecological momentary assessment to evaluate mood and stress in adult patients using mobile phones: Systematic review [J]. JMIR MHealth and UHealth, 2019, 7(4): e11215. |
[24] | CARREIROS, WITTBOLD K, INDIC P, et al. Wearable biosensors to detect physiologic change during opioid use [J]. Journal of Medical Toxicology, 2016, 12(3): 255-262. |
[14] | LUKASIEWICZ M, FARENG M, BENYAMINA A, et al. Ecological momentary assessment in addiction [J].Expert Review of Neurotherapeutics, 2007, 7(8): 939-950. |
[25] | ROBERTS W, MCKEE S A. Mobile alcohol biosensors and pharmacotherapy development research [J].Alcohol, 2019, 81: 149-160. |
[26] | BANDAWAR M, NARASIMHA V L, CHAND P. Use of digital technology in addiction disorders [J]. Indian Journal of Psychiatry, 2018, 60(suppl 4): S534-S540. |
[15] | SCOTT C K, DENNISML, GUSTAFSON D H. Using ecological momentary assessments to predict relapse after adult substance use treatment [J]. Addictive Behaviors,2018, 82: 72-78. |
[27] | COCHRAN G, STITZER M, CAMPBELL A N C, et al. Web-based treatment for substance use disorders: Differential effects by primary substance [J]. Addictive Behaviors, 2015, 45: 191-194. |
[16] | SERRE F, FATSEAS M, DENIS C, et al. Predictors of craving and substance use among patients with alcohol,tobacco, cannabis or opiate addictions: Commonalities and specificities across substances [J]. Addictive Behaviors, 2018, 83: 123-129. |
[17] | COOPER M R, CASE K R, H′EBERT E T, et al.Characterizing ENDS use in young adults with ecological momentary assessment: Results from a pilot study[J]. Addictive Behaviors, 2019, 91: 30-36. |
[28] | KILUK B D, NICH C, BUCK M B, et al. Randomized clinical trial of computerized and clinician-delivered CBT in comparison with standard outpatient treatment for substance use disorders: Primary with intreatment and follow-up outcomes [J]. The American Journal of Psychiatry, 2018, 175(9): 853-863. |
[29] | KAZEMI D M, BORSARI B, LEVINE M J, et al.A systematic review of the mHealth interventions to prevent alcohol and substance abuse [J]. Journal of Health Communication, 2017, 22(5): 413-432. |
[18] | SINGH N B, BJ¨ORLING E A. A review of EMA assessment period reporting for mood variables in substance use research: Expanding existing EMA guidelines [J]. Addictive Behaviors, 2019, 94: 133-146. |
[30] | BUDNEY A J, BORODOVSKY J T, MARSCH L A,et al. Technological innovations in addiction treatment[M]//The assessment and treatment of addiction. Amsterdam: Elsevier, 2019: 75-90. |
[19] | BERTZ J W, EPSTEIN D H, PRESTON K L. Combining ecological momentary assessment with objective,ambulatory measures of behavior and physiology in substance-use research [J]. Addictive Behaviors,2018, 83: 5-17. |
[20] | AMINIKHANGHAHI S, SCHMITTEREDGECOMBE M, COOK D J. Context-aware delivery of ecological momentary assessment [J]. IEEE Journal of Biomedical and Health Informatics, 2020,24(4): 1206-1214. |
[31] | MARICICH Y A, BICKEL W K, MARSCH L A, et al. Safety and efficacy of a prescription digital therapeutic as an adjunct to buprenorphine for treatment of opioid use disorder [J]. Current Medical Research and Opinion, 2021, 37(2): 167-173. |
[21] | HSU M, AHERN D K, SUZUKI J. Digital phenotyping to enhance substance use treatment during the COVID-19 pandemic [J]. JMIR Mental Health, 2020,7(10): e21814. |
[32] | VAIDYAM A N, WISNIEWSKI H, HALAMKA J D,et al. Chatbots and conversational agents in mental health: A review of the psychiatric landscape [J].Canadian Journal of Psychiatry Revue Canadienne DePsychiatrie, 2019, 64(7): 456-464. |
[33] | GRAHAM S, DEPP C, LEE E E, et al. Artificial intelligence for mental health and mental illnesses:An overview [J]. Current Psychiatry Reports, 2019,21(11): 1-18. |
[22] | BERGMAN B G, WU W Y, MARSCH L A, et al. Associations between substance use and instagram participation to inform social network-based screening models: Multimodal cross-sectional study [J]. Journal of Medical Internet Research, 2020, 22(9): e21916. |
[23] | CARREIRO S, CHAI P R, CAREY J, et al. mHealth for the detection and intervention in adolescent and young adult substance use disorder [J]. Current Addiction Reports, 2018, 5(2): 110-119. |
[34] | ALMUSHARRAF F, ROSE J, SELBY P. Engaging unmotivated smokers to move toward quitting: Design of motivational interviewing-based chatbot through iterative interactions [J]. Journal of Medical Internet Research,2020, 22(11): e20251. |
[24] | CARREIROS, WITTBOLD K, INDIC P, et al. Wearable biosensors to detect physiologic change during opioid use [J]. Journal of Medical Toxicology, 2016, 12(3): 255-262. |
[35] | FITZPATRICK K K, DARCY A, VIERHILE M. Delivering cognitive behavior therapy to young adults with symptoms of depression and anxiety using a fully automated conversational agent (Woebot): A randomized controlled trial [J]. JMIR Mental Health, 2017,4(2): e19. |
[36] | PROCHASKA J J, VOGEL E A, CHIENG A, et al. A therapeutic relational agent for reducing problematic substance use (Woebot): Development and usability study [J]. Journal of Medical Internet Research, 2021,23(3): e24850. |
[25] | ROBERTS W, MCKEE S A. Mobile alcohol biosensors and pharmacotherapy development research [J].Alcohol, 2019, 81: 149-160. |
[37] | ROLLAND B, D’HONDT F, MONT`EGUE S, et al.A patient-tailored evidence-based approach for developing early neuropsychological training programs in addiction settings [J]. Neuropsychology Review, 2019,29(1): 103-115. |
[26] | BANDAWAR M, NARASIMHA V L, CHAND P. Use of digital technology in addiction disorders [J]. Indian Journal of Psychiatry, 2018, 60(suppl 4): S534-S540. |
[27] | COCHRAN G, STITZER M, CAMPBELL A N C, et al. Web-based treatment for substance use disorders: Differential effects by primary substance [J]. Addictive Behaviors, 2015, 45: 191-194. |
[38] | BOFFO M, ZERHOUNI O, GRONAU Q F, et al. Cognitive bias modification for behavior change in alcohol and smoking addiction: Bayesian meta-analysis of individual participant data [J]. Neuropsychology Review,2019, 29(1): 52-78. |
[28] | KILUK B D, NICH C, BUCK M B, et al. Randomized clinical trial of computerized and clinician-delivered CBT in comparison with standard outpatient treatment for substance use disorders: Primary with intreatment and follow-up outcomes [J]. The American Journal of Psychiatry, 2018, 175(9): 853-863. |
[39] | WITTEKIND C E, L¨UDECKE D, CLUDIUS B. Webbased Approach Bias Modification in smokers: A randomized-controlled study [J]. Behaviour Research and Therapy, 2019, 116: 52-60. |
[29] | KAZEMI D M, BORSARI B, LEVINE M J, et al.A systematic review of the mHealth interventions to prevent alcohol and substance abuse [J]. Journal of Health Communication, 2017, 22(5): 413-432. |
[30] | BUDNEY A J, BORODOVSKY J T, MARSCH L A,et al. Technological innovations in addiction treatment[M]//The assessment and treatment of addiction. Amsterdam: Elsevier, 2019: 75-90. |
[31] | MARICICH Y A, BICKEL W K, MARSCH L A, et al. Safety and efficacy of a prescription digital therapeutic as an adjunct to buprenorphine for treatment of opioid use disorder [J]. Current Medical Research and Opinion, 2021, 37(2): 167-173. |
[32] | VAIDYAM A N, WISNIEWSKI H, HALAMKA J D,et al. Chatbots and conversational agents in mental health: A review of the psychiatric landscape [J].Canadian Journal of Psychiatry Revue Canadienne DePsychiatrie, 2019, 64(7): 456-464. |
[40] | WEN S, LARSEN H, BOFFO M, et al. Combining web-based attentional bias modification and approach bias modification as a self-help smoking intervention for adult smokers seeking online help: Double-blind randomized controlled trial [J]. JMIR Mental Health,2020, 7(5): e16342. |
[33] | GRAHAM S, DEPP C, LEE E E, et al. Artificial intelligence for mental health and mental illnesses:An overview [J]. Current Psychiatry Reports, 2019,21(11): 1-18. |
[41] | ZHANG M, YING J, AMRON S B, et al. A smartphone attention bias app for individuals with addictive disorders: Feasibility and acceptability study [J].JMIR MHealth and UHealth, 2019, 7(9): e15465. |
[42] | ZHU Y, JIANG H, SU H, et al. A newly designed mobile-based computerized cognitive addiction therapy app for the improvement of cognition impairments and risk decision making in methamphetamine use disorder:Randomized controlled trial [J]. JMIR MHealth and UHealth, 2018, 6(6): e10292. |
[43] | BYRNE S P, HABER P, BAILLIE A, et al. Cue exposure therapy for alcohol use disorders: What can be learned from exposure therapy for anxiety disorders?[J]. Substance Use & Misuse, 2019, 54(12): 2053-2063. |
[34] | ALMUSHARRAF F, ROSE J, SELBY P. Engaging unmotivated smokers to move toward quitting: Design of motivational interviewing-based chatbot through iterative interactions [J]. Journal of Medical Internet Research,2020, 22(11): e20251. |
[35] | FITZPATRICK K K, DARCY A, VIERHILE M. Delivering cognitive behavior therapy to young adults with symptoms of depression and anxiety using a fully automated conversational agent (Woebot): A randomized controlled trial [J]. JMIR Mental Health, 2017,4(2): e19. |
[36] | PROCHASKA J J, VOGEL E A, CHIENG A, et al. A therapeutic relational agent for reducing problematic substance use (Woebot): Development and usability study [J]. Journal of Medical Internet Research, 2021,23(3): e24850. |
[37] | ROLLAND B, D’HONDT F, MONT`EGUE S, et al.A patient-tailored evidence-based approach for developing early neuropsychological training programs in addiction settings [J]. Neuropsychology Review, 2019,29(1): 103-115. |
[38] | BOFFO M, ZERHOUNI O, GRONAU Q F, et al. Cognitive bias modification for behavior change in alcohol and smoking addiction: Bayesian meta-analysis of individual participant data [J]. Neuropsychology Review,2019, 29(1): 52-78. |
[44] | GARRETT B, TAVERNER T, GROMALA D, et al.Virtual reality clinical research: Promises and challenges [J]. JMIR Serious Games, 2018, 6(4): e10839. |
[45] | SEGAWA T, BAUDRY T, BOURLA A, et al. Virtual reality (VR) in assessment and treatment of addictive disorders: A systematic review [J]. Frontiers in Neuroscience,2019, 13: 1409. |
[46] | TRAYLOR A C, PARRISH D E, COPP H L, et al.Using virtual reality to investigate complex and contextual cue reactivity in nicotine dependent problem drinkers [J]. Addictive Behaviors, 2011, 36(11): 1068-1075. |
[47] | SALADIN M E, BRADY K T, GRAAP K, et al. A preliminary report on the use of virtual reality technology to elicit craving and cue reactivity in cocaine dependent individuals [J]. Addictive Behaviors, 2006,31(10): 1881-1894. |
[48] | PERICOT-VALVERDE I, SECADES-VILLA R,GUTI′ ERREZ-MALDONADO J, et al. Effects of systematic cue exposure through virtual reality on cigarette craving [J]. Nicotine & Tobacco Research,2014, 16(11): 1470-1477. |
[49] | METCALF M, ROSSIE K, STOKES K, et al. Virtual reality cue refusal video game for alcohol and cigarette recovery support: Summative study [J]. JMIR Serious Games, 2018, 6(2): e7. |
[50] | FERRERI F, BOURLA A, MOUCHABAC S, et al.E-addictology: An overview of new technologies for assessing and intervening in addictive behaviors [J].Frontiers in Psychiatry, 2018, 9: 51. |
[51] | TAN H Y, CHEN T Z, DU J, et al. Drug-related virtual reality cue reactivity is associated with gamma activity in reward and executive control circuit in methamphetamine use disorders [J]. Archives of Medical Research,2019, 50(8): 509-517. |
[52] | REMMERSWAAL D, JONGERLING J, JANSEN P J, et al. Impaired subjective self-control in alcohol use:An ecological momentary assessment study [J]. Drug and Alcohol Dependence, 2019, 204: 107479. |
[39] | WITTEKIND C E, L¨UDECKE D, CLUDIUS B. Webbased Approach Bias Modification in smokers: A randomized-controlled study [J]. Behaviour Research and Therapy, 2019, 116: 52-60. |
[53] | CARREIRO S, CHINTHA K K, SHRESTHA S, et al.Wearable sensor-based detection of stress and craving in patients during treatment for substance use disorder: A mixed methods pilot study [J]. Drug and Alcohol Dependence, 2020, 209: 107929. |
[40] | WEN S, LARSEN H, BOFFO M, et al. Combining web-based attentional bias modification and approach bias modification as a self-help smoking intervention for adult smokers seeking online help: Double-blind randomized controlled trial [J]. JMIR Mental Health,2020, 7(5): e16342. |
[54] | WANG Z, CHEN S, CHEN J, et al. A communitybased addiction rehabilitation electronic system to improve treatment outcomes in drug abusers: Protocol for a randomized controlled trial [J]. Frontiers in Psychiatry,2018, 9: 556. |
[41] | ZHANG M, YING J, AMRON S B, et al. A smartphone attention bias app for individuals with addictive disorders: Feasibility and acceptability study [J].JMIR MHealth and UHealth, 2019, 7(9): e15465. |
[55] | STEVENSON B L, BLEVINS C E, MARSH E, et al.An ecological momentary assessment of mood, coping and alcohol use among emerging adults in psychiatric treatment [J]. The American Journal of Drug and Alcohol Abuse, 2020, 46(5): 651-658. |
[42] | ZHU Y, JIANG H, SU H, et al. A newly designed mobile-based computerized cognitive addiction therapy app for the improvement of cognition impairments and risk decision making in methamphetamine use disorder:Randomized controlled trial [J]. JMIR MHealth and UHealth, 2018, 6(6): e10292. |
[56] | SCOTT C K, DENNIS M L, JOHNSON K A, et al. A randomized clinical trial of smartphone self-managed recovery support services [J]. Journal of Substance Abuse Treatment, 2020, 117: 108089. |
[43] | BYRNE S P, HABER P, BAILLIE A, et al. Cue exposure therapy for alcohol use disorders: What can be learned from exposure therapy for anxiety disorders?[J]. Substance Use & Misuse, 2019, 54(12): 2053-2063. |
[57] | CHAPMAN C, CHAMPION K E, BIRRELL L, et al. Smartphone apps about crystal methamphetamine (“ice”): Systematic search in app stores and assessment of composition and quality [J]. JMIR MHealth and UHealth, 2018, 6(11): e10442. |
[44] | GARRETT B, TAVERNER T, GROMALA D, et al.Virtual reality clinical research: Promises and challenges [J]. JMIR Serious Games, 2018, 6(4): e10839. |
[58] | CHE Z, ST SAUVER J, LIU H, et al. Deep learning solutions for classifying patients on opioid use [J]. AMIA Annual Symposium Proceedings, 2017, 2017: 525-534. |
[45] | SEGAWA T, BAUDRY T, BOURLA A, et al. Virtual reality (VR) in assessment and treatment of addictive disorders: A systematic review [J]. Frontiers in Neuroscience,2019, 13: 1409. |
[59] | JONES A, REMMERSWAAL D, VERVEER I, et al. Compliance with ecological momentary assessment protocols in substance users: A meta-analysis [J]. Addiction,2019, 114(4): 609-619. |
[46] | TRAYLOR A C, PARRISH D E, COPP H L, et al.Using virtual reality to investigate complex and contextual cue reactivity in nicotine dependent problem drinkers [J]. Addictive Behaviors, 2011, 36(11): 1068-1075. |
[60] | ZHANG M, YING J, SONG G, et al. Attention and cognitive bias modification apps: Review of the literature and of commercially available apps [J]. JMIR MHealth and UHealth, 2018, 6(5): e10034. |
[47] | SALADIN M E, BRADY K T, GRAAP K, et al. A preliminary report on the use of virtual reality technology to elicit craving and cue reactivity in cocaine dependent individuals [J]. Addictive Behaviors, 2006,31(10): 1881-1894. |
[61] | FU Z, BURGER H, ARJADI R, et al. Effectiveness of digital psychological interventions for mental health problems in low-income and middle-income countries: A systematic review and meta-analysis [J]. The Lancet Psychiatry, 2020, 7(10): 851-864. |
[48] | PERICOT-VALVERDE I, SECADES-VILLA R,GUTI′ ERREZ-MALDONADO J, et al. Effects of systematic cue exposure through virtual reality on cigarette craving [J]. Nicotine & Tobacco Research,2014, 16(11): 1470-1477. |
[49] | METCALF M, ROSSIE K, STOKES K, et al. Virtual reality cue refusal video game for alcohol and cigarette recovery support: Summative study [J]. JMIR Serious Games, 2018, 6(2): e7. |
[50] | FERRERI F, BOURLA A, MOUCHABAC S, et al.E-addictology: An overview of new technologies for assessing and intervening in addictive behaviors [J].Frontiers in Psychiatry, 2018, 9: 51. |
[51] | TAN H Y, CHEN T Z, DU J, et al. Drug-related virtual reality cue reactivity is associated with gamma activity in reward and executive control circuit in methamphetamine use disorders [J]. Archives of Medical Research,2019, 50(8): 509-517. |
[52] | REMMERSWAAL D, JONGERLING J, JANSEN P J, et al. Impaired subjective self-control in alcohol use:An ecological momentary assessment study [J]. Drug and Alcohol Dependence, 2019, 204: 107479. |
[53] | CARREIRO S, CHINTHA K K, SHRESTHA S, et al.Wearable sensor-based detection of stress and craving in patients during treatment for substance use disorder: A mixed methods pilot study [J]. Drug and Alcohol Dependence, 2020, 209: 107929. |
[54] | WANG Z, CHEN S, CHEN J, et al. A communitybased addiction rehabilitation electronic system to improve treatment outcomes in drug abusers: Protocol for a randomized controlled trial [J]. Frontiers in Psychiatry,2018, 9: 556. |
[55] | STEVENSON B L, BLEVINS C E, MARSH E, et al.An ecological momentary assessment of mood, coping and alcohol use among emerging adults in psychiatric treatment [J]. The American Journal of Drug and Alcohol Abuse, 2020, 46(5): 651-658. |
[56] | SCOTT C K, DENNIS M L, JOHNSON K A, et al. A randomized clinical trial of smartphone self-managed recovery support services [J]. Journal of Substance Abuse Treatment, 2020, 117: 108089. |
[57] | CHAPMAN C, CHAMPION K E, BIRRELL L, et al. Smartphone apps about crystal methamphetamine (“ice”): Systematic search in app stores and assessment of composition and quality [J]. JMIR MHealth and UHealth, 2018, 6(11): e10442. |
[58] | CHE Z, ST SAUVER J, LIU H, et al. Deep learning solutions for classifying patients on opioid use [J]. AMIA Annual Symposium Proceedings, 2017, 2017: 525-534. |
[59] | JONES A, REMMERSWAAL D, VERVEER I, et al. Compliance with ecological momentary assessment protocols in substance users: A meta-analysis [J]. Addiction,2019, 114(4): 609-619. |
[60] | ZHANG M, YING J, SONG G, et al. Attention and cognitive bias modification apps: Review of the literature and of commercially available apps [J]. JMIR MHealth and UHealth, 2018, 6(5): e10034. |
[61] | FU Z, BURGER H, ARJADI R, et al. Effectiveness of digital psychological interventions for mental health problems in low-income and middle-income countries: A systematic review and meta-analysis [J]. The Lancet Psychiatry, 2020, 7(10): 851-864. |
[1] | FU Jiawei∗ (傅家威), ZHAO Xu (赵 旭). Action-aware Encoder-Decoder Network for Pedestrian Trajectory Prediction [J]. J Shanghai Jiaotong Univ Sci, 2023, 28(1): 20-27. |
[2] | ZHANG Yilun1‡ (张轶伦), XU Sikun2‡ (徐思坤), XU Jie1 (徐 捷), ZENG Xueqi3 (曾学奇), LI Zheng4 (李 铮), XIE Chi5∗ (谢 驰). Robust Charging Demand Prediction and Charging Network Planning for Heterogeneous Behavior of Electric Vehicles [J]. J Shanghai Jiaotong Univ Sci, 2023, 28(1): 136-149. |
[3] | XIAO Pengfei, NI He, JIN Jiashan. Sequential Prediction Method of Single Parameter for Thermal System Based on MWSA [J]. Journal of Shanghai Jiao Tong University, 2023, 57(1): 36-44. |
[4] | ZENG Guozhi, WEI Ziqing, YUE Bao, DING Yunxiao, ZHENG Chunyuan, ZHAI Xiaoqiang. Energy Consumption Prediction of Office Buildings Based on CNN-RNN Combined Model [J]. Journal of Shanghai Jiao Tong University, 2022, 56(9): 1256-1261. |
[5] | DUAN Hongyan, TANG Guoxin, SHENG Jie, CAO Mengjie, PEI Lei, TIAN Hongwei. A Novel Prediction Model for Fatigue Strength [J]. Journal of Shanghai Jiao Tong University, 2022, 56(6): 801-808. |
[6] | JIANG Junhao, CHEN Gang. Dynamic Model Predictive Control Method for Steering Control of Driving Robot [J]. Journal of Shanghai Jiao Tong University, 2022, 56(5): 594-603. |
[7] | WANG Ziyao, GUO Fengxiang, CHEN Li. Engine Emission Prediction Based on Extrapolated Gaussian Process Regression Method [J]. Journal of Shanghai Jiao Tong University, 2022, 56(5): 604-610. |
[8] | LU Guannan1 (卢冠男), WANG Mengling1∗ (王梦灵), FOX Tamara2, JIANG Peng3 (蒋 鹏), JIANG Fusong3 (蒋伏松). Novel Indicators for Adverse Glycemic Events Detection Analysis Based on Continuous Glucose Monitoring Neural Network Predictive Models [J]. J Shanghai Jiaotong Univ Sci, 2022, 27(4): 498-504. |
[9] | XU Yong, CAI Yunze, SONG Lin. Review of Research on Condition Assessment of Nuclear Power Plant Equipment Based on Data-Driven [J]. Journal of Shanghai Jiao Tong University, 2022, 56(3): 267-278. |
[10] | YUAN Xiaoqi (袁筱祺), ZHU Lelan (朱乐兰), XU Qiongfan(徐琼凡), GAO Wei (高玮). Risk Prediction Model of Gallbladder Disease in Shanghai Middle-Aged and Elderly People Based on Neural Networks [J]. J Shanghai Jiaotong Univ Sci, 2022, 27(2): 153-159. |
[11] | TIAN Ruocen, ZHANG Qingzhen, GUO Yunhe, CHENG Lin. Design of Reentry Guidance Law of Hypersonic Vehicle Based on No-Fly Zone Avoidance [J]. Air & Space Defense, 2022, 5(2): 65-74. |
[12] | CHEN Zhixin, WANG Yiping, YANG Yafeng, SU Jianjun, YANG Bin. Characteristics of Droplet Transmission in Buses in Different Air Supply Modes [J]. Journal of Shanghai Jiao Tong University, 2022, 56(11): 1532-1540. |
[13] | XIA Ming (夏明), XU Tianyi (徐天意), JIANG Hong∗ (姜虹). Progress and Perspective of Artificial Intelligence and Machine Learning of Prediction in Anesthesiology [J]. J Shanghai Jiaotong Univ Sci, 2022, 27(1): 112-120. |
[14] | SHEN Hui, LIU Shimin, XU Minjun, HUANG Delin, BAO Jingsong, ZHENG Xiaohu. Adaptive Transferring Method of Digital Twin Model for Machining Domain [J]. Journal of Shanghai Jiao Tong University, 2022, 56(1): 70-80. |
[15] | ZHANG Liang, QU Gang, LI Huixing, JIN Haochun. Research and Application of Key Technologies of Network Security Situation Awareness for Smart Grid Power Control Systems [J]. Journal of Shanghai Jiao Tong University, 2021, 55(S2): 103-109. |
Viewed | ||||||
Full text |
|
|||||
Abstract |
|
|||||