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Xie A, Sun Y, Chen H, Li L, Liu P, Liao Y, Li Y. Altered dynamic functional connectivity of insular subdivisions among male cigarette smokers. Front Psychiatry 2024; 15:1353103. [PMID: 38827448 PMCID: PMC11140567 DOI: 10.3389/fpsyt.2024.1353103] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/09/2023] [Accepted: 05/06/2024] [Indexed: 06/04/2024] Open
Abstract
Background Insular subdivisions show distinct patterns of resting state functional connectivity with specific brain regions, each with different functional significance in chronic cigarette smokers. This study aimed to explore the altered dynamic functional connectivity (dFC) of distinct insular subdivisions in smokers. Methods Resting-state BOLD data of 31 smokers with nicotine dependence and 27 age-matched non-smokers were collected. Three bilateral insular regions of interest (dorsal, ventral, and posterior) were set as seeds for analyses. Sliding windows method was used to acquire the dFC metrics of different insular seeds. Support vector machine based on abnormal insular dFC was applied to classify smokers from non-smokers. Results We found that smokers showed lower dFC variance between the left ventral anterior insula and both the right superior parietal cortex and the left inferior parietal cortex, as well as greater dFC variance the right ventral anterior insula with the right middle cingulum cortex relative to non-smokers. Moreover, compared to non-smokers, it is found that smokers demonstrated altered dFC variance of the right dorsal insula and the right middle temporal gyrus. Correlation analysis showed the higher dFC between the right dorsal insula and the right middle temporal gyrus was associated with longer years of smoking. The altered insular subdivision dFC can classify smokers from non-smokers with an accuracy of 89.66%, a sensitivity of 96.30% and a specify of 83.87%. Conclusions Our findings highlighted the abnormal patterns of fluctuating connectivity of insular subdivision circuits in smokers and suggested that these abnormalities may play a significant role in the mechanisms underlying nicotine addiction and could potentially serve as a neural biomarker for addiction treatment.
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Affiliation(s)
- An Xie
- Department of Radiology, The First Affiliated Hospital of Soochow University, Suzhou, Jiangsu, China
- Department of Radiology, The People’s Hospital of Hunan Province (The First Affiliated Hospital of Hunan Normal University), Changsha, Hunan, China
- Center for Mind & Brain Sciences, Hunan Normal University, Changsha, Hunan, China
| | - Yunkai Sun
- Department of Psychiatry, Sir Run Shaw Hospital, School of Medicine, Zhejiang University, Hangzhou, Zhejiang, China
| | - Haobo Chen
- Department of Radiology, The People’s Hospital of Hunan Province (The First Affiliated Hospital of Hunan Normal University), Changsha, Hunan, China
- Center for Mind & Brain Sciences, Hunan Normal University, Changsha, Hunan, China
| | - Ling Li
- Department of Psychiatry, Sir Run Shaw Hospital, School of Medicine, Zhejiang University, Hangzhou, Zhejiang, China
| | - Peng Liu
- Department of Radiology, The People’s Hospital of Hunan Province (The First Affiliated Hospital of Hunan Normal University), Changsha, Hunan, China
- Center for Mind & Brain Sciences, Hunan Normal University, Changsha, Hunan, China
| | - Yanhui Liao
- Department of Radiology, The People’s Hospital of Hunan Province (The First Affiliated Hospital of Hunan Normal University), Changsha, Hunan, China
- Center for Mind & Brain Sciences, Hunan Normal University, Changsha, Hunan, China
- Department of Psychiatry, Sir Run Shaw Hospital, School of Medicine, Zhejiang University, Hangzhou, Zhejiang, China
| | - Yonggang Li
- Department of Radiology, The First Affiliated Hospital of Soochow University, Suzhou, Jiangsu, China
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Wu YS, Cheung YTD, Lee JJJ, Wong CKH, Ho SY, Li WHC, Yao Y, Lam TH, Wang MP. Effect of Adding Personalized Instant Messaging Apps to a Brief Smoking Cessation Model in Community Smokers in Hong Kong: Pragmatic Randomized Clinical Trial. J Med Internet Res 2024; 26:e44973. [PMID: 38739429 PMCID: PMC11130779 DOI: 10.2196/44973] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/11/2022] [Revised: 09/28/2023] [Accepted: 03/26/2024] [Indexed: 05/14/2024] Open
Abstract
BACKGROUND While text messaging has proven effective for smoking cessation (SC), engagement in the intervention remains suboptimal. OBJECTIVE This study aims to evaluate whether using more interactive and adaptive instant messaging (IM) apps on smartphones, which enable personalization and chatting with SC advisors, can enhance SC outcomes beyond the provision of brief SC advice and active referral (AR) to SC services. METHODS From December 2018 to November 2019, we proactively recruited 700 adult Chinese daily cigarette users in Hong Kong. Participants were randomized in a 1:1 ratio. At baseline, all participants received face-to-face brief advice on SC. Additionally, they were introduced to local SC services and assisted in selecting one. The intervention group received an additional 26 personalized regular messages and access to interactive chatting through IM apps for 3 months. The regular messages aimed to enhance self-efficacy, social support, and behavioral capacity for quitting, as well as to clarify outcome expectations related to cessation. We developed 3 sets of messages tailored to the planned quit date (within 30 days, 60 days, and undecided). Participants in the intervention group could initiate chatting with SC advisors on IM themselves or through prompts from regular messages or proactive inquiries from SC advisors. The control group received 26 SMS text messages focusing on general health. The primary outcomes were smoking abstinence validated by carbon monoxide levels of <4 parts per million at 6 and 12 months after the start of the intervention. RESULTS Of the participants, 505/700 (72.1%) were male, and 450/648 (69.4%) were aged 40 or above. Planning to quit within 30 days was reported by 500/648 (77.2%) participants, with fewer intervention group members (124/332, 37.3%) reporting previous quit attempts compared with the control group (152/335, 45.4%; P=.04). At the 6- and 12-month follow-ups (with retention rates of 456/700, 65.1%, and 446/700, 63.7%, respectively), validated abstinence rates were comparable between the intervention (14/350, 4.0%, and 19/350, 5.4%) and control (11/350, 3.1% and 21/350, 6.0%) groups. Compared with the control group, the intervention group reported greater utilization of SC services at 12 months (RR 1.26, 95% CI 1.01-1.56). Within the intervention group, engaging in chat sessions with SC advisors predicted better validated abstinence at 6 months (RR 3.29, 95% CI 1.13-9.63) and any use of SC services (RR 1.66, 95% CI 1.14-2.43 at 6 months; RR 1.67, 95% CI 1.26-2.23 at 12 months). CONCLUSIONS An IM-based intervention, providing support and assistance alongside brief SC advice and AR, did not yield further increases in quitting rates but did encourage the utilization of SC services. Future research could explore whether enhanced SC service utilization leads to improved long-term SC outcomes. TRIAL REGISTRATION ClinicalTrials.gov NCT03800719; https://clinicaltrials.gov/ct2/show/NCT03800719.
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Affiliation(s)
- Yongda Socrates Wu
- School of Nursing, The University of Hong Kong, Hong Kong, China (Hong Kong)
- Children's Hospital of Eastern Ontario Research Institute, Ottawa, ON, Canada
| | | | - Jay Jung Jae Lee
- School of Nursing, The University of Hong Kong, Hong Kong, China (Hong Kong)
| | - Carlos King Ho Wong
- Department of Family Medicine and Primary Care, The University of Hong Kong, Hong Kong, China (Hong Kong)
| | - Sai Yin Ho
- School of Public Health, The University of Hong Kong, Hong Kong, China (Hong Kong)
| | - William Ho Cheung Li
- School of Nursing, The University of Hong Kong, Hong Kong, China (Hong Kong)
- Nethersole School of Nursing, The Chinese University of Hong Kong, Hong Kong, China (Hong Kong)
| | - Ying Yao
- School of Nursing, The University of Hong Kong, Hong Kong, China (Hong Kong)
| | - Tai Hing Lam
- School of Public Health, The University of Hong Kong, Hong Kong, China (Hong Kong)
| | - Man Ping Wang
- School of Nursing, The University of Hong Kong, Hong Kong, China (Hong Kong)
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Yang S, Yu B, Liao K, Qiao X, Fan Y, Li M, Hu Y, Chen J, Ye T, Cai C, Ma C, Pang T, Huang Z, Jia P, Reinhardt JD, Dou Q. Effectiveness of a socioecological model-guided, smart device-based, self-management-oriented lifestyle intervention in community residents: protocol for a cluster-randomized controlled trial. BMC Public Health 2024; 24:32. [PMID: 38166669 PMCID: PMC10763380 DOI: 10.1186/s12889-023-17073-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/06/2023] [Accepted: 10/26/2023] [Indexed: 01/05/2024] Open
Abstract
BACKGROUND Healthy lifestyles are crucial for preventing chronic diseases. Nonetheless, approximately 90% of Chinese community residents regularly engage in at least one unhealthy lifestyle. Mobile smart devices-based health interventions (mHealth) that incorporate theoretical frameworks regarding behavioral change in interaction with the environment may provide an appealing and cost-effective approach for promoting sustainable adaptations of healthier lifestyles. We designed a randomized controlled trial (RCT) to evaluate the effectiveness of a socioecological model-guided, smart device-based, and self-management-oriented lifestyles (3SLIFE) intervention, to promote healthy lifestyles among Chinese community residents. METHODS This two-arm, parallel, cluster-RCT with a 6-month intervention and 6-month follow-up period foresees to randomize a total of 20 communities/villages from 4 townships in a 1:1 ratio to either intervention or control. Within these communities, a total of at least 256 community residents will be enrolled. The experimental group will receive a multi-level intervention based on the socioecological model supplemented with a multi-dimensional empowerment approach. The control group will receive information only. The primary outcome is the reduction of modifiable unhealthy lifestyles at six months, including smoking, excess alcohol consumption, physical inactivity, unbalanced diet, and overweight/obesity. A reduction by one unhealthy behavior measured with the Healthy Lifestyle Index Score (HLIS) will be considered favorable. Secondary outcomes include reduction of specific unhealthy lifestyles at 3 months, 9 months, and 12 months, and mental health outcomes such as depression measured with PHQ-9, social outcomes such as social support measured with the modified Multidimensional Scale of Perceived Social Support, clinical outcomes such as obesity, and biomedical outcomes such as the development of gut microbiota. Data will be analyzed with mixed effects generalized linear models with family and link function determined by outcome distribution and accounting for clustering of participants in communities. DISCUSSION This study will provide evidence concerning the effect of a mHealth intervention that incorporates a behavioral change theoretical framework on cultivating and maintaining healthy lifestyles in community residents. The study will provide insights into research on and application of similar mHealth intervention strategies to promote healthy lifestyles in community populations and settings. TRIAL REGISTRATION NUMBER ChiCTR2300070575. Date of registration: April 17, 2023. https://www.chictr.org.cn/index.aspx .
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Affiliation(s)
- Shujuan Yang
- West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, 610041, China.
- Department of Health Management Center, Clinical Medical College & Affiliated Hospital, Chengdu University, Chengdu, 610106, China.
- Respiratory Department, Chengdu Seventh People's Hospital, Chengdu, 610021, China.
- International Institute of Spatial Lifecourse Epidemiology (ISLE), Wuhan University, Wuhan, China.
| | - Bin Yu
- West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, 610041, China
- Institute for Disaster Management and Reconstruction, Sichuan University, Chengdu, 610207, China
| | - Kai Liao
- Department of Radiology, West China Hospital, Sichuan University, Chengdu, 610041, China
- West China Tianfu Hospital, Sichuan University, Chengdu, 610200, China
| | - Xu Qiao
- West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, 610041, China
- Institute for Disaster Management and Reconstruction, Sichuan University, Chengdu, 610207, China
| | - Yunzhe Fan
- West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, 610041, China
| | - Ming Li
- West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, 610041, China
| | - Yuekong Hu
- West China Tianfu Hospital, Sichuan University, Chengdu, 610200, China
| | - Jiayan Chen
- School of Public Health & Jiangxi Provincial Key Laboratory of Preventive Medicine, Nanchang University, Nanchang, 330006, China
| | - Tingting Ye
- West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, 610041, China
| | - Changwei Cai
- West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, 610041, China
| | - Chunlan Ma
- West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, 610041, China
| | - Tong Pang
- West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, 610041, China
| | - Zixing Huang
- Department of Radiology, West China Hospital, Sichuan University, Chengdu, 610041, China
- West China Tianfu Hospital, Sichuan University, Chengdu, 610200, China
| | - Peng Jia
- International Institute of Spatial Lifecourse Epidemiology (ISLE), Wuhan University, Wuhan, China
- School of Resource and Environmental Sciences, Wuhan University, Wuhan, 430072, China
| | - Jan D Reinhardt
- Institute for Disaster Management and Reconstruction, Sichuan University, Chengdu, 610207, China.
- Department of Rehabilitation Medicine, Jiangsu Province Hospital/Nanjing Medical University First Affiliated Hospital, Nanjing, 210009, China.
- Swiss Paraplegic Research, 6207, Nottwil, Switzerland.
- Department of Health Sciences and Medicine, University of Lucerne, 6002, Lucerne, Switzerland.
| | - Qingyu Dou
- Department of Radiology, West China Hospital, Sichuan University, Chengdu, 610041, China.
- National Clinical Research Center of Geriatrics, Geriatric Medicine Center, West China Hospital, Sichuan University, Chengdu, 610041, China.
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