Evidence map›Paper›PMID 40474311›Full record

ArticleBMC psychology2025

A study on the effects of addiction level, stress, and social support of drug relapse patients on changes in motivation of quiting substance misuse behaviors.

Shiqi Liu, Tingran Zhang, Yi Yang, Kun Wang, Jiong Luo

Abstract read
In one paragraph

Article in BMC psychology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

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Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Review
4 · The record

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PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Shiqi LiuCollege of Physical Education, Southwest University, Chongqing, China.
Tingran ZhangCollege of Physical Education, Southwest University, Chongqing, China.
Yi YangCollege of Physical Education, Southwest University, Chongqing, China.
Kun WangCollege of Physical Education, Southwest University, Chongqing, China.
Jiong LuoCollege of Physical Education, Southwest University, Chongqing, China. 784682301@qq.com.

Funding

National Social Science Fund of China 22BTY064
6 · The paper itself

Abstract

objectiveTo understand the influencing factors of withdrawal motivation among drug Addictions during the period of forced withdrawal, reveal the mediating role of drug addiction level and stress perception in the relationship between social support and withdrawal motivation changes among drug Addictions, and further improve the theoretical system of compulsory drug withdrawal.

methodBased on extensive literature review, this study adopts a cross-sectional survey design. A structured questionnaire design was adopted to conduct a comprehensive survey on the basic information, degree of addiction, perceived stress, social support, and MQSMB. Descriptive analysis, correlation analysis, stepwise regression analysis, and structural equation modeling were used to process the obtained database.

results1) The standardized regression coefficient β indicates that among the background factors affecting the Changes In MQSMB, gender is the most important (β = 0.142*), marriage is the second most important (β = -0.127*), and active addiction cessation experience is the smallest (β = 0.117*); 2) Stepwise regression analysis showed that personal background, addiction level, social support, and perceived stress had predictive powers of 14.2%, 9.1%, 5.5%, and 7.7%, respectively, for changes in MQSMB; 3) Social support can significantly reduce the addiction level and stress perception of drug addicts. The degree of addiction not only plays an mediating role in the change of social support and MQSMB, but also assumes a chain mediating role through the combination of stress perception.

conclusionIn order to enhance the MQSMB, reduce relapse rates, and increase social support, it is crucial to adjust stress response appropriately and reduce psychological dependence on medication. addict.

Indexed as

Behavior, AddictiveMotivationSocial SupportStress, PsychologicalSubstance-Related DisordersAdultCross-Sectional StudiesFemaleHumansMaleMiddle AgedRecurrenceSurveys and QuestionnairesYoung AdultChanges motivationDrug addictionPressure perceptionRelapse rateSocial support

Identifiers

PMID40474311
PMCPMC12143050

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LicenceCC BY-NC-ND
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.