Predictors of quitting support from nonsmoking mothers for smoking fathers : a cross-sectional study from Chinese pupils' families
© 2024. The Author(s)..
BACKGROUND: Quitting support from smokers' partners can predict quit attempts and smoking abstinence but research on factors that predict such support has been limited. To add more evidence for partner support and the improved interventions for smoking cessation, we analyzed some new potential predictors of quitting support from smokers' spouses.
METHOD: This cross-sectional study was conducted in in 2022 and 2023, selecting the students' families in which fathers smoked and mothers didn't smoke from grade 1-5 of 13 primary schools in Qingdao, China. Parents who met the criteria completed the online questionnaires and 1018 families were included in the analysis. We measured personal information related to smokers and their spouses such as age, education and nicotine dependence, and variables related to family and marital relationship such as family functioning, perceived responsiveness and power in decision-making of quitting smoking. Quitting support from smokers' spouses was measured by Partner Interaction Questionnaire and generalized linear model was used to explore the potential predictors of partner support.
RESULTS: In this study, the mean age of smokers was 39.97(SD = 5.57) and the mean age of smokers' spouses was 38.24(SD = 4.59). The regression analysis showed that for smokers and their spouses, the older age groups showed the lower ratio of positive/negative support(P < 0.05) and smokers with high education showed the less positive and negative partner support(P < 0.05). Nicotine dependence was positively associated with negative support (β = 0.120, P < 0.01), and perceived responsiveness (β = 0.124, P < 0.05) as well as family functioning (β = 0.059, P < 0.05) was positively associated with positive support. These three factors were associated with ratio of positive/negative support(P < 0.05). In addition, power of smoker's spouse in decision-making of quitting smoking was positively associated with the positive (β = 0.087, P < 0.001) and negative support (β = 0.084, P < 0.001).
CONCLUSIONS: Nicotine dependence, family functioning, power in decision-making of quitting smoking and perceived responsiveness were found to be the predictors of quitting support from smokers' spouses. By incorporating predictors of partner support and integrating some established theories that can improve family functioning and marital relationships, smoking cessation interventions can be further improved.
| Medienart: |
E-Artikel |
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| Erscheinungsjahr: |
2024 |
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| Erschienen: |
2024 |
| Enthalten in: |
Zur Gesamtaufnahme - volume:24 |
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| Enthalten in: |
BMC public health - 24(2024), 1 vom: 05. März, Seite 709 |
| Sprache: |
Englisch |
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| Beteiligte Personen: |
Jiang, Nan [VerfasserIn] |
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| Links: |
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| Themen: |
Family functioning |
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| Anmerkungen: |
Date Completed 07.03.2024 Date Revised 08.03.2024 published: Electronic Citation Status MEDLINE |
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| doi: |
10.1186/s12889-024-18217-2 |
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| funding: |
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| Förderinstitution / Projekttitel: |
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| PPN (Katalog-ID): |
NLM369337026 |
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| 245 | 1 | 0 | |a Predictors of quitting support from nonsmoking mothers for smoking fathers |b a cross-sectional study from Chinese pupils' families |
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| 520 | |a © 2024. The Author(s). | ||
| 520 | |a BACKGROUND: Quitting support from smokers' partners can predict quit attempts and smoking abstinence but research on factors that predict such support has been limited. To add more evidence for partner support and the improved interventions for smoking cessation, we analyzed some new potential predictors of quitting support from smokers' spouses | ||
| 520 | |a METHOD: This cross-sectional study was conducted in in 2022 and 2023, selecting the students' families in which fathers smoked and mothers didn't smoke from grade 1-5 of 13 primary schools in Qingdao, China. Parents who met the criteria completed the online questionnaires and 1018 families were included in the analysis. We measured personal information related to smokers and their spouses such as age, education and nicotine dependence, and variables related to family and marital relationship such as family functioning, perceived responsiveness and power in decision-making of quitting smoking. Quitting support from smokers' spouses was measured by Partner Interaction Questionnaire and generalized linear model was used to explore the potential predictors of partner support | ||
| 520 | |a RESULTS: In this study, the mean age of smokers was 39.97(SD = 5.57) and the mean age of smokers' spouses was 38.24(SD = 4.59). The regression analysis showed that for smokers and their spouses, the older age groups showed the lower ratio of positive/negative support(P < 0.05) and smokers with high education showed the less positive and negative partner support(P < 0.05). Nicotine dependence was positively associated with negative support (β = 0.120, P < 0.01), and perceived responsiveness (β = 0.124, P < 0.05) as well as family functioning (β = 0.059, P < 0.05) was positively associated with positive support. These three factors were associated with ratio of positive/negative support(P < 0.05). In addition, power of smoker's spouse in decision-making of quitting smoking was positively associated with the positive (β = 0.087, P < 0.001) and negative support (β = 0.084, P < 0.001) | ||
| 520 | |a CONCLUSIONS: Nicotine dependence, family functioning, power in decision-making of quitting smoking and perceived responsiveness were found to be the predictors of quitting support from smokers' spouses. By incorporating predictors of partner support and integrating some established theories that can improve family functioning and marital relationships, smoking cessation interventions can be further improved | ||
| 650 | 4 | |a Journal Article | |
| 650 | 4 | |a Family functioning | |
| 650 | 4 | |a Partner support | |
| 650 | 4 | |a Single-smoker couples | |
| 650 | 4 | |a Smoking cessation | |
| 700 | 1 | |a Huo, Ling-Ling |e verfasserin |4 aut | |
| 700 | 1 | |a Zhang, Zeng-Zhi |e verfasserin |4 aut | |
| 700 | 1 | |a Huang, Yi-Qing |e verfasserin |4 aut | |
| 700 | 1 | |a Li, Yu-Hua |e verfasserin |4 aut | |
| 700 | 1 | |a Wang, Rui |e verfasserin |4 aut | |
| 700 | 1 | |a Guo, Yi |e verfasserin |4 aut | |
| 700 | 1 | |a Qi, Fei |e verfasserin |4 aut | |
| 700 | 1 | |a Li, Shan-Peng |e verfasserin |4 aut | |
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