
==== Front
J Educ Health Promot
J Educ Health Promot
JEHP
J Edu Health Promot
Journal of Education and Health Promotion
2277-9531
2319-6440
Wolters Kluwer - Medknow India

JEHP-13-199
10.4103/jehp.jehp_4_24
Original Article
An interventional study to assess the impact of behavior modification therapy on motivation level for tobacco cessation among adult tobacco users in a resettlement colony of South Delhi
Gautam Richa
Alvi Yasir
Islam Farzana
Kumar Nitesh
Pathak Rambha 1
Agarwalla Rashmi 2
Panda Meely 3
Gupta Ekta 4
Parashar Mamta 5
Dayal Rashmi Prakash 6
Department of Community Medicine, Hamdard Institute of Medical Sciences and Research, New Delhi, India
1 Department of Community Medicine, Government Institute of Medical Sciences, Noida, Uttar Pradesh, India
2 Community and Family Medicine, All India Institute of Medical Sciences, Guwahati, Assam, India
3 Community and Family Medicine, All India Institute of Medical Sciences, Bibinagar, Hyderabad, Telangana, India
4 Scientist E, Indian Council of Medical Research, Division of Clinical Oncology, National Institute of Cancer Prevention and Research, Noida, Uttar Pradesh, India
5 Department of Community Medicine, Lady Hardinge Medical College New Delhi, India
6 Department of Psychiatry, Hamdard Institute of Medical Sciences and Research, New Delhi, India
Address for correspondence: Dr. Nitesh Kumar, Flat 204, B14-15 Maitri Apartment Nawada, Delhi - 110 059, India. E-mail: nitesh120390@gmail.com
2024
05 7 2024
13 19901 1 2024
06 3 2024
Copyright: © 2024 Journal of Education and Health Promotion
2024
https://creativecommons.org/licenses/by-nc-sa/4.0/ This is an open access journal, and articles are distributed under the terms of the Creative Commons Attribution-NonCommercial-ShareAlike 4.0 License, which allows others to remix, tweak, and build upon the work non-commercially, as long as appropriate credit is given and the new creations are licensed under the identical terms.
BACKGROUND:

Tobacco use remains a significant global health challenge, contributing to 8 million annual deaths and potentially reaching 1 billion deaths in the 21st century. Despite taking efforts like India’s National Tobacco Control Program, the country faces a persistent 39% tobacco use prevalence, particularly in low-income communities like those from Madanpur Khadar, Delhi. This study explores the effectiveness of behavior modification therapy in addressing this challenge.

MATERIALS AND METHODS:

In a community-based trial, 400 adult tobacco users from Madanpur Khadar were enrolled and randomization and allocation concealment were done (CTRI no.: CTRI/2021/06/034298). Participants were randomly assigned to intervention and control groups during the study period of 18 months. Data on sociodemographic characteristics, smoking behaviors, and motivation levels were collected. The intervention included behavior modification therapy, while the control group received brief advice. Motivation levels were assessed using the contemplation ladder, and carbon monoxide levels were measured with piCO + Smokerlyzer. The study adhered to ethical considerations and obtained approval from Jamia Hamdard’s Institutional Ethical Committee.

RESULTS:

Sociodemographic characteristics revealed a predominantly male (88%) population, aged above 30 years (68.5%), with lower middle class representation (51%). The intervention group exhibited a 7% smoking cessation rate, which is significantly higher than the control group (1%). piCO+ Smokerlyzer confirmed a 41.7% reduction in carbon monoxide levels among participants in the intervention group. High motivation levels correlated with successful quitting, with a 6.5 times higher odds ratio for highly motivated individuals compared to low or moderately motivated ones.

CONCLUSIONS:

The study highlights the cost-effective impact of behavior modification therapy in promoting tobacco cessation, particularly in resource-constrained settings. The significant association between motivation levels and quitting underscores the importance of tailored interventions in public health initiatives aimed at reducing tobacco use.

Behavior modification therapy
contemplation ladder
motivation level
Tobacco Cessation
piCO+
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pmcIntroduction

The World Health Organization (WHO) estimated 100 million premature deaths from tobacco use in the 20th century, with projections suggesting a potential 1 billion deaths in the 21st century. Tobacco use is a pressing global health issue and causes nearly 8 million annual deaths, which include 1.2 million deaths from second-hand smoke. Also, it was found that over 80% of the 1.3 billion global tobacco users reside in low- and middle-income countries and India is one of these countries. Despite the efforts taken by National Tobacco Control Program (NTCP), India faces challenges in reducing tobacco prevalence, with 39% of men and 4% of women aged 15–49 still using tobacco.[1,2], All forms of tobacco use are harmful, and there is no safe level of exposure to tobacco. Cigarette smoking is the most common form of tobacco use worldwide. Other tobacco products include waterpipe tobacco, cigars, cigarillos, heated tobacco, roll-your-own tobacco, pipe tobacco, bidis, and kreteks, and smokeless tobacco products.

The absence of cessation services may result in an additional 160 million global deaths among smokers by 2050. India’s intricate tobacco problem is influenced by diverse forms and cultural factors. All these not only complicate the cessation efforts, but also exacerbate the challenges related to nicotine addiction. In addition, it was observed that despite a majority (70%) of individuals expressing a desire to quit, only 3%–5% succeed in quitting tobacco. In an effort to improve tobacco cessation, WHO and the Ministry of Health established 19 tobacco cessation centers in India in 2002, implementing an algorithm which focused on assessing habits and providing advice, counseling, and pharmaceutical treatment to patients for tobacco cessation.

To quit tobacco in the first attempt is very difficult as it is a combination of behavioral cognitive and psychological phenomena. Still there is evidence that it is possible even in the first attempt through modification of personal behavior, which is one of the most effective interventions. Apart from modification of personal behavior, studies have suggested that tobacco cessation is one of the integral parts of tobacco control. There is a palpable need for cessation framework to break the constraints of health sector.[3,4]

Unassisted smoking cessation in India is very low unlike in the West. In India, tobacco users quit after they get some diseases. Therefore, it is all the more important that doctors and other health professionals address tobacco as a serious risk to public health. In India, tobacco cessation needs to be implemented in multiple settings. Incorporating tobacco cessation training in medical and other health professional education, training of health professionals to offer cessation advice in their routine health-care practice, and disease-specific counseling sessions in diabetes, tuberculosis, and other specialties are likely to result in significant quit rates among current tobacco users. Limited health professional training hampers tobacco cessation, but evidence supports the positive impact of behavior modification therapy. In India, a study done to assess the impact of behavior modification therapy on quitting and motivation in study participants of Delhi colony, with primary and secondary objectives focusing on percentage implementation and its impact on quitting tobacco have shown positive impact.[5]

Smoking results from nicotine addiction, activating nicotinic receptors in the brain’s reward system. The success of quitting is heavily influenced by the degree of addiction, with dependence extent and duration affecting withdrawal symptoms and relapse likelihood.[6] Understanding the process requires delving into human motivation for behavioral change, as evidenced by theories like the “transtheoretical model.” This model posits the stages precontemplation, contemplation, preparation, action, and maintenance, each requiring a specific motivation level for progression.[7,8] Health professionals’ limited training impedes tobacco interventions, but evidence supports motivation-focused behavior modification globally. Exploring the impact of behavior modification on community tobacco cessation, this study conducted in India considers demographic variations, smoking quantity, and tobacco policies in assessing quitting success. It emphasizes the pivotal role of tailored interventions based on the transtheoretical model’s behavioral stages.[9]

Novelty: Smoking cessation interventions have been shown to be an extremely cost-effective way of preserving life and reducing ill health. Community-based behavior modification therapies for tobacco cessation considered successful in other countries have not been tried and tested in Indian settings. There is a need for an effective smoking cessation service for low- and middle-income country settings, where the smoking rate is generally very high while a cessation service is not usually accessible. This study had two main objectives: the primary objective was to ascertain the percentage of adult tobacco users who successfully quit tobacco following behavior modification therapy in a Delhi resettlement colony and secondary objectives included implementing the therapy for tobacco cessation and evaluating its influence on both quitting rates and motivational levels.

Materials and Methods

Study design and setting: This was a community-based intervention trial conducted in a resettlement colony of Madanpur Khadar (which is also the field practice area of Rural Health Training Center under Department of Community Medicine, Hamdard Institute of Medical Sciences and Research, Delhi).

Study participants and sampling: Adult males and females (aged 18–65 years) who were smokers. Inclusion criteria: Adult males and females (aged 18–65 years)* smoking for the last ≥1 month and residing for the past 6 months in the study area and who gave consent to participate in the study were included. *(The study selected participants within the age range of 18–65 years. Individuals below 18 years were challenging to locate due to their nonavailability as they belonged to school and college going age group and their inclusion fell outside the study scope. Similarly, individuals aged 65 and above were not chosen due to their higher morbidity rates.) Exclusion criteria: Those who had received previous treatment for cessation of tobacco in the last 1 year or were suffering from any serious physical and/or mental illness were excluded. Those who did not give consent for participation in the study were excluded. Study duration: This study was done in a study period of 18 months.

The sample size was calculated using a smoking cessation rate of 25.6% and 11.3% (Aung MN et al.) in intervention and control arm with a power of 90% at 95% confidence interval (CI). Assuming a nonresponse rate of 10%, the total number of subjects was found to be 352, with 176 each in the intervention and control arms, which was rounded of to 200 study participants in each group [Figure 1].[10]

Figure 1 Procedure of the study

Data collections tools and technique

A self-designed pretested questionnaire collected sociodemographic data including age, sex, education, occupation, and family income. Socioeconomic status (SES) was determined using the modified Kuppuswamy scale (SES is evaluated by considering a family’s income, level of education, and occupation of the head of household).[11]

The contemplation ladder, a 10-point scale, measured motivation to quit smoking. Participants were categorized into highly motivated (score 8 or above), moderately motivated (score 5–7), and with low motivation (score less than 5).

Quitting behavior was assessed through self-reported questionnaires (which included history related to duration of smoking, smoking habits, motivating factors for smoking cessation, facilitators and barriers in tobacco cessation) and piCO+ Smokerlyzer®. It is a cheap and easy-to-use method and has been validated in tobacco control and prevention interventions in other countries. The piCO+ Smokerlyzer gives an accurate measure of expired carbon monoxide in breath.

piCO+ Smokerlyzer® is a breath carbon monoxide monitor intended for multipatient use. It measure the breath carbon monoxide in parts per million (ppm) and blood carboxyhaemoglobin in percentages (%COHb). The CO reading relates to gas in the lungs and on the breath. The cut-off point between smoker and non-smoker has been found to be 6ppm CO. The piCO+ Smokerlyzer® defines a non-smoker as 0-6ppm, a low-dependence smoker as 7-15ppm and strongly addicted smokers as over 15ppm.

Operational definitions

Ever users: Ever smoker was defined as the one who had not smoked/chewed tobacco in the past 30 days preceding the survey, but had tried in the past (even once or twice).

Current user: Current smoker was defined as the one who had smoked/chewed tobacco product on one or more days in the preceding month of the survey.

Levels of motivation: The contemplation ladder is a measure of readiness to quit smoking based on the stages of change model that characterizes readiness to change as a progression through precontemplation, contemplation, action, and maintenance phases [Table 1]. It has shown strong intercorrelations between different reporting formats (range Pearson’s r = 0.82–0.98).[11,12]

Table 1 Counseling based on stages of change

Stages of change	Patient’s response to feelings of quitting smoking	Goal of intervention	Typical physician thoughts and intervention	
Precontemplation	“I like to smoke”	Introduce ambivalence	“Your emphysema will improve after you have quit smoking”	
Contemplation	“I like to smoke but better if I quit”	Resolve ambivalence – “I know I need to quit”	“How will your life be after you have quit smoking?”	
Preparation	“I am ready to quit”	Identify successful strategies	“Choose a ‘quit day’ and let us make plans for it”	
Action	“I am not into smoking, but I still think about smoking from time to time	Provide solutions to specific relapse triggers	“How can you deal with your desire to smoke in those situations?”	
Maintenance	“I used to smoke”	Solidify patient’s commitment to a smoke-free life	“This would be a good time to share your experiences with other people”	

Precontemplation stage: A subject with no intention to quit smoking.

Contemplation stage: A subject with awareness that smoking is a problem, but with ambivalence about the perspective of changing, and hence has planned no quit date.

Preparation stage: A subject who has 6-month intention to quit smoking.

Action stage: A subject who has quit in the last 1 month or with 1-month intention to quit smoking.

Maintenance stage: A subject who has quit smoking for more than 1 month.

Ethical consideration

The study received ethical approval from Jamia Hamdard’s Institutional Ethical Committee. Participant confidentiality was rigorously upheld. Informed consent, privacy statements, and the voluntary nature of participation were communicated and documented. Data management adhered to Good Clinical Practice guidelines.

Results

The study was initiated with baseline survey during phase 1, in which a total of 400 study participants were enrolled and these participants were randomly allocated equally into intervention and control arms, that is, 200 in each group.

Sociodemographic characteristics of study participants

The study participants, in both intervention and control groups, were predominantly above 30 years old (68.5%), with mean ages of 40 ± 15.1 and 41 ± 14.8 years, respectively. Most participants followed Hinduism (85.7%), with 88% being male and 12% being female. Around 25% had a high school education or above, with a similar pattern observed in males (30%) and a majority of females (83%) being illiterate. About 83% of participants were married, 11.7% were unmarried, and 5% were separated or divorced. Occupation-wise, 71% were unskilled workers or unemployed, 22% were skilled workers, and 6.5% were involved in clerical, semi-professional, or professional occupations. The two study groups were balanced in mean age, education, occupation, and SES, but significant (P < 0.05) variations were observed in religion, gender, and marital status characteristics [Table 2].

Table 2 Comparison of sociodemographic and tobacco consumption characteristics between cases and controls

Sociodemographic characteristics	Totaln (%)	Control (n=200)	Case (n=200)	Statistic	P	
Age, mean (SD)		41	40	0.42	0.73	
  Religion		
    Hindu,n (%)	343 (85.8)	157 (46)	186 (54)	17	<0.001	
    Muslim,n (%)	56 (14)	42 (75)	14 (25)			
    Christian	1 (0.2)	1	0			
  Gender		
    Male,n (%)	351 (87.8)	188 (53)	163 (47)	14.5	<0.001	
    Female,n (%)	49 (12.2)	12 (24)	37 (76)			
Marital status		
    Married	332 (83)	175 (52)	157 (48)	9.2	<0.05	
    Unmarried	47 (11.8)	14 (29)	33 (71)			
    Separated/widow	21 (5.2)	11 (52)	10 (48)			
Education		
    Graduate or postgraduate	14 (3.5)	7 (3.5)	7 (3.5)	1.2	0.9	
    Intermediate/diploma	25 (6.3)	12 (6)	13 (6.5)			
    High school certificates	64 (16)	35 (17)	29 (15)			
    Primary school certificate	139 (34.8)	67 (34)	72 (36)			
    Illiterate	158 (39.6)	79 (40)	79 (40)			
Occupation		
    Profession	3 (0.8)	2 (1)	1 (0.5)	6.2	0.4	
    Semi-professional	7 (1.8)	4 (2)	3 (1.5)			
    Clerical	19 (4.8)	8 (4)	11 (5.5)			
    Skilled worker	88 (22)	42 (21)	46 (23)			
    Unskilled	185 (46.3)	103 (51.5)	82 (41)			
    Unemployed	98 (24.5)	41 (20.5)	57 (28.5)			
Socioeconomic status		
    Upper class	1 (0.3)	1 (0.5%)	0			
SD=standard deviation

Tobacco cessation among the study participants post-behavior modification therapy

Tobacco cessation was observed in 4% (16) of the participants at the end point of the study. In the intervention group, 7% (14) of the participants quit smoking after undergoing cognitive behavior therapy, which was higher than that of the control group, that is, 1% (2) [Table 3].

Table 3 Tobacco quitters in the case and control groups as per PiCO+ Smokerlyzer

Quit tobacco	Case (%)	Control (%)	
Yes	14 (7.0%)	2 (1.0%)	
No	186 (93.0%)	198 (99.0%)	
	χ2=9.3,P<0.002 (relative risk=7, CI 1.6–30.4)	
CI=confidence interval

This association was found to be statistically significant with an odds ratio of 7.45. The above findings were also validated using piCO+ Smokerlyzer during the end point of the study period, which depicted 41.7% reduction in piCO level among the participants who underwent cognitive behavior therapy. In the control group, only 10% reduction was observed as shown in Table 4.

Table 4 Tobacco cessation among the study participants

	piCO+ level in tobacco quitter	
	Case (mean±SD)	Control (mean±SD)	
Start of the study	7.9±4.1	9.5±0.7	
End of the study	4.6±3.5	8.5±0.7	
SD=standard deviation

Validity of tobacco cessation among the study group participants

Decrease in piCO level was found to be 41.7% among the cases who quit tobacco from the start of study till the end of the study.

Cutoff value of piCO was taken as 5 ppm to decide about the quitting rate of smokers.

At the end of the study, cases who quit tobacco were found to have a piCO level equal to or less than 5, which validates their quitting status, while in the control group, the piCO level among quitters was less than 8, which indicates biochemically the study subjects in control group did not quit smoking tobacco.

Nonsmoker = 0–6 ppm, a low-dependence smoker = 7–15 ppm, and strongly addicted smoker = >15 ppm.

Impact of behavior modification therapy on the motivation level: Behavior modification therapy was applied to all 200 cases, and tobacco users’ motivation levels were assessed using the contemplation ladder. Initially, more than half were highly motivated in both groups, but at the study end, the intervention group showed a 2% increase in quitting motivation, while the control group exhibited a 6% decline. The relative risk of high motivation in the intervention group compared to the control group increased from 2.05 to 2.22 by the study end and it was statistically significant as shown in Table 5.

Table 5 Overall motivation level among the study subjects during the study period

Motivation	Case (%)	Control (%)	Total (%)	
During the initiation of the study		
    Low	9 (4.5%)	28 (14%)	37 (9.2%)	
    Moderate	43 (21.5%)	100 (50%)	143 (35.8%)	
    High	148 (74%)	72 (36%)	220 (55%)	
		χ2=58.7,P<0.001		
High motivation/case–control		RR=2.056 (CI 1.6–2.52)		
During the end point of the study		
    Low	9 (4.5%)	37 (18.5%)	46 (11.5%)	
    Moderate	40 (20%)	95 (47.5%)	135 (33.8%)	
    High	151 (75.5%)	68 (34.0%)	219 (54.8%)	
		χ2=70.0,P<0.001		
High motivation/case–control		RR=2.22 (CI 1.8–2.7)		
CI=confidence interval, RR=relative risk

Among tobacco users who quit, the majority were highly motivated, with 6.5 times higher odds for quitting compared to low or moderate motivation. The relative risk of quitting in highly motivated cases versus controls was 5.85 (CI 0.8–43.8), indicating an increased quitting risk in the intervention group. In the control group, nearly half had moderate motivation, while the case group mostly had higher motivation, with approximately 90% of tobacco quitters from the case group, as seen in Table 6.

Table 6 Motivation level at the end of the study among the study subjects and their tobacco quitting status

Motivation level at the end of the study	Quit tobacco	
	Yes	No	Total	
Case		
   Low motivation	0	9 (4.8%)	9 (4.5%)	
   Moderate motivation	1 (7.1%)	39 (21%)	40 (20%)	
   High motivation	13 (92.9%)	138 (74.2%)	151 (75.5%)	
	χ2=2.4,P=0.12, OR (high motivation)=4.5	
   Control		
   Low motivation	1 (50%)	36 (18.2%)	37 (18.5%)	
   Moderate motivation	0	95 (48%)	95 (47.5%)	
   High motivation	1 (50%)	67 (33.8%)	68 (34%)	
	χ2=0.2,P=0.63, OR (high motivation)=1.95	
Relative risk of quitting in highly motivated participants of case/control group=5.85 (CI 0.8–43.8)	
CI=confidence interval, OR=odds ratio

Assessing nicotine dependence using the modified Fagerstrom scale revealed over half had moderate dependence and more than one third had minimal dependence [Table 7]. Among quitters, 81.3% had minimal dependence, while 58.3% of nonquitters had moderate dependence [Table 8]. I addition, 15% were in the precontemplation stage and 85% were in the contemplation stage.

Table 7 Modified Fagerstrom scale for nicotine dependence among intervention and control group participants

	Case (n=200)	Control (n=200)	Total	
Minimal dependence	73 (36.5)	69 (34.5)	142 (35.5)	
Moderate dependence	109 (54.5)	118 (59.0)	227 (56.8)	
Severe dependence	18 (9)	13 (6.5)	31 (7.8)	

Table 8 Modified Fagerstrom scale for nicotine dependence among quitters and control nonquitters

	Quitter	Nonquitter	Total	
Minimal dependence	13 (81.3)	129 (33.6)	142 (35.5)	
Moderate dependence	3 (18.8)	224 (58.3)	227 (56.8)	
Severe dependence	0	31 (8.1)	31 (7.8)	
	16	384	400	

Discussion

Advice given by the doctor during consultation is one of the cheap and simple methods of reaching a very large proportion of smokers. This acts as a tool to impart awareness and interest among the participants regarding the harmful effects of tobacco smoking. Another stage after generating awareness is to motivate. Motivation comes after self-evaluation about the benefits, which helps in decision-making. Conviction leads to action, adoption, or acceptance of the new idea. This new idea acts as the key in imparting behavioral changes.

Sociodemographic characteristics: Tobacco use is one of the major public health issues, and there is an urgent need to control this problem. In our study, around 400 study participants were enrolled. Majority of the study participants belonged to the age group of 18–45 years. Most of the study participants were found to be above 30 years of age (68.5%), with the mean age being 40 ± 15.1 and 41 ± 14.8 years, respectively, in the intervention and control groups. In a previous study conducted by Vivek Gupta et al.[13] at Ballabgarh, Haryana, India (2003–2004), it was observed that with increasing age, the proportion of tobacco usage increased consistently, reaching a peak of 71.8% among those aged 55–64 years. However, in our study, with increasing age, the proportion of tobacco smokers decreased. This finding could be due to difference in time and demographic variations. Gender-wise distribution showed that majority (88%) of the participants were males and few of them were females (12%). In addition, SES of the study subjects showed that more than half (51%) belonged to lower middle class. These findings are similar to those reported in previous studies conducted by Sharma et al.[14] at Bhopal in a labor colony and by Daoud N et al.[15] among Arabs. In addition, we observed in our study that nearly one-fourth of the study participants had a high school education or above, which is different from the results of previous studies (i.e., Sharma et al.).[14] This difference could be due to difference in the location of the study subjects.

Tobacco cessation among the study participants post-behavior modification therapy: The result of this study confirms the significant impact of setting a higher motivation level among smokers for quitting tobacco smoking. A quitting rate of 14% was observed in our study; however, this was less than the values reported in the studies conducted by Jamrozik et al. at Oxford, which reported a quitting rate of 21.2%, and by Daoud et al.[15] at London, which reported 19.1% as the quitting rate. But as these studies were conducted in 1980s, the trend toward stopping smoking was different in comparison to the present time. Also, none of the studies attempted any systematic validation of the patients.[9,16,17]

Stead L.F et al.[17] observed in their study additional behavioral support as an adjunct to pharmacotherapy for smoking cessation using Cochrane Database of Systematic Reviews. The objectives of their study were similar to those of our study, that is, to evaluate the effect of increasing the intensity of behavioral support for people using smoking cessation medications and to assess whether there are different effects depending on the type of pharmacotherapy or the amount of support in each condition. It was observed that the amount of behavioral support is likely to increase the chance of success in quitting tobacco smoking by about 10%–25%, based on a pooled estimate from 47 trials, which is comparable to our study in which an increase in the chance of success of quitting tobacco by 6% was observed among participants in the intervention group.[17]

Behavior modification therapy and impact of motivation level: In Gill et al.’s study,[18] 66% of 127 smokers were highly motivated to quit, in contrast with our intervention group in which 75.5% exhibited high motivation, while nearly one third in the control group were highly motivated to quit. Similarly Kumar et al.[19] revealed 15% in pre-contemplation and 85% in contemplation, with 16% abstaining after 6 months, akin to our findings.

On examining the NTCP, it was observed that a 21% smoking cessation rate after 6 months aligned with our 16% quit rate. Notably, in both studies, the majority of those quitting had low nicotine dependence (76% in NTCP and 81.1% in our study). Mishra et al. and Breslau et al. corroborated that higher Fagerstrom scores and nicotine dependence reduced quitting odds, akin to our observations with minimal dependence participants (81.3%).[20]

Ha and Choi et al.’s study indicated the experimental group had significantly higher change stages than the control group, while our study observed changes without significant differences, potentially due to varied study durations and participant demographics.[21] A noteworthy revelation in our study was that over two-thirds of participants smoked less than 10 cigarettes/bidis daily, paralleling Gill et al.’s mean of 6.12.[18] Moreover, both studies concurred on higher quitting odds for highly motivated individuals, with our study demonstrating 6.5 times higher odds for highly motivated participants compared to those with low or moderate motivation.

Conclusion

The study highlights the cost-effective impact of doctor consultations in creating awareness and motivation for tobacco cessation in a diverse group of participants from Madanpur Khadar. Despite variations in smoking patterns with age and education, the findings reveal a 14% quitting rate after behavior modification, underscoring the importance of behavioral support. Significant differences in motivation levels between the intervention and control groups emphasize the crucial role of motivation in successful quitting. The study aligns with previous research, emphasizing the significance of motivation, behavioral support, and minimal nicotine dependence for effective tobacco cessation, providing valuable insights for targeted public health initiatives.

Financial support and sponsorship

ICMR Funded Project RFC No. (P-32) SBHSR/Ad-hoc/5/2020-21, Dated 03/11/2020.

Conflicts of interest

There are no conflicts of interest.
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