KNOWLEDGE AND ATTITUDES TOWARDS SMOKING AND PREGNANCY: A SURVEY OF PREGNANT WOMEN IN THE UK

Table of Contents

Chapter 1: Introduction……………………………………………………………………………………………………. 4

1.1 Research Background……………………………………………………………………………………………… 4

1.2 Research Problem…………………………………………………………………………………………………… 4

1.3 Theoretical Framework……………………………………………………………………………………………. 4

1.3 Aim and Objectives………………………………………………………………………………………………… 5

1.4 Research Questions………………………………………………………………………………………………… 5

1.5 The Scope of the Study…………………………………………………………………………………………… 5

1.6 Significance of the Study………………………………………………………………………………………… 6

1.7 Structure of the study……………………………………………………………………………………………… 6

Chapter 2: Literature Review……………………………………………………………………………………………. 7

2.1 Empirical Study……………………………………………………………………………………………………… 7

2.2 Theories and Models………………………………………………………………………………………………. 9

2.3 Literature gap………………………………………………………………………………………………………. 10

Chapter 3: Methodology………………………………………………………………………………………………… 11

3.1 Research Approach……………………………………………………………………………………………….. 11

3.2 Research Design…………………………………………………………………………………………………… 11

3.3 Research Philosophy……………………………………………………………………………………………… 12

3.4 Data Collection Methods………………………………………………………………………………………. 12

3.5 Data Sampling……………………………………………………………………………………………………… 13

3.6 Data Analysis Methods…………………………………………………………………………………………. 13

3.7 Validity and Reliability…………………………………………………………………………………………. 14

3.8 Ethical Considerations…………………………………………………………………………………………… 14

Chapter 4: Results and Discussion…………………………………………………………………………………… 16

4.1 Results………………………………………………………………………………………………………………… 16

4.2 Discussion of Results……………………………………………………………………………………………. 40

Chapter 5: Conclusion and Recommendations………………………………………………………………….. 41

5.1 Research Summary……………………………………………………………………………………………….. 41

5.2 Linking Results with Objectives…………………………………………………………………………….. 41

5.3 Future Scope………………………………………………………………………………………………………… 41

5.4 Recommendations………………………………………………………………………………………………… 42

References……………………………………………………………………………………………………………………. 43

Chapter 1: Introduction

1.1 Research Background

Smoking tobacco while pregnant is very bad for the health. It may cause miscarriage, low birth weight, and sudden infant death syndrome (SIDS). In the UK, around 10.4% of pregnant women still smoke, and this number is greater among women from poorer socio-economic backgrounds. Even while there are initiatives to raise awareness and programs to help people quit, many women still don’t know all the hazards or think that smoking once in a while isn’t that bad (Hamadneh et al., 2021). Stigma from society and mental health issues make it much harder to stop. Research indicates that awareness and perceptions around smoking differ according to age, educational attainment, and economic brackets (BMC Public Health, 2022). It is essential to comprehend these disparities for the formulation of targeted solutions. This research examines the perceptions of smoking dangers among pregnant women in the UK and analyses the correlation between their knowledge, attitudes, and demographic attributes.

1.2 Research Problem

Smoking while pregnant is still a big problem for public health in the UK. It may lead to bad things, including low birth weight, early delivery, and death of infants (McDaid et al., 2021). Even if there are national efforts, many pregnant women still smoke because they don’t know enough about it, they feel ashamed, and they have mental health issues (Bowker et al., 2021). There are differences in smoking rates based on age, education, and socio-economic status, which shows that not everyone has equal access to help quitting (Froggatt et al., 2021). Current therapies may inadequately address these varied demands. This research fills the gap by examining pregnant women’s knowledge and attitudes towards smoking and determining how demographic variables affect their perspectives and readiness to stop.

1.3 Theoretical Framework

This study is underpinned by two key behavioural theories: the Health Belief Model (HBM) and the Theory of Planned Behaviour (TPB). HBM explains how perceived susceptibility, severity, benefits, and barriers influence pregnant women’s decisions to stop smoking. TPB adds depth by examining how attitudes, subjective norms, and perceived behavioural control shape intentions and behaviours. Together, these models help interpret how knowledge, beliefs, and social influences affect smoking attitudes during pregnancy. They provide a structured lens to assess why some women quit while others continue despite risks, guiding the design of effective, theory-informed health interventions for maternal smoking cessation.

1.3 Aim and Objectives

The aim is to examine the knowledge and attitudes of pregnant women about smoking, as well as the impact of demographic variables on their beliefs and behaviours.

The following are the objectives:

●       To assess the level of knowledge pregnant women in the UK have regarding the health risks of smoking during pregnancy.

●       To examine the attitudes of pregnant women towards smoking during pregnancy, including beliefs and perceived social pressures.

●       To evaluate how demographic factors such as age, education, and socio-economic status influence knowledge and attitudes toward smoking during pregnancy.

1.4 Research Questions

●       What is the level of knowledge among pregnant women in the UK regarding the risks of smoking during pregnancy?

●       What are the prevailing attitudes of pregnant women towards smoking during pregnancy?

●       How do demographic factors such as age, education, and socio-economic status influence knowledge and attitudes towards smoking during pregnancy?

1.5 The Scope of the Study

This research focuses on pregnant women living in the United Kingdom to evaluate their knowledge and attitudes on smoking during pregnancy (Griffiths et al., 2022). It investigates the impact of demographic variables, including age, educational attainment, and socio-economic position, on perceptions. The data were gathered using an online survey that uses structured questioning. The results will facilitate the creation of more focused and effective smoking cessation programs within maternal healthcare facilities.

1.6 Significance of the Study

This research is important because it looks at a major public health issue: smoking during pregnancy. It also looks at how pregnant women in the UK feel and know about smoking. By pinpointing gaps in knowledge and analysing the impact of demographic variables, the study provides significant insights for enhancing smoking cessation programs (Hunter et al., 2021). The results may assist healthcare clinicians in formulating more focused, culturally attuned, and accessible treatments designed for certain high-risk populations. The research enhances academic literature by modifying and using the STAARK scale in a novel situation (Froggatt et al., 2021). Ultimately, this study supports national objectives to decrease mother smoking rates, enhance maternal and infant health outcomes, and guide policy choices that improve prenatal care and public health education initiatives.

1.7 Structure of the study

Chapter 1: Introduction: Outlines the research background, problem, aim, objectives, research questions, scope, and significance of the study.

Chapter 2: Literature Review: Reviews empirical studies, relevant theories (HBM and TPB), and identifies gaps in existing research on smoking during pregnancy.

Chapter 3: Methodology: Describes the research approach, philosophy, data collection methods, sampling technique, data analysis tools (SPSS), and ethical considerations.

Chapter 4: Results and Discussion: Presents and interprets quantitative data, including descriptive statistics, t-tests, regression, and correlation analyses.

Chapter 5: Conclusion and Recommendations: Summarises key findings, links results to objectives, outlines future research scope, and offers practical recommendations.

Chapter 2: Literature Review

2.1 Empirical Study

Health Risks of Smoking During Pregnancy

According to Tatton and Lloyd, (2023), smoking while pregnant greatly raises the chances of bad things happening to both the mother and the baby. Women who smoke while pregnant are 2.6 times more likely to have a baby too early and 4.1 times more likely to have a baby that is too tiny for their age. Smoking doubles the risk of low birth weight, and infants born to smokers weigh around 200 grammes less than babies delivered to non-smokers. In the UK, smoking while pregnant is thought to cause more than 5,000 miscarriages, 2,200 preterm births, and 300 fatalities during pregnancy or shortly after delivery each year (Thomson et al., 2022). Additionally, the chance of stillbirth rises by about 47%, and the risk of sudden infant death syndrome (SIDS) escalates three times in infants born to smokers. These numbers show how important it is to have successful smoking cessation programs for pregnant women to lower health risks and enhance the health of newborns.

Figure: Health Risks of Smoking During Pregnancy

(Source: Mdpi, 2023)

Knowledge and Misconceptions Among Pregnant Women

Many pregnant women know that smoking is bad for them, but they do not always realise exactly what it does to them. Recent polls in the UK found that over 77% of pregnant women who smoked knew that smoking was bad for them in general, but most could not identify particular dangers like having a baby too early or with birth abnormalities (Stacey et al., 2022). According to the research conducted by Stacey et al., (2022), in larger trials, just 42% to 57% of women could name possible effects, including miscarriage or SIDS, and fewer than 25% knew how smoking may affect foetal development. Women who did not know much about health or did not have much education were more likely to think that mild or occasional smoking was safe. These wrong ideas make people feel safe when they shouldn’t and make them less likely to want to quit. This lack of awareness is particularly bad for poor people, since tailored health education is frequently not available (Hunter et al., 2021). To fix misconceptions and promote healthy pregnancy habits, it is important to raise awareness via messages that are culturally appropriate and easy to grasp.

Figure: Knowledge and Misconceptions Among Pregnant Women

(Source: IoP, 2024)

Attitudes, Beliefs, and Social Influences

Pregnant women’s views on smoking are shaped by their ideas, the opinions of others, and their surroundings. A lot of pregnant women who smoke say they feel criticised, which makes them conceal their smoking (Griffiths et al., 2022). Only 79% of pregnant women who smoke supported initiatives to help them quit, whereas 90% of women who don’t smoke did (McDougall et al., 2021). Some women think that smoking in the first trimester or tiny quantities does not hurt, which is why they keep doing it. Pictures of newborns’ health problems have been demonstrated to make people feel things and make them more likely to stop. Women who live with a spouse or family member who smokes are also far more likely to keep smoking themselves. Social support is also important; those who have good support from family and healthcare professionals are more likely to quit smoking. To get pregnant women to use smoking cessation programs more, it’s important to understand and change these beliefs.

Impact of Demographic Factors on Smoking Behaviour

Age, education, wealth, and marital status are all important demographic characteristics that affect how pregnant women smoke. In the UK, the greatest rates of smoking during pregnancy are among women aged 18 to 24 (Broadfield et al., 2021). Compared to women with university degrees, women without formal education are more than twice as likely to smoke. Income is also important. Pregnant women from families who make less than £20,000 a year are three times more likely to smoke than those who make more than £40,000. Single moms are 1.8 times more likely to smoke than married women, and being unemployed makes it even more likely that they will smoke while pregnant (Bowker et al., 2021). There are significant differences between ethnic groupings, with White British women having a greater incidence than women from other ethnic groups. These trends show that we need more specific public health initiatives that take into account the demographics of pregnant women. This will allow for more personalised treatments and better use of resources in maternal care services.

2.2 Theories and Models

Health Belief Model (HBM)

The Health Belief Model (HBM) elucidates health behaviours by examining individual beliefs of sickness risk and the advantages of preventative measures. There are six main parts to it: perceived vulnerability, perceived severity, perceived advantages, perceived obstacles, signals to action, and self-efficacy (Lutman-White et al., 2024). HBM helps us understand why some women stop smoking while pregnant and others don’t. For example, moms who believe their infant is more likely to be hurt and that quitting will assist are more likely to cease smoking. Stress or not having enough support might make people less motivated; therefore, personalised interventions are necessary for changing behaviour.

Theory of Planned Behavior (TPB)

The Theory of Planned Behaviour (TPB) posits that individual intention to engage in a behaviour is influenced by attitudes, subjective norms, and perceived behavioural control. This framework elucidates the cognitive processes behind decision-making and behaviour regulation, emphasising the role of intention as a precursor to actual behaviour (Xia et al., 2021). It integrates several psychological constructs to predict and understand human actions within specific contexts, making it an important theory in social psychology and behavioural sciences.

Figure: Theory of Planned Behavior (TPB)

(Source: Springer, 2024)

2.3 Literature gap

Studies have investigated the health concerns associated with smoking during pregnancy and general smoking habits; however, there is a paucity of research explicitly addressing the interplay of knowledge, attitudes, and demographic variables among pregnant women in the UK (Almeida et al., 2022). Current research studies focus on either knowledge or conduct in isolation, often neglecting socio-economic inequities and psychological hurdles such as stigma and stress. Moreover, the majority of smoking programs are not customised according to educational attainment, age, or income, resulting in inequitable access and participation. There is also a paucity of current data utilising validated methods, such as the STAARK scale modified for smoking during pregnancy. This research addresses the deficiency by offering a concentrated examination of the interplay among these elements that affect smoking habits.

2.4 Hypothesis

H0 (Null Hypothesis): There is no significant relationship between pregnant women’s knowledge and attitudes towards smoking during pregnancy and their demographic factors such as age, education, and socio-economic status.

H1 (Alternative Hypothesis): There is a significant relationship between pregnant women’s knowledge and attitudes towards smoking during pregnancy and their demographic factors such as age, education, and socio-economic status.

Chapter 3: Methodology

3.1 Research Approach

This study used a quantitative research methodology, appropriate for analysing quantifiable factors such as knowledge levels and attitudes of pregnant women on smoking. A quantitative methodology facilitates objective analysis using numerical data to discern trends, correlations, and patterns. It also makes it easier to do statistical tests to see whether there are any links between demographic characteristics (such as age, education, and income) and smoking-related behaviours (Thomson et al., 2024). This method makes sure that all answers are consistent, can be repeated, and are reliable by employing structured surveys and closed-ended questions. The focus is on collecting data from a large sample to formulate broadly applicable findings. This corresponds with the study objective of pinpointing knowledge deficiencies and attitudinal disparities across different demographic groups. Qualitative approaches provide profound subjective insights, but the quantitative approach facilitates systematic comparison and measurement of results. It is perfect for helping evidence-based public health programs by giving a clear, data-driven picture of how pregnant women smoke.

3.2 Research Design

This study adopts a quantitative, cross-sectional survey design to examine the knowledge and attitudes of pregnant women in the UK regarding smoking. The design is appropriate for capturing data at a single point in time to identify patterns, correlations, and demographic influences. A structured online questionnaire was administered using non-probability convenience sampling, targeting pregnant women aged 18 and above through social media and maternity forums. The survey included closed-ended multiple-choice and Likert-scale questions adapted from the STAARK scale to ensure consistency and reliability. Attitudes were measured using ten Likert-scale items adapted from the STAARK scale, assessing beliefs, social influences, and perceived control regarding smoking. Knowledge was measured through ten multiple-choice questions covering health risks, second-hand smoke, quitting benefits, and safe practices during pregnancy, with correct answers scored to produce an overall knowledge score. This design enables generalisable findings and supports evidence-based recommendations to inform public health interventions for maternal smoking cessation.

3.3 Research Philosophy

The study is based on the positivist ideology, which says that the best way to learn is via objective observation and facts that can be measured. Positivism corresponds with the use of quantitative data to examine real-world phenomena, such as smoking during pregnancy. This concept supports the notion that social phenomena, including health practices, may be examined using scientific methodologies and statistical analysis (Kalamkarian et al., 2023). It dismisses subjective interpretation and concentrates on observable, factual evidence for concluding. In this research, positivism facilitates the collection of organised answers using surveys to evaluate particular hypotheses about knowledge, attitudes, and demographic effects. The researcher adopts a neutral and objective stance, guaranteeing that the results are only derived from participant data, free from any external influence. This perspective is especially pertinent to public health research, because dependable and generalisable data is crucial for formulating successful treatments (Thomson et al., 2022). Positivism serves as the basis for generating valid, repeatable, and policy-relevant outcomes in this research.

3.4 Data Collection Methods

An online cross-sectional survey using Qualtrics was used to gather data. The poll was sent out via social media sites like Facebook and Instagram, as well as via maternity support groups, parenting forums, and women’s health websites. The participants were pregnant women aged 18 and older living in the UK (Stacey et al., 2022). There were four key parts to the questionnaire: demographic information, knowledge regarding smoking during pregnancy, attitudes towards smoking, and general thoughts. Ten multiple-choice questions will test knowledge, and ten Likert-scale items based on the STAARK scale will test attitudes. Attitudes were assessed using a 10-item STAARK scale adaptation (McDougall et al., 2021), where higher scores indicate stronger anti-smoking attitudes; Cronbach’s α = 0.82. Knowledge was measured with 10 researcher-developed items; higher scores indicate greater awareness, with content validity confirmed by expert review. Before the survey is fully deployed, it will be checked to make sure it is clear and relevant (McDougall et al., 2021). This approach makes it possible to quickly gather data from a sample that is spread out across a wide area. It does not hurt anybody, does not cost anything, and keeps the participants’ identities secret. Online data collection is also a good fit for the target group since it is easy to use and accessible, especially for those who are pregnant and do not have a lot of time or mobility.

3.5 Data Sampling

This research used a non-probability convenience sampling method to enrol 99 pregnant women around the United Kingdom. Participants were chosen based on their availability and desire to engage, mostly via unpaid online outreach on platforms such as Facebook, Instagram, and parenting forums. The sample consisted of women aged 18 years or older who are now pregnant and proficient in English (Broadfield et al., 2021). Convenience sampling facilitates fast data collection and is suitable due to the study’s exploratory character and time limitations. This strategy may restrict generalisability, but it facilitates access to a varied demography for age, education, and socio-economic position. A sample size of 99 was deemed enough for discerning patterns and conducting statistical analyses, including chi-square tests and logistic regression, particularly when informed by power analysis. This sample size also took into consideration the possibility of people not responding or not completing their submissions, which makes sure that the data are useful and dependable for the study goals.

3.6 Data Analysis Methods

SPSS (Statistical Package for the Social Sciences) was used to analyse the data from the online survey. This is a sophisticated tool for both descriptive and inferential statistical analysis. First, the dataset will be cleaned and coded (Bowker et al., 2021). Then, frequency analysis and descriptive statistics (means, percentages, and standard deviations) were used to summarise demographic data, knowledge scores, and attitude scores.

T-tests were used for inferential analysis to evaluate the relationship between categorical demographic factors (e.g., education, income level) and knowledge or attitude levels. Moreover, logistic regression will be used to forecast the impact of demographic variables on the probability of possessing inadequate or enough information and on favourable or unfavourable attitudes about smoking during pregnancy.

To find out whether anything is statistically significant, the significance threshold will be set at p < 0.05 (Lutman-White et al., 2024). The research will also use Pearson’s correlation coefficient to look at any links between knowledge and attitude scores. Normality tests (Shapiro–Wilk) showed both attitude and knowledge scores were normally distributed; therefore, Pearson’s correlation was used. To make the results easier to understand and use, tables, bar charts, and cross-tabulations will be used to show the data. SPSS will make sure that data processing and statistical testing are accurate, consistent, and open, which makes it a good tool for drawing reliable findings in public health.

3.7 Validity and Reliability

To guarantee the credibility of results, the study employed techniques that increase validity and reliability throughout the research process. Content validity will be achieved by modifying items from the validated STAARK scale to suit the situation of smoking during pregnancy. This guarantees that the survey questions comprehensively reflect the constructs of interest, knowledge and attitudes (Xia et al., 2021). The questionnaire was tested with a small sample of pregnant women to make sure the questions are clear, unambiguous, and relevant, which will improve face validity.

Construct validity was bolstered by matching survey questions with theoretical frameworks, like the Health Belief Model (HBM) and the Theory of Planned Behaviour (TPB), which elucidate the influence of beliefs and social variables on health practices (Almeida et al., 2022). To measure reliability, Cronbach’s alpha in SPSS will be used to check the internal consistency of the Likert-scale attitude items. A score higher than 0.7 will be seen as acceptable, which means that the answers to questions on the same idea are consistent.

The research guarantees that the findings are both consistent and properly represent the participants’ viewpoints by employing a structured, pre-tested instrument and statistical validation. The adoption of standardised data analysis tools and clear protocols makes the results even more reliable.

3.8 Ethical Considerations

This research follows important ethical guidelines to preserve the rights, dignity, and privacy of the people who took part. Before collecting data, the appropriate institutional review board (IRB) will be asked for ethical permission. All participants read an on-screen  Participant Information Sheet (PIS) that explained what the research is about, how it worked, what risks there could be, and that they can choose to take part. Before taking the poll, people will have to provide their informed consent online (Thomson et al., 2024).

People were able to choose to participate or not, and they could skip any question or leave at any time before submitting their answers. Because the data was gathered without names, once it is sent in, it could not be tracked back or taken back. The survey did not ask for names, phone numbers, or any other information that may identify someone, so it was private and anonymous.

The subject of smoking during pregnancy may have induced emotional distress; hence, participants were informed that they may withdraw from the survey at any moment without penalty, by closing their browser. After the questionnaire, there were resources and connections to expert quitting help agencies like NHS Smokefree (Kalamkarian et al., 2023). The study team were the only ones who could access the data, which  was stored securely on password-protected platforms. The study adhered to the General Data ProtectionRegulation (GDPR) and all relevant ethical standards for health and behavioural research involving human subjects.

Chapter 4: Results and Discussion

4.1 Results

Introduction
This section presents results from the attitudes component of the survey, measured using ten Likert-scale items adapted from the STAARK scale (McEwen & West, 2010). These items assessed participants’ beliefs, perceptions, and social influences regarding smoking during pregnancy. Higher scores indicate stronger anti-smoking attitudes. Descriptive statistics for each item are provided to summarise the central tendency and variability of responses, offering an overview of general attitudes among the surveyed population.

Table: Demographic Influences on Knowledge and Attitude Scores

*Significant at p < 0.05

Frequency Tables

From 99 responses, 7.1% strongly disagreed, 19.2% disagreed, 12.1% were not sure, 21.2% agreed, and 40.4% strongly agreed. Percentages and valid percentages are identical, with cumulative percentages progressing from 7.1% to 100% by the strongly agree category, representing responses across all possible agreement levels for the statement.

In 99 cases, 35.4% strongly disagreed, 25.3% disagreed, 23.2% were not sure, 11.1% agreed, and 5.1% strongly agreed. Cumulative percentages increase from 35.4% to 100%, and percentages equal valid percentages. All five response categories were represented among participants for this statement in the attitudes section.

Out of 99 participants, 32.3% strongly disagreed, 25.3% disagreed, 17.2% were not sure, 16.2% agreed, and 9.1% strongly agreed. Cumulative percentages rise from 32.3% to 100%. Percentages and valid percentages are identical, with responses covering all five possible categories for the statement about smoking and stress.

Among 99 responses, 3.0% strongly disagreed, 14.1% disagreed, 18.2% were not sure, 38.4% agreed, and 26.3% strongly agreed. Percentages and valid percentages match, with cumulative percentages increasing from 3.0% to 100%. All categories from strongly disagree to strongly agree received responses from participants for this statement.

From 99 respondents, 11.1% strongly disagreed, 16.2% disagreed, 26.3% were not sure, 26.3% agreed, and 20.2% strongly agreed. Percentages and valid percentages are identical, with cumulative values rising from 11.1% to 100%. Responses spanned all possible options for the statement about confidence in quitting smoking.

Of 99 participants, 27.3% strongly disagreed, 24.2% disagreed, 16.2% were not sure, 20.2% agreed, and 12.1% strongly agreed. Percentages equal valid percentages, with cumulative values increasing from 27.3% to 100%. All five categories were selected by participants when responding to this statement regarding personal autonomy.

Among 99 cases, 4.0% strongly disagreed, 10.1% disagreed, 15.2% were not sure, 19.2% agreed, and 51.5% strongly agreed. Percentages and valid percentages match, with cumulative values progressing from 4.0% to 100%. Responses covered the full range of options for this statement about healthcare worker communication.

From 99 participants, 28.3% strongly disagreed, 16.2% disagreed, 22.2% were not sure, 22.2% agreed, and 11.1% strongly agreed. Valid and percentage values are identical, and cumulative percentages range from 28.3% to 100%, showing that all possible agreement categories were selected for this statement.

Out of 99 respondents, 18.2% strongly disagreed, 18.2% disagreed, 23.2% were not sure, 23.2% agreed, and 17.2% strongly agreed. Percentages equal valid percentages, and cumulative values increase from 18.2% to 100%. All five categories were represented in responses to this statement regarding social influence.

Among 99 cases, 14.1% strongly disagreed, 15.2% disagreed, 30.3% were not sure, 21.2% agreed, and 19.2% strongly agreed. Percentages and valid percentages match, with cumulative values rising from 14.1% to 100%. All response categories were used for this statement about perceived control.              

From 99 respondents, 39.4% chose “lower chance of miscarriage,” 56.6% selected “low birth weight,” and 4.0% chose “less stress.” Percentages equal valid percentages, with cumulative values progressing from 39.4% to 100%. All three provided options received responses from participants.

Out of 99 responses, 3.0% chose “it helps them breathe better,” 71.7% selected “it reduces oxygen supply,” 22.2% answered “it makes no difference,” and 3.0% chose “it improves brain growth.” Percentages equal valid percentages, with cumulative values increasing from 3.0% to 100%.

Among 99 participants, 5.1% chose “smoke from a BBQ,” 1.0% selected “smoke from another person’s cigarette,” and 93.9% answered “smoke from a car.” Percentages equal valid percentages, with cumulative percentages rising from 5.1% to 100% across the three categories.

From 99 responses, 48.5% selected “it helps with baby’s breathing and weight,” 19.2% chose “it makes the mother more tired,” 25.3% answered “it reduces appetite,” and 7.1% said “it doesn’t help.” Percentages equal valid percentages, with cumulative percentages rising from 48.5% to 100%.

Out of 99 valid responses, 2.0% selected “after the first three months,” 24.5% chose “in small amounts,” 18.4% answered “any time,” and 55.1% selected “never.” Percentages and valid percentages differ slightly due to one missing case. Cumulative percentages range from 2.0% to 100%.

Among 99 respondents, 1.0% selected “smoking more,” 80.8% chose “willpower and support,” 16.2% answered “eating sweets,” and 2.0% said “avoiding the topic.” Percentages equal valid percentages, and cumulative values increase from 1.0% to 100% across the four categories provided.

From 99 participants, 2.0% chose “999,” 80.8% selected “NHS Stop smoking services,” 9.1% answered “police line,” and 8.1% chose “none.” Percentages equal valid percentages, with cumulative percentages increasing from 2.0% to 100% across all four options listed.

Out of 99 responses, 2.0% chose “more energy,” 22.2% selected “less illness,” 72.7% answered “breathing problems,” and 3.0% chose “stronger bones.” Percentages equal valid percentages, and cumulative percentages progress from 2.0% to 100% across the four possible answer categories.

Among 99 respondents, 42.4% selected “right away,” 28.3% chose “after the baby is born,” 20.2% answered “after one year,” and 9.1% selected “it doesn’t help.” Percentages equal valid percentages, with cumulative percentages progressing from 42.4% to 100%.

From 99 responses, 3.0% chose “higher birth weight,” 31.3% selected “fewer headaches,” 64.6% answered “premature birth,” and 1.0% chose “better sleep.” Percentages equal valid percentages, and cumulative percentages increase from 3.0% to 100% across the four answer choices provided.

Regression Analysis

The regression analysis looks at the things that make people think “smoking while pregnant is bad for the baby.” The model indicates a moderate correlation (R = 0.598) and a R² of 0.358, which means that the chosen variables explain around 36% of the difference in this view. The model is statistically significant (F(5,93) = 10.357, p <.001), which means it fits well overall. The view that “quitting smoking helps your baby” is a strong and negative predictor of the dependent variable (B = -0.764, p < .001). This means that those who agree more with the advantages of quitting are also more likely to believe that smoking is bad for babies. Other predictors, such as “people judge pregnant women who smoke too much” (p = .075) and “smoking affects baby’s oxygen” (p = .304), were not statistically significant. This means that, even if demographic and attitudinal factors have a role, knowing about the advantages of quitting has the most effect on how people see the damage (Campbell et al., 2020).

T-Test

We used the one-sample t-test to see whether the average answers to important knowledge-based questions were significantly different from a test result of 0, which means that there was full disagreement or lack of information. With p-values less than 0.001, all five variables showed statistically significant findings, which means that the mean answers of the sample were considerably greater than zero (Grant et al., 2020). The statement “Smoking during pregnancy is bad for the baby” had a high mean of 3.69 (t(98) = 26.97, p <.001), which means that most people agreed with it. In the same way, “What does second-hand smoke mean?” gets a lot of hits. (M = 2.89), “What is one thing that helps most people quit?” (M = 2.19), “Babies born to smokers are more likely to have…” (M = 2.77), and “Smoking while pregnant raises the risk of…” (M = 2.64) all demonstrated that they were aware of or agreed with the results in a statistically meaningful way. These findings show that the people who answered the survey had a moderate to high degree of awareness about the harms of smoking and how to quit. The tiny standard errors and narrow confidence intervals show that all the participants gave the same answers. Overall, the t-test findings back up the idea that the pregnant women who were polled knew a lot more than the average person about the risks and effects of smoking while pregnant.

Correlation Among Variables

N = 99
Correlation Coefficient = Pearson’s r (two-tailed)
 p < 0.001 (**) indicates statistical significance.

The correlation analysis shows that there are strong links between important knowledge factors that have to do with smoking while pregnant. There was a moderate negative relationship between “How can quitting smoking help your baby?” and “When is it safe to smoke during pregnancy?” (r = -0.524, p < .001), which means that knowing more about the advantages of quitting smoking is linked to not using dangerous smoking methods. There was also a favourable link (r = 0.542, p <.001) between knowing how to stop and knowing that the advantages start “right away.” Also, the variable “Babies born to smokers are more likely to have…” has a positive relationship with “When is it safe to smoke…” (r = 0.473, p <.001), which shows that knowing the risks makes people less inclined to smoke. The links between quitting services were smaller but remained important in several circumstances, especially between knowing about the services and the advantages of quitting (r = 0.246, p = .007). These patterns show how information and beliefs are interrelated and how they affect how pregnant women think about smoking.

4.2 Discussion of Results

The results of this study provide us important information on what pregnant women in the UK know and think about smoking. The frequency findings reveal that most people firmly agree that smoking while pregnant is bad for the baby, yet a lot of people still have wrong ideas about it. For example, 16.2% said that smoking helps them deal with stress, and 16.2% said that it’s okay to smoke a little when pregnant. This shows that psychological and behavioural aspects still affect smoking behaviours (McDaid et al., 2021). The findings of the T-test show that the people who answered the survey had a lot more than zero awareness of important health hazards including low birth weight, breathing problems, and preterm delivery. But there is still a lot of misinformation regarding secondhand smoke, and many people do not know where it comes from.

Regression analysis showed that knowing the advantages of stopping smoking was a strong predictor of believing that smoking during pregnancy is bad for people (p <.001). This shows that knowing about the good things that may happen may make people more aware of the risks and help them quit. The correlation findings also revealed that women who knew the advantages of quitting were also less likely to engage in dangerous smoking practices. This suggests that diverse areas of knowledge are linked to each other (Froggatt et al., 2021).

But the statistics also show some holes. Almost a third of the people who took part were unsure whether they could stop, and more than 40% thought that benefits take time to show up. These regions of doubt are important places to make changes. The research backs up the need for personalised, demographically sensitive quitting plans that deal with emotional stress, clear up misunderstandings, and provide pregnant women accurate, helpful information to promote the health of both mothers and babies.

Chapter 5: Conclusion and Recommendations

5.1 Research Summary

This research looked at what pregnant women in the UK know and think about smoking, as well as how their demographics and cognitive abilities affect how they see it. An online survey with both knowledge-based and attitudinal questions was sent to 99 people using a quantitative method (Hunter et al., 2021). The findings showed that although many women know the harms of smoking while pregnant, there are still some misunderstandings and doubts, especially about secondhand smoke and the immediate advantages of stopping. Regression and correlation analysis showed that knowing the advantages of stopping smoking is a powerful predictor of knowing the risks of smoking. The results show how important it is to have targeted public health messages and support programs that take into account psychological, social, and demographic factors to help mothers stop smoking and improve the health of their babies.

5.2 Linking Results with Objectives

The research was able to meet all three goals. First, it looked at how much people knew about the hazards of smoking. It found that most people knew about major problems like low birth weight and early delivery, but there was still some uncertainty about secondhand smoke and when the benefits of quitting would start. Second, an examination of attitudes showed that even though many people were against smoking, emotional dependence and social pressures still affected behaviour. Lastly, there were clear demographic effects. For example, correlations revealed that knowing the advantages of quitting was connected to rejecting dangerous practices, with differences explained by education and perceived self-efficacy. These results show that just having information isn’t enough; attitudes and the situation are also important (Griffiths et al., 2022). Overall, the study makes a strong case for the need for tailored, multidimensional treatments that are in line with women’s real-life experiences and different degrees of awareness.

5.3 Future Scope

To make the results more generalisable, future studies should use larger and more diverse samples and look at more disparities across subgroups based on age, race, and degree of education. Using a mixed-methods approach might help us learn more about the emotional and cultural hurdles to quitting, particularly for those who are vulnerable or don’t get enough help. Longitudinal studies that look at how behaviour changes over time would also be helpful for figuring out how well-focused treatments and public health campaigns work (McCormack et al., 2022). Also, making the STAARK scale more adaptable and applicable for other cultures might make it easier to compare studies on maternal smoking throughout the world. Finally, using digital tools like smartphone applications for quitting smoking or AI-based chatbots might be a new way to help, particularly for younger or tech-savvy pregnant women. This should be looked into further in future research that focuses on interventions.

5.4 Recommendations

The following are the recommendations:

●       Enhance Public Health Messaging: Tailor smoking cessation campaigns to address common misconceptions, especially around second-hand smoke and the immediate benefits of quitting. Use culturally appropriate and easy-to-understand language.

●       Strengthen Antenatal Interventions: Train midwives and health workers to deliver consistent, non-judgmental advice during routine check-ups, incorporating the STAARK scale to assess knowledge and attitudes (BMC Public Health, 2022).
Develop Targeted Support Services: Design cessation programs that consider socio-economic and psychological barriers, offering emotional support, peer groups, and digital tools like mobile apps for stress management and quitting assistance.

●       Expand Research and Monitoring: Conduct longitudinal and mixed-method studies to evaluate long-term behavioural change and the impact of tailored interventions on reducing maternal smoking rates across diverse demographics.

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