Combined counseling based on the Fogg behavior model for managing weight gain in pregnant women: A randomized controlled trial protocol

Abstract

Appropriate weight gain during pregnancy is essential, as inappropriate weight gain (too much or too little) has complications for both mother and baby, and the ideal amount depends on the mother’s body mass index. Balanced nutrition and exercise are the main foundations of a healthy pregnancy, and counseling during this period is an opportunity to promote maternal and fetal health and reduce risks such as preterm birth, gestational diabetes, and hypertension caused by excessive weight gain. This study aims to evaluate the effect of a combined counseling intervention program based on the fogg behavioral model using mobile phone technology (whatsapp or eta) on total gestational weight gain and perinatal outcomes. A randomized controlled trial in qom, iran, will recruit pregnant women to develop a whatsapp platform for individualized, continuous pregnancy weight management services based on the fogg behavior model. All participants will be included in the full analysis set (fas), while the per-protocol set (pps) will consist of women who completed the intervention and provided all outcome data. This study highlights the effectiveness of consultations utilizing the fogg model in managing appropriate weight gain during pregnancy. If the findings confirm that the fogg model-based counseling promotes healthy weight gain in pregnant women, this approach could be implemented during pregnancy to effectively minimize instances of excessive or inadequate weight gain to significantly reduce cases of excessive or insufficient weight gain.

Introduction

Gestational weight gain (GWG) impacts both maternal and infant outcomes. Research indicates that abnormal gestational weight gain is associated with increased risks of gestational diabetes (up to 2.4-fold), cesarean delivery (about 1.5-fold higher), macrosomia (20–25% greater incidence), intrauterine growth restriction, preterm birth, and even perinatal mortality[1,2,3,4,5] (Jin). Moreover, abnormal GWG is significantly associated with a higher risk of postpartum depression, with one meta-analysis reporting an odds ratio (OR) of 1.29 (95% CI: 1.08–1.53) Qiu.[6]

In the United States, nearly half of women (48.6%) experience excessive gestational weight gain (EGWG), while only 31.5% achieve optimal weight gain, and about 20% gain insufficiently (Ukah).[3] In certain low-income nations, 74% of women experience inadequate weight gain, 15% optimal, and 10% excessive GWG.[7]

Iran is also grappling with this issue, as 35% of women are affected by EGWG.[8] Additionally, a previous study indicates that while over half of women (56.4%) consider GWG important, only 27.6% adhere to the recommended guidelines (Hollis).[9] Therefore, effectively managing weight gain and supporting pregnant women in maintaining appropriate GWG remains a significant global public health challenge.

Conventional approaches to managing weight gain during pregnancy typically involve in-person group health education sessions and personalized counseling provided by physicians, nutritionists, or midwives (Aung).[10] Interventions that provide continuous, personalized support for diet, exercise, and weight monitoring have been shown to effectively reduce obstetric complications and aid in weight management, with effect sizes ranging from Cohen’s d = 0.35 to 0.50 in randomized trials Liu.[11]

In Iran, approaches to weight management during pregnancy have evolved from collective methods, such as lectures and film screenings, to individualized services including personalized health education, lifestyle guidance, weight monitoring, and pregnancy progress tracking Banafshe.[12,13,14,15] Personalized approaches have been shown to reduce excessive gestational weight gain by 18–22% and improve birth outcomes; however, they present challenges due to the shortage of nurses and midwives.[16]

Furthermore, most studies predominantly focus on interventions initiated during mid- to late pregnancy, leaving the impact of early pregnancy interventions less explored. Evidence suggests that abnormal gestational weight gain during the first and second trimesters increases the risk of gestational diabetes by 1.8–2.2 times and gestational hypertension by 1.5 times.[17,18] Therefore, early intervention is critical in promoting healthy behaviors and empowering pregnant women to manage their weight, leading to appropriate gestational weight gain.[19,20]

Late-pregnancy weight control interventions in women near or above standard weight have shown limited effectiveness, with only 10–15% achieving recommended weight gain and heightened anxiety affecting both behavior and birth outcomes.[21,22]

Managing pregnancy weight gain with mobile health (mHealth) is a promising solution to address human resource challenges. With over 90% of pregnant women in urban Iran owning smartphones, mHealth enables greater access to specialized knowledge and facilitates the adoption of healthy behaviors. Mobile technologies in perinatal health services are fully developed, with mHealth applications now replacing traditional methods like text messaging and email services.[23,24,25] Several studies have highlighted the importance of theory-based interventions in promoting healthy behaviors among pregnant women. These studies have also demonstrated the effectiveness of electronic applications and devices in supporting weight management, reporting an average weight reduction of 1.2–1.8 kg during pregnancy compared to control groups. For instance, Hakimzadeh et al. (2025) showed that an intervention based on the Extended Parallel Process Model significantly improved physical activity among overweight pregnant women.[24,26,27,28,29,30]

Some researchers[31] have also focused on evaluating the feasibility and acceptability of social platforms like Instagram to address GWG interventions. While beneficial, app usage tends to decrease by 20–30% over time, and some pregnant women express doubts about information reliability.[32] Mobile wearable devices offer simplicity and portability, but their operating systems are still under development, and their effects on pregnant women remain unclear.

WhatsApp, widely used in Iran, has over 2 billion active accounts globally,[33] making it a highly promising platform for mHealth interventions. It enables instant communication via text, images, videos, and sound, bridging geographical gaps. Studies have shown that WeChat-based interventions improved maternal BMI by 0.8–1.1 kg/m² and reduced pregnancy complications by 12–15%.[13] WhatsApp and ETA have also been employed in health management research in Iran.[34,35,36]

Fogg’s behavioral model guided the intervention, enhancing its scientific rigor. Motivation, ability, and triggers are all addressed to initiate desired behavior.[37,38,39] Based on this model, a combined online (WhatsApp and ETA) and face-to-face intervention plan was developed, targeting motivation, ability, and arousal across different pregnancy stages.

Innovation of the Study

This study is innovative in several ways. First, it is among the few randomized controlled trials in Iran to apply the Fogg behavioral model as a theoretical framework for managing GWG. Unlike conventional interventions that often begin in mid- or late pregnancy, this program emphasizes early pregnancy counseling to maximize preventive effects on maternal and neonatal outcomes. Second, the study employs a hybrid approach, combining face-to-face counseling with mHealth delivery via WhatsApp and ETA, enhancing accessibility and continuity of care while reducing the burden on limited healthcare providers. Third, the intervention design simultaneously addresses the three core elements of FBM—motivation, ability, and triggers—to provide a structured, theory-driven counseling model tailored to pregnancy. Finally, by integrating widely used social networking applications into prenatal care, the trial explores a cost-effective and scalable strategy that could be readily implemented in other low-resource settings.

Objectives

This research purpose is to investigate the effectiveness of combined in-person and online counseling (via WhatsApp or ETA platform, according to the Fogg behavioral model) in managing weight gain during pregnancy. It is hypothesized that women who receive this type of weight management will have more appropriate weight gain, better growth rates, fewer pregnancy complications, and lower rates of cesarean section and macrosomia compared to women receiving usual care. Specific goals include:

• Comparison of weight gain from the beginning of pregnancy to the 24^th week of pregnancy in the two study groups

• Comparison of weight gain from the beginning of pregnancy to the 28^th week of pregnancy in the two study groups

• Comparison of weight gain from the beginning of pregnancy to the end of pregnancy (at the 37^th week of pregnancy) in the two study groups

• Comparison of the change in lifestyle score from the beginning of pregnancy to the end of pregnancy (at the 37^th week of pregnancy) in the two study groups

• Comparison of pregnancy outcome (intrauterine growth restriction, macrosomia, preterm delivery, type of delivery, gestational diabetes, and pregnancy-induced hypertension) in the two study groups

Materials and Methods

Study design and setting

This randomized controlled trial with parallel groups will be conducted on pregnant women between 12 and 14 weeks of gestation at perinatology clinics affiliated with Qom University of Medical Sciences in Qom, Iran. The study adheres to the Consolidated Standards of Reporting Trials (CONSORT) guidelines [Figure 1]. Ethical approval was granted by the Ethics Committee of Babol University of Medical Sciences (IR.MUBABOL.HRI.REC.1403.378), and the study protocol was registered on March 15, 2025, in the Iranian Registry of Clinical Trials (IRCT20100510003902N6).

Figure 1.

Consort flow diagram of patients included in the study

Study framework

Pregnant women in their 12^th to 14^th week of pregnancy, meeting the inclusion criteria and referred to Qom University of Medical Sciences-affiliated hospital perinatology clinics, are invited to take part in this study. The selected pregnant women will then be randomly assigned to either the intervention group or the control group. After a brief explanation, participants will be asked to complete the Pregnancy Lifestyle and Fertility-Demographic Questionnaires. The participants were required to fill out a consent form. The initial session, an in-person individual counseling session for the intervention group, will be led by the project manager (student) in a lecture-style format. The subsequent three sessions will be delivered via a link shared through social media platforms like WhatsApp or utilizing ETA, each lasting 90 minutes and scheduled during the designated weeks of pregnancy. Pregnant mothers in the intervention group will receive weekly home exercises based on the training sessions. Feedback from pregnant mothers will be gathered through social media platforms, while the control group will continue to receive standard prenatal care. The researcher will measure weight before the intervention begins (during the first trimester of pregnancy) and subsequently at three intervals: 24 weeks, 28 weeks, and 37 weeks of pregnancy. Measurements will be taken using a Seca height and weight scale, specifically a Seca standing dial scale manufactured in Germany, available in the hospital clinic.

Study participants and sampling

Inclusion criteria for the study are as follow: primigravida, singleton pregnancy and normal fetal growth, as confirmed by ultrasound during the initial obstetric consultation, ages 18 to 45, Outpatient obstetrics and gynecology clinic registration (12-14 weeks of pregnancy), Qom affiliated hospital, ability and readiness to use a smartphone equipped with ETA or WhatsApp features during pregnancy, mothers’ willingness to participate in the study, possessing normal comprehension and the ability to cooperate with this study, BMI 18 to 26.

The study’s exclusion criteria consisted of obesity, hypertension, and diabetes with a familial predisposition, participation in ETA, or WhatsApp social networks to guide other specialists in studies, failure to complete the study, or cooperate.

Calculating Sample Size, the formula used to estimate the sample size was derived from two tests evaluating the population sampling rate Theory within an entirely randomized design. Literature review provided appropriate weight gain for the two specimens, indicating the control group exhibited a growth rate near (P1 = 0.1) while the intervention group showed a growth rate around (P2 = 0.34). This study determined that with a 95% confidence interval (1.96) and a statistical power of 80% (0.84), a minimum of 51 cases is required for each group (n1 = n2 = 51). Accounting for a 20% sample loss rate across both the control and intervention groups, the final sample size needed is 60 cases per group[13]

Randwom allocation

Eligible participants will be randomly assigned to either the intervention group or the control group. A block randomization method with a block size of four will be applied to ensure balanced allocation across the groups. Participants will be allocated in a 1:1 ratio, resulting in 60 individuals in each group. The randomization sequence will be generated using the Random.org website. The random number table will be administered by a midwife from the Perinatology Clinics Center who is not part of the trial research team. This procedure ensures that the researchers cannot predict the group assignment of the next eligible participant at any center.

Allocation Concealment

To maintain allocation concealment, opaque and sealed envelopes will be used. Each envelope will contain a card indicating the random group assignment, prepared in advance according to the generated sequence. The envelopes will be numbered sequentially and opened in the order of participant enrollment. An independent investigator, not involved in participant recruitment or intervention delivery, will generate the randomization sequence and place the cards into sealed envelopes. Another researcher will be responsible for participant registration and group allocation oversight.

Blinding

Due to the nature of the intervention, participants and consultants cannot be blinded to group allocation. However, the outcome assessor and the statistician performing the data analysis will remain blinded to group assignments. This approach minimizes the risk of performance and detection bias while ensuring the integrity of the trial results.

Study duration

Scheduled to commence in March 2025 and conclude by May 2026.

Data collection tool

The study will utilize four tools for data collection:

To improve data accuracy and validity, we will use questionnaires validated in prior studies.

The demographic questionnaire: Including the participant’s age, height, current weight, pre-pregnancy weight, education level (and that of their spouse), occupation (and that of their spouse), income, and place of residence, age at first marriage, gestational age at study enrollment.

The obstetric information questionnaire: Including the number of prior pregnancies, the nature of the pregnancy (whether desired or undesired), involvement in childbirth preparation classes, and gestational age at delivery, will be considered.

The pregnancy outcome checklist, completed after delivery using maternal and infant records, includes intrauterine growth restriction, macrosomia, type of delivery, preterm delivery, gestational diabetes, and pregnancy-induced hypertension.

The Pregnancy Lifestyle Questionnaire, a 46-item survey administered at the beginning and end (37 weeks) of pregnancy, assesses eight subscales: work (9 items), tobacco/alcohol/drug use (6 items), safety/self-care (9 items), family/social interactions (7 items), eating habits (6 items), mental state (4 items), physical activity/health (3 items), and doctor visits (2 items). Items are evaluated using a 5-point Likert scale (always = 5 to never = 1). Subscale and total scores are calculated by summing item scores, where higher scores indicate a healthier lifestyle.[28]

Outcome Measures

Primary outcome

Comparison of the frequency of excessive weight gain during pregnancy in the two control and intervention groups at 24, 28, and 37 weeks of pregnancy.

Secondary outcome

Comparison of mean pregnancy lifestyle scores between control and intervention groups.

Evaluation of pregnancy outcomes across the intervention and control groups

Interventions

Hybrid weight management (in-person and online)

The intervention group will receive tailored and continuous pregnancy weight management support through both in-person and online care.

Intervention group formation

An intervention team for managing pregnancy weight gain will be established, comprising an obstetrician-gynecologist, two reproductive health specialists, and a counseling midwifery master’s student. The obstetrician-gynecologist is responsible for providing comprehensive prenatal care. Supervising reproductive health professionals and the senior student will offer weight management consultations both online and in-person, guided by the Ministry of Health’s Pregnancy and Childbirth Education Manual. The student will be assigned a public WhatsApp and ETA account to create and manage groups on these platforms, oversee their usage, and gather data from pregnant women.

Design and Implementation of Intervention Strategies

The intervention strategy will primarily draw upon the principles of the Fogg behavior model. Following a thorough literature review and expert consultations, the intervention plan will be structured into four stages aligned with specific phases of pregnancy. Each stage will incorporate the three key elements of the Fogg behavioral model (motivation, ability, and arousal) to address weight management in pregnant women. The elements of the Fogg behavioral model will be applied as follows:

Motivation: Setting achievable weight management objectives for pregnant women through online and in-person methods, along with providing health education guidelines, aims to enhance their motivation for successful pregnancy weight control

Empowerment: This component is designed to empower pregnant women to manage their weight more effectively by streamlining the process and minimizing the challenges and costs associated with adopting weight control behaviors. It provides enhanced knowledge of exercise and nutrition for weight management through a public WhatsApp account and the ETA group. The public WhatsApp and ETA account pages include two submenus: “Latest Content” and “Previous Content,” allowing pregnant women to easily access relevant information. Additionally, the consultation services submenu offers contact details for the research team, while the public account page facilitates direct voice communication with researchers and text messages.

Triggering: Triggering is an intervention strategy developed by the research team to support pregnant women in achieving essential weight management milestones. It encompasses three primary approaches: stimulation, assistance, and signaling.

Stimulation focuses on inspiring pregnant women to manage their weight effectively during pregnancy by providing health education, sharing knowledge, and showcasing examples of successful weight control. Assistance involves offering detailed guidance both online and in-person to those who are motivated to manage their weight but need support in understanding proper dietary choices and exercise routines. Signaling serves as a reminder of the importance of weight management and its methods through online health education resources and face-to-face counseling sessions. Additionally, it keeps pregnant women informed about their progress by regularly monitoring and tracking their weight management efforts. Figure 2, Table 1 details WhatsApp’s intervention measures based on the Fogg behavior model.

Figure 2.

Illustrates the conceptual framework based on the Fogg behavior model used in this intervention

Table 1.

Proposed intervention strategies by the WhatsApp platform utilizing the Fogg behavior model

Intervention parts		12-14 weeks of pregnancy		15-27 weeks of pregnancy		28-36 weeks of pregnancy		37 weeks of pregnancy to delivery
Motivation		1. Pregnant women in the study will receive Face-to-face counseling services. 2. Pregnant women will be encouraged to establish personalized weight management goals together. 3. Following the determination of GWG’s overall goal, Goals for Healthy Weight Gain for pregnant women were defined for each pregnancy stage, incorporating ultrasound results, abdominal circumference, uterine height, and fetal development assessments. 4. Weight management during pregnancy is crucial, as it impacts neonatal growth, development, and the mode of delivery. 5. Surveying the back of family individuals, empowering their support, and giving back to improve pregnant women’s certainty and inspiration for weight control.		1. WhatsApp friends supported one another, while a master’s student in counseling midwifery tracked the GWG of pregnant women. 2. WhatsApp friends monitored each other, and a postgraduate midwifery student supervised the Pregnant Women’s Working Group (GWG). 3. Expectant mothers will share their weight management tips and objectives via WhatsApp groups. 4. To support weight management goals, red envelopes sent via WhatsApp will be used to reward pregnant women who effectively maintain healthy weight control. 5 Individual in-person consultations will be conducted every four weeks, providing 20 to 30 minutes of in-person interaction for ongoing assessment of gestational weight gain (GWG) and promoting active involvement from family members.		1. Following the previous measures, in-person consultations will be biweekly. 2. We will focus more on pregnant women with gestational diabetes and hypertension, emphasizing the importance of weight control.		1. To reduce childbirth complications and boost motivation for weight management, this stage will focus on highlighting the significance of maintaining proper weight control. 2. In-person consultations will be offered weekly.
Ability		1. A master’s student in counseling midwifery connected with pregnant women by adding them as WhatsApp contacts and inviting them to join a dedicated WhatsApp group. Within the group, pregnant women were encouraged to introduce themselves to foster better connections and mutual understanding. 2. Pregnant women will be encouraged to subscribe to the “Expectant Mother Weight Management” WhatsApp public account.		To support pregnant women, consultations were offered via one-to-one sessions or WhatsApp groups. WhatsApp was used to encourage and monitor weight management and exercise. Weekly health education on weight control in later pregnancy was published via WhatsApp, reducing costs and improving women’s abilities to manage their weight.
Trigger		1. The initial in-person session will include individual counseling, along with assessments of diet, exercise, and lifestyle. Based on the dietary guidelines for Qom Iranian residents, personalized nutrition guidance will be provided to pregnant women, tailored to their dietary challenges and pre-pregnancy BMI levels. 2. Exercise routines will be tailored based on the pregnancy guidelines provided by the Ministry of Health and Medical Education of Iran, while also considering the personal preferences and physical comfort of pregnant women. They will receive support to adopt and maintain a healthy lifestyle.		1. Weekly WhatsApp messages deliver tailored tips for managing weight during pregnancy, offering stage-specific health insights, nutritional advice, and effective strategies to enhance motivation and well-being. 2. Assistance: The counseling midwifery master’s student offers detailed guidance on nutrition, exercise, and lifestyle during pregnancy, providing support every four weeks. 3. Signal: The counseling midwifery master’s student will use WhatsApp to emphasize the importance of weight management and provide guidance to pregnant women.		1. Stimulation: Pregnant women diagnosed with gestational diabetes or hypertension will receive education on the potential risks of these conditions to promote adherence to their prescribed treatment plans. 2. Assistance: A master’s student in counseling midwifery will offer in-person support and guidance every two weeks, focusing on detailed pregnancy nutrition, exercise, and lifestyle. Additionally, tailored dietary recommendations will be provided for pregnant women diagnosed with gestational diabetes or gestational hypertension.		1. Stimulation: Childbirth precautions and the relationship between childbirth and weight control will be added, based on the previous stage’s measures. 2. Assistance: A midwifery master’s counseling student will offer weekly support and detailed guidance on nutrition, exercise, lifestyle, and labor awareness during the third trimester, aiming to boost pregnant women’s confidence in achieving natural childbirth.
				She will conduct in-person assessments of the women’s weight, address any existing concerns, and offer advice on precautions for the next stage, serving as a proactive reminder.		3. Signal: Building on the measures implemented in the earlier stage, tailored guidance will be offered to pregnant women experiencing gestational complications.		3. Signal: Building on the measures from the previous stage, efforts to strengthen weight management will be intensified, while fostering greater confidence in natural childbirth to reduce the risk of complications during delivery.

Standard care

Control group participants will receive standard prenatal care from enrollment to delivery, including routine pregnancy health education. This encompassed regular prenatal examinations following established guidelines,[40] along with maternity school courses. These courses will encompass preparation techniques and coping strategies for childbirth, self-monitoring practices during pregnancy, prenatal diagnostic methods, pregnancy-safe exercises, guided delivery approaches, postpartum recovery techniques, breastfeeding guidance, newborn vaccination protocols, newborn bathing instructions, and comprehensive education on universal weight management. The timing and frequency of these classes will be arranged based on individual needs and availability. Participants will also receive health education materials on pregnancy, childbirth, the postpartum period, and breastfeeding, as well as general health education. Physicians, counseling midwifery master’s student, and midwives routinely monitored maternal and fetal weight during late labor evaluations to assess the feasibility of vaginal delivery.

Data analysis

This study will adopt an intention-to-treat (ITT) analysis approach, aligning with the random allocation process. Baseline variables of participants in both the control and intervention groups will be analyzed following data collection in the first stage to confirm the appropriateness of the random assignment process. We will analyze the data using SPSS 22. Descriptive statistics will be reported as the mean ± standard deviation for quantitative variables and as frequencies with their corresponding percentages for qualitative variables. Independent t-tests and Chi-square tests, or their non-parametric equivalents if necessary, will assess relationships and differences between the two groups at baseline. An analysis of covariance (ANCOVA) will be conducted to evaluate the impact of the treatment variable across the two study groups. The results will be analyzed and presented with a 95% confidence interval, using a significance level of 0.05 for all tests.

Ethical considerations

This study has been approved by the Ethics Committee of Babol University of Medical Sciences (IR.MUBABOL.HRI.REC.1403.378) and registered in the Iranian Registry of Clinical Trials (IRCT20100510003902N6). Written informed consent will be obtained from all participants before data collection. The study will be conducted in accordance with the ethical principles of the Declaration of Helsinki. Confidentiality, anonymity, and voluntary participation will be ensured throughout the research. Appropriate measures will be taken to protect participants’ personal information and prevent any unauthorized disclosure.

Discussion

This study protocol presents a randomized controlled trial designed to evaluate the effectiveness of a combined counseling intervention, grounded in the Fogg behavior model (FBM), for managing gestational weight gain in pregnant women. Excessive gestational weight gain (EGWG) remains a major public health concern, strongly associated with adverse maternal and neonatal outcomes such as gestational diabetes, hypertensive disorders, cesarean delivery, macrosomia, and later-life obesity in offspring. Recent cohort studies from Poland and Brazil have reaffirmed these links, demonstrating higher risks of macrosomia, hypertensive complications, and low neonatal Apgar scores among women with excessive GWG. Furthermore, a recent global review confirms that both EGWG and maternal obesity substantially increase the risk of preeclampsia, gestational diabetes, and cesarean section.[4,5,41,42,43] Although numerous dietary and physical activity interventions have been evaluated to prevent excessive gestational weight gain, their effectiveness remains inconsistent and context-dependent. Recent meta-analyses of over 100 randomized trials indicate that structured dietary and moderate-intensity lifestyle programs can significantly reduce GWG and improve maternal outcomes; however, challenges in implementation fidelity and population reach continue to limit their real-world impact.[10,26,44,45]

The decision to employ the Fogg behavior model (FBM) as the cornerstone of this intervention is strongly supported by a compelling and consistent body of evidence demonstrating its efficacy across a diverse spectrum of health behaviors and cultural contexts. The FBM’s unique strength lies in its parsimonious yet powerful framework, which systematically addresses the core components required for behavior change: Motivation, Ability, and Prompts. The relevance of the FBM to the specific challenge of gestational weight management is powerfully illustrated by a pioneering Chinese study.[13]

This study demonstrated that a hybrid intervention, integrating personalized, continuous support via WeChat with offline consultations explicitly based on the FBM, yielded significant improvements in maternal and infant outcomes, including reduced maternal weight, lower macrosomia incidence, and decreased cesarean section rates. This finding provides a critical proof-of-concept, evidence that the FBM’s principles are directly transferable to the complex behavioral landscape of pregnancy.

Furthermore, the robustness of the FBM is confirmed by its successful application beyond maternal health. For instance, a rigorous evaluation of a social marketing campaign in Pakistan found that the FBM not only accurately predicted condom use but also revealed a dramatic effect: men with high levels of both motivation and ability were 34 times more likely to use condoms when appropriately prompted.[46]

This finding underscores a fundamental tenet of the FBM—that prompts are most effective when they target individuals who already possess sufficient motivation and ability. This same behavioral logic underpins our intervention, where the counseling sessions are designed to build motivation and ability, making the subsequent digital prompts far more likely to succeed.

The model’s versatility is further validated by its utility in understanding vaccine uptake and health screening behaviors. Research in Nigeria successfully applied the FBM to identify key determinants of HPV vaccine acceptance among caregivers, highlighting that interventions boosting motivation, ability, and social support could substantially improve coverage.[47]

Furthermore, the FBM proves particularly valuable in designing tailored interventions for diverse demographic groups, as evidenced by its application in a sensitive health context. A qualitative study in Cameroon, which applied the Fogg behavior model to examine attitudes toward HIV testing across three generations of men, provides a compelling case in point.[48] The study’s findings powerfully illustrate how the FBM’s core components manifest differently across populations. For younger men,[21,22,23,24,25,26,27,28,29,30] who viewed testing as normative, the primary barrier was ability (e.g., financial cost), which was effectively addressed by free testing services. In contrast, middle-aged men[13,31,32,33,34,35,36,37,38,39] faced a conflict between ability (time, location constraints) and motivation (competing work priorities), suggesting that prompts would only be effective if testing services were made more accessible. For older men (41+), the central challenge was a profound lack of motivation, heavily driven by social stigma. Crucially, the finding that all groups were motivated to seek treatment if they tested positive confirms that the FBM is not only about initiating a behavior but also about sustaining it, given the right triggers and support. This nuanced understanding, facilitated by the FBM, is directly applicable to our trial; it underscores the necessity of customizing our counseling and digital prompts to address the unique motivational and ability-related barriers faced by pregnant women from different socioeconomic, cultural, or gestational-age backgrounds, rather than employing a one-size-fits-all approach.

These studies collectively demonstrate the FBM’s capacity to diagnose behavioral bottlenecks and inform tailored strategies in various public health domains.

Finally, the FBM demonstrates exceptional utility as a practical blueprint for developing structured, evidence-based health communication campaigns. This was exemplified during the COVID-19 pandemic, where a study successfully leveraged the model to develop and validate a behavior-change messaging campaign in Saudi Arabia.[49] The researchers systematically created 32 text-based and video messages, each category meticulously designed to target one of the FBM’s core components: motivation, ability, or prompts. The rigorous validation process, which involved domain experts and healthcare workers using content validity indices, confirmed that the message libraries were both theoretically sound and practically relevant. This study is critically informative for our protocol, as it provides a validated methodological template for operationalizing the FBM into concrete intervention materials. It demonstrates that the model’s strength lies not just in explaining behavior but in offering a clear, actionable framework for designing its key components. In our trial, we have similarly structured our hybrid counseling and digital content to explicitly target these three distinct psychological pathways, ensuring our intervention is built upon a proven theoretical architecture rather than ad-hoc recommendations. Beyond its demonstrated global applicability, integrating the FBM with other theoretical frameworks, such as the Health Belief Model, can yield a more holistic understanding of behavioral change mechanisms in pregnancy. Abdolaliyan et al.[50], grounded in the Health Belief Model (HBM), provide crucial evidence that cognitive perceptions—specifically perceived benefits, barriers, and self-efficacy—are fundamental determinants of physical activity and weight management behaviors during pregnancy. Our protocol actively incorporates this understanding but extends it by employing the Fogg behavior model (FBM) as a practical implementation framework. While the HBM effectively identifies what pregnant women think and believe about weight management, the FBM provides a superior blueprint for how to translate these cognitions into sustained behavior. Our hybrid counseling intervention is specifically designed to operationalize this translation: we convert perceived benefits into motivational highlights, address perceived barriers through ability-shaping strategies that simplify complex tasks, and leverage the crucial element of prompts—which the HBM overlooks—to trigger action at opportune moments. Therefore, our study does not merely apply the FBM in isolation; it proposes an integrated approach where the FBM acts as the functional engine that drives the cognitive insights identified by models like the HBM into practical, daily action, potentially creating a more potent and comprehensive intervention for gestational weight management.[50]

This protocol is positioned to make several significant contributions to both clinical practice and behavioral science. By explicitly testing the Fogg behavior model (FBM) in the context of gestational weight management, this trial addresses a critical gap in the literature, where many existing interventions lack a strong theoretical foundation or fail to operationalize their underlying model as systematically.[10,26] The potential implications are substantial. If proven effective, this FBM-based intervention could provide a replicable and scalable model for integration into standard antenatal care, offering a structured strategy to combat excessive GWG and its associated adverse maternal and neonatal outcomes (Lackovic).[4,5] This approach moves beyond generic advice by providing a tailored framework that addresses the specific behavioral mechanisms of change.

The methodological rigor of this trial is a key strength, designed to yield high-quality, reliable evidence. The randomized controlled design, with allocation concealment and blinded outcome assessment, minimizes selection and performance bias. Furthermore, the use of objective primary outcomes, such as directly measured weight and body composition, alongside validated subjective measures, strengthens the validity and comprehensiveness of our findings. This multi-faceted assessment strategy ensures that the results are both objectively verifiable and contextually rich.

We acknowledge several important considerations proactively. The single-center design, while allowing for stringent protocol control, may affect the generalizability of our findings to other populations and healthcare settings. The success of the intervention is also contingent upon two key factors: consistent, high-fidelity implementation of the FBM principles by trained counselors and sustained adherence from the participants. To address the latter, we have incorporated engagement strategies within the digital platform and maintained regular follow-up contacts. Finally, the question of long-term sustainability remains beyond the scope of this trial. Future research should therefore focus on evaluating the persistence of these behavioral changes postpartum, their long-term impact on maternal and child health, and the cost-effectiveness of implementing this model in diverse, real-world clinical settings.

This research makes a substantive contribution to maternal health literature by systematically implementing the Fogg behavior model within a rigorous experimental design, addressing a significant gap in theoretically grounded interventions for gestational weight management. Unlike previous studies that have often applied behavioral models superficially, our protocol operationalizes all three FBM components through carefully designed intervention elements, creating a replicable template for future research and clinical practice. The comprehensive assessment strategy—incorporating both objective biometric measures and validated psychosocial instruments—will provide unprecedented insights into how behavioral mechanisms translate into measurable health outcomes during pregnancy.

The potential implications of this trial extend across multiple domains of healthcare delivery and public health. In clinical practice, demonstrated effectiveness would argue strongly for integrating FBM-based counseling into standard antenatal care pathways, particularly for populations at risk of excessive gestational weight gain. This approach offers a structured methodology for addressing the behavioral dimensions of weight management that complements conventional biomedical care. Furthermore, the hybrid delivery model—blending personal counseling with digital support—creates a scalable framework adaptable to diverse healthcare settings, from well-resourced clinical environments to communities with limited access to specialist care.

Beyond its immediate application to gestational weight management, this research demonstrates the versatility and translational potential of the Fogg behavior model across health domains. The principles and implementation strategies developed here could reasonably be extended to other perinatal health behaviors, including breastfeeding support, postpartum weight management, and mental health promotion. More broadly, the methodological approach of systematically mapping theoretical constructs to intervention components serves as a valuable case study for implementation science, offering insights into how behavioral theories can be effectively translated into real-world practice.

Ultimately, this research represents a significant step toward evidence-based, theory-driven approaches in maternal health intervention design. By rigorously testing a comprehensively conceptualized behavioral intervention, our study will generate valuable data to inform clinical guidelines, shape health policy, and advance scientific understanding of health behavior change in pregnancy. The findings will contribute to establishing a more robust epistemological foundation for developing effective interventions that address the complex interplay between psychological factors, social determinants, and health outcomes in maternal and child health.

Strengths and limitations

This study protocol possesses several notable strengths that enhance the validity and potential impact of its findings. Its primary strength lies in the randomized controlled trial design, which minimizes selection and performance bias, thereby ensuring the robustness of the results. Furthermore, the intervention is firmly grounded in the Fogg behavior model, providing a coherent and testable theoretical framework for behavior change, which is often absent in existing lifestyle interventions for pregnant women. The hybrid counseling approach, combining in-person and digital components (e.g., WhatsApp/ETA), improves accessibility, and offers a flexible, patient-centered model of care. The comprehensive outcome assessment, encompassing serial weight measurements, lifestyle scores, and key clinical endpoints like rates of gestational diabetes and cesarean delivery, will provide a holistic evaluation of the intervention’s efficacy.

However, the generalizability of our findings may be constrained by several limitations. The single-center recruitment from Qom limits the demographic and socioeconomic diversity of the sample, and the results may not be directly applicable to other populations with different cultural or healthcare contexts. Practical challenges, such as participant attrition over the extended follow-up period until 37 weeks of gestation and the reliance on self-reported data for certain lifestyle factors, pose risks to data completeness and may introduce bias. Additionally, the digital component of the intervention may inadvertently exclude individuals with limited internet access or low digital literacy, potentially creating a barrier to equitable participation. Finally, as this is a study protocol, the definitive efficacy and practical implementation challenges of the intervention will only be fully revealed upon the completion of the trial and analysis of the results. Future studies should therefore focus on multi-center replications, long-term follow-up beyond delivery, and detailed economic evaluations to assess scalability.

Implications for Health Policy

If effective, the intervention can be integrated into routine prenatal care, reducing excessive or inadequate GWG and associated complications (gestational diabetes, preterm birth, hypertension). FBM principles could be adapted for other maternal and child health interventions.

Conclusion

This study is poised to make a significant contribution. By explicitly applying the FBM to gestational weight management—a relatively novel application—this research will generate novel insights into the factors influencing GWG and provide a robustly evaluated, theory-driven intervention model. If proven effective, this combined counseling approach could be integrated into routine antenatal care to mitigate the risks of EGWG and its associated complications, ultimately improving maternal and neonatal health outcomes. Furthermore, the successful application of the FBM in this context would strengthen its evidence base and demonstrate its potential for adaptation to other behavioral outcomes in maternal and child health, thereby broadening its impact on public health practice. Future research should focus on the long-term effects of such interventions, their cost-effectiveness, and their implementation in diverse, real-world settings.

Statement on the use of AI

The authors declare that no artificial intelligence tools were used in the preparation of this manuscript.

Abbreviations

GWG: Gestational weight gain; EGWG: Excessive gestational weight gain; BMI: Body-mass-index; ITT: Intention-to-treat; FAS: Full analysis set; PPS: Per protocol set; CONSORT: Consolidated Standards of Reporting Trials; SPSS: Statistical Package for the Social Sciences; ANCOVA: Analysis of Covariance.

Ethics and dissemination

The study is approved by the Ethics Committee of Babol University of Medical Sciences (IR.MUBABOL.HRI.REC.1403.378)

Data availability statement

Data are available from the corresponding author upon reasonable request.

Conflicts of interest

There are no conflicts of interest.

Funding Statement

This work was supported by Babol University of Medical Sciences. Grant number: 724135796.