Translating Evidence into Obstetric Care: Developing a Best Practice-Informed Stepped-Care Clinical Algorithm for the Management of Gestational Insomnia

Background

Insomnia, a common adult disorder, is defined by dissatisfaction with sleep quality or duration, including sleep initiation difficulty, nocturnal or early-morning awakenings, or non-restorative sleep, along with daytime impairments such as fatigue, cognitive dysfunction, and emotional distress.¹ Its global prevalence is estimated at 16.2%,² with markedly higher rates during pregnancy. Approximately 20% of Chinese pregnant women meet the clinical criteria for insomnia.³ In Lebanon, 40.4%, 25.5%, and 8.5% of pregnant women experienced subclinical, moderate, and severe insomnia, respectively.⁴ In Poland, among pregnant women, 20.2% reported difficulties initiating sleep and 52.8% reported frequent nocturnal awakenings.⁵ A meta-analysis encompassing 15,564 participants further indicated that insomnia prevalence varies by trimester, peaking in the third trimester (39.7%) compared to the first (25.3%) and second (27.2%) trimesters.⁶ Several factors contribute to insomnia in pregnancy, including hormonal fluctuations, physical discomforts (such as nausea, back pain, and frequent urination), inadequate respiration, and changes in body position due to abdominal enlargement.⁷ Addressing gestational insomnia is critical, as it not only impairs quality of life (QoL)⁷ and social functioning,⁸ but is also associated with adverse pregnancy outcomes such as gestational diabetes,⁹ hypertensive disorders of pregnancy including preeclampsia,⁸ and preterm birth.⁹ Furthermore, prenatal insomnia may elevate the risk of postpartum depression.¹⁰

Cognitive Behavioral Therapy for Insomnia (CBT-i) is recommended as the first-line strategy for insomnia¹¹ and has demonstrated efficacy in managing gestational insomnia.¹² CBT can be delivered through multiple modalities, including traditional in-person formats (individual or group-based), fully digital or multimedia-based approaches (eg., telephone support, email, computer- or mobile applications-based platforms, audio/video programs, and self-help books), and blended models that combine face-to-face (F2F) sessions with multimedia components.¹³ Hypnotic and sedative agents are also commonly prescribed for insomnia management.¹² However, the use of benzodiazepines and Z-hypnotics to treat gestational insomnia presents considerable challenges due to potential risks to both maternal and fetal health.¹⁴ Beyond obstetricians and midwives, pregnant women may consult other healthcare providers—such as acupuncturists or naturopaths—who may recommend complementary and alternative medicine (CAM) therapies for insomnia.¹⁵ A systematic review suggests that exercise, acupuncture, and massage are commonly advised for gestational insomnia and may be associated with improved sleep quality; however, the supporting evidence is of low quality.¹⁵

In 2022, a joint position paper by the European Insomnia Network, the Italian Marcè Society, and the International Experts Task Force for Perinatal Mental Health provided guidance on assessing and managing peripartum insomnia.¹⁶ It endorsed CBT-i as the preferred treatment for gestational insomnia, noting that pharmacotherapy may be considered when nonpharmacological interventions are ineffective, in cases of severe insomnia linked to mood or anxiety disorders, or when no alternatives exist and the anticipated benefits outweigh potential risks.¹⁶ Professional organizations, including the BSA¹⁷ and the CSRS,¹⁸ have also periodically updated their clinical practice guidelines (CPGs) to incorporate recommendations for managing gestational insomnia. Nevertheless, due to variations in the objectives, focus areas, and target populations across these guidelines and expert consensus statements, the existing evidence remains fragmented and lacks an integrated framework. Notably, certain recommendations across guidelines/consensuses are not entirely consistent and occasionally contradictory. For instance, a 2019 consensus by the BAP suggests that mild-to-moderate exercise in the evening improves gestational insomnia,¹⁹ whereas the 2020 NICE guideline advises pregnant women with sleep disturbances to reduce activity before bedtime.²⁰ Similarly, guidance on the use of Zopiclone and Eszopiclone during pregnancy differs between the BSA¹⁷ and the CSRS.²¹ Systematic integration of these recommendations, with clarification of areas of consensus and divergence, is a prerequisite for establishing a unified and actionable basis for clinical decision-making. Accordingly, this study conducted a systematic review of the available evidence to identify core intervention components for gestational insomnia, critically appraised the strength of the evidence, and formulated a clinical algorithm based on consolidated best-practice recommendations to inform the clinical management of insomnia during pregnancy.

Methods

This evidence summary was developed following the JBI Manual for Evidence Synthesis.²² Its methodological framework included problem formulation, systematic literature retrieval, study selection and quality appraisal, evidence synthesis and grading, as well as evidence translation and recommendation development.²³

Problem Formulation

The PIPOST tool²⁴ was applied to structure the clinical question— “How can gestational insomnia be managed effectively and safely?”—into an evidence-based format. The population (P) consisted of pregnant women diagnosed with insomnia. Interventions (I) included lifestyle modification, psychological and behavioral therapies, pharmacological options, and CAM. The intended professionals (P) were clinicians working in obstetrics, clinical psychology, and sleep medicine. Outcomes (O) comprised insomnia severity, pregnancy-related QoL, and childbirth outcomes. Settings (S) involved obstetric clinics or wards, sleep medicine units, psychological service centers, and community health facilities. Evidence Types (T) encompassed decision-support tools, consensus statements, CPGs, and evidence summaries.

Evidence Retrieval

Evidence retrieval was guided by the 6S evidence pyramid,²⁵ with a hierarchical search strategy proceeding from higher- to lower-level evidence sources. Initial searches targeted databases of decision support systems and best-practice resources (eg., BMJ Best Practice, UpToDate, and the JBI EBP Database), as well as guideline repositories (eg., SIGN, GIN, NGC/AHRQ, NICE, and CPG Infobase). Additional searches were performed in comprehensive English and Chinese databases (eg., CNKI, SinoMed, Wanfang, CQVIP, MEDLINE, CENTRAL, and Embase) and websites of professional organizations in obstetrics and sleep medicine (eg., RACGP, RNAO, AASM, CSRS, ESRS, SOGC, CMDA, and ACOG). Reference lists of eligible studies were manually screened to ensure comprehensiveness. The search covered publications from the inception of each database through January 2026. Detailed search strategies are provided in Appendix 1.1 and Appendix 1.2. The search was executed on February 1, 2026, in compliance with the PRISMA-S Checklist (Appendix 1.3).

Literature Screening and Quality Appraisal

Inclusion and Exclusion Criteria

Literature was included if it met the following criteria: (1) the study population comprised pregnant women diagnosed with insomnia; (2) the content focused on strategies for managing gestational insomnia; (3) evidence types were limited to consensus statements, CPGs (including consensus-based guidelines), algorithms or clinical decision aids (including recommended practices), and evidence summaries, to ensure clinical applicability and comprehensiveness. Systematic reviews were excluded to avoid duplication, as guidelines and consensus statements are typically developed based on systematic review evidence. Primary studies, situated at the base of the 6S evidence pyramid,²⁵ were also excluded, as their findings are susceptible to sample size, design bias, and confounding factors.²⁶ The inherent instability and limited generalizability of results from individual primary studies render them lower in evidentiary priority than higher-level sources—such as recommendations from guidelines and consensus statements—which undergo systematic synthesis; (4) publications were written in English or Chinese. In cases where multiple versions of a guideline or consensus from the same organization existed, recommendations were primarily extracted from the most recent version, with supplementary content from earlier versions if omitted in the update, to ensure completeness of the extracted recommendations.

Literature was excluded if it met any of the following criteria: (1) research protocols, drafts, or abstracts without full text; (2) unavailability of full text despite reasonable efforts to obtain them; (3) significant methodological flaws (ie., extremely low quality); (4) translations or interpretations of original publications.

Literature Screening

All retrieved records were imported into Zotero (version 7.0) for management, and duplicates were removed. Two researchers (QQ-F and P-X), both trained in systematic literature retrieval and data entry, independently screened titles and abstracts against the inclusion and exclusion criteria. Disagreements were resolved through consultation with a third reviewer (FY-Z). Subsequently, the same reviewers independently extracted data using a standardized form, with blinding to each other’s results. Extracted information included study characteristics such as first author or organization, publication year, language, source, literature type, and thematic focus.

Literature Quality Assessment

Quality appraisal tools were selected based on literature type. CPGs were evaluated using the AGREE II instrument.²⁷ Consensus statements were assessed with the JBI Critical Appraisal Checklist for Textual Evidence: Expert Opinion.²⁸ For clinical algorithms or decision aids, quality was determined based on the methodological rigor of the source documents (eg., guidelines or consensus statements). Evidence summaries were appraised using the Revised CASE Worksheet.²⁹

Four researchers (WJ-Z, LP-Y, FY-Z, and QQ-F), all trained in evidence-based methodology and with relevant practical experience, independently conducted the quality appraisal. Discrepancies were resolved through discussion until consensus was reached. Inter-rater reliability was quantified using the intraclass correlation coefficient (ICC).

Evidence Synthesis, Translation, and Development of Practical Recommendations

First, following an established framework for evidence synthesis,³⁰ two researchers (FY-Z and WJ-Z), each with over a decade of clinical experience in sleep medicine, independently and concurrently extracted and summarized evidence from the included literature according to the following criteria: (1) for evidence with identical content, the version with the clearest, most specific, and most concise expression was retained; (2) for evidence with similar or complementary content, individual statements were merged into a unified recommendation; (3) for conflicting evidence, the original sources were traced, and priority was given to higher-quality and more recently published evidence from authoritative sources. All included evidence was graded according to the JBI Levels of Evidence System (Levels 1–5),³¹ based on study design.

Subsequently, the two researchers cross-verified the synthesized evidence and corresponding levels. Disagreements were resolved through discussion; if consensus could not be achieved, a third expert in sleep medicine (R-C) provided adjudication.

Finally, the strength of each synthesized recommendation was determined using the FAME (Feasibility, Appropriateness, Meaningfulness, and Effectiveness) Scale, in conjunction with the JBI Grades of Recommendation. Following panel discussions, each recommendation was classified as either a Strong Recommendation (Grade A) or a Weak Recommendation (Grade B).³¹ The FAME-based grading methodology is detailed in Appendix 2.

Results

Literature Search Results and Overview

The systematic search identified 178 records. After duplicate removal using Zotero, 81 records remained. Following full-text assessment, 19 documents were ultimately included: nine consensus statements, eight CPGs, one clinical decision aid, and one evidence summary. The detailed screening process is presented in Appendix 3, and the excluded literature with reasons for exclusion are provided in Appendix 4.

The basic characteristics of the included literature are summarized in Appendix 5. Among the eight CPGs, five involved version updates. Three were published by the Sleep Disorders Group of the CMA, with the initial version released in 2012,³² followed by updates in 2017³³ and 2023.³⁴ The other two were published by the CSRS, with the first edition in 2017²¹ and an updated version in 2025.¹⁸ As specified in the Methods section, during evidence extraction and synthesis, priority was given to the most recent versions, with earlier versions serving as supplementary sources. No updated versions were identified for the remaining included documents.

Literature Quality Appraisal Results

Among the eight included CPGs, two^17,20 achieved standardized scores of 60% or higher across all six AGREE II domains, meeting the criteria for a Grade A recommendation. The remaining six guidelines were rated as Grade B (Appendix 6).

All expert consensus statements were included. One statement issued by the BAP¹⁹ demonstrated clarity and explicitness across all appraisal dimensions. Only one statement³⁵ lost points on “Item 5 Is there reference to the extant literature?” due to the absence of clearly cited sources supporting the recommendations related to insomnia management during pregnancy (Appendix 7).

The single evidence summary³⁶ was rated as moderate in quality. Downgrading was primarily attributable to “No” ratings for the items “Are the reviewer(s)/editor(s) of the summary transparent?” and “Are the recommendations current?”, as well as “Not Completely” ratings for “Are the search methods transparent and comprehensive?” and “Are the recommendations appropriately cited?” (Appendix 8).

The single clinical decision aid¹⁶ was based on a high-quality guideline concerning antenatal and postnatal mental health management and service provision issued by NICE.²⁰ Accordingly, it was classified as a high-quality evidence source (Level A) (Appendix 9).

Inter-rater reliability during the quality appraisal process was high. ICC values ranged from 0.76 to 0.84 across all evaluated documents, exceeding the 0.75 threshold indicative of strong agreement.

Generation of Recommendations and Clinical Decision-Making Algorithm

Through iterative comparison, analysis, and discussion, the extracted evidence was organized into five overarching themes: (1) general principles for managing gestational insomnia; (2) behavioral interventions; (3) CBT-i-centered psychotherapy; (4) pharmacotherapy for primary insomnia and insomnia comorbid with other somatic/emotional disorders; and (5) complementary and integrative therapies. A total of 31 actionable recommendations were formulated, including 17 strong recommendations and 14 weak recommendations (see Table 1).

Table 1 Best-Practice Recommendations for the Multimodal Management of Gestational Insomnia

These five themes can be conceptualized as a stepped-care model: within this comprehensive treatment framework, lifestyle modifications are prioritized as the first-line approach, followed by CBT-i. Pharmacological or CAM interventions are considered only when CBT-i yields insufficient clinical response. The corresponding implementation pathway has been operationalized as a clinical decision-making algorithm (see Figure 1).

Figure 1 Evidence-Based Clinical Algorithm for the Management of Gestational Insomnia. Abbreviations: CBT-i, Cognitive Behavioral Therapy for Insomnia; CPAP, Continuous Positive Airway Pressure; OSAH, Obstructive Sleep Apnea-Hypopnea; WED/RLS, Willis-Ekbom Disease/Restless Legs Syndrome.

Discussion

Overarching Principles: Symptom Control, Stress Management, and Family Support

Emerging evidence suggests that identifying and managing sleep disorders during pregnancy may help reduce adverse pregnancy outcomes and enhance maternal and fetal well-being.⁴⁴ Pregnant women often express substantive concerns about their sleep. For instance, a cross-sectional study at the University of California found that among pregnant women with moderate-to-severe insomnia (ISI score > 14), 57% had discussed their sleep issues with a healthcare provider.⁴⁵ Accordingly, our algorithm recommends that when insomnia adversely affects a pregnant woman’s well-being, a personalized treatment plan should be initiated, with ongoing monitoring and evaluation to guide dynamic clinical decision-making.³⁷

Sleep quality is influenced by gestational stage and associated symptoms. In the first trimester, nausea, back pain, and frequent urination are the primary disruptors. During the second trimester, fetal movements and heartburn may disturb sleep. By the third trimester, in addition to the recurrence of back pain and urinary frequency, women may experience cramps, itching, and vivid or unpleasant dreams, resulting in more frequent nocturnal awakenings compared with earlier trimesters.¹⁹ Effective management of these pregnancy-specific symptoms is therefore likely to alleviate insomnia.

Beyond fostering a positive coping attitude toward insomnia and addressing pregnancy-related symptoms, clinical practitioners—particularly psychologists—are encouraged to strengthen pregnant individuals’ capacity for stress management.³⁸ This may include guiding them to alleviate distressing thoughts related to pregnancy and childbirth and supporting adaptation to role transitions.³⁸ Evidence indicates that perceived stress is strongly associated with poorer sleep quality in pregnant women, who are more sensitive to stress than non-pregnant women; higher stress levels correlate with shorter sleep duration and progressively worse sleep.⁴⁶ Conversely, interventions that reduce prenatal stress may effectively ameliorate insomnia.⁴⁶ Enhanced family support also moderates the impact of pregnancy-related stress on sleep,⁴⁷ highlighting the importance of educating women about available support and encouraging families to provide increased care and attention, which can reduce the incidence or severity of pregnancy insomnia.^16,38,47

Lifestyle Modifications: From Diet and Exercise to Environment and Body Positioning

Lifestyle modifications are strongly supported by the included evidence as a primary approach for preventing and alleviating gestational insomnia (Table 1). This aligns with prior research indicating that greater adherence to healthy lifestyle behaviors in pregnant women is associated with fewer sleep disturbances and improved sleep quality.⁴⁸

Nocturnal eating is common due to increased physiological appetite,⁴⁹ but prospective data indicate it correlates with sleep disturbances as evidenced by higher PSQI scores.⁵⁰ Thus, minimizing nighttime eating—particularly in bed—is advised.³⁶ Consumption of spicy, calorific, or fried foods should also be limited to reduce heartburn-related sleep disruption.³⁶ Psychoactive substances such as caffeine,²⁰ alcohol,³⁵ and heavy nicotine use³⁶ should be avoided before bedtime. Pregnant women are physiologically prone to nocturia due to elevated progesterone levels and increased glomerular filtration rate,⁵¹ a factor that contributes to sleep disruption during the first and third trimesters.¹⁹ Therefore, while adequate daytime hydration is encouraged, fluid intake after 5 p.m. should be restricted to minimize nocturia-related sleep interruptions.³⁶

Exposure to artificial light at night has been identified as a general risk factor for poor sleep.⁵⁰ Reducing nighttime light exposure is recommended, and dim nightlights can be used when necessary, such as during evening bathroom visits.³⁶

Although early AASM guidance suggested in 2001 that exercise before sleep may impair sleep quality,⁵⁰ subsequent research, including the 2013 Sleep in America Poll, found no adverse association with evening exercise.⁵² A 2019 meta-analysis further challenged the notion that evening exercise negatively affects sleep, though it cautioned that vigorous exercise performed within one hour of bedtime might impair sleep due to inadequate cardiovascular recovery, resulting in elevated heart rate and reduced parasympathetic activity at bedtime.⁵³ Based on these findings, pregnant women are recommended to engage in approximately 30 minutes of mild-to-moderate evening exercise, ideally 4–6 hours before bedtime,³⁶ such as prenatal yoga³⁹ or stretching.¹⁹

Sleep discomfort due to body position is another common disturbance.⁵⁴ Pregnant women should avoid supine sleep, particularly in late pregnancy, due to risks of maternal cardiovascular compromise and stillbirth.⁵⁵ A left lateral tilt posture—lying on the left side with knees and hips flexed and pillows placed under the abdomen, between the knees, and behind the back—can reduce lower back pressure and improve sleep comfort.³⁶

CBT-i: Digital Delivery and Platform-Supported Self-Management

Numerous systematic reviews have demonstrated that CBT-i effectively improves gestational insomnia^12,56 and may concurrently alleviate depressive and anxiety symptoms in affected women.¹² A Canadian cross-sectional survey indicated that, compared with other therapies, pregnant women preferred CBT-i for managing insomnia.⁵⁷ Consistently, most clinical guidelines and expert consensus statements recommend that, when insomnia persists despite lifestyle modifications, psychological interventions—particularly CBT-i—should be prioritized.^34,35,40

A major barrier to the widespread use of CBT-i is the insufficient availability of trained clinicians relative to clinical demand.⁵⁸ Digital CBT-i programs help bridge this science-care gap and are particularly relevant for pregnant women, who favor flexible mental health care and benefit from timely interventions.⁵⁸ Several randomized controlled trials (RCTs) have shown that digital CBT-i reduces insomnia symptoms, prolongs sleep duration,^58,59 mitigates subclinical anxiety and depressive symptoms associated with insomnia,⁵⁸ and may even prevent postpartum sleep loss.⁵⁹

The 2024 Chinese Expert Consensus on Digital Therapeutics for Insomnia advises clinicians to enhance adherence among pregnant women receiving digital CBT-i by strengthening online supervision and reminders, or by requiring them to use wearable devices to collect objective sleep data.⁴⁰ Only when insomnia persists due to “non-adherence reasons” should in-person CBT-i (i.e., F2F-CBT-i) be considered.⁴⁰ Another Chinese expert consensus published in 2025 further recommends CBT-i Coach—featuring sleep diaries, prescription updates, alarms, and reminders—to support F2F-CBT-i in pregnant women.³⁵ Developed by the U.S. Department of Veterans Affairs and Department of Defense, CBT-i Coach is a free mobile health application delivering core CBT-i components.⁶⁰ Evidence from an RCT confirms that integrating CBT-i Coach with individual CBT-i is highly feasible and acceptable to patients, enhancing their access to therapy materials and yielding significant improvements in sleep quality.⁶¹

In resource-limited settings where digital or F2F-CBT-i is unavailable, brief behavioral treatment for insomnia (BBT-i) offers a feasible alternative. Compared with standard CBT-i, BBT-i requires fewer visits, a shorter treatment duration, and can be delivered by primary care nurses rather than specialized psychologists, lowering barriers to access.⁶² Although current CPGs, consensus statements and decision aids do not yet include BBT-i, a randomized controlled trial in Australia has shown its preliminary efficacy for alleviating sleep disturbances, including insomnia, in late-pregnancy women.⁶³ We recommend that guideline developers continue to monitor emerging evidence on BBT-i’s safety and efficacy for gestational insomnia and consider its potential inclusion in future updates.

Pharmacological Management: Indications, Principles, and Considerations for Comorbid Conditions

Pharmacotherapy should be considered only for severe cases where symptoms persist despite CBT-i and other non-pharmacological interventions. Prior to initiating medication, the potential benefits and risks must be thoroughly weighed,³⁸ and the treatment decision should be made collaboratively by the patient, her family members, and the clinicians.¹⁸ Key principles for medication use include prescribing the minimum effective dose, limiting treatment duration, and preferring monotherapy whenever feasible to avoid polypharmacy.²¹ The integration of pharmacological and non-pharmacological approaches (eg., CBT-i) is encouraged to augment sleep-promoting effects.²¹

Due to the lack of extensive clinical trials on pregnant women, the safety profiles of sedative-hypnotics remain unestablished. The U.S. FDA classifies most benzodiazepines as Category D and Z-hypnotics as Category C;⁶⁴ while this suggests a relatively lower risk for the latter, the inference is drawn from limited data.²¹ Therefore, in clinical practice where pharmacotherapy is deemed unavoidable, Z-hypnotics like Eszopiclone³⁸ and Zopiclone^19,65 are considered acceptable under strict therapeutic supervision, though they should not be interpreted as first-line treatments. Additionally, a Singapore expert consensus, based on limited evidence, recommends melatonin over other sedative-hypnotics with greater side effects and dependence risks.⁴¹

Pharmacological management may also be indicated for insomnia comorbid with other conditions. In cases where gestational insomnia coexists with mood disorders and shows inadequate response to psychotherapy, tricyclic antidepressants (eg., Amitriptyline, Doxepin) may be cautiously prescribed for comorbid depression,^21,36 or low-dose Lorazepam for comorbid anxiety.^16,36 For pregnant women with insomnia accompanied by significant nausea and vomiting, antihistamines such as Doxylamine³⁶ or Diphenhydramine²¹ may be appropriate. Comorbid conditions such as restless legs syndrome (RLS)⁶⁶ and obstructive sleep apnea-hypopnea (OSAH)⁶⁷ are also frequently observed in pregnant women with insomnia. Patients with concurrent RLS often experience prolonged sleep onset latency and more severe depressive symptoms, with iron and folate deficiencies playing a mediating role in this association.⁶⁶ Accordingly, timely screening for and correction of these deficiencies is recommended.^19,36 Data from a U.S. survey indicate that 15.7% of women in their third trimester report comorbid habitual snoring and insomnia, which is associated with increased risk of hypertension and other adverse pregnancy outcomes.⁶⁷ Thus, screening for OSAH and prompt intervention are warranted in pregnant women with insomnia and suspected OSAH.³⁶

CAM Strategies in Prenatal Insomnia Care: Focus on Acupuncture, Herbal Remedies, and Light Therapy

Limited access to CBT-i and concerns regarding the adverse effects of sedative-hypnotics are primary drivers for the adoption of CAM among individuals with insomnia.¹¹ The popularity of CAM among pregnant women, specifically, is also partly motivated by a desire to maintain greater personal control over health and well-being.⁵⁷ A national Australian survey reported that 48.1% of pregnant women consulted a CAM practitioner, and 52.0% used CAM products (excluding vitamins and minerals) during pregnancy.⁶⁸

Two small controlled clinical trials have demonstrated that acupuncture can significantly improve sleep quality in pregnant women with insomnia.^69,70 One of these studies further suggested that this effect may be mediated by increased melatonin secretion.⁶⁹ Consequently, acupuncture has been incorporated into several Chinese guidelines and consensus statements for managing gestational insomnia.^42,43 However, a specific precaution is noted: the Sanyinjiao acupoint (SP6) is generally considered contraindicated for needling⁴³ due to concerns that its stimulation might provoke preterm uterine contractions.⁷¹

In addition to acupuncture, a Chinese guideline also recommends Huanglian-Ejiao Decoction for managing gestational insomnia.⁴² This aligns with China’s long tradition of using herbal medicine during pregnancy.⁷² A large cohort study of 199,710 pregnant individuals reported that 65.7% used Chinese herbal formulas.⁷² Similarly, a Swiss study found that 89.9% used herbal medicines during pregnancy.⁷³ Among these, valerian and lavender are frequently employed to alleviate sleep disturbances and restlessness,⁷³ though not currently recommended by guidelines for gestational insomnia.¹⁷ Given limited safety evidence, scholars advise obstetricians to routinely inquire about herbal or natural product use during prenatal checkups, and to educate pregnant women against assuming such medicines are inherently harmless.⁷⁴

Evidence for other CAM modalities is more limited. Light therapy is recommended for pregnancy-related insomnia in only one consensus statement to date,³⁹ although a previous meta-analysis supports its efficacy in improving both sleep disturbances and depressive symptoms in pregnant women.⁷⁵

Implementation Considerations for the Algorithm: Multidisciplinary Collaboration and Role Delineation

Efficient implementation of the proposed stepped-care algorithm in real-world clinical settings requires overcoming traditional barriers among obstetrics, sleep medicine, clinical psychology, and community-based nursing. Obstetricians and midwives are responsible for delivering first-line, low-intensity interventions following a confirmed diagnosis of gestational insomnia (eg., sleep hygiene education, lifestyle modification guidance, etc.) while screening for comorbidities such as RLS or OSAH. Clinical psychotherapists oversee subsequent treatments, prioritizing digital CBT-i to reach a larger cohort of pregnant women with mild-to-moderate insomnia and reserving face-to-face therapy for severe cases or those with comorbidities. Community nurses should longitudinally monitor treatment adherence during lifestyle modification and CBT-i interventions, promptly identifying poor responders and alerting sleep medicine physicians and obstetricians to collaboratively evaluate and initiate pharmacological treatment when necessary.

Limitations

In an effort to enhance the clinical relevance and practical applicability of the existing recommendations, this study synthesized evidence exclusively from CPGs, consensus statements, and decision-support materials. Although this approach bolsters the authority of the recommendations, the exclusion of primary research studies precludes the incorporation of the most recent research advancements.³⁰ Therefore, the future accumulation of primary study findings will necessitate periodic systematic reviews and updates of guidelines and consensus statements, enabling the ongoing integration of emerging high-quality, high-level evidence into this clinical algorithm, thereby preserving its currency and evidentiary rigor.

Although each individual component of our algorithm (eg., lifestyle modifications, CBT-i, pharmacotherapy) is supported by evidence from various moderate-to-high-quality authoritative guidance sources, the stepped-care algorithm as a whole—including decision thresholds (eg., escalation from CBT-i to pharmacotherapy) and the sequential logic linking intervention tiers—has not been prospectively validated. Consequently, whether adherence to this algorithm is more effective in improving clinical outcomes relative to existing obstetric care protocols warrants careful evaluation in future implementation science research.³⁰

In addition, the literature search was confined to publications in Chinese and English, potentially omitting critical evidence from databases in other languages.

Finally, the synthesized evidence inherently reflects the contextual conditions, regional variations, and demographic characteristics of the settings in which the included sources were developed. Socioeconomic, cultural, and behavioral barriers that may differentially affect adherence to these interventions among pregnant women with insomnia in other regions or ethnic groups were not systematically evaluated. Consequently, cultural adaptation and local validation are necessary when applying these recommendations across diverse populations and healthcare settings worldwide.⁷⁶

Conclusion

Through a systematic and comprehensive evidence synthesis, this study developed 31 recommendations and established an integrated clinical algorithm for the management of gestational insomnia. This algorithm operationalizes a patient-centered, stepped-care approach supported by the available evidence. Initially, pregnant women with insomnia are advised to implement multidimensional lifestyle modifications encompassing diet, exercise, and sleeping positions. For those with more severe insomnia, CBT-i is recommended, potentially augmented by smart platforms such as CBT-i Coach to facilitate daily self-management and enhance treatment adherence. Pharmacological interventions or CAM therapies are reserved for cases exhibiting inadequate response to psychological and behavioral interventions. Concurrently, the algorithm emphasizes stress management training for pregnant women and advocates for adequate family support from relatives. By translating existing evidence into a clear step-by-step decision pathway, this algorithm has the potential to narrow the gap between evidence and clinical practice and contribute to improved sleep health among pregnant women experiencing insomnia. Nevertheless, it should be emphasized that this algorithm should currently be interpreted as an evidence-informed structured framework rather than a definitive clinical protocol, as its feasibility and effectiveness require prospective validation in real-world obstetric settings.