Participants must be adults aged 18 years or older recruited from any source, including community or outpatient clinic populations. Inclusion is determined according to the following criteria: (1) studies with participants explicitly identified as a mixed anxiety population or a mixed anxiety-depression population will be directly eligible for inclusion; (2) studies with participants diagnosed with depression alone without any mention of anxiety conditions will be generally excluded unless the participants’ scores on an initial anxiety scale exceed the clinical cutoff for that scale, in which case the studies will be included; (3) studies with participants diagnosed with a specific anxiety disorder alone (eg, SAD or GAD) without any mention of depression or other anxiety disorders will be generally excluded unless the participants’ scores on an initial depression scale or another anxiety scale exceed the corresponding clinical cutoff, in which case the studies will be included; (4) studies with participants screened via self-report measures whose scores exceed the clinical cutoff on at least 2 relevant emotional dimensions (eg, 2 distinct anxiety disorders, one anxiety disorder combined with depression, or a general emotional distress scale) will be included; and (5) trials explicitly stating that the intervention is a transdiagnostic therapy—defined as a therapy targeting multiple EDs—will be included regardless of participants’ specific diagnoses. The following exclusion criteria also apply: (1) trials in which more than 10% of the total sample comprises patients with disorders previously classified as anxiety disorders, specifically obsessive-compulsive disorder and posttraumatic stress disorder, will be excluded (note that, following the Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition, reclassification, obsessive-compulsive disorder and posttraumatic stress disorder are no longer categorized as anxiety disorders); and (2) trials that explicitly indicate that they target participants with somatic or physical diseases will be excluded.

In this NMA, nodes will be defined based on each distinct psychotherapeutic intervention (eg, UP, TBT, ERT, acceptance and commitment therapy [ACT], and mindfulness-based cognitive therapy [MBCT]) as reported in the included studies. Node assignment will be based primarily on how the original trial authors describe and label the intervention rather than on our own theoretical judgment of the therapy’s scope. If the number of studies for a particular intervention is insufficient to support stable estimation, we will consider aggregating nodes based on shared theoretical foundations (eg, grouping similar TD-CBT interventions or aggregating third‑wave therapies) as a post hoc sensitivity analysis, and any such aggregation will be clearly justified and reported.

Transdiagnostic psychotherapies are manualized, standardized psychological interventions that treat related disorders by targeting shared transdiagnostic mechanisms underlying them. Notable examples include the UP, a transdiagnostic cognitive behavioral intervention that addresses the core underlying mechanism common to EDs (namely, neuroticism and maladaptive emotion regulation strategies); TBT; ERT; false safety behavior elimination therapy; affect regulation training; and other unified broadband protocols.

DS-CBT comprises standard protocols for a principal diagnosis of GAD, SAD, panic disorder, agoraphobia, specific phobias, or major depressive disorder.

Other EBPs are active, structured psychotherapies with established evidence, including third-wave therapies (eg, ACT and MBCT), behavioral therapies (eg, BA and PST), psychodynamic therapy, and interpersonal therapy.

Control conditions are nonactive or minimal intervention conditions, including waitlist and CAU.

This NMA will include studies comparing any 2 treatment conditions defined in the previous section. Accordingly, the following types of comparisons are eligible: (1) comparisons involving a control condition (studies comparing any active psychotherapy [eg, transdiagnostic psychotherapies, DS-CBT, or other EBPs] to a control condition) and (2) comparisons between 2 active psychotherapies (studies comparing one active psychotherapy to another active psychotherapy, which may include but is not limited to transdiagnostic psychotherapies vs DS-CBT, transdiagnostic psychotherapies vs other EBPs, DS-CBT vs other EBPs, and head-to-head comparisons among different transdiagnostic psychotherapies).

The primary outcomes (continuous measures assessed at the posttreatment time point) are (1) depression severity, measured via validated self-report or clinician-rated scales (eg, Beck Depression Inventory or Beck Depression Inventory–II [BDI-II], Patient Health Questionnaire–9 [PHQ-9], Montgomery-Åsberg Depression Rating Scale, Hamilton Depression Rating Scale, Hospital Anxiety and Depression Scale [HADS] depression subscale, and Overall Depression Severity and Impairment Scale); (2) anxiety severity, measured via validated self-report or clinician-rated scales (eg, Beck Anxiety Inventory [BAI], Generalized Anxiety Disorder–7 [GAD-7], HADS anxiety subscale, Overall Anxiety Severity and Impairment Scale, State-Trait Anxiety Inventory–Trait subscale, and Hamilton Anxiety Rating Scale); and (3) composite emotional symptom severity (where available), measured using scales that jointly assess anxiety and depression (eg, HADS total score and Patient Health Questionnaire Anxiety and Depression Scale) to align with previous transdiagnostic psychotherapy meta-analyses.

Secondary outcomes are (1) all‑cause study dropout up to the posttreatment time point (acceptability), extracted as the number of participants randomized who did not provide posttreatment data for any reason; (2) response and remission rates where consistently defined (eg, ≥50% symptom reduction; score below the threshold); and (3) remission of a secondary or nontargeted eligible anxiety or depressive disorder where reported and defined. Data will be synthesized separately if definitions and measures are sufficiently comparable across studies; otherwise, they will be summarized narratively.

The time points are at posttreatment (assessments closest to treatment end within –2 weeks to +2 weeks).

Only RCTs will be included.

These will comprise first author, publication year, country, journal, and study design (eg, individual vs cluster randomization and number of arms).

These will comprise the inclusion criteria (diagnosis vs symptom cutoff and which EDs were included); mean age, age range, and sex distribution; and recruitment source (community, clinical referrals, or other).

These will comprise treatment type and protocol name (UP, TBT, ERT, DS‑CBT, ACT, MBCT, BA, PST, or other), study protocol publication status, treatment manual availability, optional modules, session sequence and flexibility, session duration, total treatment duration, treatment format (individual vs group vs mixed), delivery mode (face-to-face, online guided, blended, videoconference, etc), treatment provider, and dropout rates.

These will comprise type of control (waitlist or CAU) and description of usual care where applicable.

These will comprise (1) outcome instrument used (eg, BDI-II, PHQ-9, BAI, or GAD-7), the corresponding means and SDs (or change scores and response and remission rates) for primary and secondary outcomes at the posttreatment time point by arm, and effect size data if directly reported (Cohen d and Hedges g); (2) the number of randomized participants and number analyzed per arm (total, mean, and SD or SE and 95% CI); and (3) the number of study dropouts by arm and reasons if reported.

We will first describe and visualize the geometry of the treatment network using the netmeta [18] package in R. In the network plot, nodes represent interventions, and edges represent direct comparisons. Node size will be proportional to the number of participants, and edge thickness will be proportional to the number of trials. Nodes will be color coded by treatment class to enhance interpretability. Additionally, we will generate a network contribution plot to illustrate the contribution of direct evidence to each network estimate and a net heat plot to identify potential inconsistency hot spots where applicable.

In the frequentist framework, P scores will be calculated to establish a hierarchy of treatment efficacy. In Bayesian sensitivity analyses, the surface under the cumulative ranking curve will be used instead. Higher values indicate a greater likelihood that a therapy is among the most effective. The certainty of the ranking will be quantified using the precision of treatment hierarchies approach as implemented in the poth package.

To explore sources of heterogeneity, the following prespecified effect modifiers will be examined where data are sufficient (defined as at least 5 studies per subgroup with adequate network connectivity to support meaningful estimation for subgroup analyses and at least 10 studies with complete covariate data for meta-regression).

Subgroup analyses (categorical moderators) will include (1) delivery format (face-to-face vs remote [delivered via smartphone apps, computer programs, or other online platforms] vs mixed [combining face-to-face and remote elements]), (2) treatment format (individual vs group), (3) guidance type (guided vs unguided), and (4) inclusion criteria (diagnosis based [eg, meeting Diagnostic and Statistical Manual of Mental Disorders or International Classification of Diseases criteria for a principal diagnosis] vs symptom cutoff based [scoring above validated thresholds on self-report measures]).

For categorical moderators, each subgroup variable will be entered separately as a categorical covariate in a network meta-regression model using the netmeta [18] function.

We will conduct network meta-regression to examine the impact of the following continuous covariates provided that the minimum study requirements are met: (1) baseline symptom severity (mean baseline score on the primary outcome measure), (2) proportion of female participants (percentage of female participants in the study sample), (3) mean study-level risk-of-bias score (aggregated RoB 2 score across domains), and (4) baseline proportion of participants with co-occurring eligible anxiety or depressive disorders.

For continuous moderators, a separate univariable random-effects meta-regression model will be fitted for each covariate using the netmeta [18] function, which estimates the regression coefficient while accounting for between-study heterogeneity. All meta-regression analyses will be considered exploratory; results will be reported as regression coefficients with 95% CIs and corresponding P values. Given the exploratory nature of these analyses, no adjustment for multiple testing will be applied, and findings will be interpreted with caution accordingly.

In NMAs, we will report the estimated between‑study SD (τ) and consider its magnitude relative to benchmarks from psychotherapy meta-analyses (eg, τ=0.1-0.2 as small, τ=0.3-0.5 as moderate, and τ>0.5 as large). We will explore the impact of heterogeneity via sensitivity analyses and, where feasible, meta-regression. Comparison‑adjusted funnel plots will be used (if there are ≥10 studies per treatment comparison) to explore small‑study effects or publication bias in the network.

Following the methodology outlined by Cuijpers et al [29] and the Confidence in Network Meta-Analysis (CINeMA) framework [30], we will evaluate the certainty of evidence for each network estimate using the CINeMA web application according to the following 6 criteria: within-study bias, reporting bias, indirectness, imprecision, heterogeneity, and incoherence. Each comparison will be rated as being of high, moderate, low, or very low certainty, and summary tables with the confidence ratings will be presented.

Preplanned sensitivity analyses include, first, analyses restricted to studies with low risk of bias. Second, analyses excluding interventions with potential transitivity violations will be conducted; interventions that are highly specific to a particular subpopulation (eg, therapies designed exclusively for older adults) may violate the transitivity assumption. Third, where Bayesian NMAs are conducted, comparison of results from the primary frequentist NMA with those from Bayesian models will be conducted to assess the robustness of treatment effect estimates and rankings.