Re-Assessment and Extension: An Ongoing Evaluation of The System for Adult Growth and Emergence-Foundations,a Modified DBT Program to Aid Emerging Adults With Emotion Regulation and Transition

Abstract

Emerging adulthood is associated with change and distress. The System for Adult Growth and Emergence – Foundations (SAGE-F) treatment program, a six-week outpatient DBT intensive, was developed to improve emotional functioning for such individuals. Utilizing a single-group design, the current study aims to re-examine (n = 48) and expand (n = 83) initial therapeutic findings of SAGE-F. Participants were administered an assessment battery at pre-treatment, upon immediate completion of SAGE-F, six-weeks after baseline, and at three months following program completion. Results were comparable to the pilot study: the completion of SAGE-F, when compared to baseline, is associated with reductions in mood dysregulation and self-harm, and improvements in functioning capacities, with gains sustained for at least three months. Further, program completion was associated with improved DBT skill use, with individuals demonstrating more insight of skill dysfunction rather than skill growth. Results continue to support that SAGE-F provides both immediate and long-term benefits.

Keywords

emerging adults DBT intensive outpatient dysregulation skills self-injury

Introduction

Emerging adulthood (EA), a developmental period that occurs between the ages of 18 and 25, has only been empirically examined over the last 20 years (Arnett, 2000, 2006). EA is marked by identity exploration, life transitions, and increasing independence, with shifts in social support and relationships (Lapierre & Poulin, 2020), attempts at balancing agency and connectedness (Branje et al., 2021; Bühler et al., 2021) the development of financial independence (Butterbaugh et al., 2020), and a reorganization of professional goals (Yau et al., 2021). Correspondingly, emerging adults (EAs) self-report intent to increase responsibility, redefine relationships, seek financial autonomy, and cement value-driven goals during this period (Nelson et al., 2007; Schwartz, 2016). Overall, EA is characterized by the ongoing effort to reach typical adulthood milestones that are often not reached until one’s thirties (Arnett, 2000, 2006).

While EA is associated with growth and progress (Yau et al., 2021), many unique challenges can arise. EAs are more vulnerable to mental illness than most developmental groups, with earlier onset predictive of diagnostic stability and interference later in life (Gustavson, et al., 2018). EA is associated with the highest prevalence rates of mental illness, with an estimated one-fifth of all EAs meeting criteria for a psychiatric disorder (Hoffman et al., 2018), including mood, substance use, and psychotic-related disorders (Chan, 2017; Gustavson et al., 2018). Further, by the end of EA, three-quarters of those with a lifetime prevalence of mental illness will have begun to manifest symptoms (Lapierre et al., 2020). While various causes have been proposed to explain this elevated rate of mental illness, including faulty coping tools, ineffective social supports, poor treatment infrastructure, and biological vulnerabilities, (Lee et al., 2017; Liu et al., 2020), this heightened risk remains noteworthy.

Despite such high psychiatric prevalence rates, overall mental health treatment compliance rates remain low for EA, and in fact, drops as individuals transition from adolescence to EA (Black et al., 2019). Exacerbating the impact of low treatment compliance, the improper management of mental healthcare is associated with poorer functional and psychological functioning in EAs as they age (Murray et al., 2022; Veldman et al., 2015), resulting in significant “occupational, psychological, and social impairments” (LaCount et al., 2015, p. 152).

Unfortunately, EAs today face a unique landscape compared to earlier cohorts that further increases this vulnerability. While all developmental cohorts were impacted by the COVID-19 pandemic, compared to other cohorts, EAs may have experienced the most significant impacts (Hussong et al., 2023; Tasso et al., 2021; Vahratian et al., 2021; Varma et al., 2021; Velez, 2023). For EAs who were already experiencing pre-pandemic psychiatric disruptions, the pandemic resulted in significant disruptions in functioning, social identity, mood, and effective coping, with significant increases in loneliness, disrupted developmental milestones, and limited social supports (Horigian et al., 2021; van den Berg et al., 2021).

Independent of the pandemic, recent societal shifts in technology, secularism, finances, sexual and gender identity, and civic responsibility have also led to significant, recent, alterations within this developmental phase (Baggio et al., 2017; Rounsefell et al., 2020; Schwartz et al., 2013; Upenieks, 2021). Societal pressures to delay immediate financial gains in order to increase one’s education credentials (Homan et al., 2022), may also be contributing to this delayed developmental shift – although recent data indicates such interests in post-secondary education may be slowing (Marcus, 2022). Such financial delays appear to at least partially explain why EAs are remaining at home with their parents for longer durations (Fry et al., 2020), delaying marriage (Horowitz et al., 2019), and starting families at a later age (United States Census Bureau, 2016). In summary, the pressures faced by today’s EAs are more demanding than previous generations, and as result, their developmental and health trajectories appear to be altered, when compared to prior cohorts of EAs.

As a result of the unique characteristics associated with EA (Arnett, 2000), the compounding effects of contemporary stressors (Horigian et al., 2021), and prior clinical recommendations for working with EAs, including a transdiagnostic approach that incorporates mindfulness, interpersonal development, and individualized goal-setting (Bentley et al., 2018; Finan et al., 2018; Fusar-Poli et al., 2021; Lapierre & Poulin, 2020; Li et al., 2018; Toms et al., 2019), our team developed an intensive outpatient, modified dialectical behavioral therapy (DBT; Linehan et al., 1991) program specifically to meet the needs of EAs called System for Adult Growth and Emergence – Foundations (SAGE-F; Taliercio et al., 2021). While reviewing the exact structure and format of SAGE-F is beyond the scope of this review (see Taliercio et al., 2023 for more details), the treatment program is an intensive six-week DBT outpatient program that incorporates individual DBT, phone coaching, and DBT skills group. Unlike standard DBT however, SAGE-F also teaches executive functioning skills such as task initiation and time management. A pilot study was previously conducted examining the therapeutic potential of SAGE-F (Taliercio et al., 2023). This initial evaluation, utilizing a single-group, pre-post design, found SAGE-F to be associated with reductions in depression, anxiety, and non-suicidal self-injurious behaviors (NSSIB), while simultaneously associated with improvements in daily functioning and perceived coping ability, both within immediate and long-term settings. While findings were promising, a number of limitations were present in this initial assessment, including high research attrition for follow-up measures – but not treatment attrition or compliance, limitations in statistical power, and a homogenous sample. To the best of our knowledge, SAGE-F is the first modified DBT treatment program specifically for EAs within an outpatient treatment setting. Considering the ongoing and unique pressures facing today’s EAs, there are clinical and public health implications for developing treatments targeting this cohort. Therefore, given the promising results of the pilot study, ongoing, and expanded, evaluation is vital to ensure SAGE-F’s continued therapeutic utility.

The current study represents both a replication and expansion of our pilot study (Taliercio et al., 2023), and required the use of two distinct samples. One sample was required when attempting to replicate our original findings, and a second, larger, sample was utilized when attempting to expand our understanding of SAGE-F. We first attempted to ensure our original findings remain valid as both statistical power increases and as the peak of the COVID-19 pandemic recedes and treatment transitions into a hybrid model, which incorporates both in-person and telehealth treatment engagement. We hypothesized that those who complete SAGE-F would experience both immediate and long-term reductions in depression, anxiety, and NSSIB, as well as improvements in their daily functioning and perceived coping capacities. We hypothesized such therapeutic gains would be similar to that of our pilot study. In attempting to expand upon our understanding of SAGE-F, multiple hypotheses were generated. Considering EA is associated with such significant growth and milestone achievements (Arnett, 2000, 2006), we also hypothesized that the completion of SAGE-F in this study would result in the achievement of developmentally-appropriate milestones, such as acquiring employment, or graduation from school. Further, as our original study only examined changes in perceived coping capacities, rather than DBT skill growth, we also hypothesized that the completion of SAGE-F would be associated with increases in DBT skill use and reductions in skill dysfunction. Finally, we hypothesized that as EAs demonstrate increased coping capacities, their perceived capacity and confidence in their ability to cope would also increase, which would indicate good insight into their own capabilities. Attempts were made to correct limitations present in the pilot study.

Methods

Participants

The current study consisted of two samples. The first sample consisted of new participants, while the second sample included participants from both sample one and those from the pilot study. The current study’s sample one consisted of 48 participants (see Table 1) who were recruited from a large metropolitan area. A majority of the sample was female (58.30%), cis-gendered (90.70%), 20-year-old (20.80%), White (66.70%), heterosexual (35.40%), and identified as students on academic leave (35.40%). A majority of this sample also attended at least one in-person group session (75.00%) and resided with either family and/or friends (68.60%). This first sample served as an independent comparison to the sample in the pilot study (Taliercio et al., 2023).

Table 1.

Demographic Characteristics of Sample 1 at Baseline.

Characteristic	n	%
Sex at Birth
Male	18	37.50
Female	28	58.30
Prefer not to answer	2	4.20
Gender^a
Male	15	34.90
Female	24	55.80
Transgender man	1	2.30
Genderqueer or gender nonconforming	3	7.0
Age
18–19	13	27.10
20–22	21	43.70
23–25	7	14.70
26+	7	14.70
Race^a
White	32	66.70
Latino	1	2.10
Asian	1	2.10
Prefer not to say	1	2.10
Multiracial	4	8.30
Sexual orientation^a
Heterosexual	17	35.40
Gay or lesbian	2	4.20
Bisexual	14	29.20
Queer, pansexual, or questioning	5	10.40
Other	1	2.10
Marital status^a
Single, never married	38	79.20
Years of completed education^a
High school	7	14.60
Some college	24	50.00
Bachelor’s degree	6	12.50
Master’s degree	2	4.20
Current employment^a
Student, currently enrolled	6	12.50
Student, on academic leave	17	35.40
Employed, full-time	1	2.10
Unemployed, and looking for work	5	10.40
Unemployed, and not looking for work	9	18.80
Sharing residence with family and/or friends^a	33	68.80
Attended in-person, at least once	36	75.00

Note. This sample was utilized when replicating the original study’s findings (Taliercio et al., 2023), and served as a comparison against the original pilot study’s findings.

^aSome participants did not respond to this question, resulting in responses equating less than 100%.

In contrast, the second, and larger sample (n = 83; see Table 2), consisted of all individuals utilized in both the pilot study (Taliercio et al., 2023) and that of the current study’s sample one. Similar to sample one, all participants were recruited from a large metropolitan area. This combined sample was also majority female (62.70%), cis-gender (80.70%), White (69.90%), heterosexual (38.60%), and identified as college students on academic leave (33.70%), who lived with either family members or friends (77.20%). In contrast, this second sample’s majority age was 19 (21.70%), while only a minority of the participants attended in-person sessions (43.40%). This second sample was utilized to examine the current study’s unique hypotheses, while maintaining ample statistical power.

Table 2.

Demographic Characteristics of Sample 2 at Baseline.

Characteristic	n	%
Sex at Birth
Male	29	34.90
Female	52	62.70
Prefer not to answer	2	2.40
Gender^a
Male	25	30.10
Female	42	50.60
Transgender male	1	1.20
Transgender female	1	1.20
Genderqueer or gender nonconforming	8	9.60
Other	1	1.20
Age
17–19	30	36.10
20–22	29	34.90
23–25	13	15.60
26+	11	13.20
Race^a
White	58	69.90
Latino	3	3.60
Asian	1	1.20
Prefer not to answer	1	1.20
Multiracial	11	13.30
Sexual orientation^a
Heterosexual	32	38.60
Gay or lesbian	5	6.00
Bisexual	23	27.70
Queer, pansexual, or questioning	10	12.00
Other	4	4.80
Marital status^a
Single, never married	72	86.70
Married, or in civil union	1	1.20
Years of completed education^a
Some high school	3	3.60
High school	15	18.10
Some college	36	42.40
Associate degree	2	2.40
Bachelor’s degree	15	18.10
Master’s degree	3	3.60
Current employment^a
Student, currently enrolled	14	16.90
Student, on academic leave	28	33.70
Employed, full-time	3	3.60
Employed, part-time	4	4.80
Unemployed, and looking for work	13	15.70
Unemployed, and not looking for work	11	13.30
Sharing residence with family and/or friends^a	54	77.20
Attended in-person, at least once	36	43.40

Note. Individuals in this sample included individuals from sample 1 and the original pilot study. This sample was utilized when assessing hypotheses unique to the current study.

^aSome participants did not respond to this question, resulting in responses equating less than 100%.

All participants (100%) across both samples successfully completed SAGE-F. No individuals from either sample requested to prematurely terminate from either the treatment or the study. In contrast, data retention was increasingly difficult following participants’ completion from the treatment program. As a result, fewer individuals responded to outreach attempts as data progression progressed. (See Table 3 for changes in response rates across the duration of the study).

Table 3.

Descriptive Characteristics and Comparison.

Variable	Pilot Study		Current Study		t
Variable	n	M (SD)	n	M (SD)	t
PHQ-9^a
T1	33	12.76 (7.01)	35	13.89 (6.12)	−0.70
T2	18	9.61 (6.66)	27	10.30 (5.75)	−0.37
T3	13	6.15 (6.58)	7	5.86 (7.43)	0.09
GAD-7^b
T1	33	8.64 (4.99)	34	10.74 (5.51)	−1.64
T2	18	6.83 (5.66)	26	8.62 (5.85)	1.01
T3	13	4.54 (4.43)	7	4.00 (5.00)	0.25
SDS^c
T1	26	20.12 (5.41)	31	21.03 (4.65)	−0.68
T2	11	15.36 (6.19)	22	17.27 (6.36)	−0.82
T3	10	11.40 (6.67)	4	7.50 (4.51)	1.06
DERS-16^d
T1	33	16.64 (4.76)	33	17.12 (5.17)	−0.39
T2	18	13.39 (4.00)	26	15.54 (5.93)	−1.34
T3	12	14.50 (5.23)	5	6.80 (2.39)	3.11*
DSHI^e
T1	33	0.48 (0.51)	33	0.58 (0.50)	−0.80
T2	17	0.22 (0.43)	24	0.17 (0.38)	0.39
T3	12	0.25 (0.45)	5	0.20 (0.45)	0.21

Note. A comparison of descriptive data comparing the original pilot study’s findings (Taliercio et al., 2023) to that of the current study’s sample. An independent t-test was conducted for each variable in order to determine if significant differences exist between each sample. While the pilot study’s total sample size consisted of 35 and sample one within the current study consisted of 48 participants, in both studies, participants skipped responses across measures, resulting in smaller samples for each scale, with maximum samples of 33 and 35 being utilized within the final analyses, respectfully.

n = sample; M = mean; SD = standard deviation of the mean; t = independent t-test statistic. p ≤ .05.

^aDerived from the Patient Health Questionnaire – 9.

^bDerived from the General Anxiety Disorder – 7.

^cDerived from the Sheehan Disability Scale.

^dDerived from the Difficulties in Emotion Regulation Scale – 16, only utilizing the Strategies subscale.

^eDerived from the Deliberate Self-Harm Inventory, with T1 scores representing lifetime reports, and T2 and T3 indicating any additional self-harm behaviors since last assessment.

Materials

The Patient Health Questionnaire 9 (PHQ-9; Spitzer et al., 1999) is a self-report measure that was initially created and validated to assess depressive symptoms within a primary care unit. The PHQ-9 is a nine-item measure, with each item requesting an individual to endorse the severity of a given depressive symptoms over the previous two weeks. Individuals respond via a Likert scale, with zero indicating depressive symptoms are “not at all” present, and three indicating they are present “nearly every day.” Higher scores are indicative of more severe depression, with a potential maximum score of 27. Since its initial conceptualization, the PHQ-9 is continuously found to have strong psychometric properties, including good internal consistency reliability, across treatment settings (Beard et al., 2016; Costantini et al., 2021).

The Generalized Anxiety Disorder-7 (GAD-7; Spitzer et al., 2006), is a brief, seven-item, measure used to assess general anxiety symptom severity. Similar in structure to the PHQ-9, participants respond to each item by endorsing numbers on a Likert scale ranging from zero, “not at all,” to three, “nearly every day,” specifically in relation to their experiences over the previous two weeks. Higher scores are indicative of more severe anxiety. Since its creation, the GAD-7 remains a popular measure, and has been found to be psychometrically sound across treatment populations and settings, including strong internal consistency reliability and convergent validity. (Johnson et al., 2019; Mossman et al., 2017).

The Sheehan Disability Scale (SDS; Sheehan, 1983) is a three-item self-report questionnaire that assesses overall functioning capacities. Participants are asked to endorse items on a Likert scale, ranging from zero to 10, with higher scores being indicative of increased impairment in everyday functioning, such as one’s ability to satisfy demands at work or school. The SDS remains a popular, and psychometrically sound, measure, including one that maintains good construct validity and internal consistency reliability (Coles et al., 2014; Sheehan et al., 2016).

The Difficulties in Emotion Regulation Scale 16 (DERS-16; Bjureberg et al., 2016) is a 16-item self-report questionnaire, derived from the longer, 36-item, DERS (Gratz & Roemer, 2004), and assesses emotion regulation across five distinct subscales. Some items of the DERS-16 are reversed-score, and higher scores, across all subscales, represents greater emotion dysregulation. In an effort to replicate the procedures of the pilot study, only one subscale was used in the current study, the Strategies subscale. This five-item subscale, which requires individuals to endorse answers on a Likert scale, ranging from one to five, assesses an individual’s perceived ability to effectively access coping skills. Higher scores on the Strategies subscale indicates a perceived lack of coping abilities. The DERS-16 is regularly found to have strong psychometric priorities, including good test-retest reliability and concurrent validity across a variety of treatment settings and patient populations (Shahabi et al., 2018; Westerlund & Santtila, 2018).

The Deliberate Self-Harm Inventory (DSHI; Gratz, 2001) is a commonly used self-report measure that assesses intentional NSSIB. Each question of the 17-item measure asks participants to endorse whether or not they have engaged in a particular method of NSSIB. If a particular method is endorsed, participants are then prompted to provide additional information about their behavior, such as frequency and date since last engagement. Since its initial creation, the DSHI is regularly found to have strong psychometric priorities, including good test-retest reliability and strong internal consistency reliability across international communities (Ohira et al., 2018; Vigfusdottir et al., 2022). In the current study, participants were simply asked, categorically, if they have ever engaged in self-harm behavior. Replicating the pilot study, the current study utilized three distinct versions of the measure. At baseline, the DSHI evaluated lifetime prevalence, while at follow-up, questions were modified to examine any self-harm occurrences since last admission.

The DBT Ways of Coping Checklist (DBT-WCCL; Neacsiu et al., 2010) was initially developed to fill a clinical gap as at the time there was no assessment of an individual’s DBT skill use. Adapted from the Revised Ways of Coping Checklist (Vitalinao et al., 1985), the DBT-WCCL is a self-report measure that consists of 59-items, and asks participants to endorse how likely they are to respond to various stressors, ranging on a Likert scale from 0, “never used,” to three, “regularly used.” The DBT-WCCL consists of three subscales, all of which were used in the current study. The Skill Subscale reflects an individual’s tendency to utilize DBT skills, with higher scores indicative of more skill use. The Dysfunctional Skills Subscale estimates an individual’s general lack of skill, with higher scores indicating a more dysfunctional response style. Finally, the Blaming Subscale refers to an individual’s tendency to blame others for their difficulties, with higher scores representing more blaming tendencies. Since its initial creation, the DBT-WCCL’s is regularly found to have strong psychometric properties, such as both good internal consistency reliability and construct validity, resulting in its utilization in a variety of treatment settings (Burmeister et al., 2016; Stein et al., 2015), and remains a commonly-used measurement today (Kells et al., 2020).

Procedures

All patients (N = 154) enrolled in SAGE-F from June 2020 to October 2023 were invited to participate in the current study. Individuals were recruited to SAGE-F utilizing a variety of methods. Some patients were direct referrals from other mental health providers and programs, while others responded to Internet marketing campaigns, and some were self-referred. Prior to entering SAGE-F, and as part of the treatment protocol, prospective patients met with a SAGE-F group leader for orientation – where the program’s rules, structure, and expectations were clarified. At these meetings, patients were also informed of the potential to engage in the ongoing assessment of the program’s therapeutic potential. Individuals were instructed their participation in the study was completely voluntary and would have no impact on their treatment or their acceptance into the SAGE-F program. Individuals were given the option to engage in the treatment program and the study, or just the treatment program. Approximately 54% of all SAGE-F patients consented to participate in the current study, while approximately 46% of individuals consented to engage solely in the treatment program, volunteering not to enroll in the current study. Data from the first sample (n = 48) was collected from October 2021 through October 2023, while data from sample two (n = 83) was collected from June 2020 through October 2023. All participants were administered the complete set of measures at three distinct periods, prior to starting the SAGE-F treatment program (T1), immediately following their graduation from the program, six-weeks after their initial enrollment (T2), and three months following their graduation from the group (T3). All testing administration was conducted virtually. Participants received emails at T1, T2, and T3 with links to complete the testing battery. Demographic data was collected at T1, and significant life changes were assessed at T3. To reduce attrition from the study, participants were reminded to complete the measures around T3, with some being reminded before the measures were sent out, and others being contacted afterwards. Participants could choose to either engage in treatment solely via telehealth, solely in-person, or through a combination of both mediums. Individuals who declined to participate in the study were not asked for their reason in declining, and no demographic data was taken from these individuals. Participants were not provided compensation for their engagement with the study.

Data collection related to sample one was independent of the pilot study in an effort to ensure an independent evaluation of the initial findings on mood, self-harm, and functioning, while the collective sample was utilized to increase statistical power and to examine hypotheses unique to the current study such as achievement of developmental milestones and DBT skills growth.

Statistical Analysis

Sample one was utilized to re-examine the pilot study’s findings. To examine changes in mood, functioning, and perceived skill growth (Taliercio et al., 2023), one-way repeated-measures ANOVAs were calculated. These assessments examined differences from T1 to T3. Findings with either significant results or moderate-to-large effect sizes, which are comparable to the effect sizes found in the pilot study, were further evaluated via a-priori repeated-measures t-tests, specifically examining changes from T1 to T2, and then again from T2 to T3. For when response rates were limited, preventing one-way repeated-measures ANOVAs from being calculated, repeated-measures t-tests were calculated to examine changes over the treatment duration. In addition, Chi-square tests were calculated, to evaluate the changes in NSSIB across the treatment period. Finally, fifteen independent t-tests were utilized to compare the findings of the current study to that of the original pilot study, in an effort to ensure similar therapeutic effects were found across independent samples.

Sample two was used to assess the new hypotheses presented within the current study. First, four Chi-square tests were calculated to assess changes in developmental milestones. Next, three one-way repeated-measures ANOVAs were used to assess both changes in DBT skill growth and changes in ineffective coping techniques across the treatment period. Similar to the above analyses, either statistically significant findings, or those with moderate-to-large effect sizes were further assessed with a-priori repeated-measures t-tests. Finally, to compare an individual’s perceived coping abilities to their actual skill use, three composition scores were first composed, pooling responses across all three time periods, and then two Pearson correlations were calculated.

In an effort to maximize statistical power while accounting for missing data, all potential participants for a given analysis were included. Such an inclusionary criteria results in inconsistent sample sizes across statistical analyses; however, potential causes for attrition rates and inconsistent responses were considered, and reported below, corresponding with prior recommendations (i.e., Hughes et al., 2019).

A-priori power analyses were calculated utilizing G*Power 3.1 (Faul et al., 2009). Utilizing findings from our previous study as guidance, a minimal sample of 12 was calculated for the repeated-measures ANOVAs, using a two-tail design, alpha level of ≤.05, power-level of 80%, and a large effect size. Relying on these same parameters, a power analysis for the Chi-square tests concluded a minimal sample of 32 was required, while a power analysis for paired sample t-tests was calculated at 23.

Results

Replication of Pilot Study’s Findings Using an Independent Sample

In an attempt to re-assess our first study’s conclusions, we first examined change within sample one. Changes in depression scores were examined from T1 to T3. The overall analysis was found to be nonsignificant, but with a large effect size, F = 1.58, p = .28, η_p² = 0.35. Due to the effect size, follow-up repeated-measures t-tests were calculated. When comparing T1 (M = 14.70, SD = 5.72) to T2 (M = 9.90, SD = 6.39), the analysis was indicative of significant change, with a moderate effect size, t (19) = 2.61, p = .02, d = 0.58. The second repeated-measures t-test was calculated as nonsignificant, T2 (M = 6.50, SD = 3.70), T3 (M = 7.50, SD = 9.33), t (3) = −0.20, p = .85, d = −0.10.

An overall analysis of anxiety symptoms was found to be nonsignificant, but with a large effect size, F = 2.70, p = .15, η_p² = 0.47. Two follow-up repeated-measures t-tests were calculated. The first examined the differences between T1 (M = 11.85, SD = 5.58) and T2 (M = 8.00, SD = 6.32), and was found to be significant, with a moderate effect size, t (19) = 2.73, p = .01, d = 0.61. The second test, examining differences between T2 (M = 4.25, SD = 1.71) and T3 (M = 5.00, SD = 6.38), was found to be nonsignificant, t (3) = 0.40, p = .80, d = −0.81.

To examine changes in functioning capacities, a repeated-measures t-tests was performed. When examining the differences between T1 (M = 23.77, SD = 3.72) and T2 (M = 17.46, SD = 6.39), results were found to be was found to be significant, with a large effect size, t (12) = 3.46, p < .01, d = 0.96. An insufficient response rate prevented an examination at T3.

A single repeated-measures t-test examined changes in perceived skill knowledge. The differences between T1 (M = 18.16, SD = 4.63) and T2 (M = 13.58, SD = 5.66) were found to be significant, t (18) = 3.70, p < .01, with a large size, d = 0.85. As with examining functioning, an insufficient response rate prevented an examination at T3.

A Chi-square test was used to examine changes in NSSIB. Examining the differences in NSSIB from T1 to T2, results were found to be nonsignificant, X² (1) = 1.59, p = .21, with a medium effect size, φ = 0.31. Due to a low response rate at T3, differences of NSSIB between T2 and T3 could not be calculated.

Finally, in an attempt to compare the findings of the current study to that of the original pilot study, fifteen independent t-tests were conducted, examining differences in reported depression, anxiety, functioning, perceived coping capacities, and NSSIB between the pilot study and the current findings, at T1, T2, and T3 (see Table 3). Out of the fifteen calculations, only one was found significant. Specifically, a statistically significant, and large, difference was found between the perceived coping capacities, at T3, with the current study having a statistically significant smaller mean (M = 6.80, SD = 2.39) than the pilot study (M = 14.50, SD = 5.23), t (15) = 3.11, p < .01, d = 1.89.

Expansion of Pilot Study’s Findings Utilizing an Expanded Sample

To expand our understanding of the therapeutic effects of SAGE-F, we first examined changes in developmental milestones, utilizing sample two. Frequencies of reported lifestyle changes were first tallied at T3, (see Table 4). All participants (100%) at T3 had continued with individual psychotherapy and a majority had continued in some form of group therapy (62.80%). None had attempted suicide (0%), and a small percentage had visited the ER (8.60%) or entered an inpatient unit (4.20%) since completing SAGE-F. Frequencies were also tallied for a variety of typical developmental milestones for EAs, including examining those who graduated from school (0.0%), started a new romantic relationship (8.60%), or went on a job interview (18.60%). Four chi-square tests were calculated to assess for professional changes from T1 to T3. First, in assessing the change between students who were on academic leave at T1 to those who either resumed or entered a new school at T3, the results were found to be nonsignificant, with a small effect size, X² (1) = .28, p = .60, φ = −0.12. In assessing the contrast between those who were academically enrolled at T1 to those who withdrew from class at T3, the results were found to be nonsignificant, with a small-to-moderate effect size X² (1) = 0.80, p = .37, φ = −0.21. In assessing those who were unemployed, but not looking for work at T1, to those who either acquired or were actively interviewing for a job at T3, the results were found to be nonsignificant, with a small-to-moderate effect size, X² (1) = 1.30, p = .25, φ = 0.26. Relatedly, in assessing those who were unemployed at T1 but were looking to work, compared to those who either acquired or were actively interviewing for a job at T3, the results were also nonsignificant, with a large effect size, X² (1) = 2.96, p = .09, φ = 0.39.

Table 4.

Frequencies of Treatment and Life Updates, at Three-Month Follow-Up, and Lifestyle Change Compared to Pre-treatment.

Characteristic	n	%	X ²
Treatment changes
Suicide attempts	0	0.00
Inpatient hospitalization	1	4.20
ER visits	2	8.60
Continued individual therapy	24	100.00
Continued with group therapy	15	62.80
Entered intensive outpatient program	1	4.30
Entered partial hospitalization program	1	4.30
Entered peer-led support group	0	0.00
Life changes
Resumed school	7	29.20
Started a new school	3	4.30
Withdrew from school	3	4.30
Graduated from school	0	0.00
Academic-leave to academic-enrollment^a			0.28
Academic-enrollment to dropout^a			0.80
Interviewed for a new job	13	18.60
Lost a job	0	100.00
Left a job, on good terms	5	7.10
Left a job, on bad terms	0	0.00
Unemployed, seeking job, to interviewing/acquired^b			2.96
Unemployed, not job-seeking, to interview/acquired^b			1.30
Started a new romantic relationship	6	8.60
Ended a romantic relationship	3	4.30
Experienced serious illness, injury, or disability	1	1.40
Engaged or married	0	100.00
Divorced	0	100.00
Pregnant or gave birth	0	100.00
Death of friend or family member	3	4.30
Serious legal trouble	1	1.40

Note. When assessing frequencies, categories were not mutually exclusive, with patients having the ability to endorse responses across different dimensions. In assessing Chi-Square analyses, responses were grouped to ensure responses were mutually exclusive, satisfying statistical assumptions. All Chi-Square tests were nonsignificant.

n = sample; % = percent of sample; X² = chi-square value.

^aResponses related to resuming school and starting a new school, at program intake, were grouped and compared to either new academic enrollments or academic dropout at the three-month follow-up.

^bAn individual’s unemployment status at program’s intake was compared to their endorsement of either securing job interviews or acquiring a job at follow-up.

DBT-based coping capacities were assessed with three distinct one-way repeated-measures ANOVAs (see Table 5). First, we examined participants’ self-reported DBT skill use. Overall, no significant change was observed, F = 2.68, p = .10, although a large effect size was calculated, η_p² = 0.20. Due to the significant effect size, follow-up repeated-measures t-tests were calculated. The analysis found a significant, moderate, difference between T1 (M = 1.97, SD = 0.53) and T2 (M = 2.30, SD = 0.62), t (19) = −2.52, p = .02, d = −0.53, and no significant difference between T2 (M = 2.35, SD = 0.49) and T3 (M = 2.28, SD = 0.45), t (11) = .59, p = .57, d = 0.17. In examining dysfunctional skill use, the overall analysis yielded significant results, with a large effect size, F = 13.42, p < .01, η_p² = 0.53. In comparing T1 (M = 3.20, SD = 0.61) to T2 (M = 2.33, SD = 1.01), the results were found to be significant, with a large effect size, t (21) = 4.74, p < .01, d = 1.01, while the comparison between T2 (M = 2.11, SD = 1.10) and T3 (M = 1.88, SD = 1.04), was found to be nonsignificant, t (12) = 0.99, p = .34, d = 0.28. Finally, participants’ overall tendency to blame others significantly changed across the treatment period, F = 3.62, p = .04, with a large effect size, η_p² = 0.23. Specifically, the change from T1 (M = 1.55, SD = 0.95) to T2 (M = 1.01, SD = 0.77) was significant, t (21) = 2.30, p = .03, with a large effect size, d = 0.49, while the difference between T2 (M = 0.83, SD = 0.82) and T3 (M = 0.83, SD = 0.78), was nonsignificant, t (12) = 0.00, p = 1.00, d = 0.00.

Table 5.

Descriptive Characteristics for DBT Ways of Coping Checklist.

Subscales	n	M	SD
Skills
T1	51	1.84	0.66
T2	26	2.33	0.61
T3	16	2.26	0.41
Dysfunction
T1	52	3.05	0.66
T2	28	2.39	0.99
T3	18	1.74	0.95
Blame
T1	54	1.57	0.88
T2	28	1.14	0.85
T3	18	0.78	0.70

Note. Descriptive statistics related to the three subscales of the DBT-Ways of Coping Checklist. Higher values within the skills subscale indicates increased skillfulness, while higher scores on the Dysfunction and Blame subscales indicate poorer functioning. All responses to the DBT-Ways of Coping Checklist consisted of participants from sample two. While sample two consisted of 83 participants, some participants either skipped this measure entirely or some skipped individual items within the measure. In such cases, total scores could not be calculated for these participants, resulting in a lower sample size for this measure.

n = sample; M = mean; SD = standard deviation of the mean.

The final set of analyses examined the differences between perceived coping abilities and self-reported coping behaviors. First, three composite scores were calculated for the DERS Strategies and DBT-WCCL Skills and Dysfunctional Subscales, allowing responses across the three time periods to be condensed to one variable each. The first calculated correlation examined the association between the Strategies and Skills subscales, and was found to be nonsignificant, r (13) = −0.7, p = .81. The second correlation, examining the Strategies and Dysfunctional subscales, was found to be significant, with a moderate correlation, r (13) = 0.63, p = .02.

Discussion

Given persistent concerns over replication within social sciences (Wiggins & Christopherson, 2019), the first goal of the current study was to re-examine the findings from our pilot study using a larger sample. In our pilot study (Taliercio et al., 2023), we demonstrated that the completion of the six-week SAGE-F treatment program corresponds to moderate reductions in depression, large reductions in anxiety, large improvements in functioning capacity, large improvements in perceived coping capacities, and large reductions in NSSIB, with no significant gains lost, when assessed at three-month follow-up. In the current study, we reevaluated these previous findings, with an independent sample, hypothesizing that similar results would be found. The results partially support our hypothesis. Corresponding to our original findings, the current study continues to support that the completion of SAGE-F, a six-week-long intensive program, when compared to baseline, is associated with moderate reductions in depression, and large improvements in both functional capacities and perceived coping strategies.

In contrast to the original study, SAGE-F completion was associated with the immediate, moderate, reductions in anxiety, relative to baseline. And although we did not observe a statistically significant change in NSSIB, a reduction was observed between T1 and T2. Despite these two minor reductions in the therapeutic effects between the pilot study and the current study, notably, improvements in mood and self-harm behaviors continued to be maintained for at least three months in those who completed follow-up measures – although fewer subjects completed measures at T3 in the current study compared to the pilot study. Historically, strong gains from intensive programs are often lost upon treatment termination (Sharma & Math, 2019). While further, experimental and randomized, assessment is warranted before suggesting SAGE-F contrasts expected trends, the current study does continue to support that the program’s value of being a powerful intensive program, with long-term benefits. Further exploration into the long-term benefits, especially if they are in contrast with prior findings, is warranted.

We also found that the current study’s pre- and post-treatment findings were statistically similar to those of the pilot study’s pre- and post-treatment findings, with one exception. Participants within the current study demonstrated similar mood dysregulation, NSSIB, perceived skills use, and overall functioning at baseline compared to participants within the original pilot study. Furthermore, the therapeutic gains from the current study resembled that of the pilot study, both in terms of immediate (at T2) and maintenance (at T3) effects. The one exception pertains to participants’ perceived coping capacities. Individuals from the current study reported a more significant improvement at T3, compared to those of the pilot study, indicating that participants in the current study gained more from the treatment.

However, despite the fact that results from the current study and the pilot study are comparable, when examining change within the current sample one, none statistically significant improvements in NSSIB were found between T1 to T2. Given that the reduction in NSSIB was similar in both the pilot and current studies, the lack of statistical significance in the current study may be the result of a smaller sample size. Given the statistically nonsignificant difference and the moderate effect size calculated within the current study, it is possible that a larger response rate at T3 would have resulted in a statistical change, which may have yielded a similar finding to that of the pilot study.

In summary, the observed therapeutic gains within the independent sample of the current study are comparable to the findings of the pilot study, lending support that the therapeutic gains observed across these two studies are valid and representative of expected treatment experiences. Further, and while not necessarily a hypothesis of this study, since a majority of participants in the pilot study engaged in treatment via telehealth visits, while a majority of the current study’s participants were physically present for SAGE-F, and the findings were comparable across samples, the current study may also support the potential that SAGE-F is effective whether delivered virtually or in-person. These findings are reflective of contemporary research that demonstrates that telehealth treatment is equally effective as in-person treatment (Snoswell et al., 2023).

We also examined significant lifestyle changes and milestone achievement in this study. While none of the participants dropped out of school between treatment completion and three-month follow-up, participants who were on academic leave did not report re-enrolling in school. Further, the completion of the 6-week SAGE-F program was not associated with gains in employment, regardless of whether participants were interested or not interested in being employed when first enrolling in SAGE-F. However, given that the effect size was large, it is possible that these results would have been significant with greater statistical power. In summary, however, EA achievement of developmental milestones does not appear to be associated with the completion of SAGE-F. Further, while none of the participants dropped out of school over the duration of treatment, it is beyond the current scope to determine if SAGE-F is protective against academic dropout or if this is reflective of a correlational relationship.

The current study also found that, when compared to baseline, the completion of SAGE-F is associated with moderate increases in DBT skill use and large decreases in dysfunctional skill use, such as a tendency to blame others when stressed. Further, the increase in skillfulness appears to be maintained for at least three months. Interestingly, while a participant’s skill use was not necessarily associated with one’s perceived coping capacity, an individual’s dysfunctional skill use was associated with one’s perceived lack of skill capacity. Previous researchers have attempted to discern how EAs comprehend their physical and psychological wellbeing, with researchers advocating that EAs place more emphasis on their impairment, which, in turn, can impair their ability to progress through treatment (McCloughen et al., 2016). Our findings appear to correspond with this claim. EAs may be better at estimating their dysfunctional coping behaviors, rather than their actual DBT skill use, even underreporting their clinical skill capacities. Specifically, EAs may not be as accurate in assessing their skill use, which could be targeted using cognitive strategies; however, they have increased insight into their struggles. Such findings may need to be considered in an effort to accurately assess clinical severity when working with EAs.

In addition to the results presented above, the current study implemented a number of recommendations made in our first publication. Adjunctive treatment enrollment was assessed, and the definition of treatment gains was expanded from the original study to include both effective coping and dysfunctional skill use. In addition, the samples were expanded to include more demographic diversity, such as increased variations in education, race, and sexual orientation, allowing for improved external validity. Furthermore, by combining sample one and sample two, the current study benefited from increased statistical power as compared to the original pilot study. Finally, the pilot study only examined participants’ engagement in SAGE-F program during the peak COVID-19 pandemic, resulting in participation exclusively occurring virtually. The current study, in contrast, included individuals who participated both virtually and in-person. In summary, this expanded study further supports our original conclusion that SAGE-F is an effective treatment for EAs, and is associated with therapeutic gains when implemented in both virtual and in-person settings.

Limitations and Future Studies

First, as with our pilot study, the current study utilizes a pre-post design, with no control group or randomization. Without such a format, analyses can only examine associations between the treatment and therapeutic gains, rather than the comparable impact of such a program. Second, data was collected via self-report questionnaires. While included measures were psychometrically sound and commonly used, the data may be limited using self-report measures, especially when assessing skill growth. Future studies may benefit from more behaviorally-focused assessments of skill growth. Utilizing a behavioral observation may also help address the observed discrepancy between perceived skill use and actual skill use. Third, while the current study examined participants who participated both virtually and in-person, future studies should examine, when given a choice, who, and why, some prefer one method over another. Finally, the impact of compounding variables was not assessed, including group member cohesion, the role of ongoing treatment, and homework completion – all of which may have impacted the reception and internalization of the treatment material. Future studies need to evaluate the potential impact of such variables.

Another significant limitation relates to the current study’s sample size. As a product of longitudinal data collection attrition, the available sample varied across testing periods and individual measures. Despite the authors’ attempts at reducing participant attrition, the current study included more study attrition compared to the pilot study. This change is not reflective of poor treatment compliance. Instead, researchers continued to experience difficulty acquiring three-month follow-up data. While there were attempts at maintaining research compliance across the study, the effort did not appear to be as successful as anticipated. It is possible participants were more willing to answer follow-up questionnaires during the pilot study, as this was during the peak of the COVID-19 pandemic, and individuals had fewer life demands (Droit-Volet et al., 2020). In addition, the role of a self-selecting bias must be considered. It is possible those who responded to the treatment were more likely to respond due to their therapeutic gains. Given the current study’s finding that individuals performed notably better in terms of perceived coping strategies, compared to the pilot study, it is possible only those who benefit most from the current study were willing to respond months after completing the treatment program. This self-selecting bias may also explain why a ceiling effect was observed when assessing NSSIB. While little change was observed from T1 to T2, participants reported little NSSIB at baseline, resulting in a perception that NSSIB is not significantly altered by SAGE-F. Finally, the order the measures were administered may have also contributed. More individuals provided responses at T3 for measurements related to anxiety and depression, when compared to other measurements within the battery. Questions related to mood were found earlier in the battery, suggesting that the testing battery may have been too long, and resulted in individuals either timing-out or prematurely exiting the testing battery. Future studies should therefore rely on a shorter testing battery. As a result of the study attrition rate, and varied responses across items, the statistical power varied across analyses, and was even underpowered with some analyses. Such limitations may be at least partially resolved by overing compensation to participants.

Additional limitations are present within our study that were not present in the pilot study, specifically in relation to our analysis of lifestyle changes. It is important to note that we did not directly assess individual goals prior to entering SAGE-F. For example, while our study did not find an association between SAGE-F and the likelihood that an individual re-enters school, we did not ask participants if their goal was to return to school at baseline. The evaluations presented here represent a change in frequency, rather than individuals’ desired goals. We did not assess desired lifestyle changes. Our analysis assumes participants had intended to make changes in such areas, when in fact some participants may not have been hoping for such change. Therefore, while it is informative that participants did not demonstrate any changes in occupational and lifestyle functioning with the completion of SAGE-F, we remain hesitant about drawing conclusions about the direct impact of the program on a given individual’s occupational and lifestyle changes. Relatedly, in assessing such developmental milestones, our response rates were also low, which may further indicate a problem with attrition at T3, or a self-selecting bias. Finally, it is possible individuals did plan on returning to school; however, their return was scheduled to occur at a later time. For example, individuals who were planning on returning in the spring, may have reported they still had not returned to school in the fall, thereby resulting in a false negative. It is also possible that completion of additional phases in the Sage treatment program, which could focus on skills generalization or overcoming avoidance, would result in greater achievement of developmental milestones, which can be examined in future studies.

Summary

The current study supports the findings of our pilot study, and expands upon our understanding of the therapeutic potential of SAGE-F. The current study continues to demonstrate that SAGE-F remains an effective DBT treatment for EAs, and is associated with improvements in mood, overall functioning, and skill use. Further, a number of improvements remained present for at least three months following treatment completion. Overall, the current study is comparable to our initial examination of the SAGE-F treatment program. SAGE-F appears not to be associated with significant changes in developmental milestones, such as acquiring a job or completing college; however, such a conclusion may be limited by the current methodology or may suggest that participants need additional phases of the Sage treatment program. Evaluation of SAGE-F is ongoing and will continue to evaluate the therapeutic potential of the program, while reducing the limitations presented within the current study.

Supplemental Material

Supplemental Material - Re-Assessment and Extension: An Ongoing Evaluation of The System for Adult Growth and Emergence-Foundations, a Modified DBT Program to Aid Emerging Adults With Emotion Regulation and Transition

Supplemental Material for Re-Assessment and Extension: An Ongoing Evaluation of The System for Adult Growth and Emergence-Foundations, a Modified DBT Program to Aid Emerging Adults With Emotion Regulation and Transition by Joseph R. Taliercio, Talia Wigod, Joy Shen, Jazmin Garcia, Suzanne Davino, Elaina Servidio, Erin Sparapani, Lata K. McGinn, and Alec L. Miller in Emerging Adulthood

Footnotes

Declaration of Conflicting Interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) received no financial support for the research, authorship, and/or publication of this article.

Ethical Statement

Informed Consent

Informed consent was obtained from all individual participants included in this study.

Transparency and Openness Statement

The raw data, analysis code, and materials used in this study are not openly available but are available upon request to the corresponding author.

ORCID iD

Joseph R. Taliercio

Supplemental Material

Supplemental material for this article is available online.

Author Biographies

Joseph R. Taliercio is a Clinical Psychologist and Coordinator of Research at Cognitive and Behavioral Consultants (CBC), a group practice located both in both the cities of New York and White Plains, where he conducts individual and group treatments, and specializes in emerging adults, severe mental illness, clinical-health, and environmental psychology. Within the current study, Joseph has served as the principal investigator for the study, aiding with the study design, procedural preparation, data collection, data analysis, and the implementation treatment protocols. He also served as the primary author for the current manuscript.

Talia Wigod is a Clinical Psychologist and Research Director at Cognitive and Behavioral Consultants (CBC), a group practice located both in both the cities of New York and White Plains, where she conducts individual and group treatments, and specializes in children, parent-child interactive therapy (PCIT), dialectical behavioral therapy (DBT), and dissemination. Within the current study, Talia has served as a researcher, aiding with the study design, procedural preparation, data collection, and the implementation of treatment protocols. Further, she has served as an editor for the current manuscript.

Joy Shen is the Chief Research Assistant at Cognitive and Behavioral Consultants (CBC), a group practice located in both the cities of New York and White Plains, where they coordinate and oversee all ongoing research projects. Joy is also a graduate student at Ferkauf Graduate School of Psychology, where they specialize in school-based mental health. Within the current study, Joy has served as a researcher assistant, aiding with the study design, procedural preparation, data collection, and implementation of treatment protocols. Further, they have served as an editor for the current manuscript.

Jazmin Garcia is a Research Assistant at Cognitive and Behavioral Consultants (CBC), a group practice located in both the cities of New York and White Plains, where she helps ensure ongoing research projects are effective and adhere to strict protocol. Jazmin is also entering Teacher’s College at Columbia University as a graduate student of psychology. Within the current study, Jazmin has served as a researcher assistant, aiding with the study design, procedural preparation, data collection, and treatment protocol implementation. Further, she has served as an editor for the current manuscript.

Suzanne Davino is a currently Founder of White Cedar Cognitive and Behavioral Health, a private practice in Ridgefield, CT, and previous Senior Director of Young Adult Programs at CBC in White Plains, NY, Suzanne specializes in dialectical behavioral therapy (DBT) and emerging adults. Within the current study, Suzanne has aided with the initial study conceptualization and design, procedural preparation and data collection. Further, she has served as an editor for the current manuscript.

Elaina Servidio is a current Coordinator of SAGE Programs at Cognitive and Behavioral Consultants (CBC), a group practice located both in both the cities of New York and White Plains, where she conducts individual and group treatments, and specializes in cognitive behavioral therapy (CBT), dialectical behavioral therapy-prolonged exposure (DBT-PE), and emerging adulthood. Within the current study, Elaina has aided with the initial study conceptualization and design, procedural preparation, treatment protocol implementation, and data collection. Further, she has served as an editor for the current manuscript.

Erin Sparapani is the current Director of QI, Clinical Assessment and Program Evaluation, and SAGE Program at Cognitive and Behavioral Consultants (CBC), a group practice located both in both the cities of New York and White Plains, where she conducts individual and group treatments, and specializes in dialectical behavioral therapy (DBT), cognitive behavioral therapy (CBT), trauma, and neurodivergent young adults. Within the current study, Erin has aided with procedural preparation, treatment protocol implementation, and data collection. Further, she has served as an editor for the current manuscript.

Lata K. McGinn is a Co-founder and Co-director of Cognitive and Behavioral Consultants, Director of the cognitive behavioral therapy (CBT) training program at the Ferkauf Graduate School of Psychology at Yeshiva University, vice-president of the Access Psychology Foundation (a non-profit that aims to increase clinical training and therapeutic access to underserved communities), and president of the World Confederation of Cognitive and Behavioral Therapies. Within the current study, Lata has aided with the study design and procedural preparation. Further, she has served as an editor for the current manuscript.

Alec L. Miller is a Co-founder and Co-director of Cognitive and Behavioral Consultants, Clinical Professor of Psychiatry and Behavioral Sciences at Montefiore Medical Center/Albert Einstein College of Medicine, and president of the Access Psychology Foundation (a non-profit that aims to increase clinical training and therapeutic access to underserved communities). Within the current study, Alec has aided with the study design and procedural preparation. Further, he has served as an editor for the current manuscript.

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