Impact of Insomnia Treatment on Veterans’ Willingness to Seek Treatment for Comorbid Health Conditions

Abstract

Objectives:

This study aimed to determine the extent to which Cognitive Behavioral Therapy for Insomnia (CBT-I) influences participant willingness to seek treatment for other prevalent health conditions. We hypothesized that, relative to sleep hygiene control, CBT-I would be associated with increased willingness to seek treatment for alcohol use, depression, anxiety, PTSD, and chronic pain.

Method:

Data were derived from a randomized controlled trial comparing the efficacy of CBT-I to sleep hygiene control among heavy-drinking Veterans with insomnia (N=70; 57 men, 13 women; age M=37.6, SD=9.4).

Results:

At the end of treatment, across both groups, participants reported most willingness to seek treatment for insomnia (M=3.08, SD=1.04), followed by chronic pain (M=2.82, SD=1.21), anxiety (M=2.76, SD=1.24), depression (M=2.75, SD=1.29), PTSD (M=2.61, SD=1.27), and alcohol use (M=2.51, SD=1.19). Relative to those in sleep hygiene, CBT-I participants reported increased willingness to seek treatment for insomnia [F(1,48)=10.25, p=.002, d=0.86] and chronic pain [F(1,48)=5.76, p= 0.02, d=0.60]. No other group-by-time interactions were significant.

Conclusions:

CBT-I does increase willingness for future treatment, but only treatment targeting insomnia and chronic pain. Continued research on how to engage Veterans in evidence-based treatment for common mental health concerns (e.g., alcohol use, depression, anxiety, and PTSD) is needed.

INTRODUCTION

Military service is associated with mental health problems like depression, anxiety, post-traumatic stress disorder (PTSD), and substance use disorders (Barlas et al., 2013). However, among Veterans, willingness to seek treatment for mental health conditions (~64%) tends to be lower than willingness to seek treatment for physical health conditions like cancer or hypertension (~72%) (Corrigan et al., 2000; Miller et al., 2022). This comparatively low willingness to seek mental health care has been attributed to stigma, culture, and understanding of treatment options. For example, in a national sample of Veterans returning, one in four participants indicated that they would think less of themselves if they sought mental health treatment, one in three said they would feel uneasy talking with a mental health provider, and more than half (59%) agreed that a problem would have to be “really bad” to seek mental health treatment (Vogt et al., 2014). Many military personnel also value self-reliance and prefer to manage problems themselves, which decreases likelihood of getting treatment (Britt et al., 2016). Finally, it is possible that individuals with mental health disorders hesitate to seek treatment because they are not sure what the treatment involves or how effective it will be. Indeed, one of the few variables that separates those who consider treatment from those who do not is positive beliefs about the treatment itself (Britt et al., 2016).

In contrast to the stigma surrounding other mental health conditions, insomnia has been identified as a health concern that “brings soldiers into mental health treatment” (Hom et al., 2016). In the 2019-2020 National Health and Resilience in Veterans Survey, approximately two in five Veterans met diagnostic criteria for clinical or subthreshold insomnia (Byrne et al., 2021). Insomnia can exacerbate other mental health conditions (e.g., depression, PTSD, substance use), but tends to be less stigmatized (Gutner et al., 2018; Hom et al., 2016; Miller et al., 2022). Indeed, 67% of Veterans returning from Iraq and Afghanistan describe sleep as one of their primary barriers to optimal productivity (Plach & Sells, 2013), and twice as many prefer behavioral strategies to medication for sleep problems (79% vs 37%) (Shepardson et al., 2014). Given these patient perspectives, Cognitive Behavioral Therapy for Insomnia (CBT-I) has been proposed as a “gateway” to other mental health treatment (Fucito et al., 2017; Gutner et al., 2018; Hom et al., 2016).

Intuitively, a successful mental health treatment experience or strong therapeutic alliance may increase openness to future treatment experiences. Specifically, evidence that mental health treatment is effective for insomnia may strengthen the belief that it will work in other contexts (e.g., for alcohol use), which may increase willingness to seek mental health treatment for other disorders as well (Britt et al., 2016). Consistent with this idea, older adults who participated in either mindfulness or CBT for anxiety reported more positive attitudes toward mental health treatment-seeking than those who did not receive treatment (Aisenberg-Shafran & Shturm, 2022).

This study aimed to determine the extent to which CBT-I influenced participant willingness to seek treatment for other prevalent health conditions; specifically, alcohol use, depression, anxiety, PTSD, and chronic pain. Data were derived from a randomized controlled trial examining the efficacy of five-session Cognitive Behavioral Therapy for Insomnia (CBT-I) relative to single-session sleep hygiene control among heavy-drinking Veterans with insomnia (clinicaltrials.gov #NCT03804788). As previously documented (Miller et al., 2024), CBT-I participants reported greater post-treatment reductions in insomnia severity than sleep hygiene controls. This study tested the extent to which treatment for insomnia increased willingness to seek treatment for other mental health conditions within this sample. Specifically, we hypothesized that CBT-I would increase willingness to seek treatment for alcohol use, depression, anxiety, PTSD, and chronic pain.

MATERIALS AND METHODS

Participants and Procedure

Recruitment spanned June 2019 through March 2023. Veterans who served in the United States military after September 11, 2001 were recruited via digital marketing to participate in an insomnia treatment study for Veterans who drink alcohol. Of the 1064 individuals who completed the screening questionnaire, 155 provided informed consent and completed baseline assessments. During baseline, participants completed a semi-structured clinical interview with doctoral students in clinical or counseling psychology, a retrospective self-report survey, and 14 days of sleep diaries. Individuals were eligible to participate if they (a) verified military service after 9/11/2001, (b) reported at least one heavy drinking episode (≥4/5 drinks for women/men) in the past month, and (c) met research diagnostic criteria for insomnia disorder (e.g., >30min sleep onset latency or wake after sleep onset on +3 days per week for 3+ months, as reported during the clinical interview) (Edinger et al., 2004; Lichstein et al., 2003). Participants were excluded if they reported mania, seizures or suicidal intent; worked overnights; were currently in alcohol treatment; or lived in a state where the principal investigator was not licensed.

Seventy-one participants (see Table 1) were randomly assigned to CBT-I (n=38) or sleep hygiene control (n=33; treatments described in more detail below). Both treatments were delivered individually by doctoral students who were trained to provide both CBT-I and sleep hygiene. Sessions could be completed in-person or via telehealth. Clinical hours were supervised by a licensed clinical psychologist (MBM), who in turn was supervised by a Diplomate of Behavioral Sleep Medicine (CSM). At the end of the five-week treatment period (“post-treatment”), participants completed another self-report survey assessing willingness to seek treatment. Participants were compensated up to $300 for completing all aspects of the parent study.

Table 1.

Participant characteristics at baseline (N=70).

	Full Sample (N = 70)	CBT-I (N = 38)	Sleep Hygiene (n = 32)
Characteristics	n (%) or M (SD)	n (%) or M (SD)	n (%) or M (SD)
Age	37.64 (9.42)	37.11 (7.65)	38.28 (11.25)
Male sex	57 (81%)	32 (84%)	25 (78%)
Race/ethnicity	---	---	---
Black only	3 (4%)	3 (8%)	0 (0%)
Multiracial or multiethnic	8 (11%)	2 (5%)	6 (18%)
White only	54 (77%)	29 (76%)	25 (78%)
Asian, Am. Indian, or Hispanic/Latinx*	5 (7%)	4 (11%)	1 (3%)
Highest level of education	---	---	---
High school	4 (6%)	1 (3%)	3 (9%)
Some college	29 (41%)	15 (40%)	14 (44%)
College graduate	18 (26%)	14 (37%)	4 (12%)
Graduate school (partial or complete)	19 (27%)	8 (21%)	11 (34%)
Military status1	---	---	---
Active duty	20 (28%)	9 (24%)	11 (33%)
Reserves	10 (14%)	5 (13%)	5 (15%)
Veteran	50 (71%)	27 (71%)	23 (72%)
Branch1	---	---	---
Air Force	6 (9%)	3 (8%)	4 (12%)
Army	48 (69%)	26 (70%)	22 (69%)
Marines	11 (16%)	7 (19%)	4 (12%)
Navy	4 (6%)	1 (3%)	3 (9%)
Insomnia severity (ISI), M (SD)	17.09 (4.29)	17.29 (4.39)	16.84 (4.21)
Hazardous drinking (AUDIT), M (SD)	12.59 (6.46)	11.92 (6.80)	13.37 (6.03)
Positive screen (≥8), n (%)	55 (79%)	29 (76%)	26 (81%)
Pain rating (VAS), M (SD)	30.03 (23.63)	27.11 (22.80)	33.42 (24.49)
Moderate to severe pain (≥40), n (%)	18 (26%)	7 (19%)	11 (34%)
Depressive symptoms (PHQ-9), M (SD)	10.10 (4.73)	10.32 (4.99)	9.84 (4.48)
Positive screen (≥10), n (%)	36 (52%)	20 (54%)	16 (50%)
Anxiety symptoms (GAD-7), M (SD)	8.30 (5.06)	7.87 (5.04)	8.81 (5.11)
Positive screen (≥10), n (%)	22 (31%)	11 (29%)	11 (34%)
PTSD symptoms (PCL-5), M (SD)	25.22 (18.33)	26.82 (18.93)	23.25 (17.71)
Positive screen (≥31), n (%)	27 (39%)	16 (43%)	11 (34%)
Lifetime history of treatment, n (%)	54 (77%)	30 (79%)	24 (75%)
Current (past month) treatment, n (%)	15 (21%)	8 (21%)	7 (22%)

Note. *Other racial/ethnic groups combined to protect confidentiality (<1 per group). ¹Not mutually exclusive. Tx=treatment.

Interventions

Cognitive Behavioral Therapy for Insomnia (CBT-I) was delivered in a five-session protocol modeled after the VA’s therapist manual (Manber et al., 2008). In Session 1, therapists reviewed the treatment rationale, oriented participants to their sleep diary data, and educated participants on sleep hygiene. Therapists also helped participants identify a consistent waketime for the remainder of treatment and instructed participants not to nap. In Session 2, therapists introduced stimulus control and sleep restriction; in Session 3, relaxation techniques; and in Session 4, cognitive therapy. Session 5 focused on insomnia relapse prevention.

Sleep hygiene was delivered in a single session to model “usual care.” Therapists reviewed the same sleep hygiene handout provided to CBT-I participants, but this was the only “sleep” intervention the control group received. Participants were asked to identify 1-2 recommendations they wanted to prioritize over the next 5 weeks.

Personalized normative feedback.

In both conditions, interventionists presented data comparing the number of drinks participants consumed each week to the number of standard drinks consumed by same-sex Veterans (descriptive norm) and the number of drinks they reported believing that same-sex Veterans consume (injunctive norm). Data were derived from a previous national study of Veterans (Pedersen et al., 2015) and were presented with the sleep hygiene recommendation to moderate alcohol use before bedtime.

Measures

Treatment satisfaction.

Participants rated their satisfaction with treatment on the 8-item Client Satisfaction Questionnaire (Larsen et al., 1979). Items prompt participants to indicate the quality of treatment received, the extent to which it met their expectations and needs, and the likelihood they would recommend it to a friend or use it again. Responses ranged from 1 (e.g., poor, definitely not) to 4 (e.g., excellent, definitely yes). This measure has demonstrated predictive validity among adults with substance use disorders (Kelly et al., 2018). In this sample, internal reliability was strong (α=.94).

Treatment willingness.

A modified version of the Treatment Willingness Scale (Miller et al., 2022) assessed participants’ willingness to seek treatment for insomnia, alcohol use, chronic pain, depression, anxiety, and PTSD. Participants rated the extent to which they agreed with the statement, “If I had problems related to [X], I would feel comfortable seeking treatment for it,” on a scale from 0 (strongly disagree) to 4 (strongly agree). Since this study aimed to determine change in interest for each individual health condition, we did not conduct analyses to confirm the factor structure of the overarching scale. However, participants’ responses to these items demonstrated internal consistency at baseline (α=0.85) and post-treatment (α=0.89).

Comorbid health conditions.

Widely-used screening measures that have been validated in general adult populations were included at baseline to screen for comorbid health conditions. All participants screened positive for insomnia (scores ≥10) on the Insomnia Severity Index (Morin et al., 2011). Scores ≥8 on the Alcohol Use Disorder Identification Test (AUDIT, total scores range 0-40) were used to indicate harmful drinking behavior (Saunders et al., 1993). We did not include a retrospective measure of pain intensity at baseline; however, participants rated their pain intensity on sleep diaries each day using a numeric rating scale from 0 (no pain) to 100 (worst pain possible) (Krebs et al., 2007). Average scores ≥40 were categorized as moderate to severe pain (Boonstra et al., 2016). Participants were categorized as screening “positive” for depression if they scored ≥10 on the Patient Health Questionnaire (PHQ-9, total scores range 0-27) (Kroenke & Spitzer, 2002); positive for anxiety if they scored ≥10 on the Generalized Anxiety Disorder screening (GAD-7, total scores range 0-21) (Spitzer et al., 2006); and positive for PTSD if they scored ≥31 on the PTSD Symptoms Checklist for DSM-5 (PCL-5, total scores range 0-80) (Bovin et al., 2016).

Data Screening and Analysis

Analyses were conducted in IBM SPSS Statistics version 29. Descriptive statistics were used to characterize participants’ satisfaction with CBT-I and willingness to seek treatment for other health conditions. Correlations between treatment willingness outcomes are depicted in Table 2. We then used repeated measures analyses of variance (ANOVA) to characterize differences between groups, with time (baseline to post-treatment) as the within-group factor and treatment condition (CBT-I or sleep hygiene) as the between-group factor. We chose individual ANOVAs over multivariate ANOVA because (a) we were interested in change in willingness to seek treatment for each individual health condition, rather than a composite “change in willingness to seek treatment” variable, and (b) Box’s test of equal covariances was significant, indicating differences in covariance structures across groups [F(21, 8561)=1.99, p=.005]. Within-group effect sizes were estimated as a function of change in means, standard deviations, and pre- and post-score correlations (δ_RM; see Morris & DeShon, 2002). Between-group Cohen’s $d$ values were calculated using the following formula (Wilson, 2023):

$$d=t\sqrt{(n1+n2)∕n1n2}$$

Table 2.

Correlation matrix of treatment willingness (N=70).

	Tx history	BL insomnia	BL alcohol	BL depr.	BL anxiety	BL PTSD	BL pain	PT insomnia	PT alcohol	PT depr	PT anxiety	PT PTSD
BL insomnia	.22	---
BL alcohol	.25*	.57*	---
BL depression	.13	.54*	.34*	---
BL anxiety	.19	.58*	.31*	.89*	---
BL PTSD	.18	.40*	.35*	.59*	.56*	---
BL pain	.09	.74*	.47*	.63*	.58*	.40*	---
PT insomnia	.22	.24	.34*	.30*	.45*	.33*	.17	---
PT alcohol	.06	.13	.36*	.30*	.25	.26	.30*	.54*	---
PT depression	.06	.32*	.28	.37*	.35*	.36*	.49*	.60*	.62*	---
PT anxiety	.11	.23	.22	.46*	.42*	.37*	.44*	.59*	.60*	.92*	---
PT PTSD	−.004	.09	.17	.32*	.32*	.51*	.22	.39*	.56*	.67*	.74*	---
PT pain	.03	.31*	.27	.37*	.36*	.21	.50*	.60*	.59*	.70*	.68*	.55*

Note. BL=baseline. Depr=depression. Pain=chronic pain. PT=post-treatment. Tx=treatment.

Listwise deletion was used for missing data in repeated measures ANOVAs. Participants who were missing treatment willingness data at post (n=20) did not differ significantly from those without missing data (n=51) in age, insomnia severity, treatment willingness (for any health condition), drinking quantity, mental health symptoms (anxiety, depression, PTSD), or chronic pain at baseline (all p>.05). Similarly, they did not differ from those with complete data in terms of sex [χ¹(1)=0.001, p=.97], treatment group [χ¹(1)=0.02, p=.88], or most race/ethnicities (all p>.10). However, we recruited only two participants who identified as Asian, and neither completed the Treatment Willingness Questionnaire following treatment; therefore, those with missing data were more likely to be Asian than any other race/ethnicity [χ¹(1)=5.25, p=.02].

RESULTS

Participant demographics and clinical characteristics are shown in Table 1. At baseline, 86% of participants screened positive for harmful drinking behavior, 51% screened positive for symptoms of depression, 38% screened positive for PTSD, 31% screened positive for anxiety, and 25% screened positive for chronic pain. Three out of four participants (76%) reported ever participating “in group or individual therapy with a counselor or psychologist,” and 15 (21%) reported therapy in the past 30 days. Rates of treatment for various conditions included: 26 (37%) insomnia, 11 (16%) sleep apnea, 37 (52%) depression, 15 (21%) suicidal thoughts, 39 (55%) anxiety, 4 (6%) panic, 37 (52%) PTSD or trauma, 11 (16%) alcohol use, and 4 (6%) eating disorder.

CBT-I Treatment Completion and Satisfaction

All 38 participants assigned to CBT-I completed at least one session, and 33 (87%) completed all five sessions. The 29 CBT-I participants who completed the treatment satisfaction questionnaire were uniformly satisfied, with 97% rating it as “good” or “excellent.” (One participant who completed only one treatment session rated it as “fair.”) All CBT-I participants agreed that they would recommend it to a friend in need of similar help. The average satisfaction rating was 3.59 (SD=0.66; range 2-4).

Change in Treatment Willingness

Means and standard deviations for willingness to seek treatment for each health condition across the two groups are reported in Table 3. At post-treatment, irrespective of treatment group, participants showed most willingness to seek treatment for insomnia (M=3.08, SD=1.04), followed by chronic pain (M=2.82, SD=1.21), anxiety (M=2.76, SD=1.24), depression (M=2.75, SD=1.29), and PTSD (M=2.61, SD=1.27). They reported least willingness to seek treatment for alcohol use (M=2.51, SD=1.19). The percentage of participants who “agreed” they would seek treatment for each condition at baseline and post-treatment is depicted for descriptive purposes in Table 4.

Table 3.

Descriptive and inferential statistics for treatment willingness to seek treatment for comorbid mental health conditions (N=70).

	Baseline			Post-Treatment			Group	Time	G x T
	n	M	SD	n	M	SD	F	F	F	Cohen’s d
Insomnia	70	3.01	1.14	51	3.08	1.04	0.02	0.04	10.25 *	0.86
CBT-I	38	2.84	1.24	27	3.33	1.00	---	---	---	1.36
Sleep Hygiene	32	3.22	0.98	24	2.79	1.02	---	---	---	-1.07
Alcohol use	70	2.73	1.20	51	2.51	1.19	2.98	2.92	0.02	0.08
CBT-I	38	2.87	1.26	27	2.70	1.24	---	---	---	-1.14
Sleep Hygiene	32	2.56	1.13	24	2.29	1.12	---	---	---	-1.38
Depression	70	2.81	1.30	51	2.75	1.29	0.12	0.38	2.35	0.50
CBT-I	38	2.58	1.45	27	2.81	1.44	---	---	---	1.44
Sleep Hygiene	32	3.09	1.06	24	2.67	1.13	---	---	---	-1.05
Anxiety	70	2.97	1.15	51	2.76	1.24	0.00	1.94	0.98	0.37
CBT-I	38	2.82	1.25	27	2.81	1.36	---	---	---	-1.62
Sleep Hygiene	32	3.16	1.02	24	2.71	1.12	---	---	---	-1.06
PTSD	70	2.80	1.30	51	2.61	1.27	0.00	0.25	0.81	0.20
CBT-I	38	2.74	1.33	27	2.67	1.27	---	---	---	-1.46
Sleep Hygiene	32	2.87	1.29	24	2.54	1.29	---	---	---	-1.41
Chronic pain	70	2.97	1.30	51	2.82	1.21	0.05	0.28	5.76*	0.60
CBT-I	38	2.74	1.44	27	2.96	1.19	---	---	---	1.86
Sleep Hygiene	32	3.19	1.09	24	2.67	1.24	---	---	---	-1.19

Note. Cohen’s d interpreted as 0.20 small, 0.50 medium, and 0.80 large (negative effect size indicates change in favor of the control group). G X T = group by time interaction. *p< .05. Scores interpreted as 0 strongly disagree, 1 disagree, 2 neither agree nor disagree, 3 agree, and 4 strongly agree.

Table 4.

Number and percentage of participants in each group who agreed they would seek treatment for each health condition at baseline and post-treatment.

	Baseline (n=70)	Post-Treatment (n=51)
Full Sample	n (%)	n (%)
Insomnia	52 (74%)	41 (80%)
Chronic pain	52 (74%)	34 (67%)
Anxiety	50 (71%)	35 (69%)
PTSD	48 (69%)	33 (65%)
Depression	47 (67%)	35 (69%)
Alcohol use	44 (63%)	30 (59%)
	Baseline (n=38)	Post-Treatment (n=27)
CBT-I	n (%)	n (%)
Insomnia	25 (66%)	23 (85%)
Chronic pain	25 (66%)	20 (74%)
Anxiety	24 (63%)	19 (70%)
PTSD	25 (66%)	18 (67%)
Depression	22 (58%)	19 (70%)
Alcohol use	27 (71%)	18 (67%)
	Baseline (n=33)	Post-Treatment (n=24)
Sleep Hygiene	n (%)	n (%)
Insomnia	27 (82%)	18 (75%)
Chronic pain	27 (82%)	14 (58%)
Anxiety	26 (79%)	16 (67%)
PTSD	23 (70%)	15 (63%)
Depression	25 (76%)	16 (67%)
Alcohol use	17 (52%)	12 (50%)

Note. Tx=treatment.

Inferential statistics and within- and between-group effect sizes are depicted in Table 3. Significant group-by-time interactions were found in the prediction of willingness to seek treatment for insomnia [F(1,48)=10.25, p=.002, d=0.86], with participants in the CBT-I group reporting increased willingness (d=1.36) and sleep hygiene participants reporting decreased willingness (d= −1.07). There was also a significant group-by-time interaction in the prediction of willingness to seek treatment for chronic pain [F(1,48)=5.76, p= 0.02, d=0.60], again with CBT-I participants reporting increases (d=1.86) and sleep hygiene participants reporting decreases from baseline to post-treatment (d= −1.19). Group-by-time interactions for willingness to seek treatment for alcohol use [F(1,48)=0.02, p=.89, d=0.08], anxiety [F(1,48)=0.98, p=.33, d=0.37], depression [F(1,48) =2.35, p=0.13, d=0.50], and PTSD [F(1,48)=0.81, p=.37, d=0.20] were not significant. Participant willingness to seek treatment for these conditions did not change significantly from baseline to post-treatment.

DISCUSSION

To our knowledge, this is the first study to examine the extent to which CBT-I may serve as a “gateway” to other forms of mental health treatment. Encouragingly, relative to those in sleep hygiene control, CBT-I participants reported increases in willingness to seek treatment for insomnia. This is consistent with previous studies suggesting that evidence-based treatment does increase openness to future treatment (Aisenberg-Shafran & Shturm, 2022). However, in contrast to hypotheses, a positive insomnia treatment experience did not impact willingness to seek treatment for alcohol use, depression, anxiety, or PTSD. Alcohol use had the lowest treatment willingness out of all conditions at both baseline and post-treatment, with two out of three participants (67%) agreeing that they would seek treatment for alcohol use if it were causing them problems. This is in line with existing literature, which demonstrates that substance use issues are stigmatized to a greater extent than other psychological or physical health disorders (Rundle et al., 2021), perhaps due to the perception that individuals have more “control” and “choice” over substance use (Corrigan et al., 2009).

In contrast to findings for other mental health disorders, CBT-I did increase willingness to seek treatment for chronic pain. While in line with hypotheses, it is striking that this is the only health condition to which a positive insomnia treatment experience generalized. We speculate that Veterans’ conceptualizations of sleep and chronic pain may contribute to this finding. To provide context for this hypothesis: one original purpose of the Treatment Willingness Scale was to compare openness to treatment for medical versus mental health conditions. Chronic pain was included on the scale as a “medical” (not “mental health”) condition; and sleep, although intended as a mental health condition, could not be categorized clearly as either “medical” or “mental health” because it cross-loaded on both factors of the scale (Miller et al., 2022). These data raise the possibility that Veterans do not conceptualize insomnia as a “mental health” issue, in which case it may make sense that CBT-I does not increase willingness to seek treatment for stereotypical mental health disorders. Instead, it increased willingness to seek treatment for chronic pain, which may be conceptualized as similarly “medical” in nature.

It may also be worth noting that, for every health condition examined, fewer sleep hygiene participants agreed they would seek treatment at post-treatment relative to baseline (see Table 4). For example, 70% of sleep hygiene participants “agreed” that they would feel comfortable seeking treatment for PTSD at baseline, but only 63% of sleep hygiene participants still agreed at the post-treatment assessment. None of these decreases in willingness were statistically significant; however, we highlight this potential pattern to encourage continued assessment of the possible iatrogenic effects of providing treatment for chronic insomnia that is not recommended (Mysliwiec et al., 2020). In this study, individuals in the sleep hygiene group were provided with sleep recommendations that we know from the literature should be insufficient to resolve chronic insomnia (Mysliwiec et al., 2020). Then, they were asked to implement those recommendations independently, without the support of a sleep coach. Multiple theories of behavior change emphasize the importance of social support and self-efficacy in intentions to seek treatment (Ajzen, 1985; Miller & Rollnick, 2023). As such, it is possible that individuals in the sleep hygiene group did not have the same scaffolding needed to support behavior change, and this suboptimal treatment experience may have reduced willingness to seek treatment in the future. If this were the case, then it is possible that a “treatment” that does not adequately address the problem (in this case, sleep hygiene alone) may be more detrimental to openness to seeking future treatment than no treatment at all. We encourage continued monitoring of this potential pattern in treatment trials.

Clinical Implications

Accumulating evidence that adults (and Veterans) are more willing to seek treatment for medical than mental health disorders may indicate a need to rebrand mental health treatment. For example, in qualitative interviews, patients have asked for less “pathologically-perceived” treatment options, calling instead for terms like “coaching” (Valerius et al., 2024). In this case, reframing “treatment” as coaching or perhaps training may make individuals feel more comfortable addressing these issues in professional contexts.

In the meantime, this study supports the idea that brief, evidence-based treatment for insomnia may serve as opportunity to engage Veterans with co-occurring mental health disorders in treatment, even if it does not directly target the comorbid mental health concern. In some cases, CBT-I has been shown to improve comorbid mental health concerns in addition to insomnia; for example, depressive symptoms, suicidal ideation, and alcohol-related problems (Manber et al., 2008; Miller et al., 2023; Pigeon et al., 2022; Trockel et al., 2015). As such, CBT-I remains a promising first line of treatment for individuals with comorbid insomnia, particularly if individuals are unwilling or uncomfortable seeking treatment for the comorbid health concern.

Limitations

Several limitations of the study design are worth noting. First, data collection occurred during the COVID-19 pandemic, which may have changed participants’ willingness to seek treatment, particularly in-person (Baum et al., 2020). Moreover, the Treatment Willingness Scale does not distinguish willingness to seek treatment in-person versus telehealth or individually versus in groups, and we did not ask participants what they were imagining “treatment” would look like when they responded to items on the scale. Veterans tend to prefer one-on-one sessions over classes or groups (Shepardson et al., 2014), in which case one’s conceptualization of what “treatment” entails likely influences their responses to the scale. The Treatment Willingness Scale also may not be representative of actual treatment seeking, in part because it is hypothetical and also because it asks if participants would “feel comfortable” seeking treatment. It is possible that participants would seek treatment for health problems even if they were uncomfortable doing so, in which case the Treatment Willingness Scale may underestimate true willingness to seek treatment. Finally, one randomized participant did not complete the Treatment Willingness Scale at baseline and only 51/70 (73%) completed it post-treatment. While this retention rate is similar to those reported in other CBT-I trials with Veterans (Edinger et al., 2009; Germain et al., 2014), it is impossible to know how findings may differ if all participants had completed both assessments. We made the assumption that the pattern of findings would be relatively consistent, since those who did complete both surveys did not differ from those who dropped out in treatment willingness at baseline.

Results can also only be generalized to the population studied. Specifically, participants were all Veterans of the United States military. The extent to which findings may generalize to civilian samples is unclear, given the distinct culture and lived experiences of military personnel. At the same time, given the high rates of mental health problems and stigma documented in military/Veteran samples (Barlas et al., 2013), treatment willingness in this population may warrant special concern. Participants were also primarily male and White, which limits generalizability to racially diverse groups. Racially diverse groups may have more barriers surrounding treatment (Carey et al., 2021; Powell et al., 2016); therefore, more research is needed to understand the differences in willingness to seek treatment across races/ethnicities.

Conclusion

Cognitive Behavioral Therapy for Insomnia (CBT-I) is highly effective in treating insomnia (Hertenstein et al., 2022; Mysliwiec et al., 2020). Heavy-drinking Veterans uniformly reported satisfaction with CBT-I and willingness to pursue future insomnia treatment if needed. However, this positive treatment experience did not translate consistently to greater willingness to engage in other forms of mental health treatment. Instead, the only comorbid condition for which treatment willingness significantly increased following CBT-I was chronic pain. We encourage continued research on how to engage Veterans in evidence-based treatment that could improve their quality of life.