Motivational Interviewing to Address SuicidalIdeation: A Randomized Controlled Trial inVeterans

PETER C. BRITTON, PHD, KENNETH R. CONNER, PSYD,MPH, BENJAMIN P. CHAPMAN,PHD,MPH AND STEPHEN A.MAISTO, PHD

Objective: Although the months following discharge from psychiatrichospitalization are a period of acute risk for veterans, there is a dearth ofempirically supported treatments tailored to veterans in acute psychiatrichospitalization.Method: We conducted a randomized controlled trial to test the efficacy ofMotivational Interviewing to Address Suicidal Ideation (MI-SI) that explored andresolved ambivalence, and a revised MI-SI (MI-SI-R) that resolved ambivalence,on suicidal ideation (SI) in hospitalized veterans who scored > 2 on the Scale forSuicidal Ideation. Participants were randomized to receive MI-SI plus treatment asusual (TAU), MI-SI-R+TAU, or TAU alone. MI-SI+TAU and MI-SI-R+TAUincluded two in-hospital therapy sessions and one telephone booster session.Participants completed follow-up assessments over 6 months.Results: Participants in all groups experienced reductions in the presence and severityof SI, but there were no significant differences among the groups. For the presenceof SI, results were in the hypothesized direction for both MI-SI+TAU conditions.Conclusions: Results are nondefinitive, but the effect size of both versions of MI-SI+TAU on the presence of SI was consistent with prior MI findings. Exploratoryanalyses suggest MI-SI-R may be preferable to MI-SI. More intensive MI-SI-Rwith a greater number of follow-ups may increase its effectiveness.

Individuals hospitalized for acute psychiatrictreatment, including veterans who receivecare from Veterans Health Administration

(VHA) hospitals, are at high risk for suicide inthe first year following discharge (Brittonet al., 2017; Chung et al., 2017; Desai,

PETER C. BRITTON, VISN 2 Center ofExcellence for Suicide Prevention, Department ofVeterans Affairs, Canandaigua Medical Center,Canandaigua, NY, USA and e-mail:peter.britton@va.gov Department of Psychiatry,University of Rochester Medical Center,Rochester, NY, USA and Center for IntegratedHealthcare, Department of Veterans Affairs,Syracuse Medical Center, Syracuse, NY, USA;KENNETH R. CONNER, VISN 2 Center ofExcellence for Suicide Prevention, Department ofVeterans Affairs, Canandaigua Medical Center,Canandaigua, NY, USA and Department ofPsychiatry, University of Rochester MedicalCenter, Rochester, NY, USA; BENJAMIN P.

CHAPMAN, Department of Psychiatry, University ofRochester Medical Center, Rochester, NY, USA;STEPHEN A. MAISTO, Center for IntegratedHealthcare, Department of Veterans Affairs,Syracuse Medical Center, Syracuse, NY, USA andDepartment of Psychology, Syracuse University,Syracuse, NY, USA

ClinicalTrials.gov Identifier: NCT01544127.Address correspondence to P. C. Britton,

VISN 2 Center of Excellence for Suicide Preven-tion, Department of Veterans Affairs, Canandai-gua Medical Center, 400 Crittenden Blvd.,Canandaigua, NY 14424, USA; E-mail: peter.brit-ton@va.gov

Suicide and Life-Threatening Behavior 1© 2019 The American Association of SuicidologyDOI: 10.1111/sltb.12581

Dausey, & Rosenheck, 2005). VHA userswho are hospitalized on psychiatric units areat eightfold risk for suicide in the year follow-ing discharge compared to general VHA users(Britton et al., 2017), with highest risk in themonths immediately following discharge(Desai et al., 2005). In recognition, VHAimplemented a suicide prevention programthat includes care coordination, safety plans,and a 24-hr crisis hotline for high-riskpatients (Britton et al., 2017; Department ofVeterans Affairs, 2008; Department of Veter-ans Affairs, Office of Inspector General,2007). Despite these efforts, there has beenno observable reduction of risk in this popula-tion (Britton et al., 2017), requiring thedevelopment and testing of additional strate-gies (The Assessment and Management ofRisk for SuicideWorking Group, 2013).

Among the top priorities for suicideprevention in veterans is a need to identify anevidence-based treatment than can be imple-mented on psychiatric inpatient units toreduce risk for suicide and suicide attempts(SA) (The Assessment and Management ofRisk for Suicide Working Group, 2013). SAare a potent risk factor for suicide and havebeen the focus of several clinical trials (Cen-ters for Disease Control and Prevention,2016; Harris & Barraclough, 1997; Owens,Horrocks, & House, 2002). Cognitive behav-ioral therapy (CBT) has been shown to reducethe incidence of SA (Tarrier, Taylor, &Gooding, 2008). However, efficacious CBTinterventions may be too lengthy to be deliv-ered during inpatient care (van den Bosch,Koeter, Stijnen, Verheul, & van den Brink,2005; Brown, Steer, Henriques, & Beck,2005; Brown, Have, et al., 2005; Linehanet al., 2006; Rudd et al., 2015; Verheul et al.,2003). We identified three randomized con-trolled trials (RCTs) of interventions thatwere administered during psychiatric hospi-talization. Two of the three trials tested CBTinterventions and did not show reductions insuicidal ideation (SI) or SA (Patsiokas &Clum, 1985; Tarrier, Haddock, Lewis,Drake, & Gregg, 2006). The third showedthat 32 hr of behavioral therapy reduced thepresence and severity of SI but not SA when

compared to insight-oriented therapy (Liber-man&Eckman, 1981).

To develop a brief intervention thatcould be adapted for inpatient units, weturned to the addiction literature, which hasemphasized brief approaches. MotivationalInterviewing (MI) is a one- to three-sessiontreatment that was developed to help moti-vate adults to change their hazardous con-sumption of alcohol (Miller & Rollnick,2002). In the second edition of the MI text,MI is described as “a client-centered, direc-tive method for enhancing intrinsic motiva-tion to change by exploring and resolvingambivalence” (p. 25) (Miller & Rollnick,2002). It has been found to improve healthbehaviors across a wide range of outcomes ina variety of populations, including veterans(Burke, Arkowitz, & Menchola, 2003; Het-tema, Steele, & Miller, 2005; Lundahl, Kunz,Brownell, Tollefson, & Burke, Mar 2010).

The efficacy and broad applicabilityof MI increased our interest in its potentialto help suicidal patients resolve theirambivalence about living (Britton, Patrick,& Williams, 2011; Britton, Williams, &Conner, 2008). Kovacs and Beck proposedthat the suicidal state is an internal strugglebetween the wish to live and the wish to die,rather than the consequence of a unidirec-tional desire to die (Kovacs & Beck, 1977).To test this hypothesis, they created anindex of the ratio of the wish to die to thewish to live using the Scale for SuicidalIdeation (SSI) (Beck, Kovacs, & Weissman,1979), which has been shown to be associ-ated with both the severity of SA and suicidedeaths (Brown, Steer, et al., 2005; Kovacs &Beck, 1977). If MI can be used to increasemotivation to change hazardous alcohol use,we posited that it may also be used toincrease the motivation to live and engagein life-sustaining and enhancing activity,which are hypothesized to reduce suicidalthoughts and behavior. We developed andtested motivational interviewing for suicidalideation (MI-SI) in an open trial with 13hospitalized veterans who showed largereductions in the severity of SI (Britton,Conner, & Maisto, 2012).

2 MOTIVATIONAL INTERVIEWING AND SUICIDAL IDEATION

Change in the Intervention

The current RCT was started in 2012,but the third edition of the MI text was pub-lished in 2013, marking critical changes. Adecade of RCTs and process–outcomeresearch led to the development of the theoryof MI that highlighted two pathways (Miller& Rose, 2009), a relational pathway exempli-fied by the MI Spirit, the empathic relation-ship that MI therapists strive to develop, anda technical pathway emphasizing increasingin-session talk about making changes (i.e.,“change talk”) while reducing talk aboutmaintaining unhealthy behavior (i.e., “coun-ter change talk”) (Amrhein, Miller, Yahne,Palmer, & Fulcher, 2003; Moyers, Martin,Houck, Christopher, & Tonigan, 2009). Thedevelopers redefinedMI, explaining that it “isdesigned to strengthen personal motivationfor and commitment to a specific goal by elic-iting and exploring the person’s own reasonsfor change within an atmosphere of accep-tance and compassion” (p. 29) (Miller & Roll-nick, 2013). Exploration of reasons not tochange was no longer a key component, withrecommendation to discontinue the use of thedecisional balance, a worksheet exploring thepros and cons of changing unhealthy behaviorand of maintaining it (Miller & Rose, 2015).

These changes inMI had critical impli-cations for MI-SI. After obtaining input fromseveral clinical research experts, our DataSafety Monitoring Board, and reviewing thetechnology and adaptive treatment literatures(Brown et al., 2009; Chow & Chang, 2008;Mohr et al., 2015), we modified MI-SI at thetrial midpoint. The specific changes includedeliminating the exploration of reasons forthinking about suicide and dropping the deci-sional balance, leading to the creation of MI-SI-revised (MI-SI-R). Our goal in doing sowas to increase the probability of a positiveoutcome for the trial, reduce the potential ofnegative outcomes for participants, andincrease what could be learned from the trial.We also revised our hypothesis. Our originalhypothesis was that MI-SI plus treatment asusual (MI-SI+TAU) would reduce the sever-ity of SI when compared to TAU alone. Our

revised hypothesis was that MI-SI-R+TAUwould reduce the severity of SI when com-pared to TAU. In exploratory analyses, weexamined dose of MI-SI conditions on the SIoutcomes, and SA as an outcome.

METHODS

Participants

Participants were 132 U.S. militaryveterans who were randomized to MI-SI plusTAU (n = 33), MI-SI-R plus TAU (n = 33),or TAU alone (n = 66), recruited from theacute psychiatric inpatient unit at the Depart-ment of Veterans Affairs, Syracuse MedicalCenter (VAMC), from August 2012 to March2017 (Figure 1). Potentially eligible patientswere identified during daily staff meetings,and interested patients were introduced to aresearch assistant who reviewed the consentform and answered questions. Inclusion crite-ria were (i) U.S. military veteran status, (ii)admitted to the unit, (iii) 18 years of age, (iv)English speaking, (v) able to provideinformed consent, (vi) cleared to participateby attending psychiatrist, (vii) receive healthcare from a VHA facility in upstate NY, and(viii) clinically significant suicidal ideation,defined as a score > 2 on the SSI (Beck et al.,1979). Exclusion criteria were (i) current psy-chosis, (ii) current mania, (iii) dementia, (iv)traumatic brain injury (TBI)-related demen-tia, (v) being inaccessible, and (vi) plan to bedischarged from the unit <48 hr after beingidentified by study staff.

The SSI was used to measure SI duringthe week prior to admission, the period ofacute risk that preceded hospitalization. Athreshold > 2 on the SSI was considered clin-ically significant because such scores predictdeath by suicide (Brown, Beck, Steer, & Gri-sham, 2000). Current psychosis and maniawere identified with the Mini-InternationalNeuropsychiatric Interview (Sheehan et al.,1998). Dementia was identified with ascore < 24 on theMini-Mental Status Exami-nation (MMSE) (Crum, Anthony, Bassett, &Folstein, 1993; Folstein, Folstein, &

BRITTON ET AL. 3

McHugh, 1975). The Ohio State TraumaticBrain Injury-ID (TBI-ID) short form (Corri-gan & Bogner, 2007) was used to identify lossof consciousness, and used for exclusion whenit occurred with a score < 27 on the MMSE(O’Bryant et al., 2008). Veterans wererecruited regardless of sex or ethnicity toensure inclusiveness (Yano et al., 2010).

Assessments

Eligible patients completed a baselineassessment that included measures of

psychiatric diagnoses found to increase riskfor suicide in veterans and outcome variables(Ilgen et al., 2010). Follow-up assessmentswere conducted at 1, 3, and 6 months via tele-phone, which was cost-efficient and enabledus to include rural veterans and assess rehos-pitalized participants (Alexopoulos et al.,2009; Bruce et al., 2004). The window forassessments opened at the midpoint betweenthe previous and current assessment andclosed at the midpoint between the currentand following assessment. Follow-up ended3 months after the target date for the

515 Invited to participate 271 (53%) Refused

244 Assessed for eligibility

132 Randomized

77 (32%) Ineligible29 (12%) Discharged4 (2%) Withdrawn

33 Randomized to MI-SI 33 Randomized to MI-SI-R 66 Randomized to TAU

MI-SI 1 Month24 (73%) Competed5 (15%) Lost to contact4 (12%) Withdrawn

MI-SI 3 Month23 (69%) Completed5 (15%) Lost to contact5 (15%) Withdrawn

MI-SI-R 1 Month28 (85%) Completed4 Lost to contact1 Withdrawn

MI-SI-R 3 Month26 (79%) Completed6 Lost to contact1 Withdrawn

TAU 1 Month56 (85%) Completed8 Lost to contact2 Withdrawn

TAU 3 Month55 (83%) Completed8 Lost to contact3 Withdrawn

MI-SI 6 Month22 (67%) Completed5 (15%) Lost to contact7 (21%) Withdrawn

MI-SI-R 6 Month27 (82%) Completed2 (6%) Lost to contact4 (12%) Withdrawn

TAU 6 Month52 (79%) Completed9 (14%) Lost to contact5 (8%) Withdrawn

2 Withdrawn by IRB

Figure 1. Participant flow diagram.

4 MOTIVATIONAL INTERVIEWING AND SUICIDAL IDEATION

6-month follow-up. Follow-up assessors wereblind to study condition.

Measures

Outcome Measures. The primary out-comes, the presence and severity of SI, weremeasured with the SSI (Beck et al., 1979), apsychometrically sound measure (Beck,Brown, & Steer, 1997; Beck, Brown, Steer,Dahlsgaard, & Grisham, 1999), sensitive tochange over time (Brown et al., 2000), thathas been used with veterans (Bell & Nye,2007). The exploratory outcome, SA, wasassessed with the Columbia-Suicide SeverityRating Scale (C-SSRS) (Posner, Oquendo,Gould, Stanley, & Davies, 2007), which alsohas sound psychometrics (Meyer et al.,2010; Mundt et al., 2013; Posner et al.,2011).

Psychiatric and Substance Use Prob-lems. Commonly used measures were usedto assess relevant psychiatric diagnoses andsubstance use-related problems to describethe sample. Depression was assessed withthe Patient Health Questionnaire (PHQ-9)(Spitzer, Kroenke, & Williams, 1999), a reli-able and valid measure that is used in VHAcare (Corson, Gerrity, & Dobscha, 2004).Posttraumatic stress disorder (PTSD) wasassessed with the PTSD Checklist CivilianVersion (PCL-C) (Weathers, Ruscio, &Keane, 1999), a reliable and valid measurethat is used with veterans (Hankin, Spiro,Miller, & Kazis, 1999; Keen, Kutter, Niles,& Krinsley, 2008). Anxiety was assessed withthe Beck Anxiety Inventory (BAI), a reliableand valid measure (Beck, Epstein, Brown, &Steer, 1988). Screening for alcohol use dis-order was assessed with the Alcohol UseDisorders Identification Test (AUDIT)(Saunders, Aasland, Babor, de la Fuente, &Grant, 1993), a measure that is reliable andvalid in veterans (Bradley et al., 1998).Screening for possible other drug use disor-der was assessed with the reliable and validshort form of the Drug Abuse ScreeningTest (DAST) (Skinner, 1982) that has beenused with veterans (Gmel, Graham, Kuen-dig, & Kuntsche, 2006).

Randomization

Blocked randomization, using blocksizes of four and six participants, was used toprevent significant imbalance between thenumbers of participants in each condition atany time, and to protect against guessing con-dition assignment (Schulz & Grimes, 2002).STATA was used to randomize the partici-pants, and the results were placed in an envel-ope that was unsealed at randomization.

Treatment Conditions

Treatment as Usual. All participantsreceived standard inpatient treatment thatincludes medication management, case man-agement, meals and a bed, and creative andsocial activities. Some families of veterans alsoreceived education to create a supportivehome environment. As part of VHA suicideprevention policy (Department of VeteransAffairs, 2008; Department of VeteransAffairs, Office of Inspector General, 2007),patients completed a safety plan prior to dis-charge (Stanley & Brown, 2012), and the careof high-risk patients was overseen by a localSuicide Prevention Coordinator and CaseManagers. Chart reviews were conducted todescribe TAU.

Experimental Treatments. Participantswho were randomized to MI-SI or MI-SI-Rreceived one to two sessions on the unit,depending on length of stay. To maximize theimpact of each session, Session 2 was held twodays (48 hr) after Session 1. Veterans in MI-SI conditions also completed one telephonebooster session (30–50 min) within onemonth (14–45 days) after discharge toincrease dosage (Fleischmann et al., 2008;Vaiva et al., 2006).

MI-SI. The goal of MI-SI is to shiftmotivation away from suicide and toward liv-ing and recovery. It is based on the premisethat ambivalence about living can be resolvedby a nonjudgmental exploration of reasonsfor and against living, such that patients feelfree to explore their reasons for living anddying in a nondefensive manner. In Phase 1,exploring the presenting problem, clinicians

BRITTON ET AL. 5

asked patients to explore the presenting prob-lem that brought them to the hospital, includ-ing their reasons for thinking about suicide.In Phase 2, building the motivation to live, clini-cians helped patients identify and exploretheir reasons for living, including an explo-ration of core beliefs and values to furtherenhance their motivation to live. Optionaltools include the decisional balance and readi-ness rulers to examine patients’ interest in liv-ing and confidence that they can establish alife worth living. In Phase 3, strengthening thecommitment to living, clinicians strengthenedpatients’ confidence that they can establish alife worth living by helping them develop aconcrete plan that includes a list of patient-generated activities intended to promote liv-ing that they intend to engage in after dis-charge. Typical activities included increasinginteraction with friends and family, engagingin treatment, and increasing enjoyable andmeaningful activities such as hiking or volun-teering. Transitioning between phases wasdependent on the patients’ level of readiness,as premature transitioning may reduce theimpact of MI (Miller & Rose, 2009).

In Session 1, clinicians sought to pro-ceed through all three phases. In Session 2,clinicians summarized Session 1 and used thepatients’ response to decide which phase toreturn to. Telephone sessions consisted of anabbreviated MI-SI interview following thestrategy of Session 2 and included a review ofpatients’ treatment needs. Treatment wasbased on a manual that was developed for thestudy.

MI-SI-R. The goal of MI-SI-R is thesame as that of MI-SI. However, MI-SI-R isbased on the premise that ambivalence aboutliving is best resolved by engaging the patientin an exploration of their reasons for living.The primary difference between the twointerventions was in Phase 1. In Phase 1, treat-ment engagement, clinicians engaged thepatient in a discussion about living. If patientswere not thinking about living, cliniciansasked them about their values and beliefs andexplored how they related to living. Phase 2,exploring the motivation to live, was identical,except that the decisional balance was

replaced with an exploring of living thatprompts an exploration of the benefits/prosof living and consequences/cons of making anattempt. Phase 3, strengthening the commitmentto living, and telephone follow-up were identi-cal to the original intervention. The studymanual was revised to incorporate thesechanges.

Treatment Fidelity

MI-SI sessions were recorded andcoded for fidelity using the MotivationalInterviewing Treatment Integrity scale(MITI) (Moyers, Martin, Manuel, Hendrick-son, & Miller, 2005). The MITI is a behav-ioral coding system that is used to code 20-min samples of tape for adherence toMI prin-ciples (e.g., empathy, autonomy support) anduse of specificMI techniques (e.g., reflections,open questions). Summary values were usedto assess fidelity (Miller &Mount, 2001). Thecoder performing the MITI ratings wastrained to reliability by the PI, a member ofthe Motivational International Network ofTrainers. Coding was conducted independentfrom the PI to reduce possible bias.

Statistical Analyses

Data were screened for missingness,outliers, nonnormality, nonlinearity, andheteroscedasticity using statistics and graphicrepresentations. Imbalances between ran-domized groups were tested at baseline, lead-ing to the identification of covariates to beincluded in analyses. Analyses were based onan intent-to-treat approach, included allavailable data, and used one-tailed directionaltests hypothesizing the experimental treat-ment plus TAU superior to TAU alone, withp < .05 as the cutoff for statistical significancefor SI, the primary outcome. For exploratoryanalyses examining SA, two-tailed test wereused, with p < .01 as the cutoff.

Due to changing the intervention, wedeveloped a two-step analytical plan to opti-mize what we could learn from the trial. InStep 1, we compared MI-SI-R+TAU to TAUand MI-SI+TAU to TAU. However, we also

6 MOTIVATIONAL INTERVIEWING AND SUICIDAL IDEATION

wanted to examine differences between theoriginal and revised versions of MI-SI. In Step2, if the effect of the MI-SI conditions was inthe same direction (i.e., both reduced SI), wecombined them and compared the resultinggroup to TAU alone. However, if the effect ofthe MI-SI was in different directions (i.e., oneincreased and one decreased SI), we comparedeach to TAU. If both versions of MI-SI wereclearly not different from TAU, we stopped atStep 1 and reported both comparisons.

Because there was an abundance ofzeros for SI, a zero-inflated Poisson withrobust standard error clustered by partici-pants to account for repeated measures wasused to examine whether there was significantchange from baseline to follow-up in SIacross all conditions. We then tested theeffect of treatment conditions on the absenceand severity of SI over 6-month follow-up.These models produce two sets of parameterestimates: The first reflects the probabilitythat a predictor, such as treatment assign-ment, is associated with a score of zero, mod-eled via logistic regression; and the secondreflects the predictor’s association with thenonzero scores, modeled via Poisson regres-sion. Logistic regression effect sizes are oddsratios and here refer to the absence of SI. Wereported odds ratios (OR) with 95% confi-dence intervals (95% CI) (Hosmer & Leme-show, 1989). Because participants receivedone to three sessions ofMI-SI, and the changepattern may not be linear over time, we testednumber of sessions of MI-SI, time of assess-ment, and their interaction in follow-up anal-yses. The interaction is of primary interestbecause it reflects treatment differences at aparticular time point rather than averagedacross all follow-up measurements. Theimpact of treatment on SA over follow-up wasalso examined using log-rank tests.

Power Analysis

Power analyses were conducted usingSTATA and based on Frison and Pocock’swork (Frison & Pocock, 1992). Using specifi-cations from prior research and our pilot datathat suggested that an approximately 5-point

difference in SSI scores would represent amedium effect (Britton et al., 2012), propos-ing one-sided analyses, and setting alpha atp < .05, there was 0.87 power to identify a 5-point difference in mean SSI scores frombaseline between MI-SI-R+TAU (n = 26) orMI-SI+TAU (n = 26) and TAU (n = 52),0.80 power to identify a 4.5-point difference,and .72 power to identify a 4-point difference.Using the noted specifications, we had 0.96power to identify a 5-point difference in meanSSI scores between the Combined MI-SI+TAU groups compared to TAU, 0.92power to identify a 4.5-point difference, and0.86 power to identify a 4-point difference.We recruited seven additional participants inMI-SI-R+TAU and MI-SI+TAU and 14 inTAU to account for withdrawals and loss tocontact.

RESULTS

Treatment Fidelity

Both MI-SI treatments were adminis-tered with acceptable proficiency. MITI 3.1.1was used to code 20% of MI-SI interviews(n = 19) (Moyers, Martin, Manuel, Miller, &Ernst, 2010), with interviews achieving thecriteria of beginning proficiency to compe-tency. The mean (SD) on the global MI Spiritscale (i.e., evocation, collaboration, auton-omy, directive, empathy) was 4.32 (0.32)(competency ≥ 4). The reflection-to-ques-tion ratio was 4.51 (2.90) (competency ≥ 2).Percent open questions (i.e., open, closed)was 80% (24.55) (competency ≥ 70%). Thepercent complex reflections (i.e., complex,simple) was 58% (6.62) (competency ≥ 50%).The percent MI adherent responses (i.e., ask-ing permission, autonomy support, affirm,general support) to all responses (MI nonad-herent included advising without permission,confronting, directing) was 99% (4.59)(Beginning proficiency ≥ 90%; Compe-tency = 100%).

MITI 4.2 was used to code 20% of MI-SI-R interviews (n = 17) (Moyers, Manuel, &Ernst, 2015), with interviews achieving

BRITTON ET AL. 7

criteria of good. The mean (SD) on the globaltechnical component (i.e., cultivate changetalk, soften sustain talk) was 4.47 (0.60)

(good ≥ 4) and the relational component (i.e.,partnership, empathy) was 4.59 (0.36)(good ≥ 4). The percent of complex

TABLE 1

Baseline demographics

Total(n = 132)

Mean (SD)N(%)

TAU (n = 66)Mean

(SD)N (%)

MI-SI(n = 33)

Mean (SD)N (%)

MI-SI-R(n = 33)

Mean (SD)N (%)

p-value

Age 45.64 (12.61) 46.03 (12.77) 46.61 (12.69) 43.91 (12.44) .70a

Sex .87b

Male 118 (89.39) 58 (87.88) 30 (90.91) 30 (90.91)Race .55b

White 102 (77.27) 52 (78.79) 25 (75.76) 25 (75.76)Black 18 (13.64) 8 (12.12) 5 (15.15) 5 (15.15)American Indian or AlaskanNative

3 (2.27) 1 (1.52) 2 (6.06) 0 (0.00)

Native Hawaiian or PacificIslander

2 (1.52) 1 (1.52) 1 (3.03) 0 (0.00)

Biracial/Multiracial 7 (5.30) 4 (6.06) 0 (0.00) 3 (9.09)Ethnicity .81b

Hispanic/Latino 3 (2.27) 2 (3.03) 1 (3.03) 0 (0.00)Marital status .22b

Married 44 (33.33) 22 (33.33) 13 (29.29) 9 (27.27)Divorced/Separated 57 (43.18) 33 (50.00) 9 (27.27) 15 (45.45)NeverMarried 25 (18.94) 10 (15.15) 8 (24.24) 7 (21.21)Widowed 6 (4.55) 1 (1.52) 3 (9.09) 2 (6.06)Employment .67b

Part-/full-time/Self-Employed

24 (18.18) 14 (21.21) 4 (12.12) 6 (18.18)

Student/Homemaker 2 (1.52) 2 (3.03) 0 (0.00) 0 (0.00)Unemployed 35 (26.52) 18 (27.27) 11 (33.33) 6 (18.18)Disabled or Retired 70 (53.03) 31 (46.97) 18 (54.55) 21 (63.64)Other 1 (0.76) 1 (1.52) 0 (0.00) 0 (0.00)Years of service 6.55 (6.40) 7.09 (6.78) 6.21 (7.05) 5.82 (4.82) .50a

Era .60b

Post-9/11 (2001–Present) 37 (28.03) 17 (25.76) 7 (21.21) 13 (39.39)Desert Storm/Shield (1990–2001)

10 (7.58) 5 (7.58) 2 (6.06) 3 (9.09)

Post-Vietnam Peace (1975–1990)

31 (23.48) 16 (24.24) 9 (27.27) 6 (18.18)

VietnamWar (1964–1975) 12 (9.09) 5 (7.58) 6 (18.18) 1 (3.03)Post-Korea Peace (1955–1964)

2 (1.52) 2 (3.03) 0 (0.00) 0 (0.00)

Multiple Eras 40 (30.30) 21 (31.82) 9 (27.27) 10 (30.30)Deployment history .83c

Deployed to combat zone 62 (46.97) 30 (45.45) 15 (45.45) 17 (51.52)

aKruskal–Wallis H test.bFisher’s exact test.cX2.

8 MOTIVATIONAL INTERVIEWING AND SUICIDAL IDEATION

reflections was 44% (7.58) (fair ≥ 40%,good ≥ 50%), possibly due to the challengeof addressing suicide talk after the changes.The reflection-to-question ratio was 3.30(2.38) (good ≥ 2). The percent MI adherentresponses (i.e., seeking collaboration, affirm,emphasizing autonomy) to all responses (MInonadherent included confront and persuade)forMI-SI-R was 100% (0.00).

Demographics, Psychological, andTreatment Variables

Consistent with randomization, therewere few differences in demographic(Table 1), psychological, and treatment vari-ables across conditions (Table 2). Exceptionswere the number of times consciousness waslost and severity of the worst TBI experience.These variables were included in multivariatemodels if they were associated with the out-come at a p < .10 level.

Withdrawals, Loss to Contact, andMissingData

Among the 132 participants, 76%(101/132) completed the 6-month

assessment, with 82% (27/33) completion inMI-SI-R+TAU, 67% (22/33) in MI-SI+TAU, and 79% (52/66) in TAU. Therewere no differences across conditions forwithdrawals and loss to contact at 6 months(X2 = 2.49, df = 2, p = .29). According toLittle’s test for which the null hypothesis isthat data are missing at random or nonignor-able, data were missing completely at random(X2 = 30.74, df = 27, p = .28).

Primary Outcomes: Presence and Severityof Suicidal Ideation

Participants in all conditions experi-enced a reduction in the presence and severityof SI (Table 3), with the likelihood of SIreduced by 71% over follow-up (OR (95%CI) = 0.29 (0.17, 0.49)). There were no statis-tically significant differences for the presenceor severity of SI for either MI-SI+TAU con-dition. However, for the presence of SI,results were in the hypothesized directionsfor both MI-SI-R+TAU (OR (95%) = 0.58(0.28, 1.24)) and MI-SI+TAU (OR(95%) = 0.60 (0.26, 1.40)) (Figure 2). TheCombined MI-SI+TAU approached, but didnot achieve significance as the CI crossed

0

10

20

30

40

50

60

70

80

90

100

0 1 2 3 4 5 6

TAU

MI-SI

MI-SI-R

Combined MI-SI

Figure 2. Presence of suicidal ideation on the Beck Scale for Suicidal Ideation (SSI) by treatment.

BRITTON ET AL. 9

1.00 (OR (95%) = 0.59 (0.31, 1.12)), andone-tailed p = .054.

Time and Dose Effects

There were no group-by-time interac-tions for the presence of SI (Table 3), butMI-SI+TAU was found to reduce the severityof SI at the 3-month follow-up, compared toTAU (b = �.52, robust SE = 0.28, one-tailedp = .04). Dose effects for number of sessionswere not observed in either MI-SI conditionor when the conditions were combined.

Exploratory Outcomes: Suicide Attempts

Across the three conditions, a total of16 (13.11%) participants attempted suicideduring the 6 months of follow-up. Two of31 (6.45%) participants in MI-SI-R+TAUhad an SA, as did six of 28 (21.43%) inMI-SI+TAU and eight of 63 (12.70%) inTAU. There were no differences in thelikelihood of a SA over follow-up (log-rankX2 = 2.83, df = 2, p = .24). Because theeffects were in different directions, the con-ditions were compared, but the difference

TABLE 2

Baseline psychiatric variables and mental health treatment

Total (n = 132)Mean (SD)N (%)

TAU (n = 66)Mean (SD)N (%)

MI-SI (n = 33)Mean (SD)N (%)

MI-SI-R (n = 33)Mean (SD)N (%)

p-value

SSICurrent 21.11 (8.38) 20.54 (8.64) 23.27 (8.33) 20.06 (7.73) .22a

Worst point 24.85 (8.92) 23.45 (9.07) 26.75 (8.50) 25.76 (8.81) .12a

Suicide attemptsLast month 30 (22.73) 17 (25.76) 6 (18.18) 7 (21.21) .68b

Lifetime 1.80 (2.57) 1.24 (1.66) 2.85 (3.44) 1.84 (2.81) .16a

TBI# times LOC 1.58 (1.98) 1.18 (1.71) 2.03 (2.23) 1.91 (2.11) .03a

# >= 30 minLOC

0.24 (0.50) 0.17 (0.41) 0.42 (0.66) 0.21 (0.42) .06a

Before 15 35 (26.52) 12 (18.18) 11 (33.33) 12 (36.36) .09b

Worst (1–5) 2.64 (1.15) 2.44 (1.18) 3.00 (1.06) 2.70 (1.10) .03a

Mental healthPHQ 18.13 (4.88) 17.92 (5.28) 18.54 (4.29) 18.12 (4.74) .86a

PCL 58.08 (12.64) 56.89 (13.35) 60.12 (11.07) 58.39 (12.73) .48c

BAI 26.91 (11.08) 26.09 (10.72) 28.24 (10.20) 27.21 (12.72) .65c

AUDIT 12.80 (11.81) 14.48 (12.53) 14.54 (11.50) 9.67 (10.19) .20a

DAST 2.86 (3.21) 3.02 (3.31) 2.58 (2.90) 2.85 (3.38) .91a

Inpatient daysAnymentalhealth

1.97 (5.87) 2.39 (6.32) 0.27 (1.15) 2.82 (7.38) .11a

Outpatient daysAnymentalhealth

2.82 (4.43) 3.58 (5.50) 2.58 (4.47) 2.82 (4.43) .46a

MedicationsPsychiatric 16.98 (12.76) 17.20 (12.82) 14.82 (12.87) 18.70 (12.61) .37a

Medical 14.00 (14.00) 14.77 (13.35) 14.45 (13.36) 16.15 (12.96) .78c

Substanceabuse

1.54 (5.89) 2.14 (7.08) 1.85 (6.09) 0.03 (0.17) .38a

aKruskal–Wallis test.bX2.cOne-way ANOVA.

10 MOTIVATIONAL INTERVIEWING AND SUICIDAL IDEATION

TABLE3

Effectsoftreatm

entonthepresenceandseverityofsuicidalideation

(SI)

NSIfree

N(%

)b

RobustSE

One-tailed

pOR(95%

CI)

SIseverity

(amongthose

withSI)

M(SD)

bRobustSE

One-tailed

p

ALL

122

2.20

0.25

<.001

0.29

(0.17,0.49

)�.

790.07

<.001

MI-SI

28.51

0.43

.12

0.60

(0.26,1.40

).09

0.12

.23

BL

0(0.00)

22.89(8.59)

1month

248(33.33

)�.

350.53

.26

16.94(9.05)

.26

0.22

.12

3months

236(26.09

)�.

250.61

.32

8.88

(9.05)

�.52

0.28

.04

6months

218(38.10

).30

0.45

.25

18.15(10.52

).20

0.22

.18

Dose

effect

a.75

0.61

.22

0.47

(0.14,1.57

)�.

040.16

.82

MI-SI-R

31.54

0.38

.08

0.58

(0.28,1.24

).01

0.13

.46

BL

0(0.00)

20.48(7.78)

1month

278(29.63

)�.

780.51

.12

14.26(9.70

�.13

0.19

.24

3months

2610

(38.46

).46

0.54

.20

15.25(9.39)

.13

0.18

.23

6months

2810

(35.71

).34

0.51

.25

16.89(9.12)

.00

0.19

.50

Dose

effect

a.27

0.17

.11

0.63

(0.21,1.83

).00

0.05

.96

Combined

MI-SI

59.52

0.32

.054

0.59

(0.31,1.12

).06

0.11

.30

BL

0(0.00)

21.63(8.19)

1month

5116

(31.37

)�.

580.43

.09

15.48(9.37)

.05

0.16

.38

3months

4916

(32.65

).13

0.45

.78

11.97(9.63)

�.16

0.17

.18

6months

4918

(36.73

).48

0.39

.11

17.42(9.62)

.09

0.16

.28

Dose

effect

a.58

0.40

.15

0.56

(0.25,1.24

)�0

.09

0.10

.38

TAU

63ref

ref

ref

ref

ref

ref

ref

BL

0(0.00)

20.95(8.44)

1month

5618

(32.14

)14

.21(6.62)

3months

5523

(23.64

)12

.74(10.06

)6months

5212

(23.08

)15

.45(10.06

)

a Exploratory

analyses

usedtw

o-tailedtests,andpwas

setat.01.

BRITTON ET AL. 11

was not significant (log-rank X2 = 2.73,df = 1, p = .10).

DISCUSSION

The results of this efficacy trial of anovel motivational interviewing interventionto reduce SI (MI-SI) in veterans hospitalizedfor acute psychiatric difficulties are non-definitive. All participants experienced sig-nificant reductions in the presence andseverity of SI over follow-up. However, nei-ther the revised MI-SI-R, original MI-SI,nor the Combined groups with treatment asusual (TAU) were shown to reduce the pres-ence or severity of SI compared to TAUalone at a statistically significant level. Forthe presence of SI, the result was in thehypothesized direction, with the individualand Combined MI-SI+TAU groups show-ing lower presence of SI than the TAUgroup. It may be that the MI-SI and/or MI-SI-R treatments have a therapeutic effect inreducing risk for SI over 6-month follow-up, but we were unable to conclude this inthe current study.

As the first controlled test of a noveltherapy, there was considerable guessworkin the sample size calculations, in part,because our power analyses were based on areduction in the severity rather than pres-ence of SI, a binary outcome that requireslarger samples. Accordingly, the trial mayhave been underpowered, and nonsignificantresults require cautious interpretation. Sub-jects randomized to either version of MI-SI+TAU were 41% less likely to report SIover 6 months following discharge thanthose who received TAU alone, an effectsize that is generally consistent with MI forother outcomes (Burke et al., 2003; Het-tema et al., 2005; Lundahl et al., Mar 2010).This is notable in light of the comparativestrength of VHA TAU for veterans hospital-ized for acute psychiatric treatment. First,95% of participants received a safety planon the unit, an evidence-based intervention(Bryan et al., 2017; Stanley & Brown, 2012;

Stanley et al., 2015, 2018). Second, 76% ofparticipants in TAU completed at least twoface-to-face mental health or substanceabuse therapy sessions by the one-monthfollow-up, indicating a high rate of treat-ment engagement.

One potential limitation was that thedecision to change the intervention midtrialmay have reduced our ability to showwhether the original MI-SI reduced SIseverity. However, data clearly showed thatneither version of MI-SI affected the sever-ity of SI. Furthermore, it is unlikely that thechange had an effect our ability to identify asignificant difference in the presence of SI,as the study was underpowered from thestart. Given that the change increased theprobability of a positive outcome for thestudy, reduced the probability of a negativeoutcome for participants, and increased ouropportunity to learn about the changes inMI, we believe that it was worthwhile. Thecurrent study was also supported by a careerdevelopment grant with a limited budget.The PI (PCB) was the only clinician for thetrial, which limits generalizability, but alsoassured that differential effects between theversions of the intervention would not becaused by having different therapists admin-ister them.

Despite the nondefinitive results, MI-SI-R (and MI-SI) is a theoretically based,brief, and practical treatment designed toreduce SI in hospitalized, at-risk veterans orother high-risk clinical populations. Given itspotential to reduce the presence of SI, webelieve it warrants further study. The currentstudy used a low-intensity version of MI-SI,and it would be straightforward to increasethe intensity of the intervention, for example,with additional in-person or telephone fol-low-ups. Furthermore, we recommend thatwork in this area use our revised version of theexperimental intervention (i.e., MI-SI-R) oranother version that integrates recent devel-opments in the theory and practice of MI(Miller & Rose, 2015), as it may have implica-tions for the effectiveness of MI interventionswith suicidal patients.

12 MOTIVATIONAL INTERVIEWING AND SUICIDAL IDEATION

REFERENCES

ALEXOPOULOS, G. S., REYNOLDS, C. F., 3RD,,BRUCE, M. L., KATZ, I. R., RAUE, P. J., MULSANT, B.H., ET AL. (2009). Reducing suicidal ideation anddepression in older primary care patients: 24-month outcomes of the PROSPECT study. Ameri-can Journal of Psychiatry, 166, 882–890.

AMRHEIN, P. C., MILLER, W. R., YAHNE, C.E., PALMER, M., & FULCHER, L. (2003). Client com-mitment language during motivational interview-ing predicts drug use outcomes. Journal ofConsulting and Clinical Psychology, 71, 862–878.

BECK, A. T., BROWN, G. K., & STEER, R. A.(1997). Psychometric characteristics of the scale forsuicide ideation with psychiatric outpatients. Beha-viour Research and Therapy, 35, 1039–1046.

BECK, A. T., BROWN, G. K., STEER, R. A.,DAHLSGAARD, K. K., & GRISHAM, J. R. (1999). Sui-cide ideation at its worst point: A predictor of even-tual suicide in psychiatric outpatients. Suicide andLife-Threatening Behavior, 29, 1–9.

BECK, A. T., EPSTEIN, N., BROWN, G., &STEER, R. (1988). An inventory for measuring clini-cal anxiety: Psychometric properties. Journal ofConsulting & Clinical Psychology, 56, 893–897.

BECK, A. T., KOVACS, M., & WEISSMAN, A.(1979). Assessment of suicidal intention: The scalefor suicide ideation. Journal of Consulting and Clini-cal Psychology, 47, 343–352.

BELL, J. B., & NYE, E. C. (2007). Specificsymptoms predict suicidal ideation in Vietnamcombat veterans with chronic post-traumatic stressdisorder.MilitaryMedicine, 172, 1144–1147.

VAN DEN BOSCH, L. M. C., KOETER, M. W.J., STIJNEN, T., VERHEUL, R., & VAN DEN BRINK, W.(2005). Sustained efficacy of dialectical behaviourtherapy for borderline personality disorder. Beha-viour Research and Therapy, 43, 1231–1241.

BRADLEY, K. A., MCDONELL, M. B., BUSH,K., KIVLAHAN, D. R., DIEHR, P., & FIHN, S. D.(1998). The AUDIT alcohol consumption ques-tions: Reliability, validity, and responsiveness tochange in older male primary care patients. Alco-holism: Clinical & Experimental Research, 22, 1842–1849.

BRITTON, P. C., BOHNERT, K. M., ILGEN, M.A., KANE, C., STEPHENS, B., & PIGEON, W. R.(2017). Suicide mortality among male veterans dis-charged from Veterans Health Administration acutepsychiatric units from 2005 to 2010. Social Psychiatryand Psychiatric Epidemiology, 52, 1081–1087.

BRITTON, P. C., CONNER, K. R., & MAISTO,S. A. (2012). An open trial of motivational inter-viewing to address suicidal ideation with hospital-ized veterans. Journal of Clinical Psychology, 68, 961–971.

BRITTON, P. C., PATRICK, H., & WILLIAMS,G. C. (2011). Motivational interviewing, self-

determination theory, and cognitive behavioraltherapy to prevent suicidal behavior. Journal of Cog-nitive Behavioral Practice, 18, 16–27.

BRITTON, P. C., WILLIAMS, G. C., & CON-

NER, K. R. (2008). Self-determination theory, moti-vational interviewing, and the treatment of clientswith acute suicidal ideation. Journal of Clinical Psy-chology, 64, 52–66.

BROWN, G. K., BECK, A. T., STEER, R. A., &GRISHAM, J. R. (2000). Risk factors for suicide inpsychiatric outpatients: A 20-year prospectivestudy. Journal of Consulting and Clinical Psychology,68, 371–377.

BROWN, G. K., HAVE, T. T., HENRIQUES, G.R., XIE, S. X., HOLLANDER, J. E., & BECK, A. T.(2005). Cognitive therapy for the prevention of sui-cide attempts: A randomized controlled trial.JAMA, 294, 563–570.

BROWN, G. K., STEER, R. A., HENRIQUES, G.R., & BECK, A. T. (2005). The internal strugglebetween the wish to die and the wish to live: A riskfactor for suicide. The American Journal of Psychia-try, 162, 1977–1979.

BROWN, C. H., TEN HAVE, T. R., JO, B.,DAGNE, G., WYMAN, P. A., MUTHEN, B., ET AL.(2009). Adaptive designs for randomized trials inpublic health. Annual Review of Public Health, 30, 1–25.

BRUCE, M. L., TEN HAVE, T. R., REYNOLDS,C. F. 3RD,, KATZ, I. I., SCHULBERG, H. C., MUL-

SANT, B. H., ET AL. (2004). Reducing suicidal idea-tion and depressive symptoms in depressed olderprimary care patients: A randomized controlledtrial. JAMA, 291, 1081–1091.

BRYAN, C. J., MINTZ, J., CLEMANS, T. A.,LEESON, B., BURCH, T. S., WILLIAMS, S. R., ET AL.(2017). Effect of crisis response planning vs. con-tracts for safety on suicide risk in U.S. army sol-diers: A randomized clinical trial. Journal ofAffective Disorders, 212, 64–72.

BURKE, B. L., ARKOWITZ, H., & MENCHOLA,M. (2003). The efficacy of motivational interviewing:A meta-analysis of controlled clinical trials. Journalof Consulting and Clinical Psychology, 71, 843–861.

Centers for Disease Control and Preven-tion. (2016). Wisqars injury mortality reports1999–2014. Retrieved November 19, 2018, fromhttps://webappa.cdc.gov/sasweb/ncipc/mortrate10_us.html

CHOW, S., & CHANG, M. (2008). Adaptivedesignmethods in clinical trials - a review.OrphanetJournal of Rare Diseases, 3, 11.

CHUNG, D. T., RYAN, C. J., HADZI-PAVLO-

VIC, D., SINGH, S. P., STANTON, C., & LARGE,M.M.(2017). Suicide rates after discharge from psychi-atric facilities: A systematic review and meta-analy-sis. JAMA Psychiatry, 74, 694–702.

BRITTON ET AL. 13

CORRIGAN, J. D., & BOGNER, J. (2007). Ini-tial validity and reliability of the Ohio StateUniversity TBI identification method. Journal ofHead Trauma Rehabilitation, 22, 318–329.

CORSON, K., GERRITY, M. S., &DOBSCHA, S.K. (2004). Screening for depression and suicidalityin a VA primary care setting: 2 items are betterthan 1 item. American Journal of Managed Care, 10,839–845.

CRUM, R. M., ANTHONY, J. C., BASSETT, S.S., & FOLSTEIN, M. F. (1993). Population-basednorms for the mini-mental state examination byage and educational level. JAMA, 269, 2386–2391.

Department of Veterans Affairs (2008).VHA handbook 1160.01, uniform mental health ser-vices in VA medical centers and clinics. Washington,DC: Veterans Health Administration.

Department of Veterans Affairs, Office ofInspector General (2007). Healthcare inspection:Implementing VHA’s mental health strategic planinitiatives for suicide prevention. RetrievedNovember 19, 2018, from http://www.va.gov/oig/54/reports/vaoig-06-03706-126.pdf.

DESAI, R. A., DAUSEY, D. J., & ROSENHECK,R. A. (2005). Mental health service delivery andsuicide risk: The role of individual patient andfacility factors. American Journal of Psychiatry, 162,311–318.

FLEISCHMANN, A., BERTOLOTE, J. M.,WASSERMAN, D., DE LEO, D., BOLHARI, J., BOTEGA,N. J., ET AL. (2008). Effectiveness of brief interven-tion and contact for suicide attempters: A random-ized controlled trial in five countries. Bulletin of theWorld Health Organization, 86, 703–709.

FOLSTEIN, M. F., FOLSTEIN, S. E., &MCHUGH, P. R. (1975). Mini-mental state. Journalof Psychiatric Research, 12, 189–198.

FRISON, L., & POCOCK, S. J. (1992).Repeated measures in clinical trials: Analysis usingmean summary statistics and its implication fordesign. Statistics inMedicine, 11, 1685–1704.

GMEL, G., GRAHAM, K., KUENDIG, H., &KUNTSCHE, S. (2006). Measuring alcohol con-sumption–should the ‘graduated frequency’approach become the norm in survey research?Addiction, 101, 16–30.

HANKIN, C. S., SPIRO, A., 3RD,, MILLER, D.R., & KAZIS, L. (1999). Mental disorders and men-tal health treatment among U.S. Department ofVeterans Affairs outpatients: The veterans healthstudy. American Journal of Psychiatry, 156, 1924–1930.

HARRIS, E. C., & BARRACLOUGH, B. (1997).Suicide as an outcome for mental disorders: Ameta-analysis. British Journal of Psychiatry, 170,205–228.

HETTEMA, J., STEELE, J., & MILLER, W. R.(2005). Motivational interviewing. Annual Reviewof Clinical Psychology, 1, 91–111.

HOSMER, D. W., & LEMESHOW, S. (1989).Applied logistic regression. New York, NY:Wiley.

ILGEN, M. A., BOHNERT, A. S., IGNACIO, R.V., MCCARTHY, J. F., VALENSTEIN, M. M., KIM, H.M., ET AL. (2010). Psychiatric diagnoses and risk ofsuicide in veterans. Archives of General Psychiatry,67, 1152–1158.

KEEN, S. M., KUTTER, C. J., NILES, B. L., &KRINSLEY, K. E. (2008). Psychometric properties ofPTSD checklist in sample of male veterans. Journalof Rehabilitation Research & Development, 45, 465–474.

KOVACS, M., & BECK, A. T. (1977). Thewish to die and the wish to live in attempted sui-cides. Journal of Clinical Psychology, 33, 361–365.

LIBERMAN, R. P., & ECKMAN, T. (1981).Behavior therapy vs insight-oriented therapy forrepeated suicide attempters. Archives of GeneralPsychiatry, 38, 1126–1130.

LINEHAN, M. M., COMTOIS, K. A., MURRAY,A. M., BROWN, M. Z., GALLOP, R. J., HEARD, H. L.,ET AL. (2006). Two-year randomized controlledtrial and follow-up of dialectical behavior therapyvs therapy by experts for suicidal behaviors andborderline personality disorder. Archives of GeneralPsychiatry, 63, 757–766.

LUNDAHL, B. W., KUNZ, C., BROWNELL, C.,TOLLEFSON, D., & BURKE, B. L. (Mar 2010). Ameta-analysis of motivational interviewing:Twenty-five years of empirical studies. Research onSocialWork Practice, 20, 137–160.

MEYER, R. E., SALZMAN, C., YOUNGSTROM,E. A., CLAYTON, P. J., GOODWIN, F. J., MANN, J. J.,ET AL. (2010). Suicidality and risk of suicide- defi-nition, drug safety concerns, and a necessary targetfor drug development: A consensus statement.Journal of Clinical Psychiatry, 71, e1–e21.

MILLER, W. R., & MOUNT, K. A. (2001). Asmall study of training in motivational interview-ing: Does one workshop change clinician and cli-ent behavior? Behavioural and CognitivePsychotherapy, 29, 457–471.

MILLER, W. R., & ROLLNICK, S. (2002).Motivational interviewing: Preparing people forchange, 2nd edn. New York, NY: Guilford Press.

MILLER, W. R., & ROLLNICK, S. (2013).Motivational interviewing: Helping people change, 3rdedn. New York, NY: Guilford Press.

MILLER, W. R., & ROSE, G. S. (2009).Toward a theory of motivational interviewing.American Psychologist, 64, 527–537.

MILLER,W. R., & ROSE, G. S. (2015). Moti-vational interviewing and decisional balance: Con-trasting responses to client ambivalence.Behavioural and Cognitive Psychotherapy, 43, 129–141.

MOHR, D. C., SCHUELLER, S. M., RILEY, W.T., BROWN, C. H., CUIJPERS, P., DUAN, N., ET AL.(2015). Trials of intervention principles:

14 MOTIVATIONAL INTERVIEWING AND SUICIDAL IDEATION

Evaluation methods for evolving behavioral inter-vention technologies. Journal of Medical InternetResearch, 17, e166.

MOYERS, T. B., MANUEL, J. K., & ERNST, D.(2015). Motivational interviewing treatment integ-rity coding manual 4.2. Unpublished. RetrievedNovember 19, 2018, from https://casaa.unm.edu/download/miti4_2.pdf

MOYERS, T. B., MARTIN, T., HOUCK, J. M.,CHRISTOPHER, P. J., & TONIGAN, J. S. (2009). Fromin-session behaviors to drinking outcomes: A cau-sal chain for motivational interviewing. Journal ofConsulting & Clinical Psychology, 77, 1113–1124.

MOYERS, T. B., MARTIN, T., MANUEL, J. K.,HENDRICKSON, S. M. L., & MILLER, W. R. (2005).Assessing competence in the use of motivationalinterviewing. Journal of Substance Abuse Treatment,28, 19–26.

MOYERS, T. B., MARTIN, T., MANUEL, J. K.,MILLER, W. R., & ERNST, D. (2010). Motivationalinterviewing treatment integrity coding manual3.1. Unpublished. Retrieved November 19, 2018,from https://casaa.unm.edu/download/miti3_1.pdf

MUNDT, J. C., GREIST, J. H., JEFFERSON, J.W., FEDERICO, M., MANN, J. J., & POSNER, K.(2013). Prediction of suicidal behavior in clinicalresearch by lifetime suicidal ideation and behaviorascertained by the electronic Columbia-suicideseverity rating scale. Journal of Clinical Psychiatry,74, 887–893.

O’BRYANT, S. E., HUMPHREYS, J. D., SMITH,G. E., IVNIK, R. J., GRAFF-RADFORD, N. R., PETER-

SEN, R. C., ET AL. (2008). Detecting dementia withthe mini-mental state examination in highly edu-cated individuals. Archives of Neurology, 65, 963–967.

OWENS, D., HORROCKS, J., & HOUSE, A.(2002). Fatal and non-fatal repetition of self-harm.Systematic review. British Journal of Psychiatry, 181,193–199.

PATSIOKAS, A. T., & CLUM, G. A. (1985).Effects of psychotherapeutic strategies in the treat-ment of suicide attempters. Psychotherapy: Theory,Research, Practice, Training, 22, 281–290.

POSNER, K., BROWN, G. K., STANLEY, B.,BRENT, D. A., YERSHOVA, K. V., OQUENDO, M. A.,ET AL. (2011). The Columbia-suicide severity rat-ing scale: Initial validity and internal consistencyfindings from three multisite studies with adoles-cents and adults. American Journal of Psychiatry,168, 1266–1277.

POSNER, K., OQUENDO, M. A., GOULD, M.,STANLEY, B., & DAVIES, M. (2007). Columbia clas-sification algorithm of suicide assessment (C-CASA): Classification of suicidal events in theFDA’s pediatric suicidal risk analysis of antidepres-sants. American Journal of Psychiatry, 164, 1035–1043.

RUDD,M. D., BRYAN, C. J.,WERTENBERGER,E. G., PETERSON, A. L., YOUNG-MCCAUGHAN, S.,MINTZ, J., ET AL. (2015). Brief cognitive-behavioraltherapy effects on post-treatment suicide attemptsin a military sample: Results of a randomized clini-cal trial with 2-year follow-up. American Journal ofPsychiatry, 172, 441–449.

SAUNDERS, J. B., AASLAND, O. G., BABOR, T.F., DE LA FUENTE, J. R., & GRANT, M. (1993).Development of the alcohol use disorders identifi-cation test (AUDIT): WHO collaborative projecton early detection of persons with harmful alcoholconsumption–II.Addiction, 88, 791–804.

SCHULZ, K. F., & GRIMES, D. A. (2002).Unequal group sizes in randomized trials: Guard-ing against guessing. Lancet, 359, 966–970.

SHEEHAN, D. V., LECRUBIER, Y., SHEEHAN,K. H., AMORIM, P., JANAVS, J., WEILLER, E., ET AL.(1998). The mini-international neuropsychiatricinterview (M.I.N.I.): The development and valida-tion of a structured diagnostic psychiatric inter-view for DSM-IV and ICD-10. Journal of ClinicalPsychiatry, 59, 22–33.

SKINNER, H. A. (1982). The drug abusescreening test.Addictive Behaviors, 7, 363–371.

SPITZER, R. L., KROENKE, K., WILLIAMS,JBW, & Patient Health Questionnaire PrimaryCare Study Group, US. (1999). Validation andutility of a self-report version of PRIME-MD: ThePHQ primary care study. JAMA, 282, 1737–1744.

STANLEY, B., & BROWN, G. K. (2012). Safetyplanning intervention: A brief intervention to miti-gate suicide risk. Cognitive and Behavioral Practice,19, 256–264.

STANLEY, B., BROWN, G. K., BRENNER, L.A., GALFALVY, H. C., CURRIER, G. W., KNOX, K.L., ET AL. (2018). Comparison of the safety plan-ning intervention with follow-up vs usual care ofsuicidal patients treated in the emergency depart-ment. JAMA Psychiatry, 75, 894.

STANLEY, B., BROWN, G. K., CURRIER, G.W., LYONS, C., CHESIN, M., & KNOX, K. L. (2015).Brief intervention and follow-up for suicidalpatients with repeat emergency department visitsenhances treatment engagement. American Journalof Public Health, 105, 1570–1572.

TARRIER, N., HADDOCK, G., LEWIS, S.,DRAKE, R., GREGG, L., & SoCRATES TrialGroup. (2006). Suicide behaviour over 18 monthsin recent onset schizophrenic patients: The effectsof CBT. Schizophrenia Research, 83, 15–27.

TARRIER, N., TAYLOR, K., & GOODING, P.(2008). Cognitive-behavioral interventions toreduce suicide behavior: A systematic review andmeta-analysis. BehaviorModification, 33, 77–108.

The Assessment and Management of Riskfor Suicide Working Group. (2013). VA/DoDclinical practice Guideline for Assessment andManagement of Patients at Risk for suicide. (No.

BRITTON ET AL. 15

1.0). Washington, DC: Department of VeteransandDepartment of Defense.

VAIVA, G., VAIVA, G., DUCROCQ, F., MEYER,P., MATHIEU, D., PHILIPPE, A., ET AL. (2006). Effectof telephone contact on further suicide attempts inpatients discharged from an emergency depart-ment: Randomised controlled study. BMJ, 333,1241–1245.

VERHEUL, R., VAN DEN BOSCH, L. M. C.,KOETER, M. W. J., DE RIDDER, M. A. J., STIJNEN,T., & VAN DEN BRINK, W. (2003). Dialectical beha-viour therapy for women with borderline personal-ity disorder: 12-month, randomised clinical trial inthe Netherlands. British Journal of Psychiatry, 182,135–140.

WEATHERS, F.W., RUSCIO, A.M., &KEANE,T. M. (1999). Psychometric properties of ninescoring rules for the clinician-administered post-traumatic stress disorder scale. Psychological Assess-ment, 11, 124–133.

YANO, E. M., HAYES, P., WRIGHT, S., SCH-

NURR, P. P., LIPSON, L., BEAN-MAYBERRY, B., ET AL.(2010). Integration of women veterans into VAquality improvement research efforts: Whatresearchers need to know. Journal of General Inter-nal Medicine, 25, 56–61.

Manuscript Received: December 14, 2018Revision Accepted: May 27, 2019

16 MOTIVATIONAL INTERVIEWING AND SUICIDAL IDEATION

The Living Ladder: Introduction and ValidityOver 6-Month Follow-Up of aOne-ItemMeasure of Readiness to Continue Living inSuicidal Patients

PETER C. BRITTON, PHD, KENNETH R. CONNER, PSYD,MPH AND STEPHEN A.MAISTO,PHD

Objective: The ability to predict suicide outcomes is limited by the lack ofconsideration of protective factors. This study examined the validity of the LivingLadder, a measure of readiness to continue living among individuals thinking ofsuicide.Methods: The Living Ladder consists of one item that assesses an individual’sreadiness to continue living when thinking about suicide. Participants (N = 130)completed the Living Ladder in-person at baseline and by-phone at 1-, 3-, and 6-month follow-up. The prospective association of the Living Ladder with suicidalideation and risk for a suicide attempt was examined using models adjusting forbaseline ideation and suicide attempts, respectively.Results: Each rung on the Living Ladder was associated with 18% lower likelihoodof suicidal ideation, OR (95% CI) = 0.82 (0.68, 0.96), and less severe suicidalideation among those with ideation. Scores >2, indicating contemplation of living,were associated with 64% lower risk for a suicide attempt, HR (95% CI) = 0.36(0.13, 0.98). Findings for suicidal ideation were replicated when administered by-phone.Conclusions: The Living Ladder is a one-item measure that is prospectivelyassociated with suicidal ideation and suicide attempts. Findings support therelevance of motivation to live to suicide outcomes.

Suicide is the tenth leading cause of death inthe United States and the fourth leading causeof years of potential life lost before age 65

(Centers for Disease Control & Prevention,2017). The Veterans Health Administration(VHA) is the largest health care system in the

PETER C. BRITTON, Department ofVeterans Affairs, Finger Lakes Healthcare System,VISN 2 Center of Excellence for SuicidePrevention, Canandaigua, NY, USA andDepartment of Psychiatry, University of RochesterMedical Center, Rochester, NY, USA andDepartment of Veterans Affairs, Center forIntegrated Healthcare, Syracuse Medical Center,Syracuse, NY, USA; KENNETH R. CONNER ,Department of Psychiatry, University of RochesterMedical Center, Rochester, NY, USA; STEPHEN A.MAISTO, Department of Veterans Affairs, Centerfor Integrated Healthcare, Syracuse Medical

Center, Syracuse, NY, USA and Department ofPsychology, Syracuse University, Syracuse, NY,USA.

We thank the research staff at the Center ofExcellence for Suicide Prevention of the VHA Fin-ger Lakes Healthcare System and clinical staff onthe acute psychiatric unit at the Syracuse VAMedi-cal Center whomade this study possible.

Address correspondence to P. C. Britton,Center of Excellence (CoE) for Suicide Preven-tion, Department of Veterans Affairs, Finger LakesHealthcare System, 400 Fort Hill Ave., Canandai-gua, NY 14424; E-mail: peter.britton@va.gov

Suicide and Life-Threatening Behavior 1© 2020 The American Association of SuicidologyDOI: 10.1111/sltb.12635

United States, with over 9 million veteransenrolled (National Center for Veterans Anal-ysis & Statistics, 2017), and individuals inVHA care are at greater risk for suicide thanmen and women of comparable age who havenot served in the military (Department ofVeterans Affairs & Office of Suicide Preven-tion, 2016). Accordingly, the VHA is a criticalvenue for suicide research and prevention. Asin other populations, risk for suicide amongVHA patients is particularly high in themonths following discharge from psychiatrichospitalization, but the ability to identifyindividuals at greatest risk after discharge islimited (Britton et al., 2017). Research onprospective correlates of suicidal behavior haslargely focused on risk factors such as historyof attempts and suicidal ideation (McCarthyet al., 2015), with comparatively less consider-ation of protective factors (Franklin et al.,2017). One such factor is the motivation tolive, which has high theoretical significancebecause of the dynamic tension betweenmotivation to live and die that many suicidalindividuals experience (Kovacs & Beck,1977).

Some suicide research has been con-ducted on constructs similar to motivation tolive. One line of research has directly exam-ined ambivalence about living and dying, cre-ating a wish to live index by reverse scoringand subtracting the wish to live item from theScale for Suicidal Ideation (SSI) from the wishto die item (Beck, Kovacs, & Weissman,1979; Kovacs & Beck, 1977). Findings showthat patients whose wish to live is equal to orgreater than their wish to die have less intentto die when they attempt suicide (Kovacs &Beck, 1977), are less likely to die by suicide(Brown, Steer, Henriques, & Beck, 2005),and that the wish to live may be more mal-leable to treatment than the wish to die(Bryan, Rudd, Peterson, Young-McCaughan,& Wertenberger, 2016). Other research hasfocused on the Reasons for Living Scale(Linehan, Goodstein, Nielsen, & Chiles,1983), a checklist of a wide range of reasonsfor living when thinking about suicide thathas been shown to be associated with reducedrisk for suicidal ideation (SI) and suicide

attempts (SA) in a variety of populations(Malone et al., 2000; Osman, Gifford, Jones,& Lickiss, 1993; Osman et al., 1999),although its utility in the context of currentsuicide prevention treatments remainsunclear (Brudern et al., 2018). Anothersemistructured interview called the SuicideStatus Form (SSF) also uses self-report itemsto create an index of the wish to live and wishto die, (Jobes, 2010) with a research studyshowing that related typologies were cross-sectionally associated with history of attempts(O’Connor et al., 2012).

Research utilizing these measures sup-ports the hypothesis that suicidal behavior isassociated with the motivation to live, yetcritical questions remain regarding processesor aspects of motivation to live that reducerisk. The wish to live index, for example, con-ceptualizes the motivation to live as thestrength of the wish to live minus the strengthof wish to die, whereas the various measuresof reasons for living conceptualize motivationto live as the strength of the individual’s speci-fic motives (e.g., family concerns, fear of sui-cide, etc.) for living. Such constructs mayreveal little about the processes by whichpatients who are considering suicide can reap-ply themselves to living (Prochaska, Redding,& Evers, 2015), or motivational constructsthat may impact the importance of reasons forliving, such as whether they are intrinsic tothe individual or extrinsic and environmental(Ryan & Deci, 2002). Applying theories ofmotivation may therefore reveal critical pro-cess or facets of the motivation to live thathave yet to be studied.

The transtheoretical model has beenused to study motivation to and processes ofchanging problematic behaviors (Prochaskaet al., 2015). The best-known part of themodel, the stages of change, posits thatchange is a process and that there are fivestages (i.e., precontemplation, contemplation,preparation, action, and maintenance) thatdemarcate where people are in the process,and what needs to happen for them to achievechange. Often applied to efforts to changeaddictive behavior such as alcohol or otherdrug use, the theory helps clinicians identify

2 LIVING LADDER

where people are in the process and to iden-tify interventions that will help them movetoward change. Individuals who believe thatthey do not have an alcohol problem, forexample, are unlikely to benefit from an inter-vention that provides skills to change theirdrinking behavior. However, an interventionthat focuses on identifying and reinforcingreasons for change may help individuals real-ize that their drinking is a problem, providingmotivation to learn the skills needed tochange (Krebs, Norcross, Nicholson, & Pro-chaska, 2018).

The transtheoretical model also positsthat an individual’s current stage of changepredicts future behavior, as the further alongthe individual is in the process of thinkingabout engaging in change behavior, the morelikely he or she is to change it. The contem-plation ladder is a visual analog of the stagesof change that consists of “rungs” that areanchored to the stages of change (Biener &Abrams, 1991), with lower scores indicatingprecontemplation (0 = “No thought of quit-ting”) and higher scores indicating that therespondent is changing his or her behavior(10 = “Taking action to quit”). For addictivebehaviors, the contemplation ladder has beenfound to have good concurrent validity withother measures of readiness to change (Amo-dei & Lamb, 2004; Biener & Abrams, 1991;Carey, Maisto, Carey, & Purnine, 2001), aswell as predictive validity (Biener & Abrams,1991; Hogue, Dauber, &Morgenstern, 2010;Slavet et al., 2006). Because it is a single-itemmeasure that has psychometric propertiescomparable to those of more complex, multi-item measures, the contemplation ladder pro-vides a practical assessment for both cliniciansand clients (Amodei & Lamb, 2004), withpotential to enhance patient-centered care(Prochaska, Norcross, &DiClemente, 2013).

Like individuals with substance prob-lems, people who have experienced suicidalcrises may not be thinking about living orready to benefit from treatments that areavailable. However, such individuals may bemore likely to engage in treatment if theyhave decided to live than if they are ambiva-lent or want to die. Unfortunately, there are

currently no measures that can be used toidentify where patients who have had a suici-dal crisis are in thinking about making theirlives more worth living. This is relevant as wedo not conceptualize motivation to be a trait-like construct that is equally associated withall behaviors. Someone, for example, can besimultaneously high in motivation to maketheir lives worth living due to feeling respon-sible for their children but low in motivationfor treatment due to stigma against receivinghealth care. Available measures such as gen-eral measures of stages of change in psy-chotherapy may not be sensitive to suchdiscrepancies which could impact their asso-ciation with suicidal behavior. The LivingLadder was therefore specifically developedbased on research on the transtheoreticalmodel, the contemplation ladder, and desires(or reasons) to live among at-risk individuals(Figure 1). The Living Ladder uses the word-ing of the original contemplation ladder thatwas developed for smoking cessation (Biener& Abrams, 1991) and has been adapted multi-ple times including for alcohol and other druguse (Carey et al., 2001; Slavet et al., 2006). AsFigure 1 shows, the Living Ladder is an 8-point scale with four rungs that are anchoredto each of the first four stages of change,which range from precontemplation(0 = “Thinking that my life is not worth liv-ing”, 2 = “Think I need to start consideringmaking changes to make my life worth liv-ing”), contemplation (4 = “Think I shouldmake changes to make my life worth living,but not quite ready”), planning (6 = “Startingto think about how to make my life worth liv-ing”), to action (8 = “Taking action to makemy life worth living”). Note that the mainte-nance stage of the transtheoretical model wasnot included, because it was not part of theoriginal contemplation ladder (Biener &Abrams, 1991). It also was not clear whetherpatients would be able to differentiatebetween the action stage (i.e., “Taking actionto make my life worth living”) and mainte-nance stage (i.e., “Maintaining activities tomake sure my life remains worth living”).

We conducted the first test of the Liv-ing Ladder in a sample of veterans receiving a

BRITTON ET AL. 3

brief intervention to reduce suicidal ideation.We hypothesized that the motivation to livewould have convergent validity with suicidalthoughts such that it would be associated witha commonly used measure of suicidal idea-tion. More specifically, we expected thatscores on the Living Ladder would be signifi-cantly negatively associated with suicidalideation as conceptualized by the SSI butexpected that the association would be ofsmall magnitude, because people can beambivalent and simultaneously think aboutsuicide and living. Similarly, we expected theLiving Ladder to be positively associated withthe wish to live item on the SSI (reversescored to reflect wish to live) and negativelyassociated with the wish to die item, with theassociation being small. We also expectedthat readiness to continue living would beprospectively associated with suicidalthoughts and behavior, evidence of validity.We therefore hypothesized that scores on theLiving Ladder would be prospectively associ-ated with the presence and severity of suicidalideation as well as suicide attempts over6 months following discharge, such thathigher readiness to continue living scoreswould be inversely associated with the fre-quency of occurrence of suicidal ideation,

severity of suicidal ideation, and number ofsuicide attempts, respectively. We also exam-ined these associations when the Living Lad-der was administered by telephone to testwhether the Ladder was useful when thevisual analog was not available. Because webelieve the simplicity of the measure wouldallow it to be administered by telephone,hypotheses were the same for in-person andtelephone administration, although therewere not enough suicide attempts to test theprospective association of the Living Ladderwith suicide attempts by telephone adminis-tration.

METHODS

Sample

The sample consisted of 130 U.S. mili-tary veterans who were recruited from anacute psychiatric inpatient unit at a Depart-ment of Veterans Affairs Medical Center andenrolled in a randomized controlled trial(RCT) to test an adaptation of motivationalinterviewing to address suicidal ideation (MI-SI) that compared two different versions ofMI-SI to treatment as usual in VHA (Britton,

Have you been thinking about suicide?

Each rung on this ladder represents where various individuals who have been thinking about suicide are in making changes tomake their lives worth living. Circle the number that indicates where you are now.

8 Taking action to make my life worth living (e.g., changing substance use, enrolling in treatment).

7

6 Starting to think about how to make my life worth living.

5

4 Think I should make changes to make my life worth living, but not quite ready.

3

2 Think I need to start considering making changes to make my life worth living.

1

0 Thinking that my life is not worth living.

Figure 1. The living ladder.

4 LIVING LADDER

Conner, Chapman, & Maisto, 2019). Theoriginal sample was 132, but 2 (1.5%) did notcomplete the Living Ladder due to adminis-trative error. Potential participants wereidentified at morning clinical meeting,obtained approval to recruit from clinic staffthat approached patients, asked about theirinterest, and introduced interested partici-pants to research staff. Inclusion criteria were(1) U.S. military veteran status, (2) admittedto the unit, (3) 18 years of age, (4) Englishspeaking, (5) able to provide informed con-sent, (6) cleared to participate by attendingpsychiatrist, (7) receive health care from aVHA facility in upstate NY, and (8) clinicallysignificant suicidal ideation, defined as a score>2 on the SSI (Beck et al., 1979). Exclusioncriteria were (1) current psychosis using theMini-International Neuropsychiatric Inter-view (MINI; Sheehan et al., 1998), (2) currentmania using the MINI, (3) dementia with ascore <24 on the Mini-Mental Status Exami-nation (MMSE; Crum, Anthony, Bassett, &Folstein, 1993; Folstein, Folstein, &McHugh, 1975), (4) traumatic brain injury(TBI)-related dementia defined as loss of con-sciousness on The Ohio State TraumaticBrain Injury-ID (TBI-ID) short form (Corri-gan & Bogner, 2007) and a score <27 on theMMSE (O’Bryant et al., 2008), (5) being inac-cessible, and (6) plan to be discharged fromthe unit less than 48 hr after being identifiedby study staff. Although the veterans enteringthe unit and eligible for recruitment were pre-dominantly male and white non-Hispanic,females and minorities were included due tothe importance of addressing risk across allpopulations (Yano et al., 2010). The studywas approved by the facility InstitutionalReview Board.

Assessments

Patients who consented and met eligi-bility criteria during screening completed abaseline assessment in-person typically threeto four days after admission and follow-upassessments at 1, 3, and 6 months via tele-phone. The window for each follow-upassessment opened at the midpoint between

the previous assessment and the currentassessment and closed at the midpointbetween the current assessment and the fol-lowing assessment (e.g., opened two weeksbefore month 1 and closed at the end ofmonth 2). Follow-up ended 3 months afterthe target date for the 6-month follow-up.Follow-up assessors were blind to study con-dition.

Measures

Demographics. Standard sociodemo-graphic and veteran items were used todescribe the sample and assess veteran experi-ences.

Living Ladder. The Living Ladderitem developed for the study is shown in Fig-ure 1. The patient read or was read theinstructions and instructed to move up theladder to identify the number that best fitwhere they were.

Suicidal Ideation. The presence andseverity of suicidal ideation were measuredwith the SSI (Beck et al., 1979). The SSI is aninterview that measures the “intensity of thepatient’s specific attitudes, behaviors, andplans to commit suicide” (p. 4; Beck, Brown,Steer, Dahlsgaard, & Grisham, 1999), and ispsychometrically sound (Beck, Brown, &Steer, 1997), sensitive to change over time(Brown, Beck, Steer, & Grisham, 2000), andhas been used with veterans (Bell & Nye,2007). The SSI is typically used to measurecurrent suicidal ideation in the prior week aswell as suicidal ideation at the worst point inlife. Adapted for the current study, the SSIwas anchored to the week before hospitaliza-tion to assess the severity during the crisis thatled to hospitalization, and at the 1-, 3-, and 6-month assessments, the SSI was anchored tothe worst point since the last assessment incase there had been a crisis that had resolved.

Suicide Attempts. Suicide attemptswere assessed with the Colombia SuicideSeverity Rating Scale (C-SSRS; Posner,Oquendo, Gould, Stanley, & Davies, 2007).The C-SSRS has been mandated for use inmedication trials by the FDA and has shownconvergent and divergent validity, internal

BRITTON ET AL. 5

consistency, and high sensitivity and speci-ficity compared with other measures (Meyeret al., 2010; Mundt et al., 2013; Posner et al.,2011).

Analyses

Descriptive. Means (SD) and frequen-cies were calculated to describe the sample.We also examined means (SD) and the stabil-ity of the Living Ladder from baseline to 1, 1–3, and 3–6months, using a signed-rank testbecause distributions were not normal.

Cross-sectional. We examined the asso-ciation of the Living Ladder with the occur-rence of a suicide attempt in the month priorto hospitalization for the baseline in-personadministration. We also examined its associa-tion with the occurrence of suicidal ideationfor both in-person and telephone administra-tion.

In-person. The SSI scores wereoverdispersed such that the variance wasgreater than the mean. Accordingly, negativebinomial regression was used to examine theassociation with Living Ladder administeredin person and SSI at baseline. Logistic regres-sion was used to examine the Living Ladder’sassociation with lifetime history of attempts,reported as odds ratios (OR) with 95% confi-dence intervals (95% CI; Hosmer & Leme-show, 1989). The correlation of the LivingLadder with the wish to live item on the SSI(reverse scored to reflect the wish to live) aswell as the wish to die item was examined withSpearman’s rho as the distributions were notnormal.

Telephone. At each telephone fol-low-up assessment, the association of the Liv-ing Ladder with the presence and severity ofsuicidal ideation was examined using a zero-inflated Poisson, or if data were overdis-persed, a zero-inflated negative binomial.Worst point suicidal ideation since last assess-ment was used given evidence it is a strongerpredictor of future suicide attempts than cur-rent suicidal ideation (Beck et al., 1999).Zero-inflated models produce two sets ofparameter estimates: The first estimatereflects the probability that an independent

variable is associated with a score of zero; thesecond estimate reflects the variable’s associa-tion with the nonzero scores. Logistic regres-sion was used to estimate effect sizes for theabsence of suicidal ideation. Spearman’s rhowas also used to examine the correlation ofthe Living Ladder with the wish to live itemand wish to die items on the SSI.

Prospective. We examined the associa-tion of the Living Ladder with suicidal idea-tion for both in-person and telephoneadministration, but only examined its associa-tion with suicide attempts for in-personadministration as there were not enoughattempts at the 3- and 6-month follow-up toexamine the association for telephone admin-istration.

In-person. A zero-inflated Poissonmodel with robust standard error clustered byparticipants to account for repeated measureswas used to examine the prospective associa-tion of the Living Ladder for the absence andseverity of suicidal ideation combined overthe 6 months of follow-up. A Poisson withrobust standard error was used over a negativebinomial because the robust standard erroraccounted for much of the overdispersion,and the Poisson is a simpler model. Logisticregression was used to estimate effect sizes forthe absence of suicidal ideation. The associa-tion of the Living Ladder with subsequentsuicide attempts was examined using log-ranktests and cox proportional-hazard regressionto examine effect size of the incidence of sui-cide attempts over follow-up assessments.Participants were censored for loss to follow-up or a suicide attempt. Although the LivingLadder is typically scored on a continuousscale, the literature suggests that stage-basedmeasures may have stronger predictive prop-erties (Carey, Purnine, Maisto, & Carey,2002), so we also ran the models using cutoffscores on the Living Ladder. We conductedsensitivity analyses using a logistic regressionwith robust standard error to examine theassociation of the Living Ladder scored con-tinuously with the presence of a suicide planwhich was measured by scoring a 2 on item 13on the SSI, “method and opportunity avail-able or future availability anticipated.” We

6 LIVING LADDER

also compared those scoring in precontem-plation to those scoring in contemplation orabove in demographics and suicide attempthistory using Pearson’s chi-squares for cate-gorical variables and Kruskal–Wallis for ageas it was a continuous variable and its distri-bution was not normal. For analyses examin-ing prospective associations, unadjustedanalyses examined the association of the Liv-ing Ladder and the outcome was conducted,and adjusted analyses were also run. For suici-dal ideation, we adjusted for baseline ideation,and for suicide attempts, we adjusted for life-time history of attempts. Treatment condi-tions were not found to be significantlyassociated with outcome in the primary analy-ses (Britton et al., 2019), but were tested inpost hoc analyses that showed they did notimpact outcomes, and thus were not reported.

Telephone. A zero-inflated Poissonmodel with robust standard error clustered byparticipants to account for repeated measureswas also used to examine the association ofthe Living Ladder measured at 1 month withthe absence and severity of suicidal ideationassessed at months 3 and 6. Logistic regres-sion was used to estimate effect sizes for theabsence of suicidal ideation.

RESULTS

Withdrawals, Loss to Contact, andMissingData

Among the 130 participants, 83%(108/130) completed the 1-month follow-upassessment, 80% (104/130) the 3-month fol-low-up, and 77% (101/130) the 6-month fol-low-up. Data were missing completely atrandom (Little’s test X2 = 27.04, df = 25,p = .35).

Descriptive

The sample on average was middleaged and was predominantly male and white.These and other sociodemographic charac-teristics are described in Table 1. Scores onthe Living Ladder were negatively skewed,

with 35% scoring an 8, indicating that theywere taking action to make life worth living(Table 2). Scores on the Living Ladder chan-ged significantly from baseline to the 1-month follow-up, but not over subsequentfollow-up periods (Table 3). Regardingstages of change, scores from baseline to1 month crossed the threshold from contem-plating living (4 = “Think I should makechanges to make my life worth living, but notquite ready”) to planning (6 = “Starting tothink about how to make my life worth liv-ing”).

Cross-sectional Analyses

Severity of Suicidal Ideation and LifetimeHistory of Attempts. In-person. Approxi-mately 55% (n = 71) of the 130 participantsreported attempting suicide at least once dur-ing their lifetime. The Living Ladder scoredcontinuously was not associated with theseverity of suicidal ideation at baseline. It wasalso not associated with a suicide attempt inthe last month (Table 4). It was also not cor-related with baseline wish to live, rs(128) = .06, p = .48, or wish to die, rs(128) = .08, p = .35.

Telephone. The Living Ladder wasassociated with the presence of suicidal idea-tion at 1 and 3 months, with a one-point (i.e.,one-rung) increase on the measure associatedwith 31% lower odds of suicidal ideation at3 months and 39% at 6 months (Table 4).Living Ladder scores were associated with theseverity of suicidal ideation at 1 and6 months, but not at 3 months. It had a smallcorrelation with the worst point wish to liveat month 1, rs (104) = .24, p < .01, and month6, rs (97) = .29, p < .01, but not month 3, rs(101) = .08, p = .43, and a small correlationwith the wish to die at month 1, rs(104) = �.24, p < .01, month 3, rs(101) = �.21, p = .04, and month 6, rs(97) = �.32, p < .01.

Prospective Analyses

Presence and Severity of Suicidal Ideationover 6-month Follow-up. In-person. Living

BRITTON ET AL. 7

Ladder scores were associated with reducedlikelihood of suicidal ideation, with eachpoint or rung on the ladder associated with19% lower odds of suicidal ideation, and lesssevere ideation among those with it (Table 5).Findings changed minimally when analyseswere adjusted for baseline ideation, as eachpoint or rung was associated with 18% lowerodds of ideation, as well as less severe suicidalideation among those with it. Adjusting fortreatment assignment did not significantlyimpact these findings.

In sensitivity analyses, each rung on theLadder was associated with 17% lower oddshaving a plan, OR (95% CI) = 0.83 (0.72,0.94), p < .01, even after adjusting for thepresence of a plan at baseline, OR (95%CI) = 0.83 (0.72, 0.94), p < .01, which did nothave a significant association, OR (95%CI) = 0.95 (0.49, 1.85), p < .01, p = .88.

Telephone. Living Ladder scoresassessed at 1 month by telephone were associ-ated with the presence of suicidal ideation,with a one-point increase being associatedwith 24% lower odds of suicidal ideation overthe 3- and 6-month assessments. However,Living Ladder scores were not associatedwith the severity of suicidal ideation amongthose who had it. After controlling for base-line ideation, Living Ladder scores were asso-ciated with the presence of suicidal ideation,with a one-point increase associated with25% lower odds of suicidal ideation; however,it was also associated with less severe suicidalideation. Adjusting for treatment assignmentdid not significantly impact these findings.

In sensitivity analyses, each rung on theLadder was associated with 17% lower oddshaving a plan, OR (95% CI) = 0.83 (0.69,0.99), p < .01, but did not after adjusting forthe presence of a plan at 1 month, OR (95%CI) = 0.93 (0.77, 1.12), p < .01, which had arobust association with having a plan inmonths 3 and 6, OR (95% CI) = 4.76 (2.10,10.81), p < .001.

TABLE 1

Sample Demographics

Total(N = 130)n (%)

Age (mean (SD)) 45.38 (12.53)Male 116 (89.23)RaceWhite 100 (76.92)Black 18 (13.85)American Indian or AlaskanNative

3 (2.31)

Native Hawaiian or PacificIslander

2 (1.54)

Biracial/multiracial 7 (5.38)EthnicityHispanic/Latino 3 (2.31)

Marital statusMarried 43 (33.08)Divorced/separated 56 (43.08)Never married 25 (19.23)Widowed 6 (4.62)

EmploymentPart/fulltime/self-employed 24 (18.46)Student/homemaker 2 (1.54)Unemployed 35 (26.92)Disabled or retired 68 (52.31)Other 1 (0.77)

Years of service (mean (SD)) 6.60 (6.43)EraPost 9/11 (2001-present) 37 (28.46)Desert storm/shield (1990–2001) 10 (7.79)Post-Vietnam Peace (1975–1990)

31 (23.48)

VietnamWar (1964–1975) 10 (7.69)Post-Korea Peace (1955–1964) 2 (1.54)Multiple Eras 40 (30.77)

Combat exposure 60 (46.15)

TABLE 2

Frequency of Living Ladder Scores

ScoreaFrequencyN = 130 Percent

Cumulativepercent

0 4 3.08 3.081 7 5.38 8.462 15 11.54 20.003 5 3.85 23.854 14 10.77 34.625 8 6.15 40.776 22 16.92 57.697 10 7.69 65.388 45 34.62 100.00

a0 = Thinking that my life is not worth liv-ing, 8 = Taking action to make life worth living.

8 LIVING LADDER

Risk for Suicide Attempts over 6-monthFollow-up. In-person. A total of 16 (12%)participants attempted suicide during the 6-month follow-up. When examined as a con-tinuous measure, the Living Ladder was notsignificantly associated with suicide attempts(log-rank X2 = 12.13, df = 1, p = .14). Aftercomparing observed and expected events ateach stage of change, the observed toexpected attempts appeared lower for scoresat or above contemplation (Living Ladder >2;Table 6). In post hoc analyses, scores abovethe cutoff of 2 for contemplation were associ-ated with significantly lower risk for a suicideattempt (log-rank X2 = 7.3, df = 1, p = .01),suggesting that patients who reported con-templating living were at 71% lower risk for asuicide attempt than those in precontempla-tion, hazard ratio (HR) with 95% confidenceinterval (95% CI) = 0.29 (0.11, 0.77). Con-templating living was also associated withlower risk by 64%, HR (95% CI) = 0.36

(0.13, 0.98), after adjusting for lifetime his-tory of attempts. A lifetime history ofattempts increased risk for a suicide attemptfivefold, HR (95% CI) = 5.07 (1.14, 22.58).Adjusting for treatment assignment did notsignificantly affect these findings.

Sensitivity analyses indicated that therewere no statistically significant differencesbetween precontemplators and contempla-tors for demographics or suicide attempt his-tory, although suicide attempt historyapproached significance with 69% (18/26) ofprecontemplators reporting lifetime attemptscompared to 51% (53/104) of contemplators,X2 (1, N = 130) = 2.80, p = .09. Attempt his-tory was controlled for in analyses as noted.

DISCUSSION

This study was designed to evaluate theLiving Ladder’s validity through examination

TABLE 3

Living LadderMeans (SD) and Sensitivity to Change

Time 1 vs. Time 2 nTime 1M (SD)

Time 2M (SD) z p

Base vs. 1 month 106 5.42 (2.56) 6.47 (1.93) �3.82 <.0011 month vs. 3 months 92 6.38 (1.97) 6.63 (1.88) �1.12 .263 months vs. 6 months 92 6.71 (1.87) 6.62 (1.95) 0.22 .83

TABLE 4

Living Ladder Cross-Sectional Associations with Presence and Severity of Suicidal Ideation and SuicideAttempt Last Month

SIFree

Odds of SA or SI

SISeverity (those with SI)

b SE p OR (95%CI) b SE p

Suicide attempt last monthBase 1.00 (0.85, 1.18)

Suicidal ideationBase �0.02 0.01 .091 month 0.38 0.14 .01 0.69 (0.52, 0.90) �0.04 0.01 .003 months 0.51 0.19 .01 0.61 (0.41, 0.89) �0.01 0.02 .496 months 0.22 0.14 .12 0.80 (0.61, 1.05) �0.11 0.04 .01

BRITTON ET AL. 9

of suicidal ideation (measured cross-section-ally and prospectively over 6 months) and sui-cide attempts (measured prospectively over6 months). Scores above the cutoff for con-templation were associated with lower risk forattempts than those below the cutoff, evenafter adjusting for prior attempts (Joiner

et al., 2005). These results suggest that think-ing about engaging in activities that are asso-ciated with living is a potential pathway toreducing risk for suicide attempts amongpatients who are thinking about suicide.However, it may also indicate that the LivingLadder is a better measure of contemplationthan it is of planning or action, which is rele-vant as 35% of participants reported that theywere in the action stage of making life worthliving. One possibility is that suicidal patientson inpatient units who want to be releasedmay report higher scores on the ladder,reducing the validity of the higher registers.Another possibility is that a subset of patientsmay fluctuate between being intensely suici-dal and committed to living. For suchpatients, a higher score may be a result oftheir extreme volatility which may in turn beassociated with increased risk for suicideattempts (Kimbrel et al., 2014; Smith et al.,2016; Witte, Fitzpatrick, Warren,Schatschneider, & Schmidt, 2006). Yet,another possibility is that patients on an inpa-tient unit can make changes that do notreduce their suicidality after discharge. Giventhat there was no a priori hypothesis

TABLE 5

Prospective Associations of the Living ladder (LL) with the Presence and Severity of Suicidal Ideation

SIFree Odds of SI

SISeverity (thosewith SI)

b SE p OR (95%CI) b SE p

Face-to-faceUnadjustedLL 0.21 0.08 .01 0.81 (0.69, 0.95) �0.07 0.21 .001SSI current �0.05 0.01 .02 1.05 (1.01, 1.09) 0.01 0.01 .10

AdjustedLL 0.20 0.08 .02 0.82 (0.68, 0.96) �0.07 0.02 .002SSI current �0.04 0.02 .06 1.04 (1.00, 1.08) 0.01 0.01 .21

TelephoneUnadjustedLL 0.27 0.12 .02 0.76 (0.61, 0.95) �0.05 0.03 .11SSI current �0.05 0.02 .02 1.05 (1.01, 1.10) 0.02 0.01 .01

AdjustedLL 0.28 0.11 .01 0.75 (0.60, 0.94) �0.07 0.03 .03SSI current �0.04 0.03 .10 1.04 (0.99, 1.10) 0.02 0.01 .01

TABLE 6

Living Ladder Observed and Expected SuicideAttempts

Scorea Observed Expected

0 1 0.45 Precontemplation1 1 1.002b 5 1.483 0 0.66 Contemplation4 2 1.695 0 0.956 2 3.017 1 1.328 4 5.44

a0 = Thinking that my life is not worth liv-ing, 8 = Taking action to make life worth living.

b2 was determined to be the ideal cutoff dueto the difference between observed and expectedsuicide attempts.

10 LIVING LADDER

regarding contemplation being the criticalstage for predicting suicide attempts, thisfinding needs to be replicated.

Scored continuously, the Living Lad-der also predicted both the presence andseverity of worst point suicidal ideation over6 months following discharge, even afteradjusting for baseline line suicidal ideation. Itwas also associated with having a well-formu-lated suicide plan. Interestingly, higher scoreson the Living Ladder that are associated withplanning and action may be better predictorsof the presence and severity of suicidal idea-tion than behaviors such as suicide attempts.The finding for presence of suicidal ideationas measured over months 3 and 6 was repli-cated when the Living Ladder was adminis-tered by telephone at 1 month. However, itwas not associated with a suicide plan, likely aresult of the robust association of the pres-ence of a plan after discharge, rather than theadministration modality.

Despite having predictive validity forideation, the Living Ladder was associatedwith the presence of suicidal ideation in 2 of 3and severity of suicidal ideation in 2 of 4cross-sectional analyses. One null finding forseverity was likely a result of nonoverlappingtime frames at baseline, and another reasonmay be because ambivalence about suicide,wanting to both live and die, is common.Relatedly, the Living Ladder was not signifi-cantly associated with the wish to live andwish to die at baseline but mostly had a smallstatistically significant association with wishto live and wish to die over follow-up in theexpected directions. Yet, another reason forinconsistent findings may be a result of thechallenge of measuring unstable suicidalthoughts. The SSI measures the most severelevel of suicidal ideation in the time since theprior assessment, providing an upper levelsummary score that has predicative validity(Beck et al., 1999). However, such summaryscores are only one method of assessing suici-dal ideation and do not include all criticalinformation regarding suicidal thoughts, suchas its variability, which also increases risk(Bryan, Rozek, Butner, & Rudd, 2019; Witte,Fitzpatrick, Joiner, & Schmidt, 2005; Witte

et al., 2006). A more detailed examination ofthe association of readiness to continue livingwith fluctuations of suicidal thoughts maytherefore also be informative.

The Living Ladder is a one-item mea-sure and thus is practical for clinical use. Fur-thermore, its development was informed byboth the transtheoretical model of change(Prochaska et al., 2015), wish to die/liveindexes (Jobes, 2010; Kovacs & Beck, 1977)and reasons for living (Linehan et al., 1983).The Living Ladder is also a rare measure inthe suicide research field to have a positivevalence, with higher scores conceptualized asprotective from suicidal behavior. Unlikemany protective factors (e.g., age, sex, socioe-conomic status), scores on the Living Laddermay be expected to change over time asdemonstrated in this study. Conceptually, theLiving Ladder may also be hypothesized torespond to clinical intervention, an importantfocus of future research. These attributes ofthe Living Ladder suggest its practical utilityand that it merits further researchmoving for-ward.

These results have implications for thetreatment of patients in acute psychiatric hos-pitalization. The Living Ladder requires min-imal training to administer and can beadministered rapidly to at-risk patients in-person or over the phone. It could be used tohelp clinicians tailor their suicide-related careto the specific stage of change the patient isendorsing, potentially improving the clini-cian’s ability to provide patient-centered careand serve as a moderator of interventionsbased on whether the intervention is consis-tent with the patient’s stage of change. It isalso possible that motivation to live is animportant mechanism for interventions tar-geting risk for suicide attempts, as the LivingLadder was sensitive to change in this high-risk population, but only when suicidal crisiswas compared to a postcrisis assessment. Out-side of suicidal crises, the readiness to con-tinue living may be somewhat stable, which isinteresting as the majority of people to makesuicide attempts do not die by suicide. Such amechanism would be not only important formotivationally based treatments (Britton,

BRITTON ET AL. 11

2015; Britton, Conner, & Maisto, 2012), butmay also be critical to understanding theeffectiveness of dialectical behavioral therapywhich targets barriers to treatment and hasthe goal of building a life worth living (Line-han, 1993), other cognitive behavioral treat-ments that have been shown to increase thewish to live and reduce risk for suicidal idea-tion and attempts (Brown et al., 2005; Bryanet al., 2016; Rudd et al., 2015), and the teach-able moment intervention that has beenshown to increase readiness for psychother-apy among patients with recent suicideattempts (O’Connor et al., 2015; O’Connoret al., 2018).

The results of this study also have theo-retical implications. The processes wherebypeople transition from not thinking about sui-cide to making an attempt are widely believedto be of key importance, and the factors thatfacilitate the development of suicidalthoughts may differ in key respects from thosethat contribute to the transition to behavior(Joiner, 2005; Klonsky & May, 2015; O’Con-nor & Kirtley, 2018; Van Orden et al., 2010).Given the association of readiness to continueliving with both suicidal ideation andattempts, the current findings suggest thatsuch readiness may be associated with a lowerlikelihood of thinking about suicide and act-ing upon their thoughts. To deepen ourunderstanding of the associations among thestages of readiness to continue living and thesuicide process, researchers may want toexamine the differential associations of con-templation, preparation, and action to eachphase.

The results of this study also suggestthat there may be competing processes thatprotect people from considering suicide andengaging in suicidal behavior. Activating thereadiness or motivation to live may also be amultistep process with different factors asso-ciated with contemplation, preparation, andengagement in life enhancing and sustainingactivities that provide protection. A similarprocess has been studied in meaning in liferesearch, which examines both the presenceand search for meaning. Although negativeconstructs such as depressive symptoms, fear,

isolation, and self-criticism are cross-section-ally associated with the search for meaning(Steger, Frazier, Oishi, & Kaler, 2006; Steger,Kashdan, Sullivan, & Lorentz, 2008), thesearch for meaning is prospectively associatedwith less future suicidal ideation (Kleiman &Beaver, 2013). The presence of meaning itselfis associated with fewer lifetime attempts andless future suicidal ideation (Kleiman & Bea-ver, 2013) and mediates the association ofgratitude, grit, and reasons for living with sui-cidal ideation (Heisel, Neufeld, & Flett,2016; Kleiman, Adams, Kashdan, & Riskind,2013). Thus, people tend to search for mean-ing when they are feeling dissatisfied withtheir lives, but the search may be protectivewhen meaning is found. Similar nuances maybe relevant to the readiness to continue livingwhen thinking about suicide. Contemplatingliving, for example, is likely to be more pro-tective for individuals who have adequatesocial and/or economic resources than forthose lacking such resources.

There are limitations of the currentstudy. The sample was veterans in acute psy-chiatric hospitalization, and although theexamination of SI and SA in this population iscritical, research is needed to examine predic-tive validity in other high-risk populations.There were too few suicide attempts over fol-low-up for empirical examination of theprospective association of the Living Ladderand suicide attempts when administered bytelephone. The follow-up period was rela-tively short-term (6 months). Relevance ofthe current findings to suicide deaths isunclear. There was also limited data onrelated constructs such as reasons for living,meaning in life, and positive affect to evaluateconvergent/divergent validity.

These limitations notwithstanding,this study showed that an easily administered,one-item measure of readiness to continueliving is associated with the presence andseverity of suicidal ideation and risk for sui-cide attempts over follow-up following dis-charge from acute psychiatric hospitalization.Brief, validated measures have exciting poten-tial to improve clinician’s ability to identifysubjects requiring additional intervention and

12 LIVING LADDER

to make empirically informed treatment deci-sions (Swets, Dawes, & Monahan, 2000) andcan be implemented into standard practice(Bryan, 2018; Zerhouni, 2005). Given the riskfor suicide in the weeks and months followingpsychiatric hospitalization (Appleby et al.,1999; Britton et al., 2017; Chung et al., 2017;Goldacre, Seagroatt, & Hawton, 1993; Mee-han et al., 2006; Olfson et al., 2016; Qin &

Nordentoft, 2005), this measure has potentialfor widespread implementation. The resultsalso illustrate that readiness to continue liv-ing, a time-varying protective factor that isamenable to intervention, is prospectivelyassociated with suicidal ideation and suicideattempt, reinforcing the importance of target-ing and measuring reasons for living in thetreatment and study of at-risk patients.

REFERENCES

AMODEI, N., & LAMB, R. J. (2004). Conver-gent and concurrent validity of the contemplationladder and URICA scales. Drug and Alcohol Depen-dence, 73(3), 301–306.

APPLEBY, L., SHAW, J., AMOS, T., MCDON-

NELL, R., HARRIS, C., MCCANN, K., ET AL. (1999).Suicide within 12 months of contact with mentalhealth services: National clinical survey. BMJ(Clinical Research Ed.), 318(7193), 1235–1239.

BECK, A. T., BROWN, G. K., & STEER,R. A. (1997). Psychometric characteristics ofthe scale for suicide ideation with psychiatricoutpatients. Behaviour Research and Therapy, 35(11), 1039–1046.

BECK, A. T., BROWN, G. K., STEER, R. A.,DAHLSGAARD, K. K., & GRISHAM, J. R. (1999). Sui-cide ideation at its worst point: A predictor of even-tual suicide in psychiatric outpatients. Suicide andLife-Threatening Behavior, 29(1), 1–9.

BECK, A. T., KOVACS, M., & WEISSMAN, A.(1979). Assessment of suicidal intention: The scalefor suicide ideation. Journal of Consulting and Clini-cal Psychology, 47(2), 343–352.

BELL, J. B., & NYE, E. C. (2007). Specificsymptoms predict suicidal ideation in Vietnamcombat veterans with chronic post-traumatic stressdisorder.MilitaryMedicine, 172(11), 1144–1147.

BIENER, L., & ABRAMS, D. B. (1991). Thecontemplation ladder: Validation of a measure ofreadiness to consider smoking cessation. HealthPsychology, 10(5), 360–365.

BRITTON, P. C. (2015). Motivational inter-viewing to address suicidal ideation. In H. Arkow-itz,W. R.Miller, & S. Rollnick (Eds.),Motivationalinterviewing in the treatment of psychological problems(2nd ed., pp. 193–218). New York, NY: The Guil-ford Press.

BRITTON, P. C., BOHNERT, K.M., ILGEN,M.A., KANE, C., STEPHENS, B., & PIGEON, W. R.(2017). Suicide mortality among male veterans dis-charged from Veterans Health Administrationacute psychiatric units from 2005 to 2010. SocialPsychiatry and Psychiatric Epidemiology, 52(9), 1081–1087. https://doi.org/10.1007/s00127-017-1377.

BRITTON, P. C., CONNER, K. R., CHAPMAN,B. P., & MAISTO, S. A. (2019). Motivational inter-viewing to address suicidal ideation: a randomizedcontrolled trial in veterans. Suicide and Life-Threat-ening Behavior, 50(1), 233–248. https://doi.org/10.1111/sltb.12581.

BRITTON, P. C., CONNER, K. R., & MAISTO,S. A. (2012). An open trial of motivational inter-viewing to address suicidal ideation with hospital-ized veterans. Journal of Clinical Psychology, 68(9),961–971.

BROWN, G. K., BECK, A. T., STEER, R. A., &GRISHAM, J. R. (2000). Risk factors for suicide inpsychiatric outpatients: A 20-year prospectivestudy. Journal of Consulting and Clinical Psychology,68(3), 371–377.

BROWN, G. K., HAVE, T. T., HENRIQUES, G.R., XIE, S. X., HOLLANDER, J. E., & BECK, A. T.(2005). Cognitive therapy for the prevention of sui-cide attempts: A randomized controlled trial.JAMA: Journal of the American Medical Association,294(5), 563–570.

BROWN, G. K., STEER, R. A., HENRIQUES, G.R., & BECK, A. T. (2005). The internal strugglebetween the wish to die and the wish to live: A riskfactor for suicide. The American Journal of Psychia-try, 162(10), 1977–1979. https://doi.org/10.1176/appi.ajp.162.10.1977.

BRUDERN, J., STAHLI, A., GYSIN-MAILLART,A., MICHEL, K., REISCH, T., JOBES, D. A., ET AL.(2018). Reasons for living and dying in suicideattempters: A two-year prospective study. BMCPsychiatry, 18(1), 1–9. https://doi.org/10.1186/s12888-018-1814-8.

BRYAN, C. J. (2018). A preliminary valida-tion study of two ultra-brief measures of suiciderisk: The suicide and perceived burdensomenessvisual analog scales. Suicide and Life-ThreateningBehavior, 49(2), 343–352. https://doi.org/10.1111/sltb.12447.

BRYAN, C. J., ROZEK, D. C., BUTNER, J., &RUDD, M. D. (2019). Patterns of change in suicideideation signal the recurrence of suicide attemptsamong high-risk psychiatric outpatients. Behaviour

BRITTON ET AL. 13

Research and Therapy, 120, 103392. https://doi.org/10.1016/j.brat.2019.04.001.

BRYAN, C. J., RUDD, M. D., PETERSON, A.L., YOUNG-MCCAUGHAN, S., &WERTENBERGER, E.G. (2016). The ebb and flow of the wish to live andthe wish to die among suicidal military personnel.Journal of Affective Disorders, 202, 58–66. https://doi.org/10.1016/j.jad.2016.05.049.

CAREY, K. B., MAISTO, S. A., CAREY, M. P.,& PURNINE, D. M. (2001). Measuring readiness-to-change substance misuse among psychiatricoutpatients: I. reliability and validity of self-reportmeasures. Journal of Studies on Alcohol, 62(1), 79–88.

CAREY, K. B., PURNINE, D. M., MAISTO, S.A., & CAREY, M. P. (2002). Correlates of stages ofchange for substance abuse among psychiatric out-patients. Psychology of Addictive Behaviors, 16(4),283–289.

Centers for Disease Control and Preven-tion. (2017). Wisqars injury mortality reports 1981–2017. Retrieved March 8, 2019, from https://www.cdc.gov/injury/wisqars/fatal.html

CHUNG, D. T., RYAN, C. J., HADZI-PAVLO-

VIC, D., SINGH, S. P., STANTON, C., & LARGE, M.M. (2017). Suicide rates after discharge from psy-chiatric facilities: A systematic review and meta-analysis. JAMA Psychiatry, 74(7), 694–702.https://doi.org/10.1001/jamapsychiatry.2017.1044.

CORRIGAN, J. D., & BOGNER, J. (2007). Ini-tial validity and reliability of the Ohio StateUniversity TBI identification method. Journal ofHead Trauma Rehabilitation, 22(6), 318–329.

CRUM, R. M., ANTHONY, J. C., BASSETT, S.S., & FOLSTEIN, M. F. (1993). Population-basednorms for the mini-mental state examination byage and educational level. JAMA, 269(18), 2386–2391.

Department of Veterans Affairs, Office ofSuicide Prevention. (2016). Suicide among veteransand other Americans 2001–2014. U.S. Department ofVeterans Affairs. Retrieved March 8, 2019, fromhttp://www.mentalhealth.va.gov/

FOLSTEIN, M. F., FOLSTEIN, S. E., &MCHUGH, P. R. (1975). Mini-mental state. Journalof Psychiatric Research, 12, 189–198.

FRANKLIN, J. C., RIBEIRO, J. D., FOX, K. R.,BENTLEY, K. H., KLEIMAN, E. M., HUANG, X.,ET AL. (2017). Risk factors for suicidal thoughts andbehaviors: A meta-analysis of 50 years of research.Psychological Bulletin, 143(2), 187–232. https://doi.org/10.1037/bul0000084.

GOLDACRE, M., SEAGROATT, V., & HAW-

TON, K. (1993). Suicide after discharge from psy-chiatric inpatient care. Lancet, 342(8866), 283–286.

HEISEL, M. J., NEUFELD, E., & FLETT, G. L.(2016). Reasons for living, meaning in life, and sui-cide ideation: Investigating the roles of key positive

psychological factors in reducing suicide risk incommunity-residing older adults. Aging & MentalHealth, 20(2), 195–207.

HOGUE, A., DAUBER, S., & MORGENSTERN,J. (2010). Validation of a contemplation ladder inan adult substance use disorder sample. Psychologyof Addictive Behaviors, 24(1), 137–144.

HOSMER, D. W., & LEMESHOW, S. (1989).Applied logistic regression. New York, NY:Wiley.

JOBES, D. A. (2010). Managing suicidal risk:A collaborative approach. New York, NY: The Guil-ford Press.

JOINER, T. E. J. (2005).Why people die by sui-cide. Cambridge, MA:Harvard University Press.

JOINER, T. E. J., CONWELL, Y., FITZPATRICK,K. K., WITTE, T. K., SCHMIDT, N. B., BERLIM, M.T., ET AL. (2005). Four studies on how past andcurrent suicidality relate even when "everythingbut the kitchen sink" is covaried. Journal of Abnor-mal Psychology, 114(2), 291–303.

KIMBREL, N. A., CALHOUN, P. S., ELBOGEN,E. B., BRANCU, M., VA Mid-Atlantic MIRECCRegistry Workgroup, & BECKHAM, J. C. (2014).The factor structure of psychiatric comorbidityamong Iraq/Afghanistan-era veterans and its rela-tionship to violence, incarceration, suicideattempts, and suicidality. Psychiatry Research, 220(1–2), 397–403.

KLEIMAN, E. M., ADAMS, L. M., KASHDAN,T. B., & RISKIND, J. H. (2013). Gratitude and gritindirectly reduce risk of suicidal ideations byenhancingmeaning in life: Evidence for a mediatedmoderation model. Journal of Research in Personal-ity, 47(5), 539–546.

KLEIMAN, E. M., & BEAVER, J. K. (2013). Ameaningful life is worth living: Meaning in life as asuicide resiliency factor. Psychiatry Research, 210(3),934–939.

KLONSKY, E. D., & MAY, A. M. (2015). Thethree-step theory (3ST): A new theory of suiciderooted in the “ideation-to-action” framework.International Journal of Cognitive Therapy, 8(2),114–129.

KOVACS, M., & BECK, A. T. (1977). Thewish to die and the wish to live in attempted sui-cides. Journal of Clinical Psychology, 33(2), 361–365.

KREBS, P., NORCROSS, J. C., NICHOLSON, J.M., & PROCHASKA, J. O. (2018). Stages of changeand psychotherapy outcomes: A review and meta-analysis. Journal of Clinical Psychology, 74(11), 1964–1979.

LINEHAN, M. M. (1993). Cognitive-behav-ioral treatment of borderline personality disorder. NewYork, NY: Guilford Press.

LINEHAN, M. M., GOODSTEIN, J. L., NIEL-

SEN, S. L., & CHILES, J. A. (1983). Reasons for stay-ing alive when you are thinking of killing yourself:The reasons for living inventory. Journal of Consult-ing and Clinical Psychology, 51(2), 276–286.

14 LIVING LADDER

MALONE, K.M., OQUENDO, M. A., HAAS, G.L., ELLIS, S. P., LI, S., &MANN, J. J. (2000). Protec-tive factors against suicidal acts in major depres-sion: Reasons for living. American Journal ofPsychiatry, 157(7), 1084–1088.

MCCARTHY, J. F., BOSSARTE, R. M., KATZ, I.R., THOMPSON, C., KEMP, J., HANNEMANN, C. M.,ET AL. (2015). Predictive modeling and concentra-tion of the risk of suicide: Implications for preven-tive interventions in the US Department ofVeterans Affairs. American Journal of Public Health,105(9), 1935–1942.

MEEHAN, J., KAPUR, N., HUNT, I. M., TURN-

BULL, P., ROBINSON, J., BICKLEY, H., ET AL. (2006).Suicide in mental health in-patients and within 3months of discharge. National clinical survey. Bri-tish Journal of Psychiatry, 188, 129–134.

MEYER, R. E., SALZMAN, C., YOUNG-

STROM, E. A., CLAYTON, P. J., GOODWIN, F. J.,MANN, J. J., ET AL. (2010). Suicidality and riskof suicide- definition, drug safety concerns, anda necessary target for drug development: Aconsensus statement. Journal of Clinical Psychia-try, 71(8), e1–e21.

MUNDT, J. C., GREIST, J. H., JEFFERSON, J.W., FEDERICO, M., MANN, J. J., & POSNER, K.(2013). Prediction of suicidal behavior in clinicalresearch by lifetime suicidal ideation and behaviorascertained by the electronic Columbia-suicideseverity rating scale. Journal of Clinical Psychiatry,74(9), 887–893.

National Center for Veterans Analysis andStatistics. (2017). Restoring trust in veterans health-care: Fiscal year 2016 annual report. Washington,DC: Veterans Health Administration. RetrievedMarch 8, 2019, from https://www.va.gov/HEALTH/docs/VHA_AR16.pdf

O’BRYANT, S. E., HUMPHREYS, J. D., SMITH,G. E., IVNIK, R. J., GRAFF-RADFORD, N. R., PETER-

SEN, R. C., ET AL. (2008). Detecting dementia withthe mini-mental state examination in highly edu-cated individuals. Archives of Neurology, 65(7), 963–967.

O’CONNOR, R. C., & KIRTLEY, O. J. (2018).The integrated motivational-volitional model ofsuicidal behaviour. Philosophical Transactions of theRoyal Society of London. Series B, Biological Sciences,373(1754), 1–10. https://doi.org/10.1098/rstb.2017.0268.

O’CONNOR, S. S., COMTOIS, K. A., WANG,J., RUSSO, J., PETERSON, R., LAPPINGCARR, L.,ET AL. (2015). The development and implementa-tion of a brief intervention for medically admittedsuicide attempt survivors. General Hospital Psychia-try, 37(5), 427–433.

O’CONNOR, S. S., JOBES, D. A., YEARGIN, M.K., FITZGERALD, M. E., RODRIGUEZ, V. M., CON-

RAD, A. K., ET AL. (2012). A cross-sectional investi-gation of the suicidal spectrum: Typologies of

suicidality based on ambivalence about living anddying.Comprehensive Psychiatry, 53(5), 461–467.

O’CONNOR, S. S., MCCLAY, M. M.,CHOUDHRY, S., SHIELDS, A. D., CARLSON, R.,ALONSO, Y., ET AL. (2018). Pilot randomized clini-cal trial of the Teachable Moment Brief Interven-tion for hospitalized suicide attempt survivors.General Hospital Psychiatry, 1–9.

OLFSON, M., WALL, M., WANG, S., CRYS-

TAL, S., LIU, S. M., GERHARD, T., ET AL. (2016).Short-term suicide risk after psychiatric hospitaldischarge. JAMA Psychiatry, 73(11), 1119–1126.https://doi.org/10.1001/jamapsychiatry.2016.2035.

OSMAN, A., GIFFORD, J., JONES, T., & LICK-

ISS, L. (1993). Psychometric evaluation of the rea-sons for living inventory. Psychological Assessment, 5(2), 154–158.

OSMAN, A., KOPPER, B. A., LINEHAN, M. M.,BARRIOS, F. X., GUTIERREZ, P. M., & BAGGE, C. L.(1999). Validation of the adult suicidal ideationquestionnaire and the reasons for living inventoryin an adult psychiatric inpatient sample. Psychologi-cal Assessment, 11(2), 115–123.

POSNER, K., BROWN, G. K., STANLEY, B.,BRENT, D. A., YERSHOVA, K. V., OQUENDO, M. A.,ET AL. (2011). The Columbia-suicide severity rat-ing scale: Initial validity and internal consistencyfindings from three multisite studies with adoles-cents and adults. American Journal of Psychiatry, 168(12), 1266–1277.

POSNER, K., OQUENDO, M. A., GOULD, M.,STANLEY, B., & DAVIES, M. (2007). Columbia clas-sification algorithm of suicide assessment (C-CASA): Classification of suicidal events in theFDA’s pediatric suicidal risk analysis of antidepres-sants. American Journal of Psychiatry, 164(7), 1035–1043.

PROCHASKA, J. O., NORCROSS, J. C., &DICLEMENTE, C. C. (2013). Applying the stages ofchange. In G. P. Koocher, J. C. Norcross, & B. A.Greene (Eds.), Psychologists’ desk reference (3rd ed.,pp. 176–181). New York, NY: Oxford UniversityPress.

PROCHASKA, J. O., REDDING, C. A., & EVERS,K. E. (2015). The transtheoretical model andstages of change. In K. Glanz, B. K. Rimer, & K.Viswanath (Eds.), Health behavior: Theory, research,and practice (5th ed., pp. 125–148). San Francisco,CA: Jossey-Bass.

QIN, P., & NORDENTOFT, M. (2005). Sui-cide risk in relation to psychiatric hospitalization:Evidence based on longitudinal registers. Archivesof General Psychiatry, 62(4), 427–432.

RUDD,M. D., BRYAN, C. J.,WERTENBERGER,E. G., PETERSON, A. L., YOUNG-MCCAUGHAN, S.,MINTZ, J., ET AL. (2015). Brief cognitive-behavioraltherapy effects on post-treatment suicide attemptsin a military sample: Results of a randomized

BRITTON ET AL. 15

clinical trial with 2-year follow-up. American Jour-nal of Psychiatry, 172(5), 441–449.

RYAN, R. M., & DECI, E. L. (2002). Over-view of self-determination theory: An organismic-dialectical perspective. In E. L. Deci, &R.M. Ryan(Eds.), Handbook of self-determination research (pp.3–33). Rochester, NY: University of RochesterPress.

SHEEHAN, D. V., LECRUBIER, Y., SHEEHAN,K. H., AMORIM, P., JANAVS, J., WEILLER, E., ET AL.(1998). The mini-international neuropsychiatricinterview (M.I.N.I.): The development and valida-tion of a structured diagnostic psychiatric inter-view for DSM-IV and ICD-10. Journal of ClinicalPsychiatry, 59(Suppl 20), 22–33.

SLAVET, J. D., STEIN, L. A. R., COLBY, S. M.,BARNETT, N. P., MONTI, P. M., GOLEMBESKE, C. J.,ET AL. (2006). The marijuana ladder: Measuringmotivation to change marijuana use in incarceratedadolescents. Drug and Alcohol Dependence, 83(1),42–48.

SMITH, N. B., MOTA, N., TSAI, J., MON-

TEITH, L., HARPAZ-ROTEM, I., SOUTHWICK, S. M.,ET AL. (2016). Nature and determinants of suicidalideation among U.S. veterans: Results from thenational health and resilience in veterans study.Journal of Affective Disorders, 197, 66–73.

STEGER, M. F., FRAZIER, P., OISHI, S., &KALER, M. (2006). The meaning in life question-naire: Assessing the presence of and search formeaning in life. Journal of Counseling Psychology, 53(1), 80–93.

STEGER, M. F., KASHDAN, T. B., SULLIVAN,B. A., & LORENTZ, D. (2008). Understanding thesearch for meaning in life: Personality, cognitive

style, and the dynamic between seeking and experi-encing meaning. Journal of Personality, 76(2), 199–228.

SWETS, J. A., DAWES, R. M., &MONAHAN, J.(2000). Psychological science can improve diag-nostic decisions. Psychological Science in the PublicInterest, 1(1), 1–26.

VAN ORDEN, K. A., WITTE, T. K.,CUKROWICZ, K. C., BRAITHWAITE, S. R., SELBY,E. A., & JOINER, T. E., JR, (2010). The inter-personal theory of suicide. Psychological Review,117(2), 575–600.

WITTE, T. K., FITZPATRICK, K. K., JOINER,T. E. JR., & SCHMIDT, N. B. (2005). Variability insuicidal ideation: A better predictor of suicideattempts than intensity or duration of ideation?Journal of Affective Disorders, 88(2), 131–136.

WITTE, T. K., FITZPATRICK, K. K.,WARREN, K. L., SCHATSCHNEIDER, C., & SCHMIDT,N. B. (2006). Naturalistic evaluation of suicidalideation: Variability and relation to attempt status.Behaviour Research & Therapy, 44(7), 1029–1040.

YANO, E. M., HAYES, P., WRIGHT, S., SCH-

NURR, P. P., LIPSON, L., BEAN-MAYBERRY, B., ET AL.(2010). Integration of women veterans into VAquality improvement research efforts: Whatresearchers need to know. Journal of General Inter-nal Medicine, 25(Suppl 1), 56–61.

ZERHOUNI, E. A. (2005). Translational andclinical science–time for a new vision. The NewEngland Journal of Medicine, 353(15), 1621–1623.https://doi.org/10.1056/NEJMsb053723.

Manuscript Received: August 26, 2019Revision Accepted: February 18, 2020

16 LIVING LADDER