Studying treatment of suicidal ideation & attempts: Designs, Statistical Analysis, and Methodological

Considerations

Jill M. Harkavy-Friedman, Ph.D.

Objective: To review the design and methodological factors that impact the study of interventions for suicidal ideation and attempts

Includes Evaluate the impact of the intervention Evaluate the intervention itself

Review of design Review of design considerations:considerations:

GoalsDesignSampleMeasuresProceduresData AnalysisTreatment Evaluation

GoalsGoals

Theory/ RationaleMeaningfulTestable hypothesesFeasible

Design considerationsDesign considerations

Type of design Questions that can be answeredQuestions that cannot be answeredMulti-method multi-trait approachStrengths and Limitations

Types of Design:Types of Design:

Pre-postControl/Comparison Group Randomized, stratified random, convenience

Longitudinal Prospective cohort design

Epidemiological Large scale cohort or case-control

Sample ConsiderationsSample Considerations

Who is the target of the intervention? Patients

All patients At-risk

Attempters, ideators

How is the sample selected?How is the sample selected?

Identification of Sample: Convenience vs. Random

Criteria for inclusion and exclusion: Recruitment and Screening

Demographic considerations: Age, sex, educational level

Determination of Control or Comparison Group

How will the nature of the sample How will the nature of the sample affect measurement and affect measurement and procedures?procedures?

Attainment of necessary sample size Developmental level and language level Potential burden/ load for participant Representativeness and generalizability Feasibility Time, place, implementation, ability of

participants, attrition

What needs to be measured?What needs to be measured?

OutcomeConfoundersMediators and ModeratorsContext

Administration ConsiderationsAdministration Considerations

Format Face-to-face interview, self-report, telephone,

computerSource of information Self, other informant, records, epidemiological

informationInstrument for repeated measures Same form, alternate forms

Outcome Measures Must:Outcome Measures Must:

Measure the target of interventionBe standardizedBe expected to change within the time frameBe Sensitive to changeBe present in all groupsHave a measurable effect sizeHave demonstrated reliability and validityBe feasible

Current Measures of OutcomeCurrent Measures of Outcome

Suicidal IdeationSuicide AttemptsCompleted SuicideLethality of attempt

# crisis callsAssociated symptomsAdjunctive medicationsHospitalization# referralsSocial Skills

Procedural ConsiderationsProcedural Considerations

Intervention Definition and manualization

# sessions, length, medication dose Expected outcomes relevant & measurable Training & ongoing supervision Maintenance of blind assessors Implementation of intervention and fidelity Adherence and attrition

Interval of Measurement One-shot, short-term, long-term

Recruitment Methods Systematic, documented Keeping people in the program

Investigator’s Role Avoid potential biases Appropriate level of supervision

Ethical Considerations Confidentiality, identification of risk, intervention

Feasibility

Data AnalysisData Analysis

Goals Efficacy/ Impact of Intervention Program Evaluation

Considerations before conducting Considerations before conducting the study that impact data analysis:the study that impact data analysis:

Specific, testable hypotheses with data analytic strategy establishedPower AnalysisPotential confounders, mediators & moderatorsType and nature of dataNumber of analysesEffect sizes and variability of measuresData reductionManaging and imputing missing data

Types of AnalysesTypes of Analyses

Univariate T-tests, chi-square, ANOVA, Correlation,

nonparametric

Multivariate Repeated Measures Path Analysis Multiple Regression techniques Survival Analysis Time series or trend analysis

Points to consider when Points to consider when analyzing:analyzing:

Know your data before any analysesReliability is the upper limit of validityNo variability means no findingNot everything is linearBuild models based on univariate statistics- test with multivariateThe analysis must fit the type of dataWith numerical data, continuous variables are more informative than categorical variables

Evaluating an interventionEvaluating an intervention

FeasibilityFidelity to interventionReliability and validity of all measuresAttritionAdherenceConsumer satisfactionNegative Outcomes/ Adverse Events

Feasibility of the interventionFeasibility of the intervention

TimeResources: staff, space, money, suppliesAvailability of participantsSetting interest and amenabilityImplementation of interventionAssessment methods

Fidelity to InterventionFidelity to Intervention

Evaluation of trainingOngoing training and reliabilityOngoing monitoring of interventionStaff efficacy and satisfaction

AttritionAttrition

Assess from recruitment to end of studyCompare rate of attrition to typical ratesCompare drop-outs to study completers on baseline, demographic and relevant variables

Reliability and Validity of Reliability and Validity of MeasuresMeasures

Assess all measures with all appropriate forms of reliabilityTest discriminant and convergent validity

AdherenceAdherence

Embed measures of adherence in intervention and assessments Attendance Questions about previous sessions Test for medication or substances Follow-up behavioral questions

Consumer SatisfactionConsumer Satisfaction

ParticipantsStaffOutside Informants family members, service providers

Monitor Negative/ Adverse Monitor Negative/ Adverse EventsEvents

Document adverse events in a standard mannerAnticipate potential adverse events and prepare assessment and monitoring toolsPlan for suicidal risk

Special considerations for Special considerations for suicide researchsuicide research

Need enough suicidal behavior to notice a difference When is an intervention effective

Reduction vs. Elimination

Monitoring for safety in an potentially unsafe sampleDecision about when a participant is exited from the studyIntervention regarding suicidal behavior is an intervention that effects outcome behavior

ConclusionConclusion

Many decisions to be made when designing a studyEach decision affects the conduct of the studyMethod determines the conclusions that can be drawn from any one studyValidity is accrued across studies