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Studying treatment of suicidal ideation & attempts: Designs, Statistical Analysis, and Methodological Considerations Jill M. Harkavy-Friedman, Ph.D.

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Presentation on theme: "Studying treatment of suicidal ideation & attempts: Designs, Statistical Analysis, and Methodological Considerations Jill M. Harkavy-Friedman, Ph.D."— Presentation transcript:

1 Studying treatment of suicidal ideation & attempts: Designs, Statistical Analysis, and Methodological Considerations Jill M. Harkavy-Friedman, Ph.D.

2 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

3 Review of design considerations: Goals Design Sample Measures Procedures Data Analysis Treatment Evaluation

4 Goals Theory/ Rationale Meaningful Testable hypotheses Feasible

5 Design considerations Type of design Questions that can be answered Questions that cannot be answered Multi-method multi-trait approach Strengths and Limitations

6 Types of Design: Pre-post Control/Comparison Group  Randomized, stratified random, convenience Longitudinal  Prospective cohort design Epidemiological  Large scale cohort or case-control

7 Sample Considerations Who is the target of the intervention?  Patients All patients At-risk  Attempters, ideators

8 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

9 How will the nature of the sample affect measurement and 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

10 What needs to be measured? Outcome Confounders Mediators and Moderators Context

11 Administration Considerations Format  Face-to-face interview, self-report, telephone, computer Source of information  Self, other informant, records, epidemiological information Instrument for repeated measures  Same form, alternate forms

12 Outcome Measures Must: Measure the target of intervention Be standardized Be expected to change within the time frame Be Sensitive to change Be present in all groups Have a measurable effect size Have demonstrated reliability and validity Be feasible

13 Current Measures of Outcome Suicidal Ideation Suicide Attempts Completed Suicide Lethality of attempt # crisis calls Associated symptoms Adjunctive medications Hospitalization # referrals Social Skills

14 Procedural 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

15 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

16 Data Analysis Goals  Efficacy/ Impact of Intervention  Program Evaluation

17 Considerations before conducting the study that impact data analysis: Specific, testable hypotheses with data analytic strategy established Power Analysis Potential confounders, mediators & moderators Type and nature of data Number of analyses Effect sizes and variability of measures Data reduction Managing and imputing missing data

18 Types 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

19 Points to consider when analyzing: Know your data before any analyses Reliability is the upper limit of validity No variability means no finding Not everything is linear Build models based on univariate statistics- test with multivariate The analysis must fit the type of data With numerical data, continuous variables are more informative than categorical variables

20 Evaluating an intervention Feasibility Fidelity to intervention Reliability and validity of all measures Attrition Adherence Consumer satisfaction Negative Outcomes/ Adverse Events

21 Feasibility of the intervention Time Resources: staff, space, money, supplies Availability of participants Setting interest and amenability Implementation of intervention Assessment methods

22 Fidelity to Intervention Evaluation of training Ongoing training and reliability Ongoing monitoring of intervention Staff efficacy and satisfaction

23 Attrition Assess from recruitment to end of study Compare rate of attrition to typical rates Compare drop-outs to study completers on baseline, demographic and relevant variables

24 Reliability and Validity of Measures Assess all measures with all appropriate forms of reliability Test discriminant and convergent validity

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

26 Consumer Satisfaction Participants Staff Outside Informants  family members, service providers

27 Monitor Negative/ Adverse Events Document adverse events in a standard manner Anticipate potential adverse events and prepare assessment and monitoring tools Plan for suicidal risk

28 Special considerations for suicide research Need enough suicidal behavior to notice a difference  When is an intervention effective Reduction vs. Elimination Monitoring for safety in an potentially unsafe sample Decision about when a participant is exited from the study Intervention regarding suicidal behavior is an intervention that effects outcome behavior

29 Conclusion Many decisions to be made when designing a study Each decision affects the conduct of the study Method determines the conclusions that can be drawn from any one study Validity is accrued across studies

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