<clinical_study>
  <!-- This xml conforms to an XML Schema at:
    https://clinicaltrials.gov/ct2/html/images/info/public.xsd -->
  <required_header>
    <download_date>ClinicalTrials.gov processed this data on September 20, 2023</download_date>
    <link_text>Link to the current ClinicalTrials.gov record.</link_text>
    <url>https://clinicaltrials.gov/ct2/show/NCT02990000</url>
  </required_header>
  <id_info>
    <org_study_id>IHS-1503-28573</org_study_id>
    <nct_id>NCT02990000</nct_id>
  </id_info>
  <brief_title>Enhancing Mental Health Care by Scientifically Matching Patients to Providers' Strengths</brief_title>
  <official_title>Enhancing Mental Health Care by Scientifically Matching Patients to Providers' Strengths</official_title>
  <sponsors>
    <lead_sponsor>
      <agency>University of Massachusetts, Amherst</agency>
      <agency_class>Other</agency_class>
    </lead_sponsor>
    <collaborator>
      <agency>Patient-Centered Outcomes Research Institute</agency>
      <agency_class>Other</agency_class>
    </collaborator>
    <collaborator>
      <agency>University at Albany</agency>
      <agency_class>Other</agency_class>
    </collaborator>
    <collaborator>
      <agency>Psychological and Behavioral Consultants</agency>
      <agency_class>Other</agency_class>
    </collaborator>
    <collaborator>
      <agency>Outcome Referrals</agency>
      <agency_class>Other</agency_class>
    </collaborator>
  </sponsors>
  <source>University of Massachusetts, Amherst</source>
  <oversight_info>
    <has_dmc>Yes</has_dmc>
    <is_fda_regulated_drug>No</is_fda_regulated_drug>
    <is_fda_regulated_device>No</is_fda_regulated_device>
  </oversight_info>
  <brief_summary>
    <textblock>
      Research has shown that mental health care (MHC) providers differ significantly in their&#xD;
      ability to help patients. In addition, providers demonstrate different patterns of&#xD;
      effectiveness across symptom and functioning domains. For example, some providers are&#xD;
      reliably effective in treating numerous patients and problem domains, others are reliably&#xD;
      effective in some domains (e.g., depression, substance abuse) yet appear to struggle in&#xD;
      others (e.g., anxiety, social functioning), and some are reliably ineffective, or even&#xD;
      harmful, across patients and domains. Knowledge of these provider differences is based&#xD;
      largely on patient-reported outcomes collected in routine MHC settings.&#xD;
&#xD;
      Unfortunately, provider performance information is not systematically used to refer or assign&#xD;
      a particular patient to a scientifically based best-matched provider. MHC systems continue to&#xD;
      rely on random or purely pragmatic case assignment and referral, which significantly &quot;waters&#xD;
      down&quot; the odds of a patient being assigned/referred to a high performing provider in the&#xD;
      patient's area(s) of need, and increases the risk of being assigned/referred to a provider&#xD;
      who may have a track record of ineffectiveness. This research aims to solve the existing&#xD;
      non-patient-centered provider-matching problem.&#xD;
&#xD;
      Specifically, the investigators aim to demonstrate the comparative effectiveness of a&#xD;
      scientifically-based patient-provider match system compared to status quo pragmatic case&#xD;
      assignment. The investigators expect in the scientific match group significantly better&#xD;
      treatment outcomes (e.g., symptoms, quality of life) and higher patient satisfaction with&#xD;
      treatment. The investigators also expect to demonstrate feasibility of implementing a&#xD;
      scientific match process in a community MHC system and broad dissemination of the easily&#xD;
      replicated scientific match technology in diverse health care settings. The importance of&#xD;
      this work for patients cannot be understated. Far too many patients struggle to find the&#xD;
      right provider, which unnecessarily prolongs suffering and promotes health care system&#xD;
      inefficiency. A scientific match system based on routine outcome data uses patient-generated&#xD;
      information to direct this patient to this provider in this setting. In addition, when based&#xD;
      on multidimensional assessment, it allows a wide variety of patient-centered outcomes to be&#xD;
      represented (e.g., symptom domains, functioning domains, quality of life).&#xD;
    </textblock>
  </brief_summary>
  <detailed_description>
    <textblock>
      Background and Significance:&#xD;
&#xD;
      Mental illness is an extraordinary and highly burdensome public health problem.&#xD;
      Unfortunately, even for individuals who access mental health care (MHC), the care is too&#xD;
      often substandard. Research has consistently demonstrated that approximately 10-15% of&#xD;
      patients will deteriorate or experience harm during treatment. Further, when these rates are&#xD;
      combined with no-change rates, only 40% or less of patients meaningfully recover.&#xD;
      Importantly, treatment research has illuminated substantial variability in providers'&#xD;
      outcomes. Simply put, the MHC provider impacts treatment outcomes, and stakeholders lack&#xD;
      systematic access to valid and actionable information to optimize effective patient-provider&#xD;
      matches. Without collecting and disseminating performance data, stakeholders lack vital&#xD;
      information on which to base health care choices and personalize treatment. Conversely, there&#xD;
      potentially is immense advantage to matching patients to providers based on scientific&#xD;
      outcome data. Patients, stakeholders, researchers, and clinicians have all endorsed such&#xD;
      applied knowledge transfer as a high priority. In response, the investigators have developed&#xD;
      and piloted a technology to test this match concept and patient-centered health model.&#xD;
&#xD;
      Prominent health care agencies have placed outcome/performance measurement at the center of&#xD;
      core initiatives. The Institute of Medicine specifically recommends integrating provider&#xD;
      performance data in treatment decision-making. Despite this rhetoric, 2 Cochrane Reviews&#xD;
      combined could only identify 4 studies that addressed this question with minimal methodology&#xD;
      standards; the results were mixed. Importantly, none involved a targeted dissemination&#xD;
      intervention, and none involved MHC. Previous research, including our own, has empirically&#xD;
      demonstrated substantial differences in projected treatment effect sizes depending on to&#xD;
      which therapist a patient is referred. The key evidence gap is the need for a rigorous test&#xD;
      of the effectiveness of a targeted MHC provider-performance dissemination intervention&#xD;
      compared to standard/pragmatic referral and case assignment. Relatedly, the Patient-Centered&#xD;
      Outcomes Research Institute (PCORI) has called for increased &quot;precision&quot; or &quot;personalized&quot;&#xD;
      treatment, with a focus on tailoring. The match algorithm responds directly to this high&#xD;
      priority call to customize care in a personal and evidence-based way.&#xD;
&#xD;
      Specific Aims:&#xD;
&#xD;
      The aim of this comparative effectiveness research (CER) is to test an innovative,&#xD;
      scientifically informed patient-therapist referral match algorithm based on MHC provider&#xD;
      outcome data. The investigators will employ a randomized controlled trial (RCT) to compare&#xD;
      the match algorithm with the commonplace pragmatic referral matching (based on provider&#xD;
      availability, convenience, or self-reported specialty). Psychosocial treatment itself will&#xD;
      remain naturalistically administered by varied providers (e.g., psychologists, social&#xD;
      workers) to patients with complex mental health concerns within a partner clinic network,&#xD;
      Psychological and Behavioral Consultants (PsychBC). The investigators hypothesize that the&#xD;
      scientific match group will outperform the pragmatic match group in decreasing patient&#xD;
      symptoms and treatment dropout, and in promoting patient functional outcomes, outcome&#xD;
      expectations, and care satisfaction, as well as patient-therapist alliance quality. Doing so&#xD;
      will establish the match algorithm as a mechanism of effective patient-centered MHC.&#xD;
&#xD;
      Methods:&#xD;
&#xD;
      The investigators will compare the effectiveness of naturalistic MHC either with or without&#xD;
      the scientific matching aid with a double blind, individual level RCT. The investigators will&#xD;
      first conduct a baseline assessment of PsychBC therapists' (target enrollment N=44)&#xD;
      performance (across at least 15 cases) to determine their strengths in treating 12 behavioral&#xD;
      health domains measured by the primary outcome tool on which our match algorithm is based --&#xD;
      the Treatment Outcome Package (TOP). The TOP is already administered routinely in our partner&#xD;
      network. Based on years of predictive analytic research, this tool classifies therapists as&#xD;
      &quot;effective,&quot; &quot;neutral,&quot; or &quot;ineffective/harmful&quot; for each TOP domain. The blinded therapists&#xD;
      will be crossed over conditions.&#xD;
&#xD;
      Next, for the trial, new adult outpatients (target enrollment N=281) will be randomly&#xD;
      assigned to the Match condition or case assignment as usual (typically based on pragmatic&#xD;
      considerations, such as provider availability, convenience, or self-reported specialty). The&#xD;
      only patient exclusion criterion will be people who are not the primary decision-maker for&#xD;
      their care. Thus, patients will present with a multitude of problems across a spectrum of&#xD;
      diagnoses. With therapist assignment as the only manipulation, participating therapists will&#xD;
      treat patients fully naturalistically. Treatment outcomes will be assessed regularly through&#xD;
      mutual termination or up to 16 weeks. Primary analyses will involve hierarchical linear&#xD;
      modeling to examine comparative rates and patterns of change on the outcomes.&#xD;
    </textblock>
  </detailed_description>
  <overall_status>Completed</overall_status>
  <start_date type="Actual">November 6, 2017</start_date>
  <completion_date type="Actual">March 15, 2020</completion_date>
  <primary_completion_date type="Actual">September 23, 2019</primary_completion_date>
  <phase>N/A</phase>
  <study_type>Interventional</study_type>
  <has_expanded_access>No</has_expanded_access>
  <study_design_info>
    <allocation>Randomized</allocation>
    <intervention_model>Parallel Assignment</intervention_model>
    <primary_purpose>Health Services Research</primary_purpose>
    <masking>Double (Participant, Care Provider)</masking>
  </study_design_info>
  <primary_outcome>
    <measure>Average Z-Scores for the Treatment Outcome Package-Clinical Scales (TOP-CS; Kraus, Seligman, &amp; Jordan, 2005)</measure>
    <time_frame>Baseline and biweekly across 16 weeks</time_frame>
    <description>The TOP-Clinical Scales consist of 58 items assessing 12 symptom and functional domains (risk-adjusted for case mix variables assessed via 37 items on the companion TOP-Case Mix form, such as divorce, job loss, comorbidity): work functioning, sexual functioning, social conflict, depression, panic/somatic anxiety, psychosis, suicidal ideation, violence, mania, sleep, substance abuse, and quality of life. Global symptom severity was assessed by averaging the z-scores (i.e., standard deviation units relative to the general population mean) across the 12 clinical scales. Higher scores indicate greater impairment. Given that we examined change over the entire treatment period for this outcome (in a longitudinal hierarchical linear model), we provide the average mean and standard deviation for the TOP-CS z-scores across all measurement occasions.</description>
  </primary_outcome>
  <secondary_outcome>
    <measure>Symptom Checklist-10 (SCL-10; Rosen, Drescher, Moos, &amp; Gusman, 1999) Total Score</measure>
    <time_frame>Baseline and biweekly across 16 weeks</time_frame>
    <description>Global psychological distress was assessed with the Symptom Checklist-10 (SCL-10; Rosen, Drescher, Moos, &amp; Gusman, 1999), a 10-item, well validated and widely used self-report inventory that assesses psychological well-being. Total scores can range from 0 to 40, with higher scores indicating greater distress. Given that we examined change over the entire treatment period for this outcome (in a longitudinal hierarchical linear model), we provide the average mean and standard deviation for the SCL-10 total score across all measurement occasions.</description>
  </secondary_outcome>
  <secondary_outcome>
    <measure>Working Alliance Inventory-Short Form, Patient Version (WAI-SF-P; Tracey, &amp; Kokotovic, 1989) Total Score</measure>
    <time_frame>Biweekly across 16 weeks</time_frame>
    <description>The WAI is the most widely used alliance measure, assessing patient-therapist agreement on the goals and tasks of treatment, and the quality of their relational bond. This 12-item short form assesses these dimensions from the patient's perspective, with higher scores indicating a more positive relationship (theoretical range = 12 to 84). Given that we examined change over the entire treatment period for this outcome (in a longitudinal hierarchical linear model), we provide the average mean and standard deviation for the WAI total score across all measurement occasions.</description>
  </secondary_outcome>
  <secondary_outcome>
    <measure>Outcome Expectation (OE) Subscale of the Credibility/Expectancy Scale (CEQ; Devilly, &amp; Borkovec, 2000)</measure>
    <time_frame>Biweekly across 16 weeks</time_frame>
    <description>The OE subscale of the CEQ is the most widely used and psychometrically sound measure of patients' expectations for the personal efficacy of treatment. The three OE items range from 1-9 or 0-100% (in 10 percentage point increments), with higher ratings indicating greater expectation for improvement. Given that the OE CEQ items are assessed on different scales, we re-scaled the items to the same metric before creating a total score (theoretical range = 3 to 27). Given that we examined change over the entire treatment period for this outcome (in a longitudinal hierarchical linear model), we provide the average mean and standard deviation for the OE subscale across all measurement occasions.</description>
  </secondary_outcome>
  <secondary_outcome>
    <measure>Domain-Specific Impairment on the Most Elevated Domain of the Treatment Outcome Package-Clinical Scales (TOP-CS)</measure>
    <time_frame>Baseline and biweekly across 16 weeks</time_frame>
    <description>The TOP-CS consists of 58 items assessing 12 symptom and functional domains (risk-adjusted for case mix variables assessed via 37 items on the companion TOP-Case Mix form, such as divorce, job loss, comorbidity): work functioning, sexual functioning, social conflict, depression, panic/somatic anxiety, psychosis, suicidal ideation, violence, mania, sleep, substance abuse, and quality of life. Domain-specific impairment reflects each patient's scores on their most elevated problem domain (i.e., the domain most elevated at baseline). These scores were standardized z-scores (i.e., standard deviation units relative to the general population mean), with higher scores indicating greater impairment. Given that we examined change over the treatment period for this outcome (hierarchical linear model), we provide the average mean and standard deviation for the most elevated TOP domain across all measurement occasions. Note that this measure was positively skewed so we log-transformed it.</description>
  </secondary_outcome>
  <secondary_outcome>
    <measure>Early Treatment Discontinuation (i.e., Attending 2 or Fewer Treatment Sessions)</measure>
    <time_frame>Early treatment discontinuation/continuation at session 2</time_frame>
    <description>Early treatment discontinuation was operationalized as a patient discontinuing treatment after 2 or fewer sessions, whereas early continuation was operationalized as attending 3 or more treatment sessions. For analyses, early treatment discontinuation was coded 1 and early continuation was coded 0.</description>
  </secondary_outcome>
  <secondary_outcome>
    <measure>Overall Provider Quality Subscale of the Treatment Outcome Package (TOP) Satisfaction Scale</measure>
    <time_frame>Assessed after 16 weeks of treatment or at the point of naturalistic treatment termination, whichever comes sooner</time_frame>
    <description>The Overall Provider Quality subscale of the TOP Satisfaction Scale assesses the extent to which patients are satisfied with their mental health care provider. This subscale reflects the average of 4 items, with higher scores indicating greater satisfaction (theoretical range = 1 to 6).</description>
  </secondary_outcome>
  <number_of_arms>2</number_of_arms>
  <enrollment type="Actual">288</enrollment>
  <condition>Mental Illness</condition>
  <arm_group>
    <arm_group_label>Pragmatic Match</arm_group_label>
    <arm_group_type>No Intervention</arm_group_type>
    <description>Randomly assigned, by a case-assigning administrator, to naturalistic treatment with a pragmatically matched provider (control group)</description>
  </arm_group>
  <arm_group>
    <arm_group_label>Scientific Match</arm_group_label>
    <arm_group_type>Experimental</arm_group_type>
    <description>Randomly assigned, by a case-assigning administrator, to naturalistic treatment with a scientifically matched provider (experimental group)</description>
  </arm_group>
  <intervention>
    <intervention_type>Behavioral</intervention_type>
    <intervention_name>Scientific Match</intervention_name>
    <description>We have developed an innovative, personalized Match System based on provider track records determined with a multidimensional outcomes tool - the Treatment Outcome Package (TOP). Specifically, patients are assigned to therapists with previously established strengths (i.e., being historically effective) in treating their primary problems (e.g., depression, anxiety).</description>
    <arm_group_label>Scientific Match</arm_group_label>
    <other_name>Match System</other_name>
  </intervention>
  <eligibility>
    <criteria>
      <textblock>
        Inclusion:&#xD;
&#xD;
          -  Being 18-70 years of age&#xD;
&#xD;
          -  Being the primary, informed decision-maker for one's care&#xD;
&#xD;
          -  Willingness to be randomized to condition and to complete a few study-specific&#xD;
             measures&#xD;
&#xD;
        Exclusion:&#xD;
&#xD;
          -  Being under 18 or over 70 years of age&#xD;
&#xD;
          -  Not being responsible for one's own treatment decisions&#xD;
&#xD;
          -  Unwillingness to be randomized to condition and/or to complete a few study-specific&#xD;
             measures&#xD;
      </textblock>
    </criteria>
    <gender>All</gender>
    <minimum_age>18 Years</minimum_age>
    <maximum_age>70 Years</maximum_age>
    <healthy_volunteers>No</healthy_volunteers>
  </eligibility>
  <overall_official>
    <last_name>Michael J Constantino, PhD</last_name>
    <role>Principal Investigator</role>
    <affiliation>University of Massachusetts, Amherst</affiliation>
  </overall_official>
  <overall_official>
    <last_name>James F Boswell, PhD</last_name>
    <role>Principal Investigator</role>
    <affiliation>University at Albany, SUNY</affiliation>
  </overall_official>
  <overall_official>
    <last_name>David R Kraus, PhD</last_name>
    <role>Principal Investigator</role>
    <affiliation>Outcome Referrals</affiliation>
  </overall_official>
  <overall_official>
    <last_name>Thomas P Swales, PhD</last_name>
    <role>Principal Investigator</role>
    <affiliation>Psychological and Behavioral Consultants</affiliation>
  </overall_official>
  <location>
    <facility>
      <name>University of Massachusetts Amherst</name>
      <address>
        <city>Amherst</city>
        <state>Massachusetts</state>
        <zip>01003</zip>
        <country>United States</country>
      </address>
    </facility>
  </location>
  <location_countries>
    <country>United States</country>
  </location_countries>
  <link>
    <url>http://improvementalhealthcare.org</url>
    <description>Study-specific website</description>
  </link>
  <verification_date>May 2020</verification_date>
  <study_first_submitted>November 29, 2016</study_first_submitted>
  <study_first_submitted_qc>December 7, 2016</study_first_submitted_qc>
  <study_first_posted type="Estimate">December 12, 2016</study_first_posted>
  <results_first_submitted>May 15, 2020</results_first_submitted>
  <results_first_submitted_qc>June 26, 2020</results_first_submitted_qc>
  <results_first_posted type="Actual">July 14, 2020</results_first_posted>
  <last_update_submitted>July 14, 2020</last_update_submitted>
  <last_update_submitted_qc>July 14, 2020</last_update_submitted_qc>
  <last_update_posted type="Actual">July 30, 2020</last_update_posted>
  <responsible_party>
    <responsible_party_type>Sponsor</responsible_party_type>
  </responsible_party>
  <condition_browse>
    <!-- CAUTION:  The following MeSH terms are assigned with an imperfect algorithm            -->
    <mesh_term>Mental Disorders</mesh_term>
  </condition_browse>
  <patient_data>
    <sharing_ipd>Yes</sharing_ipd>
    <ipd_description>Upon request on a case-by-case basis, we will share all IPD that underlie results in a publication (e.g., data extraction for meta-analyses). As appropriate, based on specific scientific journals' standards, we will provide analytic code used to generate published results.</ipd_description>
    <ipd_info_type>Study Protocol</ipd_info_type>
    <ipd_info_type>Statistical Analysis Plan (SAP)</ipd_info_type>
    <ipd_info_type>Informed Consent Form (ICF)</ipd_info_type>
    <ipd_info_type>Analytic Code</ipd_info_type>
    <ipd_time_frame>We will begin sharing IPD upon request 6 months following the publication of our peer-reviewed final research report for PCORI, and we will maintain our de-identified data set indefinitely given possible future requests (e.g., to extract data for meta-analyses).</ipd_time_frame>
    <ipd_access_criteria>We will share fully de-identified IPD, a corresponding data dictionary, and the above supporting information to professional scientific colleagues (with established reputations for publishing original psychotherapy research in accordance with ethical guidelines) for the purposes of replication efforts or meta-analyses. For other usages, such as requests to conduct novel secondary analyses, we will consider such collaborations on a case-by-case basis and clearly determine authorship arrangements in writing.&#xD;
Review requests, including a detailed plan for how the data will be used, should be directed via email to the PI, Dr. Michael Constantino (mconstantino@psych.umass.edu). Dr. Constantino reserves the right to deny individual share requests if the usage details are questionable or unclear.</ipd_access_criteria>
  </patient_data>
  <provided_document_section>
    <provided_document>
      <document_type>Study Protocol, Statistical Analysis Plan, and Informed Consent Form</document_type>
      <document_has_protocol>Yes</document_has_protocol>
      <document_has_icf>Yes</document_has_icf>
      <document_has_sap>Yes</document_has_sap>
      <document_date>October 10, 2019</document_date>
      <document_url>https://ClinicalTrials.gov/ProvidedDocs/00/NCT02990000/Prot_SAP_ICF_000.pdf</document_url>
    </provided_document>
  </provided_document_section>

  <clinical_results>

    <participant_flow>
      <group_list>
        <group group_id="P1">
          <title>Pragmatic Match</title>
          <description>Randomly assigned, by a case-assigning administrator, to naturalistic treatment with a pragmatically matched provider (control group)</description>
        </group>
        <group group_id="P2">
          <title>Scientific Match</title>
          <description>Randomly assigned, by a case-assigning administrator, to naturalistic treatment with a scientifically matched provider (experimental group)&#xD;
Scientific Match: We have developed an innovative, personalized Match System based on provider track records determined with a multidimensional outcomes tool - the Treatment Outcome Package (TOP). Specifically, patients are assigned to therapists with previously established strengths (i.e., being historically effective) in treating their primary problems (e.g., depression, anxiety).</description>
        </group>
      </group_list>
      <period_list>
        <period>
          <title>Overall Study</title>
          <milestone_list>
            <milestone>
              <title>STARTED</title>
              <participants_list>
                <participants group_id="P1" count="155">155 patients were randomly assigned to the Pragmatic Match condition</participants>
                <participants group_id="P2" count="133">133 patients were randomly assigned to the Scientific Match condition</participants>
              </participants_list>
            </milestone>
            <milestone>
              <title>Begin Treatment</title>
              <participants_list>
                <participants group_id="P1" count="119">119 Pragmatic Match patients actually began treatment (attended at least 1 session)</participants>
                <participants group_id="P2" count="99">99 Scientifically Matched patients actually began treatment (attended at least one session)</participants>
              </participants_list>
            </milestone>
            <milestone>
              <title>COMPLETED</title>
              <participants_list>
                <participants group_id="P1" count="119">119 patients provided naturalistic treatment data and were included in analyses</participants>
                <participants group_id="P2" count="99">99 patients provided naturalistic treatment data and were included in analyses</participants>
              </participants_list>
            </milestone>
            <milestone>
              <title>NOT COMPLETED</title>
              <participants_list>
                <participants group_id="P1" count="36"/>
                <participants group_id="P2" count="34"/>
              </participants_list>
            </milestone>
          </milestone_list>
          <drop_withdraw_reason_list>
            <drop_withdraw_reason>
              <title>Failed to provide data beyond baseline</title>
              <participants_list>
                <participants group_id="P1" count="36"/>
                <participants group_id="P2" count="34"/>
              </participants_list>
            </drop_withdraw_reason>
          </drop_withdraw_reason_list>
        </period>
      </period_list>
    </participant_flow>

    <baseline>
      <population>Baseline analysis population N = 218, or the final analysis sample of patients who attended at least one treatment session</population>
      <group_list>
        <group group_id="B1">
          <title>Pragmatic Match</title>
          <description>Randomly assigned, by a case-assigning administrator, to naturalistic treatment with a pragmatically matched provider (control group)</description>
        </group>
        <group group_id="B2">
          <title>Scientific Match</title>
          <description>Randomly assigned, by a case-assigning administrator, to naturalistic treatment with a scientifically matched provider (experimental group)&#xD;
Scientific Match: We have developed an innovative, personalized Match System based on provider track records determined with a multidimensional outcomes tool - the Treatment Outcome Package (TOP). Specifically, patients are assigned to therapists with previously established strengths (i.e., being historically effective) in treating their primary problems (e.g., depression, anxiety).</description>
        </group>
        <group group_id="B3">
          <title>Total</title>
          <description>Total of all reporting groups</description>
        </group>
      </group_list>
      <analyzed_list>
        <analyzed>
          <units>Participants</units>
          <scope>Overall</scope>
          <count_list>
            <count group_id="B1" value="119"/>
            <count group_id="B2" value="99"/>
            <count group_id="B3" value="218"/>
          </count_list>
        </analyzed>
      </analyzed_list>
      <measure_list>
        <measure>
          <title>Age</title>
          <units>Participants</units>
          <param>Count of Participants</param>
          <class_list>
            <class>
              <category_list>
                <category>
                  <title>&lt;=18 years</title>
                  <measurement_list>
                    <measurement group_id="B1" value="0"/>
                    <measurement group_id="B2" value="0"/>
                    <measurement group_id="B3" value="0"/>
                  </measurement_list>
                </category>
                <category>
                  <title>Between 18 and 65 years</title>
                  <measurement_list>
                    <measurement group_id="B1" value="119"/>
                    <measurement group_id="B2" value="99"/>
                    <measurement group_id="B3" value="218"/>
                  </measurement_list>
                </category>
                <category>
                  <title>&gt;=65 years</title>
                  <measurement_list>
                    <measurement group_id="B1" value="0"/>
                    <measurement group_id="B2" value="0"/>
                    <measurement group_id="B3" value="0"/>
                  </measurement_list>
                </category>
              </category_list>
            </class>
          </class_list>
        </measure>
        <measure>
          <title>Age</title>
          <units>years</units>
          <param>Mean</param>
          <dispersion>Standard Deviation</dispersion>
          <class_list>
            <class>
              <category_list>
                <category>
                  <measurement_list>
                    <measurement group_id="B1" value="34.42" spread="11.55"/>
                    <measurement group_id="B2" value="33.33" spread="10.72"/>
                    <measurement group_id="B3" value="33.93" spread="11.17"/>
                  </measurement_list>
                </category>
              </category_list>
            </class>
          </class_list>
        </measure>
        <measure>
          <title>Sex: Female, Male</title>
          <units>Participants</units>
          <param>Count of Participants</param>
          <class_list>
            <class>
              <category_list>
                <category>
                  <title>Female</title>
                  <measurement_list>
                    <measurement group_id="B1" value="81"/>
                    <measurement group_id="B2" value="66"/>
                    <measurement group_id="B3" value="147"/>
                  </measurement_list>
                </category>
                <category>
                  <title>Male</title>
                  <measurement_list>
                    <measurement group_id="B1" value="38"/>
                    <measurement group_id="B2" value="33"/>
                    <measurement group_id="B3" value="71"/>
                  </measurement_list>
                </category>
              </category_list>
            </class>
          </class_list>
        </measure>
        <measure>
          <title>Ethnicity (NIH/OMB)</title>
          <units>Participants</units>
          <param>Count of Participants</param>
          <class_list>
            <class>
              <category_list>
                <category>
                  <title>Hispanic or Latino</title>
                  <measurement_list>
                    <measurement group_id="B1" value="3"/>
                    <measurement group_id="B2" value="3"/>
                    <measurement group_id="B3" value="6"/>
                  </measurement_list>
                </category>
                <category>
                  <title>Not Hispanic or Latino</title>
                  <measurement_list>
                    <measurement group_id="B1" value="116"/>
                    <measurement group_id="B2" value="96"/>
                    <measurement group_id="B3" value="212"/>
                  </measurement_list>
                </category>
                <category>
                  <title>Unknown or Not Reported</title>
                  <measurement_list>
                    <measurement group_id="B1" value="0"/>
                    <measurement group_id="B2" value="0"/>
                    <measurement group_id="B3" value="0"/>
                  </measurement_list>
                </category>
              </category_list>
            </class>
          </class_list>
        </measure>
        <measure>
          <title>Race/Ethnicity, Customized</title>
          <units>Participants</units>
          <param>Count of Participants</param>
          <class_list>
            <class>
              <title>White</title>
              <category_list>
                <category>
                  <measurement_list>
                    <measurement group_id="B1" value="106"/>
                    <measurement group_id="B2" value="87"/>
                    <measurement group_id="B3" value="193"/>
                  </measurement_list>
                </category>
              </category_list>
            </class>
            <class>
              <title>Hispanic or Latino</title>
              <category_list>
                <category>
                  <measurement_list>
                    <measurement group_id="B1" value="3"/>
                    <measurement group_id="B2" value="3"/>
                    <measurement group_id="B3" value="6"/>
                  </measurement_list>
                </category>
              </category_list>
            </class>
            <class>
              <title>African American/Black</title>
              <category_list>
                <category>
                  <measurement_list>
                    <measurement group_id="B1" value="6"/>
                    <measurement group_id="B2" value="7"/>
                    <measurement group_id="B3" value="13"/>
                  </measurement_list>
                </category>
              </category_list>
            </class>
            <class>
              <title>American Indian or Alaska Native</title>
              <category_list>
                <category>
                  <measurement_list>
                    <measurement group_id="B1" value="0"/>
                    <measurement group_id="B2" value="0"/>
                    <measurement group_id="B3" value="0"/>
                  </measurement_list>
                </category>
              </category_list>
            </class>
            <class>
              <title>East Indian</title>
              <category_list>
                <category>
                  <measurement_list>
                    <measurement group_id="B1" value="0"/>
                    <measurement group_id="B2" value="1"/>
                    <measurement group_id="B3" value="1"/>
                  </measurement_list>
                </category>
              </category_list>
            </class>
            <class>
              <title>Other</title>
              <category_list>
                <category>
                  <measurement_list>
                    <measurement group_id="B1" value="2"/>
                    <measurement group_id="B2" value="0"/>
                    <measurement group_id="B3" value="2"/>
                  </measurement_list>
                </category>
              </category_list>
            </class>
          </class_list>
        </measure>
        <measure>
          <title>Region of Enrollment</title>
          <units>participants</units>
          <param>Number</param>
          <class_list>
            <class>
              <title>United States</title>
              <category_list>
                <category>
                  <measurement_list>
                    <measurement group_id="B1" value="119"/>
                    <measurement group_id="B2" value="99"/>
                    <measurement group_id="B3" value="218"/>
                  </measurement_list>
                </category>
              </category_list>
            </class>
          </class_list>
        </measure>
        <measure>
          <title>Treatment Outcome Package-Clinical Scales (TOP-CS): General Impairment</title>
          <description>The TOP-CS consists of 58 items assessing 12 symptom/functional domains: depression, quality of life, mania, panic, psychosis, substance abuse, social conflict, sexual functioning, sleep, suicidality, violence, and work functioning. The items are used to create domain-specific z-scores that reflect SDs relative to the general population mean. To create an index of global impairment, the 12 domain-specific z-scores are averaged. Higher scores represent greater impairment (e.g., 0 represents the general population mean, +2 represents impairment that is 2 SDs above the population mean).</description>
          <units>units on a scale</units>
          <param>Mean</param>
          <dispersion>Standard Deviation</dispersion>
          <class_list>
            <class>
              <category_list>
                <category>
                  <measurement_list>
                    <measurement group_id="B1" value="0.86" spread="0.78"/>
                    <measurement group_id="B2" value="1.04" spread=".96"/>
                    <measurement group_id="B3" value="0.94" spread="0.87"/>
                  </measurement_list>
                </category>
              </category_list>
            </class>
          </class_list>
        </measure>
        <measure>
          <title>Symptom Checklist-10 (SCL-10): Global Psychological Distress</title>
          <description>The Symptom Checklist-10 (SCL-10) was used to assess global psychological distress. The 10 items are rated from 0-4 and summed to create a total score (theoretical range = 0-40), with higher scores indicating greater distress.</description>
          <units>units on a scale</units>
          <param>Mean</param>
          <dispersion>Standard Deviation</dispersion>
          <class_list>
            <class>
              <category_list>
                <category>
                  <measurement_list>
                    <measurement group_id="B1" value="15.48" spread="7.93"/>
                    <measurement group_id="B2" value="16.08" spread="7.74"/>
                    <measurement group_id="B3" value="15.75" spread="7.83"/>
                  </measurement_list>
                </category>
              </category_list>
            </class>
          </class_list>
        </measure>
      </measure_list>
    </baseline>

    <outcome_list>
      <outcome>
        <type>Primary</type>
        <title>Average Z-Scores for the Treatment Outcome Package-Clinical Scales (TOP-CS; Kraus, Seligman, &amp; Jordan, 2005)</title>
        <description>The TOP-Clinical Scales consist of 58 items assessing 12 symptom and functional domains (risk-adjusted for case mix variables assessed via 37 items on the companion TOP-Case Mix form, such as divorce, job loss, comorbidity): work functioning, sexual functioning, social conflict, depression, panic/somatic anxiety, psychosis, suicidal ideation, violence, mania, sleep, substance abuse, and quality of life. Global symptom severity was assessed by averaging the z-scores (i.e., standard deviation units relative to the general population mean) across the 12 clinical scales. Higher scores indicate greater impairment. Given that we examined change over the entire treatment period for this outcome (in a longitudinal hierarchical linear model), we provide the average mean and standard deviation for the TOP-CS z-scores across all measurement occasions.</description>
        <time_frame>Baseline and biweekly across 16 weeks</time_frame>
        <population>All participants who were randomized to condition and completed at least one assessment after baseline (N = 218)</population>
        <group_list>
          <group group_id="O1">
            <title>Pragmatic Match</title>
            <description>Randomly assigned, by a case-assigning administrator, to naturalistic treatment with a pragmatically matched provider (control group)</description>
          </group>
          <group group_id="O2">
            <title>Scientific Match</title>
            <description>Randomly assigned, by a case-assigning administrator, to naturalistic treatment with a scientifically matched provider (experimental group)&#xD;
Scientific Match: We have developed an innovative, personalized Match System based on provider track records determined with a multidimensional outcomes tool - the Treatment Outcome Package (TOP). Specifically, patients are assigned to therapists with previously established strengths (i.e., being historically effective) in treating their primary problems (e.g., depression, anxiety).</description>
          </group>
        </group_list>
        <measure>
          <title>Average Z-Scores for the Treatment Outcome Package-Clinical Scales (TOP-CS; Kraus, Seligman, &amp; Jordan, 2005)</title>
          <description>The TOP-Clinical Scales consist of 58 items assessing 12 symptom and functional domains (risk-adjusted for case mix variables assessed via 37 items on the companion TOP-Case Mix form, such as divorce, job loss, comorbidity): work functioning, sexual functioning, social conflict, depression, panic/somatic anxiety, psychosis, suicidal ideation, violence, mania, sleep, substance abuse, and quality of life. Global symptom severity was assessed by averaging the z-scores (i.e., standard deviation units relative to the general population mean) across the 12 clinical scales. Higher scores indicate greater impairment. Given that we examined change over the entire treatment period for this outcome (in a longitudinal hierarchical linear model), we provide the average mean and standard deviation for the TOP-CS z-scores across all measurement occasions.</description>
          <population>All participants who were randomized to condition and completed at least one assessment after baseline (N = 218)</population>
          <units>units on a scale</units>
          <param>Mean</param>
          <dispersion>Standard Deviation</dispersion>
          <analyzed_list>
            <analyzed>
              <units>Participants</units>
              <scope>Measure</scope>
              <count_list>
                <count group_id="O1" value="119"/>
                <count group_id="O2" value="99"/>
              </count_list>
            </analyzed>
          </analyzed_list>
          <class_list>
            <class>
              <category_list>
                <category>
                  <measurement_list>
                    <measurement group_id="O1" value="0.57" spread="0.80"/>
                    <measurement group_id="O2" value="0.56" spread="0.82"/>
                  </measurement_list>
                </category>
              </category_list>
            </class>
          </class_list>
        </measure>
        <analysis_list>
          <analysis>
            <group_id_list>
              <group_id>O1</group_id>
              <group_id>O2</group_id>
            </group_id_list>
            <groups_desc>To account for the nested nature of the data (time points nested within patients nested within therapists), a 3-level hierarchical linear model was used to test the effect of condition (Scientific Match = 1; Pragmatic Match = 0) on weekly during-treatment change on the TOP-CS average z-scores. Given that higher TOP-CS z-scores indicate greater impairment, negative slopes indicate a weekly decrease in impairment during treatment (i.e., a better outcome or more improvement).</groups_desc>
            <non_inferiority_type>Superiority</non_inferiority_type>
            <non_inferiority_desc>We used the Optimal Design program to determine the minimum numbers of therapists and patients needed to detect a moderate effect of condition (standardized difference between change rates = .50). Based on this a priori power analysis, we will need a total of 44 therapists and 211 patients to achieve a power of .80 to detect moderate condition effects. Factoring in a 25% dropout rate, enrolling 281 patients should provide sufficient statistical power.</non_inferiority_desc>
            <p_value>.02</p_value>
            <method>3-level hierarchical linear model</method>
            <param_type>condition effect on weekly change rate</param_type>
            <param_value>-0.04</param_value>
            <dispersion_type>Standard Error of the Mean</dispersion_type>
            <dispersion_value>0.01</dispersion_value>
            <ci_percent>95</ci_percent>
            <ci_n_sides>2-Sided</ci_n_sides>
            <ci_lower_limit>-0.05</ci_lower_limit>
            <ci_upper_limit>-0.03</ci_upper_limit>
          </analysis>
        </analysis_list>
      </outcome>
      <outcome>
        <type>Secondary</type>
        <title>Symptom Checklist-10 (SCL-10; Rosen, Drescher, Moos, &amp; Gusman, 1999) Total Score</title>
        <description>Global psychological distress was assessed with the Symptom Checklist-10 (SCL-10; Rosen, Drescher, Moos, &amp; Gusman, 1999), a 10-item, well validated and widely used self-report inventory that assesses psychological well-being. Total scores can range from 0 to 40, with higher scores indicating greater distress. Given that we examined change over the entire treatment period for this outcome (in a longitudinal hierarchical linear model), we provide the average mean and standard deviation for the SCL-10 total score across all measurement occasions.</description>
        <time_frame>Baseline and biweekly across 16 weeks</time_frame>
        <population>All participants who were randomized to condition and completed at least one assessment after baseline (N = 218)</population>
        <group_list>
          <group group_id="O1">
            <title>Pragmatic Match</title>
            <description>Randomly assigned, by a case-assigning administrator, to naturalistic treatment with a pragmatically matched provider (control group)</description>
          </group>
          <group group_id="O2">
            <title>Scientific Match</title>
            <description>Randomly assigned, by a case-assigning administrator, to naturalistic treatment with a scientifically matched provider (experimental group)&#xD;
Scientific Match: We have developed an innovative, personalized Match System based on provider track records determined with a multidimensional outcomes tool - the Treatment Outcome Package (TOP). Specifically, patients are assigned to therapists with previously established strengths (i.e., being historically effective) in treating their primary problems (e.g., depression, anxiety).</description>
          </group>
        </group_list>
        <measure>
          <title>Symptom Checklist-10 (SCL-10; Rosen, Drescher, Moos, &amp; Gusman, 1999) Total Score</title>
          <description>Global psychological distress was assessed with the Symptom Checklist-10 (SCL-10; Rosen, Drescher, Moos, &amp; Gusman, 1999), a 10-item, well validated and widely used self-report inventory that assesses psychological well-being. Total scores can range from 0 to 40, with higher scores indicating greater distress. Given that we examined change over the entire treatment period for this outcome (in a longitudinal hierarchical linear model), we provide the average mean and standard deviation for the SCL-10 total score across all measurement occasions.</description>
          <population>All participants who were randomized to condition and completed at least one assessment after baseline (N = 218)</population>
          <units>units on a scale</units>
          <param>Mean</param>
          <dispersion>Standard Deviation</dispersion>
          <analyzed_list>
            <analyzed>
              <units>Participants</units>
              <scope>Measure</scope>
              <count_list>
                <count group_id="O1" value="119"/>
                <count group_id="O2" value="99"/>
              </count_list>
            </analyzed>
          </analyzed_list>
          <class_list>
            <class>
              <category_list>
                <category>
                  <measurement_list>
                    <measurement group_id="O1" value="12.52" spread="8.01"/>
                    <measurement group_id="O2" value="12.06" spread="7.70"/>
                  </measurement_list>
                </category>
              </category_list>
            </class>
          </class_list>
        </measure>
        <analysis_list>
          <analysis>
            <group_id_list>
              <group_id>O1</group_id>
              <group_id>O2</group_id>
            </group_id_list>
            <groups_desc>To account for the nested nature of the data (time points nested within patients nested within therapists), a 3-level hierarchical linear model was used to test the effect of condition (Scientific Match = 1; Pragmatic Match = 0) on weekly during-treatment change on the SCL-10 total score. Given that higher SCL-10 scores indicate greater psychological distress, negative slopes indicate a weekly decrease in impairment during treatment (i.e., a better outcome or more improvement).</groups_desc>
            <non_inferiority_type>Superiority</non_inferiority_type>
            <p_value>.03</p_value>
            <method>3-level hierarchical linear model</method>
            <param_type>condition effect on weekly change rate</param_type>
            <param_value>-0.16</param_value>
            <dispersion_type>Standard Error of the Mean</dispersion_type>
            <dispersion_value>0.07</dispersion_value>
            <ci_percent>95</ci_percent>
            <ci_n_sides>2-Sided</ci_n_sides>
            <ci_lower_limit>-0.30</ci_lower_limit>
            <ci_upper_limit>-0.02</ci_upper_limit>
          </analysis>
        </analysis_list>
      </outcome>
      <outcome>
        <type>Secondary</type>
        <title>Working Alliance Inventory-Short Form, Patient Version (WAI-SF-P; Tracey, &amp; Kokotovic, 1989) Total Score</title>
        <description>The WAI is the most widely used alliance measure, assessing patient-therapist agreement on the goals and tasks of treatment, and the quality of their relational bond. This 12-item short form assesses these dimensions from the patient's perspective, with higher scores indicating a more positive relationship (theoretical range = 12 to 84). Given that we examined change over the entire treatment period for this outcome (in a longitudinal hierarchical linear model), we provide the average mean and standard deviation for the WAI total score across all measurement occasions.</description>
        <time_frame>Biweekly across 16 weeks</time_frame>
        <population>All participants who were randomized to condition and completed at least one assessment after baseline (N = 218)</population>
        <group_list>
          <group group_id="O1">
            <title>Pragmatic Match</title>
            <description>Randomly assigned, by a case-assigning administrator, to naturalistic treatment with a pragmatically matched provider (control group)</description>
          </group>
          <group group_id="O2">
            <title>Scientific Match</title>
            <description>Randomly assigned, by a case-assigning administrator, to naturalistic treatment with a scientifically matched provider (experimental group)&#xD;
Scientific Match: We have developed an innovative, personalized Match System based on provider track records determined with a multidimensional outcomes tool - the Treatment Outcome Package (TOP). Specifically, patients are assigned to therapists with previously established strengths (i.e., being historically effective) in treating their primary problems (e.g., depression, anxiety).</description>
          </group>
        </group_list>
        <measure>
          <title>Working Alliance Inventory-Short Form, Patient Version (WAI-SF-P; Tracey, &amp; Kokotovic, 1989) Total Score</title>
          <description>The WAI is the most widely used alliance measure, assessing patient-therapist agreement on the goals and tasks of treatment, and the quality of their relational bond. This 12-item short form assesses these dimensions from the patient's perspective, with higher scores indicating a more positive relationship (theoretical range = 12 to 84). Given that we examined change over the entire treatment period for this outcome (in a longitudinal hierarchical linear model), we provide the average mean and standard deviation for the WAI total score across all measurement occasions.</description>
          <population>All participants who were randomized to condition and completed at least one assessment after baseline (N = 218)</population>
          <units>units on a scale</units>
          <param>Mean</param>
          <dispersion>Standard Deviation</dispersion>
          <analyzed_list>
            <analyzed>
              <units>Participants</units>
              <scope>Measure</scope>
              <count_list>
                <count group_id="O1" value="119"/>
                <count group_id="O2" value="99"/>
              </count_list>
            </analyzed>
          </analyzed_list>
          <class_list>
            <class>
              <category_list>
                <category>
                  <measurement_list>
                    <measurement group_id="O1" value="66.75" spread="13.35"/>
                    <measurement group_id="O2" value="68.44" spread="12.00"/>
                  </measurement_list>
                </category>
              </category_list>
            </class>
          </class_list>
        </measure>
        <analysis_list>
          <analysis>
            <group_id_list>
              <group_id>O1</group_id>
              <group_id>O2</group_id>
            </group_id_list>
            <groups_desc>To account for the nested nature of the data (time points nested within patients nested within therapists), a 3-level hierarchical linear model was used to test the effect of condition (Scientific Match = 1; Pragmatic Match = 0) on weekly during-treatment change on the patient-rated WAI. Given that higher WAI scores indicate better quality therapeutic alliances, positive slopes indicate a weekly increase in alliance during treatment (i.e., a better outcome or more improvement).</groups_desc>
            <non_inferiority_type>Superiority</non_inferiority_type>
            <p_value>.65</p_value>
            <method>3-level hierarchical linear model</method>
            <param_type>condition effect on weekly change rate</param_type>
            <param_value>-0.07</param_value>
            <dispersion_type>Standard Error of the Mean</dispersion_type>
            <dispersion_value>0.15</dispersion_value>
            <ci_percent>95</ci_percent>
            <ci_n_sides>2-Sided</ci_n_sides>
            <ci_lower_limit>-0.33</ci_lower_limit>
            <ci_upper_limit>0.21</ci_upper_limit>
          </analysis>
        </analysis_list>
      </outcome>
      <outcome>
        <type>Secondary</type>
        <title>Outcome Expectation (OE) Subscale of the Credibility/Expectancy Scale (CEQ; Devilly, &amp; Borkovec, 2000)</title>
        <description>The OE subscale of the CEQ is the most widely used and psychometrically sound measure of patients' expectations for the personal efficacy of treatment. The three OE items range from 1-9 or 0-100% (in 10 percentage point increments), with higher ratings indicating greater expectation for improvement. Given that the OE CEQ items are assessed on different scales, we re-scaled the items to the same metric before creating a total score (theoretical range = 3 to 27). Given that we examined change over the entire treatment period for this outcome (in a longitudinal hierarchical linear model), we provide the average mean and standard deviation for the OE subscale across all measurement occasions.</description>
        <time_frame>Biweekly across 16 weeks</time_frame>
        <population>All participants who were randomized to condition and completed at least one assessment after baseline (N = 218)</population>
        <group_list>
          <group group_id="O1">
            <title>Pragmatic Match</title>
            <description>Randomly assigned, by a case-assigning administrator, to naturalistic treatment with a pragmatically matched provider (control group)</description>
          </group>
          <group group_id="O2">
            <title>Scientific Match</title>
            <description>Randomly assigned, by a case-assigning administrator, to naturalistic treatment with a scientifically matched provider (experimental group)&#xD;
Scientific Match: We have developed an innovative, personalized Match System based on provider track records determined with a multidimensional outcomes tool - the Treatment Outcome Package (TOP). Specifically, patients are assigned to therapists with previously established strengths (i.e., being historically effective) in treating their primary problems (e.g., depression, anxiety).</description>
          </group>
        </group_list>
        <measure>
          <title>Outcome Expectation (OE) Subscale of the Credibility/Expectancy Scale (CEQ; Devilly, &amp; Borkovec, 2000)</title>
          <description>The OE subscale of the CEQ is the most widely used and psychometrically sound measure of patients' expectations for the personal efficacy of treatment. The three OE items range from 1-9 or 0-100% (in 10 percentage point increments), with higher ratings indicating greater expectation for improvement. Given that the OE CEQ items are assessed on different scales, we re-scaled the items to the same metric before creating a total score (theoretical range = 3 to 27). Given that we examined change over the entire treatment period for this outcome (in a longitudinal hierarchical linear model), we provide the average mean and standard deviation for the OE subscale across all measurement occasions.</description>
          <population>All participants who were randomized to condition and completed at least one assessment after baseline (N = 218)</population>
          <units>units on a scale</units>
          <param>Mean</param>
          <dispersion>Standard Deviation</dispersion>
          <analyzed_list>
            <analyzed>
              <units>Participants</units>
              <scope>Measure</scope>
              <count_list>
                <count group_id="O1" value="119"/>
                <count group_id="O2" value="99"/>
              </count_list>
            </analyzed>
          </analyzed_list>
          <class_list>
            <class>
              <category_list>
                <category>
                  <measurement_list>
                    <measurement group_id="O1" value="18.12" spread="5.45"/>
                    <measurement group_id="O2" value="19.15" spread="5.30"/>
                  </measurement_list>
                </category>
              </category_list>
            </class>
          </class_list>
        </measure>
        <analysis_list>
          <analysis>
            <group_id_list>
              <group_id>O1</group_id>
              <group_id>O2</group_id>
            </group_id_list>
            <groups_desc>To account for the nested nature of the data (time points nested within patients nested within therapists), a 3-level hierarchical linear model was used to test the effect of condition (Scientific Match = 1; Pragmatic Match = 0) on weekly during-treatment change on the OE subscale of the CEQ. Given that higher OE scores indicate more optimistic expectations, positive slopes indicate a weekly increase in OE during treatment (i.e., a better outcome or more improvement).</groups_desc>
            <non_inferiority_type>Superiority</non_inferiority_type>
            <p_value>.41</p_value>
            <method>3-level hierarchical linear model</method>
            <param_type>condition effect on weekly change rate</param_type>
            <param_value>-0.06</param_value>
            <dispersion_type>Standard Error of the Mean</dispersion_type>
            <dispersion_value>0.07</dispersion_value>
            <ci_percent>95</ci_percent>
            <ci_n_sides>2-Sided</ci_n_sides>
            <ci_lower_limit>-0.17</ci_lower_limit>
            <ci_upper_limit>0.07</ci_upper_limit>
          </analysis>
        </analysis_list>
      </outcome>
      <outcome>
        <type>Secondary</type>
        <title>Domain-Specific Impairment on the Most Elevated Domain of the Treatment Outcome Package-Clinical Scales (TOP-CS)</title>
        <description>The TOP-CS consists of 58 items assessing 12 symptom and functional domains (risk-adjusted for case mix variables assessed via 37 items on the companion TOP-Case Mix form, such as divorce, job loss, comorbidity): work functioning, sexual functioning, social conflict, depression, panic/somatic anxiety, psychosis, suicidal ideation, violence, mania, sleep, substance abuse, and quality of life. Domain-specific impairment reflects each patient's scores on their most elevated problem domain (i.e., the domain most elevated at baseline). These scores were standardized z-scores (i.e., standard deviation units relative to the general population mean), with higher scores indicating greater impairment. Given that we examined change over the treatment period for this outcome (hierarchical linear model), we provide the average mean and standard deviation for the most elevated TOP domain across all measurement occasions. Note that this measure was positively skewed so we log-transformed it.</description>
        <time_frame>Baseline and biweekly across 16 weeks</time_frame>
        <population>All participants who were randomized to condition and completed at least one assessment after baseline (N = 218)</population>
        <group_list>
          <group group_id="O1">
            <title>Pragmatic Match</title>
            <description>Randomly assigned, by a case-assigning administrator, to naturalistic treatment with a pragmatically matched provider (control group)</description>
          </group>
          <group group_id="O2">
            <title>Scientific Match</title>
            <description>Randomly assigned, by a case-assigning administrator, to naturalistic treatment with a scientifically matched provider (experimental group)&#xD;
Scientific Match: We have developed an innovative, personalized Match System based on provider track records determined with a multidimensional outcomes tool - the Treatment Outcome Package (TOP). Specifically, patients are assigned to therapists with previously established strengths (i.e., being historically effective) in treating their primary problems (e.g., depression, anxiety).</description>
          </group>
        </group_list>
        <measure>
          <title>Domain-Specific Impairment on the Most Elevated Domain of the Treatment Outcome Package-Clinical Scales (TOP-CS)</title>
          <description>The TOP-CS consists of 58 items assessing 12 symptom and functional domains (risk-adjusted for case mix variables assessed via 37 items on the companion TOP-Case Mix form, such as divorce, job loss, comorbidity): work functioning, sexual functioning, social conflict, depression, panic/somatic anxiety, psychosis, suicidal ideation, violence, mania, sleep, substance abuse, and quality of life. Domain-specific impairment reflects each patient's scores on their most elevated problem domain (i.e., the domain most elevated at baseline). These scores were standardized z-scores (i.e., standard deviation units relative to the general population mean), with higher scores indicating greater impairment. Given that we examined change over the treatment period for this outcome (hierarchical linear model), we provide the average mean and standard deviation for the most elevated TOP domain across all measurement occasions. Note that this measure was positively skewed so we log-transformed it.</description>
          <population>All participants who were randomized to condition and completed at least one assessment after baseline (N = 218)</population>
          <units>units on a scale</units>
          <param>Mean</param>
          <dispersion>Standard Deviation</dispersion>
          <analyzed_list>
            <analyzed>
              <units>Participants</units>
              <scope>Measure</scope>
              <count_list>
                <count group_id="O1" value="119"/>
                <count group_id="O2" value="99"/>
              </count_list>
            </analyzed>
          </analyzed_list>
          <class_list>
            <class>
              <category_list>
                <category>
                  <measurement_list>
                    <measurement group_id="O1" value="0.27" spread=".24"/>
                    <measurement group_id="O2" value="0.28" spread="0.23"/>
                  </measurement_list>
                </category>
              </category_list>
            </class>
          </class_list>
        </measure>
        <analysis_list>
          <analysis>
            <group_id_list>
              <group_id>O1</group_id>
              <group_id>O2</group_id>
            </group_id_list>
            <groups_desc>To account for the nested nature of the data (time points nested within patients nested within therapists), a 3-level hierarchical linear model was used to test the effect of condition (Scientific Match = 1; Pragmatic Match = 0) on weekly during-treatment change on the log-transformed TOP-CS domain-specific z-scores. Given that higher z-scores indicate greater impairment, negative slopes indicate a weekly decrease in impairment during treatment (i.e., a better outcome or more improvement).</groups_desc>
            <non_inferiority_type>Superiority</non_inferiority_type>
            <p_value>.01</p_value>
            <method>3-level hierarchical linear model</method>
            <param_type>condition effect on weekly change rate</param_type>
            <param_value>-0.01</param_value>
            <dispersion_type>Standard Error of the Mean</dispersion_type>
            <dispersion_value>0.002</dispersion_value>
            <ci_percent>95</ci_percent>
            <ci_n_sides>2-Sided</ci_n_sides>
            <ci_lower_limit>-0.01</ci_lower_limit>
            <ci_upper_limit>-0.006</ci_upper_limit>
          </analysis>
        </analysis_list>
      </outcome>
      <outcome>
        <type>Secondary</type>
        <title>Early Treatment Discontinuation (i.e., Attending 2 or Fewer Treatment Sessions)</title>
        <description>Early treatment discontinuation was operationalized as a patient discontinuing treatment after 2 or fewer sessions, whereas early continuation was operationalized as attending 3 or more treatment sessions. For analyses, early treatment discontinuation was coded 1 and early continuation was coded 0.</description>
        <time_frame>Early treatment discontinuation/continuation at session 2</time_frame>
        <population>All participants who were randomized to condition and completed at least one assessment after baseline (N = 218)</population>
        <group_list>
          <group group_id="O1">
            <title>Pragmatic Match</title>
            <description>Randomly assigned, by a case-assigning administrator, to naturalistic treatment with a pragmatically matched provider (control group)</description>
          </group>
          <group group_id="O2">
            <title>Scientific Match</title>
            <description>Randomly assigned, by a case-assigning administrator, to naturalistic treatment with a scientifically matched provider (experimental group)&#xD;
Scientific Match: We have developed an innovative, personalized Match System based on provider track records determined with a multidimensional outcomes tool - the Treatment Outcome Package (TOP). Specifically, patients are assigned to therapists with previously established strengths (i.e., being historically effective) in treating their primary problems (e.g., depression, anxiety).</description>
          </group>
        </group_list>
        <measure>
          <title>Early Treatment Discontinuation (i.e., Attending 2 or Fewer Treatment Sessions)</title>
          <description>Early treatment discontinuation was operationalized as a patient discontinuing treatment after 2 or fewer sessions, whereas early continuation was operationalized as attending 3 or more treatment sessions. For analyses, early treatment discontinuation was coded 1 and early continuation was coded 0.</description>
          <population>All participants who were randomized to condition and completed at least one assessment after baseline (N = 218)</population>
          <units>Participants</units>
          <param>Count of Participants</param>
          <analyzed_list>
            <analyzed>
              <units>Participants</units>
              <scope>Measure</scope>
              <count_list>
                <count group_id="O1" value="119"/>
                <count group_id="O2" value="99"/>
              </count_list>
            </analyzed>
          </analyzed_list>
          <class_list>
            <class>
              <category_list>
                <category>
                  <measurement_list>
                    <measurement group_id="O1" value="22"/>
                    <measurement group_id="O2" value="22"/>
                  </measurement_list>
                </category>
              </category_list>
            </class>
          </class_list>
        </measure>
        <analysis_list>
          <analysis>
            <group_id_list>
              <group_id>O1</group_id>
              <group_id>O2</group_id>
            </group_id_list>
            <groups_desc>Multilevel logistic regression analysis with patients nested within therapists (Scientific Match = 1; Pragmatic Match = 0). Statistically significant odds ratios that are greater than 1 would indicate that patients in the Scientific Match Condition were more likely to discontinue treatment early, whereas odds ratios that are less than 1 would indicate the opposite.</groups_desc>
            <non_inferiority_type>Superiority</non_inferiority_type>
            <p_value>.48</p_value>
            <method>Multilevel logistic regression</method>
            <param_type>Odds Ratio (OR)</param_type>
            <param_value>1.30</param_value>
            <dispersion_type>Standard Error of the Mean</dispersion_type>
            <dispersion_value>0.48</dispersion_value>
            <ci_n_sides>2-Sided</ci_n_sides>
          </analysis>
        </analysis_list>
      </outcome>
      <outcome>
        <type>Secondary</type>
        <title>Overall Provider Quality Subscale of the Treatment Outcome Package (TOP) Satisfaction Scale</title>
        <description>The Overall Provider Quality subscale of the TOP Satisfaction Scale assesses the extent to which patients are satisfied with their mental health care provider. This subscale reflects the average of 4 items, with higher scores indicating greater satisfaction (theoretical range = 1 to 6).</description>
        <time_frame>Assessed after 16 weeks of treatment or at the point of naturalistic treatment termination, whichever comes sooner</time_frame>
        <population>Due to a relatively large amount of missing data for this measure (compared to other study measures), this was considered a completer analysis that involved only the patients who completed this posttreatment measure (N = 97).</population>
        <group_list>
          <group group_id="O1">
            <title>Pragmatic Match</title>
            <description>Randomly assigned, by a case-assigning administrator, to naturalistic treatment with a pragmatically matched provider (control group)</description>
          </group>
          <group group_id="O2">
            <title>Scientific Match</title>
            <description>Randomly assigned, by a case-assigning administrator, to naturalistic treatment with a scientifically matched provider (experimental group)&#xD;
Scientific Match: We have developed an innovative, personalized Match System based on provider track records determined with a multidimensional outcomes tool - the Treatment Outcome Package (TOP). Specifically, patients are assigned to therapists with previously established strengths (i.e., being historically effective) in treating their primary problems (e.g., depression, anxiety).</description>
          </group>
        </group_list>
        <measure>
          <title>Overall Provider Quality Subscale of the Treatment Outcome Package (TOP) Satisfaction Scale</title>
          <description>The Overall Provider Quality subscale of the TOP Satisfaction Scale assesses the extent to which patients are satisfied with their mental health care provider. This subscale reflects the average of 4 items, with higher scores indicating greater satisfaction (theoretical range = 1 to 6).</description>
          <population>Due to a relatively large amount of missing data for this measure (compared to other study measures), this was considered a completer analysis that involved only the patients who completed this posttreatment measure (N = 97).</population>
          <units>units on a scale</units>
          <param>Mean</param>
          <dispersion>Standard Deviation</dispersion>
          <analyzed_list>
            <analyzed>
              <units>Participants</units>
              <scope>Measure</scope>
              <count_list>
                <count group_id="O1" value="54"/>
                <count group_id="O2" value="43"/>
              </count_list>
            </analyzed>
          </analyzed_list>
          <class_list>
            <class>
              <category_list>
                <category>
                  <measurement_list>
                    <measurement group_id="O1" value="5.01" spread="1.35"/>
                    <measurement group_id="O2" value="5.17" spread="1.11"/>
                  </measurement_list>
                </category>
              </category_list>
            </class>
          </class_list>
        </measure>
        <analysis_list>
          <analysis>
            <group_id_list>
              <group_id>O1</group_id>
              <group_id>O2</group_id>
            </group_id_list>
            <groups_desc>Due to the nested nature of the data (patients nested within therapists), we used a two-level hierarchical linear model to test the effect of condition on provider satisfaction at posttreatment. Because higher values indicate more satisfaction, a positive condition effect would indicate that Scientific Match patients were more satisfied than Pragmatic Match patients, whereas a negative condition effect would indicate the opposite.</groups_desc>
            <non_inferiority_type>Superiority</non_inferiority_type>
            <p_value>.44</p_value>
            <method>2-level hierarchical linear model</method>
            <param_type>condition effect on satisfaction</param_type>
            <param_value>0.37</param_value>
            <dispersion_type>Standard Error of the Mean</dispersion_type>
            <dispersion_value>0.48</dispersion_value>
            <ci_percent>95</ci_percent>
            <ci_n_sides>2-Sided</ci_n_sides>
            <ci_lower_limit>-0.57</ci_lower_limit>
            <ci_upper_limit>1.31</ci_upper_limit>
          </analysis>
        </analysis_list>
      </outcome>
    </outcome_list>

    <reported_events>
      <time_frame>Psychotherapy was delivered naturalistically. Therefore, treatment lengths varied. Patients completed study measures through the point of actual treatment termination or through 16 weeks of treatment (whichever came sooner).</time_frame>
      <group_list>
        <group group_id="E1">
          <title>Pragmatic Match</title>
          <description>Randomly assigned, by a case-assigning administrator, to naturalistic treatment with a pragmatically matched provider (control group)</description>
        </group>
        <group group_id="E2">
          <title>Scientific Match</title>
          <description>Randomly assigned, by a case-assigning administrator, to naturalistic treatment with a scientifically matched provider (experimental group)&#xD;
Scientific Match: We have developed an innovative, personalized Match System based on provider track records determined with a multidimensional outcomes tool - the Treatment Outcome Package (TOP). Specifically, patients are assigned to therapists with previously established strengths (i.e., being historically effective) in treating their primary problems (e.g., depression, anxiety).</description>
        </group>
      </group_list>
      <serious_events>
        <category_list>
          <category>
            <title>Total</title>
            <event_list>
              <event>
                <sub_title>Total, all-cause mortality</sub_title>
                <counts group_id="E1" subjects_affected="0" subjects_at_risk="119"/>
                <counts group_id="E2" subjects_affected="0" subjects_at_risk="99"/>
              </event>
              <event>
                <sub_title>Total, serious adverse events</sub_title>
                <counts group_id="E1" subjects_affected="0" subjects_at_risk="119"/>
                <counts group_id="E2" subjects_affected="0" subjects_at_risk="99"/>
              </event>
            </event_list>
          </category>
        </category_list>
      </serious_events>
      <other_events>
        <frequency_threshold>0</frequency_threshold>
        <category_list>
          <category>
            <title>Total</title>
            <event_list>
              <event>
                <sub_title>Total, other adverse events</sub_title>
                <counts group_id="E1" subjects_affected="0" subjects_at_risk="119"/>
                <counts group_id="E2" subjects_affected="0" subjects_at_risk="99"/>
              </event>
            </event_list>
          </category>
        </category_list>
      </other_events>
    </reported_events>

    <certain_agreements>
      <pi_employee>All Principal Investigators ARE employed by the organization sponsoring the study.</pi_employee>
      <restrictive_agreement>There is NOT an agreement between Principal Investigators and the Sponsor (or its agents) that restricts the PI's rights to discuss or publish trial results after the trial is completed. </restrictive_agreement>
    </certain_agreements>
    <limitations_and_caveats>The naturalistic design resulted in limited information on the treatments themselves, differing treatment lengths, and some missing data.</limitations_and_caveats>
    <point_of_contact>
      <name_or_title>Dr. Michael J. Constantino</name_or_title>
      <organization>University of Massachusetts Amherst</organization>
      <phone>4135451388</phone>
      <email>mconstantino@psych.umass.edu</email>
    </point_of_contact>
  </clinical_results>
</clinical_study>


download date: ClinicalTrials.gov processed this data on September 20, 2023
link text: Link to the current ClinicalTrials.gov record.
url: https://clinicaltrials.gov/ct2/show/NCT02990000
org study id: IHS-1503-28573
nct id: NCT02990000
lead sponsor: 
collaborator: 
collaborator: 
collaborator: 
collaborator: 
has dmc: Yes
is fda regulated drug: No
is fda regulated device: No
Research has shown that mental health care (MHC) providers differ significantly in their
      ability to help patients. In addition, providers demonstrate different patterns of
      effectiveness across symptom and functioning domains. For example, some providers are
      reliably effective in treating numerous patients and problem domains, others are reliably
      effective in some domains (e.g., depression, substance abuse) yet appear to struggle in
      others (e.g., anxiety, social functioning), and some are reliably ineffective, or even
      harmful, across patients and domains. Knowledge of these provider differences is based
      largely on patient-reported outcomes collected in routine MHC settings.

      Unfortunately, provider performance information is not systematically used to refer or assign
      a particular patient to a scientifically based best-matched provider. MHC systems continue to
      rely on random or purely pragmatic case assignment and referral, which significantly "waters
      down" the odds of a patient being assigned/referred to a high performing provider in the
      patient's area(s) of need, and increases the risk of being assigned/referred to a provider
      who may have a track record of ineffectiveness. This research aims to solve the existing
      non-patient-centered provider-matching problem.

      Specifically, the investigators aim to demonstrate the comparative effectiveness of a
      scientifically-based patient-provider match system compared to status quo pragmatic case
      assignment. The investigators expect in the scientific match group significantly better
      treatment outcomes (e.g., symptoms, quality of life) and higher patient satisfaction with
      treatment. The investigators also expect to demonstrate feasibility of implementing a
      scientific match process in a community MHC system and broad dissemination of the easily
      replicated scientific match technology in diverse health care settings. The importance of
      this work for patients cannot be understated. Far too many patients struggle to find the
      right provider, which unnecessarily prolongs suffering and promotes health care system
      inefficiency. A scientific match system based on routine outcome data uses patient-generated
      information to direct this patient to this provider in this setting. In addition, when based
      on multidimensional assessment, it allows a wide variety of patient-centered outcomes to be
      represented (e.g., symptom domains, functioning domains, quality of life).
Background and Significance:

      Mental illness is an extraordinary and highly burdensome public health problem.
      Unfortunately, even for individuals who access mental health care (MHC), the care is too
      often substandard. Research has consistently demonstrated that approximately 10-15% of
      patients will deteriorate or experience harm during treatment. Further, when these rates are
      combined with no-change rates, only 40% or less of patients meaningfully recover.
      Importantly, treatment research has illuminated substantial variability in providers'
      outcomes. Simply put, the MHC provider impacts treatment outcomes, and stakeholders lack
      systematic access to valid and actionable information to optimize effective patient-provider
      matches. Without collecting and disseminating performance data, stakeholders lack vital
      information on which to base health care choices and personalize treatment. Conversely, there
      potentially is immense advantage to matching patients to providers based on scientific
      outcome data. Patients, stakeholders, researchers, and clinicians have all endorsed such
      applied knowledge transfer as a high priority. In response, the investigators have developed
      and piloted a technology to test this match concept and patient-centered health model.

      Prominent health care agencies have placed outcome/performance measurement at the center of
      core initiatives. The Institute of Medicine specifically recommends integrating provider
      performance data in treatment decision-making. Despite this rhetoric, 2 Cochrane Reviews
      combined could only identify 4 studies that addressed this question with minimal methodology
      standards; the results were mixed. Importantly, none involved a targeted dissemination
      intervention, and none involved MHC. Previous research, including our own, has empirically
      demonstrated substantial differences in projected treatment effect sizes depending on to
      which therapist a patient is referred. The key evidence gap is the need for a rigorous test
      of the effectiveness of a targeted MHC provider-performance dissemination intervention
      compared to standard/pragmatic referral and case assignment. Relatedly, the Patient-Centered
      Outcomes Research Institute (PCORI) has called for increased "precision" or "personalized"
      treatment, with a focus on tailoring. The match algorithm responds directly to this high
      priority call to customize care in a personal and evidence-based way.

      Specific Aims:

      The aim of this comparative effectiveness research (CER) is to test an innovative,
      scientifically informed patient-therapist referral match algorithm based on MHC provider
      outcome data. The investigators will employ a randomized controlled trial (RCT) to compare
      the match algorithm with the commonplace pragmatic referral matching (based on provider
      availability, convenience, or self-reported specialty). Psychosocial treatment itself will
      remain naturalistically administered by varied providers (e.g., psychologists, social
      workers) to patients with complex mental health concerns within a partner clinic network,
      Psychological and Behavioral Consultants (PsychBC). The investigators hypothesize that the
      scientific match group will outperform the pragmatic match group in decreasing patient
      symptoms and treatment dropout, and in promoting patient functional outcomes, outcome
      expectations, and care satisfaction, as well as patient-therapist alliance quality. Doing so
      will establish the match algorithm as a mechanism of effective patient-centered MHC.

      Methods:

      The investigators will compare the effectiveness of naturalistic MHC either with or without
      the scientific matching aid with a double blind, individual level RCT. The investigators will
      first conduct a baseline assessment of PsychBC therapists' (target enrollment N=44)
      performance (across at least 15 cases) to determine their strengths in treating 12 behavioral
      health domains measured by the primary outcome tool on which our match algorithm is based --
      the Treatment Outcome Package (TOP). The TOP is already administered routinely in our partner
      network. Based on years of predictive analytic research, this tool classifies therapists as
      "effective," "neutral," or "ineffective/harmful" for each TOP domain. The blinded therapists
      will be crossed over conditions.

      Next, for the trial, new adult outpatients (target enrollment N=281) will be randomly
      assigned to the Match condition or case assignment as usual (typically based on pragmatic
      considerations, such as provider availability, convenience, or self-reported specialty). The
      only patient exclusion criterion will be people who are not the primary decision-maker for
      their care. Thus, patients will present with a multitude of problems across a spectrum of
      diagnoses. With therapist assignment as the only manipulation, participating therapists will
      treat patients fully naturalistically. Treatment outcomes will be assessed regularly through
      mutual termination or up to 16 weeks. Primary analyses will involve hierarchical linear
      modeling to examine comparative rates and patterns of change on the outcomes.
allocation: Randomized
intervention model: Parallel Assignment
primary purpose: Health Services Research
masking: Double (Participant, Care Provider)
measure: Average Z-Scores for the Treatment Outcome Package-Clinical Scales (TOP-CS; Kraus, Seligman, & Jordan, 2005)
time frame: Baseline and biweekly across 16 weeks
description: The TOP-Clinical Scales consist of 58 items assessing 12 symptom and functional domains (risk-adjusted for case mix variables assessed via 37 items on the companion TOP-Case Mix form, such as divorce, job loss, comorbidity): work functioning, sexual functioning, social conflict, depression, panic/somatic anxiety, psychosis, suicidal ideation, violence, mania, sleep, substance abuse, and quality of life. Global symptom severity was assessed by averaging the z-scores (i.e., standard deviation units relative to the general population mean) across the 12 clinical scales. Higher scores indicate greater impairment. Given that we examined change over the entire treatment period for this outcome (in a longitudinal hierarchical linear model), we provide the average mean and standard deviation for the TOP-CS z-scores across all measurement occasions.
measure: Symptom Checklist-10 (SCL-10; Rosen, Drescher, Moos, & Gusman, 1999) Total Score
time frame: Baseline and biweekly across 16 weeks
description: Global psychological distress was assessed with the Symptom Checklist-10 (SCL-10; Rosen, Drescher, Moos, & Gusman, 1999), a 10-item, well validated and widely used self-report inventory that assesses psychological well-being. Total scores can range from 0 to 40, with higher scores indicating greater distress. Given that we examined change over the entire treatment period for this outcome (in a longitudinal hierarchical linear model), we provide the average mean and standard deviation for the SCL-10 total score across all measurement occasions.
measure: Working Alliance Inventory-Short Form, Patient Version (WAI-SF-P; Tracey, & Kokotovic, 1989) Total Score
time frame: Biweekly across 16 weeks
description: The WAI is the most widely used alliance measure, assessing patient-therapist agreement on the goals and tasks of treatment, and the quality of their relational bond. This 12-item short form assesses these dimensions from the patient's perspective, with higher scores indicating a more positive relationship (theoretical range = 12 to 84). Given that we examined change over the entire treatment period for this outcome (in a longitudinal hierarchical linear model), we provide the average mean and standard deviation for the WAI total score across all measurement occasions.
measure: Outcome Expectation (OE) Subscale of the Credibility/Expectancy Scale (CEQ; Devilly, & Borkovec, 2000)
time frame: Biweekly across 16 weeks
description: The OE subscale of the CEQ is the most widely used and psychometrically sound measure of patients' expectations for the personal efficacy of treatment. The three OE items range from 1-9 or 0-100% (in 10 percentage point increments), with higher ratings indicating greater expectation for improvement. Given that the OE CEQ items are assessed on different scales, we re-scaled the items to the same metric before creating a total score (theoretical range = 3 to 27). Given that we examined change over the entire treatment period for this outcome (in a longitudinal hierarchical linear model), we provide the average mean and standard deviation for the OE subscale across all measurement occasions.
measure: Domain-Specific Impairment on the Most Elevated Domain of the Treatment Outcome Package-Clinical Scales (TOP-CS)
time frame: Baseline and biweekly across 16 weeks
description: The TOP-CS consists of 58 items assessing 12 symptom and functional domains (risk-adjusted for case mix variables assessed via 37 items on the companion TOP-Case Mix form, such as divorce, job loss, comorbidity): work functioning, sexual functioning, social conflict, depression, panic/somatic anxiety, psychosis, suicidal ideation, violence, mania, sleep, substance abuse, and quality of life. Domain-specific impairment reflects each patient's scores on their most elevated problem domain (i.e., the domain most elevated at baseline). These scores were standardized z-scores (i.e., standard deviation units relative to the general population mean), with higher scores indicating greater impairment. Given that we examined change over the treatment period for this outcome (hierarchical linear model), we provide the average mean and standard deviation for the most elevated TOP domain across all measurement occasions. Note that this measure was positively skewed so we log-transformed it.
measure: Early Treatment Discontinuation (i.e., Attending 2 or Fewer Treatment Sessions)
time frame: Early treatment discontinuation/continuation at session 2
description: Early treatment discontinuation was operationalized as a patient discontinuing treatment after 2 or fewer sessions, whereas early continuation was operationalized as attending 3 or more treatment sessions. For analyses, early treatment discontinuation was coded 1 and early continuation was coded 0.
measure: Overall Provider Quality Subscale of the Treatment Outcome Package (TOP) Satisfaction Scale
time frame: Assessed after 16 weeks of treatment or at the point of naturalistic treatment termination, whichever comes sooner
description: The Overall Provider Quality subscale of the TOP Satisfaction Scale assesses the extent to which patients are satisfied with their mental health care provider. This subscale reflects the average of 4 items, with higher scores indicating greater satisfaction (theoretical range = 1 to 6).
arm group label: Pragmatic Match
arm group type: No Intervention
description: Randomly assigned, by a case-assigning administrator, to naturalistic treatment with a pragmatically matched provider (control group)
arm group label: Scientific Match
arm group type: Experimental
description: Randomly assigned, by a case-assigning administrator, to naturalistic treatment with a scientifically matched provider (experimental group)
intervention type: Behavioral
intervention name: Scientific Match
description: We have developed an innovative, personalized Match System based on provider track records determined with a multidimensional outcomes tool - the Treatment Outcome Package (TOP). Specifically, patients are assigned to therapists with previously established strengths (i.e., being historically effective) in treating their primary problems (e.g., depression, anxiety).
arm group label: Scientific Match
other name: Match System
criteria: 
gender: All
minimum age: 18 Years
maximum age: 70 Years
healthy volunteers: No
last name: Michael J Constantino, PhD
role: Principal Investigator
affiliation: University of Massachusetts, Amherst
last name: James F Boswell, PhD
role: Principal Investigator
affiliation: University at Albany, SUNY
last name: David R Kraus, PhD
role: Principal Investigator
affiliation: Outcome Referrals
last name: Thomas P Swales, PhD
role: Principal Investigator
affiliation: Psychological and Behavioral Consultants
facility: 
country: United States
url: http://improvementalhealthcare.org
description: Study-specific website
responsible party type: Sponsor
mesh term: Mental Disorders
sharing ipd: Yes
ipd description: Upon request on a case-by-case basis, we will share all IPD that underlie results in a publication (e.g., data extraction for meta-analyses). As appropriate, based on specific scientific journals' standards, we will provide analytic code used to generate published results.
ipd info type: Study Protocol
ipd info type: Statistical Analysis Plan (SAP)
ipd info type: Informed Consent Form (ICF)
ipd info type: Analytic Code
ipd time frame: We will begin sharing IPD upon request 6 months following the publication of our peer-reviewed final research report for PCORI, and we will maintain our de-identified data set indefinitely given possible future requests (e.g., to extract data for meta-analyses).
ipd access criteria: We will share fully de-identified IPD, a corresponding data dictionary, and the above supporting information to professional scientific colleagues (with established reputations for publishing original psychotherapy research in accordance with ethical guidelines) for the purposes of replication efforts or meta-analyses. For other usages, such as requests to conduct novel secondary analyses, we will consider such collaborations on a case-by-case basis and clearly determine authorship arrangements in writing.
Review requests, including a detailed plan for how the data will be used, should be directed via email to the PI, Dr. Michael Constantino (mconstantino@psych.umass.edu). Dr. Constantino reserves the right to deny individual share requests if the usage details are questionable or unclear.
provided document: 
participant flow: 
baseline: 
outcome list: 
reported events: 
certain agreements: 
limitations and caveats: The naturalistic design resulted in limited information on the treatments themselves, differing treatment lengths, and some missing data.
point of contact: 