xml: <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/NCT05973240</url>
    </required_header>
    <id_info>
      <org_study_id>52/INT/2023</org_study_id>
      <nct_id>NCT05973240</nct_id>
    </id_info>
    <brief_title>Developing Anticoagulation Self-Report Measure in Adults</brief_title>
    <acronym>PERSONAE</acronym>
    <official_title>Multiphase Research to Develop a Self-report Measure of the Preparedness for Self-Monitoring and Self-Management of Oral Anticoagulation in Adults (The PERSONAE Project)</official_title>
    <sponsors>
      <lead_sponsor>
        <agency>IRCCS Policlinico S. Donato</agency>
        <agency_class>Other</agency_class>
      </lead_sponsor>
    </sponsors>
    <source>IRCCS Policlinico S. Donato</source>
    <oversight_info>
      <has_dmc>No</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>
        The use of oral anticoagulants has been increasing globally to prevent strokes associated&#xD;
        with atrial fibrillation and heart valve replacements. Patients on long-term anticoagulation&#xD;
        have the option to self-test their blood clotting time using point-of-care testing equipment&#xD;
        (POCT). They can choose to self-manage their medication dosage or self-monitor and seek dose&#xD;
        adjustments from a clinic. Studies have shown that self-testing approaches are effective and&#xD;
        cost-effective. However, future research should focus on understanding the factors that&#xD;
        influence people's preparedness for self-testing, such as health literacy, self-efficacy, and&#xD;
        perceived support. Assessing preparedness is crucial for tailoring healthcare delivery and&#xD;
        supporting patient education. Highlighting preparedness can also encourage the adoption of&#xD;
        self-testing approaches in countries facing barriers to implementation.&#xD;
      </textblock>
    </brief_summary>
    <detailed_description>
      <textblock>
        Scientific Rationale / Background&#xD;
  &#xD;
        In every situation where the direct oral anticoagulants are not safe (e.g., adults with&#xD;
        multiple morbidities), optimal anticoagulation with warfarin or other vitamin K antagonists&#xD;
        (VKAs) like acenocoumarol or phenprocoumon could potentially prevent more than half of the&#xD;
        strokes associated with atrial fibrillation and heart valve replacements with a relatively&#xD;
        low risk of major bleeding complications (Garcia et al., 2022). Globally, the proportion of&#xD;
        patients taking oral anticoagulants has been rising (Hsu et al., 2022). For instance, roughly&#xD;
        2 out of 100 Italians are taking oral anticoagulants (both direct and indirect drugs)&#xD;
        (Marchetti et al., 2020). As a result, regular monitoring of prothrombin time and dose&#xD;
        adjustment by a specialized hospital service, primary care physician, registered nurse, nurse&#xD;
        practitioner, or pharmacist is necessary for people in treatment with VKAs.&#xD;
  &#xD;
        People using long-term oral anticoagulation could currently use point-of-care testing&#xD;
        equipment (POCT) to keep track of their blood clotting time, which is represented by the&#xD;
        international normalized ratio (INR) (Kantito et al., 2018). Patients who self-test have two&#xD;
        options: they can self-manage (change their medication dosage following a predetermined&#xD;
        dose-INR schedule) or self-monitor (contact a clinic and ask for the proper dose adjustment)&#xD;
        (Kuljis et al., 2017). According to several published studies and systematic reviews, these&#xD;
        approaches to monitoring anticoagulant medication were found to be as good as or better than&#xD;
        routine monitoring by the traditional physician-managed approach (Heneghan et al., 2016;&#xD;
        Magon et al., 2020).&#xD;
  &#xD;
        The quality of anticoagulation control is traditionally expressed by the time in the&#xD;
        therapeutic range (%TTR). More time spent by patients within the therapeutic range (higher&#xD;
        %TTR) leads to a decline in thromboembolic events with no corresponding rise in risks. In&#xD;
        this context, CoaguChek XS and other coagulometers are presently recommended for patients&#xD;
        with atrial fibrillation and heart valve disease by the National Institute for Health and&#xD;
        Care Excellence (NICE) advice in the UK (NICE diagnostics guidance [DG14]) (NICE, 2016).&#xD;
        Similar recommendations are available worldwide, which were triggered by the COVID-19&#xD;
        pandemic (Kow et al., 2020).&#xD;
  &#xD;
        Although self-monitoring and self-management (self-testing approaches) are supported by a&#xD;
        good level of evidence showing their effectiveness and cost-effectiveness, the last Cochrane&#xD;
        review on this topic concluded that future research should examine the factors defining the&#xD;
        preparedness of people's decisions for self-testing (or not) and should take into account&#xD;
        consumer knowledge of self-management, factors that lead people to seek medical attention and&#xD;
        detailed medical information (health literacy), self-efficacy or self-confidence in one's&#xD;
        ability to self-manage, and perceived or actual support. Assessing the preparedness for&#xD;
        self-management and self-monitoring is highly strategic to tailoring the healthcare delivery,&#xD;
        boosting its efficiency, and supporting an adequate educational preparation of suitable&#xD;
        patients for self-testing (Magon et al., 2016). Highlighting the preparedness for&#xD;
        self-management and self-monitoring could also be a strategy to boost the need for adopting&#xD;
        self-testing approaches in those countries, such as Italy, where the rate of adoption of this&#xD;
        approach is undermined by several organizational and professional barriers, such as the costs&#xD;
        of POCT and the unjustified fears of losing a direct control on how patients manage their&#xD;
        treatment (Magon et al., 2022).&#xD;
  &#xD;
        Study design&#xD;
  &#xD;
        Following the recommendations to develop self-reported scales (Rattray &amp; Jones, 2007), a&#xD;
        methodological, multiphase study comprises two main phases.&#xD;
  &#xD;
        Phase one will focus on conceptualizing the PERSONAE scale and will be based on a&#xD;
        developmental methodological approach, including three primary steps. The primary step will&#xD;
        be a literature review to include all the elements linked to the preparedness for&#xD;
        self-monitoring and self-management of oral anticoagulation. The second step will be a&#xD;
        consensus meeting among developers to examine the literature review findings and endorse its&#xD;
        synthesis. Then, the third step will aim to operationalize the situations, and an external&#xD;
        panel of experts will be involved to determine the face and content validity of the newly&#xD;
        developed scale.&#xD;
  &#xD;
        Phase two will consist of the validation procedures. Initially, the PERSONAE scale showing&#xD;
        items with acceptable content validity will be used for cross-sectional data collection. This&#xD;
        specific step will determine, using the Mokken scaling analysis (MSA) procedure, how the&#xD;
        items in the first version of the PERSONAE scale will behave in response to varying levels of&#xD;
        the theoretical latent trait (preparedness) (Watson et al., 2012). The MSA is chosen by&#xD;
        design in this study over the exploratory fact analysis because it investigates the behaviors&#xD;
        of individual items about a single latent characteristic rather than looking at the link&#xD;
        between items, allowing researchers to select the items with the highest scalability toward a&#xD;
        brief, unidimensional measure that can be computed in a single score. In other words, by&#xD;
        adding just the most pertinent questions established using a hierarchical method, MSA&#xD;
        satisfied the aim of establishing a quick assessment of the preparedness for self-monitoring&#xD;
        and self-management of oral anticoagulation. Once a stable unidimensional PERSONAE scale is&#xD;
        developed, a second cross-sectional data collection will be performed to cross-validate the&#xD;
        plausible unidimensional structure of the scale.&#xD;
  &#xD;
        Participants and procedures&#xD;
  &#xD;
        In phase one, a panel of 8-12 experts (i.e., nurses, physicians, and pharmacists) will assess&#xD;
        the relevance and clarity of the proposed items derived from a literature review performed by&#xD;
        the investigators (content validity). The items will represent the situations reflecting how&#xD;
        much patients feel to be prepared to safely and effectively start self-monitoring and&#xD;
        self-management. The involved experts will sign a written consent form to allow investigators&#xD;
        to use their socio-demographic and professional characteristics in the scientific reporting&#xD;
        because content validity is closely linked to the characteristics of the involved experts. In&#xD;
        other words, this phase cannot be anonymous to allow investigators to increase the&#xD;
        transparency regarding the characteristics of the panel by collecting the following&#xD;
        variables: sex, age, academic title, previous experience in studies aimed to test content&#xD;
        validity, and experience in oral anticoagulation.&#xD;
  &#xD;
        Once adequate content validity is obtained in phase two, the study's coordinating center,&#xD;
        IRCCS Policlinico San Donato, will start the data collection. This protocol encompasses two&#xD;
        cross-sectional data collection rounds by employing web surveys to collect data by ensuring&#xD;
        anonymity. A convenience sampling procedure will be employed by using the webpages and social&#xD;
        network media pages of associations involving anticoagulated patients, such as the&#xD;
        &quot;Federazione delle Associazioni Italiane dei Pazienti Anticoagulati&quot; (Feder-AIPA) and&#xD;
        &quot;Associazione Italiana Cardiopatici Congeniti&quot; (AICCA). Once the first data collection round&#xD;
        is completed (i.e., when sample size will be achieved), the selection of the participants for&#xD;
        the second round of data collection will be based on the same approach as the first by adding&#xD;
        a communication aimed to explain that if a patient has already answered to the survey, it is&#xD;
        not possible to re-fill the survey for the second data collection round for avoiding&#xD;
        overlapping responses.&#xD;
  &#xD;
        Sampling procedure&#xD;
  &#xD;
        Data collection will be performed using a cloud-data recording system and involving a web&#xD;
        survey disseminated by the promoter using social media campaigns, newsletters, and flyers.&#xD;
        The sampling procedure will be managed by the local study coordinator and the researcher from&#xD;
        the team accountable for managing the procedure following good clinical practice principles.&#xD;
        As per previous studies, a response rate of approximately 60% of the invited patients is&#xD;
        expected (Magon et al., 2020).&#xD;
  &#xD;
        Sample size&#xD;
  &#xD;
        Considering that the number of items in the PERSONAE scale will depend on the literature&#xD;
        review and the content validity phase, few elements in this pre-development stage are&#xD;
        available to run precise Monte Carlo simulations for determining the required sample size to&#xD;
        achieve at least a power of 0.80 in rejecting the null hypothesis that total-scale H&#xD;
        coefficient = 0. To determine the sample size needed to perform the MSA, the study by Straat&#xD;
        et al. (2014) showed that a sample of 500 participants might be adequate to perform MSA.&#xD;
        Similar results have been shown in the Monte Carlo simulation performed by Ligtvoet et al.&#xD;
        (2010). For this reason, a sample size of 500 participants is required for the first round of&#xD;
        data collection. The MSA procedure will allow reducing, based on a specific hierarchy, the&#xD;
        number of items, including only the ones that will fulfill the monotonicity and the invariant&#xD;
        item ordering assumptions; the first 10-15 items resulting from the selection will define the&#xD;
        preparedness for self-monitoring and self-management of oral anticoagulation in adult&#xD;
        patients.&#xD;
  &#xD;
        For this reason, the required sample for the second round of data collection was based on&#xD;
        Monte Carlo simulations performed in Mplus 8.1 (Muthén &amp; Muthén, 2017), considering several&#xD;
        possibilities (normality vs. non-normal distribution; missing values lower than 5% vs.&#xD;
        missing values higher than 5%). With no missing data and normally distributed variables, the&#xD;
        smallest sample size for performing CFA requires 150 patients to have a power of 0.80 in&#xD;
        rejecting the null hypothesis that the factor correlation is zero. When the likelihood of&#xD;
        missing data is added to the simulation model, a sample size of 175 is needed to achieve a&#xD;
        power of 0.80. For a power of 0.80 when using the CFA model with non-normal items and no&#xD;
        missing data, 245 patients are required. While adding the likelihood of missing data, a&#xD;
        sample size of 305 patients is required for a power of 0.80 in rejecting the null hypothesis&#xD;
        that the factor correlation is zero. The last step in the simulation provides the most&#xD;
        conservative approach and, for this reason, represents the sample size for the second round&#xD;
        of data collection. For each simulation, data were generated from a population with&#xD;
        hypothesized parameter values derived from previous studies with items exploring potential&#xD;
        proxies of preparedness, such as knowledge regarding AVKs, health literacy, and health&#xD;
        engagement (Magon et al., 2018, 2021).&#xD;
  &#xD;
        Eligibility criteria&#xD;
  &#xD;
        In phase one, inclusion criteria for experts will be related to a proven background in&#xD;
        managing patients with VKAs (at least one year), at least a master of science degree in&#xD;
        nursing, pharmacy, or an MD degree, and Italian language proficiency. The exclusion criterium&#xD;
        will be related to the presence of conflicts of interest regarding the topic.&#xD;
  &#xD;
        For phase two, inclusion criteria are detailed in a subsequest table (&quot;Groups and&#xD;
        Interventions&quot; section).&#xD;
  &#xD;
        Data collection tools&#xD;
  &#xD;
        Data collection will be performed through the version of the PERSONAE scale derived from the&#xD;
        content validity phase, a socio-demographic and clinical data form, and a graphic rating&#xD;
        scale based on 5-point assessments (from 0 = strongly disagree to 5 = completely agree) to&#xD;
        assess how patients agree in stating that they would like to receive an education using a&#xD;
        list of technology-assisted learning options (each option will be rated).&#xD;
  &#xD;
        The socio-demographic data will be age (years), sex (male, female, other), marital status&#xD;
        (married, unmarried), educational level (lower than secondary school diploma, secondary&#xD;
        school diploma, university), and occupation (active worker, non-active worker). Clinical&#xD;
        variables will be the time in oral anticoagulation, clinical indication for the&#xD;
        anticoagulation, time in therapeutic range (TTR), and anamnesis of thromboembolic or bleeding&#xD;
        complications in the last three months.&#xD;
  &#xD;
        Data analysis&#xD;
  &#xD;
        The package &quot;mokken&quot; from the statistical program R (R Foundation for Statistical Computing,&#xD;
        Vienna, Austria) will be employed for performing MSA in the sample derived from the first&#xD;
        data collection round (Ark et al., 2021). The MSA allows developers to evaluate each item&#xD;
        hierarchically and select the most relevant ones to evaluate the preparedness (the first&#xD;
        10-15 items), which is the focus of the PERSONAE scale. This approach assumes that a score on&#xD;
        one item is solely a function of the latent trait (preparedness) level and not a score on any&#xD;
        other items. The automated item selection procedure (AISP) will be used in the first stage of&#xD;
        the MSA to determine how many possible scales will emerge from the provided data. The&#xD;
        scalability of the items will be assessed by evaluating the Loevinger's coefficient of&#xD;
        homogeneity (coefH) function and then checking for monotonicity violations after the items&#xD;
        for the most likely scale measuring the preparedness for self-monitoring and self-management&#xD;
        of oral anticoagulation were identified (only violations below 80 are consistent with the&#xD;
        requirements of a Mokken scale). Loevinger's coefficients of homogeneity and their confidence&#xD;
        intervals (CI) at the scale level (Hs), item level (scalability of an individual item, Hi),&#xD;
        and pairs of items (HiJ) will be computed. H values equal to or greater than 0.30, 0.40, or&#xD;
        0.50, respectively, show weak, moderate, or strong scales. The inspection of item pairs will&#xD;
        sustain the exclusion of those violating monotonicity and also provide an assessment of floor&#xD;
        and ceiling effects in data distribution. The appropriate items will then be evaluated using&#xD;
        invariant item ordering (IIO), which includes a backward item selection method algorithm to&#xD;
        narrow the pool of questions to those that best fit the requirements of the used hierarchical&#xD;
        ordering of respondents based on monotone homogeneity. The IIO procedure will remove items&#xD;
        one at a time until no significant violations are found. For each succeeding stage in which&#xD;
        the algorithm will be used, the Htrans (HT) coefficient will express the accuracy of the IIO&#xD;
        selection. HT greater than 0.30 is deemed sufficient to denote proper IIO process and&#xD;
        consistent Mokken scales (Watson et al., 2012). The final set of questions will be used to&#xD;
        calculate the rho coefficients computed using the Molenaar-Sijtsma technique for reliability.&#xD;
  &#xD;
        Confirmatory factor analysis will be employed to cross-validate the plausible unidimensional&#xD;
        structure of the PERSONAE scale derived from the MSA (theoretically including 10-15 items)&#xD;
        using Mplus 8.1 (Muthén &amp; Muthén, 2017). The first model will be unrestricted and unspecified&#xD;
        based on a maximum likelihood robust estimation of the parameters. A confirmatory factor&#xD;
        analysis with covariates (MIMIC) to estimate the measurement invariance between subgroups if&#xD;
        linear relationships between the characteristics of participants and the scale's total score&#xD;
        will be detected. In the case of employing MIMIC models, the amount of reduced χ2 for each&#xD;
        parameter will be explored using the &quot;modification indices&quot; command that will allow authors&#xD;
        to detect which items might cause such violation of invariance (because showing different&#xD;
        behaviors between groups). Items causing invariance will be evaluated for possible deletion&#xD;
        from the final scale. The suitability of confirmatory factor analyses in explaining sample&#xD;
        statistics will be evaluated using the following indices: χ2, χ2/degree of freedom (DF,&#xD;
        acceptable range: 1.5-5), the comparative fit index (CFI), and Tucker-Lewis index (TLI) (CFI&#xD;
        and TLI &gt; 0.90 indicate a good fit), and the root mean square error of approximation (RMSEA;&#xD;
        values of 0.05 or less indicating a well-fitting model, from 0.05 to 0.08 indicating an&#xD;
        adequate fit, and 0.10 or greater indicating under-optimal fit).&#xD;
  &#xD;
        Missing data will be managed using an available-case approach for missingness lower than 5%&#xD;
        or regression imputations for missingness equal to or higher than 5% if the missing at random&#xD;
        assumptions will be empirically met. Analytics will be performed with type I error equal to&#xD;
        5% and using Mplus, version 8.1 (Los Angeles, CA, USA), IBM SPSS® Statistics for Microsoft&#xD;
        Windows, version 27 (IBM Corp., Armonk, NY, USA), and R 4.2.1 (R Foundation for Statistical&#xD;
        Computing, Vienna, Austria, http://www.R-project.org/).&#xD;
  &#xD;
        Ethical considerations&#xD;
  &#xD;
        The first stage of the study (content validity) will involve experts who will be asked to&#xD;
        sign a written informed consent. The data collection via web surveys designed in the second&#xD;
        part of the study can be defined as anonymous because it is impossible to associate any&#xD;
        specific sample with a specific individual using the data collected. According to current law&#xD;
        (European Regulation 2016/679, Legislative Decree 101/2018), using a type of written informed&#xD;
        consent for this type of study is unnecessary because it would compromise the study's&#xD;
        anonymity. On the other hand, it is recommended that patients be fully informed with a&#xD;
        presentation page that is simple to read and describes the goal of the survey before they&#xD;
        complete the online questionnaire.&#xD;
  &#xD;
        Implications for clinical practice&#xD;
  &#xD;
        This project will allow clinicians (nurses, hematologists, general practitioners, and&#xD;
        cardiologists) to assess the preparedness for self-management and self-monitoring in patients&#xD;
        treated using VKAs. Assessing their preparedness could have several implications for clinical&#xD;
        practice.&#xD;
  &#xD;
        First, in Italy and several countries with a similar universal healthcare system, the&#xD;
        utilization of POCT is under-optimal (Magon et al., 2022), and highlighting a structured path&#xD;
        to best prepare patients for self-testing approaches might optimize the practical adoption of&#xD;
        these safe, effective, and cost-effective managing strategies (self-monitoring and&#xD;
        self-management). This aspect is particularly meaningful as it was demonstrated that&#xD;
        potentially eligible patients for self-testing managed with a traditional approach report&#xD;
        lower levels of mental health because they feel unable to express their potential&#xD;
        contribution to managing their condition (Magon et al., 2020).&#xD;
  &#xD;
        Second, the preparedness for self-management and self-monitoring in patients treated using&#xD;
        VKAs might guide the designing of tailored educational activities for patients. The need for&#xD;
        tailored education in patients with VKAs has been extensively proposed in the literature,&#xD;
        especially with the restrictions introduced by the COVID-19 pandemic (Price &amp; Ansell, 2022).&#xD;
        These educational approaches should also drive interprofessional collaboration and shared&#xD;
        decision-making (Gee et al., 2022).&#xD;
  &#xD;
        Third, the secondary aims of this project will provide an initial epidemiological description&#xD;
        of the preparedness in the Italian setting and can be used to prioritize public health&#xD;
        policies to close the possible emerging gaps. Furthermore, the description of the most&#xD;
        appreciated technology-assisted learning options by patients could be informative for&#xD;
        clinicians and public health officers.&#xD;
      </textblock>
    </detailed_description>
    <overall_status>Not yet recruiting</overall_status>
    <start_date type="Anticipated">August 2023</start_date>
    <completion_date type="Anticipated">December 2024</completion_date>
    <primary_completion_date type="Anticipated">June 2024</primary_completion_date>
    <study_type>Observational</study_type>
    <has_expanded_access>No</has_expanded_access>
    <study_design_info>
      <observational_model>Other</observational_model>
      <time_perspective>Cross-Sectional</time_perspective>
    </study_design_info>
    <primary_outcome>
      <measure>To develop and validate the first self-report measure assessing the preparedness for self-monitoring and self-management of oral anticoagulation in adults (the PERSONAE scale)</measure>
      <time_frame>August 2023 - June 2024</time_frame>
      <description>The PERSONAE scale will be developed and validated initially among Italian adult patients; however, it will be designed to potentially meet the needs for a scaling-up in diverse age groups and internationally.</description>
    </primary_outcome>
    <secondary_outcome>
      <measure>To describe the preliminary levels of preparedness for self-monitoring and self-management of oral anticoagulation in Italian adults.</measure>
      <time_frame>July 2024 - December 2024</time_frame>
      <description>The most technology-assisted learning options among the involved anticoagulated patients will be mapped to ensure future feasible technology-assisted learning initiatives based on a detailed bottom-up description of the preferences indicated by the responders. This information will provide a solid basis for designing future technology-assisted educational interventions to boost preparedness for self-monitoring and self-management of oral anticoagulation in adult patients.</description>
    </secondary_outcome>
    <number_of_groups>2</number_of_groups>
    <enrollment type="Anticipated">305</enrollment>
    <condition>Adults Undergoing Oral Anticoagulation Therapy</condition>
    <arm_group>
      <arm_group_label>Sample derived from the first data collection round (MSA)</arm_group_label>
      <description>Patients have to be aged 18 years and older, cross in an anticoagulation clinic for at least three months, have appropriate cognitive functioning as determined by the six-item screener, and have the ability to give informed consent will be the inclusion criteria. Patients will be excluded if their Charlson Comorbidity Index (CCI) is high (CCI &gt; 4) to account for any comorbidity-related variability and assure the homogeneity of the study sample.</description>
    </arm_group>
    <arm_group>
      <arm_group_label>Sample derived from the second data collection round (CFA)</arm_group_label>
      <description>Patients have to be aged 18 years and older, cross in an anticoagulation clinic for at least three months, have appropriate cognitive functioning as determined by the six-item screener, and have the ability to give informed consent will be the inclusion criteria. Patients will be excluded if their Charlson Comorbidity Index (CCI) is high (CCI &gt; 4) to account for any comorbidity-related variability and assure the homogeneity of the study sample.</description>
    </arm_group>
    <intervention>
      <intervention_type>Other</intervention_type>
      <intervention_name>Participation in an web-based survey</intervention_name>
      <description>Patients who agree to participate will access a web-based survey (SurveyMonkey) via social media, mobile messages, or emails. The invitation will provide study details, eligibility criteria, and tasks. Patients will confirm inclusion/exclusion criteria upon access, and those ineligible will opt out. Data collection will take approximately 10 minutes per patient. Collected data will be sent to an electronic data collector and saved as an eCRF file in REDCap. The study will conduct two cross-sectional data collection rounds using web surveys to ensure anonymity. Convenience sampling will target anticoagulated patient associations' webpages and social media (e.g., Feder-AIPA, AICCA). In the second round, participants will be informed not to resubmit if they have already completed the survey to avoid overlapping responses.</description>
      <arm_group_label>Sample derived from the first data collection round (MSA)</arm_group_label>
      <arm_group_label>Sample derived from the second data collection round (CFA)</arm_group_label>
    </intervention>
    <eligibility>
      <study_pop>
        <textblock>
          Patients have to be aged 18 years and older, cross in an anticoagulation clinic for at&#xD;
          least three months, have appropriate cognitive functioning as determined by the six-item&#xD;
          screener, and have the ability to give informed consent will be the inclusion criteria.&#xD;
          Patients will be excluded if their Charlson Comorbidity Index (CCI) is high (CCI &gt; 4) to&#xD;
          account for any comorbidity-related variability and assure the homogeneity of the study&#xD;
          sample.&#xD;
        </textblock>
      </study_pop>
      <sampling_method>Probability Sample</sampling_method>
      <criteria>
        <textblock>
          Inclusion Criteria:&#xD;
  &#xD;
            -  Adults (aged over 18 year old)&#xD;
  &#xD;
            -  In an anticoagulation clinic for at least three months&#xD;
  &#xD;
            -  Ability to give informed consent&#xD;
  &#xD;
            -  CCI ≤ 4&#xD;
  &#xD;
          Inclusion Criteria:&#xD;
  &#xD;
            -  Age &lt; 18 years&#xD;
  &#xD;
            -  Not in an anticoagulation clinic for at least three months&#xD;
  &#xD;
            -  Inability to give informed consent&#xD;
  &#xD;
            -  CCI &gt; 4&#xD;
        </textblock>
      </criteria>
      <gender>All</gender>
      <minimum_age>18 Years</minimum_age>
      <maximum_age>99 Years</maximum_age>
      <healthy_volunteers>No</healthy_volunteers>
    </eligibility>
    <overall_official>
      <last_name>Rosario Caruso</last_name>
      <role>Principal Investigator</role>
      <affiliation>IRCCS Policlinico S. Donato</affiliation>
    </overall_official>
    <overall_contact>
      <last_name>Rosario Caruso</last_name>
      <phone>02 5277</phone>
      <phone_ext>4940</phone_ext>
      <email>rosario.caruso@grupposandonato.it</email>
    </overall_contact>
    <location>
      <facility>
        <name>IRCCS Policlinico San Donato</name>
        <address>
          <city>San Donato Milanese</city>
          <state>Milano</state>
          <zip>20097</zip>
          <country>Italy</country>
        </address>
      </facility>
      <contact>
        <last_name>Rosario Caruso</last_name>
        <phone>02 5277</phone>
        <phone_ext>4940</phone_ext>
        <email>rosario.caruso@grupposandonato.it</email>
      </contact>
      <investigator>
        <last_name>Arianna Magon</last_name>
        <role>Sub-Investigator</role>
      </investigator>
      <investigator>
        <last_name>Gianluca Conte</last_name>
        <role>Sub-Investigator</role>
      </investigator>
    </location>
    <location_countries>
      <country>Italy</country>
    </location_countries>
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      <PMID>27378324</PMID>
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      <PMID>35935644</PMID>
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      <citation>Kantito S, Saokaew S, Yamwong S, Vathesatogkit P, Katekao W, Sritara P, Chaiyakunapruk N. Cost-effectiveness analysis of patient self-testing therapy of oral anticoagulation. J Thromb Thrombolysis. 2018 Feb;45(2):281-290. doi: 10.1007/s11239-017-1588-8.</citation>
      <PMID>29181693</PMID>
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      <PMID>32458370</PMID>
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      <citation>Kuljis J, Money AG, Perry M, Barnett J, Young T. Technology-assisted self-testing and management of oral anticoagulation therapy: a qualitative patient-focused study. Scand J Caring Sci. 2017 Sep;31(3):603-617. doi: 10.1111/scs.12374. Epub 2016 Aug 8.</citation>
      <PMID>27500499</PMID>
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      <citation>Ligtvoet, R., van der Ark, L. A., te Marvelde, J. M., &amp; Sijtsma, K. (2010). Investigating an Invariant Item Ordering for Polytomously Scored Items. Educational and Psychological Measurement, 70(4), 578-595. https://doi.org/10.1177/0013164409355697</citation>
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      <citation>Magon A, Arrigoni C, Durante A, Falchi C, Dellafiore F, Stievano A, Caruso R. Barriers to self-monitoring implementation in the oral anticoagulated population: A qualitative study. Int J Nurs Pract. 2023 Feb;29(1):e13095. doi: 10.1111/ijn.13095. Epub 2022 Aug 15.</citation>
      <PMID>35971277</PMID>
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      <citation>Magon A, Arrigoni C, Graffigna G, Barello S, Moia M, Palareti G, Caruso R. The effect of health literacy on vaccine hesitancy among Italian anticoagulated population during COVID-19 pandemic: the moderating role of health engagement. Hum Vaccin Immunother. 2021 Dec 2;17(12):5007-5012. doi: 10.1080/21645515.2021.1984123. Epub 2021 Oct 13.</citation>
      <PMID>34643478</PMID>
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      <citation>Magon A, Arrigoni C, Moia M, Mancini M, Dellafiore F, Manara DF, Caruso R. Determinants of health-related quality of life: a cross-sectional investigation in physician-managed anticoagulated patients using vitamin K antagonists. Health Qual Life Outcomes. 2020 Mar 16;18(1):73. doi: 10.1186/s12955-020-01326-y.</citation>
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      <PMID>34342739</PMID>
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      <citation>Straat, J. H., van der Ark, L. A., &amp; Sijtsma, K. (2014). Minimum Sample Size Requirements for Mokken Scale Analysis. Educational and Psychological Measurement, 74(5), 809-822. https://doi.org/10.1177/0013164414529793</citation>
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      <citation>Watson R, van der Ark LA, Lin LC, Fieo R, Deary IJ, Meijer RR. Item response theory: how Mokken scaling can be used in clinical practice. J Clin Nurs. 2012 Oct;21(19-20):2736-46. doi: 10.1111/j.1365-2702.2011.03893.x. Epub 2011 Aug 26.</citation>
      <PMID>21883577</PMID>
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      <citation>WHO. (2021). Ageing and health. https://www.who.int/news-room/fact-sheets/detail/ageing-and-health</citation>
    </reference>
    <verification_date>July 2023</verification_date>
    <study_first_submitted>July 26, 2023</study_first_submitted>
    <study_first_submitted_qc>July 26, 2023</study_first_submitted_qc>
    <study_first_posted type="Actual">August 2, 2023</study_first_posted>
    <last_update_submitted>July 26, 2023</last_update_submitted>
    <last_update_submitted_qc>July 26, 2023</last_update_submitted_qc>
    <last_update_posted type="Actual">August 2, 2023</last_update_posted>
    <responsible_party>
      <responsible_party_type>Principal Investigator</responsible_party_type>
      <investigator_affiliation>IRCCS Policlinico S. Donato</investigator_affiliation>
      <investigator_full_name>Rosario Caruso</investigator_full_name>
      <investigator_title>PhD, RN</investigator_title>
    </responsible_party>
    <keyword>Anticoagulation</keyword>
    <keyword>Multiphase</keyword>
    <keyword>Self-monitoring</keyword>
    <keyword>Self-management</keyword>
    <patient_data>
      <sharing_ipd>Undecided</sharing_ipd>
      <ipd_description>Data will be shared after a formal request to the institution and the Principal Investigator</ipd_description>
    </patient_data>
    <!-- Results have not yet been posted for this study                                          -->
  </clinical_study>
  
  
text: 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/NCT05973240
  org study id: 52/INT/2023
  nct id: NCT05973240
  lead sponsor: 
  has dmc: No
  is fda regulated drug: No
  is fda regulated device: No
  The use of oral anticoagulants has been increasing globally to prevent strokes associated
        with atrial fibrillation and heart valve replacements. Patients on long-term anticoagulation
        have the option to self-test their blood clotting time using point-of-care testing equipment
        (POCT). They can choose to self-manage their medication dosage or self-monitor and seek dose
        adjustments from a clinic. Studies have shown that self-testing approaches are effective and
        cost-effective. However, future research should focus on understanding the factors that
        influence people's preparedness for self-testing, such as health literacy, self-efficacy, and
        perceived support. Assessing preparedness is crucial for tailoring healthcare delivery and
        supporting patient education. Highlighting preparedness can also encourage the adoption of
        self-testing approaches in countries facing barriers to implementation.
  Scientific Rationale / Background
  
        In every situation where the direct oral anticoagulants are not safe (e.g., adults with
        multiple morbidities), optimal anticoagulation with warfarin or other vitamin K antagonists
        (VKAs) like acenocoumarol or phenprocoumon could potentially prevent more than half of the
        strokes associated with atrial fibrillation and heart valve replacements with a relatively
        low risk of major bleeding complications (Garcia et al., 2022). Globally, the proportion of
        patients taking oral anticoagulants has been rising (Hsu et al., 2022). For instance, roughly
        2 out of 100 Italians are taking oral anticoagulants (both direct and indirect drugs)
        (Marchetti et al., 2020). As a result, regular monitoring of prothrombin time and dose
        adjustment by a specialized hospital service, primary care physician, registered nurse, nurse
        practitioner, or pharmacist is necessary for people in treatment with VKAs.
  
        People using long-term oral anticoagulation could currently use point-of-care testing
        equipment (POCT) to keep track of their blood clotting time, which is represented by the
        international normalized ratio (INR) (Kantito et al., 2018). Patients who self-test have two
        options: they can self-manage (change their medication dosage following a predetermined
        dose-INR schedule) or self-monitor (contact a clinic and ask for the proper dose adjustment)
        (Kuljis et al., 2017). According to several published studies and systematic reviews, these
        approaches to monitoring anticoagulant medication were found to be as good as or better than
        routine monitoring by the traditional physician-managed approach (Heneghan et al., 2016;
        Magon et al., 2020).
  
        The quality of anticoagulation control is traditionally expressed by the time in the
        therapeutic range (%TTR). More time spent by patients within the therapeutic range (higher
        %TTR) leads to a decline in thromboembolic events with no corresponding rise in risks. In
        this context, CoaguChek XS and other coagulometers are presently recommended for patients
        with atrial fibrillation and heart valve disease by the National Institute for Health and
        Care Excellence (NICE) advice in the UK (NICE diagnostics guidance [DG14]) (NICE, 2016).
        Similar recommendations are available worldwide, which were triggered by the COVID-19
        pandemic (Kow et al., 2020).
  
        Although self-monitoring and self-management (self-testing approaches) are supported by a
        good level of evidence showing their effectiveness and cost-effectiveness, the last Cochrane
        review on this topic concluded that future research should examine the factors defining the
        preparedness of people's decisions for self-testing (or not) and should take into account
        consumer knowledge of self-management, factors that lead people to seek medical attention and
        detailed medical information (health literacy), self-efficacy or self-confidence in one's
        ability to self-manage, and perceived or actual support. Assessing the preparedness for
        self-management and self-monitoring is highly strategic to tailoring the healthcare delivery,
        boosting its efficiency, and supporting an adequate educational preparation of suitable
        patients for self-testing (Magon et al., 2016). Highlighting the preparedness for
        self-management and self-monitoring could also be a strategy to boost the need for adopting
        self-testing approaches in those countries, such as Italy, where the rate of adoption of this
        approach is undermined by several organizational and professional barriers, such as the costs
        of POCT and the unjustified fears of losing a direct control on how patients manage their
        treatment (Magon et al., 2022).
  
        Study design
  
        Following the recommendations to develop self-reported scales (Rattray & Jones, 2007), a
        methodological, multiphase study comprises two main phases.
  
        Phase one will focus on conceptualizing the PERSONAE scale and will be based on a
        developmental methodological approach, including three primary steps. The primary step will
        be a literature review to include all the elements linked to the preparedness for
        self-monitoring and self-management of oral anticoagulation. The second step will be a
        consensus meeting among developers to examine the literature review findings and endorse its
        synthesis. Then, the third step will aim to operationalize the situations, and an external
        panel of experts will be involved to determine the face and content validity of the newly
        developed scale.
  
        Phase two will consist of the validation procedures. Initially, the PERSONAE scale showing
        items with acceptable content validity will be used for cross-sectional data collection. This
        specific step will determine, using the Mokken scaling analysis (MSA) procedure, how the
        items in the first version of the PERSONAE scale will behave in response to varying levels of
        the theoretical latent trait (preparedness) (Watson et al., 2012). The MSA is chosen by
        design in this study over the exploratory fact analysis because it investigates the behaviors
        of individual items about a single latent characteristic rather than looking at the link
        between items, allowing researchers to select the items with the highest scalability toward a
        brief, unidimensional measure that can be computed in a single score. In other words, by
        adding just the most pertinent questions established using a hierarchical method, MSA
        satisfied the aim of establishing a quick assessment of the preparedness for self-monitoring
        and self-management of oral anticoagulation. Once a stable unidimensional PERSONAE scale is
        developed, a second cross-sectional data collection will be performed to cross-validate the
        plausible unidimensional structure of the scale.
  
        Participants and procedures
  
        In phase one, a panel of 8-12 experts (i.e., nurses, physicians, and pharmacists) will assess
        the relevance and clarity of the proposed items derived from a literature review performed by
        the investigators (content validity). The items will represent the situations reflecting how
        much patients feel to be prepared to safely and effectively start self-monitoring and
        self-management. The involved experts will sign a written consent form to allow investigators
        to use their socio-demographic and professional characteristics in the scientific reporting
        because content validity is closely linked to the characteristics of the involved experts. In
        other words, this phase cannot be anonymous to allow investigators to increase the
        transparency regarding the characteristics of the panel by collecting the following
        variables: sex, age, academic title, previous experience in studies aimed to test content
        validity, and experience in oral anticoagulation.
  
        Once adequate content validity is obtained in phase two, the study's coordinating center,
        IRCCS Policlinico San Donato, will start the data collection. This protocol encompasses two
        cross-sectional data collection rounds by employing web surveys to collect data by ensuring
        anonymity. A convenience sampling procedure will be employed by using the webpages and social
        network media pages of associations involving anticoagulated patients, such as the
        "Federazione delle Associazioni Italiane dei Pazienti Anticoagulati" (Feder-AIPA) and
        "Associazione Italiana Cardiopatici Congeniti" (AICCA). Once the first data collection round
        is completed (i.e., when sample size will be achieved), the selection of the participants for
        the second round of data collection will be based on the same approach as the first by adding
        a communication aimed to explain that if a patient has already answered to the survey, it is
        not possible to re-fill the survey for the second data collection round for avoiding
        overlapping responses.
  
        Sampling procedure
  
        Data collection will be performed using a cloud-data recording system and involving a web
        survey disseminated by the promoter using social media campaigns, newsletters, and flyers.
        The sampling procedure will be managed by the local study coordinator and the researcher from
        the team accountable for managing the procedure following good clinical practice principles.
        As per previous studies, a response rate of approximately 60% of the invited patients is
        expected (Magon et al., 2020).
  
        Sample size
  
        Considering that the number of items in the PERSONAE scale will depend on the literature
        review and the content validity phase, few elements in this pre-development stage are
        available to run precise Monte Carlo simulations for determining the required sample size to
        achieve at least a power of 0.80 in rejecting the null hypothesis that total-scale H
        coefficient = 0. To determine the sample size needed to perform the MSA, the study by Straat
        et al. (2014) showed that a sample of 500 participants might be adequate to perform MSA.
        Similar results have been shown in the Monte Carlo simulation performed by Ligtvoet et al.
        (2010). For this reason, a sample size of 500 participants is required for the first round of
        data collection. The MSA procedure will allow reducing, based on a specific hierarchy, the
        number of items, including only the ones that will fulfill the monotonicity and the invariant
        item ordering assumptions; the first 10-15 items resulting from the selection will define the
        preparedness for self-monitoring and self-management of oral anticoagulation in adult
        patients.
  
        For this reason, the required sample for the second round of data collection was based on
        Monte Carlo simulations performed in Mplus 8.1 (Muthén & Muthén, 2017), considering several
        possibilities (normality vs. non-normal distribution; missing values lower than 5% vs.
        missing values higher than 5%). With no missing data and normally distributed variables, the
        smallest sample size for performing CFA requires 150 patients to have a power of 0.80 in
        rejecting the null hypothesis that the factor correlation is zero. When the likelihood of
        missing data is added to the simulation model, a sample size of 175 is needed to achieve a
        power of 0.80. For a power of 0.80 when using the CFA model with non-normal items and no
        missing data, 245 patients are required. While adding the likelihood of missing data, a
        sample size of 305 patients is required for a power of 0.80 in rejecting the null hypothesis
        that the factor correlation is zero. The last step in the simulation provides the most
        conservative approach and, for this reason, represents the sample size for the second round
        of data collection. For each simulation, data were generated from a population with
        hypothesized parameter values derived from previous studies with items exploring potential
        proxies of preparedness, such as knowledge regarding AVKs, health literacy, and health
        engagement (Magon et al., 2018, 2021).
  
        Eligibility criteria
  
        In phase one, inclusion criteria for experts will be related to a proven background in
        managing patients with VKAs (at least one year), at least a master of science degree in
        nursing, pharmacy, or an MD degree, and Italian language proficiency. The exclusion criterium
        will be related to the presence of conflicts of interest regarding the topic.
  
        For phase two, inclusion criteria are detailed in a subsequest table ("Groups and
        Interventions" section).
  
        Data collection tools
  
        Data collection will be performed through the version of the PERSONAE scale derived from the
        content validity phase, a socio-demographic and clinical data form, and a graphic rating
        scale based on 5-point assessments (from 0 = strongly disagree to 5 = completely agree) to
        assess how patients agree in stating that they would like to receive an education using a
        list of technology-assisted learning options (each option will be rated).
  
        The socio-demographic data will be age (years), sex (male, female, other), marital status
        (married, unmarried), educational level (lower than secondary school diploma, secondary
        school diploma, university), and occupation (active worker, non-active worker). Clinical
        variables will be the time in oral anticoagulation, clinical indication for the
        anticoagulation, time in therapeutic range (TTR), and anamnesis of thromboembolic or bleeding
        complications in the last three months.
  
        Data analysis
  
        The package "mokken" from the statistical program R (R Foundation for Statistical Computing,
        Vienna, Austria) will be employed for performing MSA in the sample derived from the first
        data collection round (Ark et al., 2021). The MSA allows developers to evaluate each item
        hierarchically and select the most relevant ones to evaluate the preparedness (the first
        10-15 items), which is the focus of the PERSONAE scale. This approach assumes that a score on
        one item is solely a function of the latent trait (preparedness) level and not a score on any
        other items. The automated item selection procedure (AISP) will be used in the first stage of
        the MSA to determine how many possible scales will emerge from the provided data. The
        scalability of the items will be assessed by evaluating the Loevinger's coefficient of
        homogeneity (coefH) function and then checking for monotonicity violations after the items
        for the most likely scale measuring the preparedness for self-monitoring and self-management
        of oral anticoagulation were identified (only violations below 80 are consistent with the
        requirements of a Mokken scale). Loevinger's coefficients of homogeneity and their confidence
        intervals (CI) at the scale level (Hs), item level (scalability of an individual item, Hi),
        and pairs of items (HiJ) will be computed. H values equal to or greater than 0.30, 0.40, or
        0.50, respectively, show weak, moderate, or strong scales. The inspection of item pairs will
        sustain the exclusion of those violating monotonicity and also provide an assessment of floor
        and ceiling effects in data distribution. The appropriate items will then be evaluated using
        invariant item ordering (IIO), which includes a backward item selection method algorithm to
        narrow the pool of questions to those that best fit the requirements of the used hierarchical
        ordering of respondents based on monotone homogeneity. The IIO procedure will remove items
        one at a time until no significant violations are found. For each succeeding stage in which
        the algorithm will be used, the Htrans (HT) coefficient will express the accuracy of the IIO
        selection. HT greater than 0.30 is deemed sufficient to denote proper IIO process and
        consistent Mokken scales (Watson et al., 2012). The final set of questions will be used to
        calculate the rho coefficients computed using the Molenaar-Sijtsma technique for reliability.
  
        Confirmatory factor analysis will be employed to cross-validate the plausible unidimensional
        structure of the PERSONAE scale derived from the MSA (theoretically including 10-15 items)
        using Mplus 8.1 (Muthén & Muthén, 2017). The first model will be unrestricted and unspecified
        based on a maximum likelihood robust estimation of the parameters. A confirmatory factor
        analysis with covariates (MIMIC) to estimate the measurement invariance between subgroups if
        linear relationships between the characteristics of participants and the scale's total score
        will be detected. In the case of employing MIMIC models, the amount of reduced χ2 for each
        parameter will be explored using the "modification indices" command that will allow authors
        to detect which items might cause such violation of invariance (because showing different
        behaviors between groups). Items causing invariance will be evaluated for possible deletion
        from the final scale. The suitability of confirmatory factor analyses in explaining sample
        statistics will be evaluated using the following indices: χ2, χ2/degree of freedom (DF,
        acceptable range: 1.5-5), the comparative fit index (CFI), and Tucker-Lewis index (TLI) (CFI
        and TLI > 0.90 indicate a good fit), and the root mean square error of approximation (RMSEA;
        values of 0.05 or less indicating a well-fitting model, from 0.05 to 0.08 indicating an
        adequate fit, and 0.10 or greater indicating under-optimal fit).
  
        Missing data will be managed using an available-case approach for missingness lower than 5%
        or regression imputations for missingness equal to or higher than 5% if the missing at random
        assumptions will be empirically met. Analytics will be performed with type I error equal to
        5% and using Mplus, version 8.1 (Los Angeles, CA, USA), IBM SPSS® Statistics for Microsoft
        Windows, version 27 (IBM Corp., Armonk, NY, USA), and R 4.2.1 (R Foundation for Statistical
        Computing, Vienna, Austria, http://www.R-project.org/).
  
        Ethical considerations
  
        The first stage of the study (content validity) will involve experts who will be asked to
        sign a written informed consent. The data collection via web surveys designed in the second
        part of the study can be defined as anonymous because it is impossible to associate any
        specific sample with a specific individual using the data collected. According to current law
        (European Regulation 2016/679, Legislative Decree 101/2018), using a type of written informed
        consent for this type of study is unnecessary because it would compromise the study's
        anonymity. On the other hand, it is recommended that patients be fully informed with a
        presentation page that is simple to read and describes the goal of the survey before they
        complete the online questionnaire.
  
        Implications for clinical practice
  
        This project will allow clinicians (nurses, hematologists, general practitioners, and
        cardiologists) to assess the preparedness for self-management and self-monitoring in patients
        treated using VKAs. Assessing their preparedness could have several implications for clinical
        practice.
  
        First, in Italy and several countries with a similar universal healthcare system, the
        utilization of POCT is under-optimal (Magon et al., 2022), and highlighting a structured path
        to best prepare patients for self-testing approaches might optimize the practical adoption of
        these safe, effective, and cost-effective managing strategies (self-monitoring and
        self-management). This aspect is particularly meaningful as it was demonstrated that
        potentially eligible patients for self-testing managed with a traditional approach report
        lower levels of mental health because they feel unable to express their potential
        contribution to managing their condition (Magon et al., 2020).
  
        Second, the preparedness for self-management and self-monitoring in patients treated using
        VKAs might guide the designing of tailored educational activities for patients. The need for
        tailored education in patients with VKAs has been extensively proposed in the literature,
        especially with the restrictions introduced by the COVID-19 pandemic (Price & Ansell, 2022).
        These educational approaches should also drive interprofessional collaboration and shared
        decision-making (Gee et al., 2022).
  
        Third, the secondary aims of this project will provide an initial epidemiological description
        of the preparedness in the Italian setting and can be used to prioritize public health
        policies to close the possible emerging gaps. Furthermore, the description of the most
        appreciated technology-assisted learning options by patients could be informative for
        clinicians and public health officers.
  observational model: Other
  time perspective: Cross-Sectional
  measure: To develop and validate the first self-report measure assessing the preparedness for self-monitoring and self-management of oral anticoagulation in adults (the PERSONAE scale)
  time frame: August 2023 - June 2024
  description: The PERSONAE scale will be developed and validated initially among Italian adult patients; however, it will be designed to potentially meet the needs for a scaling-up in diverse age groups and internationally.
  measure: To describe the preliminary levels of preparedness for self-monitoring and self-management of oral anticoagulation in Italian adults.
  time frame: July 2024 - December 2024
  description: The most technology-assisted learning options among the involved anticoagulated patients will be mapped to ensure future feasible technology-assisted learning initiatives based on a detailed bottom-up description of the preferences indicated by the responders. This information will provide a solid basis for designing future technology-assisted educational interventions to boost preparedness for self-monitoring and self-management of oral anticoagulation in adult patients.
  arm group label: Sample derived from the first data collection round (MSA)
  description: Patients have to be aged 18 years and older, cross in an anticoagulation clinic for at least three months, have appropriate cognitive functioning as determined by the six-item screener, and have the ability to give informed consent will be the inclusion criteria. Patients will be excluded if their Charlson Comorbidity Index (CCI) is high (CCI > 4) to account for any comorbidity-related variability and assure the homogeneity of the study sample.
  arm group label: Sample derived from the second data collection round (CFA)
  description: Patients have to be aged 18 years and older, cross in an anticoagulation clinic for at least three months, have appropriate cognitive functioning as determined by the six-item screener, and have the ability to give informed consent will be the inclusion criteria. Patients will be excluded if their Charlson Comorbidity Index (CCI) is high (CCI > 4) to account for any comorbidity-related variability and assure the homogeneity of the study sample.
  intervention type: Other
  intervention name: Participation in an web-based survey
  description: Patients who agree to participate will access a web-based survey (SurveyMonkey) via social media, mobile messages, or emails. The invitation will provide study details, eligibility criteria, and tasks. Patients will confirm inclusion/exclusion criteria upon access, and those ineligible will opt out. Data collection will take approximately 10 minutes per patient. Collected data will be sent to an electronic data collector and saved as an eCRF file in REDCap. The study will conduct two cross-sectional data collection rounds using web surveys to ensure anonymity. Convenience sampling will target anticoagulated patient associations' webpages and social media (e.g., Feder-AIPA, AICCA). In the second round, participants will be informed not to resubmit if they have already completed the survey to avoid overlapping responses.
  arm group label: Sample derived from the first data collection round (MSA)
  arm group label: Sample derived from the second data collection round (CFA)
  study pop: 
  sampling method: Probability Sample
  criteria: 
  gender: All
  minimum age: 18 Years
  maximum age: 99 Years
  healthy volunteers: No
  last name: Rosario Caruso
  role: Principal Investigator
  affiliation: IRCCS Policlinico S. Donato
  last name: Rosario Caruso
  phone: 02 5277
  phone ext: 4940
  email: rosario.caruso@grupposandonato.it
  facility: 
  contact: 
  investigator: 
  investigator: 
  country: Italy
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  PMID: 35743633
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  citation: Heneghan CJ, Garcia-Alamino JM, Spencer EA, Ward AM, Perera R, Bankhead C, Alonso-Coello P, Fitzmaurice D, Mahtani KR, Onakpoya IJ. Self-monitoring and self-management of oral anticoagulation. Cochrane Database Syst Rev. 2016 Jul 5;7(7):CD003839. doi: 10.1002/14651858.CD003839.pub3.
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  citation: Magon A, Arrigoni C, Durante A, Falchi C, Dellafiore F, Stievano A, Caruso R. Barriers to self-monitoring implementation in the oral anticoagulated population: A qualitative study. Int J Nurs Pract. 2023 Feb;29(1):e13095. doi: 10.1111/ijn.13095. Epub 2022 Aug 15.
  PMID: 35971277
  citation: Magon A, Arrigoni C, Graffigna G, Barello S, Moia M, Palareti G, Caruso R. The effect of health literacy on vaccine hesitancy among Italian anticoagulated population during COVID-19 pandemic: the moderating role of health engagement. Hum Vaccin Immunother. 2021 Dec 2;17(12):5007-5012. doi: 10.1080/21645515.2021.1984123. Epub 2021 Oct 13.
  PMID: 34643478
  citation: Magon A, Arrigoni C, Moia M, Mancini M, Dellafiore F, Manara DF, Caruso R. Determinants of health-related quality of life: a cross-sectional investigation in physician-managed anticoagulated patients using vitamin K antagonists. Health Qual Life Outcomes. 2020 Mar 16;18(1):73. doi: 10.1186/s12955-020-01326-y.
  PMID: 32178684
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  responsible party type: Principal Investigator
  investigator affiliation: IRCCS Policlinico S. Donato
  investigator full name: Rosario Caruso
  investigator title: PhD, RN
  sharing ipd: Undecided
  ipd description: Data will be shared after a formal request to the institution and the Principal Investigator