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    **files (1)** – ## freezing_point_lab.pdf **## freezing_point_lab.pdf** Virtual Lab: Freezing-Point Depression and Molecular Weight (Cryoscopy) Adapted from Advanced Chemistry with Vernier, Experiment 4 Using the Physical Chemistry Virtual Lab (vLabs) Cryoscopy Simulation https://pcv-amrt.vlabs….

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    **files (1)**

    – ## freezing_point_lab.pdf

    **## freezing_point_lab.pdf**

    Virtual Lab:

    Freezing-Point Depression and Molecular Weight

    (Cryoscopy)

    Adapted from Advanced Chemistry with Vernier, Experiment 4

    Using the Physical Chemistry Virtual Lab (vLabs) Cryoscopy Simulation

    https://pcv-amrt.vlabs.ac.in/exp/cryoscopy/simulation.html

    Introduction

    When a solute is dissolved in a solvent, the freezing temperature of the resulting solution is
    lower than the freezing point of the pure solvent. This phenomenon is known as freezing-point

    depression and is classified as a colligative property, meaning it depends on the number of

    solute particles present in solution rather than their chemical identity.

    The relationship between freezing-point depression and solution concentration is described by

    the equation:

    ΔTf = Kf × i × m

    where ΔTf is the freezing-point depression, Kf is the cryoscopic constant (molal freezing-point

    depression constant) of the solvent, i is the van’t Hoff factor, and m is the molality of the solution

    (mol solute / kg solvent).

    This equation can be rearranged to solve for the molecular weight of an unknown solute:

    MB = (1000 × Kf × i × WB) / (ΔTf × WA)

    where WB is the mass of solute (g), WA is the mass of solvent (g), and MB is the molar mass of

    the solute (g/mol).

    The van’t Hoff factor (i) accounts for dissociation or association of the solute. For non-

    electrolytes (like sugar or benzoic acid), i = 1. For strong electrolytes like NaCl, i = 2 (dissociates

    into Na⁺ and Cl⁻), and for CaCl2, i = 3.

    In this virtual lab, you will use an online cryoscopy simulation to investigate freezing-point
    depression with multiple solvent-solute systems, determine unknown molecular weights, and

    compare your results with accepted values.

    Objectives

    • Explore the theory of freezing-point depression (cryoscopy) using an online simulation.

    • Use the cryoscopic equation to calculate freezing-point depression for known solutions.

    • Determine the molecular weight of an unknown solute from simulated experimental data.

    • Understand the role of the van’t Hoff factor for electrolytes vs. non-electrolytes.

    • Calculate percent error between experimental and accepted molecular weights.

    Reference Data: Cryoscopic Constants

    The following table lists cryoscopic constants and freezing points for common solvents used in

    this simulation. You will need these values for your calculations.

    Solvent Freezing Point (°C) Kf (°C·kg/mol) Molar Mass (g/mol)

    Water (H₂O) 0.00 −1.86 18.015

    Benzene (C₆H₆) 5.50 −4.90 78.11

    Carbon tetrachloride (CCl₄) −22.62 −29.8 153.82

    Carbon disulfide (CS₂) −111.61 −3.83 76.14

    Lauric acid 43.8 −3.9 200.32

    Procedure

    Part I: Explore the Virtual Lab

    1. Open the virtual lab in your web browser by navigating to:
    https://pcv-amrt.vlabs.ac.in/exp/cryoscopy/index.html

    2. Before using the simulation, read through the Theory tab on the virtual lab website to

    review the equations and concepts.

    3. Complete the Self Evaluation (pretest) questions on the virtual lab site. These will help

    you check your understanding before proceeding.

    4. Familiarize yourself with the simulation interface. Identify where you select the solvent,
    the solute, and where you enter the masses of each. Note how the simulation reports the

    freezing-point depression and/or the depressed freezing point.

    Part II: Freezing-Point Depression of a Known Solution

    In this part, you will verify the cryoscopic equation by using the simulation with a known solute
    (one whose molar mass you can look up). Compare the simulation’s output with your hand-

    calculated values.

    1. In the simulation, select Water as the solvent.

    2. Select a non-electrolyte solute available in the simulation (e.g., urea or sucrose).

    3. Enter a mass of solvent (e.g., 100 g of water) and a mass of solute (e.g., 5 g). Record

    your exact values.

    4. Run the simulation and record the freezing point of the solution as reported.

    5. Record all data in Data Table 1.

    Part III: Determining an Unknown Molecular Weight

    Now use a different solvent-solute combination to determine the molecular weight of the solute,

    as if it were unknown.

    1. Select a different solvent (e.g., Benzene or Carbon tetrachloride).

    2. Select a solute available in the simulation. Record its name, but pretend you do not

    know its molar mass.

    1. Enter masses for solvent and solute. Record exact values.

    2. Run the simulation. Record the freezing point of the solution.

    3. Use the cryoscopic equation to calculate the experimental molecular weight of the

    solute.

    4. Record all data in Data Table 2.

    [https://pcv-amrt.vlabs.ac.in/exp/cryoscopy/index.html](https://pcv-amrt.vlabs.ac.in/exp/cryoscopy/index.html)

    Data Tables

    Data Table 1: Known Solution (Part II)

    Measurement Value

    Solvent selected

    Solute selected

    Mass of solvent, W_A (g)

    Mass of solute, W_B (g)

    Freezing point of pure solvent (°C)

    Freezing point of solution from simulation (°C)

    Kf of solvent (°C·kg/mol)

    Van’t Hoff factor (i)

    Known molar mass of solute (g/mol)

    Data Table 2: Unknown Molecular Weight (Part III)

    Measurement Value

    Solvent selected

    Solute selected

    Mass of solvent, W_A (g)

    Mass of solute, W_B (g)

    Freezing point of pure solvent (°C)

    Freezing point of solution from simulation (°C)

    Observed ΔTf (°C)

    Kf of solvent (°C·kg/mol)

    Van’t Hoff factor (i)

    Data Analysis

    Complete the following calculations. Show all work with proper units.

    1. Using your Data Table 1, calculate the expected ΔTf using the cryoscopic equation: ΔTf
    = Kf × i × m. First calculate molality from the known molar mass of your solute and the

    mass of solvent. Compare your calculated ΔTf with the simulation’s result.

    2. Using your Data Table 2, calculate the molality (m) from the observed ΔTf and the

    known Kf of your solvent. Use: m = ΔTf / (Kf × i).

    3. From the molality calculated in #2, determine the moles of solute. Use: moles = m ×

    (mass of solvent in kg).

    4. Calculate the experimental molecular weight of the solute: MW = (mass of solute in g) /

    (moles of solute).

    5. Look up the accepted molecular weight of your Part III solute. Calculate the percent

    error: % error = |experimental − accepted| / accepted × 100%.

    **## freezing_point_lab.pdf**

    Virtual Lab:

    Freezing-Point Depression and Molecular Weight

    (Cryoscopy)

    Adapted from Advanced Chemistry with Vernier, Experiment 4

    Using the Physical Chemistry Virtual Lab (vLabs) Cryoscopy Simulation

    https://pcv-amrt.vlabs.ac.in/exp/cryoscopy/simulation.html

    Introduction

    When a solute is dissolved in a solvent, the freezing temperature of the resulting solution is
    lower than the freezing point of the pure solvent. This phenomenon is known as freezing-point

    depression and is classified as a colligative property, meaning it depends on the number of

    solute particles present in solution rather than their chemical identity.

    The relationship between freezing-point depression and solution concentration is described by

    the equation:

    ΔTf = Kf × i × m

    where ΔTf is the freezing-point depression, Kf is the cryoscopic constant (molal freezing-point

    depression constant) of the solvent, i is the van’t Hoff factor, and m is the molality of the solution

    (mol solute / kg solvent).

    This equation can be rearranged to solve for the molecular weight of an unknown solute:

    MB = (1000 × Kf × i × WB) / (ΔTf × WA)

    where WB is the mass of solute (g), WA is the mass of solvent (g), and MB is the molar mass of

    the solute (g/mol).

    The van’t Hoff factor (i) accounts for dissociation or association of the solute. For non-

    electrolytes (like sugar or benzoic acid), i = 1. For strong electrolytes like NaCl, i = 2 (dissociates

    into Na⁺ and Cl⁻), and for CaCl2, i = 3.

    In this virtual lab, you will use an online cryoscopy simulation to investigate freezing-point
    depression with multiple solvent-solute systems, determine unknown molecular weights, and

    compare your results with accepted values.

    Objectives

    • Explore the theory of freezing-point depression (cryoscopy) using an online simulation.

    • Use the cryoscopic equation to calculate freezing-point depression for known solutions.

    • Determine the molecular weight of an unknown solute from simulated experimental data.

    • Understand the role of the van’t Hoff factor for electrolytes vs. non-electrolytes.

    • Calculate percent error between experimental and accepted molecular weights.

    Reference Data: Cryoscopic Constants

    The following table lists cryoscopic constants and freezing points for common solvents used in

    this simulation. You will need these values for your calculations.

    Solvent Freezing Point (°C) Kf (°C·kg/mol) Molar Mass (g/mol)

    Water (H₂O) 0.00 −1.86 18.015

    Benzene (C₆H₆) 5.50 −4.90 78.11

    Carbon tetrachloride (CCl₄) −22.62 −29.8 153.82

    Carbon disulfide (CS₂) −111.61 −3.83 76.14

    Lauric acid 43.8 −3.9 200.32

    Procedure

    Part I: Explore the Virtual Lab

    1. Open the virtual lab in your web browser by navigating to:
    https://pcv-amrt.vlabs.ac.in/exp/cryoscopy/index.html

    2. Before using the simulation, read through the Theory tab on the virtual lab website to

    review the equations and concepts.

    3. Complete the Self Evaluation (pretest) questions on the virtual lab site. These will help

    you check your understanding before proceeding.

    4. Familiarize yourself with the simulation interface. Identify where you select the solvent,
    the solute, and where you enter the masses of each. Note how the simulation reports the

    freezing-point depression and/or the depressed freezing point.

    Part II: Freezing-Point Depression of a Known Solution

    In this part, you will verify the cryoscopic equation by using the simulation with a known solute
    (one whose molar mass you can look up). Compare the simulation’s output with your hand-

    calculated values.

    1. In the simulation, select Water as the solvent.

    2. Select a non-electrolyte solute available in the simulation (e.g., urea or sucrose).

    3. Enter a mass of solvent (e.g., 100 g of water) and a mass of solute (e.g., 5 g). Record

    your exact values.

    4. Run the simulation and record the freezing point of the solution as reported.

    5. Record all data in Data Table 1.

    Part III: Determining an Unknown Molecular Weight

    Now use a different solvent-solute combination to determine the molecular weight of the solute,

    as if it were unknown.

    1. Select a different solvent (e.g., Benzene or Carbon tetrachloride).

    2. Select a solute available in the simulation. Record its name, but pretend you do not

    know its molar mass.

    1. Enter masses for solvent and solute. Record exact values.

    2. Run the simulation. Record the freezing point of the solution.

    3. Use the cryoscopic equation to calculate the experimental molecular weight of the

    solute.

    4. Record all data in Data Table 2.

    [https://pcv-amrt.vlabs.ac.in/exp/cryoscopy/index.html](https://pcv-amrt.vlabs.ac.in/exp/cryoscopy/index.html)

    Data Tables

    Data Table 1: Known Solution (Part II)

    Measurement Value

    Solvent selected

    Solute selected

    Mass of solvent, W_A (g)

    Mass of solute, W_B (g)

    Freezing point of pure solvent (°C)

    Freezing point of solution from simulation (°C)

    Kf of solvent (°C·kg/mol)

    Van’t Hoff factor (i)

    Known molar mass of solute (g/mol)

    Data Table 2: Unknown Molecular Weight (Part III)

    Measurement Value

    Solvent selected

    Solute selected

    Mass of solvent, W_A (g)

    Mass of solute, W_B (g)

    Freezing point of pure solvent (°C)

    Freezing point of solution from simulation (°C)

    Observed ΔTf (°C)

    Kf of solvent (°C·kg/mol)

    Van’t Hoff factor (i)

    Data Analysis

    Complete the following calculations. Show all work with proper units.

    1. Using your Data Table 1, calculate the expected ΔTf using the cryoscopic equation: ΔTf
    = Kf × i × m. First calculate molality from the known molar mass of your solute and the

    mass of solvent. Compare your calculated ΔTf with the simulation’s result.

    2. Using your Data Table 2, calculate the molality (m) from the observed ΔTf and the

    known Kf of your solvent. Use: m = ΔTf / (Kf × i).

    3. From the molality calculated in #2, determine the moles of solute. Use: moles = m ×

    (mass of solvent in kg).

    4. Calculate the experimental molecular weight of the solute: MW = (mass of solute in g) /

    (moles of solute).

    5. Look up the accepted molecular weight of your Part III solute. Calculate the percent

    error: % error = |experimental − accepted| / accepted × 100%.

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    Mention in your journal your cumulative hours to date including direct and indirect. Complete a 1–3 pagee journal detailing your experiences and developmental process as a professional counselor at your practicum site. Although the journal will include personal insights and experiences, you need to …

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    Mention in your journal your cumulative hours to date including direct and indirect.  Complete a 1–3 pagee journal detailing your experiences and developmental process as a professional counselor at your practicum site.  Although the journal will include personal insights and experiences, you need to also demonstrate academic rigor with APA format and use a minimum of two references from peer-reviewed journal articles (published within the last 5-10 years), textbooks (e.g. Erford text), etc. In other words, use academic and professional resources to inform your developmental process and to help you demonstrate growth in the following areas (choose minimum of 2-3 of the following content areas) towards:

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    How does the principle of negligence in tort law balance the interests of holding individuals accountable for harm caused by their actions while also protecting them from undue liability? Provide examples of real-life cases or hypothetical scenarios to support your argument. 300 words for the initia…

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    How does the principle of negligence in tort law balance the interests of holding individuals accountable for harm caused by their actions while also protecting them from undue liability? Provide examples of real-life cases or hypothetical scenarios to support your argument.

    300 words for the initial post

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    respond to the 2 people in the attached **Respond** to **at least two** colleagues on **two different days** in one or more of the following ways: – Ask a probing question, substantiated with additional background information, evidence, or research. – Share an insight from having read your colleague…

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    respond to the 2 people in the attached

    **Respond** to **at least two** colleagues on **two different days** in one or more of the following ways:

    – Ask a probing question, substantiated with additional background information, evidence, or research.
    – Share an insight from having read your colleagues’ postings, synthesizing the information to provide new perspectives.
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  • [Solved] Assigment .Apa seven . All instructions attached.

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    **files (2)** – ## Articles.pdf – LiteratureReview.docx **## Articles.pdf** References 1. Aboraya, A., Elswick, D., Berry, J., Chandran, D., Hill, C., Zheng, W., Hustead, J. D., Van Oppen, D., Patel, V., Berzingi, S., Wang, K., Grimes, D., Gallucci, G., Mishra, D., Shrestha, R., Justice, J., Chumbe…

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    **files (2)**

    – ## Articles.pdf

    – LiteratureReview.docx

    **## Articles.pdf**

    References

    1. Aboraya, A., Elswick, D., Berry, J., Chandran, D., Hill, C., Zheng, W., Hustead, J. D.,

    Van Oppen, D., Patel, V., Berzingi, S., Wang, K., Grimes, D., Gallucci, G., Mishra, D.,

    Shrestha, R., Justice, J., Chumber, P., Rizvi, A., Yadava, D., … Hyacinthe, J. (2025).

    Measurement-based care training curriculum in psychiatry residency programs: Four-year

    implementation experience and future directions. Innovations in Clinical Neuroscience,

    22(4–6), 20–26.

    2. Aldis, R., Rosenfeld, L. C., Mulvaney-Day, N., Lanca, M., Zona, K., Lam, J. A., Asfour,

    J., Meltzer, J. C., Leff, H. S., Fulwiler, C., Wang, P., & Progovac, A. M. (2024).

    Determinants of remote measurement-based care uptake in a safety-net outpatient

    psychiatry department. Learning Health Systems, 8(S1), e10416.

    3. Askari, N., Gupta, R., Hussain-Shamsy, N., Barker, L. C., Champagne, T., Lam, R. W.,

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    Shanmuganathan, A., Wang, V., & Vigod, S. N. (2025). Electronic measurement-based

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    4. Azizian Kia, S., Wittkampf, L., van Lankeren, J., & Janse, P. (2025). Motives of

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    5. Barkham, M., Broglia, E., & The SCORE Consortium. (2024). Routine outcome

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    6. Bear, H. A., Dalzell, K., Edbrooke-Childs, J., & Wolpert, M. (2022). Applying behaviour

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    10. Cuperfain, A. B., Hui, K., Berkhout, S. G., Foussias, G., Gratzer, D., Kidd, S. A.,

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    and Psychiatric Sciences, 30.

    36. Rush, A. J., Gore-Langton, R. E., Bart, G., et al. (2024). Tools to implement MBC for

    OUD. Addiction Science & Clinical Practice, 19(1), 14.

    37. Sales, C. M. D., Ashworth, M., Ayis, S., et al. (2023). I-PROMs position paper. Journal

    of Clinical Psychology, 79(3), 596–621.

    38. She, Z., Xu, H., Cormier, G., Drapeau, M., & Duncan, B. L. (2024). Culture and face in

    ROM. Psychotherapy Research, 34(3), 311–322.

    39. Smits, H. J. H., Seelen-de Lang, B. L., Penterman, E. J. M., Nijman, H. L. I., &

    Noorthoorn, E. O. (2023). Quality of life outcomes in SMI. Journal of Applied Research

    in Intellectual Disabilities, 36(1), 58–67.

    40. Solstad, S. M., Kleiven, G. S., Castonguay, L. G., & Moltu, C. (2021). Clinical dilemmas

    of ROM. Psychotherapy Research, 31(2), 200–210.

    41. Solstad, S. M., Kleiven, G. S., & Moltu, C. (2021). Complexity of clinical feedback.

    Quality of Life Research, 30(11), 3117–3125.

    42. Timman, R., & Arrindell, W. A. (2022). SCL-3/7 for ROM. Acta Psychiatrica

    Scandinavica, 145(4), 397–411.

    43. Valdiviezo-Oña, J., Montesano, A., Evans, C., & Paz, C. (2023). Practice-based evidence

    via ROM. BMJ Open, 13, e071875.

    44. Van Wert, M. J., Malik, M., Memel, B., Moore, R., Buccino, D., Hackerman, F., Kumari,

    S., Everett, A., & Narrow, W. (2021). Barriers to ROM integration. Journal of Evaluation

    in Clinical Practice, 27(4), 767–775.

    45. van Sonsbeek, M. A. M. S., Hutschemaekers, G. J. M., Veerman, J. W., Vermulst, A., &

    Tiemens, B. G. (2023). Clinician-focused MBC strategies. BMC Health Services

    Research, 23(1), 326.

    46. van Sonsbeek, M. A. M. S., Hutschemaekers, G. J. M., Veerman, J. W., Vermulst, A.,

    Kleinjan, M., & Tiemens, B. G. (2021). ROM feedback challenges. Child & Youth Care

    Forum, 50(2), 307–332.

    47. Victor, S. E., Salk, R. H., Porta, G., et al. (2023). Measurement-based care for suicidal

    youth. PLOS One, 18(4), e0284073.

    48. Wiebe, D. E., Remers, S., Nippak, P., & Meyer, J. (2021). Online ROM system

    evaluation. JMIR Mental Health, 8(12), e29243.

    49. Williams, N. J., Ehrhart, M. G., Aarons, G. A., et al. (2024). Organizational climate and

    MBC. Implementation Science, 19(1), 29.

    50. Woodard, G. S., Lane, E., Ehrenreich-May, J., Ginsburg, G. S., & Jensen-Doss, A.

    (2025). Predictors of MBC fidelity. Journal of Clinical Child & Adolescent Psychology,

    54(3), 346–357.

    51. Zavaglia, E., Joober, R., Iyer, S. N., et al. (2025). Digital MBC in early psychosis.

    Schizophrenia Research, 282, 141–149.

    52. Zhou, J., Wang, X., Yang, J., Zhu, X., Xiao, L., Feng, L., & Wang, G. (2022).

    Optimization of MBC for depression. Trials, 23(1), 367.

    53. Progovac, A. M., Fulwiler, C., Lanca, M., Wang, D., Zona, K., Mulvaney-Day, N., Aldis,

    R., Leff, H. S., Wang, P., & Rosenfeld, L. C. (2025). Provider experiences with RMBC

    rollout. JMIR Formative Research, 9, e71570.

    54. Rush, A. J., Trivedi, M. H., Wisniewski, S. R., et al. (2006). Acute and longer-term

    outcomes in STAR*D. American Journal of Psychiatry, 163(11), 1905–1917.

    55. Zimmerman, M., McGlinchey, J. B., Posternak, M. A., Friedman, M., Boerescu, D., &

    Attiullah, N. (2008). How should remission be defined using the PHQ-9? Journal of

    Clinical Psychiatry, 69(12), 1856–1861.

    56. Kroenke, K., Spitzer, R. L., & Williams, J. B. W. (2001). The PHQ-9. Journal of General

    Internal Medicine, 16(9), 606–613.

    57. Spitzer, R. L., Kroenke, K., Williams, J. B. W., & Löwe, B. (2006). The GAD-7.

    Archives of Internal Medicine, 166(10), 1092–1097.

    58. Fortney, J. C., Unützer, J., Wrenn, G., Pyne, J. M., Smith, G. R., Schoenbaum, M., &

    Harbin, H. T. (2017). A tipping point for MBC. Psychiatric Services, 68(2), 179–188.

    59. Lewis, C. C., Fischer, S., Weiner, B. J., Stanick, C., Kim, M., & Martinez, R. G. (2015).

    Outcomes for implementation science. Implementation Science, 10, 1–13.

    60. Zimmerman, M., & Mattia, J. I. (2001). Psychiatric diagnosis in clinical practice.

    American Journal of Psychiatry, 158(4), 589–595.

    **LiteratureReview.docx**

    This file is too large to display. [View in new window](https://www.sweetstudy.com/files/literaturereview-docx-10504709)

    **LiteratureReview.docx**

    This file is too large to display. [View in new window](https://www.sweetstudy.com/files/literaturereview-docx-10504709)

    **## Articles.pdf**

    References

    1. Aboraya, A., Elswick, D., Berry, J., Chandran, D., Hill, C., Zheng, W., Hustead, J. D.,

    Van Oppen, D., Patel, V., Berzingi, S., Wang, K., Grimes, D., Gallucci, G., Mishra, D.,

    Shrestha, R., Justice, J., Chumber, P., Rizvi, A., Yadava, D., … Hyacinthe, J. (2025).

    Measurement-based care training curriculum in psychiatry residency programs: Four-year

    implementation experience and future directions. Innovations in Clinical Neuroscience,

    22(4–6), 20–26.

    2. Aldis, R., Rosenfeld, L. C., Mulvaney-Day, N., Lanca, M., Zona, K., Lam, J. A., Asfour,

    J., Meltzer, J. C., Leff, H. S., Fulwiler, C., Wang, P., & Progovac, A. M. (2024).

    Determinants of remote measurement-based care uptake in a safety-net outpatient

    psychiatry department. Learning Health Systems, 8(S1), e10416.

    3. Askari, N., Gupta, R., Hussain-Shamsy, N., Barker, L. C., Champagne, T., Lam, R. W.,

    Bishop, K., Pirmohamed, J., Michalowska, M., Shah, V., Katzman, H., Jalan, A.,

    Shanmuganathan, A., Wang, V., & Vigod, S. N. (2025). Electronic measurement-based

    care for perinatal depression and anxiety. BMC Psychiatry, 25(1), 437.

    4. Azizian Kia, S., Wittkampf, L., van Lankeren, J., & Janse, P. (2025). Motives of

    therapists for using routine outcome monitoring. Administration and Policy in Mental

    Health, 52(1), 159–170.

    5. Barkham, M., Broglia, E., & The SCORE Consortium. (2024). Routine outcome

    monitoring and feedback in university mental health services. Counselling and

    Psychotherapy Research, 24(2), 459–471.

    6. Bear, H. A., Dalzell, K., Edbrooke-Childs, J., & Wolpert, M. (2022). Applying behaviour

    change theory to routine outcome monitoring. British Journal of Clinical Psychology,

    61(3), 557–578.

    7. Borgnolo, L. J., McKenna, S., Hickie, I. B., Varidel, M., Turner, A., Gorban, C.,

    LaMonica, H. M., Chong, M. K., Capon, W., Dimitropoulos, G., Battisti, R., Whitwell,

    B., Hamilton, B., Scott, E. M., & Iorfino, F. (2025). Engagement with digital mental

    health technology. Journal of Medical Internet Research, 27(3), e67597.

    8. Bugatti, M., Owen, J., Richardson, Z., Rasmussen, W., & Newton, D. (2024). Therapist

    engagement in measurement-based care. Clinical Psychology & Psychotherapy, 31(1).

    9. Cheung, B. S., Murphy, J. K., Michalak, E. E., Liu, J., Yang, X., Wang, X., Chen, J., &

    Lam, R. W. (2023). Barriers to technology-enhanced MBC for depression. Journal of

    Affective Disorders, 320, 1–6.

    10. Cuperfain, A. B., Hui, K., Berkhout, S. G., Foussias, G., Gratzer, D., Kidd, S. A.,

    Kozloff, N., Kurdyak, P., Linaksita, B., Miranda, D., Soklaridis, S., Voineskos, A. N., &

    Zaheer, J. (2021). Views of measurement-based care in early psychosis. BJPsych Open,

    7(5).

    11. de Beurs, E., Carlier, I., & van Hemert, A. (2022). Patient-reported psychopathology and

    quality of life. Quality of Life Research, 31(5), 1461–1471.

    12. El Hussein, M. T., & Bal, R. (2025). Pharmacotherapy for major depressive disorder.

    Journal for Nurse Practitioners, 21(8), 105458.

    13. Gaine, G. S., Nealis, L. J., Zhou, H., Purdon, S. E., & Abba-Aji, A. (2021). Inpatient

    recovery trajectories using ROM. Psychiatry Research, 302, 114000.

    14. Halford, W. K., & Frost, A. D. J. (2021). Depression Anxiety Stress Scale-10. Behaviour

    Change, 38(4), 221–234.

    15. He, Y., Wang, X., Wang, Z., Zhang, P., Huang, X., Yu, M., Murphy, J., Michalak, E.,

    Liu, J., Yang, T., Yang, X., Fang, Y., Lam, R., & Chen, J. (2024). Standard vs enhanced

    MBC for depression. Neuropsychiatric Disease and Treatment, 20, 1465–1473.

    16. Helldin, L., Mohn, C., Olsson-Tall, M., van Dijk-Härd, I., & Olsson, A. (2024).

    Measurement-based care in schizophrenia. Archives of Psychiatric Nursing, 53, 151–157.

    17. Hoenders, R., Bartels, A., Castelein, S., Visser, E., & Booij, S. (2021). Integrative

    outpatient mental health clinic outcomes. European Psychiatry, 64(S1).

    18. Huffman, L. G., Lawrence-Sidebottom, D., Huberty, J., Roots, M., Roots, K., Parikh, A.,

    Guerra, R., & Weiser, J. (2023). Digital MBC for youth anxiety and depression. JMIR

    Pediatrics and Parenting, 6, e46154.

    19. Ibrahim, H. M., & Jha, M. K. (2023). Measurement-based care for depression.

    Psychiatric Annals, 53(9), 395–399.

    20. Jonášová, K., Čevelíček, M., Doležal, P., & Řiháček, T. (2025). In-session use of ROM.

    Administration and Policy in Mental Health, 52(1), 106–122.

    21. Jones, S. B., Ko, H., Gatto, A. J., Kablinger, A. S., Sharp, H. D., Cooper, L. D., Tenzer,

    M. M., O’Brien, V. C., & McNamara, R. S. (2024). COVID-19 impacts using MBC.

    Journal of Patient-Reported Outcomes, 8(1), 135.

    22. Khau, M., Tabbane, K., Bloom, D., Abadi, S., Villemus, C., Rabinovitch, M., Shah, J. L.,

    Veillette, A., Iyer, S. N., Boksa, P., & Joober, R. (2022). MBC in first-episode psychosis.

    Journal of Psychiatric Research, 150, 8–16.

    23. Korsen, N., & Gerrish, S. (2022). PHQ-9 use in integrated care. Annals of Family

    Medicine, 20(Suppl 1).

    24. Kumar, M., Paz, C., Falkeström, F., & Castonguay, L. (2025). Strengthening systems

    with ROM. JAMA Psychiatry, 82(10), 953–954.

    25. Lam, R. W., Michalak, E. E., Murphy, J. K., et al. (2025). EMBED trial protocol. Cureus,

    17(8), e90395.

    26. Lampis, J., & Rocca, G. (2024). ROM use in Italian public services. Clinical Psychology

    & Psychotherapy, 31(6).

    27. Lewis, C. C., Boyd, M. R., Marti, C. N., & Albright, K. (2022). Mediators of MBC

    implementation. Implementation Science, 17(1).

    28. Lui, J. H. L., Brookman-Frazee, L., Smith, A., Lind, T., Terrones, L., Rodriguez, A.,

    Motamedi, M., Villodas, M., & Lau, A. S. (2022). Implementation facilitation strategies.

    Psychological Services, 19(2), 343–352.

    29. Machleid, F., Michnevich, T., Huang, L., Schröder-Frerkes, L., Wiegmann, C., Muffel,

    T., & Kaminski, J. (2024). Remote measurement-based care. PLOS One, 19(2),

    e0297929.

    30. McCoy, T. H., Castro, V. M., & Perlis, R. H. (2025). Estimating depression severity with

    LLMs. Journal of Affective Disorders, 381, 270–274.

    31. Meyer-Kalos, P., Owens, G., Fisher, M., et al. (2024). Putting MBC into action. BMC

    Psychiatry, 24(1), 871.

    32. Moltu, C., McAleavey, A. A., Helleseth, M. M., Møller, G. H., & Nordberg, S. S. (2021).

    Developing feedback systems. International Journal of Mental Health Systems, 15(1), 43.

    33. Patel, Z. S., Jensen-Doss, A., & Lewis, C. C. (2022). Attitudes toward MBC.

    Administration and Policy in Mental Health, 49(1), 13–28.

    34. Progovac, A. M., Fulwiler, C., Lanca, M., et al. (2025). Remote MBC rollout

    experiences. JMIR Formative Research, 9, e71570.

    35. Roebroek, L., Bruins, J., Roe, D., et al. (2021). Care needs in psychosis. Epidemiology

    and Psychiatric Sciences, 30.

    36. Rush, A. J., Gore-Langton, R. E., Bart, G., et al. (2024). Tools to implement MBC for

    OUD. Addiction Science & Clinical Practice, 19(1), 14.

    37. Sales, C. M. D., Ashworth, M., Ayis, S., et al. (2023). I-PROMs position paper. Journal

    of Clinical Psychology, 79(3), 596–621.

    38. She, Z., Xu, H., Cormier, G., Drapeau, M., & Duncan, B. L. (2024). Culture and face in

    ROM. Psychotherapy Research, 34(3), 311–322.

    39. Smits, H. J. H., Seelen-de Lang, B. L., Penterman, E. J. M., Nijman, H. L. I., &

    Noorthoorn, E. O. (2023). Quality of life outcomes in SMI. Journal of Applied Research

    in Intellectual Disabilities, 36(1), 58–67.

    40. Solstad, S. M., Kleiven, G. S., Castonguay, L. G., & Moltu, C. (2021). Clinical dilemmas

    of ROM. Psychotherapy Research, 31(2), 200–210.

    41. Solstad, S. M., Kleiven, G. S., & Moltu, C. (2021). Complexity of clinical feedback.

    Quality of Life Research, 30(11), 3117–3125.

    42. Timman, R., & Arrindell, W. A. (2022). SCL-3/7 for ROM. Acta Psychiatrica

    Scandinavica, 145(4), 397–411.

    43. Valdiviezo-Oña, J., Montesano, A., Evans, C., & Paz, C. (2023). Practice-based evidence

    via ROM. BMJ Open, 13, e071875.

    44. Van Wert, M. J., Malik, M., Memel, B., Moore, R., Buccino, D., Hackerman, F., Kumari,

    S., Everett, A., & Narrow, W. (2021). Barriers to ROM integration. Journal of Evaluation

    in Clinical Practice, 27(4), 767–775.

    45. van Sonsbeek, M. A. M. S., Hutschemaekers, G. J. M., Veerman, J. W., Vermulst, A., &

    Tiemens, B. G. (2023). Clinician-focused MBC strategies. BMC Health Services

    Research, 23(1), 326.

    46. van Sonsbeek, M. A. M. S., Hutschemaekers, G. J. M., Veerman, J. W., Vermulst, A.,

    Kleinjan, M., & Tiemens, B. G. (2021). ROM feedback challenges. Child & Youth Care

    Forum, 50(2), 307–332.

    47. Victor, S. E., Salk, R. H., Porta, G., et al. (2023). Measurement-based care for suicidal

    youth. PLOS One, 18(4), e0284073.

    48. Wiebe, D. E., Remers, S., Nippak, P., & Meyer, J. (2021). Online ROM system

    evaluation. JMIR Mental Health, 8(12), e29243.

    49. Williams, N. J., Ehrhart, M. G., Aarons, G. A., et al. (2024). Organizational climate and

    MBC. Implementation Science, 19(1), 29.

    50. Woodard, G. S., Lane, E., Ehrenreich-May, J., Ginsburg, G. S., & Jensen-Doss, A.

    (2025). Predictors of MBC fidelity. Journal of Clinical Child & Adolescent Psychology,

    54(3), 346–357.

    51. Zavaglia, E., Joober, R., Iyer, S. N., et al. (2025). Digital MBC in early psychosis.

    Schizophrenia Research, 282, 141–149.

    52. Zhou, J., Wang, X., Yang, J., Zhu, X., Xiao, L., Feng, L., & Wang, G. (2022).

    Optimization of MBC for depression. Trials, 23(1), 367.

    53. Progovac, A. M., Fulwiler, C., Lanca, M., Wang, D., Zona, K., Mulvaney-Day, N., Aldis,

    R., Leff, H. S., Wang, P., & Rosenfeld, L. C. (2025). Provider experiences with RMBC

    rollout. JMIR Formative Research, 9, e71570.

    54. Rush, A. J., Trivedi, M. H., Wisniewski, S. R., et al. (2006). Acute and longer-term

    outcomes in STAR*D. American Journal of Psychiatry, 163(11), 1905–1917.

    55. Zimmerman, M., McGlinchey, J. B., Posternak, M. A., Friedman, M., Boerescu, D., &

    Attiullah, N. (2008). How should remission be defined using the PHQ-9? Journal of

    Clinical Psychiatry, 69(12), 1856–1861.

    56. Kroenke, K., Spitzer, R. L., & Williams, J. B. W. (2001). The PHQ-9. Journal of General

    Internal Medicine, 16(9), 606–613.

    57. Spitzer, R. L., Kroenke, K., Williams, J. B. W., & Löwe, B. (2006). The GAD-7.

    Archives of Internal Medicine, 166(10), 1092–1097.

    58. Fortney, J. C., Unützer, J., Wrenn, G., Pyne, J. M., Smith, G. R., Schoenbaum, M., &

    Harbin, H. T. (2017). A tipping point for MBC. Psychiatric Services, 68(2), 179–188.

    59. Lewis, C. C., Fischer, S., Weiner, B. J., Stanick, C., Kim, M., & Martinez, R. G. (2015).

    Outcomes for implementation science. Implementation Science, 10, 1–13.

    60. Zimmerman, M., & Mattia, J. I. (2001). Psychiatric diagnosis in clinical practice.

    American Journal of Psychiatry, 158(4), 589–595.

    **LiteratureReview.docx**

    This file is too large to display. [View in new window](https://www.sweetstudy.com/files/literaturereview-docx-10504709)

    **## Articles.pdf**

    References

    1. Aboraya, A., Elswick, D., Berry, J., Chandran, D., Hill, C., Zheng, W., Hustead, J. D.,

    Van Oppen, D., Patel, V., Berzingi, S., Wang, K., Grimes, D., Gallucci, G., Mishra, D.,

    Shrestha, R., Justice, J., Chumber, P., Rizvi, A., Yadava, D., … Hyacinthe, J. (2025).

    Measurement-based care training curriculum in psychiatry residency programs: Four-year

    implementation experience and future directions. Innovations in Clinical Neuroscience,

    22(4–6), 20–26.

    2. Aldis, R., Rosenfeld, L. C., Mulvaney-Day, N., Lanca, M., Zona, K., Lam, J. A., Asfour,

    J., Meltzer, J. C., Leff, H. S., Fulwiler, C., Wang, P., & Progovac, A. M. (2024).

    Determinants of remote measurement-based care uptake in a safety-net outpatient

    psychiatry department. Learning Health Systems, 8(S1), e10416.

    3. Askari, N., Gupta, R., Hussain-Shamsy, N., Barker, L. C., Champagne, T., Lam, R. W.,

    Bishop, K., Pirmohamed, J., Michalowska, M., Shah, V., Katzman, H., Jalan, A.,

    Shanmuganathan, A., Wang, V., & Vigod, S. N. (2025). Electronic measurement-based

    care for perinatal depression and anxiety. BMC Psychiatry, 25(1), 437.

    4. Azizian Kia, S., Wittkampf, L., van Lankeren, J., & Janse, P. (2025). Motives of

    therapists for using routine outcome monitoring. Administration and Policy in Mental

    Health, 52(1), 159–170.

    5. Barkham, M., Broglia, E., & The SCORE Consortium. (2024). Routine outcome

    monitoring and feedback in university mental health services. Counselling and

    Psychotherapy Research, 24(2), 459–471.

    6. Bear, H. A., Dalzell, K., Edbrooke-Childs, J., & Wolpert, M. (2022). Applying behaviour

    change theory to routine outcome monitoring. British Journal of Clinical Psychology,

    61(3), 557–578.

    7. Borgnolo, L. J., McKenna, S., Hickie, I. B., Varidel, M., Turner, A., Gorban, C.,

    LaMonica, H. M., Chong, M. K., Capon, W., Dimitropoulos, G., Battisti, R., Whitwell,

    B., Hamilton, B., Scott, E. M., & Iorfino, F. (2025). Engagement with digital mental

    health technology. Journal of Medical Internet Research, 27(3), e67597.

    8. Bugatti, M., Owen, J., Richardson, Z., Rasmussen, W., & Newton, D. (2024). Therapist

    engagement in measurement-based care. Clinical Psychology & Psychotherapy, 31(1).

    9. Cheung, B. S., Murphy, J. K., Michalak, E. E., Liu, J., Yang, X., Wang, X., Chen, J., &

    Lam, R. W. (2023). Barriers to technology-enhanced MBC for depression. Journal of

    Affective Disorders, 320, 1–6.

    10. Cuperfain, A. B., Hui, K., Berkhout, S. G., Foussias, G., Gratzer, D., Kidd, S. A.,

    Kozloff, N., Kurdyak, P., Linaksita, B., Miranda, D., Soklaridis, S., Voineskos, A. N., &

    Zaheer, J. (2021). Views of measurement-based care in early psychosis. BJPsych Open,

    7(5).

    11. de Beurs, E., Carlier, I., & van Hemert, A. (2022). Patient-reported psychopathology and

    quality of life. Quality of Life Research, 31(5), 1461–1471.

    12. El Hussein, M. T., & Bal, R. (2025). Pharmacotherapy for major depressive disorder.

    Journal for Nurse Practitioners, 21(8), 105458.

    13. Gaine, G. S., Nealis, L. J., Zhou, H., Purdon, S. E., & Abba-Aji, A. (2021). Inpatient

    recovery trajectories using ROM. Psychiatry Research, 302, 114000.

    14. Halford, W. K., & Frost, A. D. J. (2021). Depression Anxiety Stress Scale-10. Behaviour

    Change, 38(4), 221–234.

    15. He, Y., Wang, X., Wang, Z., Zhang, P., Huang, X., Yu, M., Murphy, J., Michalak, E.,

    Liu, J., Yang, T., Yang, X., Fang, Y., Lam, R., & Chen, J. (2024). Standard vs enhanced

    MBC for depression. Neuropsychiatric Disease and Treatment, 20, 1465–1473.

    16. Helldin, L., Mohn, C., Olsson-Tall, M., van Dijk-Härd, I., & Olsson, A. (2024).

    Measurement-based care in schizophrenia. Archives of Psychiatric Nursing, 53, 151–157.

    17. Hoenders, R., Bartels, A., Castelein, S., Visser, E., & Booij, S. (2021). Integrative

    outpatient mental health clinic outcomes. European Psychiatry, 64(S1).

    18. Huffman, L. G., Lawrence-Sidebottom, D., Huberty, J., Roots, M., Roots, K., Parikh, A.,

    Guerra, R., & Weiser, J. (2023). Digital MBC for youth anxiety and depression. JMIR

    Pediatrics and Parenting, 6, e46154.

    19. Ibrahim, H. M., & Jha, M. K. (2023). Measurement-based care for depression.

    Psychiatric Annals, 53(9), 395–399.

    20. Jonášová, K., Čevelíček, M., Doležal, P., & Řiháček, T. (2025). In-session use of ROM.

    Administration and Policy in Mental Health, 52(1), 106–122.

    21. Jones, S. B., Ko, H., Gatto, A. J., Kablinger, A. S., Sharp, H. D., Cooper, L. D., Tenzer,

    M. M., O’Brien, V. C., & McNamara, R. S. (2024). COVID-19 impacts using MBC.

    Journal of Patient-Reported Outcomes, 8(1), 135.

    22. Khau, M., Tabbane, K., Bloom, D., Abadi, S., Villemus, C., Rabinovitch, M., Shah, J. L.,

    Veillette, A., Iyer, S. N., Boksa, P., & Joober, R. (2022). MBC in first-episode psychosis.

    Journal of Psychiatric Research, 150, 8–16.

    23. Korsen, N., & Gerrish, S. (2022). PHQ-9 use in integrated care. Annals of Family

    Medicine, 20(Suppl 1).

    24. Kumar, M., Paz, C., Falkeström, F., & Castonguay, L. (2025). Strengthening systems

    with ROM. JAMA Psychiatry, 82(10), 953–954.

    25. Lam, R. W., Michalak, E. E., Murphy, J. K., et al. (2025). EMBED trial protocol. Cureus,

    17(8), e90395.

    26. Lampis, J., & Rocca, G. (2024). ROM use in Italian public services. Clinical Psychology

    & Psychotherapy, 31(6).

    27. Lewis, C. C., Boyd, M. R., Marti, C. N., & Albright, K. (2022). Mediators of MBC

    implementation. Implementation Science, 17(1).

    28. Lui, J. H. L., Brookman-Frazee, L., Smith, A., Lind, T., Terrones, L., Rodriguez, A.,

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    Can someone please help me complete this **files (1)** – ## Week7Instructions.docx **## Week7Instructions.docx** Instructions Week 7: Post Modern Therapies a Discuss solution-focused brief therapy. Describe key concepts and specific interventions including the use of the miracle question. b. Discuss…

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    **files (1)**

    – ## Week7Instructions.docx

    **## Week7Instructions.docx**

    Instructions

    Week 7: Post Modern Therapies

    a Discuss solution-focused brief therapy. Describe key concepts and specific interventions including the use of the miracle question.

    b. Discuss narrative therapy. Describe key concepts and specific interventions.

    c. Discuss strengths and limitations of SFBT and Narrative therapy.

    Resources

    [https://www.psychologytoday.com/us/therapy-types/narrative-therapy](https://www.psychologytoday.com/us/therapy-types/narrative-therapy)

    [https://www.cambridge.org/core/journals/advances-in-psychiatric-treatment/article/solutionfocused-brief-therapy/B8198B18DDEE77F9D39A09FDBCC0CE15](https://www.cambridge.org/core/journals/advances-in-psychiatric-treatment/article/solutionfocused-brief-therapy/B8198B18DDEE77F9D39A09FDBCC0CE15)

    [https://positivepsychology.com/miracle-question/](https://positivepsychology.com/miracle-question/)

    [https://thriveworks.com/blog/externalizing-problem-counseling-technique-narrative-therapy/](https://thriveworks.com/blog/externalizing-problem-counseling-technique-narrative-therapy/)

    **## Week7Instructions.docx**

    Instructions

    Week 7: Post Modern Therapies

    a Discuss solution-focused brief therapy. Describe key concepts and specific interventions including the use of the miracle question.

    b. Discuss narrative therapy. Describe key concepts and specific interventions.

    c. Discuss strengths and limitations of SFBT and Narrative therapy.

    Resources

    [https://www.psychologytoday.com/us/therapy-types/narrative-therapy](https://www.psychologytoday.com/us/therapy-types/narrative-therapy)

    [https://www.cambridge.org/core/journals/advances-in-psychiatric-treatment/article/solutionfocused-brief-therapy/B8198B18DDEE77F9D39A09FDBCC0CE15](https://www.cambridge.org/core/journals/advances-in-psychiatric-treatment/article/solutionfocused-brief-therapy/B8198B18DDEE77F9D39A09FDBCC0CE15)

    [https://positivepsychology.com/miracle-question/](https://positivepsychology.com/miracle-question/)

    [https://thriveworks.com/blog/externalizing-problem-counseling-technique-narrative-therapy/](https://thriveworks.com/blog/externalizing-problem-counseling-technique-narrative-therapy/)

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    **Please attach either of these reports:** **Do attach:** _**Clifton Strengths Top 5 Report**_ _**Do not attach the**_ _**Emotional Intelligence Appraisal**_ _**report to this discussion.**_ _**Please submit your prepared discussion to the assignment for Turnitin review**_ _**prior**_ _**to copy and…

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    **Please attach either of these reports:**

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    _**Please submit your prepared discussion to the assignment for Turnitin review**_ _**prior**_ _**to copy and pasting the assignment in the discussion area.**_

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    Please place your discussion post in the text box for this assignment.  Use a copy and paste of the document submitted in Step One for the Turnitin review.  We understand that the discussion assignment will sometimes experience format challenges associated with the placement of content in the text box;  please do not waste hours trying to resolve format concerns in the text box. The faculty can use your pdf file submitted in the Step One part of this assignment to confirm if the hanging indent, etc. was correct when you did the copy and paste.

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