Crafting Dissertation Problem Statements that Get Approved
Last week I was reviewing a dissertation proposal that had been rejected three times by the student’s committee. Three
times. The student was frustrated and confused because she’d revised everything her chair asked for, but it kept getting
sent back. I read the problem statement and immediately saw why. It was vague. Really vague. “There is a problem with
teacher retention in urban schools. Many teachers leave the profession within their first five years. This study will
examine factors affecting teacher retention.” That’s not a problem statement. That’s three sentences that kind of
gesture toward a problem without actually defining anything specific enough to build a study on. What’s missing? Almost
everything. There’s no theoretical framework mentioned. No specific population beyond “urban schools.” No indication of
what unit of analysis we’re studying (individual teachers? Schools? Districts?). No sampling frame. No hint about
research design. Nothing. Her committee kept rejecting it because you can’t design a study based on that problem
statement. You can’t tell what she’s actually proposing to research. This is why knowing what to include in a
dissertation problem statement matters. Your problem statement isn’t just window dressing that precedes the “real” parts
of your proposal. It’s the foundation that tells your committee exactly what you’re studying, who you’re studying, and
how you’ll study them. Let me show you exactly what needs to be in your problem statement so your committee approves it
the first time.
Before we get into what to include, let’s talk about why incomplete problem statements are such a common problem. Your dissertation committee is trying to evaluate whether your proposed study is feasible, original, and methodologically sound. They can’t do that if your problem statement doesn’t give them enough information. When your problem statement is too vague, here’s what happens: Your committee can’t tell if your study is feasible. If you don’t specify your population and sampling frame, they can’t assess whether you’ll actually be able to recruit participants. “Teachers” is too broad. “First-year elementary teachers in Title I schools in Chicago” is specific enough to evaluate feasibility. Your committee can’t tell if your study is original. If you don’t mention your theoretical framework or unit of analysis, they can’t determine whether this exact study has been done before. Hundreds of studies have examined “teacher retention.” Far fewer have examined “how novice teachers in under-resourced schools conceptualize professional identity formation using identity theory.” Your committee can’t tell if your methodology makes sense. If your problem statement doesn’t indicate your research design, they can’t evaluate whether your approach matches your questions. Are you doing qualitative interviews? Quantitative surveys? Case studies? Your problem statement should make this clear. Your committee has to ask for clarification. And that means rejecting your proposal and asking you to revise. Multiple times, usually, because each revision only addresses some of the missing information. This is why students get stuck in revision cycles. They’re trying to add information piece by piece in response to committee feedback, when what they really need is a complete problem statement from the beginning that includes all the key elements. Let me show you what those elements are.
Whether you’re writing a socioeconomic problem statement or a knowledge-gap problem statement, there are four core elements that must be present. Let’s go through each one.
Your problem statement should mention the theoretical lens through which you’re examining your problem. This doesn’t mean you need a lengthy explanation of the theory—that comes in Chapter 2. But you need to name the theory and show how it relates to your problem. Why this matters: Theory guides how you understand and interpret your problem. Different theories lead to different research questions and different methodological approaches. Your committee needs to know which theoretical perspective you’re taking. For socioeconomic problem statements: Even though you’re focused on a practical problem, you still need theory. You might write something like: “Drawing on Conservation of Resources Theory (Hobfoll, 1989), which explains stress as resulting from threatened or actual loss of valued resources, this study examines how emergency department nurses experience resource depletion in high-trauma environments.” You’ve named the theory (Conservation of Resources) and connected it to your problem (resource depletion causing nurse stress). For knowledge-gap problem statements: Theory is even more explicitly central. You might write: “While resilience theory has been applied extensively to pediatric nursing contexts (Smith, 2022), its applicability to adult trauma nursing remains underexplored. This study extends resilience theory by examining how trauma nurses develop psychological hardiness in repeatedly traumatic situations.” You’ve named the theory (resilience theory), shown where it’s been used, and indicated how your study extends it. Common mistake: Students often mention theory in their literature review but not in their problem statement. Your problem statement needs to establish upfront that you’re working from a theoretical foundation.
Your unit of analysis is what or who you’re actually studying. This sounds simple but students mess it up constantly. Common units of analysis:
Your population is the broader group from which you’ll draw your sample. It defines the general boundaries of who or what you’re studying. Why this matters: Your committee needs to understand the scope and context of your study. “Nurses” is too broad. “Emergency department nurses in urban teaching hospitals” is specific enough to evaluate. How to be specific about population: Include relevant characteristics that define your population: Geographic boundaries:
Your sampling frame is the specific group from which you’ll actually recruit participants. This is narrower than your population—it’s the accessible subset of the population you can realistically study. Why this matters: This is about feasibility. Your committee needs to know that you can actually access the people or data you plan to study. Vague statements about studying “teachers nationwide” raise red flags because that’s not feasible for a dissertation. How to specify your sampling frame: Be concrete about where you’ll recruit participants: “This study will recruit participants from emergency departments in three urban teaching hospitals in Chicago with which the researcher has established partnerships.” This tells your committee:
If you’re writing a knowledge-gap problem statement (typical for PhD programs), you need two additional elements beyond the four core elements.
Knowledge-gap problem statements should indicate what type of sampling you’ll use. This helps your committee understand your methodological approach. Common sampling techniques: For qualitative research:
Your problem statement should give clear hints about your research design—qualitative, quantitative, or mixed methods. You don’t need to say explicitly “this will be a qualitative phenomenological study” in the problem statement, but the language you use should make it obvious. Language indicating qualitative design: Words like “explore,” “understand,” “describe,” “lived experiences,” “perceptions,” “meanings,” “process,” “how participants make sense of” all signal qualitative research. “It is not known how emergency nurses experience and describe the process of developing resilience in trauma care environments.” The words “experience,” “describe,” and “process” tell your committee this is qualitative. Language indicating quantitative design: Words like “relationship between,” “extent to which,” “predict,” “correlate,” “compare,” “measure,” “effect” signal quantitative research. “The relationship between organizational support factors and nurse retention rates in urban trauma centers remains unexamined.” The words “relationship between” and “rates” tell your committee this is quantitative. Language indicating mixed methods: If you’re using mixed methods, your problem statement might indicate both kinds of language or explicitly mention multiple phases. “While quantitative research has identified factors correlated with teacher retention, qualitative understanding of how teachers experience these factors in their retention decisions is lacking.” This signals you’ll use both approaches—quantitative to examine correlations and qualitative to understand experiences.
Let me show you a complete problem statement with all elements labeled so you can see how they work together. Example Problem Statement (Knowledge-Gap Type for PhD in Nursing): While [substantial research] has examined factors contributing to nurse burnout in hospital settings (Smith, 2022; Johnson, 2023), limited understanding exists regarding how [Element #2: Unit of Analysis – individual nurses] emergency department nurses in [Element #3: Population – urban Level I trauma centers] develop and sustain psychological resilience. Existing research on [Element #1: Theoretical Framework – resilience theory] has focused primarily on pediatric and oncology nursing contexts (Brown, 2023), with trauma nursing receiving minimal scholarly attention. Most resilience studies have employed quantitative approaches [Element #6: Research Design Indicator – signaling this will be qualitative], measuring resilience as an outcome variable rather than examining the lived experiences through which nurses build resilience capabilities. It is not known how [Element #2: Unit of Analysis reinforced] trauma nurses [Element #4: Sampling Frame begins] in three urban trauma centers in the Midwest [Element #4: Sampling Frame – specific sites and region] describe their experiences of developing and maintaining resilience amid repeated exposure to traumatic patient situations. Using [Element #5: Sampling Technique] purposive sampling to identify nurses with at least two years of trauma care experience, this phenomenological study will explore these lived experiences. Every element is present:
Now let me tell you about the mistakes I see constantly in problem statements so you can avoid them.
Students often mention a theory but don’t explain how it relates to their problem. They’ll write something like: “Using Social Learning Theory, this study examines teacher retention.” Okay, but how does Social Learning Theory relate to teacher retention? What’s the connection? You can’t just name-drop a theory. Better version: “Drawing on Social Learning Theory’s emphasis on observational learning and modeling (Bandura, 1977), this study examines how novice teachers’ observations of veteran colleagues’ coping strategies influence their own retention decisions.” Now we see why Social Learning Theory is relevant—because the study focuses on how teachers learn from observing others.
Students write “this study will examine nurses” or “this study will survey teachers” without specifying which nurses or which teachers. This forces your committee to ask: What kind of nurses? Where? How many years of experience? What settings? These aren’t optional details—they’re required elements of a problem statement.
Students write problem statements that could describe either qualitative or quantitative research. They use neutral language that doesn’t signal their methodological approach. “This study will investigate factors affecting nurse retention.” Is this qualitative (interviewing nurses about their experiences) or quantitative (surveying nurses and doing statistical analysis)? Your committee can’t tell. Your problem statement language should make your research approach obvious without having to state it explicitly.
On the flip side, some students try to cram their entire methodology into the problem statement. They write three paragraphs explaining their exact data collection procedures, their specific research questions, their analytical approach, etc. The problem statement should include key elements that frame your study, but it shouldn’t be a complete methodology section. Save the details for Chapter 3. Rule of thumb: Your problem statement should be 250-400 words typically. If it’s longer than 500 words, you’re probably including too much detail.
Students sometimes start with one focus and end with another. They’ll begin talking about organizational problems and end talking about individual experiences. Or they’ll talk about a practical problem and then shift to describing knowledge gaps. Pick your type (socioeconomic or knowledge-gap) and your focus (individual, organizational, etc.) and stay consistent throughout.
Let me explain why each element matters from your committee’s perspective. Understanding what they’re looking for helps you include what they need. Theoretical framework: Your committee checks whether you understand relevant theory and whether you’re using theory appropriately to frame your study. If your theory doesn’t match your problem, they’ll question your theoretical foundation. Unit of analysis: Your committee checks whether your research questions, methodology, and analysis plan align with your unit of analysis. Misalignment here is a red flag for methodological problems. Population: Your committee assesses whether your population is specific enough to make your study meaningful. Too broad and you can’t say anything conclusive. Too narrow and your findings won’t matter to anyone. Sampling frame: Your committee evaluates feasibility. Can you actually access this population? How will you recruit them? Is your timeline realistic given your sampling frame? Sampling technique (for knowledge-gap statements): Your committee checks whether your sampling approach matches your research design and will yield appropriate data for your questions. Research design indicators: Your committee confirms that your problem statement aligns with your proposed methodology. If your problem statement sounds qualitative but you’re proposing quantitative methods, they’ll question the alignment. When all these elements are present and aligned, your committee can confidently approve your proposal because they can see that you’ve thought through every aspect of your study.
Before you submit your problem statement to your committee, use this checklist to make sure you’ve included everything: □ Have I named my theoretical framework and explained how it relates to my problem? □ Have I clearly stated my unit of analysis (individuals, organizations, teams, etc.)? □ Have I specifically defined my population with relevant characteristics? □ Have I described my sampling frame—where I’ll actually recruit participants? □ If I’m writing a knowledge-gap statement, have I indicated my sampling technique? □ Does my language clearly indicate whether this is qualitative, quantitative, or mixed methods research? □ Is my problem statement 250-400 words (not too brief, not too long)? □ Have I provided citations for key claims about the problem? □ Could a reader infer the basic design of my study from this problem statement alone? If you can check all these boxes, your problem statement is probably solid.
Here’s the thing about problem statements: they’re not just describing your problem. They’re making the case that your proposed study is the right way to address that problem. When your committee reads your problem statement, they should think: “Yes, this problem needs to be studied. Yes, this approach makes sense. Yes, this student has thought through the key elements of study design. This proposal is ready for approval.” That only happens when you include all the key elements I’ve outlined here. Missing even one element raises questions and leads to revision requests. If you’re struggling to craft a problem statement that includes all these elements in a clear, compelling way, that’s exactly what we help students with at Real Professors. We’ve reviewed thousands of problem statements. We know what committees expect. We can help you write a problem statement that gets approved the first time. Learn more about our dissertation writing service and how we help students craft every section of their dissertations, starting with rock-solid problem statements. Schedule a free consultation to talk with a professor about your problem statement. Bring what you have so far, or start from scratch—we can help either way. Don’t waste months revising an incomplete problem statement. Include all the key elements from the beginning and get your proposal approved on the first submission.
Why Incomplete Problem Statements Cause Proposal Delays
Before we get into what to include, let’s talk about why incomplete problem statements are such a common problem. Your dissertation committee is trying to evaluate whether your proposed study is feasible, original, and methodologically sound. They can’t do that if your problem statement doesn’t give them enough information. When your problem statement is too vague, here’s what happens: Your committee can’t tell if your study is feasible. If you don’t specify your population and sampling frame, they can’t assess whether you’ll actually be able to recruit participants. “Teachers” is too broad. “First-year elementary teachers in Title I schools in Chicago” is specific enough to evaluate feasibility. Your committee can’t tell if your study is original. If you don’t mention your theoretical framework or unit of analysis, they can’t determine whether this exact study has been done before. Hundreds of studies have examined “teacher retention.” Far fewer have examined “how novice teachers in under-resourced schools conceptualize professional identity formation using identity theory.” Your committee can’t tell if your methodology makes sense. If your problem statement doesn’t indicate your research design, they can’t evaluate whether your approach matches your questions. Are you doing qualitative interviews? Quantitative surveys? Case studies? Your problem statement should make this clear. Your committee has to ask for clarification. And that means rejecting your proposal and asking you to revise. Multiple times, usually, because each revision only addresses some of the missing information. This is why students get stuck in revision cycles. They’re trying to add information piece by piece in response to committee feedback, when what they really need is a complete problem statement from the beginning that includes all the key elements. Let me show you what those elements are.
The Four Core Elements Every Problem Statement Needs
Whether you’re writing a socioeconomic problem statement or a knowledge-gap problem statement, there are four core elements that must be present. Let’s go through each one.
Element #1: Theoretical Framework
Your problem statement should mention the theoretical lens through which you’re examining your problem. This doesn’t mean you need a lengthy explanation of the theory—that comes in Chapter 2. But you need to name the theory and show how it relates to your problem. Why this matters: Theory guides how you understand and interpret your problem. Different theories lead to different research questions and different methodological approaches. Your committee needs to know which theoretical perspective you’re taking. For socioeconomic problem statements: Even though you’re focused on a practical problem, you still need theory. You might write something like: “Drawing on Conservation of Resources Theory (Hobfoll, 1989), which explains stress as resulting from threatened or actual loss of valued resources, this study examines how emergency department nurses experience resource depletion in high-trauma environments.” You’ve named the theory (Conservation of Resources) and connected it to your problem (resource depletion causing nurse stress). For knowledge-gap problem statements: Theory is even more explicitly central. You might write: “While resilience theory has been applied extensively to pediatric nursing contexts (Smith, 2022), its applicability to adult trauma nursing remains underexplored. This study extends resilience theory by examining how trauma nurses develop psychological hardiness in repeatedly traumatic situations.” You’ve named the theory (resilience theory), shown where it’s been used, and indicated how your study extends it. Common mistake: Students often mention theory in their literature review but not in their problem statement. Your problem statement needs to establish upfront that you’re working from a theoretical foundation.
Element #2: Unit of Analysis
Your unit of analysis is what or who you’re actually studying. This sounds simple but students mess it up constantly. Common units of analysis:
- Individuals (teachers, nurses, managers, students, patients)
- Groups (teams, departments, classrooms)
- Organizations (schools, hospitals, companies, nonprofits)
- Programs or interventions (training programs, curricula, policies)
- Documents or artifacts (court cases, news articles, social media posts)
Element #3: Population
Your population is the broader group from which you’ll draw your sample. It defines the general boundaries of who or what you’re studying. Why this matters: Your committee needs to understand the scope and context of your study. “Nurses” is too broad. “Emergency department nurses in urban teaching hospitals” is specific enough to evaluate. How to be specific about population: Include relevant characteristics that define your population: Geographic boundaries:
- Urban vs. rural vs. suburban
- Specific regions, states, or cities
- Specific countries (for international or comparative studies)
- Type of organization (teaching hospitals, community hospitals, for-profit, nonprofit)
- Size (small schools, large districts, Fortune 500 companies)
- Sector (public, private, government)
- Age ranges
- Experience levels
- Educational backgrounds
- Professional credentials
- Experience level (first-year)
- Grade level (elementary)
- School type (Title I—high poverty)
- Setting (urban)
- Region (Midwest)
- Credentials (registered nurses)
- Experience (less than five years)
- Setting (Level I trauma centers)
Element #4: Sampling Frame
Your sampling frame is the specific group from which you’ll actually recruit participants. This is narrower than your population—it’s the accessible subset of the population you can realistically study. Why this matters: This is about feasibility. Your committee needs to know that you can actually access the people or data you plan to study. Vague statements about studying “teachers nationwide” raise red flags because that’s not feasible for a dissertation. How to specify your sampling frame: Be concrete about where you’ll recruit participants: “This study will recruit participants from emergency departments in three urban teaching hospitals in Chicago with which the researcher has established partnerships.” This tells your committee:
- How many sites (three hospitals)
- What type of sites (urban teaching hospitals)
- Where (Chicago)
- Why you can access them (established partnerships)
Additional Elements for Knowledge-Gap Problem Statements
If you’re writing a knowledge-gap problem statement (typical for PhD programs), you need two additional elements beyond the four core elements.
Element #5: Sampling Technique
Knowledge-gap problem statements should indicate what type of sampling you’ll use. This helps your committee understand your methodological approach. Common sampling techniques: For qualitative research:
- Purposive sampling (selecting participants who meet specific criteria)
- Snowball sampling (participants recruit other participants)
- Theoretical sampling (sampling based on emerging theory)
- Maximum variation sampling (selecting diverse cases)
- Random sampling (probability-based selection)
- Stratified sampling (random sampling within subgroups)
- Convenience sampling (accessible participants)
- Cluster sampling (selecting groups then individuals within groups)
Element #6: Research Design Indicators
Your problem statement should give clear hints about your research design—qualitative, quantitative, or mixed methods. You don’t need to say explicitly “this will be a qualitative phenomenological study” in the problem statement, but the language you use should make it obvious. Language indicating qualitative design: Words like “explore,” “understand,” “describe,” “lived experiences,” “perceptions,” “meanings,” “process,” “how participants make sense of” all signal qualitative research. “It is not known how emergency nurses experience and describe the process of developing resilience in trauma care environments.” The words “experience,” “describe,” and “process” tell your committee this is qualitative. Language indicating quantitative design: Words like “relationship between,” “extent to which,” “predict,” “correlate,” “compare,” “measure,” “effect” signal quantitative research. “The relationship between organizational support factors and nurse retention rates in urban trauma centers remains unexamined.” The words “relationship between” and “rates” tell your committee this is quantitative. Language indicating mixed methods: If you’re using mixed methods, your problem statement might indicate both kinds of language or explicitly mention multiple phases. “While quantitative research has identified factors correlated with teacher retention, qualitative understanding of how teachers experience these factors in their retention decisions is lacking.” This signals you’ll use both approaches—quantitative to examine correlations and qualitative to understand experiences.
Annotated Example: All Elements in Action
Let me show you a complete problem statement with all elements labeled so you can see how they work together. Example Problem Statement (Knowledge-Gap Type for PhD in Nursing): While [substantial research] has examined factors contributing to nurse burnout in hospital settings (Smith, 2022; Johnson, 2023), limited understanding exists regarding how [Element #2: Unit of Analysis – individual nurses] emergency department nurses in [Element #3: Population – urban Level I trauma centers] develop and sustain psychological resilience. Existing research on [Element #1: Theoretical Framework – resilience theory] has focused primarily on pediatric and oncology nursing contexts (Brown, 2023), with trauma nursing receiving minimal scholarly attention. Most resilience studies have employed quantitative approaches [Element #6: Research Design Indicator – signaling this will be qualitative], measuring resilience as an outcome variable rather than examining the lived experiences through which nurses build resilience capabilities. It is not known how [Element #2: Unit of Analysis reinforced] trauma nurses [Element #4: Sampling Frame begins] in three urban trauma centers in the Midwest [Element #4: Sampling Frame – specific sites and region] describe their experiences of developing and maintaining resilience amid repeated exposure to traumatic patient situations. Using [Element #5: Sampling Technique] purposive sampling to identify nurses with at least two years of trauma care experience, this phenomenological study will explore these lived experiences. Every element is present:
- ✓ Theoretical framework: Resilience theory
- ✓ Unit of analysis: Individual emergency nurses
- ✓ Population: Trauma nurses in urban Level I trauma centers
- ✓ Sampling frame: Three specific trauma centers in the Midwest
- ✓ Sampling technique: Purposive sampling (nurses with 2+ years experience)
- ✓ Research design indicators: “lived experiences,” “describe,” “phenomenological”
Common Mistakes to Avoid
Now let me tell you about the mistakes I see constantly in problem statements so you can avoid them.
Mistake #1: Naming Theory Without Connecting It
Students often mention a theory but don’t explain how it relates to their problem. They’ll write something like: “Using Social Learning Theory, this study examines teacher retention.” Okay, but how does Social Learning Theory relate to teacher retention? What’s the connection? You can’t just name-drop a theory. Better version: “Drawing on Social Learning Theory’s emphasis on observational learning and modeling (Bandura, 1977), this study examines how novice teachers’ observations of veteran colleagues’ coping strategies influence their own retention decisions.” Now we see why Social Learning Theory is relevant—because the study focuses on how teachers learn from observing others.
Mistake #2: Missing Population or Sample Details
Students write “this study will examine nurses” or “this study will survey teachers” without specifying which nurses or which teachers. This forces your committee to ask: What kind of nurses? Where? How many years of experience? What settings? These aren’t optional details—they’re required elements of a problem statement.
Mistake #3: Being Vague About Research Design
Students write problem statements that could describe either qualitative or quantitative research. They use neutral language that doesn’t signal their methodological approach. “This study will investigate factors affecting nurse retention.” Is this qualitative (interviewing nurses about their experiences) or quantitative (surveying nurses and doing statistical analysis)? Your committee can’t tell. Your problem statement language should make your research approach obvious without having to state it explicitly.
Mistake #4: Including Too Much Detail
On the flip side, some students try to cram their entire methodology into the problem statement. They write three paragraphs explaining their exact data collection procedures, their specific research questions, their analytical approach, etc. The problem statement should include key elements that frame your study, but it shouldn’t be a complete methodology section. Save the details for Chapter 3. Rule of thumb: Your problem statement should be 250-400 words typically. If it’s longer than 500 words, you’re probably including too much detail.
Mistake #5: Shifting Focus Mid-Statement
Students sometimes start with one focus and end with another. They’ll begin talking about organizational problems and end talking about individual experiences. Or they’ll talk about a practical problem and then shift to describing knowledge gaps. Pick your type (socioeconomic or knowledge-gap) and your focus (individual, organizational, etc.) and stay consistent throughout.
How Your Committee Uses These Elements
Let me explain why each element matters from your committee’s perspective. Understanding what they’re looking for helps you include what they need. Theoretical framework: Your committee checks whether you understand relevant theory and whether you’re using theory appropriately to frame your study. If your theory doesn’t match your problem, they’ll question your theoretical foundation. Unit of analysis: Your committee checks whether your research questions, methodology, and analysis plan align with your unit of analysis. Misalignment here is a red flag for methodological problems. Population: Your committee assesses whether your population is specific enough to make your study meaningful. Too broad and you can’t say anything conclusive. Too narrow and your findings won’t matter to anyone. Sampling frame: Your committee evaluates feasibility. Can you actually access this population? How will you recruit them? Is your timeline realistic given your sampling frame? Sampling technique (for knowledge-gap statements): Your committee checks whether your sampling approach matches your research design and will yield appropriate data for your questions. Research design indicators: Your committee confirms that your problem statement aligns with your proposed methodology. If your problem statement sounds qualitative but you’re proposing quantitative methods, they’ll question the alignment. When all these elements are present and aligned, your committee can confidently approve your proposal because they can see that you’ve thought through every aspect of your study.
Putting It Together: A Checklist
Before you submit your problem statement to your committee, use this checklist to make sure you’ve included everything: □ Have I named my theoretical framework and explained how it relates to my problem? □ Have I clearly stated my unit of analysis (individuals, organizations, teams, etc.)? □ Have I specifically defined my population with relevant characteristics? □ Have I described my sampling frame—where I’ll actually recruit participants? □ If I’m writing a knowledge-gap statement, have I indicated my sampling technique? □ Does my language clearly indicate whether this is qualitative, quantitative, or mixed methods research? □ Is my problem statement 250-400 words (not too brief, not too long)? □ Have I provided citations for key claims about the problem? □ Could a reader infer the basic design of my study from this problem statement alone? If you can check all these boxes, your problem statement is probably solid.
Conclusion: Your Problem Statement Should Sell Your Study
Here’s the thing about problem statements: they’re not just describing your problem. They’re making the case that your proposed study is the right way to address that problem. When your committee reads your problem statement, they should think: “Yes, this problem needs to be studied. Yes, this approach makes sense. Yes, this student has thought through the key elements of study design. This proposal is ready for approval.” That only happens when you include all the key elements I’ve outlined here. Missing even one element raises questions and leads to revision requests. If you’re struggling to craft a problem statement that includes all these elements in a clear, compelling way, that’s exactly what we help students with at Real Professors. We’ve reviewed thousands of problem statements. We know what committees expect. We can help you write a problem statement that gets approved the first time. Learn more about our dissertation writing service and how we help students craft every section of their dissertations, starting with rock-solid problem statements. Schedule a free consultation to talk with a professor about your problem statement. Bring what you have so far, or start from scratch—we can help either way. Don’t waste months revising an incomplete problem statement. Include all the key elements from the beginning and get your proposal approved on the first submission.