How do you find job ads? 

In preparation for my Fall professional development graduate classes, I compiled a list of places to search for jobs, with some help from #AcademicTwitter. And because I never met a list that didn't look better in a spreadsheet, we made a spreadsheet of Places to Search for HDFS-relevant academic and alt-academic jobs. Behold: 

Places to Search for HDFS-relevant academic and alt-academic jobs

It includes traditional places for faculty jobs, like Chronicle of Higher Ed and Academic Jobs Online. 

​It includes some places the hip young people go, like the Psych Jobs Wiki  (warning: Not for the faint of heart!).

​More specialized places like Obesity Society and Association for Public Policy Analysis and Management.

And, places for primarily alt-ac jobs, like Idealist and the Versatile PhD. 

I'm always looking to add, so please send me suggestions.

Want to check out my other compilation lists? 

Post docs (almost 140 listed)

​Fellowships (almost 100)

​Internships (almost 50)

​“Where to search for HDFS-relevant jobs" first appeared on Eva Lefkowitz’s blog on May 14, 2021.”

My favorite course to teach starts now! Here's my syllabus for my graduate seminar in professional development and career planning. 

SYLLABUS SPRING 2021

Last week I wrote about best practices in data management. And then later realized that I previously blogged about it. Today I want to address issues related to analysis and publication. Which apparently I have also previously blogged about. But I think four years later, I have enough new things to say to make it worthwhile to write a new post.
 
Much as in the past few years there have been high profile cases around issues related to data management, there have been similar high profile cases around ethical issues in responsible reporting. Although we spend a fair bit of time in class reviewing different types of ethical issues, and discussing specific case studies, I am only going to briefly mention the pitfalls here, to focus instead on best practices. Particular ethical issues in publishing (some of which I discussed in that 2015 post) include (many of these points draw from readings that I cite in my syllabus):

• Plagiarism
• Self-plagiarism
• p-hacking/fishing for significance
• HARKing: Hypothesizing after the results are known
• Garden of forking paths
• Non-transparency in analyses
• Not correcting for Type I error
• Claiming that the difference between significant and not significant is meaningful
• Overstating meaningfulness, particularly with large sample sizes (ignoring practical significance)
• Ignoring meaningful results that may not be significant
• Viewing p < .05 as a magical cutoff
• Causal conclusions without causal evidence
• Not revealing conflict of interest/funding sources

 
So, here are some suggestions for best practices:
 
Don’t plagiarize or self-plagiarize: Yes, it seems obvious. I’ve talked about these issues in more detail in previous posts. But the main point is that accidental plagiarism, and self-plagiarism, are relatively common and you should follow best practices to avoid them.
 
Write hypotheses before running analyses: It is very common for people (not just students) to say, I’m really interested in how [broad construct A] relates to [broad construct B]. Then to run a bunch of correlations trying to see if indicators of A relate to indicators of B. Then to drop variables/analyses that don’t work very well, and then keep ones that do. Then create a story around these findings. If instead you formulate hypotheses first, you can commit to running specific things, and keeping all of those analyses in your paper. And, not HARKing, or coming up with post-hoc hypotheses for why A would relate to B in that way. You don’t have to table every unsuccessful analysis – you can for instance say, we expected there would be interactions with gender, but Step 3, in which we added interactions with gender was never significant, so we do not report those analyses in the table. And, you can still run follow up analyses if you find something you can’t quite explain – but just explain clearly that you ran those analyses to follow up on the unexpected finding, rather than pretending you had planned to run them all along.
 
Statistically test the difference between two analyses: If two variables are significantly correlated but two others are not, don’t describe them as meaningfulness different findings. Or, if two variables are correlated for one group but not another, don’t describe it as X matters for group A but not group B. For instance, if you’re interested in whether body image has similar associations with girls’ sexual behavior and boys’, you can run interactions with gender rather than separate analyses. If you do the latter, and one correlation is significant and the other is not, it could be meaningful, or it could be noise that pushed one correlation slightly about p < .05 and the other below it, or it could be that the correlations are identical but one group was slightly larger. But if you run the analyses separately, you can’t conclude that the associations are meaningfully different, even if one reaches statistical significance and the other does not.
 
Describe correlational results without causal language. It is so easy to write that X predicted Y – that’s even the way we talk about variables statistically in regression. But, unless you have manipulated something, avoid using causal language. Explain associations, but don’t say that one led to the other, even if you have longitudinal data. Helpful ways to write about non-causal associations in the results section:

• Body image was positively associated with number of sexual partners
• Young men who had more positive body image tended to have more sexual partners

In the discussion, you can be more speculative, but be clear that you’re being more speculative, and explain alternative explanations. An example:

• Having better body image may lead men to feel more confident sexually, which in turn leads to opportunity for more sexual partners. However, it is important to note that these results are correlational. It is also possible that having more sexual partners leads men to feel better about their bodies, or that something else explains this association.  For instance, it may be that men with better self-esteem both feel better about their bodies, and have more sexual partners.

 
Consider effect size: If you have an enormous sample, it is easy to get a significant correlation, even at r = .10. But a correlation of .10 means that you explained 1% of the variance, which is not particularly meaningful. Be aware of the practical significance of your results.
 
Reveal all potential conflicts of interest and funding sources. Enough said.
 
Consider pre-registration: there are arguments for and against, as I discussed in my 2015 post. But do know that pre-registration is becoming increasingly common, including some journals that will review your paper before you run analyses so that, if accepted, whether you find significant results or not, they agree to publish it.
 
Somehow this list does not feel very comprehensive, perhaps because some of the best practices in data management also apply here, and also, because I wrote about the topic 4 years ago. But, if you add “avoid the bullet points at the top of this post” you have a pretty good list of good practices to follow.
 
“Best practices in responsible reporting first appeared on Eva Lefkowitz’s blog on June 13, 2019.”

Data in a dissertation can come from different sources. The six primary sources I can think of are (1) using your advisor’s pre-existing data, (2) getting involved in your advisor’s data collection and adding some research questions or measures to that project; (3) using data from another faculty member at your university – maybe another faculty member in your department whom you have worked with; (4) finding publically available secondary data; (5) collecting your own data; (6) some combination of the above. I believe that I have had students do all of these possible options at some point or another. I will discuss some of the advantages and disadvantages of each option, with examples, below.
 
Using your advisor’s data: My favorite part about being a professor is mentoring graduate students, and a large part of such mentoring is research. Advisors often love when students work with data they already have. I think all faculty feel as though we have mounds of data and we wish someone would just write it up for us. When students use their advisor’s data, life is easier for the advisor because then advising converges with the faculty member’s own research agenda. The advisor feels very knowledgeable about the topic because it is within their own research area. And, your advisor likely has high quality data, perhaps data that you could not collect on your own. You cannot, for instance, collect a 20-year longitudinal study for your dissertation, but perhaps your advisor already did. Whatever the data, using your advisor’s data is efficient and can lead to the quickest time from dissertation start to finish. However, if you use your advisor’s data, you have constraints on the research questions you can ask. You must work within these constraints, whether they are the sample not being exactly what you might like, the measures being a bit of a stretch for the research questions you want, or perhaps another student is already working on a project with those data that overlaps with some of your research questions. Nevertheless, you can have a very successful dissertation with your advisor’s data. For instance, one of my former students, Sara Vasilenko, did a multi-paper dissertation using all data my colleague and I had previously collected (though Sara was there during some of the data collection). She has multiple papers based on these data, including this paper on how daily affect varies with sexual behavior, as well as a conceptual chapter from her introduction in a volume we co-edited.
 
Adding questions to advisor’s ongoing project: Some advisors may provide an opportunity to add questions to an ongoing research project, particularly a longitudinal project where you add questions to one or more timepoints. This option is more likely if you have worked with this mentor for a while and contributed to the project already in other ways – you have shown an investment. It is beneficial for your advisor because they have an opportunity for more publications from their project. It benefits you because you can now ask more tailored questions or have measures more tailored to your interests if you simply used your advisor’s existing data. But, it may also give you access to larger or better populations than you would have the time or funding to collect on your own. However, you are unlikely to be able to add every question or every measure you might want if designing your own study – your advisor probably has limits on how many questions could be added. In addition, you still do not have control over the sample or data collection techniques. Despite possible limitations, this option can be very fruitful. My former student Meghan Gillen, was very interested in body image. We were collecting data for a longitudinal study, and she ended up selecting body image measures to add to the project. She ended up writing her master’s thesis and dissertation from these data, and published six first authored papers using aspects of these data (here’s one on the freshman 15).
 
Data from another faculty member: Frequently my students work with my colleagues to gain experience with different types of data and different mentoring styles. I have had students use data from a colleague in the same department, a colleague in a different department at the same university, and a colleague in another state. In such situations, you may find data better suited to your research interests than data your advisor already has. It provides you an opportunity to learn about new topics, new data collection techniques, or new mentoring styles. And, it provides you with another mentor who can support you and also can be part of your larger network. However, your advisor may be less invested in a project that does not use their data. There may be more negotiation of roles, both mentoring and authorship, when you use someone else’s data. So, the process may be more complicated than simply using only your mentor’s data. Although I’m not sure I’ve ever had a student use a colleague’s data in their dissertation per se, I have had several students work with and publish papers based on colleagues’ data. For instance, Rose Wesche worked both with my then colleague in sociology Derek Kreager to publish multiple papers, such as this one I recently blogged about, as well as another paper on casual sexual experiences with my colleague at Kent State, Manfred Van Dulmen.
 
Publically available secondary data: Some students find publically available secondary data to address research questions that they cannot address with their mentor’s data. This option has many of the same advantages and disadvantages as using data from another faculty member. A further potential challenge can be getting access to such data. Sometimes there are a number of hurdles required before you are allowed to use such data. In addition, sometimes you need particular conditions, such as a secure computer without internet access in a locked office. Rose also used Add Health partner data for one of three papers in her dissertation. There were some harrowing moments waiting for all of the right permissions to come through for her to be able to access the data, though in the end it arrived in time.
 
Collecting your own data: One thing I love about mentoring students in research is that they take me in directions that I may not have gone without them, but I learn lots of new things and sometimes develop my own new interest in these areas. Of course, it’s great when students primarily work with data I have. However, I also enjoy when a student takes initiative on a new project and I learn at least as much as they do along the way. When you collect your own data, you have a lot more control over the research questions, design, and sample. It is the most obvious way to do exactly what you want to do. However, it is also costlier – it can cost money to collect good quality data, and it certainly takes more time to collect your own data than to use data someone else already collected. Your funds may not allow you to collect a large enough sample to insure publication, and as discussed already, you are unlikely to be able to collect longitudinal data (other than very short term longitudinal data). And, depending on the culture in your department, your advisor may be hesitant to support you collecting your own data. When I was in grad school and decided to collect my own data (an intervention, with video observations, and four total visits), my advisor was rather resistant. But I persisted, collected my own data, and ended up with five publications from those data, including one in Child Development. My first student – Tanya Boone-Holladay, received an F31 to collect her own dissertation data. Her research had a design based off of my own dissertation data collection. Her dissertation pre-dated the department’s multi-paper dissertation option. We published one paper together from these data, and she published subsequent papers after she graduated. In contrast, Chelom Leavitt collected data on a topic much further removed from my own research. Chelom came to me with an incredibly ambitious dissertation idea – she wanted to collect data on midlife adults (not an easy to capture population), in married relationships (more constraints), in three different countries speaking three different languages (the translation!). Using mostly measures of constructs I had never measured. She did it. And her first paper from her dissertation is now in press.
 
A combination: In one way or another, many of my students, particularly students who did multi-paper dissertations, chose a combination of these options. With a combination, you can maneuver around many of the challenges described above – you have access to high quality data you may not be able to collect on your own, but can also design your own smaller study to address more specific questions exactly as you’d like to. The challenge might be that you make things more complicated for yourself, in that you may introduce some of the challenges of using secondary data, or multiple collaborators, or getting your mentor’s buy-in. Emily Waterman used data from one of my projects, and also collected her own small-scale data to address more specific questions, getting the best of both worlds. 
 
Which option you choose depends on a number of factors, some in your control and some not. Your research questions, your timeline, the data your mentor has, the culture in your department, and your advisor’s preferences among others. When making a decision, consult with your advisor and other informal mentors to figure out the best option for you. 
 
“Where should your dissertation data come from? first appeared on Eva Lefkowitz’s blog on June 11, 2019.”

Last week, I discussed whether you should do an internship during graduate school. Today, I want to share a list we compiled of internships related to Human Development and Family Sciences. Many of these internships are likely also relevant to graduate students in related disciplines such as psychology, sociology, public health, and communications.
 
As with my lists of postdoctoral positions and graduate fellowships, I make no claims that any information, including information about citizenship requirements, is accurate.
 
Also as with the other lists, it’s a broad list. Internship sites include government agencies like the National Institutes of Health, research institutes like RAND, and nonprofits like UNICEF. The topic areas vary widely, and include public health, sexual health, nutrition, statistics/psychometrics, policy, education, ethnic/racial minority families, adulthood and aging, and child development (detailed in a column). Locations are around the United States and the world (detailed in a column). Some are summer internships and others can occur during the academic year. They are as short as 8 weeks or as long as 7 months. There are both paid and unpaid internships (and a column that details whether paid, and if so how much). 
 
Find it here. 
 
If you know of any others, please share them with me and I will add them. If you find errors or broken links, please let me know.
 
“40+ internships related to Human Development & Family Sciences first appeared on Eva Lefkowitz’s blog on May 28, 2019.”

There are certain things that I think the majority of graduate students should do. Apply for external funding. Attend conferences. Publish. Do a post doc (that one less so, but still, the majority).  My advice on doing an external internship is much more of “it depends” advice than some of these other topics.
 
To clarify, I am not referring to clinical internships. If you are in a program like MFT or clinical psychology, your program and licensing has specific requirements for internship hours that of course you must meet. But I am talking about internships that are not fulfilling clinical hours, but instead are about getting experience in a non-university setting such as a research institution, non-profit organization, or government agency.
 
If you know that you want a career as a professor, then an internship may not be the best use of your time. The main accomplishments for acquiring a faculty position are relatively straightforward: publish; perhaps pursue funding, particularly if an R1 university is your dream job; perhaps get teaching experience, particularly if a more teaching-focused university is your dream job. The best use of your summers, in order to meet the goal of a tenure track faculty position, is to write. 
 
The two main reasons why you should consider doing an internship are if you do not plan to go into an academic career, or if you do not yet know what type of career you want. Here are some benefits of doing an internship, whether summer or academic year, and whether paid or unpaid:

• Learn about a field/career: Most graduate students have a relatively strong sense of what it’s like to be a professor – you spend a lot of time with professors. However, for other careers, an internship can really help you get a sense of whether you are interested in that type of institution, and/or that type of position.
• Networking: Networking in general is helpful for anyone, but for faculty positions, networking rarely leads to a job materializing just for you. The availability of new tenure track positions generally relies on many factors out of the control of an individual faculty members (or department heads!) going all the way up to the provost. However, in many other organizations, networking can result in a fast track to a position. Internships are an excellent way to make those connections – I know many people who eventually secured a full time position at the place they did their internship.
• Gain transferable skills: Even if you do not eventually secure a job at your internship site, the skills you develop there will better position you for other alt-academic positions when you do go on the job market. 

 
An important point to note about internships. Although some organizations advertise that they have internships available, not all do. If you are interested in a particular place for an internship, reach out and ask. It is helpful if you have some type of connection to someone at that organization, such as an alum of your program, a contact of your mentor, etc. Internships can be an excellent opportunity for setting yourself up for a future career outside of academia.
 
 
“Should you do an internship during graduate school? first appeared on Eva Lefkowitz’s blog on May 21, 2019.”

HDFS Graduate seminar in professional and career development
 
My grad seminar on professional and career development may be my favorite course to teach (I had to temper this statement a bit this year, as two of my students this semester TAed for me in my general education lifespan class, where I told 350 students that class was my favorite to teach). But perhaps my favorite position to date was director of the graduate program, and one of the most fulfilling aspects of my 20+ years as a professor is mentoring graduate students. Teaching this course feels like mentoring more than teaching.
 
My learning objectives have not changed much since I previously taught this course. However, I have updated the readings, played with the order of topics (there is often a chicken/egg issue of whether to cover, for instance, “how to” related to publishing and peer review, or ethics of publishing and peer review, first), and added one new assignment.
 
Here is the full syllabus:
syllabus_5095_2019-sp.pdf

 
“HDFS Graduate seminar in professional and career development first appeared on Eva Lefkowitz’s blog on January 31, 2019.”

In my adolescent development graduate seminar I once assigned a paper for our identity unit on narrative analysis of turning points (McLean & Pratt, 2006). The authors followed high school students, and about six years later asked them to “write about an important transition or change with respect to their understanding of themselves.” McLean and Pratt consider this event a turning point, and coded the narratives in terms of meaning-making from this turning point, ranging from no meaning expressed to describing an insight from the event. 
 
Discussing this article in the seminar made me realize that at least so far (and it’s been a much longer so far than six years post-high school), I cannot really identify turning points in my life, particularly in the career realm. My How-I-got-here narrative is much more serendipity and process of elimination than Aha! moments or turning points. I’m okay with that path at this point, and actually, I think it’s important to share that path with others. Sharing my own journey to this point with high school students, college students, and grad students can help them to understand that we do not all choose our career based on a critical, life altering moment in childhood, or our lifelong passion since we pretended to be doctors as toddlers. Some of us almost fall into our career path, and that’s okay.
 
I went to college without a major. My father wanted me to be an engineer, so I went to a liberal arts university that did not have an engineering program. My first semester, I took all general education courses – humanities, history, economics, and psychology. I eliminated, three of them, so my second semester I took sociology, political science, fine arts, and another psychology course. For four semesters, I took three courses and a psychology course, until we were required to declare a major, and I declared psychology. So essentially I chose my major through process of elimination.
 
Close to graduation, I decided that I wanted a job in market research, where I could use my research and psychology skills. I spent 2 ½ months the summer after I graduated traveling back and forth to the Brandeis Career Services Center to print my resume and cover letters on fancy paper and apply for market research and marketing jobs. And as time went on, a bunch of other jobs. One of those jobs was as an administrative assistant on a research project at Simmons College School of Social Work. The PI called me to say that the project would soon have a research assistant position available, and that my record seemed more suited for such a position. And so I began a two-year position as a research assistant on a project studying adolescent mental health. My initial reasoning was that I would use the research skills I gained in the job to then be more marketable for market research positions.
 
I really can’t think of a turning point during that first year, but I enjoyed the position, and at some point decided that I wanted to continue in psych research and eventually become a professor. I knew I didn’t want to be a clinician, even though some of the topics that interested me often overlapped with clinical psych faculty’s research programs. So I decided to apply to developmental and social psych programs. I guess that’s the closest I’ve had to a turning point. I actually had trouble writing my grad school application statement because it felt as though there should be a description of a turning point, and I really didn’t have one. I applied to 13 programs, was admitted to five, relatively easily narrowed it down to two, and ended up choosing UCLA over Virginia based on several small factors, mostly from ruling out some things about Virginia.
 
In grad school I had some interest in parent-adolescent relationships, and ended up working with Marian Sigman on a project on parent-child conversations about emotionally charged topics, including sexuality. That’s essentially how I ended up having a career studying sexuality during adolescence and the transition to adulthood – because my interest in parent-adolescent relationships led me to a project that included communication about sex.
 
My large, pre-tenure NIH-funded study on gender roles and sexual behavior? Early in my faculty career, NIH had an RFA on Gender and HIV Risk and I thought, I could pull together a proposal on that. I did, with help of awesome collaborators and students, and it was funded on the first try. My move to UConn and position as department head? Someone emailed me and asked me to apply, and… I did. And here I am. There was (I assure you) no lifelong dream to become a chair or move up the administrative ladder.
 
It is not only my career that has led to serendipity in my life. Take my bridesmaids, given that bridesmaids often represent our closest friends from all periods of life (if, like me, you get married after 30). In addition to my sisters (serendipity in the extreme?), I met my best friend in college because she moved to my dorm floor the second week of classes; we met in the bathroom when I was watering some birthday flowers. I met my best friend in grad school (and long term conference buddy) because we worked in the same lab. And I met my best friend as a faculty member at Penn State at an event scheduled by the New Faculty Club in my first months there, where the youngest people in the room found each other. In fact, many people I met that night continue to be my close friends, even though I have moved away. And, I met my husband when, during my first year as faculty, he interviewed for a position in the same department and a few months later, became my colleague.
 
You may be wondering why I am sharing all of these life details. I am kind of wondering the same thing, honestly. But I think the reason is that a prevailing narrative in our society around career development is to “find what you’re passionate about.” Or, “tell me what inspired you to be a professor” or “when did you know you wanted to be a professor?” (I get asked these latter two frequently by students who are interviewing me as part of a First Year Seminar course requirement). For me, though, there wasn’t a turning point or a lifelong passion. Do I love doing research on adolescent sexuality development? Absolutely. Do I like my job as HDFS department head at UConn? More days than not. Do I think I have the most amazing friends? Can’t imagine life without them. Am I passionate about many of the things in my life? Definitely. But my journey to this point was often serendipitous, and I want others to know that there is nothing wrong with that.
 
“Career serendipity first appeared on Eva Lefkowitz’s blog on November 27, 2018.”

When did you master the successful journal article search? During the course of their undergraduate studies, many students have to write a course paper that involves finding primary sources such as journal articles, particularly during junior and senior year. Undergraduate honors students almost always need primary sources for writing their thesis. Graduate students obviously also need to hunt down journal articles for course papers, comprehensive exams, and theses/dissertations throughout their time in graduate school (and after), though some begin graduate school already having developed strong skills in this area.
 
I’ve learned over time that the preparation students receive from their instructor in advance of having to track down articles varies widely. Some instructors fully prepare students for this task, particularly in honors seminars. Others, particularly by graduate school, expect students to know how to perform a successful literature review. So, my advice on how to do an effective literature search may be useful for students toward the second half of their undergraduate career, or early in their graduate career.
 

• Starting with a textbook: If you’re early in the process – let’s say, trying to narrow down a topic for a review paper for a course or your thesis, looking at your textbook for that course, or other courses, can be useful. Textbook writers spend a lot of time tracking down articles on a huge range of topics.  You can see what articles the textbook cites, and track down those original sources. For instance, if you're interested in sexual behavior, you can look in the sexual behavior section of your adolescent development textbook and track down the papers that the textbook author cited.
• Review articles: In many areas of research, someone (or multiple someones) has published review articles or meta-analyses. Review articles can be very useful because they summarize a fair bit of past work. However, there is a lot of information in one paper, so you will have to spend a lot more time reading it than an empirical article that summarizes only one study. To find review articles, you can check the titles of articles during your searches for ones that include “meta-analysis" or "review" in the title. The reference list of the review article will help you find other relevant articles (though they obviously will be older than the review article). You can also look at some specific journals that carry review articles, including Psychological Bulletin, Psychological Review, Human Development, and Developmental Review. 
• Searching in databases: Use Psychinfo, Google scholar, or other journal database to find articles on a specific topic. Learning to choose the right search terms can take time. You may need to spend a fair bit of time practicing and trying out a range of different terms before you find the right articles. If a search gives you < 10 articles, you need broader search terms. If it gives you > 1000 articles, you probably need narrower terms. If you’re using google scholar, using quotation marks can be really important. Let’s use an example. We recently wrote a paper on long-distance relationships. Here are some things I could try:
  • LONG DISTANCE RELATIONSHIPS: Without quotation marks, there are 4,740,000 results. Obviously that won’t work. Though, when I look at the first page, it is clear that they are likely some of the most relevant ones.
    

• Snowballing: If an article you read cites another article to make a specific point relevant to your interests, look it up. Researchers use this approach a lot.
• Forward searches: This technique is one of my favorites, because to me it feels like detective work. In psychinfo and google scholar, you can find all the articles that cite a specific article. So, if you find a great article on your topic, you can find all the articles published subsequently that refer to the great article. Some may not be relevant to your topic, but many likely will be.
• Don’t stop at first page of results: When you do a search, go beyond the first page. I have had students come to me with a reference list where everything was published in the past 2 years, and some are only tangentially related to their topic. The student often then tells me that s/he couldn't find anything more relevant. But often the issue is that the student didn't look through enough of the results in his/her search. When I do a search, I generally look through every article that comes up. That's why you want your search to be specific enough that it produces < 1000. The most recent research may be great, and you want to include the most recent research, but if you're not going more than 2 years back, you're likely excluding a lot of other great research.

Finding the right articles is a critical step to an effective literature review, and will save you so much time later when you are actually trying to summarize others’ work or relate it to your own.  
 
“Good journal article searching habits first appeared on Eva Lefkowitz’s blog on October 30, 2018.”

Last week I described different types of graduate programs if you want to be a clinician/counselor/therapist of some kind. This week I want to address the issue of choosing a specific graduate program once you know the general type of program you want.

First, think realistically about what limiting factors you might have in choosing your graduate program. Can you move anywhere in the country, or do you have geographic limitations (e.g., want to be within three hours’ drive of your family; have a partner who has to find work in a specific city; prefer to live in a big city or a small town; know you want to settle in CT forever)? If you have no geographic limitations you will have more possibilities for finding an ideal fit, but it doesn't make sense to look at programs that fall outside of your expectations of where you will live if you do have geographic limitations. If you are interested in programs that are very competitive (like clinical PhD programs, for instance), you might want to consider a broader geographic search. Perhaps you and your partner can live a couple of hours apart for a couple of years. In addition, think of your financial limitations. Do you have parental or other money to support your time in school, or will you have to take out loans? If you're going into a career like social work, you are unlikely to have a huge salary right after graduation, so considering the cost and what you can afford in loans after you finish is important. Programs can vary greatly. For 2018-2019, full time MSW tuition at NYU is $46,266; at Southern Connecticut State it is $12,143 in state, $24,487 out of state. Over the two-year degree that could be a difference of $60,000.

Once you have a sense of the type of program you want and any limiting factors you may have, you can start to research specific programs. Obviously, the Internet is a great source for finding out about programs (picture me, in 1991, sending letters to 30 psychology PhD programs, and then waiting for them to send me brochures about each program, and having those brochures take over my bedroom in piles of Yes/No/Maybe, and you'll start to realize what a truly great resource the internet is for this task!). There are different places you can look. US News & World Report ranks some types of programs, and so it can be a useful place to look. Let’s say I know I’m staying in North Carolina, and I’m interested in an MSW. It gives me 12 MSW programs in North Carolina. gradshools.com can sometimes be helpful. You can narrow your search down by discipline (e.g., social work), and then, if you'd like, state and/or city. If you're not interested in an online degree, make sure to check "campus" as one of the options. It is very important to note, though, that universities have to pay to advertise on gradshools.com, so you will not find every program there. Also note that there are a lot of other websites that compile graduate school information, and they may or may not charge to be listed – just be a bit careful when you are searching, as the listing could be incomplete or the information inaccurate. When I did the North Carolina MSW search on gradschools.com, I came up with only 5 programs.

You can also visit the websites of professional organizations. For instance, the American Association for Marriage and Family Therapy has a directory of training programs that lists US and Canadian programs.

Another option is a general google search. For instance, "graduate school North Carolina social work." When you do so, you will get a lot of different websites like gradschools.com, that try to compile lists of programs. You will also get a lot of ads for online programs.

But if you scroll down enough, you will also find specific programs.

 For instance, when I did this search, I found North Carolina Central University, which was not listed on gradschools.com.

When you look at specific programs, read their website carefully, and look for some of the following components (what you look for is going to vary by what kind of program you're considering):

• How do they describe their philosophy? What is their mission statement?
• What areas of specialization/emphasis do they describe, if any?
• What type of careers do they describe their graduates going into?
• How research focused is the program?
• Do they provide any information about the ranking of the program?
• Are they accredited?
• What courses do they offer? Do these courses match your interests?

For instance, back at NCCU, their mission statement includes: " The mission of the Department of Social Work is to prepare students to promote social and economic justice by engaging in problem solving efforts and offering direct and macro interventions with individuals, communities and organizations… The graduate program places special emphasis on preparing students to develop, deliver and evaluate services either for youth involved or at-risk of being involved in the juvenile justice system or with families involved with child and family services agencies." That may be great if you plan to practice in settings with at risk youth or family service agencies, but less so if your long term goal is private practice with adults. You can learn a lot about a program’s focus in their mission statement.  Over at the University of Pittsburgh site, I found information about skill concentrations, where they describe emphases in Direct Practice or Community, Organization, and Social Action. Some programs may only focus on one or the other, which you can learn pretty quickly by reading their website. They also offer a certificate in gerontology so if you're interested in aging, it could be a better program than MSW programs that don't offer such specialization.

Also consider talking to people you know. Talk to your professors, people where you work, other students. You may find someone who knows someone at a specific program, or knows about a specific program. Firsthand experience can provide information you may not find on a web site.

Throughout this process, the important thing will be finding the program that's right for you. Be realistic about your qualifications. If you don't have the highest GPA, consider programs that are not the highest ranked programs. If you're not certain whether you want to do community work or private practice, or work with children or adults, make sure you select a program that trains in both.

Also, be careful to determine the licensing regulations and requirements. Different types of degrees have different licensing requirements, and sometimes they're state specific. Some states have sharing rights for licenses, others do not. Consider these issues carefully when you decide where you want to train, and where you want to live afterward.

The better idea you have of what you want when you start this process, the easier it will be to narrow down your choices. That said, even if you start out with little sense of how to narrow things down, reading about all of the different programs will likely help you figure out what you do and don’t want in a program. Just like reading all those hard copy brochures in 1991 helped me – and you’ll harm fewer trees in the process.
 
“How to choose a graduate program first appeared on Eva Lefkowitz’s blog on October 16, 2018.”