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The United States index of socioeconomic deprivation for individuals (USiDep)

  • Boadie W. Dunlop
    Correspondence
    Corresponding author.
    Affiliations
    Department of Psychiatry and Behavioral Sciences, Emory University, 12 Executive Park Drive NE, 3rd Floor Atlanta, GA 30329, USA
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  • Jeffrey J. Rakofsky
    Affiliations
    Department of Psychiatry and Behavioral Sciences, Emory University, 12 Executive Park Drive NE, 3rd Floor Atlanta, GA 30329, USA
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  • David Mischoulon
    Affiliations
    Department of Psychiatry, Massachusetts General Hospital, 1 Bowdoin Square, 6th Floor, Boston, MA 02114, USA
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  • Helen S. Mayberg
    Affiliations
    Department of Psychiatry and Neurology, Mount Sinai School of Medicine, Mount Sinai West Floor 10 Room 10G-47, 1000 10th Ave, New York, NY 10019, USA
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  • Author Footnotes
    1 Present Address: Huntsman Mental Health Institute, University of Utah, 201 Presidents Circle, Salt Lake City, Utah, 84112, USA.
    Becky Kinkead
    Footnotes
    1 Present Address: Huntsman Mental Health Institute, University of Utah, 201 Presidents Circle, Salt Lake City, Utah, 84112, USA.
    Affiliations
    Department of Psychiatry and Behavioral Sciences, Emory University, 12 Executive Park Drive NE, 3rd Floor Atlanta, GA 30329, USA
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  • Andrew A. Nierenberg
    Affiliations
    Department of Psychiatry, Massachusetts General Hospital, 1 Bowdoin Square, 6th Floor, Boston, MA 02114, USA
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  • Thomas R. Ziegler
    Affiliations
    Department of Medicine, Emory University Atlanta, 100 Woodruff Circle, Atlanta BA 30322, USA
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  • Maurizio Fava
    Affiliations
    Department of Psychiatry, Massachusetts General Hospital, 1 Bowdoin Square, 6th Floor, Boston, MA 02114, USA
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  • Author Footnotes
    1 Present Address: Huntsman Mental Health Institute, University of Utah, 201 Presidents Circle, Salt Lake City, Utah, 84112, USA.
    Mark H. Rapaport
    Footnotes
    1 Present Address: Huntsman Mental Health Institute, University of Utah, 201 Presidents Circle, Salt Lake City, Utah, 84112, USA.
    Affiliations
    Department of Psychiatry and Behavioral Sciences, Emory University, 12 Executive Park Drive NE, 3rd Floor Atlanta, GA 30329, USA
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  • Author Footnotes
    1 Present Address: Huntsman Mental Health Institute, University of Utah, 201 Presidents Circle, Salt Lake City, Utah, 84112, USA.
Open AccessPublished:January 12, 2022DOI:https://doi.org/10.1016/j.pmip.2022.100091

      Highlights

      • Deprivation is an alternative approach for assessing socioeconomic position.
      • Socioeconomic deprivation is more closely linked to health status than poverty.
      • The USiDep is an individual-level measure of deprivation for people living in the US.
      • USiDep scores independently predicted depression outcomes in clinical trials.

      Abstract

      Background

      Individuals experiencing socioeconomic deprivation consistently demonstrate poorer physical and mental health. Income alone is inadequate as a measure of socioeconomic status (SES); a better measure for assessing the deprivation status of individuals is needed.

      Methods

      The New Zealand Index of Socioeconomic Deprivation for Individuals, a validated, eight-item measure of deprivation, was modified to create the United States Index of Socioeconomic Deprivation for Individuals (USiDep). The questionnaire was administered to patients with major depressive disorder participating in two clinical trials. Spearman’s correlation coefficients evaluated associations between USiDep scores with income and other measures associated with deprivation.

      Results

      The USiDep was completed by 118 participants, demonstrating adequate internal consistency (Crohnbach’s alpha = 0.766) and strong item-total correlations. USiDep scores were moderately correlated with past-year personal income (Spearman’s rho = -0.362, p < .001) and several other measures related to deprivation, including body mass index, level of education, quality of life, severity of childhood traumatic events, self-reported physical health, and negative life events. Patients scoring 5 on the USiDep (the highest possible score, indicating greater deprivation) had significantly lower rates of remission after 12 weeks of treatment than those scoring ≤ 4 (1/12, 8.3% vs 40/98, 40.8%, respectively, p = .03), whereas the lowest income group showed no significant associations with outcomes.

      Conclusion

      The USiDep is a valid, brief questionnaire for assessing SES that has utility for clinical research and may serve as a predictor of treatment outcomes in clinical trials. Validation of the USiDep in healthy controls and other medically and psychiatrically ill populations is warranted.

      Keywords

      1. Introduction

      The social determinants of health refer to the circumstances in which people are born, grow up, live, work and age, and include factors related to education, economics, environment, community, and health access [

      U.S. Department of Health and Human Services, Office of Disease Prevention and Health Promotion. Healthy People 2030. https://health.gov/healthypeople/objectives-and-data/social-determinants-health. Accessed Dec. 31, 2020.

      ]. An individual’s socioeconomic position is a significant contributor to their health status, including mental health [

      World Health Organization. Commission on Social Determinants of Health (CSDH), Closing the gap in a generation: health equity through action on the social determinants of health. Final report of the Commission on Social Determinants of Health. 2008, World Health Organization: Geneva.

      ,
      • Patel V.
      • Burns J.K.
      • Dhingra M.
      • Tarver L.
      • Kohrt B.A.
      • Lund C.
      Income inequality and depression: a systematic review and meta-analysis of the association and a scoping review of mechanisms.
      ]. Socioeconomic position also plays a significant role in the inter-generational transmission of inequalities in the areas of education and employment [
      • Alegría M.
      • NeMoyer A.
      • Falgàs Bagué I.
      • Wang Y.
      • Alvarez K.
      Social determinants of mental health: where we are and where we need to go.
      ,
      • Williams A.
      Inter-generational equity: An exploration of the “fair innings” argument.
      ]. For individuals, the most widely employed measure of socioeconomic status in health research is personal or household income [
      • Braveman P.A.
      • Cubbin C.
      • Egerter S.
      • Chideya S.
      • Marchi K.S.
      • Metzler M.
      • et al.
      Socioeconomic status in health research: one size does not fit all.
      ]. However, income alone has important limitations as a valid measure of socioeconomic position [

      Czajka JL, Denmead G. 2008. “Income data for Policy Analysis: A Comparative Assessment of Eight Surveys” Mathematica Reference No.: 6302-601.

      ]. Specifically, the impact of reported household income depends upon the number of individuals dependent on that income, length of time at the index income level, possession of assets that affect the utility of the income, level of committed expenditures and debt, consumption patterns, and the degree of family and social economic support [
      • Braveman P.A.
      • Cubbin C.
      • Egerter S.
      • Chideya S.
      • Marchi K.S.
      • Metzler M.
      • et al.
      Socioeconomic status in health research: one size does not fit all.
      ,

      Davis P, Howden-Chapman P, McLeod K. 1997. The New Zealand Socio-Economic Index: A census based occupational scale of socio-economic status. In P. Crampton, & P. Howden-Chapman (Eds.), Socioeconomic inequalities and health. Proceedings of the socioeconomic inequalities and health conference, Wellington, December 9–10, 1996. Wellington: Institute of Policy Studies, Victoria University of Wellington.

      ,
      • Heflin C.M.
      • Iceland J.
      Poverty, material hardship and depression.
      ,
      • Meyer B.D.
      • Wu D.
      • Mooers V.
      • Medalia C.
      The use and misuse of income data and extreme poverty in the United States.
      ,
      • Salmond C.
      • Crampton P.
      • King P.
      • Waldegrave C.
      NZiDep: a New Zealand index of socioeconomic deprivation for individuals.
      ]. Moreover, an individual’s reported income may exclude income earned through cash payments or other sources of funds, thereby misrepresenting the individual’s actual economic status [

      Czajka JL, Denmead G. 2008. “Income data for Policy Analysis: A Comparative Assessment of Eight Surveys” Mathematica Reference No.: 6302-601.

      ,
      • Meyer B.D.
      • Wu D.
      • Mooers V.
      • Medalia C.
      The use and misuse of income data and extreme poverty in the United States.
      ]. Occupation and educational attainment, which have also been used to assess socioeconomic position, also suffer from confounding influences [

      Davis P, Howden-Chapman P, McLeod K. 1997. The New Zealand Socio-Economic Index: A census based occupational scale of socio-economic status. In P. Crampton, & P. Howden-Chapman (Eds.), Socioeconomic inequalities and health. Proceedings of the socioeconomic inequalities and health conference, Wellington, December 9–10, 1996. Wellington: Institute of Policy Studies, Victoria University of Wellington.

      ] and essentially function as proxies for income level [
      • Salmond C.
      • Crampton P.
      • King P.
      • Waldegrave C.
      NZiDep: a New Zealand index of socioeconomic deprivation for individuals.
      ].
      An alternative approach to income for assessing socioeconomic position is the concept of deprivation. Deprivation was first defined by Peter Townsend and colleagues as a demonstrable disadvantage experienced by an individual or family relative to their local community or wider society [
      • Townsend P.
      • Phillimore P.
      • Beattie A.
      Health and Deprivation: Inequality and the North.
      ]. Townsend identified a distinction between poverty and deprivation, conceptualizing the former as stemming from reduced availability of resources whereas deprivation reflected the actual living conditions experienced, which may be more closely linked to health status. His team first studied socioeconomic deprivation using area-based (i.e., geographic) measures of relative socioeconomic position [
      • Townsend P.
      • Phillimore P.
      • Beattie A.
      Health and Deprivation: Inequality and the North.
      ]. Since the development of the Townsend Deprivation Index, several nations have developed area-based measures, providing valuable information about regional socioeconomic disparities and their association with health measures [
      • Mackenbach J.P.
      • Kunst A.E.
      Measuring the magnitude of socio-economic inequalities in health: An overview of available measures illustrated with two examples from Europe.
      ,
      • Phillips R.L.
      • Liaw W.
      • Crampton P.
      • Exeter D.J.
      • Bazemore A.
      • Vickery K.D.
      • et al.
      How other countries use deprivation indices - And why the United States desperately needs one.
      ,

      University of Wisconsin School of Medicine and Public Health. 2015 Area Deprivation Index v2.0. Accessible at: https://www.neighborhoodatlas.medicine.wisc.edu/. Accessed January 30, 2021.

      ]. Indeed, in the United Kingdom, one-third of premature deaths are attributable to SES inequalities, based on a residential area deprivation measure [
      • Lewer D.
      • Jayatunga W.
      • Aldridge R.W.
      • Edge C.
      • Marmot M.
      • Story A.
      • et al.
      Premature mortality attributable to socioeconomic inequality in England between 2003 and 2018: an observational study.
      ]. However, correlations between residential area deprivation measures and individual-level deprivation are relatively weak, which can result in misclassification errors at the individual level [
      • Blakely T.
      • Pearce N.
      Socio-economic position is more than just NZDep.
      ,
      • Hanley G.E.
      • Morgan S.
      On the validity of area-based income measures to proxy household income.
      ,
      • Pardo-Crespo M.R.
      • Narla N.P.
      • Williams A.R.
      • Beebe T.J.
      • Sloan J.
      • Yawn B.P.
      • et al.
      Comparison of individual-level versus area-level socioeconomic measures in assessing health outcomes of children in Olmsted County.
      ].
      Efforts to develop a more valid tool to measure socioeconomic deprivation at the level of the individual are relatively recent, beginning with the New Zealand Index of Socioeconomic Deprivation for Individuals (NZiDep). This questionnaire emerged from multi-faceted research sponsored by the New Zealand government to assess the impact of governmental policies for improving social and economic conditions [
      • Salmond C.
      • Crampton P.
      • King P.
      • Waldegrave C.
      NZiDep: a New Zealand index of socioeconomic deprivation for individuals.
      ,

      Atkinson J, Salmond C, Crampton P. 2019. NZDep2018 Index of Deprivation, Interim Research Report, December 2019. Wellington: University of Otago. Available at: https://www.otago.ac.nz/wellington/departments/publichealth/research/hirp/otago020194.html. Accessed December 26, 2020.

      ]. From 28 deprivation variables, factor analyses identified a coherent set of variables that were valid across all ethnic groups studied. Subsequent principal component analysis established the final set of 8 variables used to construct the questions comprising the NZiDep [
      • Salmond C.
      • Crampton P.
      • King P.
      • Waldegrave C.
      NZiDep: a New Zealand index of socioeconomic deprivation for individuals.
      ]. NZiDep scores correlate with many measures of socioeconomic deprivation, including education level, obesity, self-rated health, smoking status, psychiatric distress, significant life events, and biological measures of stress, such as morning cortisol [
      • Salmond C.
      • Crampton P.
      • King P.
      • Waldegrave C.
      NZiDep: a New Zealand index of socioeconomic deprivation for individuals.
      ,
      • Salmond C.
      • Crampton P.
      Measuring socioeconomic position in New Zealand.
      ,
      • Thayer Z.M.
      • Kuzawa C.W.
      Early origins of health disparities: material deprivation predicts maternal evening cortisol in pregnancy and offspring cortisol reactivity in the first few weeks of life.
      ].
      A similar questionnaire for assessing individual-level socioeconomic deprivation for use in the United States has not yet been developed [

      U.S. Department of Health and Human Services. Measures of Material Hardship: Final Report. 2004. U.S. Department of Health and Human Services. Washington, D.C. https://aspe.hhs.gov/pdf-report/measures-material-hardship. Accessed Dec. 27, 2020.

      ]. The current study examined the validity and clinical utility of the United States Index of Socioeconomic Deprivation for Individuals (USiDep), a tool which was closely modeled after the NZiDep and is reported here for the first time.

      2. Material and Methods

      USiDep data were collected as part of two clinical trials of adults with major depressive disorder (MDD) without psychotic features. Details of both studies have been published previously [

      Mischoulon D, Dunlop BW, Kinkead B, Schettler PJ, Lamon-Fava S, Rakofsky JR, Nierenberg AA, Clain AJ, Mletzko-Crowe T, Wong A, Felger JC, Sangermano L, Ziegler TR, Cusin C, Fisher LB, Fava M, Rapaport MH. Omega-3 fatty ccids for major depressive disorder with high inflammation: A personalized approach. J. Clin Psychiatry, in press.

      ,
      • Kelley M.E.
      • Choi K.S.
      • Rajendra J.K.
      • Craighead W.E.
      • Rakofsky J.J.
      • Dunlop B.W.
      • et al.
      Establishing evidence for clinical utility of a neuroimaging biomarker in major depressive disorder: Prospective testing and implementation challenges.
      ]. The first study, “Omega-3 fatty acids for MDD with high inflammation: a personalized approach,” evaluated the clinical efficacy and anti-inflammatory effects of 1, 2, or 4 gm per day of fish oil-derived polyunsaturated fatty acids (PUFA) versus placebo , in a two-site, 12-week, randomized -controlled trial [

      Mischoulon D, Dunlop BW, Kinkead B, Schettler PJ, Lamon-Fava S, Rakofsky JR, Nierenberg AA, Clain AJ, Mletzko-Crowe T, Wong A, Felger JC, Sangermano L, Ziegler TR, Cusin C, Fisher LB, Fava M, Rapaport MH. Omega-3 fatty ccids for major depressive disorder with high inflammation: A personalized approach. J. Clin Psychiatry, in press.

      ,
      • Lamon-Fava S.
      • So J.
      • Mischoulon D.
      • Ziegler T.R.
      • Dunlop B.W.
      • Kinkead B.
      • et al.
      Dose- and time-dependent increase in circulating anti-inflammatory and pro-resolving lipid mediators following eicosapentaenoic acid supplementation in patients with major depressive disorder and chronic inflammation.
      ]. The PUFA trial (Clinicaltrials.gov: NCT02553915) was carried out at Emory University (Atlanta, GA) and the Massachusetts General Hospital (Boston, MA) and was approved by the Institutional Review Boards (IRBs) of both institutions. The second study, “Insula Assessed Needs for Depression” (ISLAND), was 12-week, trial that evaluated the clinical utility of a positron emission tomography (PET) biomarker for assigning treatment with cognitive behavior therapy (CBT) or a selective serotonin reuptake inhibitor (SSRI) [
      • Kelley M.E.
      • Choi K.S.
      • Rajendra J.K.
      • Craighead W.E.
      • Rakofsky J.J.
      • Dunlop B.W.
      • et al.
      Establishing evidence for clinical utility of a neuroimaging biomarker in major depressive disorder: Prospective testing and implementation challenges.
      ]. The trial (Clinicaltrials.gov: NCT02137369) was performed at Emory University and was approved by the Emory IRB. All patients provided written informed consent for participation and the studies were conducted in accordance with the Helsinki Declaration of 1975 and its amendments.

      2.1 Subjects

      For both studies, patients with MDD of at least moderate severity were recruited from the institutions’ psychiatric clinical research programs, clinical practices, and via community advertisements. Patients were compensated for each study visit attended. Both studies enrolled adults (aged 18–80 years in PUFA, 18–60 years in ISLAND) who were not currently taking, or could be tapered off, psychotropic medications (other than hypnotics) and who had a current primary diagnosis of MDD without psychotic features, confirmed by a clinical evaluation and a semi-structured interview (the Mini-International Neuropsychiatric Interview (MINI) v.7.0 [
      • Sheehan D.V.
      • Lecrubier Y.
      • Sheehan K.H.
      • Amorim P.
      • Janavs J.
      • Weiller E.
      • et al.
      The Mini-International Neuropsychiatric Interview (M.I.N.I.): the development and validation of a structured diagnostic psychiatric interview for DSM-IV and ICD-10.
      ] for PUFA; the Structural Clinical Interview for DSM-IV Diagnoses [
      • First M.B.
      • Spitzer R.L.
      • Gibbon M.
      • et al.
      Structured clinical interview for DSM-IV Axis I disorders-patient edition (SCID-I/P, Version 2.0).
      ] for ISLAND). Additional eligibility criteria for PUFA included screening visit body mass index (BMI) > 25 kg/m2, a high-sensitivity plasma C-reactive protein concentration ≥ 3 mg/L [
      • Osimo E.F.
      • Baxter L.J.
      • Lewis G.
      • Jones P.B.
      • Khandaker G.M.
      Prevalence of low-grade inflammation in depression: a systematic review and meta-analysis of CRP levels.
      ], and a clinician-administered Inventory of Depressive Symptoms (IDS-C30) [
      • Rush A.J.
      • Gullion C.M.
      • Basco M.R.
      • Jarrett R.B.
      • Trivedi M.H.
      The Inventory of Depressive Symptomatology (IDS): psychometric properties.
      ] score ≥ 25 at both the screening and baseline visits. ISLAND patients had to score ≥ 18 at screening and ≥ 15 at the baseline on the Hamilton Depression Rating Scale (HDRS) 17-item version [
      • Hamilton M.
      A rating scale for depression.
      ].
      Both studies excluded patients with a neurocognitive disorder, psychotic disorder, bipolar disorder, anorexia nervosa, bulimia nervosa; obsessive compulsive disorder, or those who met criteria in the 3 months (PUFA) or 12 months (ISLAND) prior to the screening visit for any substance use disorder (excluding nicotine or caffeine). Additional exclusion criteria for both studies included current serious suicidal or homicidal risk, presence of a serious or unstable medical illness, pregnancy, or breast-feeding. Regarding prior treatments, PUFA excluded patients who, in the current major depressive episode, had failed to respond to > 4 adequate antidepressant trials or who had taken a supplement of ≥ 1 g/day of omega-3 fatty acids for ≥ 6 weeks; patients in ongoing psychotherapy had to have started the therapy ≥ 90 days prior to screening. ISLAND excluded patients who could not safely undergo PET or magnetic resonance imaging or who reported a lifetime history of failure to respond to four or more sessions of CBT for depression or to ≥ 6 week trials of both escitalopram (≥10 mg/day) and sertraline (≥50 mg/day).

      2.2 Assessments

      The USiDep (see Appendix) was administered at the baseline visit in both studies. The USiDep is a self-report questionnaire derived from the NZiDep, comprised of 8 yes/no questions related to socioeconomic deprivation in the previous 12 months. The eight questions address the following areas: 1, Being forced to buy cheaper food; 2, Being on a means-tested benefit (i.e., a payment for individuals who demonstrate that their economic resources are below a specific threshold); 3, Feeling cold to save on heating costs; 4, Getting help obtaining food; 5, Wearing worn out shoes; 6, Often going without fresh fruit and vegetables; 7, Obtaining help from a community organization; 8, Unemployment. Scoring for the USiDep followed the NZiDep scoring, which is based on the number of “yes” answers. Zero “yes” answers equates to a score of “1”; one “yes” scores “2”, two “yes” scores “3,” three or four “yes” scores “4,” and 5 or more “yes” answers scores “5.”
      Questions 1, 3, 5, 6, and 8 of the USiDep are worded identically to the NZiDep. The other three questions revised the corresponding NZiDep items to incorporate the specific support programs available in the US. Question 2 was revised by replacing the names of New Zealand government assistance programs to the US benefit programs (i.e., Temporary Assistance to Needy Families, Earned Income Tax Credit, and a housing assistance program). Question 4 was modified to list US specific food support programs (i.e., the Supplemental Nutrition Assistance Program, and the Women, Infants and Children). Question 7 was modified to include religious organizations as an example of a community group that provides clothing or financial support, in addition to the Salvation Army listed on the NZiDep. An additional change was moving Question 8 (Unemployment, which is Question 2 on the NZiDep) to the end of the USiDep because the question excludes people ≥ 65 years of age or who are full-time homemakers or unpaid caregivers. To improve clarity for question 8, the USiDep includes an instruction for those individuals to skip the question. As specified on the NZiDep, for these individuals the answer is required to be “No.”
      To evaluate the convergent validity of the USiDep for measuring deprivation, several self-report assessments were administered. Clinical and demographic characteristics and BMI were measured at the screening visit. Of the 118 patients, 115 reported past-year personal income, and 83 of those also reported past-year household income. Income reporting was divided into six levels: ≤$20,000, $20,001–40,000, $40,001–60,000, $60,001–80,000, $80,001–100,000, and >$100,000. The primary convergent validity measure was past-year self-reported personal income, and sensitivity analyses were conducted using household income. Other convergent validity measures in both studies included: 1) quality of life, assessed with the Quality of Life, Enjoyment and Satisfaction Questionnaire (Q-LES-Q), which determines a life satisfaction score for the prior week ranging 0–100 based on responses to 14 items [
      • Endicott J.
      • Nee J.
      • Harrison W.
      • Blumenthal R.
      Quality of Life Enjoyment and Satisfaction Questionnaire: a new measure.
      ]; and 2) adverse childhood experiences assessed with the Childhood Trauma Questionnaire (CTQ), a 28-item self-report measure that assesses levels of physical, emotional, and sexual abuse as well as physical and emotional neglect [
      • Bernstein D.P.
      • Stein J.A.
      • Newcomb M.D.
      • Walker E.
      • Pogge D.
      • Ahluvalia T.
      • et al.
      Development and validation of a brief screening version of the Childhood Trauma Questionnaire.
      ], with a total score ranging from 25 to 125. The PUFA study collected two additional scales relevant to socioeconomic deprivation. The Physicians Health Questionnaire-15 (PHQ-15) [
      • Kroenke K.
      • Spitzer R.L.
      • Williams J.B.W.
      The PHQ-15: Validity of a new measure for evaluating the severity of somatic symptoms.
      ] measures physical health by inquiring about the 15 somatic symptoms that account for 90% of the physical complaints (excluding upper respiratory tract symptoms) in outpatient settings [
      • Kroenke K.
      • Arrington M.E.
      • Mangelsdorff A.D.
      The prevalence of symptoms in medical outpatients and the adequacy of therapy.
      ]. The time frame for the PHQ-15 is the past four weeks and the score ranges from 0 to 30. Finally, negative life events in the three months prior to baseline were measured using the Life Experiences Survey (LES), a 43-item scale listing events that individuals may experience, with respondents indicating which events they have experienced, whether the event was positive or negative, and rating on a 7-point scale (-3 to + 3) the degree of impact these events have had on their lives [
      • Sarason I.
      • Johnson J.
      • Siegel J.
      Assessing the impact of life changes: development of the Life Experiences Survey. ¬J Consult.
      ]. A negative life events score is calculated from adding the scores for each negative event endorsed, with more negative scores indicating greater severity of negative events.
      Divergent validity was assessed by examining associations of the USiDep with psychiatric measures, with the expectation that among a sample with active, moderate-to-severe MDD, USiDep scores should not significantly impact measures of depression, anxiety, or functioning. Depression severity was assessed in both trials using the 16-item total score from the Quick Inventory of Depressive Symptomatology (QIDS), which ranges from 0 to 27 [
      • Rush A.J.
      • Trivedi M.H.
      • Ibrahim H.M.
      • Carmody T.J.
      • Arnow B.
      • Klein D.N.
      • et al.
      The 16-item quick inventory of depressive symptomatology (QIDS), clinician rating (QIDS-C), and self-report (QIDS-SR): a psychometric evaluation in patients with chronic major depression.
      ]. In the PUFA study the QIDS score was derived from the clinician-rated version of the IDS-C30, which contains all the QIDS items plus an additional 14 questions. In the ISLAND trial, the QIDS-self report version was used [
      • Rush A.J.
      • Trivedi M.H.
      • Ibrahim H.M.
      • Carmody T.J.
      • Arnow B.
      • Klein D.N.
      • et al.
      The 16-item quick inventory of depressive symptomatology (QIDS), clinician rating (QIDS-C), and self-report (QIDS-SR): a psychometric evaluation in patients with chronic major depression.
      ]. Anxiety was measured with the Hamilton Anxiety Rating Scale (HAMA), a 14-item clinician-administered assessment of anxiety with scores ranging from 0 to 56 [
      • Hamilton M.
      The assessment of anxiety states by rating.
      ]. Role functioning was assessed with the Sheehan Disability Scale (SDS), a 3-item measure of work, social, and family functioning, each rated 0–10 on a visual analog scale, for a total score of 0–30 [
      • Sheehan D.V.
      Sheehan disability scale.
      ].

      2.3 Statistical analysis

      The distribution of the USiDep scores was strongly left skewed, so Spearman’s rank correlation coefficients were used to assess the association of the other measures with USiDep scores. Chi-square analyses were used to evaluate categorical associations. The internal consistency of the USiDep was assessed with Crohnbach’s alpha and item-total characteristics. The primary test of convergent validity was the correlation between USiDep score and past-year household income. To examine the scale’s impact on treatment outcomes, USiDep scores were correlated with percent change in QIDS. Categorical depression treatment outcomes used the standard definitions of response (≥50% reduction from baseline QIDS score) and remission (QIDS score ≤ 5 at endpoint) [
      • Rush A.J.
      • Trivedi M.H.
      • Ibrahim H.M.
      • Carmody T.J.
      • Arnow B.
      • Klein D.N.
      • et al.
      The 16-item quick inventory of depressive symptomatology (QIDS), clinician rating (QIDS-C), and self-report (QIDS-SR): a psychometric evaluation in patients with chronic major depression.
      ]. Modified intent to treat analyses were used, including all subjects with at least one post-baseline QIDS score.

      3. Results

      There were 118 patients who completed the USiDep, 61 in the PUFA study, and 57 in ISLAND. Clinical and demographic characteristics of the separate and combined samples are presented in Table 1. The distribution of the USiDep scores did not significantly differ between the four treatment arms in the PUFA study (X2 = 14.31, p = .28), nor between the patients treated with SSRI versus CBT in the ISLAND study (X2 = 1.03, p = .79)
      Table 1Clinical and demographic characteristics.
      VariablePUFA

      n = 61
      ISLAND

      n = 57
      Combined Sample

      N = 118
      n (%)n (%)n (%)
      Gender (Female)46 (75.4)40 (70.2)86 (72.9)
      Race
      White34 (55.7)32 (56.1)66 (55.9)
      Black21 (34.4)14 (24.6)35 (29.7)
      Asian1 (1.6)1 (1.8)2 (1.7)
      More than one race2 (3.3)8 (14.0)10 (8.5)
      Not reported3 (4.9)2 (3.5)5 (4.2)
      Hispanic8 (13.1)5 (8.8)13 (11.0)
      Married/Living with Partner14 (23.0)21 (36.8)35 (29.7)
      Unemployed9 (14.8)4 (7.0)12 (11.0)
      Personal Income
      ≤ $20,00022 (36.1)20 (35.1)42 (36.5)
      $20,001- $40,00018 (29.5)13 (22.8)31 (27.0)
      $40,001-$60,00014 (23.0)10 (17.5)24 (20.9)
      $60,001- $80,0003 (4.9)7 (12.3)10 (8.7)
      $80,001-$100,0001 (1.6)2 (3.5)3 (2.6)
      > $100,0002 (3.3)3 (5.3)5 (4.3)
      Education
      High school or less12 (19.7)1 (1.8)13 (11.0)
      Some college or Bachelor’s36 (59.0)35 (61.4)71 (60.2)
      Graduate degree13 (21.3)20 (35.1)33 (28.0)
      Recurrent Major Depression36 (59.0)40 (70.2)76 (64.4)
      Current Anxiety Disorder19 (31.1)37 (64.9)56 (47.5)
      Mean (SD)Mean (SD)Mean (SD)
      Age (yrs)47.33 (13.79)37.7 (11.51)42.68 (13.57)
      BMI (kg/m2)36.79 (6.65)29.08 (7.37)33.17 (8.00)
      Q-LES-Q43.59 (15.40)41.37 (11.01)42.55 (13.51)
      CTQ Total58.28 (16.12)43.64 (15.17)51.27 (17.25)
      QIDS14.33 (3.17)13.45 (4.45)13.91 (3.84)
      HAMA15.08 (5.54)15.44 (4.87)15.25 (5.21)
      SDS15.39 (7.91)20.41 (4.62)17.9 (6.92)
      BMI: body mass index; CTQ: Childhood Trauma Questionnaire; HAMA: Hamilton Anxiety Rating Scale; QIDS: Quick Inventory of Depressive Symptomatology; Q-LES-Q: Quality of Life Enjoyment and Satisfaction Questionnaire; SDS: Sheehan Disability Scale.

      3.1 USiDep characteristics

      The distributions of the number of USiDep items answered affirmatively and the resulting USiDep score are represented in Fig. 1a, Fig. 1b, respectively. Of the 118 patients, 39 (33.1%) scored 1, 25 (21.2%) scored 2, 21 (17.8%) scored 3, 21 (17.8%) scored 4, and 12 (10.2%) scored 5. Mean USiDep scores were significantly higher in the PUFA study than the ISLAND study (2.95 ± 1.45 vs 2.04 ± 1.05, respectively, p < .001).
      Figure thumbnail gr1a
      Fig. 1aDistribution of total number of “yes” answers on the USiDep.
      Figure thumbnail gr1b
      Fig. 1bDistribution of USiDep scores, derived from number of “yes” answers (see text).
      The frequency of USiDep items endorsed, in decreasing order, were: item 1 (Cheaper food) 60 (50.8%); item 8 (Unemployed) 24 (28.8%); item 6 (Often going without fruits and vegetables) 30 (25.4%); item 3 (Feeling cold) 27 (22.9%); item 4 (Help obtaining food) 26 (22.0%); Items 2 and 5 (On government benefits and Wearing old shoes, respectively) 13 (11.0%); and item 7 (Help from a community help organization) 9 (7.8%).

      3.2 Internal consistency of the USiDep

      The internal consistency of the USiDep was acceptable, (Crohnbach’s alpha = 0.766). The strongest correlations (with Pearson r value > 0.4) were for item 6 with items 1 (r = 0.56) and 5 (r = 0.52), item 7 with items 2 (r = 0.49), 3 (r = 0.44) and 6 (r = 0.42), and item 2 with item 4 (r = 0.42). The most weakly correlated items (r < 0.2) were for item 8 (Unemployment) with items 3 (r = 0.11), 5 (r = 0.12) and 6 (r = 0.18). Item 2 also demonstrated weak correlations with item 6 (r = 0.17) and item 3 (r = 0.19). The data in Table 2 show the item-total statistics, indicating no individual item substantially impacted Crohnbach’s alpha for the scale.
      Table 2USiDep Item-Total Correlations.
      USiDep ItemScale Mean if Item DeletedScale Variance if Item DeletedCorrected Item-Total CorrelationCronbach's Alpha if Item Deleted
      Q1. Buy cheaper food1.302.7400.5200.732
      Q2. On benefit program1.703.3250.3950.752
      Q3. Feeling cold1.583.0950.3980.753
      Q4. Help obtaining food1.592.9050.5560.724
      Q5. Wear old shoes1.683.1620.5030.737
      Q6. Often no fruits/vegetables1.562.8520.5630.722
      Q7. Help from community org.1.733.2370.5790.733
      Q8. Unemployment1.493.1010.3260.770

      3.3 Associations of USiDep scores with demographic characteristics

      Age was not significantly associated with USiDep scores. In contrast, men reported significantly higher USiDep scores than women (2.94 ± 1.24 vs 2.35 ± 1.40, respectively, p = .038) and people living alone (single, separated, divorced, widowed) reported higher scores than those who were married or living with a partner (2.71 ± 1.41 vs 2.03 ± 1.18, respectively, p = .008). Although USiDep scores did not differ by race (minority vs white, p = .20), Hispanics reported higher average scores than non-Hispanics (3.23 ± 1.24 vs 2.42 ± 1.37, respectively, p = .044).

      3.4 Convergent validity

      Table 3 shows the distribution of USiDep scores with past-year personal income (reported in n = 115), which differed across the income groups (X2 = 31.23, df = 20, p = .05) and showed a significant correlation (Spearman’s rho = -0.362, p < .001). There was a clear clustering of the higher USiDep scores (i.e., 4 or 5) among individuals reporting ≤$40,000 per year in income, and lower USiDep scores were predominant among those with higher incomes. However, the table also shows that many low-income earners have low USiDep scores, indicating that personal income alone can misclassify individuals regarding their level of socioeconomic deprivation.
      Table 3Distributions of USiDep scores with reported past-year personal income.
      USiDep ScoreLess than $20,000$20,001- $40,000$40,001-$60,000$60,001- $80,000$80,001-$100,000More than $100,000Total
      1951172337
      287720125
      389400021
      498110120
      582101012
      Total4231241035115
      The 83 subjects who reported past-year household income were evaluated as a sensitivity analysis for USiDep and income associations. Again, USiDep scores differed across the income groups (X2 = 34.38, df = 20, p = .02) and showed a similar and significant correlation (Spearman’s rho = -0.372, p < .001). Of the 32 patients without a reported household income, 15 had personal incomes <$20,000; 8 reported $20,001–40,000; 7 reported $40,001–60,000, one reported $60,001–80,000, and one reported >$100,000. Of the 15 subjects reporting a past-year personal income of <$20,000, only one was married/cohabitating, and only one was under 24 years of age, suggesting that the household income for those individuals was likely to be the same as their personal income. Consistent with this supposition, 12 of the 15 had USiDep scores ≥ 4.
      Education level, severity of adverse childhood experiences, quality of life, negative life events and the physical health measures of BMI and PHQ-15 were all significantly correlated with USiDep scores, as shown in Table 4.
      Table 4Convergent and discriminant validity of the USiDep and comparison with personal income level.
      ScalenCorrelation with USiDep Score (Spearman’s rho)p-valueCorrelation with income level (Spearman’s rho)p-value
      Deprivation-related measures
      Personal Income116-0.362<0.001
      CTQ total1170.370<0.001-0.1340.16
      Education (3 group)117-0.3120.0010.2550.006
      BMI1150.361<0.001-0.1020.28
      Q-LES-Q115-0.1990.030.2020.03
      Negative Life Events610.3140.010.1520.24
      PHQ-15600.597<0.001-0.2310.08
      Psychiatric Measures
      QIDS1160.1160.21-0.1100.25
      HAMA1180.1030.26-0.1120.23
      SDS total1080.1120.25-0.1750.07
      BMI: body mass index; CTQ: Childhood Trauma Questionnaire; HAMA: Hamilton Anxiety Rating Scale; PHQ-15: Patient Health Questionnaire-15; QIDS: Quick Inventory of Depressive Symptomatology; Q-LES-Q: Quality of Life Enjoyment and Satisfaction Questionnaire; SDS: Sheehan Disability Scale.

      3.5 Discriminant validity

      Table 4 lists the correlation coefficients of the USiDep with the psychiatric rating scales used in the studies. There was no significant correlation between USiDep score at baseline with QIDS, HAMA, or SDS scores.
      Patients with recurrent MDD did not differ from single episode patients in mean USiDep scores (p = .40).

      3.6 Effect of USiDep scores on treatment outcomes

      There were no significant correlations between USiDep score and percent change in QIDS, SDS, or Q-LES-Q scores (all Spearman rho’s < 0.14, all p’s > 0.15). Inspection of the data revealed differences in outcomes beginning with USiDep scores ≥ 4. Week 12 QIDS scores were significantly higher in patients with a USiDep score ≥ 4 compared to those with scores ≤ 3 (10.16 ± 5.66 vs 7.46 ± 5.04 respectively, p = .016). The mean percent change trended to be lower among those with a USiDep score than those ≥ 4 vs ≤ 3 (29.3 ± 39.2% vs 43.0 ± 36.6%, respectively, p = .085).
      Rates of response and remission were lower in those with USiDep scores ≥ 4 than those ≤ 3, but these differences were not statistically significant (Response: 35.5% vs 44.3%, p = .40; Remission: 25.8% vs 41.8%, p = .12, respectively). Of the 12 patients with a USiDep score of 5, only 2 (16.7%) responded, compared to 44/98 (44.9%) of patients with USiDep scores < 5, (Fisher’s Exact test p = .071). For this most socioeconomically deprived group, differences in remission rates were statistically significant (1/12, 8.3% vs 40/98, 40.8%, Fisher’s Exact test p = .03).

      3.7 Correlations of income with deprivation-related and clinical measures

      As shown in Table 4, there were significant correlations of personal income grouping only with level of education and quality of life. The sensitivity analysis found that none of the variables in Table 4 were significantly correlated with past-year household income. On the clinical measures, there was no significant correlation with the baseline QIDS, HAMA, or SDS total scores. Comparing patients in the lowest personal income group (<$20,000/yr, n = 38) vs all other income groups (n = 70), did not find poorer treatment outcomes in the low-income group in rates of response (X2 = 0.79, p = .37) or remission (X2 = 1.02, p = .31). A sensitivity analysis using past-year household income <$20,000 vs all others also found no associations with outcomes.

      4. Discussion

      The USiDep aims to fill the need for an easily administered and valid measure of socioeconomic deprivation at the level of the individual. The convergent validity of the USiDep for identifying socioeconomic deprivation was demonstrated through its significant correlation with self-reported past-year income, as well as several other measures related to deprivation, including BMI, level of education, quality of life, severity of childhood traumatic events, self-reported physical health, and negative life events. Conversely, USiDep scores were not significantly associated with clinical symptom measures of depression, anxiety, or functioning in this sample of moderate-to-severe MDD patients. Finally, patients who scored highest on the USiDep had lower response and remission rates after 12 weeks of treatment in a clinical trial than patients identified as being less deprived per the USiDep. In contrast, the lowest tier of income earners did not show differences in response or remission compared to the rest of the sample. Taken together, these analyses support the use of the USiDep as an individual-level measure of socioeconomic deprivation, which may have utility for clinical research
      Although past-year personal income correlated with level of education and quality of life, these associations were not stronger than the USiDep associations. Moreover, income did not significantly correlate with BMI, childhood trauma, negative life events, or physical health, all of which were significantly correlated with USiDep score, indicating that the USiDep is superior to income for identifying individuals in socially disadvantaged positions. This conclusion is consistent with the extensive analyses from New Zealand evaluating the NZiDep [
      • Salmond C.
      • Crampton P.
      • King P.
      • Waldegrave C.
      NZiDep: a New Zealand index of socioeconomic deprivation for individuals.
      ].
      Major depressive episodes are well-established to result in lower quality of life and impaired role function [
      • Rapaport M.H.
      • Clary C.
      • Fayyad R.
      • Endicott J.
      Quality-of-life impairment in depressive and anxiety disorders.
      ,
      • IsHak W.W.
      • James D.M.
      • Mirocha J.
      • Youssef H.
      • Tobia G.
      • Pi S.
      • et al.
      Patient-reported functioning in major depressive disorder.
      ]. In the current study greater socioeconomic deprivation as indicated by higher USiDep scores was associated with a further reduced quality of life among depressed patients but did not significantly impact level of functioning. Role functioning declines with cognitive impairment [
      • Lam R.W.
      • Kennedy S.H.
      • McIntyre R.S.
      • Khullar A.
      Cognitive dysfunction in major depressive disorder: effects on psychosocial functioning and implications for treatment.
      ], reduced motivation [
      • Fervaha G.
      • Foussias G.
      • Takeuchi H.
      • Agid O.
      • Remington G.
      Motivational deficits in major depressive disorder: Cross-sectional and longitudinal relationships with functional impairment and subjective well-being.
      ], fatigue [
      • Demyttenaere K.
      • De Fruyt J.
      • Stahl S.M.
      The many faces of fatigue in major depressive disorder.
      ], and insomnia [
      • Ten Have M.
      • Penninx B.W.J.H.
      • van Dorsselaer S.
      • Tuithof M.
      • Kleinjan M.
      • de Graaf R.
      Insomnia among current and remitted common mental disorders and the association with role functioning: results from a general population study.
      ], all prominent depressive symptoms. In contrast, quality of life, as assessed by the Q-LES-Q and other scales, is a broader measure that incorporates features of physical health and wellness beyond psychic distress. Combined with the significant association of higher USiDep scores with worse PHQ-15 scores assessing physical symptoms, it appears the socioeconomic deprivation captured by the USiDep is related to poorer perceived physical health.
      The finding that patients with the highest USiDep score experienced poorer treatment outcomes is also notable, considering the low power stemming from the limited size of the sample. Poorer mental health treatment outcomes have been found using area-level deprivation measures in community studies [
      • Clark D.M.
      • Canvin L.
      • Green J.
      • Layard R.
      • Pilling S.
      • Janecka M.
      Transparency about the outcomes of mental health services (IAPT approach): an analysis of public data.
      ,

      Green SA, Honeybourne E, Chalkley SR, Poots AJ, Woodcock T, Price G, Bell D, Green J. A retrospective observational analysis to identify patient and treatment-related predictors of outcomes in a community mental health programme. BMJ Open 2015;5(5):e006103. 10.1136/bmjopen-2014-006103.

      ,
      • Finegan M.
      • Firth N.
      • Wojnarowski C.
      • Delgadillo J.
      Associations between socioeconomic status and psychological therapy outcomes: A systematic review and meta-analysis.
      ] clinical trials [
      • Cohen A.
      • Houck P.R.
      • Szanto K.
      • Dew M.A.
      • Gilman S.E.
      • Reynolds 3rd., C.F.
      Social inequalities in response to antidepressant treatment in older adults.
      ], and analyses of electronic medical records [

      Knighton AJ, Savitz L, Belnap T, et al. Introduction of an area deprivation index measuring patient socioeconomic status in an integrated health system: Implications for population health. EGEMS (Wash DC) 2016;4(3):1238. 10.13063/2327-9214.1238.

      ]. Household income did not predict outcomes in the current study, although larger trials have demonstrated low income to be one of the stronger predictors of eventual non-remission with treatment for MDD [
      • Jain F.A.
      • Hunter A.M.
      • Brooks J.O.
      • Leuchter A.F.
      Predictive socioeconomic and clinical profiles of antidepressant response and remission.
      ]. Although replication in larger samples is needed, these results suggest that the USiDep could be used to stratify patients in randomized controlled trials, in order to prevent confounding that may arise from unequal distributions of USiDep scores in treatment groups.
      The primary limitation to this analysis is that the sample was limited to patients with current MDD. Thus, the performance of the USiDep in healthy populations, the medically ill, and individuals with psychiatric disorders other than MDD will require additional study. The use of the two different versions of the QIDS (clinician-rated vs self-report) in the two studies may be considered a limitation, though the level of agreement between the two versions of the scale has been found to be very high [
      • Bernstein I.H.
      • Rush A.J.
      • Carmody T.J.
      • Woo A.
      • Trivedi M.H.
      Clinical vs. self-report versions of the quick inventory of depressive symptomatology in a public sector sample.
      ,
      • Trivedi M.H.
      • Rush A.J.
      • Ibrahim H.M.
      • Carmody T.J.
      • Biggs M.M.
      • Suppes T.
      • et al.
      The inventory of depressive symptomatology, clinician rating (IDS-C) and Self-Report (IDS-SR), and the quick inventory of depressive symptomatology, clinician rating (QIDS-C) and self-report (QIDS-SR) in public sector patients with mood disorders: a psychometric evaluation.
      ]. Because the inclusion criteria of the studies required at least a moderate level of depression severity for eligibility, it is possible that a significant association between USiDep scores and depression would emerge if a less truncated range of scores was examined, as others have reported [
      • Leung C.W.
      • Epel E.S.
      • Willett W.C.
      • Rimm E.B.
      • Laraia B.A.
      Household food insecurity is positively associated with depression among low-income supplemental nutrition assistance program participants and income-eligible nonparticipants.
      ]. We did not have household income on 27% of the participants, though this limitation was addressed using sensitivity analyses evaluating household income, which did not find any meaningful differences from the analyses conducted using personal income. A final limitation is that the USiDep only incorporates the individual’s economic hardships, excluding consideration of environmental and neighborhood factors, whichare additional social determinants of health that contribute to mental health outcomes [
      • Finegan M.
      • Firth N.
      • Delgadillo J.
      Adverse impact of neighbourhood socioeconomic deprivation on psychological treatment outcomes: the role of area-level income and crime.
      ].

      5. Conclusions

      In conclusion, the USiDep assesses socioeconomic deprivation, showing meaningful advantages over measures of past-year personal or household income. The scale may also have utility as a factor for use in interpreting treatment and clinical trial outcomes over a range of clinical conditions. In combination with other measures, the USiDep may also have utility for the emerging study of the biological consequences of socioeconomic deprivation [
      • Milaniak I.
      • Jaffee S.R.
      Childhood socioeconomic status and inflammation: A systematic review and meta-analysis.
      ].

      Role of the funding source

      This paper was supported by the National Institutes of Health [grants numbers UG3 AT008857 and R01 MH073719]. The funding sources had no input into the collection, analysis, or interpretation of the study data.

      Declaration of interests

      Dr. Dunlop has received research support from Acadia, Compass, Aptinyx, NIMH, Sage, and Takeda, and has served as a consultant to Greenwich Biosciences, Myriad Neuroscience, Otsuka, Sage, and Sophren Therapeutics. Dr. Rakofsky has received research support from American Board of Psychiatry and Neurology, NIMH, and Compass. He has received honoraria from SMI Clinical Advisor.
      Dr. Mischoulon has received research support from Nordic Naturals and heckel medizintechnik GmbH. He has received honoraria for speaking from the Massachusetts General Hospital Psychiatry Academy, Harvard Blog, and PeerPoint Medical Education Institute, LLC. He also works with the MGH Clinical Trials Network and Institute (CTNI), which has received research funding from multiple pharmaceutical companies and NIMH.
      Dr. Mayberg has received consulting and IP licensing fees from Abbott Labs and research grant support from NIH.
      Dr. Kinkead has received research grant support from NIH.
      Dr. Nierenberg has received honoraria from Sunovion and Neurostar. He has provided consulting to Acadia Pharm, Esai, Ginger, Merck, Myriad, and Protogenics. He has served on scientific advisory boards for Alkermes, Jazz Pharma, Sage Pharma, Otsuka, and Neuronetics.
      Dr. Ziegler has received research support from Takeda and NIH (NCATS, NIAID and NIDDK).
      Dr. Fava’s lifetime disclosures are listed at: https://mghcme.org/faculty/faculty-detail/maurizio_fava. He has received research support from Acadia Pharmaceuticals, Allergan, Alkermes, Inc., Aptinyx, Avanir Pharmaceuticals Inc., Axsome, Benckiser Pharmaceuticals, Inc., BioClinica, Inc, Biogen, BioHaven, Cambridge Science Corporation, Cerecor, Gate Neurosciences, Inc., GenOmind, LLC, Gentelon, LLC, Happify, Johnson & Johnson, Lundbeck Inc., Marinus Pharmaceuticals, Methylation Sciences, Inc., Millennium Pharmaceutics, Inc. Minerva Neurosciences, Neuralstem, NeuroRX Inc., Novartis, Otsuka, Pfizer, Premiere Research International, Relmada Therapeutics Inc., Reckitt, Shenox Pharmaceuticals, Stanley Medical Research Institute (SMRI), Taisho, Takeda, Vistagen, National Institute of Drug Abuse (NIDA); National Institutes of Health (NIH), National Institute of Mental Health (NIMH), and PCORI. Dr. Fava has not done any personal consulting; any consulting he has done has been on behalf of Massachusetts General Hospital. He has equity holdings with Compellis, and Psy Therapeutics. He holds patents for Sequential Parallel Comparison Design (SPCD), licensed by MGH to Pharmaceutical Product Development, LLC (PPD) (US_7840419, US_7647235, US_7983936, US_8145504, US_8145505); and patent application for a combination of Ketamine plus Scopolamine in Major Depressive Disorder (MDD), licensed by MGH to Biohaven. Patents for pharmacogenomics of Depression Treatment with Folate (US_9546401, US_9540691). He holds copyrights for the MGH Cognitive & Physical Functioning Questionnaire (CPFQ), Sexual Functioning Inventory (SFI), Antidepressant Treatment Response Questionnaire (ATRQ), Discontinuation-Emergent Signs & Symptoms (DESS), Symptoms of Depression Questionnaire (SDQ), and SAFER; Lippincott, Williams & Wilkins; Wolkers Kluwer; World Scientific Publishing Co. Pte.Ltd.
      Dr. Rapaport has received research support from NCCIH, NIMH.

      Appendix.

      United States index of deprivation for individuals (USiDep)

      The following few questions are designed to help us understand people who have had special financial needs in the last 12 months. These questions are for you personally.
      Tabled 1
      • 1.
        [Buying cheap food]
      CIRCLE ONE
      In the last 12 months have you personally been forced to buy cheaper food so that you could pay for other things you needed?
      YES/NO
      • 2.
        [Being on a means-tested benefit]
      In the last 12 months did you yourself receive payments from any of these benefit programs: Temporary Assistance to Needy Families (TANF), Earned Income Tax Credit (EITC), or a Housing Assistance program, (e.g.,Section 8 Housing voucher)?YES/NO
      • 3.
        [Feeling cold to save on heating costs]
      In the last 12 months have you personally put up with feeling cold in order to save on heating costs?YES/NO
      • 4.
        [Help obtaining food]
      In the last 12 months have you personally made use of food banks or government food programs because you did not have enough money for food? For example, did you get benefits from the Supplemental Nutrition Assistance Program (SNAP/EBT/Food stamps), or the Women, Infants and Children (WIC) food programs?YES/NO
      • 5.
        [Wearing worn-out shoes]
      In the last 12 months have you personally continued wearing shoes with holes because you could not afford replacement?YES/NO
      • 6.
        [Going without fresh fruit and vegetables]
      In the last 12 months have you personally gone without fresh fruit and vegetables, often, so that you could pay for other things you needed?
      • 7.
        [Help from community organizations]
      In the last 12 months have you personally received help in the form of clothes or money from a community organization (like a religious group or the Salvation Army)?YES/NO
      • 8.
        [Unemployment]
      NOTE: If you are 65 years old or older or if you are a full-time care-giver or home-maker, you will skip this question. You are finished with this form.
      If you are less than 65 years old: In the last 12 months, have you beenout of paid work at any time for more than one month?YES/NO
      Step 1. Add the ‘YES’ responses (any missing data are counted as ‘NO’).
      Tabled 1
      Number of ‘YES’ AnswersUSiDep Score
      01
      12
      23
      3 or 44
      5 or more5

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