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. Author manuscript; available in PMC: 2014 Jan 1.
Published in final edited form as: AIDS Care. 2012 May 30;25(1):118–125. doi: 10.1080/09540121.2012.687811

Reliability and Validity of the Functional Assessment of Human Immunodeficiency Virus Infection (FAHI) in patients with drug and alcohol use disorders

Shannon Byrne 1, Nancy M Petry 1,*
PMCID: PMC3478433  NIHMSID: NIHMS391198  PMID: 22646736

Abstract

HIV and substance use disorders can both significantly impact a patient’s quality of life (QOL), and it is therefore important to assess QOL throughout treatments for these chronic conditions. This study evaluated the psychometric properties of the Functional Assessment of Human Immunodeficiency Virus (HIV) Infection (FAHI) in 170 HIV-positive patients who participated in a substance abuse treatment study. Internal consistency of the FAHI was good. Convergent and discriminant validity were generally supported with comparisons to other patient-reported measures. FAHI scores were not significantly associated with viral loads or CD4 counts, and they were similar in patients with and without AIDS. Patients who achieved longer durations of drug and alcohol abstinence during treatment reported better quality of life post-treatment. The FAHI appears to be a reliable and valid measure for assessing quality of life in HIV-positive patients with concurrent drug and alcohol use disorders.

Keywords: HIV, quality of life, FAHI, substance use

Individuals with HIV are living longer with the help of highly active antiretroviral therapy (Hall et al., 2008; Van Sighem, Gras, Reiss, Brinkman, & de Wolf, 2010), but additional factors such as social relationships (Atkins et al., 2010), cognitive function (Vance, Wadley, Crowe, Raper, & Ball, 2011), and emotional distress (Deichert, Fekete, Boarts, Druley, & Delahanty, 2008) can substantially influence patients’ functioning as well. Problems or strengths in one area may influence functioning in another, further affecting one’s experience of HIV. For example, psychological variables (e.g., depression) may influence the experience of pain (Kowal et al., 2008), social relationships may affect a person’s mental health (Reich, Lounsbury, Zaid-Muhammad, & Rapkin, 2010), and negative or positive thoughts about one’s illness may impact daily living activities and distress levels (Evans, Weinberg, Spielman, & Fishman, 2003). Throughout treatment it is important to assess multiple areas to obtain a complete picture of the person’s life.

Quality of life (QOL) is a construct that encompasses a complex and multidimensional array of functioning, and it can provide vital information about a patient’s experience. In general, QOL involves both objective functioning (e.g., employment, daily living skills, social functioning) and subjective well being (e.g., anxiety, depression, pain; Hays & Morales, 2001). Cella, McCain, Peterman, Mo, and Wolen (1996) defined QOL as “a person’s subjective experience of the impact of illness and treatment upon physical, psychological, social and functional well-being” (p. 451). Although measures of QOL have become increasingly prevalent in research and treatment, it is not measured consistently (e.g., Eyigor, Eyigor, & Uslu, 2010; Henoch, Axelsson, & Bergman, 2010; Ivarsson et al., 2010; Palfreyman, Tod, Brazier, & Michaels, 2010). In their review of QOL assessment, Clayson et al. (2006) reported 34 different measures that had been used in HIV/AIDS-specific studies. To ensure that QOL assessment is more consistent and comparable across the literature, identification of a smaller set of reliable and valid measures is needed.

Disease-specific versus general QOL measures may be more sensitive to change throughout treatment and explain more variability in disease severity, making them a good choice for clinical trials and treatment settings (Patrick & Deyo, 1989; Ren et al., 1998). One of the most commonly used HIV-specific QOL measures is the Functional Assessment of Human Immunodeficiency Virus Infection (FAHI; Cella et al., 1996; Clayson et al., 2006; Peterman, Cella, Mo, & McCain, 1997). The FAHI was developed from the Functional Assessment of Cancer Therapy-General (FACT-G), and HIV-specific items were added. It assesses five different domains: physical well being, emotional well being, function and global well being, social well being, and cognitive function. In a sample of 1661 HIV-positive patients from two clinical trials, the FAHI demonstrated good psychometric properties, including convergent and discriminant validity, responsiveness to change, internal consistency, and clinical validity (Viala-Danten et al., 2010).

Although the FAHI has been used in a number of samples and clinical trials (e.g., Diamond, Taylor, & Anton-Culver, 2010; Hasanah, Zaliha, & Mahiran, 2011; Rao, Hahn, Cella, & Hernandez, 2007), its psychometric properties are not well established, especially in substance using populations. Among patients living with HIV, as many as 40% may have substance use disorders (e.g., Bing et al., 2001; Galvan et al, 2002; Kalichman et al., 2009; Pence, Miller, Whetten, Eron, & Gaynes, 2006), and the combination of these chronic conditions may have unique influences on QOL (Korthuis et al., 2008). Patients with substance use disorders tend to have more health problems than those who do not (Mertens, Lu, Parthasarathy, Moore, & Weisner, 2003; National Institute on Drug Abuse, 2010a,b) and they are also more likely to have co-occurring psychiatric disorders (Halikas, Crosby, Pearson, Nugent, & Carlson, 1994; Kidorf et al., 2004; Lacayo, 1995); both of these problems can result in lower QOL. Substance abusers are not as compliant with antiretroviral treatment regimens as non substance abusers (Altice, Kamarulzaman, Soriano, Schechter, & Friedland, 2010; Friedman et al., 2009; Malta, Strathdee, Magnanini, & Bastos, 2008), which could result in poorer HIV outcomes (De Olalla et al., 2002) and lower QOL (Penedo et al., 2003). Further, HIV-positive individuals who achieve abstinence from drugs may experience improvements in QOL (Petry, Alessi, & Hanson, 2007). Thus, QOL is impacted by a number of interconnected factors, particularly among patients with both HIV and substance use disorders.

The psychometric properties of the FAHI have not been evaluated specifically in substance abusing HIV-positive patients. Using data collected within a clinical trial of psychosocial treatments for substance abusing HIV patients, we conducted secondary analyses to assess the validity and reliability of the FAHI.

Method

Participants were 170 HIV-positive patients with a current substance use problems diagnosis who participated in a substance abuse treatment study (Petry, Martin, & Finocche, 2001). The primary study examined the efficacy of standard care, and the same care plus contingency management. Participants were recruited via announcements and referrals at two drop-in HIV/AIDS clinics in the greater Hartford, CT area. All participants were 18 or older. Individuals were excluded if they (a) could not comprehend the study, (b) demonstrated severely disruptive behavior during the intake evaluation (although none were excluded for this reason), or (c) were non-English speaking. Because contingency management involves an element of chance, individuals who were in recovery for pathological gambling were also excluded (however, the intervention has not been associated with increases in gambling; see Petry & Alessi, 2010; Petry, Kolodner, et al., 2006).

Average (SD) age of the sample was 42.9 (6.9) years, and 61.2% (n = 104) were male. In terms of race/ethnicity, 43.5% (n = 74) were African American, 31.8% (n = 54) were Hispanic, 15.3% (n = 26) were Caucasian, and the rest 9.4% (n =16) indicated other or non-specified race/ethnicity. Over half the sample (52.9%, n = 90) had never married. Average (SD) education was 11.3 (2.2) years. In terms of past year substance use disorders determined from modules of the Structured Clinical Interview for the DSM-IV (First, Spitzer, Gibbon, & Williams, 1996), 79.4% (n = 135) had a cocaine use disorder, 51.8% (n = 88) an opioid use disorder, and 34.7% (n = 59) an alcohol use disorder, with 64.1% (n = 109) having more than one substance use disorder.

Assessment measures relevant to this study are described below. Participants received $10 in gift certificates for completion of the intake and a $25 check for each subsequent evaluation.

The Functional Assessment of Human Immunodeficiency Virus Infection (FAHI; Cella et al., 1996) was completed at intake and at months 1 (n = 155, 91%), 3 (n = 151, 89%), 6 (post-treatment; n = 137, 81%), 9 (n = 141, 83%), and 12 (n = 144, 85%). The FAHI is a 47-item self-report questionnaire that assesses HIV-specific QOL in five domains: Physical Well Being (PWB), Emotional Well Being (EWB), Function and Global Well Being (FWB), Social Well Being (SWB), and Cognitive Functioning (CF). Individuals rate their level of agreement with each item using a 0–4 point scale to describe their functioning over the last 7 days. Forty-four items are scored, yielding total scores that range from 0 to 176, with higher scores indicating better QOL. Maximum scores for the PWB, EWB, FWB, SWB, and CF subscales are 40, 40, 52, 32, and 12, respectively. In non-substance abusing samples, internal reliability of the FAHI is good, with Cronbach’s alphas ranging from 0.72 to 0.94 (Viala-Danten et al., 2010). FAHI scores have been responsive to changes in disease severity, with worsened patients showing reductions in total scores and improved patients showing increases in total scores. FAHI scores have been positively correlated with CD4 counts and negatively correlated with viral loads, and patients in earlier stages of HIV have reported better QOL than those in later stages (Viala-Danten et al., 2010).

To determine AIDS status, CD4 counts were obtained at intake only. While CD4 counts are markers of disease stage, they do not necessarily reflect rate of disease progression. They may also not consistently improve with antiretroviral therapy (Connors et al., 1997). Therefore, as a measure of disease progression, viral loads were obtained at intake and post-treatment (month 6). Viral loads were log transformed, with viral loads less than 400 coded with a value of 2.3, due to the questionable accuracy of log values below 2.6 (400 RNA copies/ml), and “undetectable” viral loads were assigned a value of 0.5 (Gulick et al., 1997).

The Addiction Severity Index (ASI; McLellan et al., 1985) was administered at intake and post-treatment (n = 138, 81%). The ASI is a structured clinical interview that evaluates problems in seven areas frequently impacted by substance use disorders. These domains include alcohol use, drug use, medical status, legal status, psychiatric, employment, and family/social functioning. Scores range from 0 to 1.0, with higher values indicating greater severity. The ASI has demonstrated reliability and validity (Leonhard, Mulvey, Gastfriend, & Shwartz, 2000; McLellan et al., 1985), and correlates with other measures that reflect similar problem areas (Kosten, Rounsaville, & Kleber, 1983). Trails A and B, administered according to standard procedures (Reitan, 1979), evaluated cognitive ability at intake only.

Following completion of the intake assessment, participants were randomly assigned to standard substance abuse treatment (n = 81) or contingency management treatment (n = 89). Both treatments were group-based and were held once a week for 24 weeks. Participants also submitted breath and urine specimens weekly, for which patients in both conditions were modestly compensated (e.g., $1 item). Breath samples were tested for alcohol, and urine specimens were screened for opioids and cocaine using OnTrak TesTstiks (Varian, Inc., Walnut Creek, CA).

Standard treatment was 12-step oriented and focused on reducing drug use and engaging in 12-step groups. Contingency management treatment focused on reinforcing both alcohol and drug abstinence and engagement in activities that may improve health or promote continued abstinence. Participants in this condition earned chances to win prizes (ranging from $1 to $100 in value) for each negative breath and urine sample, with escalating chances to win prizes for consecutive negative samples. They also received chances of winning prizes for completing objectively verified activities, such as attending doctor’s appointments or keeping track of medication consumption. For a full description of the treatments, see Petry et al. (2001).

Data analysis

To evaluate internal consistency of the FAHI, we calculated Cronbach’s alphas for each of the five subscales and for the total score at intake. To assess the degree of association between the FAHI subscales and total FAHI scores, we calculated Pearson’s correlations.

To assess convergent and divergent validity, we calculated Pearson’s correlations between the FAHI scores and related measures assessed at intake. We focused primarily on the ASI which, due to its assessment of functioning in a variety of dimensions, is a fitting comparison to the FAHI. We expected that particular FAHI subscales would be more strongly correlated with related ASI subscales, and less so with others. For example, Physical Well Being scores should be more highly correlated with ASI Medical scores. Emotional Well Being scores, which are designed to reflect general emotional distress, should be more strongly correlated with the ASI Psychiatric subscale than with other ASI subscales. Social Well Being scores should be most strongly correlated with ASI Family scores. In terms of other measures, we expected that Cognitive Function scores would be more strongly correlated with performance on Trails A and B, which measures cognitive ability. Physical Well Being should be correlated with measures of disease severity; thus, scores on this subscale should be positively correlated with viral loads and negatively correlated with CD4 counts.

To assess discriminant validity, we conducted a one-way ANOVA comparing FAHI scores among participants with and without an AIDS diagnosis at intake (CD4 < 200 cells/μL). Since severity of drug use may impact quality of life, we entered ASI Drug scores as a covariate. We expected that patients diagnosed with AIDS would report lower scores than those without AIDS, on all FAHI subscales.

To examine predictive validity, we calculated correlations between changes in viral loads and changes in FAHI scores from intake to end of treatment. Change scores were calculated by subtracting intake from post treatment scores. We also calculated correlations between changes in FAHI scores and changes in ASI scores, with the expectation that changes in related constructs would be correlated with changes in FAHI subscores (e.g., changes in ASI Family would be correlated with changes in Social Well Being).

To assess the impact of substance use on quality of life in patients who are HIV-positive, we calculated correlations between ASI Drug and FAHI scores at baseline. Further, to address the impact of drug abstinence on QOL, we conducted a repeated measures ANOVA examining the impact of longest duration of concurrent abstinence from alcohol, cocaine, and opioids (as determined by breath and urine testing) on FAHI scores. In these analyses, FAHI scores pre and post-treatment were the dependent variables; time, longest duration of abstinence from cocaine and opioids during treatment, and treatment condition (standard treatment vs. contingency management) were included as independent variables. FAHI scores were mean-centered for these analyses, and all analyses were conducted with SPSS 15.0 for Windows, with an alpha of .05 considered significant.

Results

Means and standard deviations for the subscale and total FAHI scores are presented in Table 1. Cronbach’s alpha for each subscale and total FAHI scores are also presented. The internal consistencies were adequate (Nunnally & Bernstein, 1994).

Table 1.

Cronbach’s alpha coefficients for Functional Assessment of Human Immunodeficiency Virus Infection scores at intake

Mean (standard deviation) Cronbach’s alpha
Physical Well Being 27.07 (8.35) 0.85
Emotional Well Being 22.25 (10.90) 0.89
Function and Global Well Being 29.79 (11.46) 0.82
Social Well Being 19.07 (5.82) 0.70
Cognitive Functioning 7.35 (3.17) 0.70
Total Quality of Life 105.54 (30.14) 0.92
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Intercorrelations between FAHI subscale scores are presented in Table 2. All subscales scores were significantly correlated with each other. The strongest associations were between Physical and Emotional Well Being, and between Social and Function and Global Well Being.

Table 2.

Intra-class correlations between Functional Assessment of Human Immunodeficiency Virus Infection subscale and total scores at intake a

Physical Well Being Emotional Well Being Function/Global Well Being Social Well Being Cognitive Function Total
Physical Well Being 1
Emotional Well Being .601 1
Function/Global Well Being .396 .432 1
Social Well Being .241 .425 .532 1
Cognitive Function .458 .474 .492 .279 1
Total .740 .824 .801 .646 .644 1
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a

All correlations significant at p < .001 level.

Correlations assessing convergent and discriminant validity are presented in Table 3. FAHI subscale scores were generally most highly correlated with scores on related measures (e.g., Physical Well Being and ASI Medical, Cognitive Function and Trails A). However, they were also significantly correlated with a number of other measures; for example, Physical Well Being scores were correlated not only with ASI Medical scores, but also with ASI Psychiatric and ASI Family scores. ASI Psychiatric and ASI Family scores were significantly correlated with scores on all subscales of the FAHI. Total FAHI scores were significantly correlated with scores on multiple ASI domains including Medical, Drug, Alcohol, Family, and Psychiatric.

Table 3.

Convergent and discriminant validity of intake Functional Assessment of Human Immunodeficiency Virus Infection subscale scores with other items

Physical Well Being Emotional Well Being Function/Global Well Being Social Well Being Cognitive Function Total
ASI Medical −.404** −.305** −.157* −.078 −.226** −.321**
Viral Load .046 .105 −.003 −.019 .063 .052
CD4 Count −.021 −.068 −.011 .071 −.087 −.030
ASI Psychiatric −.462** −.469** −.378** −.203** −.417** −.524**
ASI Employment −.110 −.084 −.137 −.034 −.150 −.136
ASI Family/Social −.259** −.277** −.309** −.328** −.129 −.366**
Trails A −.027 .066 .064 .055 .177* .070
Trails B .013 −.010 −.023 .094 −.060 .003
ASI Alcohol −.130 −.200** −.122 −.094 −.065 −.180*
ASI Drug −.154* −.234** −.361** −.249** −.247** −.338**
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ASI=Addiction Severity Index

*

p < .05

**

p < .01

At the time of treatment initiation, 35 participants (20.3%) carried an AIDS diagnosis (CD4 > 200) and 111 (64.5%) were HIV-positive only; CD4 levels were not available for 26 participants. At treatment initiation, participants with an AIDS diagnosis reported similar FAHI scores to participants without an AIDS diagnosis (Table 4), even after controlling for severity of substance use.

Table 4.

Intake Functional Assessment of Human Immunodeficiency Virus Infection scores of participants with (CD4 ≥ 200) and without (CD4 < 200) AIDS diagnosis, controlling for drug use severitya

AIDS (n=35) Non-AIDS (n=111) F (1,143) p
Physical Well Being 25.21 (1.36) 27.40 (0.76) 1.99 .16
Emotional Well Being 21.55 (1.78) 21.94 (1.00) 0.04 .85
Function and Global Well Being 29.59 (1.79) 30.05 (1.01) 0.05 .82
Social Well Being 18.89 (0.93) 19.07 (0.52) 0.03 .86
Cognitive Functioning 7.71 (0.52) 7.27 (0.29) 0.53 .47
Total Quality of Life 102.94 (4.78) 105.73 (2.69) 0.26 .61
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a

Values reflect adjusted means (standard error)

From intake to post-treatment, changes in FAHI Physical scores were significantly correlated with changes in both ASI Medical and ASI Psychiatric scores (Table 5); they were not significantly correlated with changes in viral load. Changes in FAHI Emotional scores were significantly correlated with changes in ASI Psychiatric scores, but changes in FAHI Social scores were not significantly related to changes in any ASI scores. FAHI Cognitive change scores were significantly correlated with ASI Psychiatric, ASI Employment, and ASI Alcohol change scores. Changes in total FAHI scores were significantly correlated with changes in ASI Psychiatric, ASI Family, and ASI Alcohol scores. For all of these correlations, decreases in ASI scores were associated with increases in FAHI scores.

Table 5.

Correlations between changes in Functional Assessment of Human Immunodeficiency Virus Infection scores from intake to post-treatment and changes in viral loads and Addiction Severity Index (ASI) scores.

Physical Well Being Change Emotional Well Being Change Function/Global Well Being Change Social Well Being Change Cognitive Function Change Total Change
ASI Medical Change −.177* −.058 −.137 −.023 −.072 −.147
Viral Load Change −.099 .005 −.083 .065 −.047 −.053
ASI Psychiatric Change −.327** −.289** −.367** −.076 −.285** −.410**
ASI Employment Change −.093 −.107 −.155 −.025 −.168* −.158
ASI Family Change −.147 −.094 −.198* −.026 −.069 −.176*
ASI Alcohol Change .166 .134 .169* .042 .256** .211*
ASI Drug Change −.086 −.162 −.074 −.116 .030 −.140
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*

p < .05

**

p < .01

The repeated-measures ANOVA revealed a significant effect of time, such that participants reported better QOL post-treatment (M=114.51, SE=2.55) than at intake to substance abuse treatment (M=105.80, SE=2.56), F(1,134) = 19.26, p < .001. There was also a significant effect of longest duration of confirmed drug abstinence, such that participants who achieved longer durations of abstinence reported better QOL, F(1,134) = 10.22, p = .002. Neither treatment condition nor the treatment condition by time interaction had a significant impact on FAHI scores (ps > .05).

Discussion

The purpose of this study was to examine the psychometric properties of the FAHI in a sample of HIV-positive patients with concurrent substance use disorders. In general, our sample of substance users reported lower scores on all FAHI subscales, compared to a previous sample that was not necessarily substance-using (Viala-Danten et al., 2010). Internal consistency of the total and subscale scores were adequate to good. In general, our Cronbach’s alpha values were slightly lower than those observed in the non-substance abusing samples (Viala-Danten et al., 2010), although the alpha for the EWB subscale was higher in our sample. Scores on all of the FAHI subscales were correlated with each other, indicating that they are not independent.

Convergent and discriminant validity were generally supported. FAHI subscale scores were significantly correlated with corresponding scores on the ASI, although they were also correlated with a number of other ASI subscale scores. Because the subscales of the FAHI were all significantly correlated with each other, it is not surprising that they are also associated with other constructs.

We did not find an association between FAHI scores and either CD4 counts or viral loads, and changes in FAHI scores were not correlated with changes in viral loads. Further, patients with and without AIDS reported similar scores on all FAHI subscales. This finding is inconsistent with research by Viala-Danten et al. (2010), who found modest correlations between these variables, and reported lower scores on Physical Well Being and Functional Well Being in patients in later HIV stages. However, other researchers (e.g., Brechtl et al., 2001) also found no association between viral load, CD4 count, and QOL scores. Among patients with concurrent substance use disorders, other factors such as comorbid psychiatric disorders, other health problems, or poor social relationships may have a greater impact on QOL than biological markers of HIV severity. The fact that QOL was not correlated with CD4 count or viral load highlights the importance of including QOL as a separate assessment in evaluating response to treatment, especially in the substance abusing population.

FAHI scores increased significantly over the course of substance abuse treatment, and changes in FAHI subscale scores generally were correlated with changes in corresponding ASI scores. Further, patients who achieved longer durations of abstinence during treatment evidenced greater increases in FAHI scores. Thus, the FAHI appears to be sensitive to capturing changes in functioning that are associated with reductions in substance use.

The FAHI’s sensitivity to changes in functioning, and its applicability to patients with and without substance use disorders, makes it a useful tool for clinical and research purposes. In a short period of time, the FAHI can be administered to help determine aspects of life that are impacted by HIV, or to track changes throughout treatment. This brief assessment of patient functioning in a variety of domains can be easily integrated into treatment planning and ongoing evaluation among patients who are HIV positive. Although the ASI is a useful tool among patients with substance use disorders, the FAHI can be utilized in patients with and without substance use disorders. The FAHI, therefore, can be integrated into settings in which a broader variety of HIV-positive patients are seen.

Although the FAHI appears to be an appropriate tool for assessing QOL among HIV-positive patients including those with substance use disorders, several limitations of this study should be noted. Our participants were drawn from a single clinic, and our available instruments for assessing concurrent and discriminant validity were somewhat limited. Nevertheless, QOL is a complex construct that encompasses a broad area of functioning. The domains assessed by the FAHI are correlated not only with each other, but also with other constructs (e.g., depression, physical symptoms). The challenge of determining discriminant validity of the FAHI may reflect a strength of the measure – its ability to gather information about a wide range of function with a relatively brief set of questions.

Strengths of this study are that a large sample size was included, and patients had a range of substance use problems thereby increasing generalizability of these findings. Further, objective indicators of substance use and biological measures of HIV were obtained. The FAHI was administered across multiple time points, spanning a year period. The data generated from this study suggest that the FAHI appears to be a valid and reliable measure for assessing quality of life among HIV-positive patients with concurrent substance use disorders.

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