APQ-32

Aging Perceptions Questionnaire 32 (APQ - 32)

Measuring: Self-perceptions of aging through 5 dimensions; Identity, Control, Consequences, Timeline, and Emotional Representations.

Number of Items: 32

Item Question Wording TILDA Variable
1 I am conscious of getting older all the time. SCQAgePrc1
2 I am always aware of my age. SCQAgePrc2
3 I always classify myself as old. SCQAgePrc3
4 I am always aware of the fact that I am getting older. SCQAgePrc4
5 I feel my age in everything that I do. SCQAgePrc5
6 As I get older I get wiser. SCQAgePrc6
7 As I get older I continue to grow as a person. SCQAgePrc7
8 As I get older I appreciate things more. SCQAgePrc8
9 I get depressed when I think about how managing might affect the things that I can do. SCQAgePrc9
10 The quality of my social life in later years depends on me. SCQAgePrc10
11 The quality of my relationships with others in later life depends on me. SCQAgePrc11
12 Whether I continue living life to the full depends on me. SCQAgePrc12
13 I get depressed when I think about the effect getting older might have on my social life. SCQAgePrc13
14 As I get older there is much that I can do to maintain my independence. SCQAgePrc14
15 Whether getting older has positive sides to it depends on me. SCQAgePrc15
16 Getting older restricts the things that I can do. SCQAgePrc16
17 Getting older makes me less independent. SCQAgePrc17
18 Getting older makes everything a lot harder for me. SCQAgePrc18
19 As I get older I can take part in fewer activities. SCQAgePrc19
20 As I get older I do not cope well with problems that arise. SCQAgePrc20
21 Slowing down with age is not something that I can control. SCQAgePrc21
22 How mobile I am in later life is not up to me. SCQAgePrc22
23 I have no control over whether I lose vitality or zest for life as I age. SCQAgePrc23
24 I have no control over the effects which getting older has on my social life. SCQAgePrc24
25 I get depressed when I think about getting older. SCQAgePrc25
26 I worry about the effects that getting older may have on my relationships with others. SCQAgePrc26
27 I go through cycles in which my experience of ageing gets better and worse. SCQAgePrc27
28 My awareness of getting older comes and goes in cycles. SCQAgePrc28
29 I feel angry when I think about getting older. SCQAgePrc29
30 I go through phases of feeling old. SCQAgePrc30
31 My awareness of getting older changes a great deal from day to day. SCQAgePrc31
32 I go through phases of viewing myself as being old. SCQAgePrc32

Scoring Method:

Scored on a 7-point Likert scale.

1 = Strongly disagree

2 = Disagree

3 = Neither agree nor disagree

4 = Agree

5 = Strongly agree

Citation: Barker, M., O’Hanlon, A., McGee, H. M., Hickey, A., & Conroy, R. M. (2007). Cross-sectional validation of the Aging Perceptions Questionnaire: a multidimensional instrument for assessing self-perceptions of aging. BMC geriatrics, 7, 9. https://doi.org/10.1186/1471-2318-7-9

Example TILDA Papers: Robertson DA, Savva GM, King-Kallimanis BL, Kenny RA (2015) Negative Perceptions of Aging and Decline in Walking Speed: A Self-Fulfilling Prophecy. PLOS ONE 10(4): e0123260. https://doi.org/10.1371/journal.pone.0123260

Code

forvalues i = 1/32{
    recode SCQAgePrc`i' (999=.) (-99=.) (-1000/-1=.)
}

egen MHapq_tl_accr = rowmean(SCQAgePrc1 SCQAgePrc2 SCQAgePrc3 SCQAgePrc4 SCQAgePrc5) 
replace MHapq_tl_accr = . if SCQAgePrc1+SCQAgePrc2+SCQAgePrc3+SCQAgePrc4+SCQAgePrc5 ==.

egen MHapq_tl_cyc = rowmean(SCQAgePrc27 SCQAgePrc28 SCQAgePrc30 SCQAgePrc31 SCQAgePrc32) 
replace MHapq_tl_cyc = . if SCQAgePrc27+SCQAgePrc28+SCQAgePrc30+SCQAgePrc31+SCQAgePrc32 == .

egen MHapq_emo = rowmean(SCQAgePrc9 SCQAgePrc13 SCQAgePrc25 SCQAgePrc26 SCQAgePrc29) 
replace MHapq_emo = . if SCQAgePrc9+SCQAgePrc13+SCQAgePrc25+SCQAgePrc26+SCQAgePrc29==.

egen MHapq_ctpve = rowmean(SCQAgePrc10 SCQAgePrc11 SCQAgePrc12 SCQAgePrc14 SCQAgePrc15) 
replace MHapq_ctpve = . if SCQAgePrc10+SCQAgePrc11+SCQAgePrc12+SCQAgePrc14+SCQAgePrc15==.

egen MHapq_ctnve = rowmean(SCQAgePrc21 SCQAgePrc22 SCQAgePrc23 SCQAgePrc24) 
replace MHapq_ctnve = . if SCQAgePrc21+SCQAgePrc22+SCQAgePrc23+SCQAgePrc24==.
replace MHapq_ctnve = 6-MHapq_ctnve

egen MHapq_cqpve = rowmean(SCQAgePrc6 SCQAgePrc7 SCQAgePrc8) 
replace MHapq_cqpve = . if SCQAgePrc6+SCQAgePrc7+SCQAgePrc8==.

egen MHapq_cqnve = rowmean(SCQAgePrc16 SCQAgePrc17 SCQAgePrc18 SCQAgePrc19 SCQAgePrc20) 
replace MHapq_cqnve = . if SCQAgePrc16+SCQAgePrc17+SCQAgePrc18+SCQAgePrc19+SCQAgePrc20==.


label variable MHapq_tl_accr "APQ - Timeline Chronic/Acute"
label variable MHapq_tl_cyc "APQ - Timeline Cyclic"
label variable MHapq_emo "APQ - Emotional Representations"
label variable MHapq_ctpve "APQ - Control Positive"
label variable MHapq_ctnve "APQ - Control Negative"
label variable MHapq_cqpve "APQ - Consequences Positive"
label variable MHapq_cqnve "APQ - Consequences Negative"


gen MHapqmiss = 0 if has_scq == 1
forvalues i = 1/32{
gen SCQAgePrcmiss`i' = abs(SCQAgePrc`i')>10 if has_scq == 1
replace MHapqmiss = MHapqmiss + 1 if abs(SCQAgePrc`i')==.

}
foreach q in MHapq_tl_accr MHapq_emo MHapq_ctpve MHapq_ctnve MHapq_cqpve MHapq_cqnve MHapq_tl_cyc{
    replace `q' = . if `q'<0 | `q'>20
    
}
drop SCQAgePrcmiss*

Download Stata .do file

apq_vars <- paste0("SCQAgePrc", 1:32)

# Recode 999, -99, and all values from -1000 through -1 to missing.
for (v in apq_vars) {
  x <- data[[v]]
  x[x == 999 | x == -99 | (!is.na(x) & x >= -1000 & x <= -1)] <- NA_real_
  data[[v]] <- x
}

# The Stata rowmean() calculations are subsequently set to missing if any
# contributing item is missing, so complete-case row means are used here.
data$MHapq_tl_accr <- rowMeans(
  data[paste0("SCQAgePrc", c(1,2,3,4,5))], na.rm = FALSE)

data$MHapq_tl_cyc <- rowMeans(
  data[paste0("SCQAgePrc", c(27,28,30,31,32))], na.rm = FALSE)

data$MHapq_emo <- rowMeans(
  data[paste0("SCQAgePrc", c(9,13,25,26,29))], na.rm = FALSE)

data$MHapq_ctpve <- rowMeans(
  data[paste0("SCQAgePrc", c(10,11,12,14,15))], na.rm = FALSE)

data$MHapq_ctnve <- rowMeans(
  data[paste0("SCQAgePrc", c(21,22,23,24))], na.rm = FALSE)
data$MHapq_ctnve <- 6 - data$MHapq_ctnve

data$MHapq_cqpve <- rowMeans(
  data[paste0("SCQAgePrc", c(6,7,8))], na.rm = FALSE)

data$MHapq_cqnve <- rowMeans(
  data[paste0("SCQAgePrc", c(16,17,18,19,20))], na.rm = FALSE)

attr(data$MHapq_tl_accr, "label") <- "APQ - Timeline Chronic/Acute"
attr(data$MHapq_tl_cyc, "label") <- "APQ - Timeline Cyclic"
attr(data$MHapq_emo, "label") <- "APQ - Emotional Representations"
attr(data$MHapq_ctpve, "label") <- "APQ - Control Positive"
attr(data$MHapq_ctnve, "label") <- "APQ - Control Negative"
attr(data$MHapq_cqpve, "label") <- "APQ - Consequences Positive"
attr(data$MHapq_cqnve, "label") <- "APQ - Consequences Negative"

data$MHapqmiss <- NA_real_
eligible <- !is.na(data$has_scq) & data$has_scq == 1
data$MHapqmiss[eligible] <- 0

for (i in 1:32) {
  v <- paste0("SCQAgePrc", i)
  missv <- paste0("SCQAgePrcmiss", i)
  data[[missv]] <- NA
  data[[missv]][eligible] <- abs(data[[v]][eligible]) > 10
  data$MHapqmiss[eligible & is.na(data[[v]])] <-
    data$MHapqmiss[eligible & is.na(data[[v]])] + 1
}

for (v in c("MHapq_tl_accr","MHapq_emo","MHapq_ctpve",
            "MHapq_ctnve","MHapq_cqpve","MHapq_cqnve","MHapq_tl_cyc")) {
  data[[v]][!is.na(data[[v]]) & (data[[v]] < 0 | data[[v]] > 20)] <- NA_real_
}

data[grep("^SCQAgePrcmiss", names(data), value = TRUE)] <- NULL

Download R file

RECODE SCQAgePrc1 SCQAgePrc2 SCQAgePrc3 SCQAgePrc4 SCQAgePrc5 SCQAgePrc6 SCQAgePrc7 SCQAgePrc8 SCQAgePrc9 SCQAgePrc10 SCQAgePrc11 SCQAgePrc12 SCQAgePrc13 SCQAgePrc14 SCQAgePrc15 SCQAgePrc16 SCQAgePrc17 SCQAgePrc18 SCQAgePrc19 SCQAgePrc20 SCQAgePrc21 SCQAgePrc22 SCQAgePrc23 SCQAgePrc24 SCQAgePrc25 SCQAgePrc26 SCQAgePrc27 SCQAgePrc28 SCQAgePrc29 SCQAgePrc30 SCQAgePrc31 SCQAgePrc32
  (999 = SYSMIS)
  (-1000 THRU -1 = SYSMIS).

COMPUTE MHapq_tl_accr =
  MEAN.5(SCQAgePrc1, SCQAgePrc2, SCQAgePrc3, SCQAgePrc4, SCQAgePrc5).

COMPUTE MHapq_tl_cyc =
  MEAN.5(SCQAgePrc27, SCQAgePrc28, SCQAgePrc30, SCQAgePrc31, SCQAgePrc32).

COMPUTE MHapq_emo =
  MEAN.5(SCQAgePrc9, SCQAgePrc13, SCQAgePrc25, SCQAgePrc26, SCQAgePrc29).

COMPUTE MHapq_ctpve =
  MEAN.5(SCQAgePrc10, SCQAgePrc11, SCQAgePrc12, SCQAgePrc14, SCQAgePrc15).

COMPUTE MHapq_ctnve =
  MEAN.4(SCQAgePrc21, SCQAgePrc22, SCQAgePrc23, SCQAgePrc24).
COMPUTE MHapq_ctnve = 6 - MHapq_ctnve.

COMPUTE MHapq_cqpve =
  MEAN.3(SCQAgePrc6, SCQAgePrc7, SCQAgePrc8).

COMPUTE MHapq_cqnve =
  MEAN.5(SCQAgePrc16, SCQAgePrc17, SCQAgePrc18, SCQAgePrc19, SCQAgePrc20).

VARIABLE LABELS
  MHapq_tl_accr "APQ - Timeline Chronic/Acute"
  MHapq_tl_cyc "APQ - Timeline Cyclic"
  MHapq_emo "APQ - Emotional Representations"
  MHapq_ctpve "APQ - Control Positive"
  MHapq_ctnve "APQ - Control Negative"
  MHapq_cqpve "APQ - Consequences Positive"
  MHapq_cqnve "APQ - Consequences Negative".

COMPUTE MHapqmiss = $SYSMIS.
IF (has_scq = 1) MHapqmiss = 0.

DO REPEAT v = SCQAgePrc1 SCQAgePrc2 SCQAgePrc3 SCQAgePrc4 SCQAgePrc5 SCQAgePrc6 SCQAgePrc7 SCQAgePrc8 SCQAgePrc9 SCQAgePrc10 SCQAgePrc11 SCQAgePrc12 SCQAgePrc13 SCQAgePrc14 SCQAgePrc15 SCQAgePrc16 SCQAgePrc17 SCQAgePrc18 SCQAgePrc19 SCQAgePrc20 SCQAgePrc21 SCQAgePrc22 SCQAgePrc23 SCQAgePrc24 SCQAgePrc25 SCQAgePrc26 SCQAgePrc27 SCQAgePrc28 SCQAgePrc29 SCQAgePrc30 SCQAgePrc31 SCQAgePrc32.
  IF (has_scq = 1 AND MISSING(v)) MHapqmiss = MHapqmiss + 1.
END REPEAT.

DO REPEAT s =
  MHapq_tl_accr MHapq_emo MHapq_ctpve MHapq_ctnve
  MHapq_cqpve MHapq_cqnve MHapq_tl_cyc.
  IF (s < 0 OR s > 20) s = $SYSMIS.
END REPEAT.

EXECUTE.

Download SPSS .sps file